The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
MedusaScore: An Accurate Force Field-Based Scoring Function for Virtual Drug Screening
Open accessAbstract
Virtual screening is becoming an important tool for drug discovery. However, the application of virtual screening has been limited by the lack of accurate scoring functions. Here, we present a novel scoring function, MedusaScore, for evaluating protein-ligand binding. MedusaScore is based on models of physical interactions that include van der Waals, solvation, and hydrogen bonding energies. To ensure the best transferability of the scoring function, we do not use any protein-ligand experimental data for parameter training. We then test the MedusaScore for docking decoy recognition and binding affinity prediction and find superior performance compared to other widely used scoring functions. Statistical analysis indicates that one source of inaccuracy of MedusaScore may arise from the unaccounted entropic loss upon ligand binding, which suggests avenues of approach for further MedusaScore improvement.
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Cites
Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
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Golbraikh, A., & Tropsha, A. (2002) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(01)00123-1 · Cited by 3,735
The PDBbind database: methodologies and updates
Wang, R., Fang, X., Lu, Y., Yang, C.-Y., & Wang, S. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm048957q · Cited by 933
Comparative evaluation of 11 scoring functions for molecular docking.
Wang, R., Lu, Y., & Wang, S. (2003) · Journal of Medicinal Chemistry · doi:10.1021/jm0203783 · Cited by 849
Cited by
Huang, S.-Y., Grinter, S. Z., & Zou, X. (2010) · Physical Chemistry Chemical Physics · doi:10.1039/c0cp00151a · Cited by 508
Cang, Z., & Wei, G.-W. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005690 · Cited by 330
Docking Challenge: Protein Sampling and Molecular Docking Performance
Elokely, K. M., & Doerksen, R. J. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400040d · Cited by 287
Cang, Z., & Wei, G. (2018) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.2914 · Cited by 172
Nguyen, D. D., Cang, Z., Wu, K., Wang, M., Cao, Y., & Wei, G.-W. (2019) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-018-0146-6 · Cited by 155
Metadata
- Authors
- Yin, S., Biedermannova, L., Vondrasek, J., & Dokholyan, N. V.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-08-01
- Volume
- 48
- Issue
- 8
- Pages
- 1656-1662
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2108257090
- Cited by
- 204
- References
- 4
- FWCI
- 9.14
- Type
- journal article
- Language
- en
- Open access
- green
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- Yin, S., Biedermannova, L., Vondrasek, J., & Dokholyan, N. V. (2008). MedusaScore: An Accurate Force Field-Based Scoring Function for Virtual Drug Screening. Journal of Chemical Information and Modeling. https://doi.org/10.1021/ci8001167
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