Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
Levin, Nayara Maria Bernhardt
 |
| Orientador(a): |
Azevedo Junior, Walter Filgueira de
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Pontifícia Universidade Católica do Rio Grande do Sul
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Biologia Celular e Molecular
|
| Departamento: |
Faculdade de Biociências
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tede2.pucrs.br/tede2/handle/tede/7146
|
Resumo: |
Cyclin-dependent kinases (CDKs) comprise an interesting biological system for development of docking protocols and scoring functions, due to the abundance of complexed structures for which binding affinity data is available. Here, we report application of an integrated computational approach to carry out docking against a data set composed of 176 structures of CDK in complex with inhibitors. To our knowledge, this is the largest data set of CDK crystallographic structures submitted to molecular docking simulation. Our results indicate that the proposed strategy for docking against CDKs generates poses with docking root-mean square deviation below 2.0 Å for most of the structures in the data set. In addition, we describe the development of scoring functions tailored to CDKs. Statistical analysis of pre-docking and re-docking results, using the proposed scoring functions for CDKs, indicates that these functions are able to predict affinity with better performance when compared with previously reported benchmarks for CDKs. |
