{"title":"MM/GBSA prediction of relative binding affinities of carbonic anhydrase inhibitors: effect of atomic charges and comparison with Autodock4Zn","authors":"Mackenzie Taylor, Junming Ho","doi":"10.1007/s10822-023-00499-0","DOIUrl":null,"url":null,"abstract":"<div><p>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 (R<sup>2</sup> = 0.77). The use of the recently enhanced Autodock Vina and zinc optimised AD4<sub>Zn</sub> force field also predicted ligand binding affinities with moderately strong correlation (R<sup>2</sup> = 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.</p><h3>Graphical abstract</h3>\n <figure><div><div><div><picture><source><img></source></picture></div></div></div></figure>\n </div>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"37 4","pages":"167 - 182"},"PeriodicalIF":3.0000,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10822-023-00499-0.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer-Aided Molecular Design","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s10822-023-00499-0","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
The Journal of Computer-Aided Molecular Design provides a form for disseminating information on both the theory and the application of computer-based methods in the analysis and design of molecules. The scope of the journal encompasses papers which report new and original research and applications in the following areas:
- theoretical chemistry;
- computational chemistry;
- computer and molecular graphics;
- molecular modeling;
- protein engineering;
- drug design;
- expert systems;
- general structure-property relationships;
- molecular dynamics;
- chemical database development and usage.