Structural discrimination analysis for constraint selection in protein modeling

Autor(es)

Bottino, Guilherme F. ^{[1, 2]} ; Ferrari, Allan J. R. ^{[1, 2]} ; Gozzo, Fabio C. ^[1] ; Martinez, Leandro ^{[1, 2]}

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, Inst Chem, Campinas, SP - Brazil

^[2] Univ Estadual Campinas, Ctr Computat Engn & Sci, Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Bioinformatics; v. 37, n. 21, p. 3766-3773, NOV 1 2021.
• Citações Web of Science: 0

Resumo

Motivation: Protein structure modeling can be improved by the use of distance constraints between amino acid residues, provided such data reflects-at least partially-the native tertiary structure of the target system. In fact, only a small subset of the native contact map is necessary to successfully drive the model conformational search, so one important goal is to obtain the set of constraints with the highest true-positive rate, lowest redundancy and greatest amount of information. In this work, we introduce a constraint evaluation and selection method based on the point-biserial correlation coefficient, which utilizes structural information from an ensemble of models to indirectly measure the power of each constraint in biasing the conformational search toward consensus structures. Results: Residue contact maps obtained by direct coupling analysis are systematically improved by means of discriminant analysis, reaching in some cases accuracies often seen only in modern deep-learning-based approaches. When combined with an iterative modeling workflow, the proposed constraint classification optimizes the selection of the constraint set and maximizes the probability of obtaining successful models. The use of discriminant analysis for the valorization of the information of constraint datasets is a general concept with possible applications to other constraint types and modeling problems. Supplementary information: Supplementary data are available at Bioinformatics online. (AU)

• Processo FAPESP: 13/08293-7 - CECC - Centro de Engenharia e Ciências Computacionais
• Beneficiário: Munir Salomao Skaf
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 16/13195-2 - Modelagem da estrutura de proteínas e de complexos protéicos usando dados de espectrometria de massas
• Beneficiário: Allan Jhonathan Ramos Ferrari
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 19/17007-4 - Modelagem de enzimas e complexos proteicos associados com a degradação de celulose
• Beneficiário: Allan Jhonathan Ramos Ferrari
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 10/16947-9 - Estrutura, dinâmica e função em proteínas: simulação computacional e desenvolvimento de algoritmos
• Beneficiário: Leandro Martinez
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 18/14274-9 - Determinação de estruturas de proteínas usando restrições de distância obtidas de experimentos de ligação cruzada: métodos computacionais e aplicações
• Beneficiário: Leandro Martinez
• Modalidade de apoio: Auxílio à Pesquisa - Regular