MoMA-LigPath: A web server to simulate protein-ligand unbinding

Protein-ligand interactions taking place far away from the active site, during ligand binding or release, may determine molecular specificity and activity. However, obtaining information about these interactions with experimental or computational methods remains difficult. The computational tool presented in this paper, MoMA-LigPath, is based on a mechanistic representation of the molecular system, considering partial flexibility, and on the application of a robotics-inspired algorithm to explore the conformational space. Such a purely geometric approach, together with the efficiency of the exploration algorithm, enables the simulation of ligand unbinding within very short computing time. Ligand unbinding pathways generated by MoMA-LigPath are a first approximation that can provide very useful information about protein-ligand interactions. When needed, this approximation can be subsequently refined and analyzed using state-of-the-art energy models and molecular modeling methods. MoMA-LigPath is available at http://moma.laas.fr. The web server is free and open to all users, with no login requirement

Enhancing the Transition-based RRT to deal with complex cost spaces

The Transition-based RRT (T-RRT) algorithm enables to solve motion planning problems involving configuration spaces over which cost functions are defined, or cost spaces for short. T-RRT has been successfully applied to diverse problems in robotics and structural biology. In this paper, we aim at enhancing T-RRT to solve ever more difficult problems involving larger and more complex cost spaces. We compare several variants of T-RRT by evaluating them on various motion planning problems involving different types of cost functions and different levels of geometrical complexity. First, we explain why applying as such classical extensions of RRT to T-RRT is not helpful, both in a mono-directional and in a bidirectional context. Then, we propose an efficient Bidirectional T-RRT, based on a bidirectional scheme tailored to cost spaces. Finally, we illustrate the new possibilities offered by the Bidirectional T-RRT on an industrial inspection problem

On Randomized Path Coverage of Configuration Spaces

We present a sampling-based algorithm that generates a set of locally-optimal paths that differ in visibility

L'hybridation d'arbres aléatoires d'exploration et de basin hopping conduit à une exploration plus efficace des paysages énergétiques

The number of local minima of the PEL of molecular systems generally growsexponentially with the number of degrees of freedom, so that a crucial property of PEL explorationalgorithms is their ability to identify local minima which are low lying and diverse.In this work, we present a new exploration algorithm, retaining the ability of basin hopping (BH) toidentify local minima, and that of transition based rapidly growing random trees (T-RRT) to fosterthe exploration of yet unexplored regions. This ability is obtained by interleaving calls to theextension procedures of BH and T-RRT, and we show tuning the balance between these two typesof calls allows the algorithm to focus on low lying regions. Computational efficiency is obtainedusing state-of-the art data structures, in particular for searching approximate nearest neighbors inmetric spaces.We present results for the BLN69, a protein model whose conformational space has dimension 207and whose PEL has been studied exhaustively. On this system, we show that the propensity ofour algorithm to explore low lying regions of the landscape significantly outperforms those of BHand T-RRT

A generic software framework for Wang-Landau type algorithms

The Wang-Landau (WL) algorithm is a stochastic algorithm designed to compute densities of states of a physical system. Is has also been recently used to perform challenging numerical integration in high-dimensional spaces. Using WL requires specifying the system handled, the proposal to explore the definition domain, and the measured against which one integrates. Additionally, several design options related to the learning rate must be provided. This work presents the first generic (C++) implementation providing all such ingredients. The versatility of the framework is illustrated with a variety of problems including the computation of density of states of physical systems and biomolecules, and the computation of high dimensional integrals. Along the way, we that integrating against a Boltzmann like measure to estimate DoS with respect to the Lebesgue measure can be beneficial. We anticipate that our implementation, available in the Structural Bioinformatics Library (http: //sbl.inria.fr), will leverage experiments on complex systems and contribute to unravel free energy calculations for (bio-)molecular systems

Articles publicats per investigadors de l'ETSEIB indexats al Journal Citation Reports: 2011

Informe que recull els 296 treballs publicats per 220 investigadors de l'Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB) en revistes indexades al Journal Citation Reports durant l’any 2011Preprin

Randomized tree construction algorithm to explore energy landscapes

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