Academic Journal
Combining QM/MM Calculations with Classical Mining Minima to Predict Protein–Ligand Binding Free Energy
| العنوان: | Combining QM/MM Calculations with Classical Mining Minima to Predict Protein–Ligand Binding Free Energy |
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| المؤلفون: | Farzad Molani, Simon Webb, Art E. Cho |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Biophysics, Biochemistry, Physiology, Pharmacology, Biotechnology, Chemical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, specified atomic charges, proposed pose using, overall pearson correlation, mining minima approach, mechanically recalculated ones, drug discovery campaigns, classical mining minima, 147 different ligands, mean unsigned error, incorporates quantum mechanical, square error, molecular mechanical, methods examined, limited set, implicit solvent, force fields, fep +, explicit water, combined accuracy, based methods, 75 kcal, 39 kcal |
| الوصف: | We developed an effective binding free energy prediction protocol which incorporates quantum mechanical/molecular mechanical (QM/MM) calculations to substitute the specified atomic charges of force fields with quantum-mechanically recalculated ones at a proposed pose using a mining minima approach with the VeraChem mining minima engine. We tested this protocol using seven well-known targets with 147 different ligands and compared it with classical mining minima and the most popular binding free energy (BFE) methods using different metrics. Our new protocol, dubbed Qcharge-VM2, yielded an overall Pearson correlation of 0.86, which was better than all the methods examined. Qcharge-VM2 performed significantly better than implicit solvent-based methods, such as MM-GBSA and MM-PBSA, but not as good as explicit water-based free energy perturbation methods, such as FEP+, in terms of root-mean-square error, RMSE (1.75 kcal/mol) and mean unsigned error, MUE (1.39 kcal/mol) on a limited set of targets. However, our protocol is substantially less computationally demanding compared with FEP+. The combined accuracy and efficiency of our method can be valuable in drug discovery campaigns. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| Relation: | https://figshare.com/articles/journal_contribution/Combining_QM_MM_Calculations_with_Classical_Mining_Minima_to_Predict_Protein_Ligand_Binding_Free_Energy/22669787 |
| DOI: | 10.1021/acs.jcim.2c01637.s001 |
| الاتاحة: | https://doi.org/10.1021/acs.jcim.2c01637.s001 https://figshare.com/articles/journal_contribution/Combining_QM_MM_Calculations_with_Classical_Mining_Minima_to_Predict_Protein_Ligand_Binding_Free_Energy/22669787 |
| Rights: | CC BY-NC 4.0 |
| رقم الانضمام: | edsbas.68B9E0D7 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1021/acs.jcim.2c01637.s001 |
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