Exploring the electronic structure of knotted proteins: the case of two ornithine transcarbamylase family.

Knotted proteins Protein electronic structure Quantum chemical descriptors Structural fluctuations

Journal

Journal of molecular modeling
ISSN: 0948-5023
Titre abrégé: J Mol Model
Pays: Germany
ID NLM: 9806569

Informations de publication

Date de publication:
15 Jul 2024
Historique:
received: 31 01 2024
accepted: 06 06 2024
medline: 15 7 2024
pubmed: 15 7 2024
entrez: 15 7 2024
Statut: epublish

Résumé

Geometrical knots are rare structural arrangements in proteins in which the polypeptide chain ties itself into a knot, which is very intriguing due to the uncertainty of their impact on the protein properties. Presently, classical molecular dynamics is the most employed technique in the few studies found on this topic, so any information on how the presence of knots affects the reactivity and electronic properties of proteins is even scarcer. Using the electronic structure methods and quantum chemical descriptors analysis, we found that the same amino-acid residues in the knot core have statistically larger values for the unknotted protein, for both hard-hard and soft-soft interaction descriptors. In addition, we present a computationally feasible protocol, where we show it is possible to separate the contribution of the geometrical knot to the reactivity and other electronic structure properties. In order to investigate these systems, we used PRIMoRDiA, a new software developed by our research group, to explore the electronic structure of biological macromolecules. We evaluated several local quantum chemical descriptors to unveil relevant patterns potentially originating from the presence of the geometrical knot in two proteins, belonging to the ornithine transcarbamylase family. We compared several sampled structures from these two enzymes that are highly similar in both tertiary structure and function, but one of them has a knot whereas the other does not. The sampling was carried out through molecular dynamics simulations using ff14SB force field along 50 ns, and the semiempirical convergence was performed with PM7 Hamiltonian.

Identifiants

pubmed: 39008190
doi: 10.1007/s00894-024-06009-9
pii: 10.1007/s00894-024-06009-9
doi:

Substances chimiques

Ornithine Carbamoyltransferase EC 2.1.3.3

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

265

Subventions

Organisme : Universidade Federal da Paraíba
ID : PIA14864-2021
Organisme : Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
ID : AUXPE1375/2014
Organisme : Conselho Nacional de Desenvolvimento Científico e Tecnológico
ID : 440363/2022-5

Informations de copyright

© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Références

Richardson JS (1977) β-sheet topology and the relatedness of proteins. Nature 268(5620):495–500
Mansfield ML (1994) Are there knots in proteins? Nature Structural Biology 1(4):213–214
doi: 10.1038/nsb0494-213 pubmed: 7656045
Silva JCA, Chaves EJF, Carvalho GAU, Rocha GB (2022) Investigation of the structural dynamics of a knotted protein and its unknotted analog using molecular dynamics. J Mol Model 28(4):108
Hsu S-TD (2016) Protein knotting through concatenation significantly reduces folding stability. Scientific Reports 6(1):1–8
Perlinska AP, Stasiulewicz A, Nawrocka EK, Kazimierczuk K, Setny P, Sulkowska JI (2020) Restriction of s-adenosylmethionine conformational freedom by knotted protein binding sites. PLoS Computational Biology 16(5):1007904
Fonseka HYY, Javidi A, Oliveira LF, Micheletti C, Stan G (2021) Unfolding and translocation of knotted proteins by CLP biological nanomachines: synergistic contribution of primary sequence and topology revealed by molecular dynamics simulations. J Phys Chem B
Virnau P, Mirny LA, Kardar M (2006) Intricate knots in proteins: function and evolution. PLoS Computational Biology 2(9):122
Lua RC, Grosberg AY (2006) Statistics of knots, geometry of conformations, and evolution of proteins. PLoS Computational Biology 2(5):45
Dzubiella J (2009) Sequence-specific size, structure, and stability of tight protein knots. Biophysical journal 96(3):831–839
Mallam AL (2009) How does a knotted protein fold? The FEBS journal 276(2):365–375
Sułkowska JI, Noel JK, Ramírez-Sarmiento CA, Rawdon EJ, Millett KC, Onuchic JN (2013) Knotting pathways in proteins. Biochem Soc Trans 41(2):523–527
Jackson SE, Suma A, Micheletti C (2017) How to fold intricately: using theory and experiments to unravel the properties of knotted proteins. Curr Opin Struct Biol 42:6–14
Sulkowska JI (2020) On folding of entangled proteins: knots, lassos, links and θ-curves. Curr Opin Struct Biol 60:131–141
Lim NC, Jackson SE (2015) Molecular knots in biology and chemistry. J Condens Matter Phys 27(35):354101
Virnau P, Mallam A, Jackson S (2010) Structures and folding pathways of topologically knotted proteins. J Condens Matter Phys 23(3):033101
Faísca PF (2015) Knotted proteins: a tangled tale of structural biology. Comput Struct Biotechnol J 13:459–468
Potestio R, Micheletti C, Orland H (2010) Knotted vs. unknotted proteins: evidence of knot-promoting loops. PLoS Comput Biol 6(7):1000864
Forgan RS, Sauvage J-P, Stoddart JF (2011) Chemical topology: complex molecular knots, links, and entanglements. Chem Rev 111(9):5434–5464
Dabrowski-Tumanski P, Rubach P, Goundaroulis D, Dorier J, Sułkowski P, Millett KC, Rawdon EJ, Stasiak A, Sulkowska JI (2019) Knotprot 2.0: a database of proteins with knots and other entangled structures. Nucleic Acids Res 47(D1):367–375
Jarmolinska AI, Perlinska AP, Runkel R, Trefz B, Ginn HM, Virnau P, Sulkowska JI (2019) Proteins’ knotty problems. J Mol Biol 431(2):244–257
Covino R, Škrbić T, Beccara SA, Faccioli P, Micheletti C (2014) The role of non-native interactions in the folding of knotted proteins: insights from molecular dynamics simulations. Biomolecules 4(1):1–19
Sułkowska JI, Noel JK, Onuchic JN (2012) Energy landscape of knotted protein folding. Proceedings of the National Academy of Sciences 109(44):17783–17788
Paissoni C, Puri S, Wang I, Chen S-Y, Camilloni C, Hsu S-TD (2021) Converging experimental and computational views of the knotting mechanism of a small knotted protein. Biophys J 120(11):2276–2286
Xu Y, Li S, Yan Z, Luo Z, Ren H, Ge B, Huang F, Yue T (2018) Stabilizing effect of inherent knots on proteins revealed by molecular dynamics simulations. Biophys J 115(9):1681–1689
Xu Y, Li S, Yan Z, Ge B, Huang F, Yue T (2019) Revealing cooperation between knotted conformation and dimerization in protein stabilization by molecular dynamics simulations. J Phys Chem Lett 10(19):5815–5822
Perlinska AP, Kalek M, Christian T, Hou Y-M, Sulkowska JI (2020) Mg2+-dependent methyl transfer by a knotted protein: a molecular dynamics simulation and quantum mechanics study. ACS catalysis 10(15):8058–8068
Grillo IB, Urquiza-Carvalho GA, Rocha GB (2020) Primordia: a software to explore reactivity and electronic structure in large biomolecules. J Chem Inf Model 60(12):5885–5890
Grillo IB, Urquiza-Carvalho GA, Rocha GB (2023) Quantum chemical descriptors based on semiempirical methods for large biomolecules. J Chem Phys 158(20)
Geerlings P, De Proft F, Langenaeker W (2003) Conceptual density functional theory Chem rev 103(5):1793–1873 https://doi.org/10.1021/cr990029p
Grillo IB, Urquiza-Carvalho GA, Chaves EJF, Rocha GB (2020) Semiempirical methods do fukui functions: unlocking a modeling framework for biosystems. J Comput Chem
Grillo IB, Urquiza-Carvalho G, Bachega JFR, Rocha GB (2020) Elucidating enzymatic catalysis using fast quantum chemical descriptors. J Chem Inf Model
Grillo IB, Bachega JFR, Timmers LFS, Caceres RA, Souza ON, Field MJ, Rocha GB (2020) Theoretical characterization of the shikimate 5-dehydrogenase reaction from mycobacterium tuberculosis by hybrid qc/mm simulations and quantum chemical descriptors. J Mol Model 26(11):1–12
Rocha RE, Chaves EJ, Fischer PH, Costa LS, Grillo IB, Cruz LE, Guedes FC, Silveira CH, Scotti MT, Camargo AD, et al (2021) A higher flexibility at the sars-cov-2 main protease active site compared to sars-cov and its potentialities for new inhibitor virtual screening targeting multi-conformers. J Biomol Struct Dyn, 1–21
Rocha-Santos A, Chaves EJF, Grillo IB, Freitas AS, Araújo DAM, Rocha GB (2021) Thermochemical and quantum descriptor calculations for gaining insight into ricin toxin a (rta) inhibitors. ACS omega 6(13):8764–8777
Shi D, Yu X, Roth L, Morizono H, Tuchman M, Allewell NM (2006) Structures of n-acetylornithine transcarbamoylase from xanthomonas campestris complexed with substrates and substrate analogs imply mechanisms for substrate binding and catalysis. Proteins: Struct, Funct, Bioinf 64(2):532–542
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242
Case D, Ben-Shalom I, Brozell S, Cerutti D, Cheatham III T, Cruzeiro V, Darden T, Duke R, Ghoreishi D, Gilson M et al (2018) Amber 2018; 2018. University of California, San Francisco
Dolinsky TJ, Nielsen JE, McCammon JA, Baker NA (2004) Pdb2pqr: an automated pipeline for the setup of poisson–boltzmann electrostatics calculations. Nucleic Acids Res 32(suppl_2):665–667
Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C (2015) ff14sb: improving the accuracy of protein side chain and backbone parameters from ff99sb. J Chem Theory Comput 11(8):3696–3713
Ryckaert J-P, Ciccotti G, Berendsen HJ (1977) Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys 23(3):327–341
Feller SE, Zhang Y, Pastor RW, Brooks BR (1995) Constant pressure molecular dynamics simulation: the langevin piston method. J Chem Phys 103(11):4613–4621
Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with namd. J Comput Chem 26(16):1781–1802
Stewart JJ (2013) Optimization of parameters for semiempirical methods vi: more modifications to the nddo approximations and re-optimization of parameters. J Mol Model 19(1):1–32
Stewart JJ (1996) Application of localized molecular orbitals to the solution of semiempirical self-consistent field equations. Int J Quantum Chem 58(2):133–146
Parr RG, Donnelly RA, Levy M, Palke WE (1978) Electronegativity: the density functional viewpoint. J Chem Phys 68(8):3801–3807
Yang W, Parr RG, Pucci R (1984) Electron density, kohn–sham frontier orbitals, and fukui functions. J Chem Phys 81(6):2862–2863
Martínez-Araya JI (2015) Why is the dual descriptor a more accurate local reactivity descriptor than fukui functions? J Math Chem 53(2):451–465
Fukushima K, Wada M, Sakurai M (2008) An insight into the general relationship between the three dimensional structures of enzymes and their electronic wave functions: implication for the prediction of functional sites of enzymes. Proteins: Struct, Funct, Bioinf 71(4):1940–1954
Khandogin J, York DM (2004) Quantum descriptors for biological macromolecules from linear-scaling electronic structure methods. Proteins: Struct Funct 56(4):724–737 https://doi.org/10.1002/prot.20171
Klopman G (1968) Chemical reactivity and the concept of charge-and frontier-controlled reactions. J Am Chem Soc 90(2):223–234
Roy RK, Krishnamurti S, Geerlings P, Pal S (1998) Local softness and hardness based reactivity descriptors for predicting intra- and intermolecular reactivity sequences: carbonyl compounds. J Phys Chem A 5639(97):3746–3755
Chamorro E, Duque-Noreña M, Pérez P (2009) A comparison between theoretical and experimental models of electrophilicity and nucleophilicity. J Mol Struct: THEOCHEM 896(1-3):73–79
Gál T, Geerlings P, De Proft F, Torrent-Sucarrat M (2011) A new approach to local hardness. Phys Chem Chem Phys 13(33):15003–15 https://doi.org/10.1039/c1cp21213c
Berkowitz M, Ghosh SK, Parr RG (1985) On the concept of local hardness in chemistry. J Am Chem Soc 107(24):6811–6814
Cárdenas C, Tiznado W, Ayers PW, Fuentealba P (2011) The fukui potential and the capacity of charge and the global hardness of atoms. J Phys Chem A 115(11):2325–2331
Meneses L, Tiznado W, Contreras R, Fuentealba P (2004) A proposal for a new local hardness as selectivity index. Chem Phys Lett 383(1-2):181–187
Henzler-Wildman K, Kern D (2007) Dynamic personalities of proteins. Nature 450(7172):964–972
McGeagh JD, Ranaghan KE, Mulholland AJ (2011) Protein dynamics and enzyme catalysis: insights from simulations. Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics 1814(8):1077–1092
Ishima R, Torchia DA (2000) Protein dynamics from nmr. Nat Struct Biol 7(9):740–743
Healy EF, Flores R, Lynch VM, Toledo S (2020) Protein dynamics of [cu-zn] superoxide dismutase (sod1): How protein motions at the global and local levels impact the reactivity of sod1. J Inorg Biochem 210:111161

Auteurs

José Cícero Alves Silva (JC)

Department of Chemistry, Federal University of Paraíba, Cid. Universitária, João Pessoa, 58051-900, Paraíba, Brazil.

Igor Barden Grillo (I)

Department of Chemistry, Federal University of Paraíba, Cid. Universitária, João Pessoa, 58051-900, Paraíba, Brazil.

Gabriel A Urquiza-Carvalho (G)

Department of Chemistry, Federal University of Pernambuco, Cid. Universitária, Recife, 50670-901, Pernambuco, Brazil.

Gerd Bruno Rocha (G)

Department of Chemistry, Federal University of Paraíba, Cid. Universitária, João Pessoa, 58051-900, Paraíba, Brazil. gbr@quimica.ufpb.br.

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Classifications MeSH