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Prediction and redesign of protein-protein interactions.
Lua, Rhonald C; Marciano, David C; Katsonis, Panagiotis; Adikesavan, Anbu K; Wilkins, Angela D; Lichtarge, Olivier.
Afiliación
  • Lua RC; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
  • Marciano DC; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
  • Katsonis P; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
  • Adikesavan AK; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
  • Wilkins AD; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, TX 77030, USA.
  • Lichtarge O; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Computational and Integrative Biomedical Research Center, Baylor College of Med
Prog Biophys Mol Biol ; 116(2-3): 194-202, 2014.
Article en En | MEDLINE | ID: mdl-24878423
ABSTRACT
Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas / Biología Computacional / Mapeo de Interacción de Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Prog Biophys Mol Biol Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas / Biología Computacional / Mapeo de Interacción de Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Prog Biophys Mol Biol Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos