Abstract
Natural products from medicinal plants have been increasingly used in modern medicine due to their safety, efficacy, and lesser toxicity. World over, a large number of natural compounds are evaluated for the desired bioactivity. A wide range of phytoconstituents such as alkaloids, terpenoids, tannins, steroids, etc. have been recognized for their varying biological activities. However, obtaining the natural products with the desired bioactivity is a time-consuming and commercially difficult process. Molecular docking is used for screening known as well as novel drugs to identify novel compounds by predicting their binding mode and affinity. Moreover, in silico molecular docking can be performed to analyze their binding capabilities into the 3D structure of proteins. AutoDock and AutoDockTools are open-source techniques that have been extensively cited in the literature as essential tools in structure-based drug design. These methods are fast enough to permit the virtual screening of ligand libraries containing tens of thousands of compounds. This article highlights the recent developments in the virtual screening of enzyme inhibitors using various docking tools and their significant applications in designing potent inhibitors for the management of various metabolic and infectious diseases.
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References
Almasri IM (2020) Computational approaches for the discovery of natural pancreatic lipase inhibitors as antiobesity agents. Future Med Chem 12:741–757
Anigboro AA, Avwioroko OJ, Cholu CO (2020) Phytochemical constituents, antimalarial efficacy, and protective effect of Eucalyptus camaldulensis aqueous leaf extract in plasmodium berghei-infected mice. Prev Nutr Food Sci 25:58
Avwioroko OJ, Anigboro AA, Atanu FO, Otuechere CA, Alfred MO, Abugo JN, Omorogie MO (2020) Investigation of the binding interaction of α-amylase with Chrysophyllum albidum seed extract and its silver nanoparticles: a multi-spectroscopic approach. Chem Data Collect 29:100517
Baker D, Mocek U, Garr C (2000) Natural products vs. combinatorial: a case study. In: Wrigley SK, Hayes MA, Thomas R, Chrystal EJT, Nicholson N (eds) Biodiversity: new leads for pharmaceutical and agrochemical industries. The Royal Society of Chemistry, Cambridge, pp 66–72
Bondzic AM, Sencanski MV, Nikezic AVV, Kirillova MV, Andre V, Kirillov AM, Bondzic BP (2020) Aminoalcoholate-driven tetracopper (II) cores as dual acetyl and butyrylcholinesterase inhibitors: experimental and theoretical elucidation of mechanism of action. J Inorg Biochem 205:110990
Cavasotto CN (2015) In silico drug discovery and design: theory, methods, challenges, and applications. CRC Press, Boca Raton
Chen XZ, Yu XY, Dai C, Huang QY, Shen Y, Wang J, Hu Y, Lin ZH (2022) Identification of potent CypD inhibitors via pharmacophore based virtual screening, docking and molecular dynamics simulation. J Mol Struct 1247:131355
FitzGerald RJ, Cermeno M, Khalesi M, Kleekayai T, Amigo-Benavent M (2020) Application of in silico approaches for the generation of milk protein-derived bioactive peptides. J Funct Foods 64:103636
Govindappa M (2015) A review on role of plant (s) extracts and its phytochemicals for the management of diabetes. J Diabetes Metab 6(1):38
Gyebi GA, Elfiky AA, Ogunyemi OM, Ibrahim IM, Adegunloye AP, Adebayo JO, Olaiya CO, Ocheje JO, Fabusiwa M (2021) Structure-based virtual screening suggests inhibitors of 3-chymotrypsin-like protease of SARS-CoV-2 from Vernonia amygdalina and Ocimum gratissimum. Comput Biol Med 136:104671
Hou XD, Guan XQ, Cao YF, Weng ZM, Hu Q, Liu HB, Jia SN, Zang SZ, Zhou Q, Yang L (2020) Inhibition of pancreatic lipase by the constituents in St. John’s Wort: in vitro and in silico investigations. Int J Biol Macromol 145:620–633
Huang Y, Wang H, Wang H, Wen R, Geng X, Huang T, Shi J, Wang X, Wang J (2020) Structure-based virtual screening of natural products as potential stearoyl-coenzyme a desaturase 1 (SCD1) inhibitors. Comput Biol Chem 86:107263
Ijaz M, Noor R, Nayab G, Niaz S, Basharat Z, Rastrelli L, Jayanthi S, Efferth T, Khan H (2021) Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants. Comput Biol Med 133:104362
Jayaraman M, Lakshmanan L, Karthikeyan M, Krishna R (2021) Virtual screening assisted discovery of novel natural products to inhibit the catalytic mechanism of mycobacterium tuberculosis InhA. J Mol Liquids 335:116204
Jo AR, Kim JH, Yan XT, Yang SY, Kim YH (2016) Soluble epoxide hydrolase inhibitory components from Rheum undulatum and in silico approach. J Enzyme Inhib Med Chem 31:70–78
Li W, Cui X, Chen Z (2021) Screening of lactate dehydrogenase inhibitor from bioactive compounds in natural products by electrophoretically mediated microanalysis. J Chromatogr A 1656:462554
Limanaqi F, Biagioni F, Mastroiacovo F, Polzella M, Lazzeri G, Fornai F (2020) Merging the multi-target effects of phytochemicals in neurodegeneration: from oxidative stress to protein aggregation and inflammation. Antioxidants 9:1022
Mayasah A, Anand G, Gabriel A (2018) Discovery of natural product inhibitors of phosphodiesterase 10A as novel therapeutic drug for schizophrenia using a multistep virtual screening. Comput Biol Chem 77:52–63
Mentes E, Yılmaz F, Emirik M, Ülker S, Kahveci B (2018) Synthesis, molecular docking and biological evaluation of some benzimidazole derivatives as potent pancreatic lipase inhibitors. Bioorg Chem 76:478–486
Miners JO, Smith PA, Sorich MJ, McKinnon RA, Mackenzie PI (2004) Predicting human drug glucuronidation parameters: application of in vitro and in silico modeling approaches. Annu Rev Pharmacol Toxicol 44:1–25
Moreno EN, Arvizu-Flores AA, Valenzuela-Soto EM, Garcia Orozco KD, Wall-Medrano A, Alvarez-Parrilla E, Ayala-Zavala JF, Dominguez Avila JA, Gonzalez-Aguilar GA (2020) Gallotannins are uncompetitive inhibitors of pancreatic lipase activity. Biophys Chem 264:106409
Narendra G, Raju B, Verma H, Sapra B, Silakari O (2021) Multiple machine learning models combined with virtual screening and molecular docking to identify selective human ALDH1A1 inhibitors. J Mol Graph Model 107:107950
Oyebamiji AK, Tolufashe GF, Oyawoye OM, Oyedepo TA, Semire B (2020) Biological activity of selected compounds from Annona muricata seed as antibreast cancer agents: theoretical study. J Chem 2020:6735232
Pablo AN, Rogerio AS, Diones CB, Lilian JL, Cristiane LD, Braga MM, Denis BR, Joao BTR (2015) Virtual screening of acetylcholinesterase inhibitors using the lipinski’s rule of five and zinc databank. BioMed Res Int 8:20
Padhi S, Masi M, Chourasia R, Rajashekar Y, Rai A, Evidente A (2021) ADMET profile and virtual screening of plant and microbial natural metabolites as SARS-CoV-2 S1 glycoprotein receptor binding domain and main protease inhibitors. Eur J Pharmacol 890:173648
Park H, Jung HY, Mah S, Hong S (2018) Systematic computational design and identification of low picomolar inhibitors of aurora kinase A. J Chem Inf Model 58(3):700–709
Rajguru T, Dipshikha B, Mahendra KM (2022) Identification of promising inhibitors for Plasmodium haemoglobinase Falcipain-2, using virtual screening, molecular docking, and MD simulation. J Mol Struct 1248:131427
Rauf A, Jehan N (2017) Natural products as a potential enzyme ihnhibitors from medicinal plants, enzyme inhibitors and activators, Murat Senturk. IntechOpen, London. https://www.intechopen.com/chapters/54038
Rauf B, Rashid U, Khalil A, Khan S, Anwar S, Alafnan A, Alamri A, Rengasamy KRR (2021) Docking-based virtual screening and identification of potential COVID-19 main protease inhibitors from brown algae. S Afr J Bot 143:428–434
Schames JR, Henchman RH, Siegel JS, Sotriffer CA, Ni H, McCammon JA (2004) Discovery of a novel binding trench in HIV integrase. J Med Chem 47(8):1879–1881
Siahaan P, Sasongko NA, Lusiana RA, Prasasty VD, Martoprawiro MA (2021) The validation of molecular interaction among dimer chitosan with urea and creatinine using density functional theory: in application for hemodyalisis membrane. Int J Biol Macromol 168:339–349
Singh J, Chuaqui CE, Boriack-Sjodin PA, Lee W-C, Pontz T, Corbley MJ (2003) Successful shape-based virtual screening: the discovery of a potent inhibitor of the type I TGFβ receptor kinase (TβRI). Bioorg Med Chem Lett 13(24):4355–4359
Sofiene L, Chaker BS, Houssem H, Kamel B (2014) In silico screening and study of novel ERK2 inhibitors using 3D QSAR, docking and molecular dynamics. J Mol Graph Model 53:1–12
Teli DM, Shah MB, Chhabria MT (2021) In silico screening of natural compounds as potential inhibitors of SARS-CoV-2 main protease and spike RBD: targets for COVID-19. Front Mol Biosci 7:599079
Twilley D, Langhansova L, Palaniswamy D, Lall N (2017) Evaluation of traditionally used medicinal plants for anticancer, antioxidant, anti-inflammatory and anti-viral (HPV-1) activity. S Afr J Bot 112:494–500
Van Tilbeurgh H, Egloff MP, Martinez C, Rugani N, Verger R, Cambillau C (1993) Interfacial activation of the lipase-procolipase complex by mixed micelles revealed by X-ray crystallography. Nature 362:814–820
Varady J, Wu X, Fang X, Min J, Hu Z, Levant B (2003) Molecular modeling of the three-dimensional structure of dopamine 3 (D3) subtype receptor: discovery of novel and potent D3 ligands through a hybrid pharmacophore- and structure-based database searching approach. J Med Chem 46(21):4377–4392
Winkler FK, D’Arcy A, Hunziker W (1990) Structure of human pancreatic lipase. Nature 343:771–774
Xiong F, Xiaoyu D, Hao Z, Xiaomin L, Kaixian C, Hualiang J, Cheng L, Xu H (2021) Discovery of novel reversible monoacylglycerol lipase inhibitors via docking-based virtual screening. Bioorg Med Chem Lett 41:127986
Xu J, Liangqin G, Huiqing L, Shaoliang Z, Penghua L, Shaodong C (2021) Evidence for the anti-NAFLD effectiveness of chlorogenic acid as a HAT inhibitor using in vivo experiments supported by virtual molecular docking. Phytomed Plus 1(4):100055
Yang Y, Tian JY, Ye F, Xiao Z (2020) Identification of natural products as selective PTP1B inhibitors via virtual screening. Bioorg Chem 98:103706
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Patil, M., Patil, S., Maheshwari, V.L., Zawar, L., Patil, R.H. (2022). Recent Updates on In Silico Screening of Natural Products as Potential Inhibitors of Enzymes of Biomedical and Pharmaceutical Importance. In: Maheshwari, V.L., Patil, R.H. (eds) Natural Products as Enzyme Inhibitors. Springer, Singapore. https://doi.org/10.1007/978-981-19-0932-0_4
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DOI: https://doi.org/10.1007/978-981-19-0932-0_4
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