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Ligand-based design of anticancer MMP2 inhibitors: a review

    Saptarshi Sanyal

    Natural Science Laboratory, Division of Medicinal & Pharmaceutical Chemistry, Department of Pharmaceutical Technology, PO Box 17020, Jadavpur University, Kolkata, 700032, India

    School of Medical Sciences, Adamas University, Kolkata, India

    ,
    Sk Abdul Amin

    Natural Science Laboratory, Division of Medicinal & Pharmaceutical Chemistry, Department of Pharmaceutical Technology, PO Box 17020, Jadavpur University, Kolkata, 700032, India

    ,
    Nilanjan Adhikari

    Natural Science Laboratory, Division of Medicinal & Pharmaceutical Chemistry, Department of Pharmaceutical Technology, PO Box 17020, Jadavpur University, Kolkata, 700032, India

    &
    Tarun Jha

    *Author for correspondence:

    E-mail Address: tjupharm@yahoo.com

    Natural Science Laboratory, Division of Medicinal & Pharmaceutical Chemistry, Department of Pharmaceutical Technology, PO Box 17020, Jadavpur University, Kolkata, 700032, India

    Published Online:https://doi.org/10.4155/fmc-2021-0262

    MMP2, a Zn2+-dependent metalloproteinase, is related to cancer and angiogenesis. Inhibition of this enzyme might result in a potential antimetastatic drug to leverage the anticancer drug armory. In silico or computer-aided ligand-based drug design is a method of rational drug design that takes multiple chemometrics (i.e., multi-quantitative structure–activity relationship methods) into account for virtually selecting or developing a series of probable selective MMP2 inhibitors. Though existing matrix metalloproteinase inhibitors have shown plausible pan-matrix metalloproteinase (MMP) activity, they have resulted in various adverse effects leading to their being rescinded in later phases of clinical trials. Therefore a review of the ligand-based designing methods of MMP2 inhibitors would result in an explicit route map toward successfully designing and synthesizing novel and selective MMP2 inhibitors.

    Papers of special note have been highlighted as: • of interest; •• of considerable interest

    References

    • 1. Mowers EE, Sharifi MN, Macleod KF. Autophagy in cancer metastasis. Oncogene 36, 1619–1630 (2017).
    • 2. Seyfried TN, Huysentruyt LC. On the origin of cancer metastasis. Crit. Rev. Oncog. 18, 43–73 (2013).
    • 3. Anand P, Kunnumakara AB, Sundaram C et al. Cancer is a preventable disease that requires major lifestyle changes. Pharm. Res. 25, 2097–2116 (2008).
    • 4. World Health Organisation. The top 10 causes of death (2018). www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
    • 5. International Agency for Research on Cancer. All cancers (excluding non-melanoma skin cancer) estimated incidence, mortality and prevalence worldwide (2012). http://globocan.iarc.fr
    • 6. Bray F, Ferlay J, Soerjomataram I, Siegel R, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394–424 (2018).
    • 7. De Vita VT Jr, Chu E. A history of cancer chemotherapy. Cancer Res. 68(21), 8643–8653 ( 2008).
    • 8. Adhikari N. Glutamine derivatives and analogs as matrix metalloproteinase-2 inhibitors: rational design, synthesis, biological screening and molecular modeling studies [PhD Thesis]. Jadavpur University, Kolkata, India (2018).
    • 9. Gialeli C, Theocharis AD, Karamanos NK. Roles of matrix metalloproteinases in cancer progression and their pharmacological targeting. FEBS J. 278, 16–27 (2011).
    • 10. Adhikari N, Amin SA, Saha A, Jha T. Understanding chemico-biological interactions of glutamate MMP-2 inhibitors through rigorous alignment-dependent 3D-QSAR analyses. Chem. Sel. 2, 7888–7898 (2017).
    • 11. Frantz C, Stewart KM, Weaver VM. The extracellular matrix at a glance. J. Cell Sci. 123, 4195–4200 (2010).
    • 12. Jarvelainen H, Sainio A, Koulu M, Wight TN, Penttinen R. Extracellular matrix molecules: potential targets in pharmacotherapy. Pharmacol. Rev. 61, 198–223 (2009).
    • 13. Hynes RO. The extracellular matrix: not just pretty fibrils. Science 326, 1216–1219 (2009).
    • 14. Bonnans C, Chou J, Werb Z. Remodelling the extracellular matrix in development and disease. Nat. Rev. Mol. Cell Biol. 15, 786–801 (2014).
    • 15. Adhikari N, Amin SA, Saha A, Jha T. Structural exploration for the refinement of anticancer matrix metalloproteinase-2 inhibitor designing approaches through robust validated multi-QSARs. J. Mol. Struct. 1156, 501–515 (2018).
    • 16. Adhikari N, Amin SA, Saha A, Jha T. Exploring in house glutamate inhibitors of matrix metalloproteinase-2 through validated robust chemico-biological quantitative approaches. Struct. Chem. 29, 285–297 (2018).
    • 17. Naveed M, Han L, Hasnat M et al. Suppression of TGP on myocardial remodeling by regulating the NF-κB pathway. Biomed. Pharmacother. 108, 1460–1468 (2018).
    • 18. Xue C, Wu N, Li X, Qiu M, Du X, Ye Q. Serum concentrations of Krebs von den Lungen-6, surfactant protein D, and matrix metalloproteinase-2 as diagnostic biomarkers in patients with asbestosis and silicosis: a case–control study. BMC Pulm. Med. 17, 144 (2017).
    • 19. Fang JH, Zhou HC, Zeng C et al. MicroRNA-29b suppresses tumor angiogenesis, invasion, and metastasis by regulating matrix metalloproteinase 2 expression. Hepatology 54, 1729–1740 (2011).
    • 20. Halder AK, Saha A, Jha T. Exploring QSAR and pharmacophore mapping of structurally diverse selective matrix metalloproteinase-2 inhibitors. J. Pharm. Pharmacol. 65, 1541–1554 (2013).
    • 21. Adhikari N, Halder AK, Mallick S, Saha A, Saha KD, Jha T. Robust design of some selective matrix metalloproteinase-2 inhibitors over matrix metalloproteinase-9 through in silico/fragment-based lead identification and de novo lead modification: syntheses and biological assays. Bioorg. Med. Chem. 24, 4291–4309 (2016). • Covers a multi-QSAR approach for designing aryl sulfonamide glutamine derivatives.
    • 22. Jha T, Adhikari N, Saha A, Amin SA. Multiple molecular modelling studies on some derivatives and analogues of glutamic acid as matrix metalloproteinase-2 inhibitors. SAR QSAR Environ. Res. 29, 43–68 (2018).
    • 23. Sanyal S, Amin SA, Adhikari N, Jha T. QSAR modeling on a series of arylsulphonamide-based hydroxamates as potent MMP-2 inhibitors. SAR QSAR Environ. Res. 30, 247–263 (2019).
    • 24. Adhikari N, Amin SA, Jha T. Collagenases and gelatinases and their inhibitors as anticancer agents. In: Cancer Leading Proteases. 1st Edition. Gupta SP (Ed.). Chapter 10 Elsevier, MA, USA 265–294 (2020).
    • 25. Jabłońska-Trypuć A, Matejczyk M, Rosochacki S. Matrix metalloproteinases (MMPs), the main extracellular matrix (ECM) enzymes in collagen degradation, as a target for anticancer drugs. J. Enzyme Inhib. Med. Chem. 31, 177–183 (2016).
    • 26. Adhikari N, Mukherjee A, Saha A, Jha T. Arylsulfonamides and selectivity of matrix metalloproteinase-2: an overview. Eur. J. Med. Chem. 129, 72–109 (2017). • Covers important topics on some arylsulfonamides with great MMP2 inhibitory activity.
    • 27. Fanjul-Fernández M, Folgueras AR, Cabrera S, López-Otín C. Matrix metalloproteinases: evolution, gene regulation and functional analysis in mouse models. Biochim. Biophys. Acta 1803, 3–19 (2010).
    • 28. Murphy G, Knauper V. Relating matrix metalloproteinase structure to function: why the ‘hemopexin’ domain? Matrix Biol. 15, 511–518 (1997).
    • 29. Tester AM, Cox JH, Connor AR et al. LPS responsiveness and neutrophil chemotaxis in vivo require PMN MMP-8 activity. PLoS ONE 2, e312 (2007).
    • 30. Gearing AJ, Beckett P, Christodoulou M et al. Processing of tumour necrosis factor-alpha precursor by metalloproteinases. Nature 370, 555–557 (1994).
    • 31. Stolow MA, Bauzon DD, Li J et al. Identification and characterization of a novel collagenase in Xenopus laevis: possible roles during frog development. Mol. Biol. Cell 7, 1471–1483 (1996).
    • 32. Barksby HE, Milner JM, Patterson AM et al. Matrix metalloproteinase 10 promotion of collagenolysis via procollagenase activation: implications for cartilage degradation in arthritis. Arth. Rheum. 54, 3244–3253 (2006).
    • 33. Geurts N, Martens E, Van Aelst I, Proost P, Opdenakker G, Van den Steen G. Beta-hematin interaction with the hemopexin domain of gelatinase B/MMP-9 provokes autocatalytic processing of the propeptide, thereby priming activation by MMP-3. Biochemistry 47, 2689–2699 (2008).
    • 34. Shapiro SD, Kobayashi DK, Ley TJ. Cloning and characterization of a unique elastolytic metalloproteinase produced by human alveolar macrophages. J. Biol. Chem. 268, 23824–23829 (1993).
    • 35. Kolb C, Mauch S, Peter HH, Krawinkel U, Sedlacek R. The matrix metalloproteinase RASI-1 is expressed in synovial blood vessels of a rheumatoid arthritis patient. Immunol. Lett. 57, 83–88 (1997).
    • 36. Lu Y, Papagerakis P, Yamakoshi Y, Hu JC, Bartlett JD, Simmer JP. Functions of KLK4 and MMP-20 in dental enamel formation. Biol. Chem. 389, 695–700 (2008).
    • 37. Bar-Or B, Nuttall RK, Duddy M et al. Analyses of all matrix metalloproteinase members in leukocytes emphasize monocytes as major inflammatory mediators in multiple sclerosis. Brain 126, 2738–2749 (2003).
    • 38. Overall CM. Molecular determinants of metalloproteinase substrate specificity: matrix metalloproteinase substrate binding domains, modules, and exosites. Mol. Biotechnol. 22, 51–86 (2002).
    • 39. Rio MC. From a unique cell to metastasis is a long way to go: clues to stromelysin-3 participation. Biochimie 87, 299–306 (2005).
    • 40. Motrescu ER, Blaise S, Etique N et al. Matrix metalloproteinase-11/stromelysin-3 exhibits collagenolytic function against collagen VI under normal and malignant conditions. Oncogene 27, 6347–6355 (2008).
    • 41. Werner SR, Dotzlaf JE, Smith RC. MMP-28 as a regulator of myelination. BMC Neurosci. 9, 83 (2008).
    • 42. Zucker S, Pei D, Cao J, Lopez-Otin C. Membrane type-matrix metalloproteinases (MT-MMP). Curr. Top. Dev. Biol. 54, 1–74 (2003).
    • 43. Sounni NE, Noel A. Membrane type-matrix metalloproteinases and tumor progression. Biochimie 87, 329–342 (2005).
    • 44. Nagase H, Visse R, Murphy G. Structure and function of matrix metalloproteinases and TIMPs. Cardiovasc. Res. 69, 562–573 (2006).
    • 45. Morgunova E, Tuuttila A, Bergmann U et al. Structure of human pro-matrix metalloproteinase-2: activation mechanism revealed. Science 284, 1667–1670 (1999).
    • 46. Tallant C, Marrero A, Gomis-Rüth FX. Matrix metalloproteinases: fold and function of their catalytic domains. Biochim. Biophys. Acta 1803, 20–28 (2010).
    • 47. Iyer S, Visse R, Nagase H, Acharya KR. Crystal structure of an active form of human MMP-1. J. Mol. Biol. 362, 78–88 (2006).
    • 48. Bode W. A helping hand for collagenases: the haemopexin-like domain. Structure 3, 527–530 (1995).
    • 49. Maskos K. Crystal structures of MMPs in complex with physiological and pharmacological inhibitors. Biochimie 87, 249–263 (2005).
    • 50. Schechter I, Berger A. On the size of the active site in proteases. I. Papain. Biochem. Biophys. Res. Commun. 27, 157–162 (1967).
    • 51. Jacobsen JA, Jourden JLM, Miller MT, Cohen SM. To bind zinc or not to bind zinc: an examination of innovative approaches to improved metalloproteinase inhibition. Biochim. Biophys. Acta 1803, 72–94 (2010).
    • 52. Aureli L, Gioia M, Cerbara I et al. Structural bases for substrate and inhibitor recognition by matrix metalloproteinases. Curr. Med. Chem. 15, 2192–2222 (2008).
    • 53. Park HI, Jin Y, Hurst DR et al. The intermediate S1′ pocket of the endometase/matrilysin-2 active site revealed by enzyme inhibition kinetic studies, protein sequence analyses, and homology modelling. J. Biol. Chem. 278, 51646–51653 (2003).
    • 54. Johnson AR, Pavlovsky AG, Ortwine DF et al. Discovery and characterization of a novel inhibitor of matrix metalloprotease-13 that reduces cartilage damage in vivo without joint fibroplasia side effects. J. Biol. Chem. 282, 27781–27791 (2007).
    • 55. Brkic M, Balusu S, Libert C, Vandenbroucke RE. Friends or foes: matrix metalloproteinases and their multifaceted roles in neurodegenerative diseases. Mediators Inflamm. 2015, 620581 (2015).
    • 56. Fabre B, Ramos A, de Pascual-Teresa B. Targeting matrix metalloproteinases: exploring the dynamics of the S1 pocket in the design of selective, small molecule inhibitors. J. Med. Chem. 57, 10205–10219 (2014).
    • 57. Altruda F, Poli V, Restagno G, Argos P, Cortese R, Silengo L. The primary structure of human hemopexin deduced from cDNA sequence: evidence for internal, repeating homology. Nucleic Acids Res. 13, 3841–3859 (1985).
    • 58. Jenne D, Stanley KK. Nucleotide sequence and organisation of the human S-protein gene: repeating peptide motifs in the ‘pexin’ family and a model for their evolution. Biochemistry 26, 6735–6742 (1987).
    • 59. Pelmenschikov V, Siegbahn PE. Catalytic mechanism of matrix metalloproteinases: two-layered ONIOM study. Inorg. Chem. 41, 5659–5666 (2002).
    • 60. Scozzafava A, Supuran CT. Carbonic anhydrase and matrix metalloproteinase inhibitors: sulfonylated amino acid hydroxamates with MMP inhibitory properties act as efficient inhibitors of CA isozymes I, II, and IV, and N-hydroxysulfonamides inhibit both these zinc enzymes. J. Med. Chem. 43, 3677–3687 (1997).
    • 61. Bertini I, Fragai M, Giachetti A et al. Combining in silico tools and NMR data to validate protein-ligand structural models: application to matrix metalloproteinases. J. Med. Chem. 48, 7544–7559 (2005).
    • 62. Aschi M, Besker N, Re N et al. Stereoselectivity by enantiomeric inhibitors of matrix metalloproteinase-8: new insights from molecular dynamics simulations. J. Med. Chem. 50, 211–218 (2007).
    • 63. Amin SA, Adhikari N, Jha T. Is dual inhibition of metalloenzymes HDAC-8 and MMP-2 a potential pharmacological target to combat hematological malignancies? Pharmacol. Res. 122, 8–19 (2017). •• Review article that covers the dual activity of MMP2 and HDAC8 inhibitors.
    • 64. Nuti E, Casalini F, Santamaria S et al. Synthesis and biological evaluation in U87MG glioma cells of (ethynylthiophene)sulfonamido-based hydroxamates as matrix metalloproteinase inhibitors. Eur. J. Med. Chem. 46, 2617–2629 (2011).
    • 65. Fabre B, Filipiak K, Zapico JM et al. Progress towards water-soluble triazole-based selective MMP-2 inhibitors. Org. Biomol. Chem. 11, 6623–6641 (2013).
    • 66. Rossello A, Nuti E, Orlandini E et al. New N-arylsulfonyl-Nalkoxyaminoacetohydroxamic acids as selective inhibitors of gelatinase A (MMP-2). Bioorg. Med. Chem. Lett. 12, 2441–2450 (2004).
    • 67. Nuti E, Cantelmo AR, Gallo C et al. N-O-isopropyl sulfonamido based hydroxamates as matrix metalloproteinase inhibitors: hit selection and in vivo antiangiogenic activity. J. Med. Chem. 58, 7224–7240 (2015).
    • 68. Rossello A, Nuti E, Carelli P et al. N-i-PropoxyN-biphenylsulfonylaminobutylhydroxamic acids as potent and selective inhibitors of MMP-2 and MT1-MMP. Bioorg. Med. Chem. Lett. 15, 1321–1326 (2005).
    • 69. Zhang J, Li X, Jiang Y et al. Design, synthesis and preliminary evaluation of α-sulfonyl γ-(glycinyl-amino)proline peptidomimetics as matrix metalloproteinase inhibitors. Bioorg. Med. Chem. 22, 3055–3064 (2014).
    • 70. Halder AK, Mallick S, Shikha D, Saha A, Saha KD, Jha T. Design of dual MMP-2/HDAC-8 inhibitors by pharmacophore mapping, molecular docking, synthesis and biological activity. RSC Adv. 5, 72373–72386 (2015).
    • 71. Park IH, Kim MM. Spermidine inhibits MMP-2 via modulation of histone acetyltransferase and histone deacetylase in HDFs. Int. J. Biol. Macromol. 51, 1003–1007 (2012).
    • 72. MacPherson LJ, Bayburt EK, Capparelli MP et al. Discovery of CGS 27023A, a non-peptidic, potent, and orally active stromelysin inhibitor that blocks cartilage degradation in rabbits. J. Med. Chem. 40, 2525–2532 (1997).
    • 73. Whittaker M, Floyd CD, Brown P, Gearing AJ. Design and therapeutic application of matrix metalloproteinase inhibitors. Chem. Rev. 99, 2735–2776 (2007).
    • 74. Hu PEJ, Van den Steen QX, Sang GO. Matrix metalloproteinase inhibitors as therapy for inflammatory and vascular diseases.. Nat. Rev. Drug. Discov. 6, 480–498 (2007).
    • 75. Hoekstra R, Eskens FA, Verweij J. Matrix metalloproteinase inhibitors: current developments and future perspectives. Oncologist 6, 415–427 (2001).
    • 76. Skiles JW, Monovich LG, Jeng AY. Matrix metalloproteinase inhibitors for treatment of cancer. Ann. Rep. Med. Chem. 35, 167–176 (2000).
    • 77. Verma RP, Hansch C. Matrix metalloproteinases (MMPs): chemical-biological functions and (Q) SARs. Bioorg. Med. Chem. 15, 2223–2268 (2007).
    • 78. Bourguet E, Sapi J, Emonard H, Hornebeck W. Control of melanoma invasiveness by anticollagenolytic agents: a reappraisal of an old concept. Anticancer Agents Med. Chem. 9, 576–579 (2009).
    • 79. Kaludercic N, Lindsey ML, Tavazzi B, Lazzarino G, Paolocci N. Inhibiting metalloproteases with PD 166793 in heart failure: impact on cardiac remodelling and beyond. Cardiovasc. Ther. 26, 24–37 (2008).
    • 80. Hansch C, Maloney P, Fujita T, Muir R. Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 194, 178–180 (1962).
    • 81. Sendecor GW, Cochran WG. Multiple Regression in Statistical Methods. 6th Edition. Oxford & IBH, New Delhi, India (1967).
    • 82. Yap CW. PaDELe Descriptor: an open source software to calculate molecular descriptors and fingerprints. J. Comput. Chem. 32, 1466–1474 (2011).
    • 83. Mauri A, Consonni V, Pavan M, Todeschini R. Dragon software: an easy approach to molecular descriptor calculations. MATCH Commun. Math. Comput. Chem. 56, 237–248 (2006).
    • 84. Ambure P, Aher RB, Gajewicz A, Puzyn T, Roy K. ‘Nano-BRIDGES’ software: open access tools to perform QSAR and nano-QSAR modeling. Chemometr. Intell. Lab. Syst. 147, 1–13 (2015).
    • 85. Golbraikh A, Tropsha A. Beware of q2! J. Mol. Graph. Model. 20, 269–276 (2002).
    • 86. Todeschini R, Consonni V, Gramatica P. Chemometrics in QSAR. In: Comprehensive Chemometrics (Volume 4). Brown STauler RWalczak R (Eds). Elsevier, Oxford, UK, 129–172 (2009). •• Contains a description of molecular descriptors useful for the QSAR technique.
    • 87. Tute MS. History and objectives of quantitative drug design. In: Comprehensive Medicinal Chemistry (Volume 4). Hansch CSammes PGTaylor JB (.Eds). Pergamon Press, Oxford, UK, 1–31 (1990).
    • 88. Cai J, Li C, Liu Z et al. Predicting DPP-IV inhibitors with machine learning approaches. J. Comput. Aided. Mol. Des. 31, 393–402 (2017).
    • 89. Berger JO. Statistical Decision Theory and Bayesian Analysis. Springer Science & Business Media, NY, USA (2013).
    • 90. BIOVIA Discovery Studio Visualizer (2021). https://www.3dsbiovia.com/products/collaborative-science/biovia-discovery-studio/visualization.html
    • 91. Chen L, Li Y, Zhao Q, Peng H, Hou T. ADME evaluation in drug discovery. 10. Predictions of p-glycoprotein inhibitors using recursive partitioning and naive Bayesian classification techniques. Mol. Pharm. 8, 889–900 (2011).
    • 92. Sastry M, Lowrie JF, Dixon SL, Sherman W. Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments. J. Chem. Inf. Model. 50, 771–784 (2010).
    • 93. Roy K, Kar S, Das RN. Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment. Elsevier, USA (2015). •• An important book that holistically covers the topics of QSAR in pharmaceutical sciences.
    • 94. Galvez-Llompart M, Recio MC, García-Domenech R. Topological virtual screening: a way to find new compounds active in ulcerative colitis by inhibiting NF-kB. Mol. Divers. 15, 917–926 (2011).
    • 95. Kamsri P, Punkvang A, Hannongbua S et al. In silico study directed towards identification of the key structural features of GyrB inhibitors targeting MTB DNA gyrase: HQSAR, CoMSIA and molecular dynamics simulations. SAR QSAR Environ. Res. 30, 775–800 (2019).
    • 96. Debnath AK. Pharmacophore mapping of a series of 2,4-diamino-5-deazapteridine inhibitors of mycobacterium avium complex dihydrofolate reductase. J. Med. Chem. 45, 41–53 (2002).
    • 97. Pourbasheer E, Aalizadeh R, Shokouhi TS, Ganjali MR, Norouzi P, Shadmanesh J. 2D and 3D quantitative structure–activity relationship study of hepatitis C virus NS5B polymerase inhibitors by comparative molecular field analysis and comparative molecular similarity indices analysis methods. J. Chem. Inform. Model. 54, 2902–2914 (2014).
    • 98. Cramer RD, Wendt B. Pushing the boundaries of 3D-QSAR. J. Comput. Aided Drug Des. 21, 23–32 (2007).
    • 99. Cramer RD III, Patterson DE, Bunce JD. Comparative molecular field analysis (CoMFA). Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc. 110, 5959–5967 (1988).
    • 100. Certara. Certara enhances SYBYL-X drug design and discovery software suite. www.certara.com/pressreleases/certara-enhances-sybyl-x-drug-design-and-discovery-software-suite/
    • 101. Tosco P, Balle T. Open3DQSAR: a new open-source software aimed at high-throughput chemometric analysis of molecular interaction fields. J. Mol. Mod. 17(1), 201–208 (2011). • This article marks the inception of Open3DQSAR, an alternate method to CoMFA and CoMSIA techniques.
    • 102. Schrödinger. PyMOL. https://pymol.org/2/
    • 103. Schrödinger. Maestro. www.schrodinger.com/maestro
    • 104. Senese CL, Hopfinger AJ. Receptor-independent 4D-QSAR analysis of a set of norstatine derived inhibitors of HIV-1 protease. J. Chem. Inf. Comput. Sci. 43, 1297–1307 (2003).
    • 105. Kumar D, Gupta SP. A quantitative structure–activity relationship study on some matrix metalloproteinase and collagenase inhibitors. Bioorg. Med. Chem. 11, 421–426 (2002).
    • 106. Gupta SP, Kumar D, Kumaran S. A quantitative structure–activity relationship study of hydroxamate matrix metalloproteinase inhibitors derived from funtionalized 4-aminoprolines. Bioorg. Med. Chem. 11, 1975–1981 (2003).
    • 107. De Melo EB. A QSAR study of matrix metalloproteinases type 2 (MMP-2) inhibitors with cinnamoyl pyrrolidine derivatives. Sci. Pharm. 80, 265–281 (2006).
    • 108. Fernandez M, Caballro J, Tundidor-Camba A. Linear and nonlinear QSAR study of N-hydroxy-2-[(phenylsulfonyl)amino]acetamide derivatives as matrix metalloproteinase inhibitors. Bioorg. Med. Chem. 14, 4137–4150 (2006).
    • 109. Randic M. Characterization of molecular branching. J. Am. Chem. Soc. 97, 6609–6615 (1975).
    • 110. Jamloki A, Karthikeyan C, Moorthy HNNS, Trivedi P. QSAR analysis of some 5-amino-2-mercapto-1,3,4-thiadiazole based inhibitors of matrix metalloproteinases and bacterial collagenase. Bioorg. Med. Chem. Lett. 16, 3847–3854 (2006).
    • 111. Kumaran S, Gupta SP. A quantitative structure–activity relationship study on matrix metalloproteinase inhibitors: piperidine sulfonamide aryl hydroxamic acid analogs. J. Enzyme Inhib. Med. Chem. 22, 23–27 (2007).
    • 112. Zhu H, Fang H, Cheng X et al. 3D-QSAR study of pyrrolidine derivatives as matrix metalloproteinase-2 inhibitors. Med. Chem. Res. 18, 683–701 (2009).
    • 113. Nicolotti O, Catto M, Giangreco I et al. Design, synthesis and biological evaluation of 5-hydroxy, 5-substitutedpyrimidine-2,4,6-triones as potent inhibitors of gelatinases MMP-2 and MMP-9. Eur. J. Med. Chem. 58, 368–376 (2012).
    • 114. GOLD 5.1, The Cambridge Crystallographic Data Centre, UK. https://www.ccdc.cam.ac.uk/solutions/csd-discovery/components/gold/
    • 115. Qiu HY, Wang ZC, Wang PF et al. Design, synthesis, evaluation and 3D-QSAR analysis of benzosulfonamide benzenesulfonates as potent and selective inhibitors of MMP-2. RSC Adv. 4, 39214–39225 (2014).
    • 116. Turra KM, Diogo RP, De Moraes Barros S, Pasqualoto KFM. Predicting novel antitumor agents: 3D-pharmacophore mapping of b-N-biaryl ether sulfonamide-based hydroxamates as potentially MMP-2 inhibitors. Mol. Inf. 33, 573–587 (2014).
    • 117. Abbasi M, Fatemeh R, Elyasi MF, Sadeghi-Aliabadi H, Amanlou M. A study on quantitative structure–activity relationship and molecular docking of metalloproteinase inhibitors based on L-tyrosine scaffold. DARU J. Pharm. Sci. 23, 29–39 (2015).
    • 118. Hyper (2019). http://www.hyper.com/
    • 119. Gaussian 16 (2021). https://gaussian.com/gaussian16/
    • 120. The Scripps Research Institute. AutoDock. http://autodock.scripps.edu/
    • 121. Yan XQ, Wang CZ, Li Z et al. Sulfonamide derivatives containing dihydropyrazole moieties selectively and potently inhibit MMP-2/MMP-9: design, synthesis, inhibitory activity and 3D-QSAR analysis. Bioorg. Med. Chem. Lett. 25, 4664–4671 (2015).
    • 122. Zheng J, Wen R, Guillaume D. Three-dimensional quantitative structure–activity relationship (CoMFA and CoMSIA) studies on galardin derivatives as gelatinase A (matrix metalloproteinase 2) inhibitors. J. Enz. Inhib. Med. Chem. 23, 445–453 (2017).