Using Local States To Drive the Sampling of Global Conformations in Proteins

Pandini, Alessandro; Fornili, Arianna

doi:10.1021/acs.jctc.5b00992

Cited by 16 publications

(16 citation statements)

References 70 publications

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“…For every simulation, we have used GSATools (Pandini et al, 2013) to encode the conformation of each frame into a SA string, composed of 117 letters for our 120-residue protein. We then transformed the SA representation to that of a reduced structural alphabet (rSA), according to the mapping defined between these two alphabets (Pandini and Fornili, 2016). The rSA is a reduced representation of the original alphabet in which each letter corresponds to a macro-region of the density space.…”

Section: Structural Alphabetsmentioning

confidence: 99%

The conformational and mutational landscape of the ubiquitin-like marker for the autophagosome formation in cancer

Fas

Kumar

Sora

et al. 2019

Preprint

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Autophagy is a cellular process to recycle damaged cellular components and its modulation can be exploited for disease treatments. A key autophagy player is a ubiquitin-like protein, LC3B. Compelling evidence attests the role of autophagy and LC3B in different cancer types. Many LC3B structures have been solved, but a comprehensive study, including dynamics, has not been yet undertaken. To address this knowledge gap, we assessed ten physical models for molecular dynamics for their capabilities to describe the structural ensemble of LC3B in solution using different metrics and comparison with NMR data. With the resulting LC3B ensembles, we characterized the impact of 26 missense mutations from Pan-Cancer studies with different approaches. Our findings shed light on driver or neutral mutations in LC3B, providing an atlas of its modifications in cancer. Our framework could be used to assess the pathogenicity of mutations by accounting for the different aspects of protein structure and function altered by mutational events.

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Section: Structural Alphabetsmentioning

confidence: 99%

The conformational and mutational landscape of the ubiquitin-like marker for the autophagosome formation in cancer

Fas

Kumar

Sora

et al. 2019

Preprint

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“…SA approach is therefore particularly adapted to compare and characterize of structural variability [ 31 ] and to characterize and predict protein flexibility [ 32 ]. A tool based on a SA of 28 SLs, called “GSATools” was developed to analyze an ensemble of molecular dynamics models associated with the same sequence [ 23 ] and combined to molecular simulation to increase the exploration of the conformational space of proteins [ 33 ]. Based on another SA of 16 SLs, Mahajan et al (2014) compared the local conformation variations observed at structurally equivalent positions of a multiple structural alignment obtained using NMR models and different homologous structures of a single protein [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight

et al. 2017

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Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels.

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“…in 63 . Furthermore, our method could be combined with others enhancing the sampling of orthogonal degrees of freedom, such as global protein motions 60,81 , rotations around torsional angles 61,62 , secondary structure changes 82,83 , rescaled protein-ligand interactions 54,63 , just to cite a few options. In addition, experimental information from many sources could be easily encoded in new CVs and/or restraints.…”

Section: Discussionmentioning

confidence: 99%

An enhanced-sampling MD-based protocol for molecular docking

Basciu

Malloci

Pietrucci

et al. 2018

Preprint

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Understanding molecular recognition of proteins by small molecules is key for drug design. Despite the number of experimental structures of ligand-protein complexes keeps growing, the number of available targets remains limited compared to the druggable genome, and structural diversity is generally low, which affects the chemical variance of putative lead compounds. From a computational perspective, molecular docking is widely used to mimic ligand-protein association in silico. Ensembledocking approaches include flexibility through a set of different conformations of the protein obtained either experimentally or from computer simulations, e.g. molecular dynamics. However, structures prone to host (the correct) ligands are generally poorly sampled by standard molecular dynamics simulations of the apo protein. In order to address this limitation, we introduce a computational approach based on metadynamics simulations (EDES -Ensemble-Docking with Enhanced-sampling of pocket Shape) to generate druggable conformations of proteins only exploiting their apo structures. This is achieved by defining a set of collective variables that effectively sample different shapes of the binding site, ultimately mimicking the steric effect due to ligands to generate holo-like binding site geometries. We assessed the method on two challenging proteins undergoing different extents of conformational changes upon ligand binding. In both cases our protocol generated a significant fraction of structures featuring a low RMSD from the experimental holo conformation. Moreover, ensemble docking calculations using those conformations yielded native-like poses among the top ranked ones for both targets. This proof of concept study paves the route towards an automated workflow to generate druggable conformations of proteins, which should become a precious tool for structure-based drug design.

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Using Local States To Drive the Sampling of Global Conformations in Proteins

Cited by 16 publications

References 70 publications

The conformational and mutational landscape of the ubiquitin-like marker for the autophagosome formation in cancer

The conformational and mutational landscape of the ubiquitin-like marker for the autophagosome formation in cancer

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight

An enhanced-sampling MD-based protocol for molecular docking

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