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Tamang JSD, Banerjee S, Baidya SK, Ghosh B, Adhikari N, Jha T. Employing comparative QSAR techniques for the recognition of dibenzofuran and dibenzothiophene derivatives toward MMP-12 inhibition. J Biomol Struct Dyn 2024; 42:7304-7320. [PMID: 37498149 DOI: 10.1080/07391102.2023.2239923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/17/2023] [Indexed: 07/28/2023]
Abstract
Among various matrix metalloproteinases (MMPs), MMP-12 is one of the potential targets for cancer and other diseases. However, none of the MMP-12 inhibitors has passed the clinical trials to date. Therefore, designing potential MMP-12 inhibitors as new drug molecules can provide effective therapeutic strategies for several diseases. In this study, a series of dibenzofuran and dibenzothiophene derivatives were subjected to different 2D and 3D-QSAR techniques to point out the crucial structural contributions highly influential toward the MMP-12 inhibitory activity. These techniques identified some structural attributes of these compounds that are responsible for influencing their MMP-12 inhibition. The carboxylic group may enhance proper binding with catalytic Zn2+ ion at the MMP-12 active site. Again, the i-propyl sulfonamido carboxylic acid function contributed positively toward MMP-12 inhibition. Moreover, the dibenzofuran moiety conferred stable binding at the S1' pocket for higher MMP-12 inhibition. The steric and hydrophobic groups were found favourable near the furan ring substituted at the dibenzofuran moiety. Besides these ligand-based approaches, molecular docking and molecular dynamic (MD) simulation studies not only elucidated the importance of several aspects of these MMP-12 inhibitors while disclosing the significance of the finding of these QSAR studies and their influences toward MMP-12 inhibition. The MD simulation study also revealed stable and compact binding between such compounds at the MMP-12 active site. Therefore, the findings of these validated ligand-based and structure-based molecular modeling studies can aid the development of selective and potent lead molecules that can be used for the treatment of MMP-12-associated diseases.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Jigme Sangay Dorjay Tamang
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - Suvankar Banerjee
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - Sandip Kumar Baidya
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - Balaram Ghosh
- Epigenetic Research Laboratory, Department of Pharmacy, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Shamirpet, Hyderabad, India
| | - Nilanjan Adhikari
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - Tarun Jha
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
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Amor M, Bianco V, Buerger M, Lechleitner M, Vujić N, Dobrijević A, Akhmetshina A, Pirchheim A, Schwarz B, Pessentheiner AR, Baumgartner F, Rampitsch K, Schauer S, Klobučar I, Degoricija V, Pregartner G, Kummer D, Svecla M, Sommer G, Kolb D, Holzapfel GA, Hoefler G, Frank S, Norata GD, Kratky D. Genetic deletion of MMP12 ameliorates cardiometabolic disease by improving insulin sensitivity, systemic inflammation, and atherosclerotic features in mice. Cardiovasc Diabetol 2023; 22:327. [PMID: 38017481 PMCID: PMC10685620 DOI: 10.1186/s12933-023-02064-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 11/13/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Matrix metalloproteinase 12 (MMP12) is a macrophage-secreted protein that is massively upregulated as a pro-inflammatory factor in metabolic and vascular tissues of mice and humans suffering from cardiometabolic diseases (CMDs). However, the molecular mechanisms explaining the contributions of MMP12 to CMDs are still unclear. METHODS We investigated the impact of MMP12 deficiency on CMDs in a mouse model that mimics human disease by simultaneously developing adipose tissue inflammation, insulin resistance, and atherosclerosis. To this end, we generated and characterized low-density lipoprotein receptor (Ldlr)/Mmp12-double knockout (DKO) mice fed a high-fat sucrose- and cholesterol-enriched diet for 16-20 weeks. RESULTS DKO mice showed lower cholesterol and plasma glucose concentrations and improved insulin sensitivity compared with LdlrKO mice. Untargeted proteomic analyses of epididymal white adipose tissue revealed that inflammation- and fibrosis-related pathways were downregulated in DKO mice. In addition, genetic deletion of MMP12 led to alterations in immune cell composition and a reduction in plasma monocyte chemoattractant protein-1 in peripheral blood which indicated decreased low-grade systemic inflammation. Aortic en face analyses and staining of aortic valve sections demonstrated reduced atherosclerotic plaque size and collagen content, which was paralleled by an improved relaxation pattern and endothelial function of the aortic rings and more elastic aortic sections in DKO compared to LdlrKO mice. Shotgun proteomics revealed upregulation of anti-inflammatory and atheroprotective markers in the aortas of DKO mice, further supporting our data. In humans, MMP12 serum concentrations were only weakly associated with clinical and laboratory indicators of CMDs. CONCLUSION We conclude that the genetic deletion of MMP12 ameliorates obesity-induced low-grade inflammation, white adipose tissue dysfunction, biomechanical properties of the aorta, and the development of atherosclerosis. Therefore, therapeutic strategies targeting MMP12 may represent a promising approach to combat CMDs.
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Affiliation(s)
- Melina Amor
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Valentina Bianco
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Martin Buerger
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Margarete Lechleitner
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Nemanja Vujić
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Anja Dobrijević
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
- Institute for Vascular Biology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Alena Akhmetshina
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Anita Pirchheim
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Birgit Schwarz
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
| | - Ariane R Pessentheiner
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
- Institute for Molecular Biosciences, University of Graz, Graz, Austria
| | | | | | - Silvia Schauer
- Diagnostics and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Iva Klobučar
- Sisters of Charity, University Hospital Centre, Zagreb, Croatia
| | - Vesna Degoricija
- University of Zagreb School of Medicine, Zagreb, Croatia
- Department of Medicine, Sisters of Charity, University Hospital Centre, Zagreb, Croatia
| | - Gudrun Pregartner
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Daniel Kummer
- Gottfried Schatz Research Center, Cell Biology, Histology and Embryology, Medical University of Graz, Graz, Austria
| | - Monika Svecla
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Gerhard Sommer
- Institute of Biomechanics, Graz University of Technology, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Dagmar Kolb
- Gottfried Schatz Research Center, Cell Biology, Histology and Embryology, Medical University of Graz, Graz, Austria
- Core Facility Ultrastructural Analysis, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Gerhard A Holzapfel
- Institute of Biomechanics, Graz University of Technology, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Department of Structural Engineering, Norwegian University of Science and Technology, Trondheim, Norway
| | - Gerald Hoefler
- Diagnostics and Research Institute of Pathology, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Saša Frank
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria
- BioTechMed-Graz, Graz, Austria
| | - Giuseppe Danilo Norata
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Dagmar Kratky
- Gottfried Schatz Research Center, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstrasse 6/4, Graz, 8010, Austria.
- BioTechMed-Graz, Graz, Austria.
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Baidya SK, Banerjee S, Adhikari N, Jha T. Selective Inhibitors of Medium-Size S1' Pocket Matrix Metalloproteinases: A Stepping Stone of Future Drug Discovery. J Med Chem 2022; 65:10709-10754. [PMID: 35969157 DOI: 10.1021/acs.jmedchem.1c01855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Among various matrix metalloproteinases (MMPs), MMPs having medium-size S1' pockets are established as promising biomolecular targets for executing crucial roles in cancer, cardiovascular diseases, and neurodegenerative diseases. However, no such MMP inhibitors (MMPIs) are available to date as drug candidates despite a lot of continuous research work for more than three decades. Due to a high degree of structural resemblance among these MMPs, designing selective MMPIs is quite challenging. However, the variability and uniqueness of the S1' pockets of these MMPs make them promising targets for designing selective MMPIs. In this perspective, the overall structural aspects of medium-size S1' pocket MMPs including the unique binding patterns of enzyme-inhibitor interactions have been discussed in detail to acquire knowledge regarding selective inhibitor designing. This overall knowledge will surely be a curtain raiser for the designing of selective MMPIs as drug candidates in the future.
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Affiliation(s)
- Sandip Kumar Baidya
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India
| | - Suvankar Banerjee
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India
| | - Nilanjan Adhikari
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India
| | - Tarun Jha
- Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India
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Yu Y, Wang R, Teo RD. Machine Learning Approaches for Metalloproteins. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27041277. [PMID: 35209064 PMCID: PMC8878495 DOI: 10.3390/molecules27041277] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 02/10/2022] [Accepted: 02/11/2022] [Indexed: 01/10/2023]
Abstract
Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.
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Affiliation(s)
- Yue Yu
- Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, Jiangsu 215316, China;
- Department of Physics, Duke University, Durham, NC 27708, USA
| | - Ruobing Wang
- Department of Chemistry, Duke University, Durham, NC 27708, USA;
| | - Ruijie D. Teo
- Department of Chemistry, Duke University, Durham, NC 27708, USA;
- UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Correspondence:
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Pande A, Manchanda M, Bhat HR, Bairy PS, Kumar N, Gahtori P. Molecular insights into a mechanism of resveratrol action using hybrid computational docking/CoMFA and machine learning approach. J Biomol Struct Dyn 2021; 40:8286-8300. [PMID: 33829956 DOI: 10.1080/07391102.2021.1910572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
A phytoalexin, Resveratrol remains a legendary anticancer drug candidate in the archives of scientific literature. Although earlier wet-lab experiments rendering its multiple biological targets, for example, epidermal growth factors, Pro-apoptotic protein p53, sirtuins, and first apoptosis signal (Fas) receptor, Mouse double minute 2 (MDM2) ubiquitin-protein ligase, Estrogen receptor, Quinone reductase, etc. However, notwithstanding some notable successes, identification of an appropriate Resveratrol target(s) has remained a major challenge using physical methods, and hereby limiting its translation into an effective therapeutic(s). Thus, computational insights are much needed to establish proof-of-concept towards potential Resveratrol target(s) with minimum error rate, narrow down the search space, and to assess a more accurate Resveratrol signaling pathway/mechanism at the starting point. Herein, a brute-force technique combining computational receptor-, ligand-based virtual screening, and classification-based machine learning, reveals the precise mechanism of Resveratrol action. Overall, MDM2 ubiquitin-protein ligase (4OGN.pdb) and co-crystallized quinone reductases 2 (4QOH.pdb) were found two suitable drug targets in the case of Resveratrol derivatives. Indeed, carotenoid cleaving oxygenase together with later twos gave gigantic momentum in guiding the rational drug design of Resveratrol derivatives. These molecular modeling insights would be useful for Resveratrol lead optimization into a more precise science.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Akshara Pande
- Department of Computer Science, Graphic Era Hill University, Dehradun, Uttarakhand, India
| | - Mahesh Manchanda
- Department of Computer Science & Engineering, Graphic Era Hill University, Dehradun, Uttarakhand, India
| | - Hans Raj Bhat
- Department of Pharmaceutical Sciences, Dibrugarh University, Dibrugarh, Dehradun, Uttarakhand, India
| | | | - Navin Kumar
- Department of Biotechnology, Graphic Era University, Dehradun, Uttarakhand, India
| | - Prashant Gahtori
- School of Pharmacy, Graphic Era Hill University, Dehradun, Uttarakhand, India
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