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Combating mutations in genetic disease and drug resistance: understanding molecular mechanisms to guide drug design.
Albanaz, Amanda T S; Rodrigues, Carlos H M; Pires, Douglas E V; Ascher, David B.
Afiliação
  • Albanaz ATS; a Centro de Pesquisas René Rachou, FIOCRUZ , Belo Horizonte , MG , Brazil.
  • Rodrigues CHM; b Department of Biochemistry and Immunology , Universidade Federal de Minas Gerais , Belo Horizonte , Minas Gerais , Brazil.
  • Pires DEV; a Centro de Pesquisas René Rachou, FIOCRUZ , Belo Horizonte , MG , Brazil.
  • Ascher DB; b Department of Biochemistry and Immunology , Universidade Federal de Minas Gerais , Belo Horizonte , Minas Gerais , Brazil.
Expert Opin Drug Discov ; 12(6): 553-563, 2017 Jun.
Article em En | MEDLINE | ID: mdl-28490289
INTRODUCTION: Mutations introduce diversity into genomes, leading to selective changes and driving evolution. These changes have contributed to the emergence of many of the current major health concerns of the 21st century, from the development of genetic diseases and cancers to the rise and spread of drug resistance. The experimental systematic testing of all mutations in a system of interest is impractical and not cost-effective, which has created interest in the development of computational tools to understand the molecular consequences of mutations to aid and guide rational experimentation. Areas covered: Here, the authors discuss the recent development of computational methods to understand the effects of coding mutations to protein function and interactions, particularly in the context of the 3D structure of the protein. Expert opinion: While significant progress has been made in terms of innovative tools to understand and quantify the different range of effects in which a mutation or a set of mutations can give rise to a phenotype, a great gap still exists when integrating these predictions and drawing causality conclusions linking variants. This often requires a detailed understanding of the system being perturbed. However, as part of the drug development process it can be used preemptively in a similar fashion to pharmacokinetics predictions, to guide development of therapeutics to help guide the design and analysis of clinical trials, patient treatment and public health policy strategies.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Desenho de Fármacos / Doenças Genéticas Inatas / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Desenho de Fármacos / Doenças Genéticas Inatas / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article