Localization of Energetic Frustration in Proteins.


Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2022
Historique:
entrez: 30 11 2021
pubmed: 1 12 2021
medline: 19 1 2022
Statut: ppublish

Résumé

We present a detailed heuristic method to quantify the degree of local energetic frustration manifested by protein molecules. Current applications are realized in computational experiments where a protein structure is visualized highlighting the energetic conflicts or the concordance of the local interactions in that structure. Minimally frustrated linkages highlight the stable folding core of the molecule. Sites of high local frustration, in contrast, often indicate functionally relevant regions such as binding, active, or allosteric sites.

Identifiants

pubmed: 34845622
doi: 10.1007/978-1-0716-1716-8_22
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

387-398

Informations de copyright

© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Références

Vannimenus J, Toulouse G (1977) Theory of the frustration effect. II. Ising spins on a square lattice. J Phys C: Solid State Phys 10:L537–L542
doi: 10.1088/0022-3719/10/18/008
Wolynes PG (2015) Evolution, energy landscapes and the paradoxes of protein folding. Biochimie 119:218–230
doi: 10.1016/j.biochi.2014.12.007
Wei G, Xi W, Nussinov R, Ma B (2016) Protein ensembles: how does nature harness thermodynamic fluctuations for life? The diverse functional roles of conformational ensembles in the cell. Chem Rev 116:6516–6551
doi: 10.1021/acs.chemrev.5b00562
Bryngelson JD, Wolynes PG (1987) Spin glasses and the statistical mechanics of protein folding. Proc Natl Acad Sci U S A 84:7524–7528
doi: 10.1073/pnas.84.21.7524
Tzul FO, Vasilchuk D, Makhatadze GI (2017) Evidence for the principle of minimal frustration in the evolution of protein folding landscapes. Proc Natl Acad Sci U S A 114:E1627–E1632
doi: 10.1073/pnas.1613892114
Lubchenko V (2008) Competing interactions create functionality through frustration. Proc Natl Acad Sci U S A 105:10635–10636
doi: 10.1073/pnas.0805716105
Ferreiro DU, Komives EA, Wolynes PG (2014) Frustration in biomolecules. Q Rev Biophys 47:285–363
doi: 10.1017/S0033583514000092
Panchenko AR, Luthey-Schulten Z, Wolynes PG (1996) Foldons, protein structural modules, and exons. Proc Natl Acad Sci U S A 93:2008–2013
doi: 10.1073/pnas.93.5.2008
Ferreiro DU, Hegler JA, Komives EA, Wolynes PG (2007) Localizing frustration in native proteins and protein assemblies. Proc Natl Acad Sci U S A 104:19819–19824
doi: 10.1073/pnas.0709915104
Parra RG, Schafer NP, Radusky LG, Tsai M-Y, Brenda Guzovsky A, Wolynes PG, Ferreiro DU (2016) Protein Frustratometer 2: a tool to localize energetic frustration in protein molecules, now with electrostatics. Nucleic Acids Res 44:W356–W360
doi: 10.1093/nar/gkw304
Davtyan A, Zheng W, Schafer N, Wolynes P, Papoian G (2012) AWSEM-MD: coarse-grained protein structure prediction using physical potentials and Bioinformatically based local structure biasing. Biophys J 102:619a
doi: 10.1016/j.bpj.2011.11.3373
Chen M, Chen X, Schafer NP, Clementi C, Komives EA, Ferreiro DU, Wolynes PG (2020) Surveying biomolecular frustration at atomic resolution. Nat Commun 11(1):5944
doi: 10.1038/s41467-020-19560-9
Berman HM (2000) The Protein Data Bank. Nucleic Acids Res 28:235–242
doi: 10.1093/nar/28.1.235
Bank RPD RCSB PDB. https://www.rcsb.org/pdb/static.do?p=software/software_links/analysis_and_verification.html. Accessed 16 Dec 2017
Sippl MJ, Wiederstein M (2008) A note on difficult structure alignment problems. Bioinformatics 24:426–427
doi: 10.1093/bioinformatics/btm622
Kurplus M, McCammon JA (1983) Dynamics of proteins: elements and function. Annu Rev Biochem 52:263–300
doi: 10.1146/annurev.bi.52.070183.001403
Lindorff-Larsen K, Maragakis P, Piana S, Eastwood MP, Dror RO, Shaw DE (2012) Systematic validation of protein force fields against experimental data. PLoS One 7:e32131
doi: 10.1371/journal.pone.0032131
Pan AC, Weinreich TM, Piana S, Shaw DE (2016) Demonstrating an order-of-magnitude sampling enhancement in molecular dynamics simulations of complex protein systems. J Chem Theory Comput 12:1360–1367
doi: 10.1021/acs.jctc.5b00913
Schafer NP, Kim BL, Zheng W, Wolynes PG (2014) Learning to fold proteins using energy landscape theory. Isr J Chem 54:1311–1337
doi: 10.1002/ijch.201300145
Capelli R, Paissoni C, Sormanni P, Tiana G (2014) Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale. J Chem Phys 140:195101
doi: 10.1063/1.4876219
Krick T, Verstraete N, Alonso LG, Shub DA, Ferreiro DU, Shub M, Sánchez IE (2014) Amino acid metabolism conflicts with protein diversity. Mol Biol Evol 31:2905–2912
doi: 10.1093/molbev/msu228
Plotkin SS, Wang J, Wolynes PG (1996) Correlated energy landscape model for finite, random heteropolymers. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics 53:6271–6296
pubmed: 9964988
Onuchic JN, Wolynes PG, Luthey-Schulten Z, Socci ND (1995) Toward an outline of the topography of a realistic protein-folding funnel. Proc Natl Acad Sci U S A 92:3626–3630
doi: 10.1073/pnas.92.8.3626
Luthey-Schulten Z, Ramirez BE, Wolynes PG (1995) Helix-coil, liquid crystal, and spin glass transitions of a collapsed Heteropolymer. J Phys Chem 99:2177–2185
doi: 10.1021/j100007a057
Chowdary PD, Gruebele M (2009) Molecules: what kind of a bag of atoms? J Phys Chem A 113:13139–13143
doi: 10.1021/jp903104p
Ferreiro DU, Komives EA, Wolynes PG (2017) Frustration, function and folding. Curr Opin Struct Biol 48:68–73
doi: 10.1016/j.sbi.2017.09.006
Parra RG, Gonzalo Parra R, Espada R, Verstraete N, Ferreiro DU (2015) Structural and energetic characterization of the Ankyrin repeat protein family. PLoS Comput Biol 11:e1004659
doi: 10.1371/journal.pcbi.1004659
Brenner S (2010) Sequences and consequences. Philos Trans R Soc Lond Ser B Biol Sci 365:207–212
doi: 10.1098/rstb.2009.0221
Schwede T (2013) Protein modelling: what happened to the “protein structure gap”? Structure 21:1531–1540
doi: 10.1016/j.str.2013.08.007
Papoian GA, Ulander J, Wolynes PG (2003) Role of water mediated interactions in protein−protein recognition landscapes. J Am Chem Soc 125:9170–9178
doi: 10.1021/ja034729u

Auteurs

A Brenda Guzovsky (AB)

Protein Physiology Lab, Facultad de Ciencias Exactas y Naturales-Universidad de Buenos Aires. IQUIBICEN/CONICET. Intendente Güiraldes 2160 - Ciudad Universitaria - C1428EGA, Buenos Aires, Argentina.

Nicholas P Schafer (NP)

Department of Chemistry, Rice University, Houston, TX, USA.
Department of Physics, Rice University, Houston, TX, USA.
Department of Biosciences, Rice University, Houston, TX, USA.
Center for Theoretical Biological Physics, Rice University, Houston, TX, USA.

Peter G Wolynes (PG)

Department of Chemistry, Rice University, Houston, TX, USA.
Department of Physics, Rice University, Houston, TX, USA.
Department of Biosciences, Rice University, Houston, TX, USA.
Center for Theoretical Biological Physics, Rice University, Houston, TX, USA.

Diego U Ferreiro (DU)

Protein Physiology Lab, Facultad de Ciencias Exactas y Naturales-Universidad de Buenos Aires. IQUIBICEN/CONICET. Intendente Güiraldes 2160 - Ciudad Universitaria - C1428EGA, Buenos Aires, Argentina. diegulise@gmail.com.

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