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5 results on '"Kevin Molloy"'

1. Combining System Design and Path Planning

Author

Thierry Simeon, Juan Cortés, Laurent Denarie, Kevin Molloy, Marc Vaisset, Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Service Informatique : Développement, Exploitation et Assistance (LAAS-IDEA), Goldberg K., Abbeel P., Bekris K., Miller L., Springer, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
0209 industrial biotechnology, Mathematical optimization, Computer science, 0102 computer and information sciences, 02 engineering and technology, robot motion planning, 01 natural sciences, Any-angle path planning, 020901 industrial engineering & automation, computational biology, Simple (abstract algebra), [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Motion planning, [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biochemistry [q-bio.BM], protein design, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], business.industry, Sampling (statistics), sampling-based algorithms, Robotics, 010201 computation theory & mathematics, Path (graph theory), Systems design, Artificial intelligence, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business, Combinatorial explosion
Abstract

International audience; This paper addresses the simultaneous design and path planning problem, in which features associated to the bodies of a mobile system have to be selected to find the best design that optimizes its motion between two given configurations. Solving individual path planning problems for all possible designs and selecting the best result would be a straightforward approach for very simple cases. We propose a more efficient approach that combines discrete (design) and continuous (path) optimization in a single stage. It builds on an extension of a sampling-based algorithm, which simultaneously explores the configuration-space costmap of all possible designs aiming to find the best path-design pair. The algorithm filters out unsuitable designs during the path search, which breaks down the combinatorial explosion. Illustrative results are presented for relatively simple (academic) examples. While our work is currently motivated by problems in computational biology, several applications in robotics can also be envisioned.

Published
2020

2. A Reinforcement-Learning-Based Approach to Enhance Exhaustive Protein Loop Sampling

Author

Juan Cortés, Marc Vaisset, Thierry Simeon, Amélie Barozet, Kevin Molloy, Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Service Informatique : Développement, Exploitation et Assistance (LAAS-IDEA), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
Models, Molecular, Statistics and Probability, Loop (graph theory), Molecular model, Protein Conformation, Computer science, 01 natural sciences, Biochemistry, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 03 medical and health sciences, 0103 physical sciences, Reinforcement learning, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Representation (mathematics), Molecular Biology, 030304 developmental biology, Flexibility (engineering), chemistry.chemical_classification, 0303 health sciences, 010304 chemical physics, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], Biomolecule, Proteins, Sampling (statistics), Solver, Computer Science Applications, Computational Mathematics, Computational Theory and Mathematics, chemistry, Benchmark (computing), [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Algorithm, Algorithms, Software
Abstract

Motivation Loop portions in proteins are involved in many molecular interaction processes. They often exhibit a high degree of flexibility, which can be essential for their function. However, molecular modeling approaches usually represent loops using a single conformation. Although this conformation may correspond to a (meta-)stable state, it does not always provide a realistic representation. Results In this paper, we propose a method to exhaustively sample the conformational space of protein loops. It exploits structural information encoded in a large library of three-residue fragments, and enforces loop-closure using a closed-form inverse kinematics solver. A novel reinforcement-learning-based approach is applied to accelerate sampling while preserving diversity. The performance of our method is showcased on benchmark datasets involving 9-, 12- and 15-residue loops. In addition, more detailed results presented for streptavidin illustrate the ability of the method to exhaustively sample the conformational space of loops presenting several meta-stable conformations. Availability and implementation We are developing a software package called MoMA (for Molecular Motion Algorithms), which includes modeling tools and algorithms to sample conformations and transition paths of biomolecules, including the application described in this work. The binaries can be provided upon request and a web application will also be implemented in the short future. Supplementary information Supplementary data are available at Bioinformatics online.

Published
2020

3. Hybrid parallelization of a multi-tree path search algorithm: Application to highly-flexible biomolecules

Author

Juan Cortés, Alejandro Estaña, Pau Bernadó, Marc Vaisset, Kevin Molloy, Thierry Simeon, Nathalie Sibille, Centre de Biochimie Structurale [Montpellier] (CBS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J), Service Informatique : Développement, Exploitation et Assistance (LAAS-IDEA), Unité de Glycobiologie Structurale et Fonctionnelle UMR 8576 (UGSF), Institut National de la Recherche Agronomique (INRA)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Unité de Glycobiologie Structurale et Fonctionnelle - UMR 8576 (UGSF), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Cortés, Juan, Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse Capitole (UT Capitole), Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), and Université de Lille-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, 0209 industrial biotechnology, Speedup, [SDV.BBM.BS] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], Computer Networks and Communications, Computer science, Computation, Parallel algorithm, 02 engineering and technology, Parallel computing, Intrinsically disordered proteins, Hybrid parallelization, Theoretical Computer Science, Path planning algorithms, 03 medical and health sciences, 020901 industrial engineering & automation, Artificial Intelligence, Computer cluster, Random tree, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Intrinsically Disordered Proteins (IDPs), [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO], Computer Graphics and Computer-Aided Design, [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biomolecules [q-bio.BM], Range (mathematics), Tree (data structure), 030104 developmental biology, Hardware and Architecture, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Molecular energy landscape exploration, Algorithm, High Performance Computing (HPC), Software
Abstract

International audience; The study of the conformational energy landscape of a molecule is essential for the understanding of its physicochemical properties. This requires the exploration of a continuous, high-dimensional space to identify the most probable conformations and the transition paths between them. The problem is computationally difficult, in particular for highly-flexible biomolecules such as Intrinsically Disordered Proteins (IDPs). In recent years, a robotics-inspired algorithm called Transition-based Rapidly-exploring Random Tree (TRRT) has been proposed to solve this problem, and has been shown to provide good results with small and middle-sized biomolecules. Aiming to treat larger systems, we propose a hybrid strategy for the efficient parallelization of a multi-tree variant of TRRT, called Multi-TRRT, enabling an efficient execution in (possibly large) computer clusters. The parallel algorithm uses OpenMP multi-threading for computation inside each multi-core processor and MPI to perform the communication between processors. Results show a near-linear speedup for a wide range of cluster configurations. Although the paper mainly deals with the application of the proposed parallel algorithm to the investigation of biomolecules, the explanations concerning the methods are general, aiming to inspire future work on the parallelization of related algorithms.

Published
2018

4. A Reinforcement Learning Approach to Protein Loop Modeling

Author

Kevin Molloy, Nicolas Buhours, Marc Vaisset, Thierry Siméon, Étienne Ferré, Juan Cortés, Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Siemens Industry Software SAS [Roanne], Service Informatique : Développement, Exploitation et Assistance (LAAS-IDEA), ANR-12-MONU-0015,ProtiCAD,Modèles multi-physiques et algorithmes robotiques pour la conception assistée par ordinateur de protéines(2012), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
[SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], conformational search, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], loop closure, robotic motion planning
Abstract

International audience; Modeling the loop regions of proteins is an active area of research due to their significance in defining how the protein interacts with other molecular partners. The high structural flexibility of loops presents formidable challenges for both experimental and computational approaches. In this work, we combine a robotics approach with reinforcement learning (RL) to compute an ensemble of loop configurations. We are actively performing experiments on well known benchmark sets to illustrate how RL improves the efficiency and effectiveness of our approach.

Published
2015

5. Characterizing Energy Landscapes of Peptides using a Combination of Stochastic Algorithms

Author

Didier Devaurs, Amarda Shehu, Juan Cortés, Marc Vaisset, Kevin Molloy, Thierry Simeon, Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, University of Toulouse, Service Informatique : Développement, Exploitation et Assistance (LAAS-IDEA), Department of Computer Science [Fairfax] (Volgenau School of Engineering), George Mason University [Fairfax], Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
Mathematical optimization, Computer science, Biomedical Engineering, Pharmaceutical Science, Medicine (miscellaneous), Bioengineering, 01 natural sciences, 03 medical and health sciences, stochastic algorithms, 0103 physical sciences, Random tree, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], [INFO]Computer Science [cs], Electrical and Electronic Engineering, Cluster analysis, 030304 developmental biology, Flexibility (engineering), Stochastic Processes, 0303 health sciences, Quantitative Biology::Biomolecules, 010304 chemical physics, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], energy landscape, Computational Biology, Sampling (statistics), Energy landscape, Models, Theoretical, Computer Science Applications, [CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry, Path (graph theory), peptides, Thermodynamics, Minification, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Biological system, Algorithms, Energy (signal processing), Biotechnology
Abstract

International audience; Obtaining accurate representations of energy landscapes of biomolecules such as proteins and peptides is central to the study of their physicochemical properties and biological functions. Peptides are particularly interesting, as they exploit structural flexibility to modulate their biological function. Despite their small size, peptide modeling remains challenging due to the complexity of the energy landscape of such highly-flexible dynamic systems. Currently, only stochastic sampling-based methods can efficiently explore the conformational space of a peptide. In this paper, we suggest to combine two such methods to obtain a full characterization of energy landscapes of small yet flexible peptides. First, we propose a simplified version of the classical Basin Hopping algorithm to reveal low-energy regions in the landscape, and thus to identify the corresponding meta-stable structural states of a peptide. Then, we present several variants of a robotics-inspired algorithm, the Transition-based Rapidly-exploring Random Tree, to quickly determine transition path ensembles, as well as transition probabilities between meta-stable states. We demonstrate this combined approach on met-enkephalin.

Published
2015

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