Mechanistic QSAR analysis to predict the binding affinity of diverse heterocycles as selective cannabinoid 2 receptor inhibitor

References

• Turkman N, Shavrin A, Ivanov RA, et al. Fluorinated cannabinoid CB2 receptor ligands: Synthesis and in vitro binding characteristics of 2-oxoquinoline derivatives. Bioorg Med Chem. 2011;19(18):5698–5707. doi:10.1016/j.bmc.2011.07.062
   PubMed Web of Science ®Google Scholar
• Han S, Zhang F-F, Qian H-Y, et al. Molecular design, synthesis and biological research of novel pyridyl acridones as potent DNA-binding and apoptosis-inducing agents. Eur J Med Chem. 2015;93:214–226. doi:10.1016/j.ejmech.2015.02.003
   PubMed Web of Science ®Google Scholar
• Markt P, Feldmann C, Rollinger JM, et al. Discovery of novel CB2 receptor ligands by a pharmacophore-based virtual screening workflow. J Med Chem. 2008;52(2):369–378.
   Web of Science ®Google Scholar
• Durdagi S, Kapou A, Kourouli T, et al. The application of 3D-QSAR studies for novel cannabinoid ligands substituted at the C1’ position of the alkyl side chain on the structural requirements for binding to cannabinoid receptors CB1 and CB2. J Med Chem. 2007;50(12):2875–2885. doi:10.1021/jm0610705
   PubMed Web of Science ®Google Scholar
• Pinna G, Loriga G, Lazzari P, et al. Tricyclic pyrazoles. Part 6. Benzofuro[3,2-c]pyrazole: A versatile architecture for CB2 selective ligands. Eur J Med Chem. 2014;82:281–292.
   PubMed Web of Science ®Google Scholar
• Porter RF, Szczesniak A-M, Toguri JT, et al. Selective cannabinoid 2 receptor agonists as potential therapeutic drugs for the treatment of endotoxin-induced uveitis. Molecules. 2019;24(18):3338.
   PubMed Web of Science ®Google Scholar
• Klegeris A, Bissonnette CJ, McGeer PL. Reduction of human monocytic cell neurotoxicity and cytokine secretion by ligands of the cannabinoid-type CB2 receptor. Br J Pharmacol. 2003;139(4):775–786. doi:10.1038/sj.bjp.0705304
   PubMed Web of Science ®Google Scholar
• Ehrin E, Gawell L, Högberg T, et al. Synthesis of [methoxy-3H]- and [methoxy-11C]- labelled raclopride. Specific dopamine-D2 receptor ligands. J Label Compds Radiopharmac. 1987;24(8):931–940. doi:10.1002/jlcr.2580240808
   Web of Science ®Google Scholar
• Gramatica P. On the development and validation of QSAR models. Comput Toxicol Meth Mol Biol. 2013;930: 499–526.
   PubMedGoogle Scholar
• Toma C, Gadaleta D, Roncaglioni A, et al. Qsar development for plasma protein binding: influence of the ionization state. Pharm Res. 2018;36(2):28.
   PubMed Web of Science ®Google Scholar
• Lee W, Park S-J, Hwang J-Y, et al. QSAR model for predicting the cannabinoid receptor 1 binding affinity and dependence potential of synthetic cannabinoids. Molecules. 2020;25(24).
   Web of Science ®Google Scholar
• Günther R, Deuther-Conrad W, Moldovan R, et al. A 3D-QSAR model for cannabinoid receptor (CB2) ligands derived from aligned pharmacophors. J Cheminform. 2013: 5(S1):P40.
   PubMedGoogle Scholar
• Floresta G, Apirakkan O, Rescifina A, et al. Discovery of high-affinity cannabinoid receptors ligands through a 3D-QSAR ushered by scaffold-hopping analysis. Molecules. 2018;23(9):2183.
   PubMed Web of Science ®Google Scholar
• Fichera M, Cruciani G, Bianchi A, et al. A 3D-QSAR study on the structural requirements for binding to CB1 and CB2 Cannabinoid receptors. J Med Chem. 2000;43(12):2300–2309. doi:10.1021/jm991074s
   PubMed Web of Science ®Google Scholar
• Patel NR, Patel DV, Murumkar PR, et al. Contemporary developments in the discovery of selective factor Xa inhibitors: A review. Eur J Med Chem. 2016;121:671–698. doi:10.1016/j.ejmech.2016.05.039
   PubMed Web of Science ®Google Scholar
• Matter H, Will DW, Nazaré M, et al. Structural requirements for factor Xa inhibition by 3-oxybenzamides with neutral P1 substituents: combining X-ray crystallography, 3D-QSAR, and tailored scoring functions. J Med Chem. 2005;48(9):3290–3312. doi:10.1021/jm049187l
   PubMed Web of Science ®Google Scholar
• Ye B, Arnaiz DO, Chou Y-L, et al. Thiophene-Anthranilamides as highly potent and orally available factor Xa inhibitors. J Med Chem. 2007;50(13):2967–2980. doi:10.1021/jm070125f
   PubMed Web of Science ®Google Scholar
• Liu T, Lin Y, Wen X, et al. BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 2007;35:D198–D201. doi:10.1093/nar/gkl999
   PubMed Web of Science ®Google Scholar
• O'Boyle NM, Banck M, James CA, et al. Open Babel: An open chemical toolbox. J Cheminform. 2011;3(1):33.
   PubMed Web of Science ®Google Scholar
• Tosco P, Balle T, Shiri F. Open3DALIGN: an open-source software aimed at unsupervised ligand alignment. J Comput Aided Mol Des. 2011;25(8):777–783. doi:10.1007/s10822-011-9462-9
   PubMed Web of Science ®Google Scholar
• Masand VH, Rastija V. PyDescriptor : A new PyMOL plugin for calculating thousands of easily understandable molecular descriptors. Chemom Intell Lab Syst. 2017;169:12–18. doi:10.1016/j.chemolab.2017.08.003
   Web of Science ®Google Scholar
• Gramatica P, Chirico N, Papa E, et al. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. J Comput Chem. 2013;34(24):2121–2132. doi:10.1002/jcc.23361
   Web of Science ®Google Scholar
• Gramatica P, Cassani S, Roy PP, et al. Qsar Modeling is not “Push a Button and Find a Correlation”: A Case Study of Toxicity of (Benzo-)triazoles on Algae. Mol Inform. 2012;31(11-12):817–835. doi:10.1002/minf.201200075
   PubMed Web of Science ®Google Scholar
• Dearden JC, Cronin MTD, Kaiser KLE. How not to develop a quantitative structure–activity or structure–property relationship (QSAR/QSPR). SAR QSAR Environ Res. 2009;20(3-4):241–266. doi:10.1080/10629360902949567
   PubMed Web of Science ®Google Scholar
• Fujita T, Winkler DA. Understanding the Roles of the “Two QSARs”. J Chem Inf Model. 2016;56(2):269–274. doi:10.1021/acs.jcim.5b00229
   PubMed Web of Science ®Google Scholar
• Gramatica P. Principles of QSAR Modeling. Intern J Quant Struct Prop Relat. 2020;5(3):61–97. doi:10.4018/IJQSPR.20200701.oa1
   Google Scholar
• Martin TM, Harten P, Young DM, et al. Does rational selection of training and test sets improve the outcome of QSAR modeling? J Chem Inf Model. 2012;52(10):2570–2578. doi:10.1021/ci300338w
   PubMed Web of Science ®Google Scholar
• Masand VH, Mahajan DT, Nazeruddin GM, et al. Effect of information leakage and method of splitting (rational and random) on external predictive ability and behavior of different statistical parameters of QSAR model. Med Chem Res. 2014;24(3):1241–1264.
   Web of Science ®Google Scholar
• Consonni V, Ballabio D, Todeschini R. Comments on the definition of the Q2 parameter for QSAR validation. J Chem Inf Model. 2009;49(7):1669–1678. doi:10.1021/ci900115y
   PubMed Web of Science ®Google Scholar
• Consonni V, Todeschini R, Ballabio D, et al. On the misleading Use of QF32 for QSAR model comparison. Mol Inform. 2019;38(1-2). doi:10.1002/minf.201800029
   Web of Science ®Google Scholar
• Chirico N, Gramatica P. Real external predictivity of QSAR models: How To evaluate It? comparison of different validation criteria and proposal of using the concordance correlation coefficient. J Chem Inf Model. 2011;51(9):2320–2335. doi:10.1021/ci200211n
   PubMed Web of Science ®Google Scholar
• Cherkasov A, Muratov EN, Fourches D, et al. QSAR modeling: where have you been? Where are you going to? J Med Chem. 2014;57(12):4977–5010. doi:10.1021/jm4004285
   PubMed Web of Science ®Google Scholar
• Consonni V, Ballabio D, Todeschini R. Comments on the definition of the Q2 parameter for QSAR validation. J Chem Inf Model. 2009;49(7):1669–1678. doi:10.1021/ci900115y
   PubMed Web of Science ®Google Scholar
• Zaki MEA, Al-Hussain SA, Masand VH, et al. Qsar and pharmacophore modeling of nitrogen heterocycles as potent human N-myristoyltransferase (Hs-NMT) inhibitors. Molecules. 2021;26(7):1834.
   PubMed Web of Science ®Google Scholar
• Li X, Hua T, Vemuri K, et al. Crystal structure of the human cannabinoid receptor CB2. Cell. 2019;176(3):459–467. doi:10.1016/j.cell.2018.12.011
   PubMed Web of Science ®Google Scholar
• Gaudreault F, Morency L-P, Najmanovich RJ. NRGsuite: a PyMOL plugin to perform docking simulations in real time using FlexAID. Bioinformatics. 2015;31(23):3856–3858.
   PubMed Web of Science ®Google Scholar
• Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7(1). doi:10.1038/s41598-022-25895-8
   PubMedGoogle Scholar
• Abchir O, Yamari I, Nour H, et al. Structure-based virtual screening, ADMET analysis, and molecular dynamics simulation of Moroccan natural compounds as candidates α-amylase inhibitors. ChemistrySelect. 2023;8(26):1092.
   Web of Science ®Google Scholar
• Abchir O, Daoui O, Nour H, et al. Exploration of Cannabis constituents as potential candidates against diabetes mellitus disease using molecular docking, dynamics simulations and ADMET investigations. Scientific African. 2023;21:e01745.
   Google Scholar
• Daoui O, Mali SN, Elkhattabi K, et al. Repositioning Cannabinoids and Terpenes as Novel EGFR-TKIs Candidates for Targeted Therapy Against Cancer: A virtual screening model using CADD and biophysical simulations. Heliyon. 2023;9(4):e15545.
   PubMed Web of Science ®Google Scholar
• Shivakumar D, Williams J, Wu Y, et al. Prediction of absolute solvation free energies using molecular dynamics free energy perturbation and the OPLS force field. J Chem Theory Comput. 2010;6(5):1509–1519. doi:10.1021/ct900587b
   PubMed Web of Science ®Google Scholar
• Jorgensen WL, Chandrasekhar J, Madura JD, et al. Comparison of simple potential functions for simulating liquid water. J Chem Phys. 1983;79(2):926–935. doi:10.1063/1.445869
   Web of Science ®Google Scholar
• Martyna GJ, Klein ML, Tuckerman M. Nosé–Hoover chains: The canonical ensemble via continuous dynamics. J Chem Phys. 1992;97(4):2635–2643. doi:10.1063/1.463940
   Web of Science ®Google Scholar
• Toukmaji AY, Board JA. Ewald summation techniques in perspective: a survey. Comput Phys Commun. 1996;95(2-3):73–92. doi:10.1016/0010-4655(96)00016-1
   Web of Science ®Google Scholar
• Kagami LP, das Neves GM, Timmers LFSM, et al. Geo-measures: A PyMOL plugin for protein structure ensembles analysis. Comput Biol Chem. 2020;87:107322.
   PubMed Web of Science ®Google Scholar
• Ghosh A, Mukerjee N, Sharma B, et al. Target specific inhibition of protein tyrosine kinase in conjunction with cancer and SARS-COV-2 by olive nutraceuticals. Front Pharmacol. 2022;12:812565.
   PubMed Web of Science ®Google Scholar
• Masand VH, El-Sayed NNE, Bambole MU, et al. Multiple quantitative structure-activity relationships (QSARs) analysis for orally active trypanocidal N-myristoyltransferase inhibitors. J Mol Struct. 2019;1175:481–487. doi:10.1016/j.molstruc.2018.07.080
   Web of Science ®Google Scholar
• Masand VH, Mahajan DT, Alafeefy AM, et al. Optimization of antiproliferative activity of substituted phenyl 4-(2-oxoimidazolidin-1-yl) benzenesulfonates: QSAR and CoMFA analyses. Eur J Pharm Sci. 2015;77:230–237.
   PubMed Web of Science ®Google Scholar
• Zhou L, Zhou S, Yang P, et al. Targeted inhibition of the type 2 cannabinoid receptor is a novel approach to reduce renal fibrosis. Kidney Int. 2018;94(4):756–772. doi:10.1016/j.kint.2018.05.023
   PubMed Web of Science ®Google Scholar
• Xiang W, Shi R, Kang X, et al. Monoacylglycerol lipase regulates cannabinoid receptor 2-dependent macrophage activation and cancer progression. Nat Commun. 2018;9(1):2574.
   PubMed Web of Science ®Google Scholar
• Shire D, Calandra B, Bouaboula M, et al. Cannabinoid receptor interactions with the antagonists SR 141716A and SR 144528. Life Sci. 1999;65(6-7):627–635. doi:10.1016/S0024-3205(99)00285-4
   PubMed Web of Science ®Google Scholar
• Cichero E, Menozzi G, Guariento S, et al. Ligand-based homology modelling of the human CB2 receptor SR144528 antagonist binding site: a computational approach to explore the 1,5-diaryl pyrazole scaffold. MedChemComm. 2015;6(11):1978–1986. doi:10.1039/C5MD00333D
   Web of Science ®Google Scholar
• Ji B, Liu S, He X, et al. Prediction of the binding affinities and selectivity for CB1 and CB2 ligands using homology modeling, molecular docking, molecular dynamics simulations, and MM-PBSA binding free energy calculations. ACS Chem Neurosci. 2020;11(8):1139–1158. doi:10.1021/acschemneuro.9b00696
   PubMed Web of Science ®Google Scholar
• Bertini S, Chicca A, Arena C, et al. Synthesis and pharmacological evaluation of new biphenylic derivatives as CB 2 receptor ligands. Eur J Med Chem. 2016;116:252–266. doi:10.1016/j.ejmech.2016.03.072
   PubMed Web of Science ®Google Scholar
• Waring MJ. Lipophilicity in drug discovery. Expert Opin Drug Discov. 2010;5(3):235–248. doi:10.1517/17460441003605098
   PubMed Web of Science ®Google Scholar
• Delaney JS. Esol: estimating aqueous solubility directly from molecular structure. J Chem Inf Comput Sci. 2004;44(3):1000–1005. doi:10.1021/ci034243x
   PubMedGoogle Scholar
• Ali J, Camilleri P, Brown MB, et al. In silico prediction of aqueous solubility using simple QSPR models: the importance of phenol and phenol-like moieties. J Chem Inf Model. 2012;52(11):2950–2957. doi:10.1021/ci300447c
   PubMed Web of Science ®Google Scholar
• Daina A, Zoete V. A BOILED-Egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem. 2016;11(11):1117–1121. doi:10.1002/cmdc.201600182
   PubMed Web of Science ®Google Scholar
• Thomas H, Coley HM. Overcoming multidrug resistance in cancer: An update on the clinical strategy of inhibiting P-glycoprotein. Cancer Control. 2017;10(2):159–165.
   Google Scholar
• Bickerton GR, Paolini GV, Besnard J, et al. Quantifying the chemical beauty of drugs. Nat Chem. 2012;4(2):90–98. doi:10.1038/nchem.1243
   PubMed Web of Science ®Google Scholar
• Martin YC. A bioavailability score. J Med Chem. 2005;48(9):3164–3170. doi:10.1021/jm0492002
   PubMed Web of Science ®Google Scholar
• Lipinski CA, Lombardo F, Dominy BW, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2012;64:4–17. doi:10.1016/j.addr.2012.09.019
   Web of Science ®Google Scholar
• Brown NP, Orengo CA, Taylor WR. A protein structure comparison methodology. Comput Chem. 1996;20(3):359–380. doi:10.1016/0097-8485(95)00062-3
   Google Scholar