Virtual Screening of COX-2 Inhibitory Components in Huoluowan(HLW) for Treatment of Osteoarthritis Based on Pharmacophore Model
ZHANG Mina,b, LI Chao-xina,b, YAO Juana,b, QIU Luc, ZHANG Hao-boa,b, LIU Yong-qic,d*, JIN Xiao-jiea,b,c*
a. School of Pharmacy; b. Northwest Collaborative Innovation Center for Chinese Medicine; c. Gansu University Key Laboratory for Molecular Medicine and Chinese Medicine Prevention and Treatment of Major Diseases; d. Dunhuang Key Laboratory of Medicine and Transformation, Ministry of Education, Gansu University of Chinese Medicine, Lanzhou 730000, China
Abstract：OBJECTIVE To explore the components in Huoluowan(HLW) that inhibit cyclooxygenase-2(COX-2) by using the hierarchical virtual screening strategy of pharmacophore, molecular docking, free energy calculation combined enzyme activity inhibition experiment. METHODS The phase module in Schrödinger 2020-4 software was used to construct the pharmacophore model of COX-2 small molecule inhibitor, the selected optimal pharmacophore model was used to screen virtually the traditional Chinese medicine compound library of HLW, and the screened components that meet the pharmacophore model are subjected to molecular docking and binding free energy calculation based on target structure. The potential inhibitory components were selected for enzyme activity determination, and the pharmacokinetic and toxicological properties of small molecules with good activity were predicted. RESULTS The best pharmacophore model has two hydrogen bond receptors and two aromatic ring centers. The enzyme activity assay results showed that all the small molecules had different degrees of inhibition on COX-2 and the component with stronger inhibition activity was epicatechin with IC50 of (0.93±0.15)μmol·L-1, the IC50 of luteolin was (1.96±0.19)μmol·L-1, the IC50 of quercetin was (2.09±0.28)μmol·L-1, ADMET calculation results showed that luteolin, epicatechin and quercetin had good drug properties. CONCLUSION In this study, pharmacophore model, molecular docking, combined free energy calculation and in vitro enzyme activity inhibition experiment are used to excavate the components in HLW that inhibit COX-2. At the same time, it provides clues for the modern research of the monomer components of traditional Chinese medicine for osteoarthritis.
张敏, 李潮新, 姚娟, 邱璐, 张浩波, 刘永琦, 靳晓杰. 基于药效团模型虚拟筛选活络丸中治疗骨关节炎的COX-2抑制成分[J]. 中国药学杂志, 2022, 57(20): 1742-1749.
ZHANG Min, LI Chao-xin, YAO Juan, QIU Lu, ZHANG Hao-bo, LIU Yong-qi, JIN Xiao-jie. Virtual Screening of COX-2 Inhibitory Components in Huoluowan(HLW) for Treatment of Osteoarthritis Based on Pharmacophore Model. Chinese Pharmaceutical Journal, 2022, 57(20): 1742-1749.
HUNTER D J, BIERMA-ZEINSTRA S. Osteoarthritis[J]. Lancet, 2019, 393(10182):1745-1759.
[2]
WALLACE I J, WORTHINGTON S, FELSON D, et al. Knee osteoarthritis has doubled in prevalence since the mid-20th century[J]. Proc Natl Acad Sci USA, 2017, 114(35):9332-9336.
[3]
ZHU Z H, LI J,RUAN G F, et al. Investigational drugs for the treatment of osteoarthritis, an update on recent developments[J]. Expert Opin Investig Drugs, 2018,27(11):881-900.
[4]
Joint Surgery Group, Chinese Society of Osteology, Chinese Medical Association. Chinese clinical practice guideline for pain management in osteoarthritis(2020 edition)[J]. Chin J Orthop(中华骨科杂志), 2020,46(8): 469-476.
[5]
DU X L. Cyclooxygenase-2 specific inhibitor-ericoxib[J]. Chin Pharm J(中国药学杂志), 2012, 47(5): 399-400.
[6]
JOHNSON A G, QUINN D I, DAY R O. Non-steroidal anti-inflammatory drugs[J]. Med J Aust,1995,163(3):155-158.
[7]
JONIT SURGERY GROUP, OSTEOLOGY SOCIETY, CHINESE MEDICAL ASSOCIATION. Chinese clinical practice guideline for pain management in osteoarthritis (2020 edition)[J]. Chin J Orthop(中华骨科杂志),2020, 40(8): 469-476.
[8]
ZHU L G,ZHOU S Q, WEI X, et al. Clinical research progress in treatment of knee osteoarthritis with traditional Chinese medicine[J]. Med Recapit(医学综述), 2021, 27(5): 973-977.
[9]
ZHANG J D, YE P H, MA J, et al. Discussion on the inheritance and innovation of traditional Chinese patent medicines and simple preparations intervention in subhealth[J]. China J Tradit Chin Med Pharm(中华中医药杂志), 2021, 36(3): 1278-1281.
[10]
CHEN R. Clinical application analysis of Huoluo pill[J]. Chin Comm Doc(中国社区医师), 2012, 28(13): 12.
[11]
SEIDEL T, SCHUETZ D A, GARON A, et al. The Pharmacophore concept and its applications in computer-aided drug design[J]. Prog Chem Org Nat Prod, 2019, 110: 99-141.
[12]
CUI W Q, AOUIDATE A, WANG S G, et al. Discovering anti-cancer drugs via computational methods[J]. Front Pharmacol, 2020, 11:733. Doi: 10.3389/fphar.2020.00733.
[13]
RU J L, LI P, WANG J A, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines[J]. J Cheminform, 2014, 6:13. Doi: 10.1186/1758-2946-6-13.
[14]
XUE R C, FANG Z, ZHANG M X, et al. TCMID: Traditional Chinese Medicine integrative database for herb molecular mechanism analysis[J]. Nucleic Acids Res, 2013, 41(Database issue): D1089-D095.
[15]
SHARMA V, BHATIA P, ALAM O, et al. Recent advancement in the discovery and development of COX-2 inhibitors: insight into biological activities and SAR studies(2008-2019)[J]. Bioorg Chem,2019, 89:103007. Doi: 10.1016/j.bioorg.2019.103007.
[16]
DIXON S L, SMONDYREV A M, KNOLL E H, et al. PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results[J]. J Comput Aided Mol Des, 2006, 20(10-11):647-671.
[17]
CHANG G, GUIDA W C, STILL W C. An internal-coordinate Monte Carlo method for searching conformational space[J]. J Am Chem Soc, 1989, 111(12): 4379-4386.
[18]
HE S, LI C, LIU Y, et al. Discovery of highly potent microsomal prostaglandin e2 synthase 1 inhibitors using the active conformation structural model and virtual screen[J]. J Med Chem, 2013, 56(8): 3296-3309.
[19]
LIAO C Z, SITZMANN M, PUGLIESE A, et al. Software and resources for computational medicinal chemistry[J]. Future Med Chem, 2011, 3(8): 1057-1085.
[20]
CUTINHO P F, SHANKAR R C, ANAND A, et al. Hit identification and drug repositioning of potential non-nucleoside reverse transcriptase inhibitors by structure-based approach using computational tools(part II)[J]. J Biomol Struct Dyn, 2020, 38(13):3772-3789.
[21]
JIN X J, WANG Y R, WANG Y, et al. Explore the material basis of treating pulmonary fibrosis with Yifei Jianpi prescription based on network pharmacology, molecular docking and chemical informatics[J]. Chin J Mod Appl Pharm(中国现代应用药学), 2020, 37(8): 897-906.
[22]
CUTINHO P F, ROY J, ANAND A, et al. Design of metronidazole derivatives and flavonoids as potential non-nucleoside reverse transcriptase inhibitors using combined ligand- and structure-based approaches[J]. J Biomol Struct Dyn, 2020, 38(6):1626-1648.
[23]
MATTER H, SCHIDER W. In-Silico ADME Modeling. Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays[M]. Berlin: Springer,2013:1005-1052.
[24]
BANERJEE P, ECKERT A O, SCHREY A K, et al. ProTox-II: a webserver for the prediction of toxicity of chemicals[J]. Nucleic Acids Res, 2018(W1): W257-W263.
[25]
FANG C, XIAO Z Y. Receptor-based 3D-QSAR in drug design: methods and applications in kinase studies[J]. Curr Top Med Chem, 2016, 16(13):1463-1477.
[26]
KB S, KUMARI A, SHETTY D, et al. Structure based pharmacophore modelling approach for the design of azaindole derivatives as DprE1 inhibitors for Tuberculosis[J]. J Mol Graph Model, 2020, 101: 107718. Doi: 10.1016/j.jmgm.2020.107718.
[27]
ROHINI K, RAMANATHAN K, SHANTHI V. Multi-dimensional screening strategy for drug repurposing with statistical framework-a new road to influenza drug discovery[J]. Cell Biochem Biophys, 2019, 77(4):319-333.
[28]
KIEFER J R, PAWLITZ J L, MORELAND K T, et al. Structural insights into the stereochemistry of the cyclooxygenase reaction[J]. Nature, 2000, 405(6782): 97-101.
[29]
YAN Y M, ZHANG H X, LIU H, et al.(+/)-Lucidumone, a COX-2 inhibitory caged fungal meroterpenoid from ganoderma lucidum[J]. Org Lett, 2019, 21(21) :8523-8527.
[30]
CHIKOWE I, PHIRI A C, MBEWE K P, et al. In-silico evaluation of Malawi essential medicines and reactive metabolites for potential drug-induced toxicities[J]. BMC Pharmacol Toxicol, 2021, 22(1): 36. Doi: 10.1186/s40360-021-00499-6.
[31]
LIPINSKI C A, LOMBARDO F, DOMINY B W, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings[J]. Adv Drug Deliv Rev, 2001, 46(1-3):3-26.
[32]
HOU T J, WANG J M, LI Y Y, et al. Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations[J]. J Chem Inf Model, 2011, 51(1):69-82.
[33]
AJAY, BEMIS G W, MURCKO M A. Designing libraries with CNS activity[J]. J Med Chem, 1999, 42(24): 4942-4951.
[34]
KARLE M, KNECHT W, XUE Y F. Discovery of benzothiazole guanidines as novel inhibitors of thrombin and trypsin IV[J]. Bioorg Med Chem Lett, 2012, 22(14) :4839-4843.
[35]
MARGULIS E, DAGAN-WIENER A, IVES R S, et al. Intense bitterness of molecules: Machine learning for expediting drug discovery[J]. Comput Struct Biotechnol J, 2021, 19: 568-576.
[36]
GAO L, LIU A L, DU G H. Application progress of computer aided drug design in drug development process[J]. Chin Pharm J(中国药学杂志), 2011, 46(9): 641-645.
[37]
CHEN G Y, CHEN J Q, LIU X Y, et al. Total flavonoids of rhizoma drynariae restore the MMP/TIMP balance in models of osteoarthritis by inhibiting the activation of the NF- κ B and PI3K/AKT pathways[J]. Evid Based Complement Alternat Med, 2021, 2021 :6634837. Doi: 10.1155/2021/6634837.
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