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Exploring the effects of missense mutations on protein thermodynamics through structure-based approaches: findings from the CAGI6 challenges.
Rodrigues, Carlos H M; Portelli, Stephanie; Ascher, David B.
Afiliação
  • Rodrigues CHM; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.
  • Portelli S; School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, QLD, 4072, Australia.
  • Ascher DB; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.
Hum Genet ; 2024 Jan 16.
Article em En | MEDLINE | ID: mdl-38227011
ABSTRACT
Missense mutations are known contributors to diverse genetic disorders, due to their subtle, single amino acid changes imparted on the resultant protein. Because of this, understanding the impact of these mutations on protein stability and function is crucial for unravelling disease mechanisms and developing targeted therapies. The Critical Assessment of Genome Interpretation (CAGI) provides a valuable platform for benchmarking state-of-the-art computational methods in predicting the impact of disease-related mutations on protein thermodynamics. Here we report the performance of our comprehensive platform of structure-based computational approaches to evaluate mutations impacting protein structure and function on 3 challenges from CAGI6 Calmodulin, MAPK1 and MAPK3. Our stability predictors have achieved correlations of up to 0.74 and AUCs of 1 when predicting changes in ΔΔG for MAPK1 and MAPK3, respectively, and AUC of up to 0.75 in the Calmodulin challenge. Overall, our study highlights the importance of structure-based approaches in understanding the effects of missense mutations on protein thermodynamics. The results obtained from the CAGI6 challenges contribute to the ongoing efforts to enhance our understanding of disease mechanisms and facilitate the development of personalised medicine approaches.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article