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Predicting the stability of homotrimeric and heterotrimeric collagen helices.
Walker, Douglas R; Hulgan, Sarah A H; Peterson, Caroline M; Li, I-Che; Gonzalez, Kevin J; Hartgerink, Jeffrey D.
Afiliação
  • Walker DR; Department of Chemistry, Rice University, Houston, TX, USA.
  • Hulgan SAH; Department of Chemistry, Rice University, Houston, TX, USA.
  • Peterson CM; Department of Chemistry, Rice University, Houston, TX, USA.
  • Li IC; Department of Chemistry, Rice University, Houston, TX, USA.
  • Gonzalez KJ; Department of Chemistry, Rice University, Houston, TX, USA.
  • Hartgerink JD; Department of Chemistry, Rice University, Houston, TX, USA. jdh@rice.edu.
Nat Chem ; 13(3): 260-269, 2021 03.
Article em En | MEDLINE | ID: mdl-33589786
ABSTRACT
Robust methods for predicting thermal stabilities of collagen triple helices are critical for understanding natural structure and stability in the collagen family of proteins and also for designing synthetic peptides mimicking these essential proteins. In this work, we determine the relative stability imparted on the collagen triple helix by single amino acids and interactions between amino acid pairs. Using this analysis, we create a comprehensive algorithm, SCEPTTr, for predicting melting temperatures of synthetic triple helices. Critically, our algorithm is compatible with every natural amino acid, can evaluate both homotrimers and heterotrimers, and accounts for all possible helix compositions and registers, including non-canonically staggered helices. We test and optimize our algorithm against 431 published collagen triple helices to demonstrate the quality of our predictive system. Finally, we use this algorithm to successfully guide the design of an ABC heterotrimer possessing high assembly specificity.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Colágeno Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nat Chem Assunto da revista: QUIMICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Colágeno Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nat Chem Assunto da revista: QUIMICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos