Insights into the Design of Anti-inflammatory Agents Against Arthritis Based on Molecular Docking
DOI:
https://doi.org/10.20883/medical.e1612Keywords:
molecular docking, anti-inflammatory agents, arthritis, structure-activity relationship (SAR)Abstract
Introduction. Arthritis encompasses a heterogeneous group of chronic disorders, notably rheumatoid arthritis (RA) and osteoarthritis (OA), which differ mechanistically yet converge on persistent inflammation and progressive cartilage destruction. These states are mediated by overlapping inflammatory cascades, including cyclooxygenases (COX), lipoxygenases (LOX), nuclear factor-κB (NF-κB), TNF- and IL-6 cytokines, and subsequent JAK/STAT signalling. Although numerous therapeutic strategies have been developed, existing therapies are still hampered by toxicity, slower effects, or an inability to control the disease, due to a failure to counter pathway redundancy in molecular design.
Material and methods. A structured literature survey was conducted using PubMed, Scopus, Web of Science, and Google Scholar to identify peer-reviewed studies on molecular docking-guided anti-inflammatory drug design for arthritis-related targets. The relevant studies were assessed for the suitability of the target, docking process, validation method, key ligand-protein interactions, and correlation with experimental anti-inflammatory potential.
Results. The review critically analyses docking-guided studies in natural products, synthetic small molecules, and biologically inspired inhibitors, but especially aims to determine the rich structure-activity relationship (SAR) principles rather than docking scores. The main lessons involve the role of conserved binding poses, regulated molecular flexibility and target selectivity.
Conclusions. The future lies in combining docking, molecular dynamics, ADMET forecasting, and multi-target design techniques to develop sustainable arthritis therapeutics.
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References
Zhang Z, Shao Z, Xu Z, Wang J. Similarities and differences between osteoarthritis and rheumatoid arthritis: insights from Mendelian randomization and transcriptome analysis. J Transl Med. 2024;22(1):851. https://doi.org/10.1186/s12967-024-05643-4. DOI: https://doi.org/10.1186/s12967-024-05643-4
Peng X, Chen X, Zhang Y, Tian Z, Wang M, Chen Z. Advances in the pathology and treatment of osteoarthritis. J Adv Res. 2025;78:257-283. https://doi.org/10.1016/j.jare.2025.01.053. DOI: https://doi.org/10.1016/j.jare.2025.01.053
Yuan Y, Yu L, Bi C, Huang L, Su B, Nie J, et al. A new paradigm for drug discovery in the treatment of complex diseases: drug discovery and optimization. Chin Med. 2025;20(1):40. https://doi.org/10.1186/s13020-025-01075-4. DOI: https://doi.org/10.1186/s13020-025-01075-4
Martinez-Garcia M, Hernandez-Lemus E. Pro-inflammatory and anti-inflammatory interleukins in periodontitis: molecular roles, immune crosstalk, and therapeutic perspectives. Int J Mol Sci. 2025;26(20):10094. https://doi.org/10.3390/ijms262010094. DOI: https://doi.org/10.3390/ijms262010094
Harwood JL. Polyunsaturated fatty acids: conversion to lipid mediators, roles in inflammatory diseases and dietary sources. Int J Mol Sci. 2023;24(10):8838. https://doi.org/10.3390/ijms24108838. DOI: https://doi.org/10.3390/ijms24108838
Liu T, Zhang L, Joo D, Sun SC. NF-kappaB signaling in inflammation. Signal Transduct Target Ther. 2017;2:17023. https://doi.org/10.1038/sigtrans.2017.23. DOI: https://doi.org/10.1038/sigtrans.2017.23
Xue C, Yao Q, Gu X, Shi Q, Yuan X, Chu Q, et al. Evolving cognition of the JAK-STAT signaling pathway: autoimmune disorders and cancer. Signal Transduct Target Ther. 2023;8(1):204. https://doi.org/10.1038/s41392-023-01468-7. DOI: https://doi.org/10.1038/s41392-023-01468-7
Lei ZN, Tian Q, Teng QX, Wurpel JND, Zeng L, Pan Y, et al. Understanding and targeting resistance mechanisms in cancer. MedComm [2020]. 2023;4(3):e265. https://doi.org/10.1002/mco2.265. DOI: https://doi.org/10.1002/mco2.265
Kasturi J, Palla PR, Bakshi V, Bogg N. Non-steroidal anti-inflammatory drugs: an overview. J Drug Deliv Ther. 2019;9(1-s):442-448. https://doi.org/10.22270/jddt.v9i1-s.2287. DOI: https://doi.org/10.22270/jddt.v9i1-s.2287
Bindu S, Mazumder S, Bandyopadhyay U. Non-steroidal anti-inflammatory drugs (NSAIDs) and organ damage: a current perspective. Biochem Pharmacol. 2020;180:114147. https://doi.org/10.1016/j.bcp.2020.114147. DOI: https://doi.org/10.1016/j.bcp.2020.114147
Pinzi L, Rastelli G. Molecular docking: shifting paradigms in drug discovery. Int J Mol Sci. 2019;20(18):4331. https://doi.org/10.3390/ijms20184331. DOI: https://doi.org/10.3390/ijms20184331
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-461. https://doi.org/10.1002/jcc.21334. DOI: https://doi.org/10.1002/jcc.21334
Blobaum AL, Marnett LJ. Structural and functional basis of cyclooxygenase inhibition. J Med Chem. 2007;50(7):1425-1441. https://doi.org/10.1021/jm0613166. DOI: https://doi.org/10.1021/jm0613166
Chatzipieris FP, Petsas E, Lambrinidis G, Vassiliou S, Chasapis CT. Recent advances in dual COX/LOX inhibitor design (2020-2024): establishing the rule of four for inflammation. Life (Basel). 2026;16(1):163. https://doi.org/10.3390/life16010163. DOI: https://doi.org/10.3390/life16010163
Metkin G, Suntar I, Senol Deniz FS, Tugay O, Demiralp M, Pittala V. Investigating COX-2 and 5-LOX enzyme-related anti-inflammatory and antioxidant activities and phytochemical features of Scutellaria salviifolia Benth. Int J Mol Sci. 2025;26(12):5608. https://doi.org/10.3390/ijms26125608. DOI: https://doi.org/10.3390/ijms26125608
Stiller CO, Hjemdahl P. Lessons from 20 years with COX-2 inhibitors: importance of dose-response considerations and fair play in comparative trials. J Intern Med. 2022;292(4):557-574. https://doi.org/10.1111/joim.13505. DOI: https://doi.org/10.1111/joim.13505
Mohsin NUA, Aslam S, Ahmad M, Irfan M, Al-Hussain SA, Zaki MEA. Cyclooxygenase-2 (COX-2) as a target of anticancer agents: a review of novel synthesized scaffolds having anticancer and COX-2 inhibitory potentialities. Pharmaceuticals (Basel). 2022;15(12):1471. https://doi.org/10.3390/ph15121471. DOI: https://doi.org/10.3390/ph15121471
Rouzer CA, Marnett LJ. Structural and chemical biology of the interaction of cyclooxygenase with substrates and non-steroidal anti-inflammatory drugs. Chem Rev. 2020;120(15):7592-7641. https://doi.org/10.1021/acs.chemrev.0c00215. DOI: https://doi.org/10.1021/acs.chemrev.0c00215
Bello-Vargas E, Leyva-Peralta MA, Gomez-Sandoval Z, Ordonez M, Razo-Hernandez RS. A computational method for the binding mode prediction of COX-1 and COX-2 inhibitors: analyzing the union of coxibs, oxicams, propionic and acetic acids. Pharmaceuticals (Basel). 2023;16(12):1688. https://doi.org/10.3390/ph16121688. DOI: https://doi.org/10.3390/ph16121688
Zarghi A, Arfaei S. Selective COX-2 inhibitors: a review of their structure-activity relationships. Iran J Pharm Res. 2011;10(4):655-683. https://doi.org/10.22037/ijpr.2011.1047.
Gimenez-Bastida JA, Gonzalez-Sarrias A, Laparra-Llopis JM, Schneider C, Espin JC. Targeting mammalian 5-lipoxygenase by dietary phenolics as an anti-inflammatory mechanism: a systematic review. Int J Mol Sci. 2021;22(15):7937. https://doi.org/10.3390/ijms22157937. DOI: https://doi.org/10.3390/ijms22157937
Schimanski JB. Leukotriene biosynthesis influenced by natural compounds and pathogenic fungi. 2025.
Haeggstrom JZ, Newcomer ME. Structures of leukotriene biosynthetic enzymes and development of new therapeutics. Annu Rev Pharmacol Toxicol. 2023;63:407-428. DOI: https://doi.org/10.1146/annurev-pharmtox-051921-085014
Cruz A, Gonzalez-Lafont A, Lluch JM. Theoretical study of the arachidonic acid conversion into leukotriene A4 catalyzed by human 5-lipoxygenase: hydroperoxidation and epoxidation mechanisms and arachidonic acid active site access. ACS Catal. 2023;14(2):637-656. DOI: https://doi.org/10.1021/acscatal.3c04954
Spassov DS. Binding affinity determination in drug design: insights from lock and key, induced fit, conformational selection, and inhibitor trapping models. Int J Mol Sci. 2024;25(13). DOI: https://doi.org/10.3390/ijms25137124
Ibrahim SSA, Huttunen KM. Orchestrated modulation of rheumatoid arthritis via crosstalking intracellular signaling pathways. Inflammopharmacology. 2021;29(4):965-974. DOI: https://doi.org/10.1007/s10787-021-00800-3
Li CZ, Grajales S, Shuang S, Dong C, Nair M. β-amyloid biomarker detection for Alzheimer’s disease. J Anal Test. 2017;1:1-11. DOI: https://doi.org/10.1007/s41664-017-0014-8
Rosell M, Fernandez-Recio J. Docking-based identification of small-molecule binding sites at protein-protein interfaces. Comput Struct Biotechnol J. 2020;18:3750-3761. https://doi.org/10.1016/j.csbj.2020.11.061. DOI: https://doi.org/10.1016/j.csbj.2020.11.029
Saboor M, Nesraoui S, Abdulrab R, Babar S, Thabit B. The JAK-STAT pathway in rheumatoid arthritis: from mechanisms to JAK inhibitors. Egypt Rheumatol Rehabil. 2026;53(1). DOI: https://doi.org/10.1186/s43166-025-00370-0
Meszaros EC, Malemud CJ. STAT1 is constitutively activated in the T/C28a2 immortalized juvenile human chondrocyte line and stimulated by IL-6 plus soluble IL-6R. J Clin Cell Immunol. 2015;6(2):307. DOI: https://doi.org/10.4172/2155-9899.1000307
Maji L, Sengupta S, Purawarga Matada GS, Teli G, Biswas G, Das PK, et al. Medicinal chemistry perspective of JAK inhibitors: synthesis, biological profile, selectivity, and structure activity relationship. Mol Divers. 2024;28(6):4467-4513. DOI: https://doi.org/10.1007/s11030-023-10794-5
Castelo-Soccio L, Kim H, Gadina M, Schwartzberg PL, Laurence A, O’Shea JJ. Protein kinases: drug targets for immunological disorders. Nat Rev Immunol. 2023;23(12):787-806. DOI: https://doi.org/10.1038/s41577-023-00877-7
Tuzikiewicz A, Wawrzyniak W, Kutner A, Zolek T. Advances in targeting BCR-ABLT315I mutation with imatinib derivatives and hybrid anti-leukemic molecules. Molecules. 2026;31(2):341. DOI: https://doi.org/10.3390/molecules31020341
Mao H, Zhao X, Sun SC. NF-kappaB in inflammation and cancer. Cell Mol Immunol. 2025;22(8):811-839. DOI: https://doi.org/10.1038/s41423-025-01310-w
Nivatya HK, Singh A, Kumar N, Sonam, Sharma L, Singh V, et al. Assessing molecular docking tools: understanding drug discovery and design. Future J Pharm Sci. 2025;11(1). DOI: https://doi.org/10.1186/s43094-025-00862-y
Singh A, Sharma AK, Singh TG. Unlocking the therapeutic potential: exploring NF-kappaB as a viable target for diverse pharmacological approaches. Int J Pharm Pharm Sci. 2024;16:1-9. DOI: https://doi.org/10.22159/ijpps.2024v16i6.49530
Tian H, Huber M, Mower CE, Han Z, Li C, Duan X, et al. Semi-autonomous laparoscopic robot docking with learned hand-eye information fusion. IEEE Trans Biomed Eng. 2025. DOI: https://doi.org/10.1109/TBME.2025.3550974
Ouyang Z, Dong L, Yao F, Wang K, Chen Y, Li S, et al. Cartilage-related collagens in osteoarthritis and rheumatoid arthritis: from pathogenesis to therapeutics. Int J Mol Sci. 2023;24(12):9841. https://doi.org/10.3390/ijms24129841. DOI: https://doi.org/10.3390/ijms24129841
Cuffaro D, Ciccone L, Rossello A, Nuti E, Santamaria S. Targeting aggrecanases for osteoarthritis therapy: from zinc chelation to exosite inhibition. J Med Chem. 2022;65(20):13505-13532. DOI: https://doi.org/10.1021/acs.jmedchem.2c01177
Morici L, Allemann E, Jordan O, Nikolic I. Promising LOX proteins for cartilage-targeting osteoarthritis therapy. Pharmacol Res. 2025;212:107627. DOI: https://doi.org/10.1016/j.phrs.2025.107627
Mukhopadhyay N, Shukla A, Makhal PN, Kaki VR. Natural product-driven dual COX-LOX inhibitors: overview of recent studies on the development of novel anti-inflammatory agents. Heliyon. 2023;9(3). DOI: https://doi.org/10.1016/j.heliyon.2023.e14569
Ding Q, Hu W, Wang R, Yang Q, Zhu M, Li M, et al. Signaling pathways in rheumatoid arthritis: implications for targeted therapy. Signal Transduct Target Ther. 2023;8(1):68. DOI: https://doi.org/10.1038/s41392-023-01331-9
Duzgun Z, Eroglu Z. CG-COA: a coarse-grained cubic orientation approach for systematic protein-protein docking validation. J Mol Graph Model. 2025:109245. DOI: https://doi.org/10.1016/j.jmgm.2025.109245
Chen T, Shu X, Zhou H, Beckford FA, Misir M. Algorithm selection for protein-ligand docking: strategies and analysis on ACE. Sci Rep. 2023;13(1):8219. DOI: https://doi.org/10.1038/s41598-023-35132-5
de Angelo RM, de Sousa DS, da Silva AP, Chiari LP, da Silva AB, Honorio KM. Molecular docking: state-of-the-art scoring functions and search algorithms. In: Computer-Aided and Machine Learning-Driven Drug Design: From Theory to Applications. Springer; 2025. p. 163-198. DOI: https://doi.org/10.1007/978-3-031-76718-0_7
Conflitti P, Raniolo S, Limongelli V. Perspectives on ligand/protein binding kinetics simulations: force fields, machine learning, sampling, and user-friendliness. J Chem Theory Comput. 2023;19(18):6047-6061. DOI: https://doi.org/10.1021/acs.jctc.3c00641
Morales-Bayuelo A, Vivas-Reyes R, Kaya S. Analyzing a series of ligands against malaria through the application of molecular docking, molecular quantum similarity, and reactivity indices. F1000Res. 2024;13:435. DOI: https://doi.org/10.12688/f1000research.147631.1
Blanes-Mira C, Fernandez-Aguado P, de Andres-Lopez J, Fernandez-Carvajal A, Ferrer-Montiel A, Fernandez-Ballester G. Comprehensive survey of consensus docking for high-throughput virtual screening. Molecules. 2022;28(1). DOI: https://doi.org/10.3390/molecules28010175
Temml V, Kutil Z. Structure-based molecular modeling in SAR analysis and lead optimization. Comput Struct Biotechnol J. 2021;19:1431-1444. https://doi.org/10.1016/j.csbj.2021.02.016. DOI: https://doi.org/10.1016/j.csbj.2021.02.018
C S, S DK, Ragunathan V, Tiwari P, A S, P BD. Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. J Biomol Struct Dyn. 2022;40(2):585-611. DOI: https://doi.org/10.1080/07391102.2020.1815584
Mateev E, Valkova I, Angelov B, Georgieva M, Zlatkov A. Validation through re-docking, cross-docking and ligand enrichment in various well-resoluted MAO-B receptors. Int J Pharm Sci Res. 2022;13(3):1000-1007.
Prieto JM, Schottlender G, Clemente CM, Betanzos R, Fernandez Do Porto D, Marti MA. Docking and bias docking. In: Structure-Based Drug Design. Springer; 2024. p. 127-148.
Enni MA, Maraj MAA. In silico drug repurposing for inflammatory diseases: a systematic review of molecular docking and virtual screening studies. Am J Adv Technol Eng Solut. 2022;2(4):35-64. DOI: https://doi.org/10.63125/j1hbts51
Garcia-Ortegon M, Simm GN, Tripp AJ, Hernandez-Lobato JM, Bender A, Bacallado S. DOCKSTRING: easy molecular docking yields better benchmarks for ligand design. J Chem Inf Model. 2022;62(15):3486-3502. DOI: https://doi.org/10.1021/acs.jcim.1c01334
Ahmadi M, Bekeschus S, Weltmann KD, von Woedtke T, Wende K. Non-steroidal anti-inflammatory drugs: recent advances in the use of synthetic COX-2 inhibitors. RSC Med Chem. 2022;13(5):471-496. DOI: https://doi.org/10.1039/D1MD00280E
Gilbert NC, Bartlett SG, Waight MT, Neau DB, Boeglin WE, Brash AR, et al. The structure of human 5-lipoxygenase. Science. 2011;331(6014):217-219. https://doi.org/10.1126/science.1197203. DOI: https://doi.org/10.1126/science.1197203
Kahnt AS, Hafner AK, Steinhilber D. The role of human 5-lipoxygenase (5-LO) in carcinogenesis: a question of canonical and non-canonical functions. Oncogene. 2024;43(18):1319-1327. DOI: https://doi.org/10.1038/s41388-024-03016-1
Liu Y, Wang K, Cao F, Gao N, Li W. Interactions between inhibitors and 5-lipoxygenase: insights from Gaussian accelerated molecular dynamics and Markov state models. Int J Mol Sci. 2024;25(15):8295. https://doi.org/10.3390/ijms25158295. DOI: https://doi.org/10.3390/ijms25158295
Fraj E, Elbouzidi A, Bouammali H, Jaouani H, Bourhou C, Addi M, et al. Design, synthesis, and in vitro enzymatic evaluation of novel flavone derivatives as dual COX-2/5-LOX inhibitors supported by molecular docking and ADMET analysis. Curr Issues Mol Biol. 2026;48(3):243. https://doi.org/10.3390/cimb48030243. DOI: https://doi.org/10.3390/cimb48030243
El-Miligy MM, Al-Kubeisi AK, Bekhit MG, El-Zemity SR, Nassra RA, Hazzaa AA. Towards safer anti-inflammatory therapy: synthesis of new thymol-pyrazole hybrids as dual COX-2/5-LOX inhibitors. J Enzyme Inhib Med Chem. 2023;38(1):294-308. DOI: https://doi.org/10.1080/14756366.2022.2147164
Alqahtani YS, Jan MS, Mahnashi MH, Alyami BA, Alqarni AO, Rashid U, et al. Anti-inflammatory potentials of β-ketoester derivatives of N-aryl succinimides: in vitro, in vivo, and molecular docking studies. J Chem. 2022;2022:8040322. https://doi.org/10.1155/2022/8040322. DOI: https://doi.org/10.1155/2022/8040322
Saraf P, Tripathi PN, Tripathi MK, Tripathi A, Verma H, Waiker DK, et al. Novel 5,6-diphenyl-1,2,4-triazine-3-thiol derivatives as dual COX-2/5-LOX inhibitors devoid of cardiotoxicity. Bioorg Chem. 2022;129:106147. https://doi.org/10.1016/j.bioorg.2022.106147. DOI: https://doi.org/10.1016/j.bioorg.2022.106147
Boskovic J, Ruzic D, Cudina O, Nikolic K, Dobricic V. Design of dual COX-2 and 5-LOX inhibitors with iron-chelating properties using structure-based and ligand-based methods. Lett Drug Des Discov. 2022;19(4):279-292. DOI: https://doi.org/10.2174/1570180818666210714161908
M SL. Novel approach of multi-targeted thiazoles and thiazolidenes toward anti-inflammatory and anticancer therapy: dual inhibition of COX-2 and 5-LOX enzymes. Med Chem Res. 2021;30(1):236-257. DOI: https://doi.org/10.1007/s00044-020-02655-9
Sisa M, Dvorakova M, Temml V, Jarosova V, Vanek T, Landa P. Synthesis, inhibitory activity and in silico docking of dual COX/5-LOX inhibitors with quinone and resorcinol core. Eur J Med Chem. 2020;204:112620. https://doi.org/10.1016/j.ejmech.2020.112620. DOI: https://doi.org/10.1016/j.ejmech.2020.112620
Vittorio S, Lunghini F, Morerio P, Gadioli D, Orlandini S, Silva P, et al. Addressing docking pose selection with structure-based deep learning: recent advances, challenges and opportunities. Comput Struct Biotechnol J. 2024;23:2141-2151. DOI: https://doi.org/10.1016/j.csbj.2024.05.024
Nabi T, Riyed TH, Ornob A. Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of rheumatoid arthritis: virtual screening to comprehensive in silico investigation. PLoS One. 2024;19(12):e0303954. https://doi.org/10.1371/journal.pone.0303954. DOI: https://doi.org/10.1371/journal.pone.0303954
Pantsar T, Poso A. Binding affinity via docking: fact and fiction. Molecules. 2018;23(8):1899. https://doi.org/10.3390/molecules23081899. DOI: https://doi.org/10.3390/molecules23081899
Warren GL, Andrews CW, Capelli AM, Clarke B, LaLonde J, Lambert MH, et al. A critical assessment of docking programs and scoring functions. J Med Chem. 2006;49(20):5912-5931. https://doi.org/10.1021/jm050362n. DOI: https://doi.org/10.1021/jm050362n
Paggi JM, Pandit A, Dror RO. The art and science of molecular docking. Annu Rev Biochem. 2024;93:389-410. DOI: https://doi.org/10.1146/annurev-biochem-030222-120000
Huang Y, Zhang B, Li J, Liu H, Zhang Y, Yang Z, et al. Design, synthesis, biological evaluation and docking study of novel indole-2-amide as anti-inflammatory agents with dual inhibition of COX and 5-LOX. Eur J Med Chem. 2019;180:41-50. DOI: https://doi.org/10.1016/j.ejmech.2019.07.004
Wang K, Huang Y, Wang Y, You Q, Wang L. Recent advances from computer-aided drug design to artificial intelligence drug design. RSC Med Chem. 2024;15(12):3978-4000. DOI: https://doi.org/10.1039/D4MD00522H
Pasrija P, Jha P, Upadhyaya P, Khan MS, Chopra M. Machine learning and artificial intelligence: a paradigm shift in big data-driven drug design and discovery. Curr Top Med Chem. 2022;22(20):1692-1727. DOI: https://doi.org/10.2174/1568026622666220701091339
Vamathevan J, Clark D, Czodrowski P, Dunham I, Ferran E, Lee G, et al. Applications of machine learning in drug discovery and development. Nat Rev Drug Discov. 2019;18(6):463-477. https://doi.org/10.1038/s41573-019-0024-5. DOI: https://doi.org/10.1038/s41573-019-0024-5
Gentile F, Agrawal V, Hsing M, Ton AT, Ban F, Norinder U, et al. Deep docking: a deep learning platform for augmentation of structure based drug discovery. ACS Cent Sci. 2020;6(6):939-949. https://doi.org/10.1021/acscentsci.0c00229. DOI: https://doi.org/10.1021/acscentsci.0c00229
dos Santos Nascimento IJ, da Silva-Junior EF. TNF-alpha inhibitors from natural compounds: an overview, CADD approaches, and their exploration for anti-inflammatory agents. Comb Chem High Throughput Screen. 2022;25(14):2317-2340. DOI: https://doi.org/10.2174/1386207324666210715165943
Cozzini P, Kellogg GE, Spyrakis F, Abraham DJ, Costantino G, Emerson A, et al. Target flexibility: an emerging consideration in drug discovery and design. J Med Chem. 2008;51(20):6237-6255. https://doi.org/10.1021/jm800562d. DOI: https://doi.org/10.1021/jm800562d
Chai Y, Huang X. A large language model-guided reinforcement learning framework for EGFR anticancer drug design. J Comput Aided Mol Des. 2026;40(1):50. DOI: https://doi.org/10.1007/s10822-025-00753-7
Basha NJ. Small molecules as anti-inflammatory agents: molecular mechanisms and heterocycles as inhibitors of signaling pathways. ChemistrySelect. 2023;8(9):e202204723. https://doi.org/10.1002/slct.202204723. DOI: https://doi.org/10.1002/slct.202204723
Flores D, Jerves C. Computational comparison of the binding affinity of selective and nonselective NSAIDs to COX-2 using molecular docking. Bionatura J. 2025;2(3). DOI: https://doi.org/10.70099/BJ/2025.02.02.3
Rudrapal M, Eltayeb WA, Rakshit G, El-Arabey AA, Khan J, Aldosari SM, et al. Dual synergistic inhibition of COX and LOX by potential chemicals from Indian daily spices investigated through detailed computational studies. Sci Rep. 2023;13(1):8656. DOI: https://doi.org/10.1038/s41598-023-35161-0
Bastos LL, Mariano D, Lemos RP, Bialves TS, Oliveira CJF, de Melo-Minardi RC. The role of structural bioinformatics in understanding tumor necrosis factor alpha-interacting protein mechanisms in chronic inflammatory diseases: a review. Immuno. 2024;4(1):14-42. DOI: https://doi.org/10.3390/immuno4010002
Heinrich PC, Behrmann I, Muller-Newen G, Schaper F, Graeve L. Interleukin-6-type cytokine signalling through the gp130/Jak/STAT pathway. Biochem J. 1998;334(Pt 2):297-314. https://doi.org/10.1042/bj3340297. DOI: https://doi.org/10.1042/bj3340297
Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: challenges and successes. Wiley Interdiscip Rev Comput Mol Sci. 2021;11(6):e1529. https://doi.org/10.1002/wcms.1529. DOI: https://doi.org/10.1002/wcms.1529
Callis TB, Garrett TR, Montgomery AP, Danon JJ, Kassiou M. Recent scaffold hopping applications in central nervous system drug discovery. J Med Chem. 2022;65(20):13483-13504. DOI: https://doi.org/10.1021/acs.jmedchem.2c00969
Akgul O, Gul M, Gul HI. Exploring the structure-activity relationship of COX inhibitors with anticancer effects: a comprehensive review. Curr Top Med Chem. 2024. DOI: https://doi.org/10.2174/0115680266333495241011063253
Gulcin I, Alwasel SH. Metal ions, metal chelators and metal chelating assay as antioxidant method. Processes. 2022;10(1):132. https://doi.org/10.3390/pr10010132. DOI: https://doi.org/10.3390/pr10010132
Abdel-Aziz AAM, El-Azab AS, AlSaif NA, Alanazi MM, El-Gendy MA, Obaidullah AJ, et al. Synthesis, anti-inflammatory, cytotoxic, and COX-1/2 inhibitory activities of cyclic imides bearing 3-benzenesulfonamide, oxime, and β-phenylalanine scaffolds: a molecular docking study. J Enzyme Inhib Med Chem. 2020;35(1):610-621. https://doi.org/10.1080/14756366.2020.1720019. DOI: https://doi.org/10.1080/14756366.2020.1722120
Hawash M, Jaradat N, Abualhasan M, Sukuroglu MK, Qaoud MT, Kahraman DC, et al. Design, synthesis, molecular docking studies and biological evaluation of thiazole carboxamide derivatives as COX inhibitors. BMC Chem. 2023;17(1):11. https://doi.org/10.1186/s13065-023-00937-y. DOI: https://doi.org/10.1186/s13065-023-00924-3
Kiani A, Rezaee E, Tabatabai SA. Novel group of imidazole derivatives as atypical selective cyclooxygenase-2 inhibitors: design, synthesis and biological evaluation. Iran J Pharm Res. 2018;17(Suppl 2):78-86.
Alanazi AM, El-Azab AS, Al-Suwaidan IA, ElTahir KEH, Asiri YA, Abdel-Aziz NI, et al. Structure-based design of phthalimide derivatives as potential cyclooxygenase-2 (COX-2) inhibitors: anti-inflammatory and analgesic activities. Eur J Med Chem. 2015;92:115-123. https://doi.org/10.1016/j.ejmech.2014.12.039. DOI: https://doi.org/10.1016/j.ejmech.2014.12.039
Habeeb AG, Praveen Rao P, Knaus EE. Design and synthesis of celecoxib and rofecoxib analogues as selective cyclooxygenase-2 inhibitors: replacement of sulfonamide and methylsulfonyl pharmacophores by an azido bioisostere. J Med Chem. 2001;44(18):3039-3042. https://doi.org/10.1021/jm010154c. DOI: https://doi.org/10.1021/jm010153c
Bhat D, Spoorthy L, Sharanya R, Siddesh M, Kumar AU, Lokanath N. Influence of hydroxyl group in stabilizing the Schiff base crystal structure: crystal structure, computational and molecular docking studies. J Mol Struct. 2023;1280:135054. https://doi.org/10.1016/j.molstruc.2023.135054. DOI: https://doi.org/10.1016/j.molstruc.2023.135054
Kaushik V, Karmakar S, Fernandes H. Old target with new vision: in search of new therapeutics for diabetic retinopathy by selective modulation of aldose reductase. 2025. DOI: https://doi.org/10.20944/preprints202512.1408.v1
Spasov AA, Iezhitsa IN, Vassiliev PM, Ozerov AA, Agarwal R. Pharmacology of Drug Stereoisomers. Springer; 2022. DOI: https://doi.org/10.1007/978-981-19-2320-3
Love AM, Toomey CG, Kumar A, Kashyap SN, Santhamoorthy DK, Muthuraj L, et al. Reversal of the Leloir pathway to promote galactose and tagatose synthesis from glucose. Cell Rep Phys Sci. 2025;6(12). DOI: https://doi.org/10.1016/j.xcrp.2025.102993
Baek SH, Hwang S, Park T, Kwon YJ, Cho M, Park D. Evaluation of selective COX-2 inhibition and in silico study of kuwanon derivatives isolated from Morus alba. Int J Mol Sci. 2021;22(7):3659. https://doi.org/10.3390/ijms22073659. DOI: https://doi.org/10.3390/ijms22073659
Lees P, Toutain PL, Elliott J, Giraudel JM, Pelligand L, King JN. Pharmacology, safety, efficacy and clinical uses of the COX-2 inhibitor robenacoxib. J Vet Pharmacol Ther. 2022;45(4):325-351. DOI: https://doi.org/10.1111/jvp.13052
Chahal S, Rani P, Kiran, Sindhu J, Joshi G, Ganesan A, et al. Design and development of COX-II inhibitors: current scenario and future perspective. ACS Omega. 2023;8(20):17446-17498. DOI: https://doi.org/10.1021/acsomega.3c00692
Dubey V, Subba D. A comparative study of curcumin, mesalazine and COX-2 inhibitors as therapeutic agents for ulcerative colitis using a Swiss-Dock model. J Adv Immunol. 2025;2(1):18-37.
Agrawal N. A comprehensive review on the advancements of dual COX-2/5-LOX inhibitors as anti-inflammatory drugs. Chem Biol Drug Des. 2025;105(5):e70114. DOI: https://doi.org/10.1111/cbdd.70114
Abechi SE, Ejeh S, Abduljelil A. In silico screening of potential tumor necrosis factor alpha (TNF-alpha) inhibitors through molecular modeling, molecular docking, and pharmacokinetics evaluations. Sci Afr. 2023;21:e01830. https://doi.org/10.1016/j.sciaf.2023.e01830. DOI: https://doi.org/10.1016/j.sciaf.2023.e01830
Chedotal H, Narayanan D, Povlsen K, Gotfredsen CH, Brambilla R, Gajhede M, et al. Small-molecule modulators of tumor necrosis factor signaling. Drug Discov Today. 2023;28(6):103575. https://doi.org/10.1016/j.drudis.2023.103575. DOI: https://doi.org/10.1016/j.drudis.2023.103575
Raavi, Koehler AN, Vegas AJ. At the interface: small-molecule inhibitors of soluble cytokines. Chem Rev. 2025;125(9):4528-4568. DOI: https://doi.org/10.1021/acs.chemrev.4c00469
El-Hussieny M, Mansour ST, Hashem AI, Fouad MA, Abd-El-Maksoud MA. Design, synthesis, and biological evaluation of new heterocycles bearing both silicon and phosphorus as potent MMP-2 inhibitors. J Chin Chem Soc. 2022;69(11):1908-1923. DOI: https://doi.org/10.1002/jccs.202200327
Ortega-Balleza JL, Vazquez-Jimenez LK, Ortiz-Perez E, Avalos-Navarro G, Paz-Gonzalez AD, Lara-Ramirez EE, et al. Current strategy for targeting metallo-β-lactamase with metal-ion-binding inhibitors. Molecules. 2024;29(16):3944. https://doi.org/10.3390/molecules29163944. DOI: https://doi.org/10.3390/molecules29163944
Sarkar K, Debnath S, Sen D, Kar S, Sil SK. Crucial structural understanding for selective HDAC8 inhibition: common pharmacophores, molecular docking, molecular dynamics, and zinc binder analysis of selective HDAC8 inhibitors. Med Chem. 2025;21(7):597-618. DOI: https://doi.org/10.2174/0115734064320232240709105228
Li S, Shi L, Guo Y, Wang J, Liu D, Zhao S. Selective oxygen reduction reaction: mechanism understanding, catalyst design and practical application. Chem Sci. 2024;15(29):11188-11228. DOI: https://doi.org/10.1039/D4SC02853H
Kontogiorgis CA, Papaioannou P, Litina DJH. Matrix metalloproteinase inhibitors: a review on pharmacophore mapping and (Q)SARs results. Front Med Chem. 2009;4:424-462. DOI: https://doi.org/10.2174/978160805207310904010424
Akbar R, Robert PA, Weber CR, Widrich M, Frank R, Pavlovic M, et al. In silico proof of principle of machine learning-based antibody design at unconstrained scale. MAbs. 2022;14(1):2031482. https://doi.org/10.1080/19420862.2022.2031482. DOI: https://doi.org/10.1080/19420862.2022.2031482
Chen Y, Kirchmair J. Cheminformatics in natural product-based drug discovery. Mol Inform. 2020;39(12):2000171. https://doi.org/10.1002/minf.202000171. DOI: https://doi.org/10.1002/minf.202000171
Robin C, Lacroix S. Multi-robot target detection and tracking: taxonomy and survey. Auton Robots. 2016;40(4):729-760. https://doi.org/10.1007/s10514-016-9541-6. DOI: https://doi.org/10.1007/s10514-015-9491-7
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