Protein-Ligand Interactions

Books

Docking Screens for Drug Discovery. Editor: de Azevedo Jr., Walter Filgueira (Ed.)

Progress in Cell Cycle Research: Volume 2

Projects

SAnDReS: Statistical Analysis of Docking Results and Scoring functions

SFSXplorer: Scoring Function Space eXplorer

Taba: A Tool to Analyze the Binding Affinity

Citation

Citation Metrics

Editorships

Frontiers Section Editor (Bioinformatics and Biophysics) for the Current Drug Targets ISSN: 1873-5592

Section Editor (Bioinformatics in Drug Design and Discovery) for the Current Medicinal Chemistry ISSN: 1875-533X

Section Editor (Combinatorial/Medicinal Chemistry) for the Combinatorial Chemistry & High Throughput Screening ISSN: 1875-5402

Member of the Editorial Board for the PeerJ ISSN: 2167-8359

Member of the Editorial Board for the Current Bioinformatics ISSN: 2212-392X (Online) ISSN: 1574-8936 (Print)

Member of the Editorial Board for the Organic & Medicinal Chemistry International Journal ISSN: 2474-7610

Section Editor in Chief (Bioinformatics) for Bioengineering International. ISSN 2668-7119

Member of the Editorial Board for the PeerJ Physical Chemistry

Research

Protein-Ligand Interacions

Molecular Docking

Bioinspired Computing

Computational Systems Biology

Recent Publications

da Silva AD et al. J Comput Chem. 2020; 41(1): 69-73.

Volkart PA et al. Curr Drug Targets. 2019;20(7):716-726

Russo S, De Azevedo WF. Curr Med Chem 2019. 26(10):1908-1919

Protein-Ligand Interaction

In the study of intermolecular interactions involving protein and ligands, we expect to gain further insights into the structural basis for the specificity of small-molecule ligands against a specific protein target (De Azevedo, 2008). Analysis of protein-ligand interaction is a central problem in the drug design. Knowledge of the key features responsible for the specificity of a ligand for a protein allows us to determine which physical-chemical parameters could be changed to improve the protein-ligand interaction (De Azevedo & Dias, 2008a). Furthermore, the development of a computational model to predict the binding affinity based on the atomic coordinates of a protein-ligand complex (De Azevedo & Dias, 2008b) opens the possibility to apply virtual screening approaches to search small-molecule databases to identify a drug candidate (De Azevedo, 2010a). To study protein-ligand interactions, we make use of protein crystallography (Canduri & De Azevedo, 2008), nuclear magnetic resonance spectroscopy (Fadel et al., 2005), molecular docking (De Azevedo, 2010b), and molecular dynamics (De Azevedo, 2011).

References

Canduri F, de Azevedo WF. Protein crystallography in drug discovery. Curr Drug Targets. 2008; 9(12):1048–1053. PubMed

De Azevedo WF Jr. Protein-drug interactions. Curr Drug Targets. 2008; 9(12):1030. PubMed

De Azevedo WF Jr, Dias R. Experimental approaches to evaluate the thermodynamics of protein-drug interactions. Curr Drug Targets. 2008a; 9(12):1071–1076. PubMed

De Azevedo WF Jr, Dias R. Computational methods for calculation of ligand-binding affinity. Curr Drug Targets. 2008b; 9(12):1031–1039. PubMed

De Azevedo WF Jr. Structure-based virtual screening. Curr Drug Targets. 2010a; 11(3):261–263. PubMed

De Azevedo WF Jr. MolDock applied to structure-based virtual screening. Curr Drug Targets. 2010b; 11(3):327–334. PubMed

De Azevedo WF Jr. Molecular dynamics simulations of protein targets identified in Mycobacterium tuberculosis. Curr Med Chem. 2011; 18(9):1353–1366. PubMed

Fadel V, Bettendorff P, Herrmann T, de Azevedo WF Jr, Oliveira EB, Yamane T, Wüthrich K. Automated NMR structure determination and disulfide bond identification of the myotoxin crotamine from Crotalus durissus terrificus. Toxicon. 2005; 46(7):759–767. PubMed