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MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn
MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn
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MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn
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MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn
MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn

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MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn
MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn
Journal Article

MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn

2023
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Overview
Carbonic anhydrase is an attractive drug target for the treatment of many diseases. This paper examines the ability of end-state MM/GBSA methods to rank inhibitors of carbonic anhydrase in terms of their binding affinities. The MM/GBSA binding energies were evaluated using different atomic charge schemes (Mulliken, ESP and NPA) at different levels of theories, including Hartree–Fock, B3LYP-D3(BJ), and M06-2X with the 6–31G(d,p) basis set. For a large test set of 32 diverse inhibitors, the use of B3LYP-D3(BJ) ESP atomic charges yielded the strongest correlation with experiment (R2 = 0.77). The use of the recently enhanced Autodock Vina and zinc optimised AD4Zn force field also predicted ligand binding affinities with moderately strong correlation (R2 = 0.64) at significantly lower computational cost. However, the docked poses deviate significantly from crystal structures. Overall, this study demonstrates the applicability of docking to estimate ligand binding affinities for a diverse range of CA inhibitors, and indicates that more theoretically robust MM/GBSA simulations show promise for improving the accuracy of predicted binding affinities, as long as a validated set of parameters is used.
Publisher
Springer Nature B.V