Cédric Herpson
email: cedric.herpson@lip6.fr

P r e -p r i n t Dedale : A Dedicated Testbed for Multi-Agents Problems

Keywords: Multi-agent, environment, simulation, testbed, p2p, decentralised problem solving, coordination, decisionmaking, learning

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INTRODUCTION

In recent years, single-agent standardised environments allowed the research community to efficiently benchmark their proposals, which led to real progress in the field [START_REF] Adil | State-of-the-art and open challenges in rts gameai and starcraft[END_REF][START_REF] Marc G Bellemare | The arcade learning environment: evaluation platform for general agents[END_REF][START_REF] Vinyals | Alphastar: Mastering the realtime strategy game starcraft ii[END_REF]. Unfortunately, there is currently no equivalent for multi-agent coordination, learning and decision-making problems under real-life hypotheses.

Several experimental platforms have been built in the last 30 years [START_REF] Thierry Bouron | Mages: A multi-agent testbed for heterogeneous agents[END_REF][START_REF] Brockman | Openai gym[END_REF][START_REF] Kitano | Robocup rescue: A grand challenge for multiagent and intelligent systems[END_REF][START_REF] Kravari | A survey of agent platforms[END_REF][START_REF] Michael | Complex adaptive systems modeling with repast simphony[END_REF][START_REF] Van Gompel | Mas-discosim 4 pdp: a testbed for multi-agent solutions to pdps[END_REF]. Nevertheless, they either focus on large-scale Complex Adaptive Systems (CAS) [START_REF] John | Studying complex adaptive systems[END_REF] and are thus restricted to synchronous environments with no [START_REF] Michael | Complex adaptive systems modeling with repast simphony[END_REF] or few communication [START_REF] Taillandier | Building, composing and experimenting complex spatial models with the gama platform[END_REF] capabilities or they assume closed-world environments where evolve up to only 4 homogeneous agents with a perfect vision of the system in zero-sum games between two teams [START_REF] Resnick | Pommerman: A multi-agent playground[END_REF], when they are not controlled from a unique omniscient entity [START_REF] Hausknecht | Half field offense: An environment for multiagent learning and ad hoc teamwork[END_REF]. In both cases, these platforms make unrealistic hypotheses. It thus makes their use difficult or even impossible for coordination problems, and may render the proposed solutions ineffective or inoperable in a real situation. As a result, researchers working on these issues often use their own (unpublished) toy examples environments, which can unfortunately turn out to be over-fitting the proposed algorithms or make the results difficult to reproduce.

Through the release of Dedale, we aim to facilitate and improve the experimental evaluation conditions of the devel-oped algorithms, and to contribute to the progress of the field towards decentralised solutions able to deal with real-world hypotheses and problems. Section 1 presents the state of the art of multi-agent testbeds and compare them to Dedale through the prism of what we define as the 8 fallacies of MAS. Section 2 presents Dedale, and more particularly the important features from the user's point of view. In Section 3, we present three class of multiagent problems that can be studied through the use of Dedale as well as the associated open-research issues. Finally, section 4 presents the peer-to-peer capabilities of Dedale for longterm experiments in open-world before discussing its future evolutions.

I. EXISTING PLATFORMS AND THE 8 FALLACIES OF MAS

To study decentralised multi-agents coordination, decisionmaking and learning problems under real-life hypotheses, a suitable testbed should avoid what we call the 8 fallacies of MAS:

1) Agents take turns executing each other 2) Agents are homogeneous and run at the same speed 3) Agents have access to unlimited resources 4) Agents are reliable 5) Agents are sure 6) Agents have a global and perfect vision of the system 7) Agents number does not change over time 8) Communication respects the 8 fallacies1 of distributed systems [START_REF] Rotem-Gal-Oz | Fallacies of distributed computing explained[END_REF]. To consider turns (1) make disappear all questions related to synchronized actions and drastically reduce conflicts over resources. [START_REF] Noa Agmon | Multi-robot perimeter patrol in adversarial settings[END_REF][START_REF] Alspach | Searching and sweeping graphs: a brief survey[END_REF] Homogeneous agents -both in term of capacities and (unlimited) computational capabilitieseliminates bottlenecks and operational constraints (calculation time, memory, and energy), and simplifies coordination problems (the agents are interchangeable). [START_REF] Antoniades | Pursuit-evasion strategies for teams of multiple agents with incomplete information[END_REF][START_REF] Marc G Bellemare | The arcade learning environment: evaluation platform for general agents[END_REF] In real life situations, whether deployed on servers or mobile robots, agents can experience malfunctions, face byzantine behaviours,.. Eliminating these hypotheses does not make it possible to study the robustness of the proposed solutions. [START_REF] Luigi Bellifemine | Developing multi-agent systems with JADE[END_REF][START_REF] Beynier | Cooperative multiagent patrolling for detecting multiple illegal actions under uncertainty[END_REF] Outside of toy use-cases, open-environments and limited-percepts' agents are the norm. Assuming complete P r e -p r i n t observation and a fixed number of agents thus conducts proposed solutions to be non-scalable. [START_REF] Thierry Bouron | Mages: A multi-agent testbed for heterogeneous agents[END_REF] To assume a perfect, instantaneous and zero-cost communication network lead to bias the evaluation of all proposed solutions. Finally, from an initially easy to understand and tackle team-of-two independent agents setup, the environment should allow users to progressively raise the complexity by increasing the number of agents as well as to remove simplifying but unrealistic hypotheses (either online or offline). Indeed, this progressivity is a necessary step to evaluate and validate both the robustness and scalability of a decentralised proposal.

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Table I summarizes the behavior of the main simulation environments available today to study multi-agent problems with respect to the 8 fallacies of MAS. The Repast [START_REF] Collier | Repast: An extensible framework for agent simulation[END_REF][START_REF] Michael | Complex adaptive systems modeling with repast simphony[END_REF] and Gama [START_REF] Taillandier | Building, composing and experimenting complex spatial models with the gama platform[END_REF] platforms are central when it comes to agent simulation, but, focusing on largescale Complex Adaptive Systems, they are not designed to study coordination problems. Their objective is to simulate and study the behaviour are emerging from tens of thousands of agents for problems related to transport, climate or epidemiology within GIS-based environments. Communications between agents simply does not exist, and agents runs on a turn-by-turn basis.

On the opposite spectrum, a platform such as Gym [START_REF] Brockman | Openai gym[END_REF], dedicated to reinforcement learning research, is focused on mono or 2 agents use-cases with unlimited computation capabilities and no explicit coordination.

If the well-known Starcraft II testbed [START_REF] Adil | State-of-the-art and open challenges in rts gameai and starcraft[END_REF] offers the possibility to confront more than two adversaries at the same time, no coordination can take place as each agent controls all the entities that compose its "team" and as no communication channel exist between entities within the game. Although technically impressive, DeepMind recent results [START_REF] Vinyals | Grandmaster level in starcraft ii using multi-agent reinforcement learning[END_REF] are no exception. The multi-agent dimension they consider is for them to specialise 3 agents in order to play the 3 available Starcraft races. The same limitation appears with the Robocup Soccer simulator [START_REF] Hausknecht | Half field offense: An environment for multiagent learning and ad hoc teamwork[END_REF]. It is theoretically possible to consider a team composed of more than 2 autonomous agents, but, in practice, the framework's incentive leads users to develop one central agent that efficiently control all the entities that compose a team.

Pommerman [START_REF] Resnick | Pommerman: A multi-agent playground[END_REF], a multi-agent environment based on Bomberman, assumes closed-world environments where evolve up to only 4 homogeneous agents in zero-sum games between two teams [START_REF] Resnick | Pommerman: A multi-agent playground[END_REF]. Communication is synchronous and restricted to 2 Ints in [0,8]. Focused on team-of-two agents learning, it does not currently allow users to scale-up and thus meanly attract the research community around Deep reinforcement learning.

To our knowledge, RoboCup Rescue [START_REF] Skinner | The robocup rescue simulation platform[END_REF] and Mages [START_REF] Thierry Bouron | Mages: A multi-agent testbed for heterogeneous agents[END_REF] platforms are the closest ones to cover all required criteria to study and evaluate multi-agent coordination, learning, and decision-making under realistic hypotheses. If Mages is no longer supported (nor available), RoboCup rescue is still actively developed. In addition to asynchronous and potentially failing communications, Robocup Rescue is the only one (with Dedale) to support explicit limitation of the computational capabilities of the agents2 . Nevertheless, to guarantee their scenarios to scale-up to hundreds of agents, they favour simple agents' architectures and run in a turn-peer-turn unrealistic setting which removes much of the complexity inherent to decentralised problems.

We aim for the Dedale testbed to provide for the multi-agent community a plateform allowing to work under parametrizable but realistic hypotheses and environment setups without sacrificing the number nor the complexity of deployable agents.

II. THE DEDALE PLATFORM

Figure 1 illustrates Dedale's general architecture. From a synthetic standpoint, it combines the well-known Jade framework and the Inter-Platform Mobility Service (IPMS) [START_REF] Luigi Bellifemine | Developing multi-agent systems with JADE[END_REF] with the GraphStream (GS) [START_REF] Dutot | Graphstream: A tool for bridging the gap between complex systems and dynamic graphs[END_REF] and jMonkeyEngine (JME3) [START_REF] Kusterer | jMonkeyEngine 3.0 Beginner's Guide[END_REF][START_REF] Rocha | Selecting the best open source 3d games engines[END_REF] libraries. While Jade is in charge of the MAS management, GraphStream and Jme are respectively handling the two types of environments currently provided by Dedale : discrete dynamic graphs and continuous 3D-environments. Users' agents will then have to evolve within them to accomplish their goals. Note that Dedale and its components are all open-source. Our website [START_REF] Herpson | Dedale : Will your agents succed[END_REF] contains all required information on how to install, configure and run it.

P r e -p r i n t The use of Jade allows us to make real-life hypotheses on the agent's functioning. Each agent is a thread, their respective execution speed can thus vary. Furthermore, there is no bound on the transmission time of a message sent between agents (messages can be lost, delayed, or have a maximum reach depending on the users' choices). We are thus considering both system and communication asynchronism. From these choices, we avoid the 1 st ,2 nd and 8 th fallacies previously introduced. To this point, we made implementation choices guaranteeing to avoid the 5 remaining fallacies of MAS.

The types of continuous environments we currently offer through the JME game-engine increases the complexity of the environment and the planning needs for the agents without intrinsically changing the properties of the problems considered. Thus, for sake of clarity, we will focus in the present document on the case of discreet environments, referring to the continuous case only when the agents' behaviour is significantly impacted.

In the discrete case (see figure 2), the environment is a graph. Nodes are rooms associated with a unique identifier where the agents will find objects to interact with, and edges are non-oriented corridors between them. The topology can be hand-made, generated or imported from OpenStreetMap [15]. The number and the initial location of both objects and agents can also be either generated or hand-picked. By default, only one agent can be on a given node at any given time. However, the user can decide otherwise and individually set higher capacities to nodes. A. Activable elements within the environment 1) Wells: They are dangerous nodes where any agent coming-in falls and dies. Wells generate wind in their surrounding nodes (the distance is parametrizable), giving a warning to any passing agent.

2) Treasures: A treasure is stored within a safe, and is defined by its type (gold or diamonds), its value and its lock (a set of skills required to open it combining strengh and lockpicking expertise).

When an agent (see next section) is in a room where a treasure is, and if its backPack and expertise allow it, then the agent can grab it.

• If the safe is locked and the agent does not possess sufficient expertise to open it, he needs to call for help. Several agent can indeed pool their forces to meet the lock requirements. • If the agent backPack is full or the treasure is a different type than his, then he grabs nothing. • If the agent cannot grab all the treasure of an opened safe, the remaining treasure stays on the map. Another agent can come and take it. The system is designed so that an agent drops a portion of the treasure by picking it up. The more picking actions are made on a treasure, the more the loss is important. This will therefore conduct the agents to opt for picking up a single treasure in a minimum of actions.

3) Benchmark agents (Golems): They are "native" Dedale's agents activable within the environment. Dedale currently offers three types of Golem's behaviours :

• DummyMovingGolem : As he moves, the Golem will shift all or part of the treasures he discovers.

P r e -p r i n t

• CollectingGolem : He will explore the environment and collect the treasures he finds. • EscapingGolem : He will try to move around indefinitely. Golems release a stench which allow other agents to detect them before encountering them. In Fig. 2, the emission radius is set to 1. As we will see in section III, Golem(s) significantly increase the complexity of the tasks to be performed by user's agents.

B. User's agents

Dedale's agents can be of 3 different types : 1) Agent-centered representation: At the beginning, agents are deployed (randomly or not) on the map. The agents do not know the topology beforehand and thus have to discover and learn it.

a) Limited percepts: When an agent is in a room, it can only perceives :

• The id -unique -of the room.

• The names of the others agents in the room, if any.

• The occurrence, if any, of a treasure, its type, value and opening conditions. • The links to the neighbouring rooms (and associated observations, if any). b) Limited communication range: Agents can communicate through messages to share their knowledge, coordinate and optimize their actions. Nevertheless, the reach is limited. An Agent can only communicate with the ones in the neighbourhood (a distance that can vary with each agent). The coordination solutions should thus take into account this fact.

2) Agent observations and actions: In the absence of treasures, 4 actions are available to the agents, 9 otherwise. a) Observation, communication and motion:

• getCurrentPosition() : Returns the current position of the agent

C. Performance analysis

To properly compare the performances of different proposals to a given problem instance, several evaluation metrics are available.

• The number of messages exchanged between the agents • The number of actions executed • The overall time needed to complete a task In the case of a treasure hunt, the quantity of collected resources is also stored. Finally, for both analytical and debugging purposes all of the agents' actions are logged.

III. MULTI-AGENTS USE-CASES

In this section, we present the main classes of multi-agent problems that can be currently studied through the use of Dedale as well as the associated open research issues.

A. Distributed exploration

Consider an unknown finite graph, a set of agents randomly deployed, a limited communication range and the impossibility for two agents to be on the same node at the same time. How to efficiently explore the environment ? This classical problem was initially formulated by Shannon [START_REF] Ce Shannon | Presentation of a maze solving machine. cybernetics: Circular, casual, and feedback mechanisms in biological and social systems[END_REF] and has been extensively studied since then (see [START_REF] Fiorino | Coordinated exploration for labyrinthine environments with application to the pursuit-evasion problem[END_REF][START_REF] Renoux | Contribution to multiagent planning for active information gathering[END_REF][START_REF] Shantanu | Graph Explorations with Mobile Agents[END_REF]).

If uniquely labelled nodes and no harmful situations allow a smooth exploration through the use of Distributed DFS-like algorithms, the activation of the well(s) introduced in section II-A1 significantly change the problem. Indeed, any agent visiting a "well-node" is instantaneously destroyed. In this context, the complete exploration of the environment require for at least one agent to survive knowing all edges leading to the well(s). The location of the harmful node(s) must thus be based on a coordinated exploration and communication strategy.

• What is the minimal number of agents required to locate all wells and finish the exploration ? • For a given number of agent and wells, what is the quickest possible strategy and the minimal number of messages exchanged ? In synchronous cases, when the agents know the topology beforehand or when they start from the same location and P r e -p r i n t have unlimited communication range, some proposal and complexity bound have been established [START_REF] Cooper | Searching for blackhole faults in a network using multiple agents[END_REF][START_REF] Das | Map construction of unknown graphs by multiple agents[END_REF][START_REF] Fraigniaud | Collective tree exploration[END_REF]. Nevertheless, to our knowledge, no algorithm seems to have so far been proposed in the general setting above-mentioned.

Another interesting variation offered by Dedale is to study the cooperative exploration of an unlabelled graph. Once again, under the previously introduced hypotheses, no optimal strategy seems to currently exist [START_REF] Chalopin | Constructing a map of an anonymous graph: Applications of universal sequences[END_REF].

B. Cooperative patrolling and pursuit-evasion games

The second setup is the well known patrolling problem and its related pursuit-evasion game. Consider an unknown finite environment E, a set of agents A, a set of intruders I and limited communication ranges C.

• What is the minimal size of A in order to guarantee that there exist a finite solution to detect and block all the intruders in E ? • For a given number of agent (and intruders), what is the best possible strategy ? To determine the minimal number of agents required for any graph is an NP-Hard problem [START_REF] Alspach | Searching and sweeping graphs: a brief survey[END_REF][START_REF] Chung | Search and pursuit-evasion in mobile robotics[END_REF], but several heuristics have been proposed [START_REF] Antoniades | Pursuit-evasion strategies for teams of multiple agents with incomplete information[END_REF]. Regarding the optimal strategy for a given A and I, if its easy on a (finite) binary tree with unlimited communication range and only one intruder, it becomes more difficult when you set a limited communication range, use a complex environment such as Fig. 3a and annoyingly clever intruder(s). In this context existing proposals mainly tend to decrease the size of the subgraph that the evader(s) can safely reach instead of minimizing the distance between pursuers and evader(s).

As illustrated in Fig 4, the key problem is that an already explored (and thus considered as cleared) area can be contaminated by an intruder moving behind the agents' back, thus requiring to maintain containments areas whose size depend of both the graph structure, the number of patrolling agents and of their respective communication ranges.

Numerous work have been published regarding multiagent patrolling, either from the robotic [START_REF] Noa Agmon | Multi-robot perimeter patrol in adversarial settings[END_REF][START_REF] Portugal | A survey on multi-robot patrolling algorithms[END_REF] or mas [START_REF] Beynier | Cooperative multiagent patrolling for detecting multiple illegal actions under uncertainty[END_REF][START_REF] Chevaleyre | Theoretical analysis of the multi-agent patrolling problem[END_REF][START_REF] Poulet | The open system setting in timed multiagent patrolling[END_REF] communities. But little attention has been paid to the impact of asynchronism, limited communication range or dynamic environments on the agents cooperation [START_REF] Othmani-Guibourg | Multi-agent patrolling in dynamic environments[END_REF]. We believe Dedale to be a suitable testbed in these directions.

C. Treasure(s) hunt & pickup and delivery problems

This last setup, the treasure hunt, is the more complex one as it can include the two previous and create an additional level of difficulty through the agents' heterogeneity and the problems induced. Note that the pickup and delivery problem [START_REF] Martin | The general pickup and delivery problem[END_REF] is a subset of the treasure hunt problem where the pickup and delivery locations are a priori known.

Consider an unknown finite environment with treasure chests, a set of heterogeneous agents randomly deployed and limited communication ranges. Assuming that the team's score only takes into account the treasures stored within the tankers at the end of the time limit:

• What is the best strategy to maximise the overall treasure value within the Tankers' backpacks ?

As highlighted in II-A2, the agents have to minimize the number of picking to maximise the amount of treasure grabbed. The agents goals are thus to : (1) locate the treasures, (2) collectively decide on the coalitions required to efficiently open them, (3) determine the optimal picking order as well as (4) quickly and repetitively find the tankers to unload their backpacks. As agents initally start from distinct locations and do not posses an unlimited communication range, steps 2 to 4 require to solve the rendez-vous problem [START_REF] Pelc | Deterministic rendezvous in networks: A comprehensive survey[END_REF]. Moreover, steps 3 and 4 will make the interlocking problem arise.

1) Path planning and the interlocking problem: Interlocking are non-existent during the exploration phase: When two agents meet each others they only need to share their respective knowledge to get what they were immediately looking for and solve their momentary issue. In the case of a treasure hunt, the heterogeneity of the agents will on contrary generate noninterchangeable objectives and a dynamical hierarchy between agents. Fig. 5 illustrates a typical situation.

A 1 wants to go the node where A 3 is and conversely. At the same time A 2 is moving in towards its goal, node 7, increasing the interlocking complexity. Here, the locked agent (A 3 ) should become prioritary over A 1 as it has no escaping path to let A 1 going through. This priority should not be of one-action duration, otherwise A 1 and A 3 will oscillate "infinitely", soon joined by A 2 . The obvious solution is, in the current example, for A 1 and A 2 to move towards nodes 1 and 2 and wait until A 3 leaves the sub-tree and inform them of this fact before leaving trough node E.

In the general case, multi-agent path planning has been shown to be a PSPACE-hard problem [START_REF] Hopcroft | On the complexity of motion planning for multiple independent objects; pspacehardness of the" warehouseman's problem[END_REF]. Even when the information are available, a global search is only tractable by aggregating the agents [START_REF] Sharon | Conflict-based search for optimal multi-agent pathfinding[END_REF]. In real conditions, from air traffic control to computer games, decentralised replanning and heuristic procedures are the preferred methods to break the occurring interlocks [START_REF] Ko-Hsin | Fast and memory-efficient multiagent pathfinding[END_REF].

Capable of transparently support a hundred of agents on a standard computer 3 , Dedale offers a flexible testbed to study and compare the efficacy, the scalability, and the robustness of those approaches.

2) Dynamicity and decision-making trade-off: If we release the Golem(s) or allow several adversarial teams on the same map, the environment becomes dynamic.

• In the case of the Golems, they will move the treasures.

Consequently, two agents meeting each others might face inconsistency while sharing their knowledge. Until now, the value of a treasure on a given position could only diminish. Now it can also increase. Without the use P r e -p r i n t Fig. 4: The containment problem : Agent A 1 is looking for the intruder I 1 . Its field of view allow him to check the neighbouring nodes. While A 1 explores the graph (arrows 1 to 5), the intruder can move behind its back and join a previously secured area (dotted arrows 6 to 9). of common clock, the agents are no longer capable of identifying the most recent information. • In the case of adversarial teams, in addition to collecting resources some adversaries may block the access to a subgraph without the possibility for a member of a different team to trigger interlocking procedures. The topology of the accessible graph will thus change over time. In both cases the agents will have to significantly adapts their strategy to this situation. When a treasure is discovered, each agent have to choose between picking it up (if possible), protecting it or looking for his team before someone else discovers it. The chosen decision-making process (robust, risk-adverse,..) will greatly influence the result of the team and we believe cooperative learning to be perfectly fitted for the emergence of innovative and adaptive strategies in this context.

IV. FROM A LOCAL TESTBED TO A PEER-TO-PEER ENVIRONMENT FOR LONG-TERM EXPERIMENTS IN OPEN-WORLD

We have so far introduced the different characteristics of Dedale and highlighted its advantages, inherent to the fact that the 8 fallacies of MAS are taken into account. What we believe to be an additional stand-out factor comparatively to the literature is its ability to work as a node in a network of Dedale's environments. Indeed, after conscientiously designing their environment and developing the capabilities of their agents, each user can decide to open incoming or outgoing access to their instance. This offers for the user's agents the possibility to explore foreign and unknown environments, and for foreign agents to discover and test their robustness facing an environment -and potentially the agents's -the local user designed. The size, the complexity and the richness of the "networked" environment accessible to the agents therefore becomes virtually unlimited. This is made possible by the fact that Dedale relies on the JADE multiagent platform [START_REF] Luigi Bellifemine | Developing multi-agent systems with JADE[END_REF], which supports inter-platform migration. When activated, this feature gives two additional actions to the agents :

• getNeighbours(): The list of Dedale's nodes connected to this environment.

• migrateTo(myDestination): Makes the agent migrate to the distant environment it is willing to be deployed in (if the authorisation is granted). For the sake of clarity we will only present here the key points associated with this peer-to-peer feature from the agent perspective.

A. The

To allow foreign agents to dynamically move-in and out of a Dedale instance require to manage two critical elements : security and deployment. Both of them are at the Gatekeeper's expense. As illustrated on Fig. 6, its a supervision agent that authorises or refuses the access to the environment it manages according to the local user preferences as well as on the locally available computational and memory capacities. Once the authorisation received, the local gatekeeper initiates the agent transfer with the distant one following a transaction-type process. All classes that constitute the agent are serialized and sent over the network 4 . A reference to the environment managed by the local gatekeeper is given to the agent while him and his previous knowledge are instantiated. Once the migration achieved, the original agent is transparently destroyed by its former gatekeeper.

B. Supervising distant agents

To allow its agents to leave the nest represents both an opportunity and a risk. An opportunity for learning agents to improve their knowledge and performances, a risk for all to die if the new environment is dangerous or the platform unstable. Either way, to supervise and monitor distants agents is challenging. Dedale currently offer no default backup for the agents, their logs are stored within them and only written on disk when and where the agent dies. Nevertheless, through its local gatekeeper, the user keep a minimalistic control over 4 All of the agent's classes and libraries should thus be serializable. its agents and can send two predefined priority-orders to each of them : goHome and terminate. Thus, a misbehaving but living learning agent can still be repatriated and its knowledge and behaviours analysed.

We believe Dedale's peer-to-peer network feature to be suited for multi-agent coooperative learning and research on long-term autonomy. The user can at the same time tailor its environment to meet its experiments requirements and let its agents face the unexpected, guaranteeing Dedale to be a challenging environment for years to come.

CONCLUSION

Avoiding what we introduced as the 8 fallacies of MAS, we opensource [START_REF] Herpson | Dedale : Will your agents succed[END_REF] the first testbed exclusively designed for studying truly multi-agents problems under real-life hypotheses : asynchronous agents evolving in open, dynamic, and partially observable continuous and discrete environments. From distributed exploration to cooperative pick-up and delivery, including pursuit-evasion games, Dedale offers a wide range of multi-agents use-cases which represent as many open research challenges.

Our next steps will be : (1) To set up a public and automated ranking of the best strategies found for each configuration.

(2) To propose a peer-to-peer network management algorithm allowing the automatic placement of Dedale's nodes according to their reliability, thus offering a classification and a cartography of relatively (un)safe areas for the agents to explore.

Dedale was successfully tested by more than 150 earlyusers, either researchers or post-graduate students on distributed AI. The very positive feedbacks confirm its ease of use and the progressiveness offered. In its educational dimension, its led in particular to the publication of a press article by one of its users on the richness and difficulties inherent to multiagent systems [START_REF] Trazzi | Why coding multi-agent systems is hard[END_REF]. More generally, we believe that Dedale offers a challenging but accessible -because fully parametrizable -combination of coordination, decision-making and learning situations, both for research and teaching activities, outside of the too restrictive multi-agents team-of-2 setup. Its peer-to-peer feature also opens new perspectives with the possibility for researchers to study agents' capabilities to remain autonomous on a long term basis at minimal cost. Finally, if easily reproducible experiments with teams of dozens or hundreds of agents are not common today, we believe that Dedale provides a step towards this goal.

Fig. 1 :

 1 Fig. 1: Dedale's architecture overview : The Jade platform combined with the IPMP component is used as a baseline to create a distributed environment. One GateKeeper's agent (GK) is deployed on each computer and is in charge of the local environment's creation and management. It maintain a view of the distant locations that can be reached from its local map and takes care of incoming and exiting migration requests made by users' agents intending to complete their missions.

Fig. 2 :

 2 Fig. 2: Part of a 400-nodes hand-made environment integrating treasures (gold and diamonds), wells, golems and several teams of 10 heterogeneous agents. 1 Tanker, 2 Explorers and 2 Collectors are visible.

  (a) Groix island, France. Topology imported from OpenStreetMap and used as default testbed for real-world discrete case-study for mas patrolling, treasures hunt or pickup and delivery problems. Pick-up locations are represented as treasures (yellow) and delivery locations as Tanker agents (purple). The collector agents (blue nodes) are the delivery vehicles. (b) Mountainous area, Auvergne, France. Heightmap imported from terrain.party and used as default testbed for 3 dimensional and continuous environments. Only grounded agents are currently considered.

Fig. 3 :

 3 Fig. 3: Dedale's discrete and continuous default testbeds for real-word environments. Users can easily choose the topology they want to consider for their experiments, either it is generated or based on a real geographical area.

A 3 Fig. 5 :

 35 Fig.5: Interlocking problem : Let 3 agents A 1 ,A 2 and A 3 on a known graph and their communication range set to 2. Node E represents the exit, any agent moving in will transfer its backpack to the tanker. Agents A 1 and A 2 are of gold type, and their backpack capacities are respectively 80 and 10. A 3 is of diamond type and posses a 51 carrying capacity. Each agent's goal is to reach the node possessing their resource type. When picking, 50% of the remaining resources is definitely lost. No prior coordination have been made.

Fig. 6 :

 6 Fig. 6: Migration process : Gk is the local gatekeeper, Gk the distant one.

TABLE I :

 I Multi-agent testbeds facing the 8 fallacies of MAS.

•

  Explorer : It cannot collect, only explore • Tanker : It possesses a nearly unlimited storage capacity, but cannot pick anything • Collector : It possess a backpack specific to a given type of treasure, and a limited carrying capacity. It can pick a treasure, and drop it in the Tanker if the latter is in reach The scenario designer can decide to activate one or several type of agents.

  Additionally, if its a treasure-type scenario, then the following actions are available to the agents : b) Treasures and safes: Type of treasure that the agent can grab (only one type per agent) • getMyExpertise(): Expertise of the agent (strengh and lockpicking) to open safes • openLock(): Open the safe present in the current room if the required expertise is provided. • pick(): Grab all of any of the treasure available on the current position (according to agent type, capacity and safe state) • EmptyMyBackPack(agentTankerName): Allow the agent to transfer its backpack within the Tanker agent in the vicinity (if any).

	• observe() : Returns the set of observables that can
	be perceived from the agent current position as a list of
	couple (position,list(ObservationType,Value))

• moveTo(myDestination) : Makes the agent move to myDestination (if reachable)

• sendMessage(msg) : Send a message and manage the communication radius. It can contain any information. If the recipient is not in range, the message is lost.

• getMyTreasureType():

The network is secure, reliable, instantaneous, with infinite bandwidth, the topology is fixed and homogeneous, communications costs are non-existent.

This was done in order for the users to take into account the scarcity and unreliability of available resources in disaster-like situations

The number of agents that Dedale can manage without slowing down depends on their inner complexity as well as on available processing cores.


domain: chim chim.orga sdv

text:
Nassim Borazjani

Saghi Sepehri

Maryam Behzadi

Aliasghar Jarrahpour
email: jarahpor@shirazu.ac.ir

Javad Ameri Rad

Maryam Sasanipour

Milad Mohkam

Younes Ghasemi

Reza Amin

Carole Akbarizadeh

Digiorgio

Reza Akbarizadeh

Carole Digiorgio

Jean Michel Brunel

Mohammad Mehdi Ghanbari

Gyula Batta

Edward Turos

Three-Component Synthesis of Chromeno β-Lactam Hybrids for Inflammation and Cancer Screening

Keywords: β-Lactams, tetrahydro-4H-chromene, dihydropyrano[c]-chromene, one-pot threecomponent synthesis, DABCO, anti-inflammatory, anticancer, colon cancer, cytotoxicity

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Introduction

In the recent past, our laboratories have pursued research exploring the synthetic combination of several prominent classes of bioactive compounds to create new scaffolds with pharmacological potential. Pharmacophore hybridization has emerged as a paradigm for pharmaceutical chemists. The main motivations for using this strategy are the significant improvement in the therapeutic potential, strength, mode of action and pharmacokinetics [START_REF] Morphy | The physicochemical challenges of designing multiple ligands[END_REF][START_REF] Muregi | Next-generation antimalarial drugs: hybrid molecules as a new strategy in drug design[END_REF][START_REF] Raj | Synthesis and preliminary in vitro activity of mono-and bis-1H-1,2,3-triazole-tethered β-lactamisatin conjugates against the human protozoal pathogen Trichomonas vaginalis[END_REF][START_REF] Meunier | Hybrid molecules with a dual mode of action: dream or reality?[END_REF]. Multicomponent reactions (MCRs) have recently been exploited as a means to synthesize a variety of chemically-hybridized compounds, including those of interest for biological evaluation. Among the synthetic methods utilized for this purpose, single-pot multi-component reactions provide the most efficient routes to the desired products, avoiding the need to isolate and purify intermediate products while improving atom economy and product yields [START_REF] Fareghi-Alamdari | Enhancement of catalytic activity in the synthesis of 2-amino-4H-chromene derivatives using both copper-and cobalt-incorporated magnetic ferrite nanoparticles[END_REF]. Medicinal chemists have further exploited multi-component synthesis in order to construct compounds of pharmaceutical interest, by combining two or more structural subunits units that have their own biological activities. In some cases, these biological activities are complementary to one another or aid in the enrichment of some desired properties, such as antimicrobial activity (bifunctional or even trifunctional prodrugs), or completely orthogonal (such as anticancer with antimicrobial). Recently our laboratories have explored applications of the MCR approach to uncover new chemical structures with intriguing biological properties. In this study, we explore the unique combination of two different classes of bioactive structures, namely fused chromenes and β-lactams (Figure 1). Tetrahydro-4H-chromenes and dihydropyrano[c]-chromenes have diverse pharmacological potential as anti-allergenic, anti-proliferative, antibacterial, antiviral, antifungal, antioxidant, antitumor, and anticancer agents [START_REF] Dos-Santos | New method for the synthesis of chromeno[4,3b]chromene derivatives via multicomponent reaction promoted by niobium pentachloride[END_REF][START_REF] Pratap | Natural and synthetic chromenes, fused chromenes, and versatility of dihydrobenzo[h]chromenes in organic synthesis[END_REF][START_REF] Tanna | Copper nanoparticles catalysed an efficient one-pot multicomponents synthesis of chromenes derivatives and its antibacterial activity[END_REF][START_REF] Sabry | Synthesis of 4Hchromene, coumarin, 12H-chromeno[2,3-d]pyrimidine derivatives and some of their antimicrobial and cytotoxicity activities[END_REF]. Examples include benzopyrans A and B, which possess anticancer activity [START_REF] Banerjee | Design, synthesis and biological evaluation of novel 5H-chromenopyridines as potential anti-cancer agents[END_REF], and compound C, which has antibacterial activity [START_REF] Zhang | One-pot enantioselective synthesis of functionalized pyranocoumarins and 2-amino-4H-chromenes: discovery of a type of potent antibacterial agent[END_REF] (Figure 2). The discovery and clinical development of β-lactam antibiotics remains one of the major advances in modern medicine [START_REF] Ameri Rad | Synthesis of some novel indeno[1,2-b]quinoxalin spiro--lactam conjugates[END_REF]. The commonly used bicyclic β-lactam antibiotics such as the penicillins and cephalosporins prevent bacterial transpeptidases from crosslinking the polysaccharide cell wall [START_REF] Vandekerckhove | Exploration of aziridine and β-lactam-based hybrids as both bioactive substances and synthetic intermediates in medicinal chemistry[END_REF]. More recently, functionalized monocyclic β-lactams have been developed having a host of other pharmaceutical capabilities, such as anti-HIV [START_REF] Sperka | Tozsér, β-Lactam compounds as apparently uncompetitive inhibitors of HIV-1 protease[END_REF], antifungal [START_REF] Jarrahpour | Synthesis of some novel 3-spiro monocyclic β-lactams and their antibacterial and antifungal investigations, Iran[END_REF], anticancer [START_REF] Banik | Asymmetric synthesis of anticancer β-lactams via Staudinger reaction: Utilization of chiral ketene from carbohydrate[END_REF][START_REF] O'boyle | Synthesis and evaluation of azetidinone analogues of combretastatin A-4 as tubulin targeting agents[END_REF] and antimalarial [START_REF] Alborz | Synthesis and biological evaluation of some novel diastereoselective benzothiazole β-lactam conjugates[END_REF] (Figure 3), anti-inflammatory, or analgesic activities [START_REF] Indrani | Microwave-induced synthesis of enantiopure βlactams[END_REF]. Thus, the β-lactam framework presents a rich source of diverse biological properties. In this current study, we set our focus on unique β-lactams 8a-p bearing tetrahydro-4Hchromene and dihydropyrano[c]-chromene pharmacophores, through the development of a singlepot, multi-component coupling strategy (Scheme 1).

Scheme 1: Multi-component synthesis of aldehydic β-lactams 5a-j and chromeno β-lactam hybrids 8a-p.

Results and discussion

Chemistry

In this study, β-lactams 5a-j were synthesized by a diastereoselective ketene-imine cycloaddition reaction (Scheme 1) [START_REF] Alborz | Synthesis and biological evaluation of some novel diastereoselective benzothiazole β-lactam conjugates[END_REF][START_REF] Borazjani | Design, synthesis and biological evaluation of some novel diastereoselective β-lactams bearing 2-mercaptobenzothiazole and benzoquinoline[END_REF]. The reaction of 4-hydroxybenzaldehyde (1) with bromoacetic acid (2) in DMF at 70 o C in the presence of solid K2CO3 afforded 2-(4formylphenoxy)acetic acid [START_REF] Raj | Synthesis and preliminary in vitro activity of mono-and bis-1H-1,2,3-triazole-tethered β-lactamisatin conjugates against the human protozoal pathogen Trichomonas vaginalis[END_REF]. Treatment of 3 with Schiff bases 4a-j in the presence of equimolar amounts of triethylamine and p-toluenesulfonyl chloride produced the cis-β-lactams 5a-j in isolated yields varying from 68-80% after column chromatography. Structures were established on the basis of their IR, 1 H NMR, 13 C NMR spectral data and elemental analysis (see supplementary material). The IR spectra of 5b showed absorption band at υ 1759 cm -1 for the βlactam carbonyl group and absorption band at υ 1689 cm -1 for the aldehyde carbonyl group. Compound 5b showed doublets at δ 5.79 ppm and δ 6.03 ppm for the H-2 and H-3 β-lactam ring protons. The aldehydic hydrogen resonated as a singlet at δ 9.81 ppm. The 13 C NMR spectral data for compound 5b exhibited signals at δ 60.9 and δ 80.4 ppm for the C-2 and C-3 β-lactam ring protons, respectively, the aromatic carbons at appropriate shifts, the β-lactam carbonyl carbon at δ 161.4 ppm and the aldehyde carbonyl carbon at δ 190.5 ppm. The cis stereochemistry was confirmed from the vicinal coupling constants of the two β-lactam ring protons, H-2 and H-3 (J2,3 ≥4.0 Hz) [START_REF] Alborz | Synthesis and biological evaluation of some novel diastereoselective benzothiazole β-lactam conjugates[END_REF]. X-Ray single crystal analysis done on β-lactam 5b confirmed the cis stereochemistry (Fig. 3). Crystallographic data, details of the data collection and structure refinement can be found in the supplementary material [START_REF] Baghernejad | 1,4-Diazabicyclo[2.2.2octane (DABCO) as a useful catalyst in organic synthesis[END_REF]. From aldehydic β-lactams 5, we further developed an expedient multi-component approach for constructing chromeno β-lactam hybrids 8 (Scheme 2). To optimize the reaction conditions, β-lactam 5a was stirred in ethanol with equimolar amounts of malononitrile (6) and 5,5-dimethylcyclohexane-1,3-dione (7a) in the presence of different amine base catalysts (Table 1). A higher yield and shorter reaction time were observed when the reaction was carried out in the presence of a molar equivalent of 1,4-diazabicyclo[2.2.2]octane (DABCO) under reflux conditions (entry 6) [START_REF] Wu | DABCO: An efficient organocatalyst in the ring-opening reactions of aziridines with amines or thiols[END_REF][START_REF] Razzaghi-Asl | Identification of COX-2 inhibitors via structure-based virtual screening and molecular dynamics simulation[END_REF].

Table 1. Effects of reagent and solvent on the reaction of β-lactam 5a, malononitrile (6) and 5,5dimethylcyclohexane-1,3-dione (7a) under different reaction conditions. Subsequently, these optimized reaction conditions were used for the condensations of β-lactams 5a-j (Table 2). The cycloadducts were characterized by spectral analysis. The IR spectra of 8b showed the NH2 stretching vibration at 3386 and 3325 cm -1 , the CN stretching at 2198 cm -1 , and the β-lactam carbonyl at 1743 cm -1 . We also noted the absence of the aldehyde carbonyl group at 1689 cm -1 , and the appearance of a sharp band at 1666 cm -1 for the vinylogous carbonyl (ketone or lactone). The 1 H NMR spectrum for 8b showed a signal at δ 4.07 [1H, s, CH-4], doublets at δ 5.69 [1H, d, J = 5.0 Hz, H-2 of β-lactam] and δ 5.82 [1H, d, J = 5 Hz, H-3 of β-lactam] and NH2 protons in the aromatic region. These NH2 protons were deuterium-exchanged with D2O and the integration of 4Hs in the region of δ 6.88-6.95 (m, ArH, NH2) decreased to 2H, producing a sharp doublet at δ 6.94 (J = 10.0 Hz). The 13 C NMR spectral data for compound 8b exhibited aliphatic carbons and aromatic carbons at appropriate shifts, and the ketone carbonyl carbon at δ 195.9.

Entry

Anti-inflammatory activity assay

Inflammation contributes to the degenerative processes of host of human ailments and diseases, such as cancer, arthritis, atherosclerosis, autoimmune diseases and aging of skin and other tissues and organs. Treatment with anti-inflammatory compounds may reduce the severity of inflammation. Non-steroidal anti-inflammatory drugs (NSAIDs) are the most popular pharmaceutical agents for the treatment of chronic inflammatory diseases, pain and fever that exert their therapeutic effect via blockade of cyclooxygenase isoenzymes (arachidonic acid pathway) to prevent the production of prostaglandins and other inflammatory mediators [START_REF] Razzaghi-Asl | Identification of COX-2 inhibitors via structure-based virtual screening and molecular dynamics simulation[END_REF]. Nitric oxide (NO) plays significant roles in the pathophysiology of inflammatory illnesses. It gives an antiinflammatory effect under normal physiological conditions. NO is synthesized and released into the endothelial cells by the help of nitric oxide synthases that convert arginine into citrulline producing NO in the process. Also, NO is considered as a pro-inflammatory mediator that induces inflammation because of over production in abnormal situations. Therefore, NO inhibitors represent important therapeutic advance in the management of inflammatory diseases [START_REF] Sharma | Role of nitric oxide in inflammatory diseases[END_REF]. In order to identify new anti-inflammatory candidates, the RAW 264.7 murine macrophage assay was used to examine anti-inflammatory behavior of the new β-lactam hybrids we synthesized. This assay monitors the inflammatory cascade leading to an overproduction of NO in the endothelial lining of blood vessels. In the present study, it was performed to evaluate the capacity of the compounds to inhibit the pro-inflammatory cascade leading to NO production in mouse macrophages. Results are reported in Table 3. Compound 8b was the most active of all the chromeno β-lactam hybrids tested, with a 19.8 anti-inflammatory ratio. For comparison, we also checked anti-inflammatory activity for the aldehydic β-lactams 5a-j (Table 4). As observed for lactam 8b, the p-tolyl group on N-1 of the β-lactam ring of 5b enhances anti-inflammatory activity in this assay, more active than the corticosteroid drug, dexamethasone.

Anticancer activity and cytotoxicity assays

In vitro cytotoxicity and anti-cancer activity were also evaluated for each of the compounds synthesized. Three of the chromeno β-lactam hybrid compounds (8c, 8j and 8p) showed elevated anti-cancer activity against the SW 1116 (colon cancer) cell lines, with IC50 values of 7.29, 8.83, and 7.43 µM, respectively, in comparison to the anticancer agent methotrexate (IC50 of 2.49 µM). The remainder of the lactams 8 afford no anticancer activity at or below 200 μM. Since all of these lactams carry a tetrahydro-4H-chromene or dihydropyrano[c]-chromene group on C-3 of the βlactam ring, the aryl substituents at N-1 and C-2 of the β-lactam ring are responsible for these differences in activity. A tentative structure-activity relationship exists, in that the presence of a pnitrophenyl or p-chlorophenyl group on C-2 of the β-lactam ring and a p-methoxyphenyl, p-tolyl, p-ethoxyphenyl or p-N,N-dimethylaminophenyl ring on N-1 of the β-lactam provide the best anticancer bioactivity. Additionally, five of the aldehydic β-lactams (5a, 5b, 5e, 5f and 5g) possess comparable IC50 values. IC50 values are 10.26, 10.00, 6.71, 8.19, and 6.93 μM, respectively. Conversely, none of the lactams (5a-j or 8a-p) have cytotoxicity against HepG2 cells, with IC50 concentrations not being found at or below 200 μM.

Molecular docking studies

Validation of molecular docking

The performance of a common computational docking technique can be tested by checking its power to foresee the most significant binding mode of a cognate (co-crystallographic) ligand [41]. This method was carried out by eliminating the structure of a cognate ligand and re-docking it into its protein (self-docking). Root-mean-square deviation (RMSD) of the Cartesian coordinates of the atoms of the ligand in the docked and crystallographic conformations is the principle of the docking validation (RMSD < 2 Å). Validation of molecular docking showed RMSD values were for PDB ID: 4NOS = 0.4 Å and for PDB ID: 3LN1 = 0.01 Å (Supplementary Information).

Study of the binding mode

Molecular docking experiments suggest that chromeno β-lactams 8a-p may bind to human inducible nitric oxide synthase protein via hydrogen bond and hydrophobic interactions with specific active site amino acid residues. Members of this group exhibit weak to good (in the case of 8b) in vitro anti-inflammatory activity, such that higher lipophilicity enhances these particular hydrophobic interactions. Indeed, 8b exhibited the best docking score from the computational studies, coinciding with the most potent in vitro anti-inflammatory activity. Interactions of 8b with the enzyme active site are depicted in Figure 4. The carbonyl and 4-oxyphenyl oxygen atoms interact through hydrogen bonds with Arg381 (O…NH, 1.96 Å and O…NH, 1.98 Å). Also the amine nitrogen atom of the C-2 chromeno moiety is involved in a hydrogen bond with Asp382 amino acid (NH…O, 1.96 Å). Compound 8b was found to also interact with a hydrophobic surface formed by Gln263, Val352, Glu377, Arg388, Trp463, Met120, Pro467, Ile462, Pro466 and Val465 residues. Replacement of the p-chlorophenyl group at C-4 position of the lactam ring in 8e with a pnitrophenyl in 8f substantially decreased the in vitro activity. The calculated CLogP value for 8e (6.75) indicates that it is somewhat more lipophilic than 8f (CLogP = 5.78) and can thus experience stronger interactions with hydrophobic amino acids, accounting for its better antiinflammatory activity and free binding energy (Table 4, in Supplementary Information).

Replacing the p-(N,N-dimethylamino)phenyl ring of 8h with an anthracene moiety at the C-4 position (8i) decreased the in vitro activity. The lower anti-inflammatory activity of 8i can be attributed to steric hindrance and a change in the orientation of compound 8i in the active site, which weakens the intermolecular interactions.

The higher lipophilicity of compound 8m (CLogP = 6.51) compared with 8g (CLogP = 5.50) likely diminishes cell membrane permeability, causing lower anti-inflammatory activity.

Dexamethasone was likewise computationally docked into the protein and showed a very similar binding mode to the β-lactams, forming hydrogen bonds and hydrophobic interactions with (Figure 5). For comparison, we also examined the docking of aldehydic β-lactams 5 into the human inducible nitric oxide synthase active site. Compounds 5b and 5e gave the best docking scores (Table 4, in supporting information) that correspond with their strong anti-inflammatory activity (Table 2). The carbonyl oxygen atom of lactam ring of 5b formed a hydrogen bond interaction with NH of Gln263 (O…HN, 1.84 Å). Moreover, 5e formed two hydrogen bonds with amino acid active sites. The carbonyl oxygen atom of lactam ring displayed a hydrogen bond with OH group of Tyr373 (O…HO, 2.59 Å) and the carbonyl oxygen atom of aldehyde showed a hydrogen bond with NH group of Arg388 (O…HN, 2.18 Å). The binding mode of compounds 5b and 5e to the human inducible nitric oxide synthase active site is revealed in Figure 6 The three aryl rings of 5b were located within the hydrophobic pocket enclosed by Ala351, Asp382, Arg381, Glu377, Tyr373, Pro350, Ala262, Val352, Met355 and Asn354. Exposed residues Arg266, Arg388, Ala262, Val352, Gln263, Pro350, Gly371, Asn370, Glu377 and Phe369 also formed hydrophobic interactions with 5e. Our docking calculations revealed that 5e forms a cation-π interaction with the Arg266 residue. All these interactions help anchor 5b and 5e in the binding site of the human inducible nitric oxide synthase protein. In addition, anti-inflammatory activity of 5b was higher than that of the clinically-used anti-inflammatory agent, dexamethasone (IC50-NO release = 5.02 μM).

Replacing the 4-chlorophenyl ring (5e) with the 4-nitrophenyl ring (5f) and 4-(N,Ndimethylamino)phenyl ring (5h) decreased the anti-inflammatory activity. The increased polarization and strong electron-donating characters reduced the potency of compounds but addition of hydrophobic groups had a positive effect. Also, docking results exposed that compounds 5e and 5f formed a cation-π and π-π stacking interactions with Arg266 and Tyr491 amino acids, respectively. While compound 5h did not participate in these contacts (Figure 7). A methoxy or methyl group at the para position of the aryl ring induced different conformations, leading to a change in interactions with the hydrophobic pocket of the protein. This suggests this is the reason for compound 5b showing higher anti-inflammatory activity and ΔGbind value than compound 5a. In addition, the carbonyl oxygen atom of lactam ring of 5b formed a hydrogen bond interaction with NH of Gln263 (O…HN, 1.84 Å), whereas 5a did not have this interaction. The superimposition of 5a and 5b in the enzyme binding site is illustrated in Figure 8. Compound 5a, having a methoxy group at the para position of the aryl ring, showed lower inhibitory activity than compound 5e that has an ethoxy group at the same position (Table 2). The lower anti-inflammatory activity of 5a can be attributed to the improper geometric orientation in the active site of enzyme. Also, compound 5e shows two hydrogen bonds with Arg388 and Tyr373 residues and a cation-π stacking interaction with Arg266, while compound 5a did not have these interactions (Figure 9). Our docking calculations indicate that 5e has stronger interactions than 5a with active site amino acids, accounting for its elevated anti-inflammatory activity. It is also interesting to compare β-lactam 5e with 5i. While 5e has a p-chlorophenyl ring at the C-2 position of lactam ring, 5i has a bulkier anthracene moiety (Figure 10). The computational modeling suggest that steric differences between these two aryl groups, along with the differences in the calculated ΔGbind values for lactams 5e and 5i, may account for the different antiinflammatory potencies. Moreover, lactam 5e is less hydrophobic than compound 5i (CLogP = 5.82 for 5e vs. CLogP = 7.45 for 5i) and may have reduced permeability through the cell membrane. Replacing the N-aryl ethoxy substituent (5f) with an N,N-dimethylamino (5g) increased antiinflammatory activity, suggesting that increased electron-donation into the N-aryl ring improves potency. This is corroborated by computational docking experiments showing that while compound 5f forms looser hydrogen bonds with Tyr373 and Arg388, compound 5g forms a tighter hydrogen bond to the Cys110 residue in the enzyme binding pocket.

Conclusion

This article describes the first diastereoselective synthesis of chromeno-substituted β-lactams. The compounds were accessed by an expedient single-pot three-component synthesis approach, to give exclusively the cis-disubstituted adducts. The series of chromeno β-lactam hybrids 8a-p, as well as their aldehydic precursors 5a-j, were evaluated for anti-inflammatory activity. The best anti-inflammatory activity was observed for compounds 5b and 8b (53.4 and 19.8 antiinflammatory ratio, respectively). Moreover, based on the results of anti-inflammatory activity and molecular docking calculations of the synthesized compounds, the anti-inflammatory activity is closely dependent on the substituents at the N1 and C-2 centers of the lactam ring. Chromeno lactams 8c, 8j and 8p, as well as aldehydic lactams 5a, 5b, 5e, 5f, 5g, display in vitro anticancer activity against the SW 1116 colon cancer cell line, without noticeable cytotoxicity towards healthy cells. Studies are now underway to improve the biological activity and determine the mechanism of action.

Figure 1 :

 1 Figure 1: Generalized structure of a fused chromene-β-lactam hybrid.

Figure 2 :

 2 Figure 2: Structures of biologically-active fused chromenes.

Figure 3 :

 3 Figure 3: Structures of some biologically active monocyclic β-lactam derivatives.

Figure 3 :

 3 Figure 3: ORTEP diagram of β-lactam 5b.

Scheme 2 :

 2 Scheme 2: Multi-component synthesis of chromeno β-lactam hybrids 8a-p.

a

  Isolated yields.

Figure 4 :

 4 Figure 4: Compound 8b in the human inducible nitric oxide synthase active site. The 3D (left) and 2D (right) ligand interaction diagrams.

Figure 5 :

 5 Figure 5: Hydrogen bonds and hydrophobic interactions of dexamethasone within the human inducible nitric oxide synthase active site.

Figure 6 :

 6 Figure 6: Binding modes of compound 5b (A) and 5e (B) with human inducible nitric oxide synthase active site (PDB ID: 4NOS).

Figure 7 :

 7 Figure 7: Close up of the calculated binding of 5e (A) and 5f (B) within the human inducible nitric oxide synthase enzyme active site.

Figure 8 :

 8 Figure 8: Superimposition of 5a (violet) and 5b (green) within the enzyme binding site.

Figure 9 :

 9 Figure 9: Calculated binding modes of compound 5a (A) and 5e (B) within the human inducible nitric oxide synthase active site (PDB ID: 4NOS).

Figure 10 :

 10 Figure 10: Calculated binding mode of compound 5e (A) and 5i (B) within the human inducible nitric oxide synthase active site (PDB ID: 4NOS

Table 2 .

 2 Isolated yields of chromeno β-lactam hybrids 8 under the optimized reaction conditions.

	Cpd	R	Ar	Time	Yield	Cpd	R	Ar	Time	Yield
				(h)	(%)				(h)	(%)
	8a	4-OMe	4-ClPh	1.5	95	8i	4-OEt	Anthracene	1.5	92
	8b	4-Me	4-ClPh	2.5	90	8j	4-OMe	Anthracene	1.5	90
	8c	4-Cl	3-NO2Ph	2.2	92	8k	4-OEt	4-ClPh	3.0	85
	8d	4-OMe	3-NO2Ph	3.5	80	8l	4-OMe	4-ClPh	2.6	92
	8e	4-OEt	4-ClPh	2.5	94	8m	4-N(Me)2	4-NO2Ph	4.0	82
	8f	4-OEt	4-NO2Ph	1.6	95	8n	4-OEt	4-N(Me)2Ph	3.8	90
	8g	4-N(Me)2	4-NO2Ph	3.2	85	8o	4-OEt	Anthracene	1.8	95
	8h	4-OEt	4-N(Me)2Ph	3.0	90	8p	4-OMe	Anthracene	2.0	90

Table 3 .

 3 Anti-inflammatory activity of chromeno β-lactam hybrids 8a-p.

		IC50-NO release	IC50-cell viability	Anti-
	Sample	Sample (µM)	Sample (µM)	inflammatory
				ratio
	8a	ND	ND	ND
	8b	6.24 + 1.28	123.47 + 13.24	19.8
	8c	53.41 + 5.13	124.21 + 8.23	2.3
	8d	100.02 + 6.21	114.31 + 10.31	1.1
	8e	73.36 + 7.94	201.45 + 11.56	2.7
	8f	89.42 + 6.81	124.31 + 11.39	1.4
	8g	60.08 + 5.24	251.48 + 8.37	4.1
	8h	38.10 + 4.31	146.25 + 7.23	3.8
	8i	101.65 + 23.24	165.23 + 10.87	1.6
	8j	56.41 + 5.64	134.63 + 8.24	2.4
	8k	ND	ND	ND
	8l	89.56 + 3.81	124.31 + 8.33	1.4
	8m	161.36 + 21.54	163.24 + 11.42	1.0
	8n	ND	ND	ND
	8o	168.23 + 11.41	224.34 + 11.84	1.3
	8p	164.57 + 8.84	198.56 + 12.09	1.2
	Dexamethasone	5.02 + 1.34 µM	159.2 + 26.35 µM	31.9
	ND : Not determined due to poor solubility

Table 4 .

 4 Anti-inflammatory activity of derivatives 5a-j.

		IC50-NO release	IC50-cell viability	Anti-
	Sample	Sample (µM	Sample (µM	inflammatory
				ratio
	5a	92.42 + 6.81	131.31 + 9.39	1.4
	5b	2.31 +0.56	123.78 + 7.49	53.4
	5c	63.65 + 4.07	132.48 + 6.37	2.1
	5d	2.91 + 0.84	4.15 + 1.66	1.4
	5e	11.32 + 0.89	56.28 + 6.31	4.9

Acknowledgements

The authors would like to thank the Shiraz University Research Council for financial support (Grant No. 97-GR-SC-23) and Dr. Attila Benyei for collecting X-ray data.

Conflict of interest

The authors declare that they have no conflict of interest. Electronic Supplementary Information (ESI) available: Spectra for new compounds (IR, 1 H NMR, 13 C NMR spectral data), elemental analysis, molecular docking studies data, crystallographic data and structure determination and General experimental methods.


Aaron Millan-Oropeza

Celine C Henry

Clara Lejeune

Michelle David

Marie-Jöelle Virolle

S Lividans

S Coelicolor

M.-J Virolle

Anti-correlation between the ability to produce antibiotics and that to accumulate storage lipids of the TriAcylGlycerol family in

A proteomic approach revealed the nature and the cause of the different metabolic features of weak and strong antibiotic producers of the Streptomyces genus.

Introduction Bibliography

.

Results

A proteomic approach revealed the nature and the cause of the different metabolic features of weak and strong antibiotic producers of the Streptomyces genus.

Streptomycetes are efficient producers of chemically diverse bio-active molecules useful to human health including life-saving antibiotics. The biosynthesis of these metabolites usually occurs in the period of slow or no growth and is thought to be triggered by nutritional limitations, especially in phosphate, that are correlating with energy shortage. Despites numerous important scientific contributions over the past 40 years, a systemic understanding of the complex regulation of the biosynthesis and of the function of these bio-active metabolites for the producing bacteria remains incomplete. The model strains, Streptomyces lividans (SL) and Streptomyces coelicolor (SC), are extensively studied by the scientific community to address these questions. These closely related species possess identical biosynthetic pathways directing the synthesis of three well characterized secondary metabolites (CDA, RED and ACT) but only S. coelicolor expresses them at a high level. A comparative proteomic analysis of these strains, grown on phosphate limited R2YE medium, with glucose as main carbon source, was carried out in order to establish the specific metabolic features linked to weak (SL) and strong (SC) antibiotic production. A possible cause of such differences and a novel view of the function of the antibiotics for the producing bacteria in the specific context of their production was inferred from this study.

B

Conclusions

We demonstrated that the ability of S. lividans and S. coelicolor to produce antibiotics was anti-correlated with their ability to accumulate TAG (2, 3) and that the expression of the two component system PhoR/PhoP was low in S. coelicolor. This led to a severe Pi limitation and thus energy shortage that the strain tries to compensates by activating its oxidative metabolism.

The activation of the oxydative metabolism requires the feeding of the Krebs cycle by acetylCoA resulting into the very low TAG content of this strain. TAG and antibiotics biosynthesis thus compete for common precursors, acetylCoA or its derivatives. This is true for thebiosynthesis of polyketide antibiotics (ACT) that are directly using acetylCoA or malonylCoA as precursors but that is also true for that of peptidic antibiotics (CDAand RED) that are synthesised from amino acids, often derived from intermediates of the Krebs cycle. Furthermore, we proposed thta the produced antibiotics are playing important roles in the regulation of the energetic metabolism of the bacteria in condition of phosphate scarcity. For instance, CDA and RED, produced before ACT, are thought to promote cell death and lysis of a fraction of the population, via membrane damages, to feed and especially provide phosphate to the surviving one (7). The provided phosphate would allow the temporary activation of the oxidative metabolism of the strain to re-establish its energy balance. However when phosphate is exhausted, oxydative phosphorylation has to be stopped and ACT was proposed to fulfill such function.

The two component system PhoR/PhoP is know to regulate positively phosphate (Pi) scavenging and uptake and negatively nitrogen (N) assimilation (1). The weak expression of PhoR/PhoP in SC and thus the toning down of its regulatory role was correlated with low abundance of proteins involved in Pi scavenging and uptake leading to severe Pi limitation as well as with high N availability. High N availability is likely to be responsible for the inhibition of TAG biosynthesis in S. coelicolor as in most micro-organisms and thus for the low TAG content of this strain (2, 3). Inhibition of TAG biosynthesis is predicted to lead to high acetylCoA availability, that together with high N availability, would fuel the Krebs cycle to support the oxidative metabolism characteristic of this strain (2). The noticed up-regulation of enzymes generating reduced co-factors belonging to the Krebs cycle or to amino acid degradative pathways in SC is consistent with the previously reported high ATP content of this strain (2).

The activation of the oxidative metabolism in S. coelicolor is seen as an attempt to restore its energy balance . To do so most of the acetylCoA, generated by glycolysis or amino acids degradation, is used to feed the Krebs cycle rather than being stored as TAG.

Figure 1 :

 1 Figure 1: Heatmap representation of proteins of the Pho regulon belonging to phosphate metabolism with significant abundance change (ANOVA, adjusted p value < 0.01) between S. coelicolor and S. lividans grown on R2YE medium limited in phosphate (1mM) with either glucose or glycerol as main carbon source, for 36, 48 and 72 h at 28°C. The quantification methods are displayed in the vertical bar indicating those proteins quantified by SC (orange) or XIC (black).

Figure 2 :

 2 Figure 2: Cultures of S. lividans, its ppk mutant (3, 5, 6) and S. coelicolor grown on R2YE glucose limited in phosphate (1mM). Estimation of growth (continuous lines, mg of dry biomass per plate) of S. lividans (black circles), its ppk mutant (grey circles) and S. coelicolor (white circles), and evolution of the levels of ACT produced extracellularly and intracellularly by the ppk mutant of S. lividans (grey and grey hatched histograms, respectively) and S. coelicolor (plain white and hatched histograms, respectively) (A). Quantification of intracellular ATP levels in S. lividans (black circles), its ppk mutant (grey circles) and S. coelicolor (open circles). The error bars represent the standard deviation of at least three independent experiments. (2)