Title |
Fully Flexible Docking via Reaction-Coordinate-Independent Molecular Dynamics Simulations
|
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Published in |
Journal of Chemical Information and Modeling, February 2018
|
DOI | 10.1021/acs.jcim.7b00674 |
Pubmed ID | |
Authors |
Martina Bertazzo, Mattia Bernetti, Maurizio Recanatini, Matteo Masetti, Andrea Cavalli |
Abstract |
Predicting the geometry of protein-ligand binding complexes is of primary importance for structure-based drug discovery. Molecular dynamics (MD) is emerging as a reliable computational tool for use in conjunction with, or an alternative to, docking methods. However, simulating the protein-ligand binding process often requires very expensive simulations. This drastically limits the practical application of MD-based approaches. Here, we propose a general framework to accelerate the generation of putative protein-ligand binding modes using potential-scaled MD simulations. The proposed dynamical protocol has been applied to two pharmaceutically relevant systems (GSK-3β and the N-terminal domain of HSP90α). Our approach is fully independent of any predefined reaction coordinate (or collective variable). It identified the correct binding mode of several ligands and can thus save valuable computational time in dynamic docking simulations. |
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Geographical breakdown
Country | Count | As % |
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France | 3 | 23% |
United States | 3 | 23% |
Germany | 1 | 8% |
United Kingdom | 1 | 8% |
Unknown | 5 | 38% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 7 | 54% |
Scientists | 5 | 38% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 39 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 28% |
Researcher | 10 | 26% |
Student > Doctoral Student | 3 | 8% |
Other | 2 | 5% |
Student > Master | 1 | 3% |
Other | 3 | 8% |
Unknown | 9 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 14 | 36% |
Biochemistry, Genetics and Molecular Biology | 6 | 15% |
Agricultural and Biological Sciences | 4 | 10% |
Computer Science | 2 | 5% |
Linguistics | 1 | 3% |
Other | 1 | 3% |
Unknown | 11 | 28% |