A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Case-specific performance of MM-PBSA, MM-GBSA, and SIE in virtual screening
Tekijät: Virtanen SI, Niinivehmas SP, Pentikainen OT
Kustantaja: ELSEVIER SCIENCE INC
Julkaisuvuosi: 2015
Journal: Journal of Molecular Graphics and Modelling
Tietokannassa oleva lehden nimi: JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Lehden akronyymi: J MOL GRAPH MODEL
Vuosikerta: 62
Aloitussivu: 303
Lopetussivu: 318
Sivujen määrä: 16
ISSN: 1093-3263
DOI: https://doi.org/10.1016/j.jmgm.2015.10.012
Tiivistelmä
In drug discovery the reliable prediction of binding free energies is of crucial importance. Methods that combine molecular mechanics force fields with continuum solvent models have become popular because of their high accuracy and relatively good computational efficiency. In this research we studied the performance of molecular mechanics generalized Born surface area (MM-GBSA), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), and solvated interaction energy (SIE) both in their virtual screening efficiency and their ability to predict experimentally determined binding affinities for five different protein targets. The protein-ligand complexes were derived with two different approaches important in virtual screening: molecular docking and ligand-based similarity search methods. The results show significant differences between the different binding energy calculation methods. However, the length of the molecular dynamics simulation was not of crucial importance for accuracy of results. (C) 2015 Elsevier Inc. All rights reserved.
In drug discovery the reliable prediction of binding free energies is of crucial importance. Methods that combine molecular mechanics force fields with continuum solvent models have become popular because of their high accuracy and relatively good computational efficiency. In this research we studied the performance of molecular mechanics generalized Born surface area (MM-GBSA), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), and solvated interaction energy (SIE) both in their virtual screening efficiency and their ability to predict experimentally determined binding affinities for five different protein targets. The protein-ligand complexes were derived with two different approaches important in virtual screening: molecular docking and ligand-based similarity search methods. The results show significant differences between the different binding energy calculation methods. However, the length of the molecular dynamics simulation was not of crucial importance for accuracy of results. (C) 2015 Elsevier Inc. All rights reserved.
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