The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Predicting Binding Affinities of Protein Ligands from Three-Dimensional Models: Application to Peptide Binding to Class I Major Histocompatibility Proteins
Abstract
A simple and fast free energy scoring function (Fresno) has been developed to predict the binding free energy of peptides to class I major histocompatibility (MHC) proteins. It differs from existing scoring functions mainly by the explicit treatment of ligand desolvation and of unfavorable protein-ligand contacts. Thus, it may be particularly useful in predicting binding affinities from three-dimensional models of protein-ligand complexes. The Fresno function was independently calibrated for two different training sets: (a) five HLA-A0201-peptide structures, which had been determined by X-ray crystallography, and (b) three-dimensional models of 37 H-2K(k)-peptide structures, which had been obtained by knowledge-based homology modeling. For both training sets, a good cross-validated fit to experimental binding free energies was obtained with predictive errors of 3-3.5 kJ/mol. As expected, lipophilic interactions were found to contribute the most to HLA-A0201-peptide interactions, whereas H-bonding predominates in H-2K(k) recognition. Both cross-validated models were afterward used to predict the binding affinity of a test set of 26 peptides to HLA-A0204 (an HLA allele closely related to HLA-A0201) and of a series of 16 peptides to H-2K(k). Predictions were more accurate for HLA-A2-binding peptides as the training set had been built from experimentally determined structures. The average error in predicting the binding free energy of the test peptides was 3.1 kJ/mol. For the homology model-derived equation, the average error in predicting the binding free energy of peptides to K(k) was significantly higher (5.4 kJ/mol) but still very acceptable. The present scoring function is thus able to predict with a good accuracy binding free energies from three-dimensional models, at the condition that the backbone coordinates of the MHC-bound peptide have first been determined with an accuracy of about 1-1.5 A. Furthermore, it may be easily recalibrated for any protein-ligand complex.
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Cites
Cramer, R. D., Patterson, D. E., & Bunce, J. D. (1988) · Journal of the American Chemical Society · doi:10.1021/ja00226a005 · Cited by 3,931
Cited by
Bissantz, C., Folkers, G., & Rognan, D. (2000) · Journal of Medicinal Chemistry · doi:10.1021/jm001044l · Cited by 740
Self-citationJain, A. N. (2007) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-007-9114-2 · Cited by 587
Moitessier, N., Englebienne, P., Lee, D., Lawandi, J., & Corbeil, C. R. (2008) · British Journal of Pharmacology · doi:10.1038/sj.bjp.0707515 · Cited by 514
Guedes, I. A., Pereira, F. S. S., & Dardenne, L. E. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.01089 · Cited by 331
Bissantz, C., Bernard, P., Hibert, M., & Rognan, D. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10237 · Cited by 293
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Metadata
- Authors
- Rognan, D., Lauemøller, S. L., Holm, A., Buus, S., & Tschinke, V.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 1999-10-01
- Volume
- 42
- Issue
- 22
- Pages
- 4650-4658
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W1984078422
- Cited by
- 165
- References
- 1
- FWCI
- 2.07
- Type
- journal article
- Language
- en
- Open access
- closed
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