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Protein & Peptide Letters

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ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

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Research Article

Thermostability of Lipase A and Dynamic Communication Based on Residue Interaction Network

Author(s): Qian Xia and Yanrui Ding*

Volume 26, Issue 9, 2019

Page: [702 - 716] Pages: 15

DOI: 10.2174/0929866526666190617091812

Price: $65

Abstract

Objective: Dynamic communication caused by mutation affects protein stability. The main objective of this study is to explore how mutations affect communication and to provide further insight into the relationship between heat resistance and signal propagation of Bacillus subtilis lipase (Lip A).

Methods: The relationship between dynamic communication and Lip A thermostability is studied by long-time MD simulation and residue interaction network. The Dijkstra algorithm is used to get the shortest path of each residue pair. Subsequently, time-series frequent paths and spatio-temporal frequent paths are mined through an Apriori-like algorithm.

Results: Time-series frequent paths show that the communication between residue pairs, both in wild-type lipase (WTL) and mutant 6B, becomes chaotic with an increase in temperature; however, more residues in 6B can maintain stable communication at high temperature, which may be associated with the structural rigidity. Furthermore, spatio-temporal frequent paths reflect the interactions among secondary structures. For WTL at 300K, β7, αC, αB, the longest loop, αA and αF contact frequently. The 310-helix between β3 and αA is penetrated by spatio-temporal frequent paths. At 400K, only αC can be frequently transmitted. For 6B, when at 300K, αA and αF are in more tight contact by spatio-temporal frequent paths though I157M and N166Y. Moreover, the rigidity of the active site His156 and the C-terminal of Lip A are increased, as reflected by the spatio-temporal frequent paths. At 400K, αA and αF, 310-helix between β3 and αA, the longest loop, and the loop where the active site Asp133 is located can still maintain stable communication.

Conclusion: From the perspective of residue dynamic communication, it is obviously found that mutations cause changes in interactions between secondary structures and enhance the rigidity of the structure, contributing to the thermal stability and functional activity of 6B.

Keywords: Lipase thermostability, dynamic residue interaction network, communication path, mutation, structural rigidity, frequent, time-series frequent paths.

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[1]
Jaeger, K-E.; Reetz, M.T. Microbial lipases form versatile tools for biotechnology. Trends Biotechnol., 1998, 16(9), 396-403.
[http://dx.doi.org/10.1016/S0167-7799(98)01195-0] [PMID: 9744114]
[2]
Jaeger, K.E.; Dijkstra, B.W.; Reetz, M.T. Bacterial biocatalysts: molecular biology, three-dimensional structures, and biotechno-logical applications of lipases. Annu. Rev. Microbiol., 1999, 53, 315-351.
[http://dx.doi.org/10.1146/annurev.micro.53.1.315] [PMID: 10547694]
[3]
Kamal, M.Z.; Ahmad, S.; Molugu, T.R.; Vijayalakshmi, A.; Deshmukh, M.V.; Sankaranarayanan, R.; Rao, N.M. In vitro evolved non-aggregating and thermostable lipase: structural and thermodynamic investigation. J. Mol. Biol., 2011, 413(3), 726-741.
[http://dx.doi.org/10.1016/j.jmb.2011.09.002] [PMID: 21925508]
[4]
Acharya, P.; Rajakumara, E.; Sankaranarayanan, R.; Rao, N.M. Structural basis of selection and thermostability of laboratory evolved Bacillus subtilis lipase. J. Mol. Biol., 2004, 341(5), 1271-1281.
[http://dx.doi.org/10.1016/j.jmb.2004.06.059] [PMID: 15321721]
[5]
Ahmad, S.; Rao, N.M. Thermally denatured state determines refolding in lipase: mutational analysis. Protein Sci., 2009, 18(6), 1183-1196.
[http://dx.doi.org/10.1002/pro.126] [PMID: 19472328]
[6]
Ahmad, S.; Kamal, M.Z.; Sankaranarayanan, R.; Rao, N.M. Thermostable Bacillus subtilis lipases: in vitro evolution and structural insight. J. Mol. Biol., 2008, 381(2), 324-340.
[http://dx.doi.org/10.1016/j.jmb.2008.05.063] [PMID: 18599073]
[7]
Kamal, M.Z.; Mohammad, T.A.S.; Krishnamoorthy, G.; Rao, N.M. Role of active site rigidity in activity: MD simulation and fluorescence study on a lipase mutant. PLoS One, 2012, 7(4)e35188
[http://dx.doi.org/10.1371/journal.pone.0035188] [PMID: 22514720]
[8]
Rathi, P.C.; Jaeger, K-E.; Gohlke, H. Structural rigidity and protein thermostability in variants of lipase A from Bacillus subtilis. PLoS One, 2015, 10(7)e0130289
[http://dx.doi.org/10.1371/journal.pone.0130289] [PMID: 26147762]
[9]
Singh, B.; Bulusu, G.; Mitra, A. Understanding the thermostability and activity of Bacillus subtilis lipase mutants: insights from molecular dynamics simulations. J. Phys. Chem. B, 2015, 119(2), 392-409.
[http://dx.doi.org/10.1021/jp5079554] [PMID: 25495458]
[10]
Singh, B.; Bulusu, G.; Mitra, A. Effects of point mutations on the thermostability of B. subtilis lipase: investigating non-additivity. J. Comput. Aided Mol. Des., 2016, 30(10), 899-916.
[http://dx.doi.org/10.1007/s10822-016-9978-0] [PMID: 27696241]
[11]
Srivastava, A.; Sinha, S. Thermostability of in vitro evolved Bacillus subtilis lipase A: a network and dynamics perspective. PLoS One, 2014, 9(8)e102856
[http://dx.doi.org/10.1371/journal.pone.0102856] [PMID: 25122499]
[12]
Zhang, L.; Ding, Y. The relation between lipase thermostability and dynamics of hydrogen bond and hydrogen bond network based on long time molecular dynamics simulation. Protein Pept. Lett., 2017, 24(7), 643-648.
[http://dx.doi.org/10.2174/0929866524666170502151429] [PMID: 28464764]
[13]
Kandhari, N.; Sinha, S. Complex network analysis of thermostable mutants of Bacillus subtilis Lipase A. Appl Netw Sci, 2017, 2(1), 18.
[http://dx.doi.org/10.1007/s41109-017-0039-y] [PMID: 30443573]
[14]
del Sol, A.; Fujihashi, H.; O’Meara, P. Topology of small-world networks of protein-protein complex structures. Bioinformatics, 2005, 21(8), 1311-1315.
[http://dx.doi.org/10.1093/bioinformatics/bti167] [PMID: 15659419]
[15]
del Sol, A.; Fujihashi, H.; Amoros, D.; Nussinov, R. Residues crucial for maintaining short paths in network communication mediate signaling in proteins. Mol. Syst. Biol, 2006, 2, 0019.
[http://dx.doi.org/10.1038/msb4100063] [PMID: 16738564]
[16]
Ribeiro, A.A.; Ortiz, V. Determination of signaling pathways in proteins through network theory: importance of the topology. J. Chem. Theory Comput., 2014, 10(4), 1762-1769.
[http://dx.doi.org/10.1021/ct400977r] [PMID: 26580384]
[17]
Amitai, G.; Shemesh, A.; Sitbon, E.; Shklar, M.; Netanely, D.; Venger, I.; Pietrokovski, S. Network analysis of protein structures identifies functional residues. J. Mol. Biol., 2004, 344(4), 1135-1146.
[http://dx.doi.org/10.1016/j.jmb.2004.10.055] [PMID: 15544817]
[18]
del Sol, A.; Fujihashi, H.; Amoros, D.; Nussinov, R. Residue centrality, functionally important residues, and active site shape: analysis of enzyme and non-enzyme families. Protein Sci., 2006, 15(9), 2120-2128.
[http://dx.doi.org/10.1110/ps.062249106] [PMID: 16882992]
[19]
Atilgan, A.R.; Akan, P.; Baysal, C. Small-world communication of residues and significance for protein dynamics. Biophys. J., 2004, 86(Pt 1), 85-91.
[http://dx.doi.org/10.1016/S0006-3495(04)74086-2] [PMID: 14695252]
[20]
Brinda, K.V.; Vishveshwara, S. A network representation of protein structures: implications for protein stability. Biophys. J., 2005, 89(6), 4159-4170.
[http://dx.doi.org/10.1529/biophysj.105.064485] [PMID: 16150969]
[21]
Vijayabaskar, M.S.; Vishveshwara, S. Interaction energy based protein structure networks. Biophys. J., 2010, 99(11), 3704-3715.
[http://dx.doi.org/10.1016/j.bpj.2010.08.079] [PMID: 21112295]
[22]
Guzel, P.; Kurkcuoglu, O. Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models. Biochim. Biophys. Acta, Gen. Subj., 2017, 1861(12), 3131-3141.
[http://dx.doi.org/10.1016/j.bbagen.2017.09.005] [PMID: 28917952]
[23]
del Sol, A.; Tsai, C-J.; Ma, B.; Nussinov, R. The origin of allosteric functional modulation: multiple pre-existing pathways. Structure, 2009, 17(8), 1042-1050.
[http://dx.doi.org/10.1016/j.str.2009.06.008] [PMID: 19679084]
[24]
Anwar, M.A.; Choi, S. Structure-Activity Relationship in TLR4 Mutations: atomistic molecular dynamics simulations and residue interaction network analysis. Sci. Rep., 2017, 7, 43807.
[http://dx.doi.org/10.1038/srep43807] [PMID: 28272553]
[25]
Tse, A.; Verkhivker, G.M. Molecular dynamics simulations and structural network analysis of c-Abl and c-Src kinase core proteins: capturing allosteric mechanisms and communication pathways from residue centrality. J. Chem. Inf. Model., 2015, 55(8), 1645-1662.
[http://dx.doi.org/10.1021/acs.jcim.5b00240] [PMID: 26236953]
[26]
Tsai, C-J.; del Sol, A.; Nussinov, R. Allostery: absence of a change in shape does not imply that allostery is not at play. J. Mol. Biol., 2008, 378(1), 1-11.
[http://dx.doi.org/10.1016/j.jmb.2008.02.034] [PMID: 18353365]
[27]
Khor, S. Comparing local search paths with global search paths on protein residue networks: allosteric communication. J. Complex Netw., 2016, 5, 409-432.
[http://dx.doi.org/10.1093/comnet/cnw020]
[28]
Vuillon, L.; Lesieur, C. From local to global changes in proteins: a network view. Curr. Opin. Struct. Biol., 2015, 31, 1-8.
[http://dx.doi.org/10.1016/j.sbi.2015.02.015] [PMID: 25791607]
[29]
Bouakkaz, M.; Ouinten, Y.; Loudcher, S.; Fournier-Viger, P. Efficiently mining frequent item sets applied for textual aggregation. Appl. Intell., 2018, 48, 1013-1019.
[http://dx.doi.org/10.1007/s10489-017-1050-9]
[30]
Agrawal, R.; Srikant, R. Fast algorithms for mining association rules. Proc. 20th Int. Conf. Very Large Data Bases, VLDB., 1994, 1215, pp. 487-499.
[31]
Yang, J.Y.; Meng, Z.Q.; Jiang, L. Logistics frequent path sequence mining algorithm based on topological information. J. Comput. Sci., 2015, 42(4), 258-262.
[http://dx.doi.org/10.11896/j.issn.1002-137X.2015.04.053]
[32]
Fang, P.P.; Kong-Fa, H.U.; Chen-Jun, H. U.; Xie, J.D. Algorithm for miningfrequent path pattern of chinese herbal pieces based on FP-Tree. Lishizhen Med. Mater. Med. Res, 2017.
[33]
Zhang, J.; Mao, G.J. Prefix-based XML frequent path mining algorithm. J. Comput. Syst. Appl, 2018.
[34]
Martin, A.J.; Vidotto, M.; Boscariol, F.; Di Domenico, T.; Walsh, I.; Tosatto, S.C. RING: networking interacting residues, evolutionary information and energetics in protein structures. Bioinformatics, 2011, 27(14), 2003-2005.
[http://dx.doi.org/10.1093/bioinformatics/btr191] [PMID: 21493660]
[35]
Piovesan, D.; Minervini, G.; Tosatto, S.C. The RING 2.0 web server for high quality residue interaction networks. Nucleic Acids Res., 2016, 44(W1), W367-W374.
[http://dx.doi.org/10.1093/nar/gkw315] [PMID: 27198219]
[36]
Chennubhotla, C.; Bahar, I. Signal propagation in proteins and relation to equilibrium fluctuations. PLOS Comput. Biol., 2007, 3(9), 1716-1726.
[http://dx.doi.org/10.1371/journal.pcbi.0030172] [PMID: 17892319]
[37]
Dijkstra, E.W. A note on two problems in connexion with graphs. Numer. Math., 1959, 1, 269-271.
[http://dx.doi.org/10.1007/BF01386390]
[38]
Mardana, H.; Maharani, S.; Hatta, H.R. Applications to determine the shortest tower BTS distance using Dijkstra algorithm. AIP Conf. Proc; , 2017, pp. 1813-040002.
[http://dx.doi.org/10.1063/1.4975967]
[39]
Xiao, J.; Dongfang, W.; Jiancang, H. An improved Apriori algorithm based on transactional granule. Information Technology, Networking Electronic and Automation Control Conference IEEE., 2016, 1044-1046.
[http://dx.doi.org/10.1109/ITNEC.2016.7560523]
[40]
Yuan, Y.; Huang, T. A matrix algorithm for mining association rules. In: International Conference on Intelligent Computing: Advances in Intelligent Computing Springer Berlin: Heidelberg,; , 2005, pp. 370-379.
[http://dx.doi.org/10.1007/11538059_39]
[41]
Mamonova, T.B.; Glyakina, A.V.; Galzitskaya, O.V.; Kurnikova, M.G. Stability and rigidity/flexibility-two sides of the same coin? Biochim. Biophys. Acta, 2013, 1834(5), 854-866.
[http://dx.doi.org/10.1016/j.bbapap.2013.02.011] [PMID: 23416444]
[42]
Rathi, P.C.; Fulton, A.; Jaeger, K-E.; Gohlke, H. Application of rigidity theory to the thermostabilization of lipase A from Bacillus subtilis. PLOS Comput. Biol., 2016, 12(3)e1004754
[http://dx.doi.org/10.1371/journal.pcbi.1004754] [PMID: 27003415]
[43]
Sljoka, A.; Tsuchimura, N. Exploring protein flexibility and allosteric signalling mechanism with rigidity theory. Computer Science and Engineering (APWC on CSE), 3rd Asia-Pacific World Congress on, IEEE, 2016, 240-249.
[http://dx.doi.org/10.1109/APWC-on-CSE.2016.047]
[44]
Sani, H.A.; Shariff, F.M.; Rahman, R.N.Z.R.A.; Leow, T.C.; Salleh, A.B. The effects of one amino acid substitutions at the C-terminal region of thermostable L2 lipase by computational and experimental approach. Mol. Biotechnol., 2018, 60(1), 1-11.
[http://dx.doi.org/10.1007/s12033-017-0038-3] [PMID: 29058211]
[45]
Vogt, G.; Woell, S.; Argos, P. Protein thermal stability, hydrogen bonds, and ion pairs. J. Mol. Biol., 1997, 269(4), 631-643.
[http://dx.doi.org/10.1006/jmbi.1997.1042] [PMID: 9217266]
[46]
Xie, Y.; An, J.; Yang, G.; Wu, G.; Zhang, Y.; Cui, L.; Feng, Y. Enhanced enzyme kinetic stability by increasing rigidity within the active site. J. Biol. Chem.jbc, 2014.M113.536045.
[47]
Nicholson, H.; Becktel, W.J.; Matthews, B.W. Enhanced protein thermostability from designed mutations that interact with α-helix dipoles. Nature, 1988, 336(6200), 651-656.
[http://dx.doi.org/10.1038/336651a0] [PMID: 3200317]
[48]
Russell, R.J.; Ferguson, J.M.; Hough, D.W.; Danson, M.J.; Taylor, G.L. The crystal structure of citrate synthase from the hyperthermophilic archaeon Pyrococcus furiosus at 1.9 A resolution. Biochemistry, 1997, 36(33), 9983-9994.
[http://dx.doi.org/10.1021/bi9705321] [PMID: 9254593]
[49]
Ding, Y.; Cai, Y. Conformational dynamics of xylanase A from Streptomyces lividans: Implications for TIM-barrel enzyme thermostability. Biopolymers, 2013, 99(9), 594-604.
[http://dx.doi.org/10.1002/bip.22220] [PMID: 23404081]

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