Books

Docking Screens for Drug Discovery

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

 

Progress in Cell Cycle Research

 

Springer

Progress in Cell Cycle Research: Volume 2

 

 

Projects

SAnDReS

SAnDReS-SigmaSAnDReS: Statistical Analysis of Docking Results and Scoring functions

 

SFSXplorer

 

SFSXplorer

SFSXplorer: Scoring Function Space eXplorer

 

Taba

TabaTaba: A Tool to Analyze the Binding Affinity

 

Citation

Citation Metrics

Citation Metrics

Citation Metrics

 

Editorships

Current Drug Targets

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

Bentham Link

Current Medicinal Chemistry

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

Bentham Link

Journal of Molecular Structure

Member of the Editorial Board of the Journal of Molecular Structure ISSN: 0022-2860

Journal of Molecular Structure Link

Molecular Diversity

Member of the Editorial Board of Molecular Diversity ISSN: 1381-1991 (Print) 1573-501X (Online)

Molecular Diversity Link

Exploration of Drug Science

Associate Editor for Exploration of Drug Science

Exploration of Drug Science Link

Frontiers in Chemistry

Reviewer Editor for Frontiers in Chemistry ISSN: 2296-2646

Frontiers in Chemistry Link

Organic and Medicinal Chemistry International Journal

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

Bentham Link

 

SAnDReS         

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Highlights

SAnDReS 2.0 (Statistical Analysis of Docking Results and Scoring functions) brings advanced computational tools for protein-ligand docking simulation and machine-learning modeling. We have AutoDock Vina (version 1.2.3) as a docking engine. Also, SAnDReS 2.0 has 54 regression methods implemented using Scikit-Learn, which allows us to explore the Scoring Function Space (SFS) concept. This exploration of the SFS permits us to have an adequate machine learning model for a targeted protein system. This approach creates computational models with superior predictive performance compared with classical scoring functions (also known as universal scoring functions). SAnDReS aims to merge the holistic view of systems biology with machine-learning methods to contribute to drug discovery projects. Dr. Walter F. de Azevedo Jr. proposed the initial idea of SAnDReS in 2016, which now has an international team of scientists participating in its development and testing.

Downloads  

Useful Sites and Related Programs

DOME - IIB | Elixir Italy

 

Funding

The Brazilian National Council for Scientific and Technological Development (CNPq) (Process 306298/2022-8) supports this research project.