Back to Search Start Over

Effect of preprocessing and simulation parameters on the performance of molecular docking studies.

Authors :
Callil-Soares, Pedro Henrique
Biasi, Lilian Caroline Kramer
Pessoa Filho, Pedro de Alcântara
Source :
Journal of Molecular Modeling. Aug2023, Vol. 29 Issue 8, p1-15. 15p.
Publication Year :
2023

Abstract

Context: Molecular docking is an important and rapid tool that provides a comprehensive view of different molecular mechanisms. It is often used to verify the binding interactions of many pairs of molecules and is much faster than more rigorous approaches. However, its application requires carefully preprocessing each molecule and selecting a series of simulation parameters, which is not always done correctly. We show how preprocessing and simulation parameters can positively or negatively impact molecular docking performance. For example, the inclusion of hydrogen atoms leads to better redocking scores, but molecular dynamics simulations must be performed under certain constraints; otherwise, it may worsen performance rather than improve it. This study clarifies the importance and influence of these different parameters in the simulation results. Methods: We analyzed the influence of different parameters on the predictive ability of molecular docking techniques using two software packages: AutoDock Vina and AutoDock-GPU. Thus, 90 receptor-ligand complexes were redocked, evaluating the root mean square deviation (RMSD) between the original position of the ligand (receptor-ligand complex obtained experimentally) and that obtained by the software for every analysis. We investigated the influence of hydrogen atoms (on the receptor and on the receptor-ligand complex), partial charges (QEq, QTPIE, EEM, EEM2015ha, MMFF94, Gasteiger-Marsili, and no charge), search boxes (size and exhaustiveness), ligand characteristics (size and number of torsions), and the use of molecular dynamics (of the receptor or the receptor-ligand complex) before docking analyses. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16102940
Volume :
29
Issue :
8
Database :
Academic Search Index
Journal :
Journal of Molecular Modeling
Publication Type :
Academic Journal
Accession number :
169995457
Full Text :
https://doi.org/10.1007/s00894-023-05637-x