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Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge.
Savojardo, Castrense; Petrosino, Maria; Babbi, Giulia; Bovo, Samuele; Corbi-Verge, Carles; Casadio, Rita; Fariselli, Piero; Folkman, Lukas; Garg, Aditi; Karimi, Mostafa; Katsonis, Panagiotis; Kim, Philip M; Lichtarge, Olivier; Martelli, Pier Luigi; Pasquo, Alessandra; Pal, Debnath; Shen, Yang; Strokach, Alexey V; Turina, Paola; Zhou, Yaoqi; Andreoletti, Gaia; Brenner, Steven E; Chiaraluce, Roberta; Consalvi, Valerio; Capriotti, Emidio.
Afiliação
  • Savojardo C; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
  • Petrosino M; Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Roma, Roma, Italy.
  • Babbi G; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
  • Bovo S; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
  • Corbi-Verge C; Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
  • Casadio R; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
  • Fariselli P; Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies (IBIOM), Italian National Research Council (CNR), Bari, Italy.
  • Folkman L; Department of Medical Sciences, University of Torino, Torino, Italy.
  • Garg A; School of Information and Communication Technology, Griffith University, Southport, Queensland, Australia.
  • Karimi M; Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru, India.
  • Katsonis P; Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas.
  • Kim PM; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.
  • Lichtarge O; Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
  • Martelli PL; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
  • Pasquo A; Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
  • Pal D; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.
  • Shen Y; Department of Biochemistry & Molecular Biology, Baylor College of Medicine, Houston, Texas.
  • Strokach AV; Department of Pharmacology, Baylor College of Medicine, Houston, Texas.
  • Turina P; Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, Texas.
  • Zhou Y; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
  • Andreoletti G; Diagnostics and Metrology Laboratory, FSN-TECFIS-DIM, ENEA CR Frascati, Frascati, Italy.
  • Brenner SE; Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru, India.
  • Chiaraluce R; Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas.
  • Consalvi V; Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
  • Capriotti E; Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
Hum Mutat ; 40(9): 1392-1399, 2019 09.
Article em En | MEDLINE | ID: mdl-31209948
ABSTRACT
Frataxin (FXN) is a highly conserved protein found in prokaryotes and eukaryotes that is required for efficient regulation of cellular iron homeostasis. Experimental evidence associates amino acid substitutions of the FXN to Friedreich Ataxia, a neurodegenerative disorder. Recently, new thermodynamic experiments have been performed to study the impact of somatic variations identified in cancer tissues on protein stability. The Critical Assessment of Genome Interpretation (CAGI) data provider at the University of Rome measured the unfolding free energy of a set of variants (FXN challenge data set) with far-UV circular dichroism and intrinsic fluorescence spectra. These values have been used to calculate the change in unfolding free energy between the variant and wild-type proteins at zero concentration of denaturant (ΔΔGH2O) . The FXN challenge data set, composed of eight amino acid substitutions, was used to evaluate the performance of the current computational methods for predicting the ΔΔGH2O value associated with the variants and to classify them as destabilizing and not destabilizing. For the fifth edition of CAGI, six independent research groups from Asia, Australia, Europe, and North America submitted 12 sets of predictions from different approaches. In this paper, we report the results of our assessment and discuss the limitations of the tested algorithms.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Substituição de Aminoácidos / Proteínas de Ligação ao Ferro Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Hum Mutat Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Substituição de Aminoácidos / Proteínas de Ligação ao Ferro Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Hum Mutat Ano de publicação: 2019 Tipo de documento: Article