Raphaël Gazzotti

Fabien Gandon

When owl:sameAs is the Same: Experimenting Online Resolution of Identity with SPARQL queries to Linked Open Data Sources

Keywords: Equivalence links, Coreference resolution, SPARQL, Linked Data, Data curation, sameAs

Equivalence links are the cornerstone of Linked Data and their integration. However, it is not easy to establish and manipulate them, since the Web is always evolving with datasets emerging and disappearing. Inconsistencies may also be present on the Web, leading to erroneous assertions and inferences. We propose a method to identify owl:sameAs relationships of a resource relying on online SPARQL querying of distributed datasets and to correct results using declarative curation rules. We also exploit and inspect the quality of owl:InverseFunctionalProperty and owl:FunctionalProperty relationships, using the definitions given by their schemata, endpoints and a voting approach. We evaluate our method on an existing benchmark and compare to state of the art baselines. We show that a heuristic approach can retrieve high quality equivalence links without requiring the extraction of all the alleged existing equivalence relations.

INTRODUCTION

The ability to establish links is key to weaving the Web in general and the semantic Web in particular (Gandon, 2018). But the Web is in constant evolution with resources added and deleted all the time. Linked data, in particular, rely on our ability to establish links between the different datasets on the Web and as such, the detection of equivalence links is a central task. And as the Web evolves, this linking has to evolve with it. Establishing equivalences between resources is also key to data integration use cases to join knowledge graphs with different provenances. More recently this ability to combine such graphs also proved important in machine learning approaches relying on embeddings based on a set of linked graphs to capture the semantics surrounding a concept more accurately and more richly.

Approaches discovering equivalence links that rely on a snapshot of the Web run the risk of capturing relationships that already belong to the past. Equivalence links can also be retrieved by exploiting OWL semantics, e.g., properties of type (inverse) functional can indicate the uniqueness of a resource, leading to the inference of owl:sameAs relationships when different URIs are used as their subject or object (Alle-• Where to find and how to retrieve SPARQL endpoint information to be explored for equivalence detection?

• How to identify and correct misinformation about owl:sameAs statements? • How to detect wrong type for assserted owl:InverseFunctionalProperty and owl:FunctionalProperty properties? The paper is structured as follows. We survey the related work in Section 2 and position our contribution. In Section 3 we introduce the definition of the equivalence detection task and the vocabulary we used to solve it. Then, in Section 4 we describe how we proceed to obtain information on datasets and their SPARQL endpoints. Section 5 details how we proceed to collect and curate equivalence links. We evaluate the quality of the retrieved equivalent links on a public benchmark, comparing to state of the art baselines, and discuss our results in Section 6. We conclude with some perspectives in Section 7.

RELATED WORK

Surprisingly, there are not so many available services to establish owl:sameAs relationships for a given URI.

The sameAs.org (Jaffri et al., 2008) is one of the pioneers to propose a service of URIs coresolution. The equivalences are collected through different RDF files and SPARQL endpoints chosen by the authors.

Equivalent URIs are stored with different identifiers depending on the context. Different coreference contexts are captured by different coreference resolution services, because depending on the usage and context, an equivalence either holds or not. A context is represented as a bundle attached to a URI. However the approach mixes different predicates which can be far from a owl:sameAs, e.g., ov:similarTo1 is a property for things that are not linked by owl:sameAs, but that are similar to a certain extent. The system also does not ensure that resources are actually equivalent and proposes only one concept of equivalence. Therefore, it does not allow to distinguish different notions of equivalence as indicated by (Halpin et al., 2010) and defined in the Similarity Ontology. 2 In addition, with the online portal, it is unfortunately not possible to distinguish the different contexts considered for a given resource. Unlike the other works, sameAs.org does not use a curation algorithm for owl:sameAs relationships.

The LODsyndesis3 (Mountantonakis and Tzitzikas, 2018) platform, in addition to providing various services and metrics related to many datasets, also performs coreference resolution. The algorithm introduced by the authors incrementally uses the same identifier for pairs of URIs (linked by the owl:sameAs property) defining the same resource. The authors show that by leveraging content or graph metrics, erroneous equivalence links can be detected. Their approach relies on the data provided by (Schmachtenberg et al., 2014) that are crawled from the LOD Cloud with LDSpider,4 on various datasets: Yago, datahub.io, DBpedia v3.9, Wikidata, Freebase and LinkLion. Unfortunately, the number of coreferences that this service can offer is sometimes limited.

The sameAs.cc dataset accessible through the SPARQL endpoint5 (Raad et al., 2020) exploits the LOD-a-Lot dataset (Fernández et al., 2017) and the Louvain algorithm (Blondel et al., 2008) for detect-ing communities, an approach that leads them to identify errors between owl:sameAs relations. This approach succeeds in extracting more equivalence links than in the previous work, LODsyndesis (Mountantonakis and Tzitzikas, 2018). Different human annotators evaluated a subset of 200 owl:sameAs relations based on their descriptions to assess the relevance of these relations based on different thresholds of degrees of error. They apply their findings on these thresholds to cluster equivalence links that relate to the former U.S. president Barack Obama.6 providing a valuable benchmark. One of the disadvantages of using the Louvain algorithm is that it must be run several times on the complete set of alleged equivalences to get the "best clusters" with no ensurance of reaching the global maximum of modularity, as it is a greedy and non-deterministic method.

Our approach differs from previous work in that it is not performed on a locally stored dataset but dynamically and online, on the SPARQL endpoints of many datasets. The list of considered endpoints is open and can be extended at will with new public and private endpoints as well as their description relevant to the application. Moreover, it uses other relations than owl:sameAs to define equivalence relations between different resources since we also rely on the properties owl:InverseFunctionalProperty and owl:FunctionalProperty.

We also propose several techniques to curate the equivalences found on the fly and the properties declared as owl:InverseFunctionalProperty and owl:FunctionalProperty. We did this after noticing their definitions on datasets may differ from what was intended by the creators of the ontologies (see Section 5). Our algorithm also relies almost exclusively on SPARQL queries, ensuring a high compatibility with different engines and a declarativity that brings flexibility and extensibility in the sources and rules considered. The idea is to provide and evaluate a mechanism that could be implemented on top of any SPARQL engine and customized to any application.

SAMELIVE APPROACH: ALGORITHM AND TASK DEFINITION

Let S = s 1 , ..., s k be the set of k seed URIs s i for which we want to obtain equivalent URIs. Some of these seed URIs may be equivalent, i.e., they share a owl:sameAs relationship, which will result in faster convergence of the algorithm. We show this in the case study described in sub-section 6.3. First we need to identify a set of endpoints N = E 1 , ..., E m that we will query to discover equivalent URIs. The process to calculate the closure of the equivalent relations is a greedy incremental algorithm that iterates on a growing collection of URIs linked by equivalence statements until no more new statement can be obtained from the set of endpoints N. At each iteration we also test an extensible set of declarative heuristics to detect if an equivalence is an error and avoid its transitive propagation.

Moreover, to ensure portability, distributability, and federability, the algorithm we have written is primarily in SPARQL 1.1, with calls in SPARQL 1.0 7 when we contact online SPARQL endpoints. Many endpoints on the Linked Open Data still do not support SPARQL 1.1, but the functionalities of this language allow us on a local endpoint to process properties of type (inverse) functional as well as to perform curation of owl:sameAs relationships and to provide statistics on the extracted data. We also trace all the steps of the algorithm by the generation of several named graphs and with the help of a small dedicated vocabulary introduced in this section and summarized in Table 1. We use a set of classes and properties to represent the input and output of each iteration. Together with the named graphs they capture the state of each iteration and the provenance of our results.

In the rest of this section, anchors in footnotes refer to labelled functions in the source code. The initialization of the algorithm consists of:

1. identifying datasets and their corresponding SPARQL endpoints and populating the named graph same:N with their description and checking their availability (see Section 4, done with 8 SPARQL queries, 3 of them being used for data cleaning); 8 2. populating the named graph Q 0 with the set S of seed URIs for which we want to obtain equivalent URIs. These seeds URI are typed as same:Target (done with 1 SPARQL query); 9

3. identifying and storing the definitions of owl:InverseFunctionalProperty and owl:FunctionalProperty in the named graph kg:default: in a preselection step the (inverse) functional properties identified from N are placed in the named graph same:Properties alongside with their namespaces to deference them. If they cannot be dereferenced they are stored in the 7 https://www.w3.org/TR/rdf-sparql-query/ 8 Functions N1 to N3 load information about datasets, CN1 is responsible for data cleaning, A1 is responsible for checking endpoint availability. 9 Function P1 populates Q 0 with seed URIs.

named graph same:NotDeferencedProperties to be put to a vote (see the sub-section 5.1, done with 12 SPARQL queries, 2 of them being run in a loop). 10 This step refers to the block corresponding to the first "if" in algorithm 1.

The core of the algorithm (mainly inside the "while" loop of algorithm 1) consists of iterating on a growing collection of named graphs Q i for which at each iteration i: 4. the obtained owl:sameAs are added in a specific named graph with a name based on the endpoint and the iteration in which the owl:sameAs relationship was identified;

1. we query Q i-
5. we check that the owl:sameAs relationships conform to some rules (described in the sub-section 5.2.1) and if it is not the case, identified instances of same:Target become of type same:Rotten and are placed in the named graph Q -1 before their relationships are removed: incoming and outgoing owl:sameAs relationships from a same:Rotten are deleted. This also applies to its owl:InverseFunctionalProperty and owl:FunctionalProperty, and the outgoing same:Target from a same:Rotten are deleted if it has no other same:Target incoming relationship (done with 5 SPARQL queries, 3 of them being used to remove relationships); 14 6. the new resources are added to named graph Q i .

10 Function G -(I)FP1 retrieves the properties known as (inverse) functional, LDD -(I)FP1 attempts to deference and load the RDF document of properties from their namespaces, LDS -(I)FP1 stores as information that an endpoint has the schema of a property, V -(I)FP1 performs the voting on the type of the property.

11 Function T 1 gets the same:Target resources in Q i-1 .

12 Function S1 retrieves owl:sameAs relationships.

13 Function (I)FP1 retrieves the actual instances of (inverse) functional properties and (I)FP2 infers owl:sameAs relationships from them. 14 Function R1 refers to the rule #1 used to detect same:Rotten, respectively R2 refers to the rule #2, RC1 is used to remove relationships ; details in Section 5.2.

The stop condition is that the resources to be explored are exhausted, i.e., there are no more resources to explore for the current iteration i and Q i is empty. A last check with (c.f., the rule #2, sub-section 5.2.1) is necessary to ensure that there is no relationship between two resources sharing the same authority (resources obtained at i). The pseudo-code of SameLive is represented by the algorithm 1.

Algorithm 1: Online resolution of identity with the SameLive algorithm.

Initialize Vocabulary // Also initialize

Q -1 Initialize N // Availability is checked Initialize Q 0 //
i = 1 L = length(Q 0 ) while L != 0 do Initialize Q i Q i += Retrieve owl:sameAs relations of Q i-1 over N if properties condition then
Retrieve triples comporting Q i-1 who have a property typed typed as (inverse) functional over N Q i += Infer owl:sameAs relations with the triples previously extracted over N // Curation rules have an impact on all

Q i Q -1 += Apply curation rules i += 1 L = length(Q i-1 ) Q -1 += Apply curation rule #2

EXTRACTION AND INTEGRATION OF ENDPOINTS' INFORMATION

The first step is to identify the datasets that can contribute to solving this problem. Various strategies exist for this purpose such as relying on search engines, using previously crawled RDF data (i.e., using the RFC 8615,15 etc.) or even catalogs referencing these datasets. To achieve our means, we rely on famous catalogs listing datasets, using their metadata as well as the URLs for their SPARQL endpoints. These catalogs are regularly updated so we can keep up with the latest updates of the Web of Data. Moreover this approach supports the addition of new catalogs at any time, including private endpoints. However, just because a dataset is referenced in a catalog does not mean it is available. To define if a SPARQL endpoint is available or not, we rely on the EndS ontology (Endpoint Status Ontology) 16 which is an extension of VoiD. 17 We use in particular the property ends:statusIsAvailable. This ontology is involved in the description of the different datasets retrieved from the catalogs detailed in the following sub-sections. For each source we create a distinct named graph and then combine all unduplicated results (i.e., different SPARQL endpoint URL) into one initial named graph same:N containing all our sources. From the different catalogs we present, we only rely on the asserted availability of endpoints from YummyData. The other catalogs listed here do not have regular updates on this property and we perform the availability ourselves.

voiD store

We rely on the voiD store18 and query it for instances of void:Dataset with their void:sparqlEndpoint to access them. To avoid duplicating entries for a same dataset -as datasets can be referred with several types in the voiD store-or incomplete results we limit ourselves to the extraction of resources of type void:Dataset and we ensure to not retrieve blank nodes. We also check that these resources have a title (property dcterms:title) 19 and, of course, a SPARQL endpoint (property void:sparqlEndpoint). Any doubloon is eliminated (i.e., datasets using the same SPARQL endpoint), datasets can be represented several times in the voiD store. The retrieval of the information about endpoints and the removal of the doubloons is carried out in two steps to overcome the limitations of the voiD store SPARQL endpoint. 20 . The endpoint of the voiD store has recently been closed due to the decision of the service maintainers, however our approach still works with the other catalogs and we pro- vide code to integrate its data if someone decides to continue maintaining this service. Our results were obtained while this service was still in operation. A large majority of the core datasets of the Linked Open Data are also referenced by the LODCloud.

LODCloud

The main purpose of the LODCloud 21 website is to provide a diagram of the LOD cloud. The JSON data used to build it are available 22 and we translate selected parts of them in RDF as different data are represented within this JSON document. We first check if a dataset has an entry related to a SPARQL endpoint ("sparql" field) in which case we include it. If we find information about a voiD page, we store this data as well. However, some of the information contained in the lod-cloud is not always up to date: an endpoint 21 https://lod-cloud.net/ 22 https://lod-cloud.net/lod-data.json marked as unavailable may be in fact available at the time of our query and vice-versa. Therefore, before executing our approach we check the availability of the endpoints to avoid waiting unnecessarily for a response from an unavailable endpoint.

YummyData

YummyData23 (Yamamoto et al., 2018) is a site referencing and monitoring various SPARQL endpoints in the biomedical domain. We first get the URL leading to the SPARQL endpoint of the datasets from the JSON data obtained from their API. Then we check if the datasets have a VoiD annotation ('void' field equal to True) and in such case we remove the suffixes "virtuoso/sparql" or "sparql" from the URLs of the SPARQL endpoints and we add as a new suffix ".well-known/void" to refer to the VoiD page describ-ing the datasets. 24 For instance, to obtain the VoiD page of the Protein Ontology the URL https://sparql. proconsortium.org/virtuoso/sparql becomes https:// sparql.proconsortium.org/.well-known/void). Now that we have described how we retrieve information about SPARQL endpoints, we will get to the heart of the matter by describing the resources needed by the algorithm and some of its key steps.

EQUIVALENCE LINKS RETRIEVAL AND DATA CURATION

Collecting true instances of (inverse) functional properties

To establish identity, we collect relevant owl:InverseFuntionalProperty and owl:FunctionalProperty that we store in the named graph same:Properties.

According to OWL specifications: if a, b, c are three resources, (i) 25 if there exist inverse functional property relations ip(a, b) and ip(c, b) there also exists an equivalence relation owl : sameAs(a, c) and (ii) 26 similarly, if there exist functional property relations f p(a, b) and f p(a, c) there exists an owl : sameAs(b, c) equivalence relation.

However, depending on the SPARQL endpoints, the properties' definitions may vary and contain abusive usage of these types or at least usage that should be limited to a local closed world.

For instance, rdfs:label is defined as an owl:InverseFunctionalProperty in the National Digital Data Archive of Hungary 27 or agront:isPartOfSubvocabulary 28 is defined as a owl:FunctionalProperty by the LusTRE endpoint. 29 Table 2 provides some statistics we computed about this problem. The following steps (sections 5.1.1 to 5.1.3) refer to the block corresponding to the first "if" in algorithm 1 and the item 3 in the 24 first list in Section 3.

Initialization

We first query all available endpoints (property ends:statusIsAvailable set to true) in the named graph same:N to return their properties of type owl:InverseFunctionalProperty and owl:FunctionalProperty. A filter is performed on the properties defined as blank nodes. Then, these data are stored as RDF* triples (Hartig and Thompson, 2014) in the named graph same:Properties and we keep as information the dataset from which they come with the same:statementInDataset property. These triples are stored in RDF* to record the statements typing properties together with the provenance dataset in which they were found, i.e.:

<<foaf:firstName a owl:FunctionalProperty>> same:statementInDataset <http://uriburner.com/>

We then perform two types of curation: curation by schema and curation by voting. Properties for which the definition could not be deferenced or found in the SPARQL endpoints are excluded.

Curation by schema

We ensure that the use of these properties corresponds to what was intended by the creators of the ontologies is to extract the schemas of these properties by deferencing them. To do so, we use the namespaces of these properties which we have inserted into our local triplestore in the named graph same:Properties using the property same:hasNamespace and perform the SPARQL clause: LOAD SILENT <namespace> INTO GRAPH kg:default;

Using namespaces to retrieve RDF documents is more efficient since it avoids downloading multiple times the same document where multiple properties of type owl:InverseFunctionalProperty and owl:FunctionalProperty are defined. These documents are then loaded into the named graph kg:default. This first step already corrects some assertions about properties (see Table 2).

Curation by voting

In a second step, we handle properties for which no schema could be deferenced.

We have placed these properties in the graph named same:NotDeferencedProperties to distinguish them from the others. We perform queries on the available endpoints in the set N.

After identifying whether the endpoints have the schemas of a property, we count the number of endpoints including the schemas against the property types so that we can perform a vote on the most accepted definition of a property. The condition for assigning the type (property same:votingType) owl:InverseFunctionalProperty and/or owl:FunctionalProperty is that a property must be defined as such, by at least half of the SPARQL endpoints that store a schema for the given property. The statistics to compute the type of these properties are stored in the named graph same:PropertiesNotDeferencedStatistics. For this purpose we declared several properties such as same:nbOfTimesDefinedAsFunctionalProperty and same:inNbOfDatasetWithSchema.

By this means, we are able to identify for example the property sparql:endpoint 30 as an owl:InverseFunctionalProperty and the property semsci:CHEMINF 000009 31 as a owl:FunctionalProperty.

From the set of curated properties, we can infer owl:sameAs relationships of the same:Target of the current Qi with the available endpoints same:N.

Extraction of owl:sameAs properties

Now that we have inspected and corrected the type of the owl:InverseFunctionalProperty and owl:FunctionalProperty properties, it is possible to infer owl:sameAs relationships. To do this, we extract the owl:sameAs relationships for the same:Target resources and curate them by following an iterative mechanism. The goal being not to question the endpoints twice about the same resource same:Target for its owl:sameAs relationships. For this purpose, these resources are stored in different named graphs same:Qi at each iteration i. We query the available endpoints in N with the same:Target of the current iteration (in same:Qi) and we store the resulting equivalent URIs in the next named graph same:Qi+1. A filter clause ensures that we do not store an already existing same:Target in the named graph same:Qi+1. The stop condition of the algorithm is to exhaust all instances of same:Target. This step refers to the block corresponding to the "while" loop of algorithm 1.

Working with live endpoints of the World Wild Web, we pay attention to technical details such as the fact that we have to query some endpoints with only URIs that include ASCII characters since we have identified some SPARQL endpoints that do not support non-ASCII char-30 http://www.w3.org/ns/sparql-service-description#endpoint 31 https://semanticscience.org/resource/CHEMINF 000009 acters. 32 We actually extract and store URIs containing non-ASCII characters but we perform a transformation using the following SPARQL clause:

FILTER(!REGEX(str(?URITarget), "[ˆ\x00-\x7F]", "i")). This point can be improved later in a future work with a more detailed description of SPARQL access points. We also extract the authority component of the URIs33 and store them with the same:hasAuthority property. This will be used to curate owl:sameAs relationships.

Curation of the owl:sameAs links

We carry out the curation of owl:sameAs relationships assuming that equivalent resources with URIs defined within the same authority must explicitly be asserted as equivalent by that authority. These links were obtained through a direct owl:sameAs relationship or from a owl:InverseFunctionalProperty and a owl:FunctionalProperty. Thus, we will ensure that the resources linked by owl:sameAs relationships comply with the rules defined below.

We identified two different patterns for erroneous relationships linked through resources that we call same:Rotten. More patterns may be added to further extend the constraints that equivalent resources must meet.

For complexity reasons we split the curation between two rules: one operating on the results from the same authority obtained at distinct iterations (rule #1) and one operating on the results of the same authority at the same iteration (rule #2):

• Rule #1 : Let a: be the prefix of an authority and b: the prefix of another authority, if there is a sameAs(a:1,b:1) relationship and a sameAs(b:1,a:2) relationship and no sameAs(a:1,a:2) relationship, this rule states that b:1 is of type same:Rotten. This rule is applied regardless of the length of the path of owl:sameAs between a:1 and a:2.

• Rule #2 : Let a: be the prefix of an authority and b: the prefix of another authority, if there is a sameAs The Figure 2 displays two examples on which these rules are applied. Once identified as such we delete the owl:sameAs relations including a same:Rotten and the same:Target resulting from these resources. Before the application of the two rules above, all resources (a:1, a:2, b:1, b:2) are of type same:Target. Contrarily to other methods, this approach does not require the extraction of all the alleged existing equivalence relations for processing their quality and it also trims as soon as possible the exploration of bad quality equivalences and their transitive closure.

EXPERIMENTAL PROTOCOL AND EVALUATION

6.1 Quantitative Evaluation on Linked Open

Table 2 shows statistics about the properties of type owl:InverseFunctionalProperty and owl:FunctionalProperty found online and on which we applied the process described in section 5.1 to collect true instances of these types. Only 22% of the RDF documents queried that a priori contained properties of type owl:InverseFunctionalProperty or owl:InverseFunctionalProperty could be loaded. Approximately 17% of the properties claimed of type owl:FunctionalProperty were verified as such by voting or dereferencing, while for the properties of type owl:InverseFunctionalProperty, they have been verified as such in 60% of the cases. The large majority of properties of type owl:InverseFunctionalProperty have been deferenced, while about half of the properties of type owl:FunctionalProperty were identified by voting.

Protocol, Dataset and Baselines

The different experiments were conducted on an HP EliteBook 840 G2, 2.6 hHz, 16 GB RAM with a virtual environment under Python 3.8.5 and the software Corese Semantic Web Factory 34 (Corby and Zucker, 2010) version 4.1.6d deployed locally. Corese is used as a local triplestore on which we mainly use SPARQL 1.1 Query and Update features. We evaluated our approach on the Barack Obama identity links knowledge graph developed by (Raad et al., 2020). 35 Regarding the initialization, we declared for our algorithm the target URI dbr:Barack Obama 36 (a same:Target) in the named graph same:Q0. The 34 https://project.inria.fr/corese/ 35 https://github.com/raadjoe/obama-lod-identity-analysis 36 PREFIX dbr: <http://dbpedia.org/resource/> different closures on the Barack Obama entity with which we compare ourselves (with sameAs.cc (Raad et al., 2020), LODsyndesis (Mountantonakis and Tzitzikas, 2018) and sameas.org (Jaffri et al., 2008)) and our approach, SameLive, are the following:

• Ground truth: The manual annotation of the closure of the owl:sameAs extracted from the LOD-a-lot dataset distributed into 8 identity sets (Barack Obama, Obama's Presidency, Obama's Presidential Transition, Obama's Senate Career, Obama's Presidential Centre, Obama's Biography, Obama's Photos, Black President). The undetermined URIs included in the identity cluster about Barack Obama are essentially URIs for which we do not have enough semantics to confidently annotate them.

• sameAs 0.99: Results after removing the relations with an error degree greater than 0.99 with the method used by sameAs.cc where the error degree is based on the communities resulting from the Louvain algorithm. This approach leads to two identities sets B 1 and B 2 , and enabled the separation of URIs referring to the Obama's presidency and his presidential transition from the other identity sets. However, these two sets are still inconsistent since they do not allow to perform a closure on a single real world entity.

• sameAs 0.4: Results after removing the relations with an error degree greater than 0.4 in the method of sameAs.cc. This approach leads to 219 identity sets (C 1 to C 219 ) with only one identity set C 1 with non-singleton URIs.

• sameAs.org: Results were obtained through the API of sameAs.org,37 and we corrected URI encoding issues to avoid counting them as new ones.

• LODsyndesis: To detect errors, both clustering with similarity function (content based detection) and shortest path between a pair of instances (graph based detection) are used. Results were obtained through the API of LODsyndesis,38 and we corrected their encoding issues too.

• SameLive: Our closure performed on the data extracted from the SPARQL endpoints indexed by the voiD Store, the LODCloud and the Yummy-Data websites. O 1 only includes resources of type same:Target, O 2 contains both resources of types same:Target and same:Rotten Table 3, based on the work of (Raad et al., 2020), reports the results of our approach compared to sameAs.cc, LODsyndesis and sameAs.org on the Barack Obama identity links knowledge graph.

Discussion

After three iterations of the algorithm, we reached the closure of our solution.

The closure on dbr:Barack Obama by considering only owl:sameAs relationships takes 40 minutes, and considering the owl:InverseFunctionalProperty and owl:FunctionalProperty properties takes 21 hours and a half with a regular laptop setup described in section 6.1.1. The execution time comes mainly from the endpoint querying. We intend to look at approaches to improve this with timeouts and further parallel querying. We are currently working on a cluster version of SameLive for this purpose. In terms of statistics that represent 1 starting URI same:Target (in Q0), 130 in Q1, 9 in Q2, 1 in Q3 and 53 same:Rotten in Q -1 .

Assessing our results on this graph presents a clear disadvantage for our approach because it involves a snapshot of the 2015 Linked Open Data (LOD). As a result, links that have disappeared are not included in our approach. However these are the best baselines as far as we know and our crawling-free online approach still obtains slightly lower results but comparable to the best approach, the sameAs 0.4 proposed by (Raad et al., 2020). Moreover, if we focus on the advantages of SameLive, the online na- The SPARQL query we use to detect potential errors eliminates redirect links in a dataset if they are not declared as owl:sameAs in it (or by extension if there is no owl:InverseFunctionProperty or owl:FunctionalProperty relationship in the same dataset).

To increase this coverage with our approach, we would have to include specific properties to redirects such as the property dbo:wikiPageRedirects 40 with DBpedia).

Qualitative Evaluation on Specific Examples

From the Barack Obama identity links knowledge graph, one can notice that: some of the resources evaluated as being of the same nature as dbr:Barack Obama are no longer valid, 41 URLs redirecting to valid resources are considered valid, 42 while other more questionable resources are also considered valid. 43 Depending on the application, it may be unnec- essary to obtain such a degree of confidence for obtaining equivalence links as proposed by sameAs 0.99, but in the case where one really wants to obtain owl:sameAs relations, only sameAs 0.4, LODsyndesis and our approach provide an answer. With the graph of identity links about Barack Obama only entities more or less related to Obama exist. However this is not the case for all the graphs obtained by extracting owl:sameAs relationships (i.e., previous extractions present on the English DBpedia endpoint linked dbr:Berlin to dbr:Tirana, dbr:Gaspé Peninsula, dbr:Jersey City, New Jersey, dbr:Point Reyes National Seashore, dbr:Flint, Michigan, and this is still the case on sameAs.org). Thus, even if we lower our similarity expectations, the sameAs 0.99 approach does not necessarily guarantee that on such graphs its results do not keep wrong relationships.

Our system, unlike sameAs.cc, discriminates redirects to a resource if it does not have a direct owl:sameAs relationship with that resource. This point may have its advantage in error detection. However the public benchmark on which we are evaluating discriminates against this position.

Another important point is that two resources belonging to the same identity cluster may result in the generation of different equivalence links depending on the starting resources. The reason for this is that we do not process the whole graph of equivalences, the greedy algorithm starts from the set S of seeds and stops as soon as possible to avoid propagating errors or querying the endpoints more than necessary.

Application Evaluation on Specific Use Case

The source code of the project and its instructions are available at https://github.com/Wimmics/SameLive and the algorithm vocabulary at https: //ns.inria.fr/same/same.owl. Two modes of the algorithm are available to consider or not the owl:InverseFunctionalProperty and owl:FunctionalProperty. We also performed an evaluation on a real application: the integration of the knowledge graphs obtained from different named entity recognition and linking methods applied to the same corpus. In this type of usecase, to consolidate the knowledge graph and support further processing and visualization, it is important to detect that two URIs extracted by two different annotators are in fact identifying the same resource. We tested our approach on the public dataset CovidOnTheWeb (Michel et al., 2020), where the authors extract named entities but do not propose equivalence links between the URIs produced by different annotators.

As an example we report here on the result obtained on the article "COVID-19: what has been learned and to be learned about the novel coronavirus disease" 44 (Yi et al., 2020) and more precisely on the 312 distinct entities from DBpedia and Wikidata extracted from it with semantic annotators.

By exploring only the owl:sameAs relationships on these 312 starting URIs (in Q0), the algorithm ends after 6 iterations with: 1526 same:Target in Q1, 3762 in Q2, 1797 in Q3, 78 in Q4, 71 in Q5 and 2 in Q6. We computed a total of 6001 same:Rotten in Q -1 , correcting errors such as, for instance, the confusion between URIs coming from the French chapter of DBpedia identifying the kidney vs. a specific portion of it called the "distal convoluted tubule". 45 Among the 312 seeds URIs, 32 are determined as equivalent. Some of these 32 resources considered as equivalent are not available in sameAs.cc, sameAs.org and LODsyndesis. This is the case for example for: the respiratory syndrom caused by SARS coronavirus 2 in DBpedia and Wikidata, 46 and the strain of the COVID-19 itself in these two sources. 47 An interesting fact is that so far these resources speaking about the COVID-19 do not have any owl:sameAs relationship in the English chapter of DBpedia.

CONCLUSION

We proposed a method to identify owl:sameAs relationships relying on the online SPARQL querying of distributed datasets and using heuristic rules to correct results. We also exploit and inspect the quality of owl:InverseFunctionalProperty and owl:FunctionalProperty relationships, using the 44 http://ns.inria.fr/covid19/0eadf5a901c0d89fad2c202990056556be103e12 45 e.g., http://fr.dbpedia.org/resource/Tubule distal and http://fr. dbpedia.org/resource/Rein 46 e.g., http://dbpedia.org/resource/Coronavirus disease 2019 and http://www.wikidata.org/entity/Q84263196 47 e.g., http://dbpedia.org/resource/Severe acute respiratory syndrome coronavirus 2 and http://www.wikidata.org/entity/Q82069695 definitions given by endpoints and a voting approach. We show that a heuristic approach can retrieve high quality equivalence links without requiring the extraction of all the alleged existing equivalence relations. In addition, it is possible to use other algorithms (community detection, similarity function, graph-based metric, etc.) in addition to/instead of the curation rules we have implemented.

Because our algorithm works online this also exposes it to return different results for the same input, for example, if a SPARQL endpoint does not answer. Inversely, our method has the advantage of giving the user the possibility to include or exclude endpoints (public or private) on the fly, and thus to include locally stored datasets as long as a SPARQL endpoint is deployed.

It may be interesting to include other dataset catalogs, such as the ones using the CKAN API. 48 Related to this, integrating SPARQL Micro-Services (Michel et al., 2018) or other mapping approaches on top of these catalogs would allow us to query them directly with SPARQL instead of manipulating beforehand their data with another language. The use of such techniques could also help us extend our method to include non-RDF datasets.

Extracting owl:InverseFunctionalProperty, owl:FunctionalProperty and owl:sameAs relationships is not enough for some datasets. For instance Wikidata formalizes equivalence relationships with identifiers (typed as external identifier wikibase:ExternalId using wikibase:propertyType49 ) leveraging URI patterns. Also, although they seem to be rarely used, we intend to study the inclusion of owl:hasKey to have a modular and extensive set in the analysis of equivalence links. In addition we plan to consider redirects -including different scheme component of the URIs such as HTTP/S. All these extensions could be addressed by adding additional rules, some of which could be the result of mining and learning approaches.

Deferencing resources deemed as same:Rotten and comparing them to same:Target with a similarity metric is also a direction to obtain more results. Exploiting the underlying semantics (e.g., owl:differentFrom, owl:AllDifferent...) of the resources is also worth exploring.

Finally, we intend to follow different leads to improve the performance of our approach in terms of speed, from query optimization (in particular for the owl:InverseFunctionalProperty and owl:FunctionalProperty properties) and further parallel querying. We will also study the software and hardware architecture needed to provide a web service with a caching system. We plan also to further exploit the monitoring capabilities of SPARQL, by using for example the PROV-O ontology 50 to better track the provenance of results, this could be used in particular for owl:sameAs relationships stored in specific named graphs (see Section 3, item 4 in the second list). We also want to exploit timestamps to, among other things, timely re-run queries executed a long time ago or to query an endpoint that was previously unavailable.

Figure 1 :

 1 Figure 1: Workflow diagram of the steps followed to retrieve equivalent links from the starting resources in Q 0 with the available endpoints in same:N.

  (a:1,b:1) relationship and a sameAs(a:1,b:2) relationship and no sameAs(b:1,b:2) relationship, this query states that b:1 and b:2 are both of type same:Rotten.

Figure 2 :

 2 Figure 2: Examples of resources identified as same:Rotten (green dots) in a path of owl:sameAs relations with the rules mentioned in the sub-section 5.2.1. The red pause icon indicates that there is no owl:sameAs relationship between two resources.Table 2: Statistics linked to the properties of type owl:InverseFunctionalProperty and owl:FunctionalProperty. The incorrect properties are stated as such after loading the RDF document defining them. Category Number of elements Properties asserted as owl:InverseFunctionalProperty 3784 Properties asserted as owl:FunctionalProperty 13298 Not deferenced properties among those extracted 14192 Incorrect owl:InverseFunctionalProperty properties 10 Incorrect owl:FunctionalProperty properties 35 Properties participating in the voting process 1220 Properties voted as owl:InverseFunctionalProperty 123 Properties voted as owl:FunctionalProperty 1111 Properties voted as not owl:InverseFunctionalProperty 1097 Properties voted as not owl:FunctionalProperty 109 Final number of owl:InverseFunctionalProperty 2288 Final number of owl:FunctionalProperty 2261 Number of loaded RDF documents 168 Number of missing RDF documents 781

Table 1 :

 1 Main vocabulary introduced for the equivalence discovering algorithm.

	Element	Main type	Role
	same:Rotten	owl:Class	Resource that is source of potentially erroneous relationships.
	same:N	rdfg:Graph	Named graph that contains information about the void:Dataset resources.
	same:Properties	rdfg:Graph	Named graph that contains asserted owl:InverseFunctionalProperty and owl:FunctionalProperty.
	same:PropertiesNotDeferenced rdfg:Graph	Named graph that contains not deferenced properties after the LOAD clause.
	same:Q-1	rdfg:Graph	Named graph that contains the same:Rotten resources.
	same:Q0	rdfg:Graph	Named graph that contains the starting same:Target.
	same:Qi	rdfg:Graph	Named graph that contains the same:Target retrieved at the i iteration of the equivalence relationships algorithm.

same:Target owl:Class Targeted resource for discovering equivalence relationships. same:hasAuthority owl:DatatypeProperty Authority of the resource. same:hasIteration owl:DatatypeProperty Iteration of the equivalence relationships algorithm during which the named graph was generated. same:hasNamespace owl:DatatypeProperty Namespace of the resource. same:statementInDataset rdf:ObjectProperty Points to the void:Dataset that a statement is a part of. same:votingType owl:ObjectProperty rdf:type of the resource determined after voting.

  see VoiD documentation on "discovering": https://www.

	w3.org/TR/void/#well-known.
	25 https://www.w3.org/TR/2012/REC-owl2-syntax-20121211/#Inverse-
	Functional Object Properties
	26 https://www.w3.org/TR/2012/REC-owl2-syntax-20121211/
	#Functional Object Properties
	27 http://lod.sztaki.hu/sparql
	28 http://aims.fao.org/aos/agrontology#isPartOfSubvocabulary
	29 the endpoint http://linkeddata.ge.imati.cnr.it:8890/sparql in-
	cludes the EARTh -Enviromental Applications Refer-
	ence THesaurus-and ThIST -Italian Thesaurus of Earth
	Sciences-datasets)

Table 3 :

 3 Comparison of the owl:sameAs closures on dbr:Barack Obama. Rotten (subtraction of sets O 2 and O 1 on the total of URIs), and 67 new URIs about Barack Obama compared to the LOD-a-Lot dataset. As an example, we identified as same:Rotten URIs coming from URIBurner that include resources of dubious quality such as "The Irishman" on Netflix. 39 11 resources of type same:Rotten are considered as belonging to the identity set of Barack Obama (subtraction of sets O 2 and O 1 on the entity set about Barack Obama).

		Ground truth	sameAs 0.99	sameAs 0.4 sameAs.org LODsyndesis	SameLive
	Real World Entity	A 1	B 1	B 2	C 1	S 1	L 1	O 1	O 2
	Barack Obama	260	260	0	120	240	19	105	116
	Other Real World Entity	78	10	68	0	22	0	0	0
	New URIs outside A 1	0	0	0	0	413	14	27	67
	Undetermined URIs	102	92	10	1	32	4	9	11
	Identity Sets	1	2		219	1	1	1	1
	Total URIs in Identity Set	440	362	78	121	707	37	141	194
	ture of it, we are able to identify a total of 141
	equivalent resources of type same:Target and 53
	same:

PREFIX ov:<http://open.vocab.org/terms/>

https://web.archive.org/web/20170510073633/http: //kakapo.dcs.qmul.ac.uk/ontology/musim/0.2/musim.html

https://demos.isl.ics.forth.gr/lodsyndesis/

https://github.com/ldspider/ldspider

http://sage.univ-nantes.fr/see/sameAs

https://github.com/raadjoe/obama-lod-identity-analysis

https://tools.ietf.org/html/rfc8615

PREFIX ends: <https://labs.mondeca.com/vocab/endpointStatus/>, archive link: https://web.archive.org/web/20210302021149/https://labs. mondeca.com/vocab/endpointStatus/

https://www.w3.org/TR/void/

http://void.rkbexplorer.com

PREFIX dcterms: <http://purl.org/dc/terms/>

http://void.rkbexplorer.com/sparql

https://yummydata.org/

e.g. http://linkedlifedata.com/sparql

URI = scheme:[//authority]path[?query] [#fragment] in RFC 3986

http://sameas.org/rdf?uri=http://dbpedia.org/resource/Barack Obama

https://demos.isl.ics.forth.gr/lodsyndesis/rest-api/objectCoreference? uri=http://dbpedia.org/resource/Barack Obama

https://docs.ckan.org/

PREFIX wikibase: <http://wikiba.se/ontology#>


François Stoffelbach

Dirk Saurenz

Rinaldo Poli
email: rinaldo.poli@u-bourgogne.fr

Improved Preparations of Molybdenum Coordination Compounds from Tetrachlorobis(diethylether)molybdenum(IV)

Reduction / Molybdenum / Chlorides / Inorganic Synthesis / O ligands Reduction of MoCl5 with metallic tin in diethylether provides a rapid and convenient entry to compound MoCl4(OEt2)2. The latter can be transformed easily and in high yields into a variety of other useful synthons. Loss of ether in the solid state affords a new and reactive form of MoCl4.

Treatment with THF, PMe3, or LiOBu t affords compounds MoCl4(THF)2, MoCl4(PMe3)3, or Mo(OBu t )4, respectively, in high isolated yields. Treatment with metallic tin in THF affords MoCl3(THF)3. All of these reactions can be carried out under simple experimental conditions and represent significant improvements relative to previously reported syntheses of the same compounds.

Introduction

The element molybdenum displays a very rich chemistry in low, intermediate and high oxidation states alike. Research with this metal is intense in the organometallic/catalysis, coordination, bioinorganic, cluster, and solid state/materials areas. However, all this activity stems from a very limited amount of commercially available Mo-containing starting materials, the most convenient ones being elemental Mo, Mo(CO)6, MoS2, MoO3 and MoCl5. Some transformations require long multiple-step procedures, resulting in a considerable investment of time and especially in considerable product losses due to the compounding of imperfect reaction yields. The amelioration of known synthetic methods and the search for alternative procedures allowing a reduction of reaction times, the simplification of isolation and purification procedures, and an increase of overall yields are continuous goals of the synthetic chemist.

The situation is perhaps best illustrated by the example of MoCl3(THF)3, a useful intermediate for a wide variety of inorganic synthetic applications. Following the first reported preparation by a carbonyl route, [1] the compound was subsequently obtained by a reductive procedure starting from MoCl5. This pentachloride compound is, at the same time, a strong Lewis acid and a powerful oxidant and its direct reduction in THF is complicated by the acid-catalysed ring opening polymerization of THF, a problem which is circumvented by using other solvents. The most commonly employed synthetic procedure (Scheme 1) starts with the interaction of MoCl5 with a nitrile RCN to afford MoCl4(RCN)2, followed by replacement of the nitrile with THF and final reduction to the Mo(III) product. A variety of ameliorations of this procedure have been published over the years including three reports in Inorganic Synthesis, replacing propionitrile with acetonitrile, zinc with tin as the reducing agent, and modifying the reaction conditions and product separation procedures. [2][3][4][5][6][7] Nevertheless, this three-step procedure remains rather long and requires, in our hands, isolation of both MoCl4(MeCN)2 and MoCl4(THF)2 intermediates in order to obtain a product of sufficient quality. With individual step yields of 63-86%, the overall yield from MoCl5 is 46% at best with a time investment of ≥ 2 days. Another variation on the same theme (Scheme 1) is reduction of MoCl4(MeCN)2 to MoCl3(MeCN)3, followed by solvent exchange. [8] A direct and rapid one-step high-yield (85%) procedure has been published more recently, but this requires the use of Ph2SiH2 as a reducing agent and a controlled, slow addition of the MoCl5 solid to the silanecontaining THF solution. [9] A reverse addition of the silane to MoCl5 is possible only in pentane as solvent, prolonging the reaction time to 48 h.

Scheme 1

Our continuous interest in the coordination and organometallic chemistry of middle-valent molybdenum continuously pushes us to ameliorate the preparative procedures of our needed synthetic intermediates. Our attention has been attracted by compound MoCl4(OEt2)2, whose high yield synthesis was reported a few years ago from MoCl5 and either norbornene [10] or allyltrimethylsilane [11] as reducing agents. Only a limited use of this compound in subsequent synthetic work was detailed, however, in those previous studies. In this contribution, we shall show that MoCl4(OEt2)2 can also be conveniently prepared by tin reduction of MoCl5, and that it is a versatile intermediate for the preparation of a variety of other molybdenum compounds. In particular, MoCl3(THF)3 becomes now accessible in a half-day, two-step, single-flask procedure (no isolation of intermediates is required) in greater than 80% overall yields from MoCl5 and the common reagents ether, THF, and metallic tin.

Results and Discussion

While the high Lewis acidity of MoCl5 makes this compound incompatible with the THF solvent, causing its cationic ring opening polymerization, non cyclic ethers do not suffer from this detrimental decomposition pathway. Ethereal solutions of MoCl5 are stable and are rapidly reduced by metallic tin, to yield a fine orange crystalline powder of MoCl4(OEt2)2, equation 1. The reaction is fast but controlled at room temperature, being usually complete within 1/2 h as evident from the visual appearance of the powdery orange precipitate. No wild exothermic behavior has been observed during this reductive process, which therefore does not require any special precaution. In addition, the tin chloride co-product is ether-soluble while MoCl4(OEt2)2 is only sparingly soluble.

Therefore, the Mo(IV) product is easily purified by ether washings with only minimal product loss.

The yields of this preparation are consistently greater than 80% for quantities of product greater than a gram. These yields and the product purity are comparable with those of the previously reported syntheses, which used more exotic reducing agents such as allyltrimethylsilane or norbornene. [10,11] It is to be remarked that a possible by-product, MoOCl3(Et2O)2, [12] may form when wet ether and/or partially hydrolyzed MoCl5 starting compound are employed. This compound, however, is green and soluble in ether, [10] while the MoCl4(Et2O)2 product is orange and sparingly soluble. Thus, minor impurities of the molybdenyl species may be easily eliminated. In our work, we had no evidence for the formation of this by-product.

(1)

We have not investigated in detail the nature of the oxidized tin product. The literature reports that SnCl2 is capable of reducing MoCl4(THF)2 in THF to afford MoCl3(THF)3 and SnCl4(THF)2. [9] Metallic tin is equally capable of carrying out the same reduction and to even over-reduce the metal below the III level. In ether, however, any further reduction by Sn (which may be used in excess) must be extremely slow since we found no NMR evidence for the formation of Mo(III), after isolation of the solid material and exchange with THF (vide infra). On the basis of this observation, we assume that SnCl2 is probably also a poorer reductant in ether than in THF. Thus, the tin/ether combination seems ideal, giving rise to a rapid, controlled and selective reduction.

Although compound MoCl4(OEt2)2 is only sparingly soluble in ether, it is well soluble in aromatic hydrocarbons. In this respect, it resembles its sulfur congener, MoCl4(SEt2)2. [13] Besides elemental analysis and IR, no additional characterization was shown in the previous reports. The magnetic moment (µeff = 2.33 µB) is significantly lower than the spin-only value for two unpaired electrons, because of the expected spin-orbit coupling for the triplet ground state derived from the pseudo-t2g 2 configuration. This value is in the range observed for other MoCl4L2 complexes (L = THF, MeCN, PPh3, etc.), namely 2.2-2.5 µB. [14] The 1 H NMR spectrum in C6D6 shows only one resonance for the methyl and one for the methylene protons. These resonances are broad as may be expected for a paramagnetic complex. However, there are not significantly contact-shifted from the position of free ether (cf. the highly shifted resonances of the bis-THF adduct, vide infra, or those of the sulfur congener, MoCl4(SEt2)2 [13] ). We attribute this behavior to the rapid dissociation equilibrium of equation 2, as proposed previously. [10] Thus, the broad lines would be the time-averaged signals of the methylene and methyl protons of the diamagnetic free ether and the paramagnetic complexes, at the fast exchange limit. In comparison with the related bis-SEt2 complex, the NMR spectrum shows that diethylether is a much more labile ligand than its sulfur congener, as might be expected.

(2)

The only available crystal structure for a Mo IV X4L2 complex with monodentate ligands apperars to be that of the sulfur congener, MoCl4(SEt2)2, which is trans. [13] Compound MoCl4(CH3OCH2CH2OCH3) has a cis arrangement enforced by the chelating dimethoxyethane ligand. [15] For this reason, it is likely that complex MoCl4(OEt2)2 also adopts a trans configuration.

Most related Mo(III) anions [Mo III X4L2] -also adopt a trans arrangement, [16][17][18] although examples having the cis configuration are also known. [19,20] In spite of numerous attempts under a variety of conditions, we have not been able to grow single crystals of this compound.

The synthetic utility of MoCl4(OEt2)2 has been investigated in some detail and the results are Three different crystalline forms of MoCl4 have been described in the literature, namely -MoCl4, [21] -MoCl4, [22,23] and -MoCl4. [24] The  form was obtained from MoCl5 by reflux with tetrachloroethylene in carbon tetrachloride; a reflux time shorter than 2 days is said to leave unreacted pentachloride. [21] The  form was obtained by conproportionation of MoCl5 and MoCl3 in a temperature gradient, [22] while the  form was prepared by heating a mixture of MoO2 and carbon with a nitrogen stream saturated with CCl4 vapors. [24] The observed magnetic moment of 1.6 µB for our amorphous MoCl4 does not compare with any of those reported for the three crystalline phases (i.e. 0.85 µB for -MoCl4, [21] 2.31-2.54 µB for -MoCl4, [22] and 1.91 µB for -MoCl4 [24] ), although it is closest to that of the  phase. An additional and significant difference is observed in the temperature behavior. A disproportionation process occurs at temperatures above 140°C to generate MoCl5 and MoCl3. This process is also observed for the  phase, but only at about 288°C. [24] On the other hand, the  phase was shown to transform at ca. 140°C into the  phase, which in turn converts into the  phase at ca. 240°C. Our evidence for the disproportionation of amorphous MoCl4 at 140°C is clear: volatile MoCl5 sublimes and the solid residue transforms into a reddish material which is no longer soluble in ethanol, indicating the formation of lower chlorides. Furthermore, the signals of MoCl3 in this material have been detected by powder X-ray diffraction. On the basis of this evidence, it seems obvious that amorphous MoCl4 is a labile and reactive form, leading directly to the thermodynamic mixture of Mo(III) and Mo(V) chlorides at relatively low temperature, while the crystalline and phases are more inert.

The lability of amorphous MoCl4 is further shown by its high chemical reactivity. Addition of THF leads to the rapid and exothermic formation of MoCl4(THF)2 and treatment of the resulting mixture with other reagents (for instance, LiOBu t ) affords the expected Mo(IV) products in excellent yields, vide infra. The conversion of MoCl4 to the bis-THF adduct is quantitative and is best accomplished by addition of THF to a pentane suspension of the tetrachloride, in order to evacuate the reaction heat.

Scheme 2

Compound MoCl4(THF)2, however, is more conveniently obtained by direct substitution of ether from MoCl4(OEt2)2, which may be obtained in situ from MoCl5 (overall 89% isolated yields). This route appears to give a cleaner MoCl4(THF)2 product relative to the previously described synthesis from MoCl4(MeCN)2. It is possible that the ligand exchange equilibrium is further shifted toward the bis-THF product when the less coordinating Et2O ligand is bonded to the metal center. Like for the bis-Et2O analogue, no NMR data seem to be available in the literature for compound MoCl4(THF)2. The NMR spectrum in CDCl3 shows highly shifted (12.5 and -32.8 ppm) but relatively sharp (w1/2 = 12 and 15 Hz, respectively) resonances, indicating the presence of a single isomer in solution. These chemical shifts compare relatively well with those of the bis-thioether complex MoCl4(SEt2)2. [13] Like for the bis-Et2O analogue, we were unable to grow single crystals of this compound. Substitution of ether in MoCl4(OEt2)2 with PMe3 conveniently leads to the previously reported compound MoCl4(PMe3)3. [25] Besides substitution reactions of the ether ligand, the chlorides can also be easily replaced. This metathesis process provides a convenient entry to the tetrakis(tert-butoxo) derivative Mo(OBu t )4.

The previous synthesis of this compound involves metathesis from Mo(NMe2)4, [26] a compound available only in low yields from MoCl5. [27] After its first report, this compound does not appear to have been used for further investigations, possibly because of the laborious and low yield synthetic procedure. It is now available, however, in a practical half-day procedure in greater than 80% yields from MoCl5. As such, it may constitute a new useful synthon for Mo(IV) chemistry.

Previous physical characterization of compound Mo(OBu t )4 comprised IR, UV-visible and mass spectra, and magnetic susceptibility. The compound was reported as having an intermediate magnetic moment between those expected for a magnetically diluted compound with two unpaired electron and a diamagnetic compound (eff = 1.38 B in toluene or 1.37-1.40 B in the solid state). [26] In our hands, the compound is diamagnetic by solid state magnetic susceptibility and by NMR and EPR spectroscopies. In this respect, it appears perfectly homologous to the corresponding thiolato derivative, Mo(SBu t )4. [28] Other MoX4 compounds with -donor X ligands, namely Mo(NMe2)4, [29] Mo(PCy2)4, [30] and other mixed amido-phosphido derivatives [31] are mononuclear and diamagnetic, while compounds with -neutral X ligands such as Mo(2-MeC6H4)4 [32] and Mo(norbornyl)4 [33] are paramagnetic for two unpaired electrons.

When compound MoCl4(OEt2)2 was exposed to THF in the presence of metallic tin, a smooth reduction to MoCl3(THF)3 occurred. This is not surprising because the transformation of

Conclusion

In conclusion, we have developed a new, simple and time-efficient preparation of MoCl4(OEt2)2, and demonstrated its synthetic utility with the improved preparation of a few key materials such as MoCl4(THF)2, MoCl3(THF)3, Mo(OBu t )4, and a new and reactive form of MoCl4.

Experimental Section

General Remarks: All manipulations were carried out under an atmosphere of dry and oxygen-free argon with standard Schlenk techniques. Solvents were dried and deoxygenated by refluxing over suitable reagents (THF and ether over sodium benzophenone ketyl, toluene over sodium) and distilled under argon before use. 1 H measurements were color and 1 H NMR spectrum of this material are identical with the analyzed product obtained as described in the previous section.

(c) From MoCl4. 553 mg (2,33 mmol) black MoCl4 was suspended in 5 ml of pentane. After addition of 5 ml THF on top of the pentane layer the mixture was allowed to stir for 2 minutes. The reaction occurred very rapidly to produce an orange precipitate. The colorless supernatant was removed by cannula and the residue was dried in vacuo leaving 890 mg of MoCl4(THF)2 (quantitative yield). NMR properties of this material correspond with those previously described for MoCl3(THF)3. [34] Synthesis of MoCl4(PMe3)3. To a magnetically stirred suspension of MoCl4(Et2O)2 (0.96 g, ca. ) corresponds to that reported in the literature. [25] Synthesis of Mo(O-t-Bu)4. (a) From MoCl4. THF (15 mL) was added to 330 mg (1.39 mmol) of black MoCl4 causing slight warming and precipitation of the orange THF adduct. The suspension was cooled in an ice bath and a 1 M LiO t Bu solution in THF/hexane (5.55 mL, 5.55 mmol) were added via syringe. The reaction mixture was sirred for one hour at 0°C, then slowly warmed to room temperature and stirred overnight to complete the reaction. The THF was removed in vacuo from the dark brown solution. The brown solid was extracted with 20 mL of pentane, then with 10 mL of CH2Cl2. After filtration, the combined extracts were evaporated in vacuo to dryness, leaving crude Mo(O-t-Bu)4 as a brown solid (540 mg, quantitative yield). The product can be recrystallized in low yields (ca. 25%) from cold pentane.

Synthesis of

Anal. Calcd. for C16H36MoO4: C, 49.48; H, 9.34. Found: C, 49.58; H, 9.29. 1 H NMR ():1.55 (s) in C6D6, 1.66 (s) in C6D5CD3 and 1.12 (s) in acetone-d 6 . All these solutions are EPR-silent, but a strong signal rapidly develops upon exposure to air. µeff = 0.72 µB (diamagnetic correction:  = -219.92 . 10 -6 c.g.s. units).

(b) From MoCl4(Et2O)2. Compound MoCl4(Et2O)2 was obtained in situ from MoCl5 (3.06 g, 11.2 mmol) and tin as described above. After separation from the excess tin and the ether, it was suspended in 40 mL of THF and the suspension was cooled in an ice bath. After addition of LiO t Bu (40 ml of a 1 M solution in THF/hexane, 40 mmol) the reaction mixture was stirred at 0 °C for 2 h, then slowly warmed to room temperature and stirred overnight to complete the reaction. Removal of the solvent in vacuo left a brown residue which was extracted with 35 mL of CH2Cl2 and filtered. After total removal of the solvent in vacuo, a gummy brown-black residue was left which became an almost black powdery solid over a period of two days. The yield of crude Mo(O-t-Bu)4 was 3.517 g (81 % from MoCl5).

summarized in Scheme 2 .

 2 Because of the facile ether loss shown by the NMR study above, it is best to use a freshly prepared sample for the purpose of further synthetic applications. Heating the isolated MoCl4(OEt2)2 solid under vacuum leads to the complete loss of the ether ligands at a relative low temperature, leaving amorphous (by X-ray powder diffraction) MoCl4. Darkening of the solid already occurs at about 55 °C, while at 80 °C the powder was totally black. Samples of ether-free MoCl4 have been obtained by operating at temperatures up to 130°. This procedure is considerably more practical and time efficient than the literature preparations (see below) and leads to a more chemically reactive material.

MoCl4(OEt2) 2

 2 to MoCl4(THF)2 in a THF slurry has been established above, and the reduction of the latter to MoCl3(THF)3 by tin in THF is a well established process. However, we find that this reaction gives excellent results without the need to isolate the MoCl4(OEt2)2 product after the first reductive step, nor the second MoCl4(THF)2 intermediate. Thus, it suffices to use enough tin reagent to reduce Mo(V) to Mo(III) and to replace the solvent after completion of the first reduction step, in order to achieve a convenient high-yield synthesis of MoCl3(THF)3 in one half day from MoCl5.

  2.5 mmol) in THF (10 mL), a THF solution of PMe3 (1 M, 8 mL, 8 mmol) was slowly added. The orange suspension rapidly transformed into a deep violet suspension. The mixture was stirred for 4 h at room temperature, then the supernatant was decanted off and the solid was washed with THF (2 x 5 mL) and dried under vacuum. Yield : 0.78 g, 67%. Anal. Calcd. for C9H27Cl4MoP3: C, 23.20; H, 5.84. Found : C, 23.04; H, 5.62. The 1 H NMR spectrum (broad band at -17 ppm (w1/2 = 130 Hz) in CDCl3 at 25°C

  The mixture was then stirred for 30 min at room temperature to form an orange solution and orange solid. The supernatant was decanted off and 30 mL of THF was added. The mixture was then stirred for 3 h at room temperature. The pale orange-brown crystalline product MoCl3(THF)3 was separated from excess tin as described above for the synthesis of MoCl4(Et2O)2. The product was then washed with Et2O (2 x 15 mL) and dried under vacuum. Yield : 3.99 g, 82%. Anal. Calcd. for C12H24Cl3MoO3: C, 34.43; H, 5.78. Found : C, 34.04; H, 5.51. The 1 H

	MoCl3(THF)3. MoCl5 (3.18 g; 11.64 mmol) and coarse tin powder (2.77 g; 23.33 mmol) were suspended
	in 30 mL of Et2O.

Acknowledgments

We are grateful to the CNRS for funding and for a student fellowship (BDI) to FS. DS thanks the Conseil Régional de Bourgogne for a postdoctoral fellowship.

Graphical Abstract

The reduction of MoCl5 by tin in diethylether is rapid, controlled and selective to afford MoCl4(OEt2)2 in high yields. A variety of other useful synthetic intermediates have been obtained by rapid, practical and high-yield new procedures.

carried out on a Bruker AC 200 spectrometer. The peak positions are reported with positive shifts in ppm downfield of TMS as calculated from residual solvent peaks. The magnetic susceptibility measurements were carried out with a Johnson Matthey magnetic balance, which operates by a modified Gouy method. The molar susceptibilities for the calculation of the magnetic moments were corrected for the diamagnetism of the ligands by using Pascal's constants.

Elemental analyses were performed with a Fisons EA 1108 apparatus. MoCl5, PMe3 (1 M in THF) and Sn (fine grains, 20 mesh) were purchased from Aldrich Chemical Co. and used as received.

Synthesis of MoCl4(Et2O)2: MoCl5 (1.20 g; 4.39 mmol) and coarse tin powder (1.04 g; 8.76 mmol) were suspended in 30 mL of Et2O at room temperature. The mixture was then stirred for 30 min to form an orange solution and orange solid. The latter was separated mechanically from the excess tin taking advantage of the large difference in density between the two solids. Under gentle stirring with a magnetic stirring bar, the metallic tin remained at the bottom of the flask and the supernatant suspension of the MoCl4(Et2O)2 product was transferred into a new flask via a medium size (G15) cannula. The product was then collected by filtration, washed with Et2O (5 x 5 mL) and dried under vacuum.

Yield : 1.36g, 80%. The compound has a marked tendency to loose diethyl ether (see Results and Discussion) and samples dried without special precautions systematically gave low C,H analyses; a freshly prepared sample which was dried at -20°C gave a correct analysis: C, 25.31; H, 5.23 (Calcd. for C8H20Cl4MoO2: C, 24.89; H, 5.22). The IR spectrum (Nujol mull) is identical with that reported in the literature. [11]

Synthesis of MoCl4.

In a typical reaction orange MoCl4(Et2O)2 was placed in a dry, air-free Schlenk tube and slowly heated under vacuum in an oil bath. First darkening occured at about 55 °C. At 80 °C the powder was totally black.

The yield of MoCl4 produced is quantitative. Two experiments, carried out at 120° for 5 h and at 130° for 2 h gave materials with the same properties. Elemental analysis of the black material confirmed the absence of C and H. µeff = 1.60 µB and 1.61 µB, respectively (diamagnetic correction:  = -80.4 . 10 -6 c.g.s. units). The product dissolves completely in ethanol. When the reaction temperature is raised above 140 °C, sublimation of MoCl5 is observed and the resulting reddish solid residue (MoCl3) is no longer ethanol soluble. This decomposition process is equally observed for isolated MoCl4 in vacuum and under an argon atmosphere in a sealed ampoule.

Synthesis of MoCl4(THF)2. (a)

From isolated MoCl4(Et2O)2. Compound MoCl4(Et2O)2 (1.26 g, ca. 3.26 mmol) was suspended in 15 mL of THF. The mixture was then stirred for 3 h at room temperature to form an orange-yellow solid.

The supernatant was decanted off and the solid was washed with THF (10 mL), then ether (10 mL), and finally dried under vacuum. Yield: 0.99 g (79%). (b) From MoCl5. MoCl5 (1.156 g, 4.23 mmol) and coarse tin powder (1 g, 8.42 mmol) were suspended in 20 mL of Et2O at room temperature. The mixture was stirred for 30 min to form MoCl4(Et2O)2 . Then, the excess metallic tin was eliminated by transferring the supernatant suspension of MoCl4(Et2O)2 into a new flask via a medium-size cannula. The solid was washed with Et2O (3 x 10 mL) and 20 mL of THF was subsequently added. The mixture was then stirred for 3 h at room temperature to form an orange-yellow solid. Then the supernatant was decanted off and the residue was washed with 10 mL of THF and then with 10 mL of ether, and finally dried under vacuum. Yield: 1.438 g, 89%. The


Rim Aissa

Samia Guezane-Lakoud

Emilie Kolodziej

Martial Toffano

Louisa Aribi-Zouioueche

lipase catalytic promiscuity

Diastereoselective synthesis of bis(α-aminophosphonates) by

Introduction

The α-aminophosphonates are of great biochemical and pharmacological effects 1,2 due to the association of phosphonate and amine. These molecules are phosphorus structural analogues of amino acid 3 and they are interesting for medicinal chemistry. 4 The α-aminophosphonates derivatives have received much attention owing as enzyme inhibitors, pharmacogenic agents, haptens of catalytic antibodies, herbicidals, inhibitors of serine hydrolases, inhibitors of UDP-galactopyranose mutase and also as anticancer agents as reported in the literature. 5 The Kabachnik-Fields reaction is the most efficient method for the synthesis of α-aminophosphonates. 6 We found various synthetic methodologies using different catalysts for the synthesis of α-aminophosphonates derivatives. 7 Recently, we have reported the synthesis of α-aminophosphonates by enzymatic catalytic promiscuity using Candida antarctica lipase B (CAL-B) by Kabachnik-Fields reaction. 8 This is the first example of C-P bond formation involving the principle of enzymatic promiscuity. These findings inspired us to seek lipase that could catalyze the formation of bis(α-aminophosphonates). These multidentate ligands are extremely interesting compounds that can be used in the extraction of metals or as monomers in the preparation of macrocyclic compounds or as polymers carrying phosphonate and amine. 9 Bis(α-aminophosphonates) exhibit significant biological activities (Figure 1), compound 1 shows antifungal activity, compound 2 has antioxidant activity, 10 and compound 3 shows optimal antiproliferative activity to human tumoral cells from colon carcinoma. 11 Figure 1. Bis(α-aminophosphonates) having biological activities Bis(α-aminophosphonates) were synthesized from Schiff bases 12 or diamine 9,13,[START_REF] Milen | [END_REF] under microwave irradiation 10 or with Lewis acid. 9 However, most of these approaches involve longer reaction times, expensive reagents, high temperature, stoichiometric amount of catalysts, low diastereoisomers ratio and metallic contamination due to the use of metal catalyst or Lewis acid. Herein, we applied catalytic promiscuity with lipase as an efficient 'Green' method for the synthesis of new bis (α-aminophosphonates) with excellent diastereocontrol by Kabachnik-Fields multi-component condensation.

Enzymes are well-known for catalyzing specific reactions, and for their ability to perform highly regio-, chemo-and stereo-selective transformations, at high reaction rates in relatively mild conditions. 15 Enzymes have many benefits in the context of green and sustainable chemistry and are integrated to efficient and environmentally benign processes for chiral drug development by kinetic resolution or asymmetric synthesis. 16 Lipases especially, are the most used enzymes in synthetic organic chemistry. 17 They are known for their advantages such as providing products of high purity and good selectivity in one reaction step, fewer byproducts and simple separation, as shown in our previous works. 18 Furthermore, the use of organic solvents in the enzymatic reaction instead of conventional media or aqueousorganic co-solvent mixtures, 19 allowed application of enzymes to expand in catalytic promiscuity, especially in multi-component reaction. Exploiting enzymatic catalytic promiscuity might lead to improvements in existing catalysts and furnish judicious synthesis pathways. Enzymatic promiscuity is the ability of a single enzyme active site to catalyze multiple chemical transformations with different transition states, other than the reactions for which it has been specialized. This innovating approach is the starting point for a divergent evolution of new protein function which is explained by the creation of a new enzymatic activity depending on circumstances. 20, 21 Hult and Berglund 22 defined three types of promiscuity: (i)-condition promiscuity: catalysis of different reactions under different conditions from the native one, (ii)-substrate promiscuity: enzymes with broad substrate specificity and (iii)-catalytic promiscuity based on the ability of a single enzyme active site to catalyze several chemical transformations with different transition states. Recently, the product promiscuity was considered as a fourth kind, in which a single enzyme converts a single substrate to multiple products by different transition states. 20a (Figure 2). 24 Biginelli reaction, 25 Mannich reaction, 26 Morita-Baylis-Hillman reaction, 27 Henry reaction, 28 Michael reaction, 29 Aldolisation reaction 30 and others. 31,32,33 In organophosphorus chemistry, utilization of lipases is also described for the resolution of racemic hydroxyphosphonates by acylation 34 or hydrolysis. 35 To the best of our knowledge, the use of lipase catalytic promiscuity in a diastereoselective synthesis including the simultaneous formation of two P-C bond is novel and has never been reported yet (c est une proposition de modification.

Results and discussion

The multi-component reactions (MCRs) are realized by lipase catalytic promiscuity for the bis(α-aminophosphonates) synthesis. This new benign and clean protocol implies the condensation in one pot of two equivalents of benzaldehyde 1a, one equivalent of benzidine 2 and two equivalents of diethylphosphite 3 which is used as model reaction with lipase in 2 mL of organic solvent. Several parameters have been studied such as: lipases, solvents, temperature and the reaction time. The reactions were monitored by TLC analysis. The products were obtained in two diastereoisomers mixture, and then separated by extraction or by flash chromatography in ethyl acetate and hexane (70/30). All results are summarized in Table 1.

Table 1. Optimization reaction of the bis (α-aminophosphonates).

Entry a

Lipase (mg) Solvent T °C Time /h Yield(%) In all cases the bis (α-aminophosphonates) 4a were obtained with high yield by catalytic promiscuity using CAL-B. Firstly, the multi-component reaction was performed without lipase in THF during 24 hours, the results show that no reaction was observed even by increasing the temperature up to 70°C (Table 1, entry 1). The denatured CAL-B has been tested, there is no advancement. The nature of the lipase has a significant effect on reaction, five lipases were examined (two animals and three microbial): Rabbit gastric Lipase (RGL) lipase, 36 Porcine pancreatic lipase (PPL) and: Candida cylindracea lipase (CCL), Pseudomonas cepacia lipase (PCL) which are free lipases and Candida antarctica B lipase immobilized on acrylic resin (CAL-B). Under these conditions, only CAL-B can promote catalytic promiscuity and allows obtaining 4a compound with 80% yield (Table 1, entry 2), compared with the use of PCL, CCL, PPL and RGL lipases which lead to the bis(α-aminophosphonates) with low yields (< 29%) (Table 1, entries 3, 4, 5 and6). For a better performance, the temperature was increased to 50°C with CAL-B and the product 4a was obtained in 90% yield (Table 1, entry 7). Product 4a was obtained in a similar yield at the same temperature by decreasing the amount of CAL-B lipase from 100 mg to 50 mg (Table 1, entry 8) but no reaction by less than 50 mg of CAL-B or at room temperature. Subsequently, the hydrophobicity solvent effect has been studied, we found that the THF is the best solvent (Table 1, entry 8 vs entries 9, 10, 11 and 12). No progress of the reaction was observed in TBME and toluene (Table 1, entry 9 and 10) and a moderate yield was obtained in Et2O (26%) (Table 1, entry 11), whereas in AcOEt 62% of 4a was isolated (Table 1, entry 12). A study of the time was also carried out; we found that at the 30th minute, a total disappearance of benzidine was observed (90% yield) (Table 1, entry 15).

In addition, a recycling of CAL-B was examined on the model reaction, it showed that the lipase lost its catalytic performance from the fourth cycle (Fig 3). So, in optimized conditions, the bis(α-aminophosphonate) 4a was obtained with high yield using CAL-B (50mg) in THF at 50°C. In order to explore the effectiveness and limitations of the MCRs by biocatalytic promiscuity with CAL-B, we applied optimized reaction conditions on a series of variously substituted aldehydes with electron-withdrawing and electron-donating groups (Table 2). The molecular structure of all bis (α-aminophosphonates) was confirmed by NMR 1 H, 13 C and 31 P spectroscopy and HRMS analysis. 1 H NMR and 31 P NMR experiments were used for diastereomers (meso/dl ratio) quantification in the crude reaction. The results of Table 2 show the efficiency of the MCRs catalyzed by CAL-B for the preparation of bis(α-aminophosphonates) giving a 66-90% yield with high diastereoselectivity control depending on the electronic effect of aldehydes. The best results yields (> 80%) are obtained for: 4a, 4b, 4c, 4d, 4h, 4j and 4k, and with average yields (66-77%) for 4e, 4f, 4g, and 4i compounds.

In addition, five derivatives of bis (α-aminophosphonates) 4a, 4c, 4h, 4i and 4k are obtained with a total diastereoselectivity (100% dr). A high diastereoselectivity is obtained for 4b (96/4% dr), even for 4f and 4j which is obtained with (80/20% and 86/14% dr) respectively, it also remains good for 4d (71/29% dr). On the other hand, the diastereoselectivity decreases sharply for the 4g and 4e, this is probably be due to the high steric hindrance of aldehydes. To the best of our knowledge, all these bis(α-aminophosphonates) derivatives, except the 4h compound, have never been reported in the literature yet. 37 We completed this works by a multi-gram scale reaction. Thus, a scaling up of the procedure was carried out from 0,636 g (6 mmol) of aromatic aldehyde, 0,636 g (3 mmol) benzidine, (0,828 g, 6 mmol) diethylphosphite in THF and an appropriate amount of CAL-B lipase. The quantitative yields were obtained regardless of the scale and the remaining product was isolated with (up on 92%).

In order to be able to propose a reaction mechanism, we proceeded to several experiments. When the multicomponent reaction is carried out with an equimolar quantity of starting materials (1/1/1 ratio of aldehyde / benzidine / diethylphosphite), the results show that the bis(α-aminophosphonates) is the sole and only compound obtained in these reaction conditions. No trace of mono-phosphonated compound is observed. This suggests that the formation of the C-P bond is performed on both sides simultaneously of benzidine or that the second addition of diethylphosphonate is extremely rapid and efficient which is probably favored by the proximity of the monophosphonate/enzyme pair. Anyway, at this stage, we suppose that the enzyme plays a crucial role in the privileged selectivity for the bis-phosphonate compounds formation. Combining the viewpoints developed by Per Berglund et al 22 and on the basis of our observations described above, we proposed the mechanism of the reaction, summarized in Scheme 1. We propose a mechanism involving the coordination to the oxyanion hole by the carbonyl and simultaneous activation of nucleophile by histidine and aspartate from the active site.

Scheme 1. Proposed mechanism of CAL-B-catalyzed bis(α-aminophosphonates) synthesis

The oxyanion hole activates the carbonyl of aldehyde substrate and renders it susceptible to nucleophilic attack by one amine of benzidine to form an imine (Step I). The active-site histidine with aspartate as a base that activates the diethylphosphite as nucleophile for attack of the imine to form the corresponding product (Step II). In a concomitant manner in the same active site of lipase, the oxyanion hole activates the carbonyl of aldehyde which promotes the attack of the second amine of benzidine to form the corresponding imine (Step III). The following nucleophilic attack of the diethylphosphite activated by histidine / aspartate couple, leads to the formation of the bis(α-aminophosphonate) 4.

Conclusion

In conclusion, we describe the first simultaneous formation of two Carbon-Phosphore bonds by catalytic promiscuity using acrylic resin-immobilized lipase CAL-B in a one pot multi-component reaction. This original strategy gives access to a novel series of bis(α-aminophosphonates) with high diastereoselectivity and very satisfactory yields, in a short reaction time and under mild and green chemistry conditions. The lipase-catalyzed Kabachnik-Fields reaction provides a new case of catalytic promiscuity and might be a useful synthetic method for bioorganic synthesis. The CAL-B was easily recovered and reused several times. We have also, devised a multi-gram scale reaction for the preparation of bis(α-aminophosphonates) 4a with replicable quantitative yields . The development of this new easy route opens up very interesting perspectives to easily recoverable applications. We design a straightforward, efficient and utile protocol to create double Carbon-Phosphore bond formation using CAL-B in non-conventional media and metal-free access. These results suggest a new synthetic route toward biological derivatives under mild and green conditions.

Experimental section

General information: All starting materials, reagents and enzymes used in this study were purchase from Sigma-Aldrich or Acros company and were used without purification. Various commercially available lipases were screened: lipase from Porcine pancreas type II (PPL; LA = 100-500 U/mg), Rabbit Gastric Lipase (RGL; LA > 1170 U/mg), Candida Cylindracea lipase (CCL, LA = 3.85 U/mg), Pseudomonas Cepacia lipase (PCL; LA > 30 000 U/mg), and the Candida antarctica lipase fraction B immobilized on acrylic resin (CAL-B; LA > 5 000 U/mg). All reactions were monitored by thin-layer chromatography (TLC) carried out on 0.25-mm Merck silica gel plates (60F-254) using ultraviolet light (254 nm) as the visualizing agent and KMnO4 solution as developing agents. 1 H NMR and 13 C NMR spectra were recorded with Bruker spectrometers (360MHz, 300 MHz and 250 MHz for 1H, 90 MHz, 75 MHz or 63 MHz for 13 C and 101 MHz or 121 MHz for 31 P). Chemical shifts were reported downfield from CDCl3 (δ = 7.26 ppm). For 13 C NMR, chemical shifts were reported in the scale relative to the solvent of CDCl3 (δ = 77 ppm) used as internal reference. Coupling constants (J) are given in hertz. Following abbreviations classify the multiplicity: s = singlet, d = doublet, t = triplet, q = quartet, m = multiplet, br = broad signal. Melting points were measured using Buchi Melting Point B-545. Mass spectra were recorded with a MicrOTOF-Q Bruker spectrometer using electrospray ionization (ESI) analysis.

General procedure for synthesis of bis(α-aminophosphonates) 4a-4k.

To the stirred mixture of aromatic aldehyde (2 mmol), benzidine (184 mg, 1 mmol) and diethylphosphite (331.2 mg, 2.4 mmol) in THF (2ml), the CAL-B (50 mg) was added. The reaction was stirred at 50°C for 30 minutes. After the reaction proceeded to completion, the lipase was removed by filtration. The two diastereoismer mixtures were separated by column chromatography using ethyl acetate /hexane: 90/10 as eluent. Complete experimental data have been provided (NMR spectra and HRMS). These compounds do not have rotatory power, it means that the diastereomers obtained exist as meso (RS/SR) or racemic (RR/SS) forms mixtures. Tetraethyl [(4,1-phenylene) bis(azanediyl)] bis[(phenyl) methylene] bisphosphonate (4a). Yellow solid, Yield: 90%, mp 210°C. 1 H NMR (250 MHz, CDCl3) δ 7.49 (dd, J = 5.6, 3.8 Hz, 4H, H-Ar), 7.38 -7.17 Tetraethyl [(4,1-phenylene)bis(azanediyl)] bis[(4-nitrophenyl) methylene]bisphosphonate (4b). Orange solid, 90% Yield, mp: 219.5°C. 1 H NMR (250 MHz, CDCl3) δ 8.20 (d, J = 8.3 Hz, 4H), 7.66 (dd, J = 8.9, 2.3 Hz, 4H), 7.27 -7.18 (m, 4H), 6.54 (d, J = 8.6 Hz, 4H), 4.86 (d, J = 25.1 Hz, 2H), 4.22 -3.96 (m, 8H), 3.93 -3.81 (m, 2H), 1.30 (t, J = 7.1 Hz, 6H), 1.18 (t, J = 7.1 Hz, 6H). 13 C NMR (63 MHz, CDCl3) δ 144. 21 (dd, J = 20.4, 8.9 Hz), 132.16 -131.84 (m), 128.63 (d, J = 4.7 Hz), 127.31 (s), 123.78 (s), 114.12 (s), 63.63 (dd, J = 15.8, 7.0 Hz), 57.33 (s), 54.98 (s), 16.33 (dd, J = 10.9, 5.7 Hz). 31 Tetraethyl [(4,1-phenylene)bis(azanediyl)] bis[(4-fluoro-phenyl)methylene] bisphosphonate (4d). Green solid, 84% Yield, mp: 172.3°C. 1 H NMR (250 MHz,CDCl3,4H,7.27 (d,J = 8.5 Hz,4H,, 7.06 (t, J = 8.6 Hz, 4H, H-Ar), 6.62 (d, J = 8.4 Hz, 4H, H-Ar), 4.79 (d, J = 24.2 Hz, 3H, HCP+NH), 4.25 -4.07 (m, 4H, O-CH2-CH3), 4.07 -3.84 (m, 2H, O-CH2-CH3), 3.86 -3.63 (m, 2H, O-CH2-CH3), 1.31 (t, J = 7.1 Hz, 6H, O-CH2-CH3), 1.17 (t, J = 7.0 Hz, 6H, O-CH2-CH3). 13 C NMR (63 MHz, CDCl3): δ 164. 44 (s), 160.47 (s), 144.79 (d, J = 15.0 Hz), 131.64 (d, J = 13.2 Hz), 130.13 -128.79 (m), 127.14 (s), 115.76

Figure 2 .

 2 Figure 2. Different kinds of promiscuity Catalytic promiscuity is described by several reactions for the C-C and C-N bond formation in the presence of different enzymes 23 such as: Knoevenagel reaction,24 Biginelli reaction,25 Mannich reaction,26 Morita-Baylis-Hillman reaction, 27 Henry reaction,28 Michael reaction,29 Aldolisation reaction 30 and others.31,32,33 In organophosphorus chemistry, utilization of lipases is also described for the resolution of racemic hydroxyphosphonates by acylation 34 or hydrolysis.35 To the best of our knowledge, the use of lipase catalytic promiscuity in a diastereoselective synthesis including the simultaneous formation of two P-C bond is novel and has never been reported yet (c est une proposition de modification.

Figure 3

 3 Figure 3 Reusing of the CAL-B catalyst

a

  Reaction conditions: benzaldehyde (2 mmol), benzidine (1 mmol) and diethylphosphite (2.4 mmol), CAL-B (50 mg), room temperature, 30min. b Yield of the pure product, purified by column chromatography or recrystallization from hexane.

  (m, 10H, H-Ar), 6.61(d, J = 8.6 Hz, 4H, H-Ar), 4.78 (d, J = 24.3 Hz, HCP), 4.24 -4.02 (m, 4H, O-CH2-CH3), 4.02 -3.82 (m, 2H, O-CH2-CH3 ), 3.74 -3.57 (m, 2H, O-CH2-CH3), 1.28 (t, J = 7.1 Hz, 6H, O-CH2-CH3), 1.11 (t, J = 7.1 Hz, 6H, O-CH2-CH3). 13 C NMR (91 MHz, CDCl3) δ 144.89 (d, J = 14.7 Hz), 135.92 (s), 131.42 (s), 128.62 (s), 127.90 (dd, J = 9.5, 4.0 Hz), 127.10 (s), 114.10 (s), 63.31 (d, J = 6.0 Hz), 56.96 (s), 55.30 (s), 16.32 (dd, J = 22.2, 5.9 Hz). 31 P NMR (121 MHz, CDCl3, 25°C): δ 22.63 ppm. HRMS (ESI) m/z calcd for C34H42N2O6NaP2 [M +Na + ]: 659.2410; Found 659.2406.

  P NMR (121 MHz, CDCl3, 25°C): δ 20.70 ppm. HRMS (ESI) m/z calcd for C34H40N4O10NaP2 [M+Na + ]: 749.2111; Found 749.2129. Tetraethyl [(4,1-phenylene)bis(azanediyl)] bis[(4-cyano-phenyl) methylene] bisphosphonate (4c). Yellow solid, 85% Yield, mp: 203.7°C. NMR 1 H (250 MHz, CDCl3, 25°C) :δ 7.71 -7.58 (m, 8H, H-Ar), 7.31 -7.18 (m, 4H, H-Ar), 6.57 (d, J = 11.0 Hz, 4H, H-Ar), 4.84 (d, J = 22.0 Hz, 4H, HCP+NH ), 4.24 -4.10 (m, 4H, O-CH2-CH3), 4.09 -3.96 (m, 2H, O-CH2-CH3), 3.95 -3.75 (m, 2H, O-CH2-CH3), 1.31 (t, J = 7.1 Hz, 6H , O-CH2-CH3), 1.19 (t, J = 7.1 Hz, 6H, O-CH2-CH3). NMR 13 C (63 MHz, CDCl3, 25°C): δ 144.42 (d, J 3 C-P = 14.2 Hz), 142.00, 139.17 (s), 132.38 (s), 131.78 (s), 128.55 (d, J 2 C-P = 5.1 Hz), 127.27 (s), 114.09 (s), 111.79 (d, J = 3.4 Hz), 111.13 (s), 63.66 (d, J C-P = 14.8Hz, C-O), 63.42 (d, J C-P = 6.7 Hz, C-O), 57.38(s, C-N), 55.02(s, C-P), 16.43 (d, J 3 C-P = 5.7 Hz, CH3-CH2-O-P), 16.24 (d, J 3 C-P = 5.5 Hz, CH3-CH2-O-P). 31 P NMR (121 MHz, CDCl3, 25°C): δ 22.05 ppm. HRMS (ESI) m/z calcd for C36H40N4NaO6P2 [M +Na + ]: 709.2135; Found 709.2344.

Table 2

 2 Lipase-catalyzed bis (α-aminophosphonates) synthesis a

Acknowledgements

The Algerian Ministry of Higher Education and Scientific Research (DGRSDT, FNR) is gratefully acknowledged for financial support of this work. The authors knowledge Dr. Nadia Grine for English reviewing of this manuscript.

Conflicts of interest

There are no conflicts to declare.