Evaluation of the inhibitory potential of Valproic acid against histone deacetylase of Leishmania donovani and computational studies of Valproic acid derivatives

References

• Ahn, W.-Y., Kalinichev, A. G., & Clark, M. M. (2008). Effects of background cations on the fouling of polyethersulfone membranes by natural organic matter: Experimental and molecular modeling study. Journal of Membrane Science, 309(1–2), 128–140. https://doi.org/10.1016/j.memsci.2007.10.023
   Web of Science ®Google Scholar
• Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of Molecular Biology, 215(3), 403–410. https://doi.org/10.1016/S0022-2836(05)80360-2
   PubMed Web of Science ®Google Scholar
• Azam, S. S., & Abbasi, S. W. (2013). Molecular docking studies for the identification of novel melatoninergic inhibitors for acetylserotonin-O-methyltransferase using different docking routines. Theoretical Biology and Medical Modelling, 10(1), 1–16. https://doi.org/10.1186/1742-4682-10-63
   PubMedGoogle Scholar
• Azam, S. S., Abro, A., Raza, S., & Saroosh, A. (2014). Structure and dynamics studies of sterol 24-C-methyltransferase with mechanism based in activators for the disruption of ergosterol biosynthesis. Molecular Biology Reports, 41(7), 4279–4293.
   PubMed Web of Science ®Google Scholar
• Baell, J. B., & Holloway, G. A. (2010). New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. Journal of Medicinal Chemistry, 53(7), 2719–2740. https://doi.org/10.1021/jm901137j
   PubMed Web of Science ®Google Scholar
• Bhowmik, D., Jagadeesan, R., Rai, P., Nandi, R., Gugan, K., & Kumar, D. (2020). Evaluation of potential drugs against leishmaniasis targeting catalytic subunit of Leishmania donovani nuclear DNA primase using ligand based virtual screening, docking and molecular dynamics approaches. Journal of Biomolecular Structure and Dynamics,39(5), 1838–1852.
   PubMed Web of Science ®Google Scholar
• Borkotoky, S., Meena, C. K., & Murali, A. (2016). Interaction analysis of T7 RNA polymerase with heparin and its low molecular weight derivatives - An in silico approach. Bioinformatics and Biology Insights, 10(BBI), BBI.S40427. https://doi.org/10.4137/BBI.S40427
   Google Scholar
• Cerveny, L., Svecova, L., Anzenbacherova, E., Vrzal, R., Staud, F., Dvorak, Z., Ulrichova, J., Anzenbacher, P., & Pavek, P. (2007). Valproic acid induces CYP3A4 and MDR1 gene expression by activation of constitutive and rostane receptor and pregnane X receptor pathways. Drug Metabolism and Disposition: The Biological Fate of Chemicals, 35(7), 1032–1041. https://doi.org/10.1124/dmd.106.014456
   PubMed Web of Science ®Google Scholar
• Chawla, B., & Madhubala, R. (2010). Drug targets in Leishmania. Journal of Parasitic Diseases, 34(1), 1–13.
   PubMedGoogle Scholar
• Colovos, C., & Yeates, T. O. (1993). Verification of protein structures: Patterns of nonbonded atomic interactions. Protein Science, 2(9), 1511–1519.
   PubMed Web of Science ®Google Scholar
• Cyrański, M. K., Jezierska, A., Klimentowska, P., Panek, J. J., & Sporzyński, A. (2008). Impact of intermolecular hydrogen bond on structural properties of phenylboronic acid: Quantum chemical and X-ray study. Journal of Physical Organic Chemistry, 21(6), 472–482. https://doi.org/10.1002/poc.1389
   Web of Science ®Google Scholar
• Gasteiger, E., Hoogland, C., Gattiker, A., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein identification and analysis tools on the ExPASy server. The Proteomics Protocols Handbook, 112, 571–607.
   Google Scholar
• Geourjon, C., & Deleage, G. (1995). SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Computer Applications in the Biosciences, 11(6), 681–684. https://doi.org/10.1093/bioinformatics/11.6.681
   PubMedGoogle Scholar
• Göttlicher, M., Minucci, S., Zhu, P., Krämer, O. H., Schimpf, A., Giavara, S., Sleeman, J. P., Lo Coco, F., Nervi, C., Pelicci, P. G., & Heinzel, T. (2001). Valproic acid defines a novel class of HDAC inhibitors inducing differentiation of transformed cells. The EMBO Journal, 20(24), 6969–6978.
   PubMed Web of Science ®Google Scholar
• Guex, N., & Peitsch, M. C. (1997). SWISS-MODEL and the Swiss-Pdb Viewer: An environment for comparative protein modeling. Electrophoresis, 18(15), 2714–2723. https://doi.org/10.1002/elps.1150181505
   PubMed Web of Science ®Google Scholar
• Gupta, C. L., Khan, M. K. A., Khan, M. F., & Tiwari, A. K. (2013). Homology modeling of LmxMPK4 of Leishmania mexicana and virtual screening of potent inhibitors against it. Interdisciplinary Sciences: Computational Life Sciences, 5(2), 136–144.
   PubMed Web of Science ®Google Scholar
• Guruprasad, K., Reddy, B. V. B., & 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, Design and Selection, 4(2), 155–161. https://doi.org/10.1093/protein/4.2.155
   Google Scholar
• 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
   PubMed Web of Science ®Google Scholar
• Hsu, K.-C., Chen, Y.-F., Lin, S.-R., & Yang, J.-M. (2011). iGEMDOCK: A graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis. BMC Bioinformatics, 12(S1), 1–11. https://doi.org/10.1186/1471-2105-12-S1-S33
   PubMedGoogle Scholar
• Ibrahim, T. S., Sheha, T. A., Abo-Dya, N. E., AlAwadh, M. A., Alhakamy, N. A., Abdel-Samii, Z. K., Panda, S. S., Abuo-Rahma, G. E.-D. A., & Mohamed, M. F. A. (2020). Design, synthesis and anticancer activity of novel valproic acid conjugates with improved histone deacetylase (HDAC) inhibitory activity. Bioorganic Chemistry, 99, 103797. https://doi.org/10.1016/j.bioorg.2020.103797
   PubMed Web of Science ®Google Scholar
• Ikai, A. (1980). Thermostability and aliphatic index of globular proteins. The Journal of Biochemistry, 88(6), 1895–1898.
   PubMed Web of Science ®Google Scholar
• Koko, W. S., Al Nasr, I. S., Khan, T. A., Schobert, R., & Biersack, B. (2022). An update on natural antileishmanial treatment options from plants, fungi and algae. Chemistry & Biodiversity, 19(1), e202100542. https://doi.org/10.1002/cbdv.202100542
   PubMed Web of Science ®Google Scholar
• Kuldeep, J., Kaur, P., Goyal, N., & Siddiqi, M. I. (2021). Identification of potential anti-leishmanial agents using computational investigation and biological evaluation against trypanothione reductase. Journal of Biomolecular Structure & Dynamics, 39(3), 960–969. https://doi.org/10.1080/07391102.2020.1721330
   PubMed Web of Science ®Google Scholar
• Kumar, A., Pandey, S. C., & Samant, M. (2018). Slow pace of antileishmanial drug development. Parasitology Open, 4, 1–11. https://doi.org/10.1017/pao.2018.1
   Google Scholar
• Lüthy, R., Bowie, J. U., & Eisenberg, D. (1992). Assessment of protein models with three-dimensional profiles. Nature, 356(6364), 83–85. https://doi.org/10.1038/356083a0
   PubMed Web of Science ®Google Scholar
• Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993). PROCHECK: A program to check the stereochemical quality of protein structures. Journal of Applied Crystallography, 26(2), 283–291. https://doi.org/10.1107/S0021889892009944
   Web of Science ®Google Scholar
• Laskowski, R. A., & Swindells, M. B. (2011). LigPlot+: Multiple ligand-protein interaction diagrams for drug discovery. ACS Publications.
   Google Scholar
• Leeson, P. (2012). Drug discovery: Chemical beauty contest. Nature, 481(7382), 455–456. https://doi.org/10.1038/481455a
   PubMed Web of Science ®Google Scholar
• Luthra, P. M., Kumar, R., & Prakash, A. (2009). Demethoxycurcumin induces Bcl-2 mediated G2/M arrest and apoptosis in human glioma U87 cells. Biochemical and Biophysical Research Communications, 384(4), 420–425.
   PubMed Web of Science ®Google Scholar
• Mabkhot, Y., Alatibi, F., El-Sayed, N., Al-Showiman, S., Kheder, N., Wadood, A., Rauf, A., Bawazeer, S., & Hadda, T. (2016). Antimicrobial activity of some novel armed thiophene derivatives and petra/osiris/molinspiration (POM) analyses. Molecules, 21(2), 222. https://doi.org/10.3390/molecules21020222
   PubMed Web of Science ®Google Scholar
• Machado, P. d. A., Carneiro, M. P. D., Sousa-Batista, A. d. J., Lopes, F. J. P., Lima, A. P. C. d. A., Chaves, S. P., Sodero, A. C. R., & de Matos Guedes, H. L. (2019). Leishmanicidal therapy targeted to parasite proteases. Life Sciences, 219, 163–181. https://doi.org/10.1016/j.lfs.2019.01.015
   PubMed Web of Science ®Google Scholar
• Maganti, L., Manoharan, P., & Ghoshal, N. (2010). Probing the structure of Leishmania donovani chagasi DHFR-TS: Comparative protein modeling and protein-ligand interaction studies. Journal of Molecular Modeling, 16(9), 1539–1547. https://doi.org/10.1007/s00894-010-0649-0
   PubMed Web of Science ®Google Scholar
• Mbongo, N., Loiseau, P. M., Billion, M. A., & Robert-Gero, M. (1998). Mechanism of amphotericin B resistance inLeishmania donovani promastigotes. Antimicrobial Agents and Chemotherapy, 42(2), 352–357. https://doi.org/10.1128/AAC.42.2.352
   PubMed Web of Science ®Google Scholar
• Mishra, C. B., Kumari, S., Prakash, A., Yadav, R., Tiwari, A. K., Pandey, P., & Tiwari, M. (2018). Discovery of novel Methylsulfonyl phenyl derivatives as potent human Cyclooxygenase-2 inhibitors with effective anticonvulsant action: Design, synthesis, in-silico, in-vitro and in-vivo evaluation. European Journal of Medicinal Chemistry, 151, 520–532. https://doi.org/10.1016/j.ejmech.2018.04.007
   PubMed Web of Science ®Google Scholar
• Morris, G. M., Huey, R., & Olson, A. J. (2008). Using autodock for ligand-receptor docking. Current Protocols in Bioinformatics, 24(1), 8.14.11–18.14.40. https://doi.org/10.1002/0471250953.bi0814s24
   Google Scholar
• O'Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. Journal of Cheminformatics, 3(1), 1–14. https://doi.org/10.1186/1758-2946-3-33
   PubMed Web of Science ®Google Scholar
• Oryan, A., & Akbari, M. (2016). Worldwide risk factors in leishmaniasis. Asian Pacific Journal of Tropical Medicine, 9(10), 925–932. https://doi.org/10.1016/j.apjtm.2016.06.021
   PubMed Web of Science ®Google Scholar
• Pandey, R. K., Kumbhar, B. V., Sundar, S., Kunwar, A., & Prajapati, V. K. (2017). Structure-based virtual screening, molecular docking, ADMET and molecular simulations to develop benzoxaborole analogs as potential inhibitor against Leishmania donovani trypanothione reductase. Journal of Receptor and Signal Transduction Research, 37(1), 60–70.
   PubMed Web of Science ®Google Scholar
• Papaleo, E., Riccardi, L., Villa, C., Fantucci, P., & De Gioia, L. (2006). Flexibility and enzymatic cold-adaptation: A comparative molecular dynamics investigation of the elastase family. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, 1764(8), 1397–1406. https://doi.org/10.1016/j.bbapap.2006.06.005
   PubMed Web of Science ®Google Scholar
• Pathak, R. K., Baunthiyal, M., Shukla, R., Pandey, D., Taj, G., & Kumar, A. (2017). In silico identification of mimicking molecules as defense inducers triggering jasmonic acid mediated immunity against alternaria blight disease in brassica species. Frontiers in Plant Science, 8, 609. https://doi.org/10.3389/fpls.2017.00609
   PubMed Web of Science ®Google Scholar
• Perrino, E., Cappelletti, G., Tazzari, V., Giavini, E., Del Soldato, P., & Sparatore, A. (2008). New sulfurated derivatives of valproic acid with enhanced histone deacetylase inhibitory activity. Bioorganic & Medicinal Chemistry Letters, 18(6), 1893–1897. https://doi.org/10.1016/j.bmcl.2008.02.007
   PubMed Web of Science ®Google Scholar
• 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
   PubMed Web of Science ®Google Scholar
• Pradeepkiran, J. A., Kumar, K. K., Kumar, Y. N., & Bhaskar, M. (2015). Modeling, molecular dynamics, and docking assessment of transcription factor rho: A potential drug target in Brucella melitensis 16M. Drug Design, Development and Therapy, 9, 1897–1912. https://doi.org/10.2147/DDDT.S77020
   PubMed Web of Science ®Google Scholar
• 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 (Oxford, England), 29(7), 845–854. https://doi.org/10.1093/bioinformatics/btt055
   PubMed Web of Science ®Google Scholar
• Raj, S., Sasidharan, S., Balaji, S. N., & Saudagar, P. (2020). An overview of biochemically characterized drug targets in metabolic pathways of Leishmania parasite. Parasitology Research, 119(7), 2025–2037.
   PubMed Web of Science ®Google Scholar
• Rajasekaran, R., & Chen, Y.-P. P. (2012). Probing the structure of Leishmania major DHFR TS and structure based virtual screening of peptide library for the identification of anti-leishmanial leads. Journal of Molecular Modeling, 18(9), 4089–4100.
   PubMed Web of Science ®Google Scholar
• Roy, S., Chakraborty, H. J., Kumar, V., Behera, B. K., Rana, R. S., & Babu, G. (2018). In silico structural studies and molecular docking analysis of Delta6-desaturase in HUFA biosynthetic pathway. Animal Biotechnology, 29(3), 161–173. https://doi.org/10.1080/10495398.2017.1332639
   PubMed Web of Science ®Google Scholar
• Sangshetti, J. N., Khan, F. A. K., Kulkarni, A. A., Arote, R., & Patil, R. H. (2015). Antileishmanial drug discovery: Comprehensive review of the last 10 years. RSC Advances, 5(41), 32376–32415. https://doi.org/10.1039/C5RA02669E
   Web of Science ®Google Scholar
• Sargsyan, K., Grauffel, C. d., & Lim, C. (2017). How molecular size impacts RMSD applications in molecular dynamics simulations. Journal of Chemical Theory and Computation, 13(4), 1518–1524.
   PubMed Web of Science ®Google Scholar
• Singh, N., Kumar, A., Gupta, P., Chand, K., Samant, M., Maurya, R., & Dube, A. (2008). Evaluation of antileishmanial potential of Tinospora sinensis against experimental visceral leishmaniasis. Parasitology Research, 102(3), 561–565. https://doi.org/10.1007/s00436-007-0822-2
   PubMed Web of Science ®Google Scholar
• Singh, N., Kumar, M., & Singh, R. K. (2012). Leishmaniasis: Current status of available drugs and new potential drug targets. Asian Pacific Journal of Tropical Medicine, 5(6), 485–497.
   PubMed Web of Science ®Google Scholar
• Singh, N. S., & Singh, D. P. (2019). A review on major risk factors and current status of visceral leishmaniasis in north India. American Journal of Entomology, 3(1), 6.
   Google Scholar
• Sixto-López, Y., Bello, M., & Correa-Basurto, J. (2020). Exploring the inhibitory activity of valproic acid against the HDAC family using an MMGBSA approach. Journal of Computer-Aided Molecular Design, 34(8), 857-878.
   PubMed Web of Science ®Google Scholar
• Sundar, S., Singh, O. P., & Chakravarty, J. (2018). Visceral leishmaniasis elimination targets in India, strategies for preventing resurgence. Expert Review of anti-Infective Therapy, 16(11), 805–812.
   PubMed Web of Science ®Google Scholar
• Thakur, L., Singh, K. K., Shanker, V., Negi, A., Jain, A., Matlashewski, G., & Jain, M. (2018). Atypical leishmaniasis: A global perspective with emphasis on the Indian subcontinent. PLoS Neglected Tropical Diseases, 12(9), e0006659. https://doi.org/10.1371/journal.pntd.0006659
   PubMed Web of Science ®Google Scholar
• Tian, W., Chen, C., Lei, X., Zhao, J., & Liang, J. (2018). CASTp 3.0: Computed atlas of surface topography of proteins. Nucleic Acids Research, 46(W1), W363–W367. https://doi.org/10.1093/nar/gky473
   PubMed Web of Science ®Google Scholar
• Torres-Santos, E. C., Sampaio-Santos, M. I., Buckner, F. S., Yokoyama, K., Gelb, M., Urbina, J. A., & Rossi-Bergmann, B. (2009). Altered sterol profile induced in Leishmania amazonensis by a natural dihydroxymethoxylated chalcone. The Journal of Antimicrobial Chemotherapy, 63(3), 469–472. https://doi.org/10.1093/jac/dkn546
   PubMed Web of Science ®Google Scholar
• Tung, E. W.-Y. (2012). The role of oxidative stress and epigenetic modifications in valproic acid-induced teratogenesis in the mouse.
   Google Scholar
• Vanommeslaeghe, K., Hatcher, E., Acharya, C., Kundu, S., Zhong, S., Shim, J., Darian, E., Guvench, O., Lopes, P., Vorobyov, I., & Mackerell, A. D. (2010). CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. Journal of Computational Chemistry, 31(4), 671–690. https://doi.org/10.1002/jcc.21367
   PubMed Web of Science ®Google Scholar
• Vargas, J. A. R., Lopez, A. G., Piñol, M. C., & Froeyen, M. (2018). Molecular docking study on the interaction between 2-substituted-4, 5-difuryl Imidazoles with different Protein Target for antileishmanial activity. Journal of Applied Pharmaceutical Science, 8(03), 014–022.
   Google Scholar
• 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–W410.
   PubMed Web of Science ®Google Scholar
• Yang, J., Roy, A., & Zhang, Y. (2013). Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment. Bioinformatics, 29(20), 2588–2595. https://doi.org/10.1093/bioinformatics/btt447
   PubMed Web of Science ®Google Scholar