Enhancing <scp>MM</scp>/P(G)<scp>BSA</scp> Methods: Integration of Formulaic Entropy for Improved Binding Free Energy Calculations
Balancing computational efficiency and precision, MM/P(G)BSA methods have been widely employed in the estimation of binding free energies within biological systems. However, the entropy contribution to the binding free energy is often neglected in MM/P(G)BSA calculations, due to the computational cost of conventional methods such as normal mode analysis (NMA). In this work, the entropy effect using a formulaic entropy can be computed from one single structure according to variations in the polar and non-polar solvents accessible surface areas and the count of rotatable bonds in ligands. It was incorporated into MM/P(G)BSA methods to enhance their performance. Extensive benchmarking reveals that the integration of formulaic entropy systematically elevates the performance of both MM/PBSA and MM/GBSA without incurring additional computational expenses. In addition, we found the inclusion of dispersion can deteriorate the correlation performance (R<sub>p</sub>) but reduce the root mean square error (RMSE) of both MM/PBSA and MM/GBSA. Notably, MM/PBSA_S, including the formulaic entropy but excluding the dispersion, surpasses all other MM/P(G)BSA methods across a spectrum of datasets. Our investigation furnishes a valuable and practical MM/P(G)BSA method, optimizing binding free energy calculations for a variety of biological systems.
Authors
- Pengfei Li (ORCID: https://orcid.org/0000-0002-2572-5935)
- Lina Dong (ORCID: https://orcid.org/0000-0003-3922-5912)
- Binju Wang (ORCID: https://orcid.org/0000-0002-3353-9411)
Institutions
- Xiamen University (CN)
- Loyola University Chicago (US)
Publication Details
- Journal
- Journal of Computational Chemistry
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1002/jcc.70093
- Citations
- 5
- Primary Topic
- Protein Structure and Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 4.03
Funders
- Loyola University Chicago
- National Natural Science Foundation of China
- Fundamental Research Funds for the Central Universities