83
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Discovery of novel inhibitor via molecular dynamics simulations against D-alanyl-D-alanine carboxypeptidase of Enterobacter cloacae

, &
Received 26 Sep 2023, Accepted 01 Feb 2024, Published online: 20 Feb 2024

References

  • Ahmad, S., Abbasi, H. W., Shahid, S., Gul, S., & Abbasi, S. W. (2020). Molecular docking, simulation and MM-PBSA studies of nigella sativa compounds: A computational quest to identify potential natural antiviral for COVID-19 treatment. Journal of Biomolecular Structure & Dynamics, 39(12), 4225–4233. https://doi.org/10.1080/07391102.2020.1775129
  • Ahmad, S., Raza, S., Abro, A., Liedl, K. R., & Azam, S. S. (2019). Toward novel inhibitors against KdsB: A highly specific and selective broad-spectrum bacterial enzyme. Journal of Biomolecular Structure & Dynamics, 37(5), Article 5–1345. https://doi.org/10.1080/07391102.2018.1459318
  • Anbarasu, K., & Jayanthi, S. (2018). Identification of curcumin derivatives as human LMTK3 inhibitors for breast cancer: A docking, dynamics, and MM/PBSA approach. 3 Biotech, 8(5), 228. https://doi.org/10.1007/s13205-018-1239-6
  • Bachmair, A., Finley, D., & Varshavsky, A. (1986). In vivo half-life of a protein is a function of its amino-terminal residue. Science (New York, N.Y.), 234(4773), 179–186. https://doi.org/10.1126/science.3018930
  • Case, D. A., Betz, R. M., D. S., Cerutti, Cheatham, T., Darden, T., Duke, R. E., T. J., Giese, Gohlke, H., Götz, A. W., Homeyer, N., Izadi, S., Janowski, P. A., J., Kaus, Kovalenko, A., Tai-Sung Lee, S., LeGrand, P., Li, C., Lin, Luchko, T., Kollman, P. A. … (2016). Amber 16, University of California, San Francisco. University of California, San Francisco. https://doi.org/10.13140/rg.2.2.27958.70729
  • CDC. (2021, March 2). Antibiotic-resistant Germs: New Threats. Centers for Disease Control and Prevention. https://www.cdc.gov/drugresistance/biggest-threats.html
  • CDC. (2022, July 15). The biggest antibiotic-resistant threats in the U.S. Centers for Disease Control and Prevention. https://www.cdc.gov/drugresistance/biggest-threats.html
  • Chen, L., Yang, J., Yu, J., Yao, Z., Sun, L., Shen, Y., & Jin, Q. (2005). VFDB: A reference database for bacterial virulence factors. Nucleic Acids Research, 33(Database issue), D325–328. https://doi.org/10.1093/nar/gki008
  • Chin, D. N., Chuaqui, C. E., & Singh, J. (2004). Integration of virtual screening into the drug discovery process. Mini Reviews in Medicinal Chemistry, 4(10), 1053–1065. https://doi.org/10.2174/1389557043403044
  • Colovos, C., & Yeates, T. O. (1993). Verification of protein structures: Patterns of nonbonded atomic interactions. Protein Science: A Publication of the Protein Society, 2(9), 1511–1519. https://doi.org/10.1002/pro.5560020916
  • Donohue, J. (1954). Radial distribution functions of some structures of the polypeptide chain. Proceedings of the National Academy of Sciences of the United States of America, 40(6), 377–381. https://doi.org/10.1073/pnas.40.6.377
  • Egan, W. J., Merz, K. M., & Baldwin, J. J. (2000). Prediction of drug absorption using multivariate statistics. Journal of Medicinal Chemistry, 43(21), 3867–3877. https://doi.org/10.1021/jm000292e
  • Eisenberg, D., Lüthy, R., & Bowie, J. U. (1997). Verify3d: Assessment of protein models with three-dimensional profiles. In Methods in enzymology (Vol. 277, pp. 396–404). Academic Press. https://doi.org/10.1016/S0076-6879(97)77022-8
  • Fiser, A., & Sali, A. (2003). Modeller: Generation and refinement of homology-based protein structure models. Methods in Enzymology, 374, 461–491. https://doi.org/10.1016/S0076-6879(03)74020-8
  • Fu, L., Niu, B., Zhu, Z., Wu, S., & Li, W. (2012). CD-HIT: Accelerated for clustering the next-generation sequencing data. Bioinformatics (Oxford, England), 28(23), 3150–3152. https://doi.org/10.1093/bioinformatics/bts565
  • Genheden, S., Kuhn, O., Mikulskis, P., Hoffmann, D., & Ryde, U. (2012). The normal-mode entropy in the MM/GBSA method: Effect of system truncation, buffer region, and dielectric constant. Journal of Chemical Information and Modeling, 52(8), 2079–2088. https://doi.org/10.1021/ci3001919
  • Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999). A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. Journal of Combinatorial Chemistry, 1(1), 55–68. https://doi.org/10.1021/cc9800071
  • Guruprasad, K., Reddy, B. V., & Pandit, M. W. (1990). Correlation between stability of a protein and its dipeptide composition: A novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Engineering, 4(2), 155–161. https://doi.org/10.1093/protein/4.2.155
  • Hann, M. M., & Oprea, T. I. (2004). Pursuing the leadlikeness concept in pharmaceutical research. Current Opinion in Chemical Biology, 8(3), 255–263. https://doi.org/10.1016/j.cbpa.2004.04.003
  • Herschlag, D., & Pinney, M. M. (2018). Hydrogen bonds: Simple after All? Biochemistry, 57(24), 3338–3352. https://doi.org/10.1021/acs.biochem.8b00217
  • Hooft, R. W., Sander, C., & Vriend, G. (1997). Objectively judging the quality of a protein structure from a Ramachandran plot. Computer Applications in the Biosciences: CABIOS, 13(4), 425–430. https://doi.org/10.1093/bioinformatics/13.4.425
  • Hossain, M., Chowdhury, D. U. S., Farhana, J., Akbar, M. T., Chakraborty, A., Islam, S., & Mannan, A. (2013). Identification of potential targets in Staphylococcus aureus N315 using computer aided protein data analysis. Bioinformation, 9(4), 187–192. https://doi.org/10.6026/97320630009187
  • 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
  • Ikai, A. (1980). Thermostability and aliphatic index of globular proteins. Journal of Biochemistry, 88(6), 1895–1898.
  • Izaguirre, J. A., Catarello, D. P., Wozniak, J. M., & Skeel, R. D. (2001). Langevin stabilization of molecular dynamics. The Journal of Chemical Physics, 114(5), Article 5–2098. https://doi.org/10.1063/1.1332996
  • Jones, G., Willett, P., Glen, R. C., Leach, A. R., & Taylor, R. (1997). Development and validation of a genetic algorithm for flexible docking. Journal of Molecular Biology, 267(3), 727–748. https://doi.org/10.1006/jmbi.1996.0897
  • Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., & Sternberg, M. J. E. (2015). The Phyre2 web portal for protein modelling, prediction and analysis. Nature Protocols, 10(6), 845–858. https://doi.org/10.1038/nprot.2015.053
  • Kellogg, G. E. (2006). Computer applications in pharmaceutical research and development edited by Sean Ekins. John Wiley & Sons, Inc., Hoboken, NJ. 2006. Xix + 805 pp. 16 × 24 cm. ISBN 0-471-73779-8. $125.00. Journal of Medicinal Chemistry, 49(26), 7923–7923. https://doi.org/10.1021/jm0680474
  • Kouetcha, D. N., Ramézani, H., & Cohaut, N. (2017). Ultrafast scalable parallel algorithm for the radial distribution function histogramming using MPI maps. The Journal of Supercomputing, 73(4), 1629–1653. https://doi.org/10.1007/s11227-016-1854-0
  • Kraker, M. E. A. D., Stewardson, A. J., & Harbarth, S. (2016). Will 10 million people die a year due to antimicrobial resistance by 2050? PLoS Medicine, 13(11), e1002184. https://doi.org/10.1371/journal.pmed.1002184
  • Kräutler, V., Gunsteren, W. V. V., & Hünenberger, P. (2001). A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations.
  • Kumar, N., Hendriks, B. S., Janes, K. A., de Graaf, D., & Lauffenburger, D. A. (2006). Applying computational modelling to drug discovery and development. Drug Discovery Today, 11(17-18), 806–811. https://doi.org/10.1016/j.drudis.2006.07.010
  • Kyte, J., & Doolittle, R. F. (1982). A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology, 157(1), 105–132. https://doi.org/10.1016/0022-2836(82)90515-0
  • Li, W., & Godzik, A. (2006). Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics (Oxford, England), 22(13), 1658–1659. https://doi.org/10.1093/bioinformatics/btl158
  • Lipinski, C. A. (2004). Lead- and drug-like compounds: The rule-of-five revolution. Drug Discovery Today. Technologies, 1(4), 337–341. https://doi.org/10.1016/j.ddtec.2004.11.007
  • Miller, B. R., McGee, T. D., Swails, J. M., Homeyer, N., Gohlke, H., & Roitberg, A. E. (2012). MMPBSA.py: An efficient program for end-state free energy calculations. Journal of Chemical Theory and Computation, 8(9), Article 9–3321. https://doi.org/10.1021/ct300418h
  • Moreira, I. S., Fernandes, P. A., & Ramos, M. J. (2007). Computational alanine scanning mutagenesis—An improved methodological approach. Journal of Computational Chemistry, 28(3), Article 3–654. https://doi.org/10.1002/jcc.20566
  • Moriya, Y., Itoh, M., Okuda, S., Yoshizawa, A. C., & Kanehisa, M. (2007). KAAS: An automatic genome annotation and pathway reconstruction server. Nucleic Acids Research, 35(Web Server issue), W182–185. https://doi.org/10.1093/nar/gkm321
  • Mount, D. W. (2007). Using the Basic Local Alignment Search Tool (BLAST). CSH Protocols, 2007, pdb.top17. https://doi.org/10.1101/pdb.top17
  • Muegge, I., Heald, S. L., & Brittelli, D. (2001). Simple selection criteria for drug-like chemical matter. Journal of Medicinal Chemistry, 44(12), 1841–1846. https://doi.org/10.1021/jm015507e
  • Naz, A., Awan, F. M., Obaid, A., Muhammad, S. A., Paracha, R. Z., Ahmad, J., & Ali, A. (2015). Identification of putative vaccine candidates against Helicobacter pylori exploiting exoproteome and secretome: A reverse vaccinology based approach. Infection, Genetics and Evolution, 32, 280–291. https://doi.org/10.1016/j.meegid.2015.03.027
  • NCBI Resource Coordinators. (2018). Database resources of the National Center for Biotechnology Information. Nucleic Acids Research, 46(D1), D8–D13. https://doi.org/10.1093/nar/gkx1095
  • Nguyen, A. T., Jones, J. W., Ruge, M. A., Kane, M. A., & Oglesby-Sherrouse, A. G. (2015). Iron depletion enhances production of antimicrobials by Pseudomonas aeruginosa. Journal of Bacteriology, 197(14), 2265–2275. https://doi.org/10.1128/JB.00072-15
  • Oprea, T. I., & Matter, H. (2004). Integrating virtual screening in lead discovery. Current Opinion in Chemical Biology, 8(4), 349–358. https://doi.org/10.1016/j.cbpa.2004.06.008
  • Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
  • Price, D. J., & Brooks, C. L. (2004). A modified TIP3P water potential for simulation with Ewald summation. The Journal of Chemical Physics, 121(20), 10096–10103. https://doi.org/10.1063/1.1808117
  • Rao, V. S., Srinivas, K., Sujini, G. N., & Kumar, G. N. (2014). Protein-protein interaction detection: Methods and analysis. International Journal of Proteomics, 2014, 147612–147648. https://doi.org/10.1155/2014/147648
  • Raza, S., & Azam, S. S. (2018). AFD: An application for bi-molecular interaction using axial frequency distribution. Journal of Molecular Modeling, 24(4), 84. https://doi.org/10.1007/s00894-018-3601-3
  • Ren, Y., Ren, Y., Zhou, Z., Guo, X., Li, Y., Feng, L., & Wang, L. (2010). Complete genome sequence of Enterobacter cloacae subsp. Cloacae type strain ATCC 13047. Journal of Bacteriology, 192(9), Article 9–2464. https://doi.org/10.1128/JB.00067-10
  • Roche, O., & Guba, W. (2005). Computational chemistry as an integral component of lead generation. Mini Reviews in Medicinal Chemistry, 5(7), 677–683. https://doi.org/10.2174/1389557054368826
  • Roe, D. R., & Cheatham, T. E. (2013). PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. Journal of Chemical Theory and Computation, 9(7), 3084–3095. https://doi.org/10.1021/ct400341p
  • Roy, A., Kucukural, A., & Zhang, Y. (2010). I-TASSER: A unified platform for automated protein structure and function prediction. Nature Protocols, 5(4), 725–738. https://doi.org/10.1038/nprot.2010.5
  • Schwede, T., Kopp, J., Guex, N., & Peitsch, M. C. (2003). SWISS-MODEL: An automated protein homology-modelling server. Nucleic Acids Research, 31(13), Article 13–3385. https://doi.org/10.1093/nar/gkg520
  • Sikic, K., & Carugo, O. (2010). Protein sequence redundancy reduction: Comparison of various method. Bioinformation, 5(6), 234–239. https://doi.org/10.6026/97320630005234
  • Stahl, M., Guba, W., & Kansy, M. (2006). Integrating molecular design resources within modern drug discovery research: The Roche experience. Drug Discovery Today, 11(7-8), 326–333. https://doi.org/10.1016/j.drudis.2006.02.008
  • Stoermer, M. J. (2006). Current status of virtual screening as analysed by target class. Medicinal Chemistry (Shariqah (United Arab Emirates)), 2(1), 89–112. https://doi.org/10.2174/157340606775197750
  • Sussman, J. L., Lin, D., Jiang, J., Manning, N. O., Prilusky, J., Ritter, O., & Abola, E. E. (1998). Protein Data Bank (PDB): Database of three-dimensional structural information of biological macromolecules. Acta Crystallographica. Section D, Biological Crystallography, 54(Pt 6 Pt 1), 1078–1084. https://doi.org/10.1107/s0907444998009378
  • Systèmes, D. (2020, March 20). Free Download: BIOVIA Discovery Studio Visualizer. Dassault Systèmes. https://discover.3ds.com/discovery-studio-visualizer-download
  • Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., Kuhn, M., Bork, P., Jensen, L. J., & von Mering, C. (2015). STRING v10: Protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Research, 43(Database issue), D447–452. https://doi.org/10.1093/nar/gku1003
  • Tang, Y. T., & Marshall, G. R. (2011). Virtual screening for lead discovery. Methods in Molecular Biology (Clifton, N.J.), 716, 1–22. https://doi.org/10.1007/978-1-61779-012-6_1[Mismatch GBSA based binding free energies]
  • Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
  • Veber, D. F., Johnson, S. R., Cheng, H.-Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n
  • Verdonk, M. L., Cole, J. C., Hartshorn, M. J., Murray, C. W., & Taylor, R. D. (2003). Improved protein-ligand docking using GOLD. Proteins, 52(4), 609–623. https://doi.org/10.1002/prot.10465
  • Walsh, T. R., Gales, A. C., Laxminarayan, R., & Dodd, P. C. (2023). Antimicrobial resistance: Addressing a global threat to humanity. PLoS Medicine, 20(7), e1004264. https://doi.org/10.1371/journal.pmed.1004264
  • Wiederstein, M., & Sippl, M. J. (2007). ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research, 35(Web Server issue), W407–410. https://doi.org/10.1093/nar/gkm290
  • Wolber, G., & Langer, T. (2005). LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. Journal of Chemical Information and Modeling, 45(1), 160–169. https://doi.org/10.1021/ci049885e
  • Woods, C. J., Malaisree, M., Hannongbua, S., & Mulholland, A. J. (2011). A water-swap reaction coordinate for the calculation of absolute protein–ligand binding free energies. The Journal of Chemical Physics, 134(5), Article 5. https://doi.org/10.1063/1.3519057
  • Yu, C.-S., Cheng, C.-W., Su, W.-C., Chang, K.-C., Huang, S.-W., Hwang, J.-K., & Lu, C.-H. (2014). CELLO2GO: A web server for protein subCELlular LOcalization prediction with functional gene ontology annotation. PLoS One, 9(6), e99368. https://doi.org/10.1371/journal.pone.0099368
  • Zhang, R., Ou, H.-Y., & Zhang, C.-T. (2004). DEG: A database of essential genes. Nucleic Acids Research, 32(Database issue), D271–272. https://doi.org/10.1093/nar/gkh024

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.