References
- Adi, P. J., Yellapu, N. K., & Matcha, B. (2016). Modeling, molecular docking, probing catalytic binding mode of acetyl-CoA malate synthase G in Brucella melitensis 16M. Biochemistry and Biophysics Reports., 8, 192–199. https://doi.org/10.1016/j.bbrep.2016.08.020
- Amadei, A., Linssen, A., & Berendsen, H. J. C. (1993). Essential dynamics of proteins. Proteins: Structure, Function, and Genetics, 17(4), 412–425. https://doi.org/10.1002/prot.340170408
- Anstrom, D. M., Kallio, K., & Remington, S. J. (2003). Structure of the Escherichia coli malate synthase G: Pyruvate: Acetyl‐coenzyme A abortive ternary complex at 1.95 Å resolution. Protein Science, 12(9), 1822–1832. https://doi.org/10.1110/ps.03174303
- Anstrom, D. M., & Remington, S. J. (2006). The product complex of M. tuberculosis malate synthase revisited. Protein Science, 15(8), 2002–2007. https://doi.org/10.1110/ps.062300206
- 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, 98(18), 10037–10041. https://doi.org/10.1073/pnas.181342398
- Banks, J. L., Beard, H. S., Cao, Y., Cho, A. E., Damm, W., Farid, R., Felts, A. K., Halgren, T. A., Mainz, D. T., Maple, J. R., Murphy, R., Philipp, D. M., Repasky, M. P., Zhang, L. Y., Berne, B. J., Friesner, R. A., Gallicchio, E., & Levy, R. M. (2005). Integrated Modeling Program, Applied Chemical Theory (IMPACT). Journal of Computational Chemistry, 26(16), 1752–1780. https://doi.org/10.1002/jcc.20292
- Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., Lee, P. W., & Tang, Y. (2012). admetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties. Journal of Chemical Information and Modeling, 52(11), 3099–3105. https://doi.org/10.1021/ci300367a
- Cole, S. T., Brosch, R., Parkhill, J., Garnier, T., Churcher, C., Harris, D., Gordon, S. V., Eiglmeier, K., Gas, S., Barry, C. E., Tekaia, F., Badcock, K., Basham, D., Brown, D., Chillingworth, T., Connor, R., Davies, R., Devlin, K., Feltwell, T., … Barrell, B. G. (1998). Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature, 393(6685), 537–544. https://doi.org/10.1038/31159
- Darden, T., York, D., & Pedersen, L. G. (1993). Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems. Journal of Chemical Physics., 98(12), 10089–10092. https://doi.org/10.1063/1.464397
- Ellenbarger, J. F., Krieger, I. V., Huang, H-l., Gómez-Coca, S., Ioerger, T. R., Sacchettini, J. C., Wheeler, S. E., & Dunbar, K. R. (2018). Anion-π interactions in computer-aided drug design: Modeling the inhibition of malate synthase by phenyl-diketo acids. Journal of Chemical Information and Modeling, 58(10), 2085–2091. https://doi.org/10.1021/acs.jcim.8b00417
- Essmann, U., Perera, L., Berkowitz, M. L., Darden, T., Lee, H., & Pedersen, L. G. (1995). A smooth particle mesh Ewald method. Journal of Chemical Physics., 103(19), 8577–8593. https://doi.org/10.1063/1.470117
- Friesner, R. A., Murphy, R. B., Repasky, M. P., Frye, L. L., Greenwood, J. R., Halgren, T. A., Sanschagrin, P. C., & Mainz, D. T. (2006). Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. Journal of Medicinal Chemistry, 49(21), 6177–6196. https://doi.org/10.1021/jm051256o
- Goletti, D., Lindestam Arlehamn, C. S., Scriba, T. J., Anthony, R., Cirillo, D. M., Alonzi, T., Denkinger, C. M., & Cobelens, F. (2018). Can we predict tuberculosis cure? What tools are available? European Respiratory Journal, 52(5), 1801089. https://doi.org/10.1183/13993003.01089-2018
- Gomez, J. E., & McKinney, J. D. (2004). M. tuberculosis persistence, latency, and drug tolerance. Tuberculosis, 84(1-2), 29–44. https://doi.org/10.1016/j.tube.2003.08.003
- Goodsell, D. S., Morris, G. M., & Olson, A. J. (1996). Automated docking of flexible ligands: Applications of AutoDock. Journal of Molecular Recognition, 9(1), 1–5. https://doi.org/10.1002/(SICI)1099-1352(199601)9:1<1::AID-JMR241>3.0.CO;2-6
- Goyal, N., Chandra, A., Qamar, I., & Singh, N. (2019). Structural studies on dihydrouridine synthase A (DusA) from Pseudomonas aeruginosa. International Journal of Biological Macromolecules, 132, 254–264. https://doi.org/10.1016/j.ijbiomac.2019.03.209
- Greenwood, J. R., Calkins, D., Sullivan, A. P., & Shelley, J. C. (2010). Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution. Journal of Computer-Aided Molecular Design, 24(6-7), 591–604. https://doi.org/10.1007/s10822-010-9349-1
- Halgren, T. A., Murphy, R. B., Friesner, R. A., Beard, H. S., Frye, L. L., Pollard, W. T., & Banks, J. L. (2004). Glide: A new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. Journal of Medicinal Chemistry, 47(7), 1750–1759. https://doi.org/10.1021/jm030644s
- Hess, B., Bekker, H., Berendsen, H. J., & Fraaije, J. G. (1997). LINCS: A linear constraint solver for molecular simulations. Journal of Computational Chemistry, 18(12), 1463–1472. https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H
- Hess, B., Kutzner, C., van der Spoel, D., & Lindahl, E. (2008). GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. Journal of Chemical Theory and Computation, 4(3), 435–447. https://doi.org/10.1021/ct700301q
- Houben, R. M., & Dodd, P. J. (2016). The global burden of latent tuberculosis infection: A Re-estimation using mathematical modelling. PLOS Medicine, 13(10), e1002152. https://doi.org/10.1371/journal.pmed.1002152
- Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. 27–28
- Kalita, J., Shukla, R., & Tripathi, T. (2019). Structural basis of urea-induced unfolding of Fasciola gigantica glutathione S-transferase. Journal of Cellular Physiology, 234(4), 4491–4503. https://doi.org/10.1002/jcp.27253
- Krieger, I. V., Freundlich, J. S., Gawandi, V. B., Roberts, J. P., Gawandi, V. B., Sun, Q., Owen, J. L., Fraile, M. T., Huss, S. I., Lavandera, J.-L., Ioerger, T. R., & Sacchettini, J. C. (2012). Structure-guided discovery of phenyl-diketo acids as potent inhibitors of M. tuberculosis malate synthase. Chemistry & Biology, 19(12), 1556–1567. https://doi.org/10.1016/j.chembiol.2012.09.018
- Kumari, R., Kumar, R., & Lynn, A., Open Source Drug Discovery Consortium. (2014). g_mmpbsa–a GROMACS tool for high-throughput MM-PBSA calculations. Journal of Chemical Information and Modeling, 54(7), 1951–1962. https://doi.org/10.1021/ci500020m
- May, E. E., Leitão, A., Tropsha, A., & Oprea, T. I. (2013). A systems chemical biology study of malate synthase and isocitrate lyase inhibition in Mycobacterium tuberculosis during active and NRP growth. Computational Biology and Chemistry, 47, 167–180. https://doi.org/10.1016/j.compbiolchem.2013.07.002
- McFadden, B. A., & Purohit, S. (1977). Itaconate, an isocitrate lyase-directed inhibitor in Pseudomonas indigofera. Journal of Bacteriology, 131(1), 136–144. https://doi.org/10.1128/JB.131.1.136-144.1977
- McKinney, J. D., zu Bentrup, K. H., Muñoz-Elías, E. J., Miczak, A., Chen, B., Chan, W.-T., Swenson, D., Sacchettini, J. C., Jacobs, W. R., & Russell, D. G. (2000). Persistence of Mycobacterium tuberculosis in macrophages and mice requires the glyoxylate shunt enzyme isocitrate lyase. Nature, 406(6797), 735–738. https://doi.org/10.1038/35021074
- Munoz-Elias, E. J., & McKinney, J. D. (2005). Mycobacterium tuberculosis isocitrate lyases 1 and 2 are jointly required for in vivo growth and virulence. Nature Medicine, 11(6), 638–644. https://doi.org/10.1038/nm1252
- Oostenbrink, C., Villa, A., Mark, A. E., & van Gunsteren, W. F. (2004). A biomolecular force field based on the free enthalpy of hydration and solvation: The GROMOS force-field parameter sets 53A5 and 53A6. Journal of Computational Chemistry, 25(13), 1656–1676. https://doi.org/10.1002/jcc.20090
- Pandey, R. K., Verma, P., Sharma, D., Bhatt, T. K., Sundar, S., & Prajapati, V. K. (2016). High-throughput virtual screening and quantum mechanics approach to develop imipramine analogues as leads against trypanothione reductase of leishmania. Biomedicine & Pharmacotherapy, 83, 141–152. https://doi.org/10.1016/j.biopha.2016.06.010
- Pandey, T., Shukla, R., Shukla, H., Sonkar, A., Tripathi, T., & Singh, A. K. (2017). A combined biochemical and computational studies of the rho-class glutathione s-transferase sll1545 of Synechocystis PCC 6803. International Journal of Biological Macromolecules., 94(Pt A), 378–385. https://doi.org/10.1016/j.ijbiomac.2016.10.040
- 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
- Pronk, S., Páll, S., Schulz, R., Larsson, P., Bjelkmar, P., Apostolov, R., Shirts, M. R., Smith, J. C., Kasson, P. M., van der Spoel, D., Hess, B., & Lindahl, E. (2013). GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics, 29(7), 845–854. https://doi.org/10.1093/bioinformatics/btt055
- Puckett, S., Trujillo, C., Wang, Z., Eoh, H., Ioerger, T. R., Krieger, I., Sacchettini, J., Schnappinger, D., Rhee, K. Y., & Ehrt, S. (2017). Glyoxylate detoxification is an essential function of malate synthase required for carbon assimilation in Mycobacterium tuberculosis. Proceedings of the National Academy of Sciences, 114(11), E2225–E2232. https://doi.org/10.1073/pnas.1617655114
- Sastry, G. M., Adzhigirey, M., Day, T., Annabhimoju, R., & Sherman, W. (2013). Protein and ligand preparation: Parameters, protocols, and influence on virtual screening enrichments. Journal of Computer-Aided Molecular Design, 27(3), 221–234. https://doi.org/10.1007/s10822-013-9644-8
- Schuttelkopf, A. W., & van Aalten, D. M. (2004). PRODRG: A tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallographica Section D Biological Crystallography, 60(8), 1355–1363. https://doi.org/10.1107/S0907444904011679
- Shelley, J. C., Cholleti, A., Frye, L. L., Greenwood, J. R., Timlin, M. R., & Uchimaya, M. (2007). Epik: A software program for pK(a) prediction and protonation state generation for drug-like molecules. Journal of Computer-Aided Molecular Design, 21(12), 681–691. https://doi.org/10.1007/s10822-007-9133-z
- Shukla, H., Shukla, R., Sonkar, A., Pandey, T., & Tripathi, T. (2017). Distant Phe345 mutation compromises the stability and activity of Mycobacterium tuberculosis isocitrate lyase by modulating its structural flexibility. Scientific Reports, 7(1), 1058. https://doi.org/10.1038/s41598-017-01235-z
- Shukla, H., Shukla, R., Sonkar, A., & Tripathi, T. (2017). Alterations in conformational topology and interaction dynamics caused by L418A mutation leads to activity loss of Mycobacterium tuberculosis isocitrate lyase. Biochemical and Biophysical Research Communications, 490(2), 276–282. https://doi.org/10.1016/j.bbrc.2017.06.036
- Shukla, R., Chetri, P. B., Sonkar, A., Pakharukova, M. Y., Mordvinov, V. A., & Tripathi, T. (2018). Identification of novel natural inhibitors of Opisthorchis felineus cytochrome P450 using structure-based screening and molecular dynamic simulation. Journal of Biomolecular Structure and Dynamics, 36(13), 3541–3556. https://doi.org/10.1080/07391102.2017.1392897
- Shukla, R., Shukla, H., Kalita, P., Sonkar, A., Pandey, T., Singh, D. B., Kumar, A., & Tripathi, T. (2018). Identification of potential inhibitors of Fasciola gigantica thioredoxin1: Computational screening, molecular dynamics simulation, and binding free energy studies. Journal of Biomolecular Structure and Dynamics, 36(8), 2147–2162. https://doi.org/10.1080/07391102.2017.1344141
- Shukla, R., Shukla, H., Kalita, P., & Tripathi, T. (2018). Structural insights into natural compounds as inhibitors of Fasciola gigantica thioredoxin glutathione reductase. Journal of Cellular Biochemistry, 119(4), 3067–3080. https://doi.org/10.1002/jcb.26444
- Shukla, R., Shukla, H., Sonkar, A., Pandey, T., & Tripathi, T. (2018). Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase. Journal of Biomolecular Structure and Dynamics., 36(8), 2045–2057. https://doi.org/10.1080/07391102.2017.1341337
- Shukla, R., Shukla, H., & Tripathi, T. (2018). Activity loss by H46A mutation in Mycobacterium tuberculosis isocitrate lyase is due to decrease in structural plasticity and collective motions of the active site. Tuberculosis, 108, 143–150. https://doi.org/10.1016/j.tube.2017.11.013
- Shukla, R., Shukla, H., & Tripathi, T. (2019). Structural and energetic understanding of novel natural inhibitors of Mycobacterium tuberculosis malate synthase. Journal of Cellular Biochemistry, 120(2), 2469–2482. https://doi.org/10.1002/jcb.27538
- Smith, C. V., Huang, C.-C., Miczak, A., Russell, D. G., Sacchettini, J. C., & zu Bentrup, K. H. (2003). Biochemical and structural studies of malate synthase from Mycobacterium tuberculosis. Journal of Biological Chemistry, 278(3), 1735–1743. https://doi.org/10.1074/jbc.M209248200
- Smith, C. V., Sharma, V., & Sacchettini, J. C. (2004). TB drug discovery: Addressing issues of persistence and resistance. Tuberculosis, 84(1-2), 45–55. https://doi.org/10.1016/j.tube.2003.08.019
- Stewart, G. R., Robertson, B. D., & Young, D. B. (2003). Tuberculosis: A problem with persistence. Nature Reviews Microbiology, 1(2), 97–105. https://doi.org/10.1038/nrmicro749
- Trott, O., & Olson, A. J. (2009). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), NA–461. https://doi.org/10.1002/jcc.21334
- Tugarinov, V., Choy, W.-Y., Orekhov, V. Y., & Kay, L. E. (2005). Solution NMR-derived global fold of a monomeric 82-kDa enzyme. Proceedings of the National Academy of Sciences, 102(3), 622–627. https://doi.org/10.1073/pnas.0407792102
- Wallis, R. S., Maeurer, M., Mwaba, P., Chakaya, J., Rustomjee, R., Migliori, G. B., Marais, B., Schito, M., Churchyard, G., Swaminathan, S., Hoelscher, M., & Zumla, A. (2016). Tuberculosis—advances in development of new drugs, treatment regimens, host-directed therapies, and biomarkers. Lancet Infectious Diseases., 16(4), e34–e46. https://doi.org/10.1016/S1473-3099(16)00070-0
- Wayne, L. G. (1994). Dormancy of Mycobacterium tuberculosis and latency of disease. European Journal of Clinical Microbiology & Infectious Diseases, 13(11), 908–914. https://doi.org/10.1007/BF02111491
- WHO. (2018). Global Tuberculosis Report 2018. WHO. Retrieved from World Health Organization. https://www.who.int/tb/publications/global_report/tb19_Exec_Sum_medium_v4-compressed_12Nov2019.pdf?ua=1.
- Zu Bentrup, K. H., Miczak, A., Swenson, D. L., & Russell, D. G. (1999). Characterization of activity and expression of isocitrate lyase in Mycobacterium avium and Mycobacterium tuberculosis. Journal of Bacteriology, 181(23), 7161–7167. https://doi.org/10.1128/JB.181.23.7161-7167.1999
- Zuniga, E. S., Early, J., & Parish, T. (2015). The future for early-stage tuberculosis drug discovery. Future Microbiol, 10(2), 217–229. https://doi.org/10.2217/fmb.14.125