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Modeling Peptide-Protein Interactions by a Logo-Based Method: Application in Peptide-HLA Binding Predictions.
Doytchinova, Irini; Atanasova, Mariyana; Fernandez, Antonio; Moreno, F Javier; Koning, Frits; Dimitrov, Ivan.
Afiliación
  • Doytchinova I; Faculty of Pharmacy, Medical University of Sofia, 1000 Sofia, Bulgaria.
  • Atanasova M; Faculty of Pharmacy, Medical University of Sofia, 1000 Sofia, Bulgaria.
  • Fernandez A; European Food Safety Authority, 43126 Parma, Italy.
  • Moreno FJ; Instituto de Investigación en Ciencias de la Alimentación (CIAL), CSIC-UAM, CEI (UAM+CSIC), Nicolás Cabrera, 9, 28049 Madrid, Spain.
  • Koning F; Department of Immunohematology and Blood Transfusion, Leiden University Medical Centre, 2333 ZA Leiden, The Netherlands.
  • Dimitrov I; Faculty of Pharmacy, Medical University of Sofia, 1000 Sofia, Bulgaria.
Molecules ; 29(2)2024 Jan 05.
Article en En | MEDLINE | ID: mdl-38257197
ABSTRACT
Peptide-protein interactions form a cornerstone in molecular biology, governing cellular signaling, structure, and enzymatic activities in living organisms. Improving computational models and experimental techniques to describe and predict these interactions remains an ongoing area of research. Here, we present a computational method for peptide-protein interactions' description and prediction based on leveraged amino acid frequencies within specific binding cores. Utilizing normalized frequencies, we construct quantitative matrices (QMs), termed 'logo models' derived from sequence logos. The method was developed to predict peptide binding to HLA-DQ2.5 and HLA-DQ8.1 proteins associated with susceptibility to celiac disease. The models were validated by more than 17,000 peptides demonstrating their efficacy in discriminating between binding and non-binding peptides. The logo method could be applied to diverse peptide-protein interactions, offering a versatile tool for predictive analysis in molecular binding studies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos / Enfermedad Celíaca Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Bulgaria Pais de publicación: Suiza
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos / Enfermedad Celíaca Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Bulgaria Pais de publicación: Suiza