Protein-Ligand Interactions

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

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)

Research

Protein-Ligand Interacions

Molecular Docking

Bioinspired Computing

Computational Systems Biology

Recent Publications

Volkart PA et al. Cyclin-Dependent Kinase 2 in Cellular Senescence and Cancer. A Structural and Functional Review. Curr Drug Targets. 2018.

de Ávila MB et al.. Structural Basis for Inhibition of Enoyl-[Acyl Carrier Protein] Reductase (InhA) from Mycobacterium tuberculosis. Curr Med Chem 2018.

Protein-Ligand Interactions

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