Geometric algorithms for the conformational analysis of long protein loops

Cortés, Juan; Siméon, Thierry; Remaud‐Siméon, Magali; Tran, V.H.

doi:10.1002/jcc.20021

Cited by 87 publications

(93 citation statements)

References 53 publications

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“…Recent works show that algorithms originating from robotics can be the basis for the development of efficient conformational sampling and exploration methods in computational biochemistry. For instance, methods based on robotics algorithms have been proposed to analyze protein loop mobility [29,30], to compute large-amplitude conformational transitions in proteins [31,32], to investigate protein and RNA folding pathways [33,34], or to simulate ligand diffusion inside proteins considering flexible molecular models [35,36]. The present work proposes a conformational exploration method, called Transition-RRT (T-RRT) [37], which is inspired by robotic path planning algorithms and by methods in statistical physics.…”

Section: Introductionmentioning

confidence: 99%

Randomized tree construction algorithm to explore energy landscapes

et al. 2011

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We report in the present work a new method for exploring conformational energy landscapes. The method, called T-RRT, combines ideas from statistical physics and robot path planning algorithms. A search tree is constructed on the conformational space starting from a given state. The tree expansion is driven by a double strategy: on the one hand, it is naturally biased towards yet unexplored regions of the space; on the other, a Monte Carlo-like transition test guides the expansion toward energetically favorable regions. The balance between these two strategies is automatically achieved thanks to a self-tuning mechanism. The method is able to efficiently find both, energy minima and transition paths between them. As a proof of concept, the method is applied to two academic benchmarks and to the alanine dipeptide.

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Section: Introductionmentioning

confidence: 99%

Randomized tree construction algorithm to explore energy landscapes

et al. 2011

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“…A first step toward a completely general approach may be to consider protein loop motions. We expect to integrate ML-RRT into the combined molecular-modeling/path-planning approach described in [7], [8].…”

Section: Discussionmentioning

confidence: 99%

Molecular Disassembly With Rrt-Like Algorithms

Cortés

Jaillet

Siméon

2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Abstract-This paper addresses the problem of computing pathways for a ligand to exit from the active site of a protein. Such problem can be formulated as a mechanical disassembly problem for two articulated objects. Its solution requires searching paths in a constrained high-dimensional configurationspace. Indeed, the ligand passageway inside the protein is often extremely cluttered so that current path planning techniques are unable to solve the disassembly problem in reasonable computing time. The techniques presented in this paper are based on the RRT algorithm. First we discuss some simple and general modifications of the basic algorithm that significantly improve its performance. Then we describe a new variant of the planner that treats ligand and protein degrees of freedom separately. This new algorithm outperforms the basic RRT, particularly for very constrained problems, and is able to handle models with hundreds of degrees of freedom. We analyze the effects of each RRT variant via several examples of different complexity. Although discussions and results of this paper focus on molecular models, the ideas behind the algorithms are general and can be applied to path planners for disassembling articulated mechanical parts.

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“…Numerical methods able to isolate the whole conformational space and that are not affected by singularities also exist [46]. Finally, problems with more degrees of freedom can also be addressed with local perturbation techniques [58,35], with approaches where some of the variables are sampled and the rest is solved via inverse kinematics [15,14] or combining inverse kinematics, fragment assembly, and local optimization methods [26,36].…”

Section: Related Workmentioning

confidence: 99%

Exploring the energy landscapes of flexible molecular loops using higher‐dimensional continuation

Porta

Jaillet

2012

J Comput Chem

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The conformational space of a flexible molecular loop includes the set of conformations fulfilling the geometric loop-closure constraints and its energy landscape can be seen as a scalar field defined on this implicit set. Higher-dimensional continuation tools, recently developed in Dynamical Systems and also applied to Robotics, provide efficient algorithms to trace out implicitly defined sets. This paper describes these tools and applies them to obtain full descriptions of the energy landscapes of short molecular loops that, otherwise, can only be partially explored, mainly via sampling. Moreover, to deal with larger loops, this paper exploits the higher-dimensional continuation tools to find local minima and minimum energy transition paths between them, without deviating from the loop-closure constraints. The proposed techniques are applied to previously studied molecules revealing the intricate structure of their energy landscapes. This paper introduces the use of higher-dimensional continuation tools to explore the energy landscapes of the implicitly-defined conformational spaces of flexible molecular loops. These tools produce an atlas composed by coordinated charts that parametrize the conformational space. The atlas captures the structure of this space, which determines the motion of the loop and the transition paths between conformations, something that is hard to obtain using existing approaches.

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Geometric algorithms for the conformational analysis of long protein loops

Cited by 87 publications

References 53 publications

Randomized tree construction algorithm to explore energy landscapes

Randomized tree construction algorithm to explore energy landscapes

Molecular Disassembly With Rrt-Like Algorithms

Exploring the energy landscapes of flexible molecular loops using higher‐dimensional continuation

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