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Hum Mutat. 2019 Sep;40(9):1392-1399. doi: 10.1002/humu.23843. Epub 2019 Jul 12.

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

Author information

1
Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
2
Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Roma, Roma, Italy.
3
Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
4
Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies (IBIOM), Italian National Research Council (CNR), Bari, Italy.
5
Department of Medical Sciences, University of Torino, Torino, Italy.
6
School of Information and Communication Technology, Griffith University, Southport, Queensland, Australia.
7
Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru, India.
8
Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas.
9
Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.
10
Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
11
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
12
Department of Biochemistry & Molecular Biology, Baylor College of Medicine, Houston, Texas.
13
Department of Pharmacology, Baylor College of Medicine, Houston, Texas.
14
Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, Texas.
15
Diagnostics and Metrology Laboratory, FSN-TECFIS-DIM, ENEA CR Frascati, Frascati, Italy.
16
Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.
17
Institute for Glycomics, Griffith University, Southport, Queensland, Australia.
18
Department of Plant and Microbial Biology, University of California, Berkeley, California.

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.

KEYWORDS:

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

PMID:
31209948
PMCID:
PMC6744327
[Available on 2020-09-01]
DOI:
10.1002/humu.23843

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