Literature DB >> 31209948

Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge.

Castrense Savojardo1, Maria Petrosino2, Giulia Babbi1, Samuele Bovo1, Carles Corbi-Verge3, Rita Casadio1,4, Piero Fariselli5, Lukas Folkman6, Aditi Garg7, Mostafa Karimi8, Panagiotis Katsonis9, Philip M Kim3,10,11, Olivier Lichtarge9,12,13,14, Pier Luigi Martelli1, Alessandra Pasquo15, Debnath Pal7, Yang Shen8, Alexey V Strokach11, Paola Turina16, Yaoqi Zhou6,17, Gaia Andreoletti18, Steven E Brenner18, Roberta Chiaraluce2, Valerio Consalvi2, Emidio Capriotti16.   

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 ( Δ Δ G H 2 O ) . 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 Δ Δ G H 2 O 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.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  free energy change; machine learning; protein folding; protein stability; single amino acid variant

Year:  2019        PMID: 31209948      PMCID: PMC6744327          DOI: 10.1002/humu.23843

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  18 in total

1.  Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations.

Authors:  Raphael Guerois; Jens Erik Nielsen; Luis Serrano
Journal:  J Mol Biol       Date:  2002-07-05       Impact factor: 5.469

2.  GROMACS: fast, flexible, and free.

Authors:  David Van Der Spoel; Erik Lindahl; Berk Hess; Gerrit Groenhof; Alan E Mark; Herman J C Berendsen
Journal:  J Comput Chem       Date:  2005-12       Impact factor: 3.376

Review 3.  Computational and theoretical methods for protein folding.

Authors:  Mario Compiani; Emidio Capriotti
Journal:  Biochemistry       Date:  2013-11-21       Impact factor: 3.162

4.  INPS-MD: a web server to predict stability of protein variants from sequence and structure.

Authors:  Castrense Savojardo; Piero Fariselli; Pier Luigi Martelli; Rita Casadio
Journal:  Bioinformatics       Date:  2016-04-10       Impact factor: 6.937

5.  Frataxin participates to the hypoxia-induced response in tumors.

Authors:  I Guccini; D Serio; I Condò; A Rufini; B Tomassini; A Mangiola; G Maira; C Anile; D Fina; F Pallone; M P Mongiardi; A Levi; N Ventura; R Testi; F Malisan
Journal:  Cell Death Dis       Date:  2011-02-24       Impact factor: 8.469

Review 6.  Friedreich ataxia.

Authors:  Massimo Pandolfo
Journal:  Arch Neurol       Date:  2008-10

7.  Dynamics, stability and iron-binding activity of frataxin clinical mutants.

Authors:  Ana R Correia; Chiara Pastore; Salvatore Adinolfi; Annalisa Pastore; Cláudio M Gomes
Journal:  FEBS J       Date:  2008-07       Impact factor: 5.542

8.  I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.

Authors:  Emidio Capriotti; Piero Fariselli; Rita Casadio
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

9.  A formal perturbation equation between genotype and phenotype determines the Evolutionary Action of protein-coding variations on fitness.

Authors:  Panagiotis Katsonis; Olivier Lichtarge
Journal:  Genome Res       Date:  2014-09-12       Impact factor: 9.043

10.  Human Frataxin Folds Via an Intermediate State. Role of the C-Terminal Region.

Authors:  Santiago E Faraj; Rodolfo M González-Lebrero; Ernesto A Roman; Javier Santos
Journal:  Sci Rep       Date:  2016-02-09       Impact factor: 4.379

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  4 in total

1.  Are machine learning based methods suited to address complex biological problems? Lessons from CAGI-5 challenges.

Authors:  Castrense Savojardo; Giulia Babbi; Samuele Bovo; Emidio Capriotti; Pier Luigi Martelli; Rita Casadio
Journal:  Hum Mutat       Date:  2019-06-18       Impact factor: 4.878

2.  Turning Failures into Applications: The Problem of Protein ΔΔG Prediction.

Authors:  Rita Casadio; Castrense Savojardo; Piero Fariselli; Emidio Capriotti; Pier Luigi Martelli
Journal:  Methods Mol Biol       Date:  2022

3.  CAGI5: Objective performance assessments of predictions based on the Evolutionary Action equation.

Authors:  Panagiotis Katsonis; Olivier Lichtarge
Journal:  Hum Mutat       Date:  2019-08-07       Impact factor: 4.878

4.  SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability.

Authors:  Gen Li; Shailesh Kumar Panday; Emil Alexov
Journal:  Int J Mol Sci       Date:  2021-01-09       Impact factor: 5.923

  4 in total

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