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Current Computer-Aided Drug Design

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ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

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Research Article

A Computational Investigation on Chitosan Derivatives using Pharmacophore- based Screening, Molecular Docking, and Molecular Dynamics Simulations against Kaposi Sarcoma

Author(s): Kiruba Sakthivel, Priyanka Ganapathy, Kirubhanand Chandrasekaran, Gowtham Kumar Subbaraj and Langeswaran Kulanthaivel*

Volume 20, Issue 3, 2024

Published on: 17 May, 2023

Page: [248 - 263] Pages: 16

DOI: 10.2174/1573409919666230428100646

Price: $65

Abstract

Background: Cancer is one of the most dangerous illnesses to the human body due to its severity and progressive nature. Kaposi's Sarcoma (KS) tumor can appear as painless purple spots on the legs, foot, or face. This cancer develops in the lining of lymph arteries and blood vessels. Along with the enlargement of lymph nodes, the vaginal region and the mouth portion are the additional target areas of KS. DNA-binding proteins known as Sox proteins are found in all mammals and belong to the HMG box superfamily. They controlled a wide range of developmental procedures, such as the formation of the germ layer, the growth of organs, and the selection of the cell type. Human developmental abnormalities and congenital illnesses are frequently caused by the deletion or mutation of the Sox protein.

Aim: The purpose of this study is to determine the promising Kaposi's sarcoma inhibitors through computational studies.

Objective: In this present study computational approaches were used to evaluate the anti- carcinogenic efficacy against Kaposi's sarcoma.

Methods: Ligand-based pharmacophore screening was performed utilising four different chemical libraries (Asinex, Chembridge, Specs, and NCI Natural products (NSC)) depending on the top hypothesis. The top hits were examined using molecular docking, absorption, distribution, metabolism and excretion. Highest occupied molecular orbital and lowest unoccupied molecular orbital were analysed to determine the lead compounds' biological and pharmacological efficacy. The results of the study indicated that the leading candidates were possible SOX protein inhibitors.

Results: A pharmacophore model to inhibit the production of SOX protein in Kaposi Sarcoma was generated in this computational experiment using a set of 19 Chitosan compounds.

Conclusion: The results revealed that the top hits responded to all of the pharmacological druglikening criteria and had the best interaction residues, fitness scores, and docking scores. The resulting leads might be potential Kaposi's Sarcoma alternative treatments.

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[1]
Chalya, P.L.; Mbunda, F.; Rambau, P.F.; Jaka, H.; Masalu, N.; Mirambo, M.; Mushi, M.F.; Kalluvya, S.E. Kaposi’s sarcoma: A 10-year experience with 248 patients at a single tertiary care hospital in Tanzania. BMC Res. Notes, 2015, 8(1), 440.
[http://dx.doi.org/10.1186/s13104-015-1348-9] [PMID: 26374100]
[2]
Ruocco, E.; Ruocco, V.; Tornesello, M.L.; Gambardella, A.; Wolf, R.; Buonaguro, F.M. Kaposi’s sarcoma: Etiology and pathogenesis, inducing factors, causal associations, and treatments: Facts and controversies. Clin. Dermatol., 2013, 31(4), 413-422.
[http://dx.doi.org/10.1016/j.clindermatol.2013.01.008] [PMID: 23806158]
[3]
Gaglia, M.M. Kaposi’s sarcoma-associated herpesvirus at 27. Tumour Virus Res., 2021, 12, 200223.
[http://dx.doi.org/10.1016/j.tvr.2021.200223] [PMID: 34153523]
[4]
Glaunsinger, B.A.; Ganem, D.E. Messenger RNA turnover and its regulation in herpesviral infection. Adv. Virus Res., 2006, 66, 337-394.
[http://dx.doi.org/10.1016/S0065-3527(06)66007-7] [PMID: 16877064]
[5]
Borah, S.; Darricarrère, N.; Darnell, A.; Myoung, J.; Steitz, J.A. A viral nuclear noncoding RNA binds re-localized poly(A) binding protein and is required for late KSHV gene expression. PLoS Pathog., 2011, 7(10), e1002300.
[http://dx.doi.org/10.1371/journal.ppat.1002300] [PMID: 22022268]
[6]
Lou, T.; Yan, X.; Wang, X. Chitosan coated polyacrylonitrile nanofibrous mat for dye adsorption. Int. J. Biol. Macromol., 2019, 135, 919-925.
[http://dx.doi.org/10.1016/j.ijbiomac.2019.06.008] [PMID: 31170493]
[7]
Razmi, F.A.; Ngadi, N.; Wong, S.; Inuwa, I.M.; Opotu, L.A. Kinetics, thermodynamics, isotherm and regeneration analysis of chitosan modified pandan adsorbent. J. Clean. Prod., 2019, 231, 98-109.
[http://dx.doi.org/10.1016/j.jclepro.2019.05.228]
[8]
Modak, C.; Jha, A.; Sharma, N.; Kumar, A. Chitosan derivatives: A suggestive evaluation for novel inhibitor discovery against wild type and variants of SARS-CoV-2 virus. Int. J. Biol. Macromol., 2021, 187, 492-512.
[http://dx.doi.org/10.1016/j.ijbiomac.2021.07.144] [PMID: 34324908]
[9]
Kumar, R.; Garg, P.; Bharatam, P.V. Shape-based virtual screening, docking, and molecular dynamics simulations to identify Mtb -ASADH inhibitors. J. Biomol. Struct. Dyn., 2015, 33(5), 1082-1093.
[http://dx.doi.org/10.1080/07391102.2014.929535] [PMID: 24875451]
[10]
Pal, S.; Kumar, V.; Kundu, B.; Bhattacharya, D.; Preethy, N.; Reddy, M.P.; Talukdar, A. Ligand-based pharmacophore modeling, virtual screening and molecular docking studies for discovery of potential topoisomerase I inhibitors. Comput. Struct. Biotechnol. J., 2019, 17, 291-310.
[http://dx.doi.org/10.1016/j.csbj.2019.02.006] [PMID: 30867893]
[11]
Vijayakumar, B.; Umamaheswari, A.; Puratchikody, A.; Velmurugan, D. Selection of an improved HDAC8 inhibitor through structure-based drug design. Bioinformation, 2011, 7(3), 134-141.
[http://dx.doi.org/10.6026/97320630007134] [PMID: 22125384]
[12]
Kouassi, K.A.R.; Ganiyou, A.; Didier, D.G.G.; Benié, A.; Nahossé, Z. In silico Docking of rhodanine derivatives and 3D-QSAR study to identify potent prostate cancer inhibitors. Comput. Chem., 2022, 10(2), 19-52.
[http://dx.doi.org/10.4236/cc.2022.102002]
[13]
Zhao, S.; Li, X.; Peng, W.; Wang, L.; Ye, W.; Zhao, Y.; Yin, W.; Chen, W.D.; Li, W.; Wang, Y.D. Ligand-based pharmacophore modeling, virtual screening and biological evaluation to identify novel TGR5 agonists. RSC Advances, 2021, 11(16), 9403-9409.
[http://dx.doi.org/10.1039/D0RA10168K] [PMID: 35423434]
[14]
Schroodinger, S.R. 2: LigPrep, version 2.7; Schrödinger, LLC: New York, NY, 2013.
[15]
Release, S. 2021-4: Glide; Schrodinger, LLC: New York, NY, 2021.
[16]
Pattar, S.V.; Adhoni, S.A.; Kamanavalli, C.M.; Kumbar, S.S. In silico molecular docking studies and MM/GBSA analysis of coumarin-carbonodithioate hybrid derivatives divulge the anticancer potential against breast cancer. Beni. Suef Univ. J. Basic Appl. Sci., 2020, 9(1), 36.
[http://dx.doi.org/10.1186/s43088-020-00059-7]
[17]
Xu, M.; Lill, M.A. Induced fit docking, and the use of QM/MM methods in docking. Drug Discov. Today. Technol., 2013, 10(3), e411-e418.
[http://dx.doi.org/10.1016/j.ddtec.2013.02.003] [PMID: 24050138]
[18]
Karthick, T.; Balachandran, V.; Perumal, S.; Nataraj, A. Rotational isomers, vibrational assignments, HOMO–LUMO, NLO properties and molecular electrostatic potential surface of N-(2 bromoethyl) phthalimide. J. Mol. Struct., 2011, 1005(1-3), 202-213.
[http://dx.doi.org/10.1016/j.molstruc.2011.08.051]
[19]
Sangeetha, R. ArockiaJeyaYasmi Prabha E, Lakshmi A, Sangavi P, Langeswaran K. Molecular docking and dynamic simulations of Ocimumbasilicum compounds against HCC and structural, vibrational, quantum, and chemical investigation of campesterol. J. Biomol. Struct. Dyn., 2021, 40(24), 13997-14012.
[20]
Pradeepkiran, J.A. konidala, K.; Yellapu, N.; Bhaskar, M. Modeling, molecular dynamics, and docking assessment of transcription factor rho: A potential drug target in Brucella melitensis 16M. Drug Des. Devel. Ther., 2015, 9, 1897-1912.
[http://dx.doi.org/10.2147/DDDT.S77020] [PMID: 25848225]
[21]
Turner, P.J. Version 5.1. 19. Center for Coastal and Land-Margin Research; Oregon Graduate Institute of Science and Technology: Beaverton, 2005.
[22]
Banerjee, P.; Eckert, A.O.; Schrey, A.K.; Preissner, R. ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Res., 2018, 46(W1), W257-W263.
[http://dx.doi.org/10.1093/nar/gky318] [PMID: 29718510]

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