Prediction of Protein Mutational Free Energy: Benchmark and Sampling Improvements Increase Classification Accuracy.
mutation
mutation free energy
protein
protein design and engineering
thermodynamics
Journal
Frontiers in bioengineering and biotechnology
ISSN: 2296-4185
Titre abrégé: Front Bioeng Biotechnol
Pays: Switzerland
ID NLM: 101632513
Informations de publication
Date de publication:
2020
2020
Historique:
received:
05
05
2020
accepted:
16
09
2020
entrez:
2
11
2020
pubmed:
3
11
2020
medline:
3
11
2020
Statut:
epublish
Résumé
Software to predict the change in protein stability upon point mutation is a valuable tool for a number of biotechnological and scientific problems. To facilitate the development of such software and provide easy access to the available experimental data, the ProTherm database was created. Biases in the methods and types of information collected has led to disparity in the types of mutations for which experimental data is available. For example, mutations to alanine are hugely overrepresented whereas those involving charged residues, especially from one charged residue to another, are underrepresented. ProTherm subsets created as benchmark sets that do not account for this often underrepresent tense certain mutational types. This issue introduces systematic biases into previously published protocols' ability to accurately predict the change in folding energy on these classes of mutations. To resolve this issue, we have generated a new benchmark set with these problems corrected. We have then used the benchmark set to test a number of improvements to the point mutation energetics tools in the Rosetta software suite.
Identifiants
pubmed: 33134287
doi: 10.3389/fbioe.2020.558247
pmc: PMC7579412
doi:
Types de publication
Journal Article
Langues
eng
Pagination
558247Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM123089
Pays : United States
Informations de copyright
Copyright © 2020 Frenz, Lewis, King, DiMaio, Park and Song.
Références
Bioinformatics. 2016 Oct 1;32(19):2936-46
pubmed: 27318206
J Mol Biol. 2005 Mar 18;347(1):203-27
pubmed: 15733929
PLoS One. 2015 Sep 11;10(9):e0138022
pubmed: 26361227
PLoS One. 2015 Sep 03;10(9):e0130433
pubmed: 26335248
Elife. 2016 Sep 26;5:
pubmed: 27669148
Protein Eng Des Sel. 2009 Sep;22(9):553-60
pubmed: 19561092
Curr Opin Struct Biol. 1995 Apr;5(2):229-35
pubmed: 7648326
J Med Chem. 2001 Oct 11;44(21):3417-23
pubmed: 11585447
Proc Int Conf Intell Syst Mol Biol. 1995;3:81-8
pubmed: 7584470
Nat Methods. 2009 Jan;6(1):3-4
pubmed: 19116609
Proteins. 2011 Mar;79(3):830-8
pubmed: 21287615
J Mol Biol. 1996 Apr 19;257(5):1112-26
pubmed: 8632471
Proteins. 2000 Nov 15;41(3):385-97
pubmed: 11025549
Biochim Biophys Acta. 1975 Oct 20;405(2):442-51
pubmed: 1180967
Methods Enzymol. 2011;487:545-74
pubmed: 21187238
J Chem Theory Comput. 2016 Dec 13;12(12):6201-6212
pubmed: 27766851
J Mol Biol. 2002 Jul 5;320(2):369-87
pubmed: 12079393
Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W306-10
pubmed: 15980478
Nat Protoc. 2009;4(7):1073-81
pubmed: 19561590