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Current Drug Metabolism

Author(s): Dakshinamurthy Sivakumar and Sangwook Wu*

DOI: 10.2174/1389200223666220315160835

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Classical and Machine Learning Methods for Protein - Ligand Binding Free Energy Estimation

Page: [252 - 259] Pages: 8

  • * (Excluding Mailing and Handling)

Abstract

Binding free energy estimation of drug candidates to their biomolecular target is one of the best quantitative estimators in computer-aided drug discovery. Accurate binding free energy estimation is still a challengeable task even after decades of research, along with the complexity of the algorithm, time-consuming procedures, and reproducibility issues. In this review, we have discussed the advantages and disadvantages of diverse free energy methods like Thermodynamic Integration (TI), Bennett's Acceptance Ratio (BAR), Free Energy Perturbation (FEP), and alchemical methods. Moreover, we discussed the possible application of the machine learning method in proteinligand binding free energy estimation.

Keywords: Free energy, Bennett's acceptance ratio (BAR), alchemical methods, machine learning, computer-aided drug discovery, thermodynamic integration (TI).

Graphical Abstract

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