Efficient exploration of molecular paths from As-Rigid-As-Possible approaches and motion planning methods

Minh Khoa Nguyen 1, 2
2 NANO-D - Algorithms for Modeling and Simulation of Nanosystems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : Proteins are macromolecules participating in important biophysical processes of living organisms. It has been shown that changes in protein structures can lead to changes in their functions and are found linked to some diseases such as those related to neurodegenerative processes. Hence, an understanding of their structures and interactions with other molecules such as ligands is of major concern for the scientific community and the medical industry for inventing and assessing new drugs.In this dissertation, we are particularly interested in developing new methods to find for a system made of a single protein or a protein and a ligand, the pathways that allow changing from one state to another. During past decade, a vast amount of computational methods has been proposed to address this problem. However, these methods still have to face two challenges: the high dimensionality of the representation space, associated to the large number of atoms in these systems, and the complexity of the interactions between these atoms.This dissertation proposes two novel methods to efficiently find relevant pathways for such biomolecular systems. The methods are fast and their solutions can be used, analyzed or improved with more specialized methods. The first proposed method generates interpolation pathways for biomolecular systems using the As-Rigid-As-Possible (ARAP) principle from Computer Graphics. The method is robust and the generated solutions preserve at best the local rigidity of the original system. An energy-based extension of the method is also proposed, which significantly improves the solution paths. However, in scenarios requiring complex deformations, this geometric approach may still generate unnatural paths. Therefore, we propose a second method called ART-RRT, which combines the ARAP principle for reducing the dimensionality, with the Rapidly-exploring Random Trees from Robotics for efficiently exploring possible pathways. This method not only gives a variety of pathways in reasonable time but the pathways are also low-energy and clash-free, with the local rigidity preserved as much as possible. The mono-directional and bi-directional versions of the ART-RRT method were applied for finding ligand-unbinding and protein conformational transition pathways, respectively. The results are found to be in good agreement with experimental data and other state-of-the-art solutions.
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Minh Khoa Nguyen. Efficient exploration of molecular paths from As-Rigid-As-Possible approaches and motion planning methods. Bioinformatics [q-bio.QM]. Université Grenoble Alpes, 2018. English. ⟨NNT : 2018GREAM013⟩. ⟨tel-01978418v2⟩

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