TY - JOUR
T1 - Development and evaluation of MM/GBSA based on a variable dielectric GB model for predicting protein-ligand binding affinities
AU - Wang, Ercheng
AU - Liu, Hui
AU - Wang, Junmei
AU - Weng, Gaoqi
AU - Sun, Huiyong
AU - Wang, Zhe
AU - Kang, Yu
AU - Hou, Tingjun
N1 - Funding Information:
This work was financially supported by the Key R&D Program of Zhejiang Province (2020C03010), the National Natural Science Foundation of China (21575128, 81773632), and the Zhejiang Provincial Natural Science Foundation of China (LZ19H300001).
Publisher Copyright:
© 2020 American Chemical Society.
PY - 2020/11/23
Y1 - 2020/11/23
N2 - In structure-based drug design (SBDD), the molecular mechanics generalized Born surface area (MM/GBSA) approach has been widely used in ranking the binding affinity of small molecule ligands. However, an accurate estimation of protein-ligand binding affinity still remains a challenge due to the intrinsic limitation of the standard generalized Born (GB) model used in MM/GBSA. In this study, we proposed and evaluated the MM/GBSA approach based on a variable dielectric generalized Born (VDGB) model using residue-type-based dielectric constants. In the VDGB model, different dielectric values were assigned for the three types of protein residues, and the magnitude of the dielectric constants for residue types follows this order: charged ≥ polar ≥ nonpolar. We found that MM/GBSA based on a VDGB model (MM/GBSAVDGB) with an optimal dielectric constant of 4.0 for the charged residues and 1.0 for the noncharged residues together with a net-charge-dependent dielectric value for ligands achieved better predictions as judged by Pearson's correlation coefficient than the standard MM/GBSA with a uniform solute dielectric constant of 4.0 for the training set of 130 protein-ligand complexes. The prediction on the test set with 165 protein-ligand complexes also validated the better performance of MM/GBSAVDGB. Moreover, this method exhibited potential in predicting the relative binding free energies for multiple ligands against the same target. Furthermore, we found that rational truncation of protein residues far from the binding site can significantly speed up the MM/GBSAVDGB calculations, while it almost does not influence the prediction accuracy. Therefore, it is feasible to implement the system-truncated MM/GBSAVDGB as a scoring function for SBDD.
AB - In structure-based drug design (SBDD), the molecular mechanics generalized Born surface area (MM/GBSA) approach has been widely used in ranking the binding affinity of small molecule ligands. However, an accurate estimation of protein-ligand binding affinity still remains a challenge due to the intrinsic limitation of the standard generalized Born (GB) model used in MM/GBSA. In this study, we proposed and evaluated the MM/GBSA approach based on a variable dielectric generalized Born (VDGB) model using residue-type-based dielectric constants. In the VDGB model, different dielectric values were assigned for the three types of protein residues, and the magnitude of the dielectric constants for residue types follows this order: charged ≥ polar ≥ nonpolar. We found that MM/GBSA based on a VDGB model (MM/GBSAVDGB) with an optimal dielectric constant of 4.0 for the charged residues and 1.0 for the noncharged residues together with a net-charge-dependent dielectric value for ligands achieved better predictions as judged by Pearson's correlation coefficient than the standard MM/GBSA with a uniform solute dielectric constant of 4.0 for the training set of 130 protein-ligand complexes. The prediction on the test set with 165 protein-ligand complexes also validated the better performance of MM/GBSAVDGB. Moreover, this method exhibited potential in predicting the relative binding free energies for multiple ligands against the same target. Furthermore, we found that rational truncation of protein residues far from the binding site can significantly speed up the MM/GBSAVDGB calculations, while it almost does not influence the prediction accuracy. Therefore, it is feasible to implement the system-truncated MM/GBSAVDGB as a scoring function for SBDD.
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U2 - 10.1021/acs.jcim.0c00024
DO - 10.1021/acs.jcim.0c00024
M3 - Article
C2 - 32175734
AN - SCOPUS:85095113772
SN - 1549-9596
VL - 60
SP - 5353
EP - 5365
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
IS - 11
ER -