Identification of potential mutational hotspots in serratiopeptidase to address its poor pH tolerance issue

References

• Baker, N. A., Sept, D., Joseph, S., Holst, M. J., & McCammon, J. A. (2001). Electrostatics of nanosystems: Application to microtubules and the ribosome. Proceedings of the National Academy of Sciences of the United States of America, 98(18), 10037–10041. https://doi.org/10.1073/pnas.181342398
   PubMed Web of Science ®Google Scholar
• Bauer, J. A., Pavlovíc, J., & Bauerová-Hlinková, V. (2019). Normal mode analysis as a routine part of a structural investigation. Molecules, 24(18), 3293. https://doi.org/10.3390/molecules24183293
   PubMed Web of Science ®Google Scholar
• Baumann, U. (1994). Crystal structure of the 50 kDa metallo protease from Serratia marcescens. Journal of Molecular Biology, 242(3), 244–251. https://doi.org/10.1006/jmbi.1994.1576
   PubMed Web of Science ®Google Scholar
• Baumann, U., Bauer, M., Létoffé, S., Delepelaire, P., & Wandersman, C. (1995). Crystal structure of a complex between Serratia marcescens metallo-protease and an inhibitor from Erwinia chrysanthemi. Journal of Molecular Biology, 248(3), 653–661. https://doi.org/10.1006/jmbi.1995.0249
   PubMed Web of Science ®Google Scholar
• Berendsen, H. J. C., Postma, J. P. M., Van Gunsteren, W. F., Dinola, A., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8), 3684–3690. https://doi.org/10.1063/1.448118
   Web of Science ®Google Scholar
• Berendsen, H. J. C., Postma, J., P. M., van Gunsteren, W. F., & Hermans, J. (1981). Interaction models for water in relation to protein hydration. The Journal of Chemical Physics, 81(8), 331–342. https://doi.org/10.1007/978-94-015-7658-1_21
   Google Scholar
• Bhardwaj, V. K., & Purohit, R. (2021). Computer simulation to identify selective inhibitor for human phosphodiesterase 10A. Journal of Molecular Liquids, 328, 115419. https://doi.org/10.1016/j.molliq.2021.115419
   Web of Science ®Google Scholar
• bioinformatics, J. F.-B. (2020). A critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation. Academic.Oup.Com. Retrieved 2022, January 9, from https://academic.oup.com/bib/article-abstract/21/4/1285/5527140
   Google Scholar
• Bischoff, R., & Schlüter, H. (2012). Amino acids: Chemistry, functionality and selected non-enzymatic post-translational modifications. Journal of Proteomics, 75(8), 2275–2296. https://doi.org/10.1016/j.jprot.2012.01.041
   PubMed Web of Science ®Google Scholar
• Capriotti, E., Fariselli, P., & Casadio, R. (2005). I-Mutant2.0: Predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Research, 33(Web Server), W306–W310. https://doi.org/10.1093/nar/gki375
   PubMed Web of Science ®Google Scholar
• Cheng, J., Randall, A., & Baldi, P. (2006). Prediction of protein stability changes for single-site mutations using support vector machines. Proteins, 62(4), 1125–1132. https://doi.org/10.1002/prot.20810
   PubMed Web of Science ®Google Scholar
• Costa, E. B., Silva, R. C., Espejo-Román, J. M., Neto, M., F., d A., Cruz, J. N., Leite, F. H. A., Silva, C. H. T. P., Pinheiro, J. C., Macêdo, W. J. C., & Santos, C. B. R. (2020). Chemometric methods in antimalarial drug design from 1,2,4,5-tetraoxanes analogues. SAR and QSAR in Environmental Research, 31(9), 677–695. https://doi.org/10.1080/1062936X.2020.1803961
   PubMed Web of Science ®Google Scholar
• da Silva Júnior, O. S., Franco, C. d J. P., de Moraes, A. A. B., Cruz, J. N., da Costa, K. S., do Nascimento, L. D., & Andrade, E. H. d A. (2021). In silico analyses of toxicity of the major constituents of essential oils from two Ipomoea L. species. Toxicon, 195, 111–118. https://doi.org/10.1016/j.toxicon.2021.02.015
   PubMed Web of Science ®Google Scholar
• de Vries, S. J., & Bonvin, A. M. J. J. (2011). Cport: A consensus interface predictor and its performance in prediction-driven docking with HADDOCK. PLoS One, 6(3), e17695. https://doi.org/10.1371/journal.pone.0017695
   PubMed Web of Science ®Google Scholar
• De Vries, S. J., Van Dijk, M., & Bonvin, A. M. J. J. (2010). The HADDOCK web server for data-driven biomolecular docking. Nature Protocols, 5(5), 883–897. https://doi.org/10.1038/nprot.2010.32
   PubMed Web of Science ®Google Scholar
• Desser, L., Rehberger, A., Kokron, E., & Paukovits, W. (1993). Cytokine synthesis in human peripheral blood mononuclear cells after oral administration of polyenzyme preparations. Oncology, 50(6), 403–407. https://doi.org/10.1159/000227219
   PubMed Web of Science ®Google Scholar
• Dolinsky, T. J., Czodrowski, P., Li, H., Nielsen, J. E., Jensen, J. H., Klebe, G., & Baker, N. A. (2007). PDB2PQR: Expanding and upgrading automated preparation of biomolecular structures for molecular simulations. Nucleic Acids Research, 35(Web Server), W522–W525. https://doi.org/10.1093/nar/gkm276
   PubMedGoogle Scholar
• Ethiraj, S., & Gopinath, S. (2017). Production, purification, characterization, immobilization, and application of Serrapeptase: a review. Frontiers in Biology, 12(5), 333–348. https://doi.org/10.1007/s11515-017-1461-3
   Google Scholar
• Fasim, A., More, V. S., & More, S. S. (2021). Large-scale production of enzymes for biotechnology uses. Current Opinion in Biotechnology, 69, 68–76. https://doi.org/10.1016/j.copbio.2020.12.002
   PubMed Web of Science ®Google Scholar
• Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein identification and analysis tools on the ExPASy server. In The proteomics protocols handbook (pp. 571–607). Springer. https://doi.org/10.1385/1-59259-890-0:571
   Google Scholar
• Gromiha, M. M., Nagarajan, R., & Selvaraj, S. (2018). Protein structural bioinformatics: An overview. Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, 1–3, 445–459. https://doi.org/10.1016/B978-0-12-809633-8.20278-1
   Google Scholar
• Hamada, K., Hata, Y., Katsuya, Y., Hiramatsu, H., Fujiwara, T., & Katsube, Y. (1996). Crystal structure of Serratia protease, a zinc-dependent proteinase from Serratia sp. E-15, containing a β-sheet coil motif at 2.0 Å resolution. Journal of Biochemistry, 119(5), 844–851. https://doi.org/10.1093/oxfordjournals.jbchem.a021320
   PubMed Web of Science ®Google Scholar
• Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
   PubMedGoogle Scholar
• Indrayati, A., Asyarie, S., Suciati, T., & Retnoningrum, D. S. (2014). Study on the properties of purified recombinant superoxide dismutase from staphylococcus equorum, A local isolate from Indonesia. International Journal of Pharmacy and Pharmaceutical Sciences, 6(11), 440–445. https://hero.epa.gov/hero/index.cfm/reference/details/reference_id/8431121
   Google Scholar
• Isono, M., Kazutaka, M., & Kodama, R. (1974). Method of treating inflammation and composition therefor. Google Patents. https://patents.google.com/patent/US3792160A/en
   Google Scholar
• Kaviyarasi, N. S., Prashantha, C. N., & Suryanarayana, V. V. S. (2016). In silico analysis of inhibitor and substrate binding site of serrapeptidase from Serratia marcescens MTCC 8708. International Journal of Pharmacy and Pharmaceutical Sciences, 8(4), 123–128. https://core.ac.uk/download/pdf/72805721.pdf
   Google Scholar
• Kumar Bhardwaj, V., Das, P., & Purohit, R. (2022). Identification and comparison of plant-derived scaffolds as selective CDK5 inhibitors against standard molecules: Insights from umbrella sampling simulations. Journal of Molecular Liquids, 348, 118015. https://doi.org/10.1016/j.molliq.2021.118015
   Web of Science ®Google Scholar
• Kumar, S. (2018). The emerging role of serratiopeptidase in oral surgery: Literature update. Asian Journal of Pharmaceutical and Clinical Research, 11(3), 19–23. https://doi.org/10.22159/ajpcr.2018.v11i3.23471
   Google Scholar
• Kumar, S., Bhardwaj, V. K., Singh, R., Das, P., & Purohit, R. (2022). Evaluation of plant-derived semi-synthetic molecules against BRD3-BD2 protein: a computational strategy to combat breast cancer. Molecular Systems Design & Engineering, 7(4), 381–391. https://doi.org/10.1039/D1ME00183C
   Web of Science ®Google Scholar
• Liu, Z., Zhao, H., Han, L., Cui, W., Zhou, L., & Zhou, Z. (2019). Improvement of the acid resistance, catalytic efficiency, and thermostability of nattokinase by multisite-directed mutagenesis. Biotechnology and Bioengineering, 116(8), 1833–1843. https://doi.org/10.1002/bit.26983
   PubMed Web of Science ®Google Scholar
• Mazzone, A., Catalani, M., Costanzo, M., Drusian, A., Mandoli, A., Russo, S., Guarini, E., & Vesperini, G. (1990). Evaluation of serratia peptidase in acute or chronic inflammation of otorhinolaryngology pathology: A multicentre, double-blind, randomized trial versus placebo. The Journal of International Medical Research, 18(5), 379–388. https://doi.org/10.1177/030006059001800506
   PubMed Web of Science ®Google Scholar
• Medeiros, I. G., Cruz, J. N., Oliveira, M. S., Costa, W. A., Lima, A. H. L., Brasil, L., S., N. S., Junior, R., N. C., Neto, A., M. J. C., & Brasil, D. S. B. (2019). Removal of organic pollutants benzene and phenol using nanofiltration: A molecular dynamics study. Journal of Nanoscience and Nanotechnology, 19(9), 5979–5983. https://doi.org/10.1166/jnn.2019.16511
   PubMed Web of Science ®Google Scholar
• Miyata, K., Maejima, K., Tomoda, K., & Isono, M. (1970). Serratia protease Part I. Purification and general properties of the enzyme. Agricultural and Biological Chemistry, 34(2), 310–318. https://doi.org/10.1271/bbb1961.34.310
   Web of Science ®Google Scholar
• Miyata, K., Tomoda, K., & Isono, M. (1970). Serratia protease: Part II. Substrate specificity of the enzyme. Agricultural and Biological Chemistry, 34(10), 1457–1462. https://doi.org/10.1080/00021369.1970.10859796
   Web of Science ®Google Scholar
• Molla, A., Matsumoto, K., Oyamada, I., Katsuki, T., & Maeda, H. (1986). Degradation of protease inhibitors, immunoglobulins, and other serum proteins by Serratia protease and its toxicity to fibroblasts in culture. Infection and Immunity, 53(3), 522–529. https://doi.org/10.1128/iai.53.3.522-529.1986
   PubMed Web of Science ®Google Scholar
• Nakahama, K., Yoshimura, K., Marumoto, R., Kikuchi, M., Lee, I. S., Hase, T., & Matsubara, H. (1986). Cloning and sequencing of Serratia protease gene. Nucleic Acids Research, 14(14), 5843–5855. https://doi.org/10.1093/nar/14.14.5843
   PubMed Web of Science ®Google Scholar
• Nakamuha, S., Hashimoto, Y., Mikami, M., Yamanaka, E., Soma, T., Hino, M., Azuma, A., & Kudoh, S. (2003). Effect of the proteolytic enzyme serrapeptase in patients with chronic airway disease. Respirology (Carlton, Vic.), 8(3), 316–320. https://doi.org/10.1046/J.1440-1843.2003.00482.X
   PubMed Web of Science ®Google Scholar
• Neto, R. d A. M., Santos, C. B. R., Henriques, S. V. C., Machado, L. d O., Cruz, J. N., d., Silva, C. H., T., d P., Federico, L. B., Oliveira, E. H., C., d., de Souza, M. P. C., d., Silva, P., N. B., Taft, C. A., Ferreira, I. M., & Gomes, M. R. F. (2022). Novel chalcones derivatives with potential antineoplastic activity investigated by docking and molecular dynamics simulations. Journal of Biomolecular Structure & Dynamics, 40(5), 2204–2216. https://doi.org/10.1080/07391102.2020.1839562
   PubMed Web of Science ®Google Scholar
• Parrinello, M., & Rahman, A. (1981). Polymorphic transitions in single crystals: A new molecular dynamics method. Journal of Applied Physics, 52(12), 7182–7190. https://doi.org/10.1063/1.328693
   Web of Science ®Google Scholar
• Parthiban, V., Gromiha, M. M., & Schomburg, D. (2006). CUPSAT: Prediction of protein stability upon point mutations. Nucleic Acids Research, 34(Web Server), W239–W242. ISS https://doi.org/10.1093/nar/gkl190
   PubMedGoogle Scholar
• Pinto, V., de, S., Araújo, J. S. C., Silva, R. C., da Costa, G. V., Cruz, J. N., Neto, M. F. D. A., Campos, J. M., Santos, C. B. R., Leite, F., H. A., & Junior, M. C. S. (2019). In silico study to identify new antituberculosis molecules from natural sources by hierarchical virtual screening and molecular dynamics simulations. Pharmaceuticals, 12(1), 36. https://doi.org/10.3390/ph12010036
   Web of Science ®Google Scholar
• Rego, C. M. A., Francisco, A. F., Boeno, C. N., Paloschi, M. V., Lopes, J. A., Silva, M. D. S., Santana, H. M., Serrath, S. N., Rodrigues, J. E., Lemos, C. T. L., Dutra, R. S. S., da Cruz, J. N., dos Santos, C., B., R., da S. Setúbal, S., Fontes, M., R. M., Soares, A. M., Pires, W. L., & Zuliani, J. P. (2022). Inflammasome NLRP3 activation induced by Convulxin, a C-type lectin-like isolated from Crotalus durissus terrificus snake venom. Scientific Reports, 12(1), 1–17. https://doi.org/10.1038/s41598-022-08735-7
   PubMed Web of Science ®Google Scholar
• Reijenga, J., van Hoof, A., van Loon, A., & Teunissen, B. (2013). Development of methods for the determination of pKa values. Analytical Chemistry Insights, 8(1), 53–71. https://doi.org/10.4137/ACI.S12304
   PubMedGoogle Scholar
• Rodrigues, C. H. M., Pires, D. E. V., & Ascher, D. B. (2018). DynaMut: Predicting the impact of mutations on protein conformation, flexibility and stability. Nucleic Acids Research, 46(W1), W350–W355. https://doi.org/10.1093/nar/gky300
   PubMed Web of Science ®Google Scholar
• Rouhani, M., Valizadeh, V., Aghai, A., Pourasghar, S., Molasalehi, S., Cohan, R. A., & Norouzian, D. (2021). Design, expression and functional assessment of novel engineered serratiopeptidase analogs with enhanced protease activity and thermal stability. World Journal of Microbiology & Biotechnology, 38(1), 17–17. https://doi.org/10.1007/s11274-021-03195-z
   PubMed Web of Science ®Google Scholar
• Selan, L., Papa, R., Tilotta, M., Vrenna, G., Carpentieri, A., Amoresano, A., Pucci, P., & Artini, M. (2015). Serratiopeptidase: A well-known metalloprotease with a new non-proteolytic activity against S. aureus biofilm. BMC Microbiology, 15(1), 1-6. https://doi.org/10.1186/s12866-015-0548-8
   Google Scholar
• Singh, R., Bhardwaj, V. K., & Purohit, R. (2022a). Computational targeting of allosteric site of MEK1 by quinoline-based molecules. Cell Biochemistry and Function, 40(5), 481–490. https://doi.org/10.1002/cbf.3709
   PubMed Web of Science ®Google Scholar
• Singh, R., Kumar, S., Bhardwaj, V. K., & Purohit, R. (2022b). Screening and reckoning of potential therapeutic agents against DprE1 protein of Mycobacterium tuberculosis. Journal of Molecular Liquids, 358, 119101. https://doi.org/10.1016/j.molliq.2022.119101
   Web of Science ®Google Scholar
• Spasic, A., Serafini, J., & Mathews, D. H. (2012). The amber ff99 force field predicts relative free energy changes for RNA helix formation. Journal of Chemical Theory and Computation, 8(7), 2497–2505. https://doi.org/10.1021/ct300240k
   PubMed Web of Science ®Google Scholar
• Srivastava, S., Singh, D., Patel, S., & Singh, M. R. (2017). Treatment of rheumatoid arthritis by targeting macrophages through folic acid tailored superoxide dismutase and serratiopeptidase. Journal of Drug Delivery Science and Technology, 41, 431–435. https://doi.org/10.1016/j.jddst.2017.09.002
   Web of Science ®Google Scholar
• Sumbalova, L., Stourac, J., Martinek, T., Bednar, D., & Damborsky, J. (2018). HotSpot Wizard 3.0: Web server for automated design of mutations and smart libraries based on sequence input information. Nucleic Acids Research, 46(W1), W356–W362. https://doi.org/10.1093/nar/gky417
   PubMed Web of Science ®Google Scholar
• Van Dijk, M., Van Dijk, A. D. J., Hsu, V., Rolf, B., & Bonvin, A. M. J. J. (2006). Information-driven protein-DNA docking using HADDOCK: It is a matter of flexibility. Nucleic Acids Research, 34(11), 3317–3325. https://doi.org/10.1093/nar/gkl412
   PubMed Web of Science ®Google Scholar
• van Gunsteren, W. F., Billeter, S. R., Eising, A. A., Hunenberger, P. H., Kruger, P., Mark, A. E., Scott, W. R. P., & Tironi, I. G. (1996). Biomolecular simulation: The {GROMOS96} manual and user guide, Biomos Vdf Hochschulverlag AG an der ETH Zürich.
   Google Scholar
• Wallace, A. C., Laskowski, R. A., & Thornton, J. M. (1995). Ligplot: A program to generate schematic diagrams of protein-ligand interactions. Protein Engineering, 8(2), 127–134. https://doi.org/10.1093/protein/8.2.127
   PubMedGoogle Scholar
• Wang, Z., Huang, C., Lv, H., Zhang, M., & Li, X. (2020). In silico analysis and high-risk pathogenic phenotype predictions of non-synonymous single nucleotide polymorphisms in human Crystallin beta A4 gene associated with congenital cataract. PLoS One, 15(1), e0227859. https://doi.org/10.1371/journal.pone.0227859
   PubMed Web of Science ®Google Scholar
• Ward, A. J., Masters, A. F., & Maschmeyer, T. (2013). Cobalt(II) carboxylate chemistry and catalytic applications. In Comprehensive inorganic chemistry II. (Second edition): From elements to applications (Vol. 6, pp. 665–684). Elsevier. https://doi.org/10.1016/B978-0-08-097774-4.00630-6
   Google Scholar
• Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., De Beer, T. A. P., Rempfer, C., Bordoli, L., Lepore, R., & Schwede, T. (2018). SWISS-MODEL: Homology modelling of protein structures and complexes. Nucleic Acids Research, 46(W1), W296–W303. https://doi.org/10.1093/nar/gky427
   PubMed Web of Science ®Google Scholar
• Wu, D., Ran, T., Wang, W., & Xu, D. (2016). Structure of a thermostable serralysin from Serratia sp. FS14 at 1.1Å resolution. Acta Crystallographica Section: F Structural Biology Communications, 72, 10–15. https://doi.org/10.1107/S2053230X15023092
   PubMed Web of Science ®Google Scholar
• Yamasaki, H., Tsuji, H., & Saeki, K. (1967). Anti-inflammatory action of a protease, TSP, produced by Serratia. Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica, 63(4), 302–314. https://doi.org/10.1254/fpj.63.302
   PubMedGoogle Scholar
• Zhu, D., Wu, Q., & Wang, N. (2011). Industrial enzymes. In Comprehensive biotechnology (2nd ed., Vol. 3). Pergamon. https://doi.org/10.1016/B978-0-08-088504-9.00182-3
   Google Scholar