ArticleMolecular informatics2018
Prediction of Protein-compound Binding Energies from Known Activity Data: Docking-score-based Method and its Applications.
Article in Molecular informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
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- In Silico Comparative Analysis of Ivermectin and Nirmatrelvir Inhibitors Interacting with the SARS-CoV-2 Main Protease.Biomolecules · 2024Article
- Insight into the Potential Mechanisms of Endocrine Disruption by Dietary Phytoestrogens in the Context of the Etiopathogenesis of Endometriosis.International journal of molecular sciences · 2023Review
- Computational biophysics and structural biology of proteins-a Special Issue in honor of Prof. Haruki Nakamura's 70th birthday.Biophysical reviews · 2022Article
- Anthocyanin-Related Pigments: Natural Allies for Skin Health Maintenance and Protection.Antioxidants (Basel, Switzerland) · 2021Article
- Analysis of non-structural proteins, NSPs of SARS-CoV-2 as targets for computational drug designing.Biochemistry and biophysics reports · 2021Article
- Prediction of Passive Membrane Permeability by Semi-Empirical Method Considering Viscous and Inertial Resistances and Different Rates of Conformational Change and Diffusion.Molecular informatics · 2020Article
- Developing a Kinase-Specific Target Selection Method Using a Structure-Based Machine Learning Approach.Advances and applications in bioinformatics and chemistry : AABC · 2020Article
- Prediction of Protein-compound Binding Energies from Known Activity Data: Docking-score-based Method and its Applications.Molecular informatics · 2018Article
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4 authors.
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Abstract
We used protein-compound docking simulations to develop a structure-based quantitative structure-activity relationship (QSAR) model. The prediction model used docking scores as descriptors. The binding free energy was approximated by a weighted average of docking scores for multiple proteins. This approximation was based on a pharmacophore model of receptor pockets and compounds. The weights of the docking scores were restricted to small values to avoid unrealistic weights by a regularization term. Additional outlier elimination improved the results. We applied this method to two groups of targets. The first target was the kinase family. The cross-validation results of 107 kinase proteins showed that the RMSE of predicted binding free energies was 1.1 kcal/mol. The second target was the matrix metalloproteinase (MMP) family, which has been difficult for docking programs. MMPs require metal-binding groups in their inhibitor structures in many cases. A quantum effect contributes to the metal-ligand interaction. Despite this difficulty, the present method worked well for the MMPs. This method showed that the RMSE of predicted binding free energies was 1.1 kcal/mol. In comparison, with the original docking method the RMSE was 1.7 kcal/mol. The results suggest that the present QSAR model should be applied to general target proteins.
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