Intern | 2021-2023
B.S. in Computer Engineering | 2018-2023
Briefings in Bioinformatics | September 2022
Co-authors: Vinícius A. Paiva, Sabrina A. Silveira, David B. Ascher, Douglas E. V. Pires, Sandro C Izidoro
Abstract: Metals are present in >30% of proteins found in nature and assist them to perform important biological functions, including storage, transport, signal transduction and enzymatic activity. Traditional and experimental techniques for metal-binding site prediction are usually costly and time-consuming, making computational tools that can assist in these predictions of significant importance. Here we present Genetic Active Site Search (GASS)-Metal, a new method for protein metal-binding site prediction. The method relies on a parallel genetic algorithm to find candidate metal-binding sites that are structurally similar to curated templates from M-CSA and MetalPDB. GASS-Metal was thoroughly validated using homologous proteins and conservative mutations of residues, showing a robust performance. The ability of GASS-Metal to identify metal-binding sites was also compared with state-of-the-art methods, outperforming similar methods and achieving an MCC of up to 0.57 and detecting up to 96.1% of the sites correctly. GASS-Metal is freely available at https://gassmetal.unifei.edu.br. The GASS-Metal source code is available at https://github.com/sandroizidoro/gassmetal-local.
Read the full paperComputers in Biology and Medicine | August 2022
Co-authors: Vinícius de Almeida Paiva, Isabela de Souza Gomes, Cleiton Rodrigues Monteiro, Pedro Magalhães Martins, Charles Abreu Santana, Valdete Gonçalves-Almeida, Sandro Carvalho Izidoro, Raquel Cardoso de Melo-Minardi, Sabrina de Azevedo Silveira
Abstract: Proteins play a crucial role in organisms in nature. They are able to perform structural, catalytic, transport and defense functions in cells, among others. We understand that a variety of resources do exist to work with protein structural bioinformatics, which perform tasks such as protein modeling, protein docking, protein molecular dynamics, protein interaction, active and binding site prediction and mutation analysis. Nonetheless, they are generally spread all over different online repositories. For the students or professionals interested in working with protein structural bioinformatics, it may not be trivial to know what resources he/she should learn/use or where these could be accessed. Here, the main subareas in the field of protein structural bioinformatics are introduced with a brief description, and we point to and discuss several online resources, such as methods, databases and tools, in order to give an overview of this research field. Furthermore, we developed Protein Structural bioinformatics Overview (PreStO), a web tool available at http://bioinfo.dcc.ufmg.br/presto/, to organize and make it possible to retrieve these online resources based on a search term. We believe that this paper can be a starting point for potential bioinformaticians to trace a path that can be followed to build competencies and achieve knowledge milestones in the context of protein structural bioinformatics.
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