Discovery of non-peptide GLP-1r natural agonists for enhancing coronary safety in type 2 diabetes patients

References

• Adane, F., Asres, K., Ergete, W., Woldekidan, S., Abebe, A., Lengiso, B., & Seyoum, G. (2021). Research article composition of the essential oil thymus schimperi and evaluation of its acute and subacute toxicity in wistar albino rats: In silico toxicity studies. Evidence-Based Complementary and Alternative Medicine, 2021, 1–17. https://doi.org/10.1155/2021/5521302
   Web of Science ®Google Scholar
• Afza, N., Fatma, S., Ghous, F., Shukla, S., Rai, S., Srivastava, K., & Bishnoi, A. (2023). An efficient multicomponent synthesis, characterization, SAR, In-silico ADME prediction and molecular docking studies of 2-amino-7-(substituted-phenyl)-3-cyano-4-phenyl-4, 5, 6, 7-tetrahydropyrano [2, 3-b] pyrrole-5-carboxylic acid derivatives and their in-vitro antimicrobial activity. Journal of Molecular Structure, 1276, 134721. https://doi.org/10.1016/j.molstruc.2022.134721
   Web of Science ®Google Scholar
• Ahangarzadeh, N., Shakour, N., Rezvanpoor, S., Bakherad, H., Pakdel, M. H., Farhadi, G., & Sepehri, S. (2022). Design, synthesis, and in silico studies of tetrahydropyrimidine analogs as urease enzyme inhibitors. Archiv Der Pharmazie, 355(10), e2200158. https://doi.org/10.1002/ardp.202200158
   PubMed Web of Science ®Google Scholar
• Amadei, A., Linssen, A. B., & Berendsen, H. J. (1993). Essential dynamics of proteins. Proteins, 17(4), 412–425. https://doi.org/10.1002/prot.340170408
   PubMed Web of Science ®Google Scholar
• Amadei, A., Linssen, A., de Groot, B. L., Van Aalten, D., & Berendsen, H. (1996). An efficient method for sampling the essential subspace of proteins. Journal of Biomolecular Structure & Dynamics, 13(4), 615–625. https://doi.org/10.1080/07391102.1996.10508874
   PubMed Web of Science ®Google Scholar
• Association, A.D. 8. (2017). Pharmacologic approaches to glycemic treatment. Diabetes Care, 40, S64–S74.
   PubMed Web of Science ®Google Scholar
• Azzam, K. A. (2023). SwissADME and pkCSM webservers predictors: an integrated online platform for accurate and comprehensive predictions for in silico ADME/T properties of artemisinin and its derivatives. Kompleksnoe Ispol′zovanie Mineral′nogo Syr′â/Complex Use of Mineral Resources/Mineraldik Shikisattardy Keshendi Paidalanu, 325(2), 14–21. https://doi.org/10.31643/2023/6445.13
   Google Scholar
• Banerjee, M., Pal, R., Mukhopadhyay, S., & Nair, K. (2023). GLP-1 Receptor agonists and risk of adverse cerebrovascular outcomes in type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials. The Journal of Clinical Endocrinology & Metabolism, 108(7), 1806–1812. https://doi.org/10.1210/clinem/dgad076
   PubMed Web of Science ®Google Scholar
• Berendsen, H. J., & Hayward, S. (2000). Collective protein dynamics in relation to function. Current Opinion in Structural Biology, 10(2), 165–169. https://doi.org/10.1016/s0959-440x(00)00061-0
   PubMed Web of Science ®Google Scholar
• Bethel, M. A., Patel, R. A., Merrill, P., Lokhnygina, Y., Buse, J. B., Mentz, R. J., Pagidipati, N. J., Chan, J. C., Gustavson, S. M., Iqbal, N., Maggioni, A. P., Öhman, P., Poulter, N. R., Ramachandran, A., Zinman, B., Hernandez, A. F., & Holman, R. R, EXSCEL Study Group. (2018). Cardiovascular outcomes with glucagon-like peptide-1 receptor agonists in patients with type 2 diabetes: A meta-analysis. The Lancet. Diabetes & Endocrinology, 6(2), 105–113. https://doi.org/10.1016/S2213-8587(17)30412-6
   PubMed Web of Science ®Google Scholar
• Boyenle, I. D., Adelusi, T. I., Ogunlana, A. T., Oluwabusola, R. A., Ibrahim, N. O., Tolulope, A., Okikiola, O. S., Adetunji, B. L., Abioye, I. O., & Kehinde Oyedele, A.-Q. (2022). Consensus scoring-based virtual screening and molecular dynamics simulation of some TNF-alpha inhibitors. Informatics in Medicine Unlocked, 28, 100833. https://doi.org/10.1016/j.imu.2021.100833
   Google Scholar
• Bozorgi, A. H. A., & Zarghi, A. (2014). Search for the pharmacophore of histone deacetylase inhibitors using pharmacophore query and docking study. Iranian Journal of Pharmaceutical Research: IJPR, 13(4), 1165–1172.
   PubMed Web of Science ®Google Scholar
• Braga, R. C., Alves, V. M., Silva, M. F. B., Muratov, E., Fourches, D., Lião, L. M., Tropsha, A., & Andrade, C. H. (2015). Pred‐hERG: A novel web‐accessible computational tool for predicting cardiac toxicity. Molecular Informatics, 34(10), 698–701. https://doi.org/10.1002/minf.201500040
   PubMed Web of Science ®Google Scholar
• Brereton, R. G. (2023). Principal components analysis with several objects and variables (Vol. 37, p. e3408). Wiley Online Library.
   Google Scholar
• Burrows, N. R., Li, Y., Gregg, E. W., & Geiss, L. S. (2018). Declining rates of hospitalization for selected cardiovascular disease conditions among adults aged≥ 35 years with diagnosed diabetes, US, 1998–2014. Diabetes Care, 41(4), e59–302. https://doi.org/10.2337/dci17-0062
   PubMed Web of Science ®Google Scholar
• Cao, Y., Yang, R., Wang, W., Jiang, S., Yang, C., Liu, N., Dai, H., Lee, I., Meng, X., & Yuan, Z. (2022). Probing the formation, structure and free energy relationships of M protein dimers of SARS-CoV-2. Computational and Structural Biotechnology Journal, 20, 573–582. https://doi.org/10.1016/j.csbj.2022.01.007
   PubMed Web of Science ®Google Scholar
• Carlson, H. A. (2002). Protein flexibility and drug design: How to hit a moving target. Current Opinion in Chemical Biology, 6(4), 447–452. https://doi.org/10.1016/s1367-5931(02)00341-1
   PubMed Web of Science ®Google Scholar
• Cavender, M. A., Steg, P. G., Smith, S. C., Eagle, K., Ohman, E. M., Goto, S., Kuder, J., Im, K., Wilson, P. W. F., & Bhatt, D. L, REACH Registry Investigators. (2015). Impact of diabetes mellitus on hospitalization for heart failure, cardiovascular events, and death: Outcomes at 4 years from the Reduction of Atherothrombosis for Continued Health (REACH) Registry. Circulation, 132(10), 923–931. https://doi.org/10.1161/CIRCULATIONAHA.114.014796
   PubMed Web of Science ®Google Scholar
• Chatterjee, D., Vhora, N., Goswami, A., Hiray, A., Jain, A., & Kate, A. S. (2022). In-silico and in-vitro hybrid approach to identify glucagon-like peptide-1 receptor agonists from anti-diabetic natural products. Natural Product Research, 37(10), 1651–1655. https://doi.org/10.1080/14786419.2022.2106567
   PubMed Web of Science ®Google Scholar
• Chaudhary, N., & Aparoy, P. (2017). Deciphering the mechanism behind the varied binding activities of COXIBs through molecular dynamic simulations, MM-PBSA binding energy calculations and per-residue energy decomposition studies. Journal of Biomolecular Structure & Dynamics, 35(4), 868–882. https://doi.org/10.1080/07391102.2016.1165736
   PubMed Web of Science ®Google Scholar
• Chess, D. J., & Stanley, W. C. (2008). Role of diet and fuel overabundance in the development and progression of heart failure. Cardiovascular Research, 79(2), 269–278. https://doi.org/10.1093/cvr/cvn074
   PubMed Web of Science ®Google Scholar
• Collaboration, E. R. F. (2010). Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: A collaborative meta-analysis of 102 prospective studies. The Lancet, 375, 2215–2222.
   PubMed Web of Science ®Google Scholar
• Congreve, M., de Graaf, C., Swain, N. A., & Tate, C. G. (2020). Impact of GPCR structures on drug discovery. Cell, 181(1), 81–91. https://doi.org/10.1016/j.cell.2020.03.003
   PubMed Web of Science ®Google Scholar
• Dankwa, B., Broni, E., Enninful, K. S., Kwofie, S. K., & Wilson, M. D. (2022). Consensus docking and MM-PBSA computations identify putative furin protease inhibitors for developing potential therapeutics against COVID-19. Structural Chemistry, 33(6), 2221–2241. https://doi.org/10.1007/s11224-022-02056-1
   PubMed Web of Science ®Google Scholar
• David, C. C., & Jacobs, D. J. (2014). Principal component analysis: A method for determining the essential dynamics of proteins. In Protein dynamics: Methods and protocols (pp. 193–226). Totowa, NJ: Humana Press.
   Google Scholar
• Delaunay, M., & Ha-Duong, T. (2021). Computational tools and strategies to develop peptide-based inhibitors of protein-protein interactions. In Computational peptide science: methods and protocols, pp. 205–230. Springer.
   Google Scholar
• Doner, A. C., Moran, H. A., Webb, A. R., Christianson, M. G., Koritzke, A. L., Dewey, N. S., Hartness, S. W., & Rotavera, B. (2023). Machine learning models for binary molecular classification using VUV absorption spectra. Journal of Quantitative Spectroscopy and Radiative Transfer, 297, 108438. https://doi.org/10.1016/j.jqsrt.2022.108438
   Web of Science ®Google Scholar
• Ejaz, S. A., Aziz, M., Fawzy Ramadan, M., Fayyaz, A., & Bilal, M. S. (2023). Pharmacophore-based virtual screening and in-silico explorations of biomolecules (curcumin derivatives) of Curcuma longa as potential lead inhibitors of ERBB and VEGFR-2 for the treatment of colorectal cancer. Molecules (Basel, Switzerland), 28(10), 4044. https://doi.org/10.3390/molecules28104044
   PubMed Web of Science ®Google Scholar
• Elgaher, W. A., Hayallah, A. M., Salem, O. I., & Abdel Alim, A. A. M. (2009). Synthesis, anti-bronchoconstrictive, and antibacterial activities of some new 8-substituted-1, 3-dimethylxanthine derivatives. Bulletin of Pharmaceutical Sciences. Assiut, 32(1), 153–187. https://doi.org/10.21608/bfsa.2009.63355
   Google Scholar
• Filipe, H. A., & Loura, L. M. (2022). Molecular dynamics simulations: Advances and applications. Molecules (Basel, Switzerland), 27(7), 2105. https://doi.org/10.3390/molecules27072105
   PubMed Web of Science ®Google Scholar
• Frimann, T. M., Ko, S. K., Harris, P., Bukrinski, J. T., & Peters, G. H. (2022). In-silico study of the interactions between acylated glucagon like-peptide-1 analogues and the native receptor. Journal of Biomolecular Structure & Dynamics, 41(11), 5007–5021. https://doi.org/10.1080/07391102.2022.2078409
   PubMed Web of Science ®Google Scholar
• Gerstein, H. C., Colhoun, H. M., Dagenais, G. R., Diaz, R., Lakshmanan, M., Pais, P., Probstfield, J., Riesmeyer, J. S., Riddle, M. C., Rydén, L., Xavier, D., Atisso, C. M., Dyal, L., Hall, S., Rao-Melacini, P., Wong, G., Avezum, A., Basile, J., Chung, N., … Temelkova-Kurktschiev, T. (2019). Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): A double-blind, randomised placebo-controlled trial. The. Lancet (London, England), 394(10193), 121–130. https://doi.org/10.1016/S0140-6736(19)31149-3
   PubMed Web of Science ®Google Scholar
• Gerstein, H. C., Sattar, N., Rosenstock, J., Ramasundarahettige, C., Pratley, R., Lopes, R. D., Lam, C. S. P., Khurmi, N. S., Heenan, L., Del Prato, S., Dyal, L., & Branch, K. (2021). Cardiovascular and renal outcomes with efpeglenatide in type 2 diabetes. The New England Journal of Medicine, 385(10), 896–907. https://doi.org/10.1056/NEJMoa2108269
   PubMed Web of Science ®Google Scholar
• Gm, C., Pushkaran, A., MariaT, A., & Biswas, R. (2023). Identification of a PD1/PD-L1 inhibitor by structure-based pharmacophore modelling, virtual screening, molecular docking and biological evaluation. Molecular Informatics, 2200254.
   Google Scholar
• Gnanaraj, C., Sekar, M., Fuloria, S., Swain, S. S., Gan, S. H., Chidambaram, K., Rani, N. N. I. M., Balan, T., Stephenie, S., Lum, P. T., Jeyabalan, S., Begum, M. Y., Chandramohan, V., Thangavelu, L., Subramaniyan, V., & Fuloria, N. K. (2022). In silico molecular docking analysis of karanjin against Alzheimer’s and Parkinson’s diseases as a potential natural lead molecule for new drug design, development and therapy. Molecules (Basel, Switzerland), 27(9), 2834. https://doi.org/10.3390/molecules27092834
   PubMed Web of Science ®Google Scholar
• Goel, H., Hazel, A., Ustach, V. D., Jo, S., Yu, W., & MacKerell, A. D. (2021). Rapid and accurate estimation of protein–ligand relative binding affinities using site-identification by ligand competitive saturation. Chemical Science, 12(25), 8844–8858. https://doi.org/10.1039/d1sc01781k
   PubMedGoogle Scholar
• Grant, P. J., & Cosentino, F, (2019). The 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: New features and the ‘Ten Commandments’ of the 2019 Guidelines are discussed by Professor Peter J. Grant and Professor Francesco Cosentino, the Task Force Chairmen. Oxford University Press,
   Google Scholar
• Griffith, D. A., Edmonds, D. J., Fortin, J.-P., Kalgutkar, A. S., Kuzmiski, J. B., Loria, P. M., Saxena, A. R., Bagley, S. W., Buckeridge, C., Curto, J. M., Derksen, D. R., Dias, J. M., Griffor, M. C., Han, S., Jackson, V. M., Landis, M. S., Lettiere, D., Limberakis, C., Liu, Y., … Tess, D. A. (2022). A small-molecule oral agonist of the human glucagon-like peptide-1 receptor. Journal of Medicinal Chemistry, 65(12), 8208–8226. https://doi.org/10.1021/acs.jmedchem.1c01856
   PubMed Web of Science ®Google Scholar
• Guo, X., Sang, C., Tang, R., Jiang, C., Li, S., Liu, N., Long, D., Du, X., Dong, J., & Ma, C. (2023). Effects of glucagon‐like peptide‐1 receptor agonists on major coronary events in patients with type 2 diabetes. Diabetes, Obesity & Metabolism, 25 Suppl 1(S1), 53–63. https://doi.org/10.1111/dom.15043
   PubMedGoogle Scholar
• Hernandez, A. F., Green, J. B., Janmohamed, S., D'Agostino, R. B., Granger, C. B., Jones, N. P., Leiter, L. A., Rosenberg, A. E., Sigmon, K. N., Somerville, M. C., Thorpe, K. M., McMurray, J. J. V., & Del Prato, S. (2018). Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (harmony outcomes): A double-blind, randomised placebo-controlled trial. Lancet (London, England), 392(10157), 1519–1529. https://doi.org/10.1016/S0140-6736(18)32261-X
   PubMed Web of Science ®Google Scholar
• Holman, R. R., Bethel, M. A., Mentz, R. J., Thompson, V. P., Lokhnygina, Y., Buse, J. B., Chan, J. C., Choi, J., Gustavson, S. M., Iqbal, N., Maggioni, A. P., Marso, S. P., Öhman, P., Pagidipati, N. J., Poulter, N., Ramachandran, A., Zinman, B., & Hernandez, A. F, EXSCEL Study Group. (2017). Effects of once-weekly exenatide on cardiovascular outcomes in type 2 diabetes. The New England Journal of Medicine, 377(13), 1228–1239. https://doi.org/10.1056/NEJMoa1612917
   PubMed Web of Science ®Google Scholar
• Huang, S.-Y., & Zou, X. (2010). Inclusion of solvation and entropy in the knowledge-based scoring function for protein − ligand interactions. Journal of Chemical Information and Modeling, 50(2), 262–273. https://doi.org/10.1021/ci9002987
   PubMed Web of Science ®Google Scholar
• Husain, M., Birkenfeld, A. L., Donsmark, M., Dungan, K., Eliaschewitz, F. G., Franco, D. R., Jeppesen, O. K., Lingvay, I., Mosenzon, O., Pedersen, S. D., Tack, C. J., Thomsen, M., Vilsbøll, T., Warren, M. L., & Bain, S. C. (2019). Oral semaglutide and cardiovascular outcomes in patients with type 2 diabetes. The New England Journal of Medicine, 381(9), 841–851. https://doi.org/10.1056/NEJMoa1901118
   PubMed Web of Science ®Google Scholar
• Jayaprakashkamath, A., Murali, M., Nair, B., Benny, F., Mani, R. P., Suresh, D., Presanna, A. T., Areekkara, A. N., & Nath, L. R. (2023). Identification of Kaempferol as viral entry inhibitor and DL-Arginine as viral replication inhibitor from selected plants of Indian traditional medicine against COVID-19: An in silico guided in vitro approach. Current Computer-Aided Drug Design, 19(4), 313–323. https://doi.org/10.2174/1573409919666230112123213
   PubMed Web of Science ®Google Scholar
• Junghare, V., Bhattacharya, S., Ansari, K., & Hazra, S. (2023). Markov state models of molecular simulations to study protein folding and dynamics. In Protein folding dynamics and stability: Experimental and computational methods (pp. 147–164). Springer.
   Google Scholar
• Kabsch, W., & Sander, C. (1983). Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features. Biopolymers, 22(12), 2577–2637. https://doi.org/10.1002/bip.360221211
   PubMed Web of Science ®Google Scholar
• Kharatmal, S. B., Singh, J. N., & Sharma, S. S. (2011). Patch clamp technique: Application in drug discovery. 12(4), 62–70.
   Google Scholar
• Kikhney, A. G., & Svergun, D. I. (2015). A practical guide to small angle X-ray scattering (SAXS) of flexible and intrinsically disordered proteins. FEBS Letters, 589(19 Pt A), 2570–2577. https://doi.org/10.1016/j.febslet.2015.08.027
   PubMed Web of Science ®Google Scholar
• Kristensen, S. L., Rørth, R., Jhund, P. S., Docherty, K. F., Sattar, N., Preiss, D., Køber, L., Petrie, M. C., & McMurray, J. J. V. (2019). Cardiovascular, mortality, and kidney outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: A systematic review and meta-analysis of cardiovascular outcome trials. The Lancet. Diabetes & Endocrinology, 7(10), 776–785. https://doi.org/10.1016/S2213-8587(19)30249-9
   PubMed Web of Science ®Google Scholar
• Kumari, R., Kumar, R., Consortium, O. S. D. D., & Lynn, A. (2014). g_mmpbsa- A GROMACS tool for high-throughput MM-PBSA calculations. Journal of Chemical Information and Modeling, 54(7), 1951–1962. https://doi.org/10.1021/ci500020m
   PubMed Web of Science ®Google Scholar
• Lee, M. M., Kristensen, S. L., Gerstein, H. C., McMurray, J. J., & Sattar, N. (2022). Cardiovascular and mortality outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: A meta-analysis with the FREEDOM cardiovascular outcomes trial. Diabetes & Metabolic Syndrome, 16(1), 102382. https://doi.org/10.1016/j.dsx.2021.102382
   PubMed Web of Science ®Google Scholar
• Lokhande, K. B., Shrivastava, A., & Singh, A. (2023). In silico discovery of potent inhibitors against monkeypox’s major structural proteins. Journal of Biomolecular Structure & Dynamics, 41(23), 14259–14274. https://doi.org/10.1080/07391102.2023.2183342
   PubMed Web of Science ®Google Scholar
• Lovshin, J. A., & Drucker, D. J. (2009). Incretin-based therapies for type 2 diabetes mellitus. Nature Reviews. Endocrinology, 5(5), 262–269. https://doi.org/10.1038/nrendo.2009.48
   PubMed Web of Science ®Google Scholar
• Luhadiya, N., Kundalwal, S., & Sahu, S. K. (2022). Adsorption and desorption behavior of titanium-decorated polycrystalline graphene toward hydrogen storage: A molecular dynamics study. Applied Physics A, 128(1), 1–13. https://doi.org/10.1007/s00339-021-05194-1
   Web of Science ®Google Scholar
• Malla, B. A., Ali, A., Maqbool, I., Dar, N. A., Ahmad, S. B., Alsaffar, R. M., & Rehman, M. U. (2023). Insights into molecular docking and dynamics to reveal therapeutic potential of natural compounds against P53 protein. Journal of Biomolecular Structure & Dynamics, 41(18), 8762–8781. https://doi.org/10.1080/07391102.2022.2137241
   PubMed Web of Science ®Google Scholar
• Manna, S., Samal, P., Basak, R., Mitra, A., Roy, A. K., Kundu, R., Ahir, A., Roychowdhury, A., & Hazra, D. (2023). Amentoflavone and methyl hesperidin, novel lead molecules targeting epitranscriptomic modulator in acute myeloid leukemia: In silico drug screening and molecular dynamics simulation approach. Journal of Molecular Modeling, 29(1), 9. https://doi.org/10.1007/s00894-022-05407-1
   Web of Science ®Google Scholar
• Mannucci, E., Dicembrini, I., Nreu, B., & Monami, M. (2020). Glucagon‐like peptide‐1 receptor agonists and cardiovascular outcomes in patients with and without prior cardiovascular events: An updated meta‐analysis and subgroup analysis of randomized controlled trials. Diabetes, Obesity & Metabolism, 22(2), 203–211. https://doi.org/10.1111/dom.13888
   PubMed Web of Science ®Google Scholar
• Marso, S. P., Bain, S. C., Consoli, A., Eliaschewitz, F. G., Jódar, E., Leiter, L. A., Lingvay, I., Rosenstock, J., Seufert, J., Warren, M. L., Woo, V., Hansen, O., Holst, A. G., Pettersson, J., & Vilsbøll, T. (2016). Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. The New England Journal of Medicine, 375(19), 1834–1844. https://doi.org/10.1056/NEJMoa1607141
   PubMed Web of Science ®Google Scholar
• Marso, S. P., Daniels, G. H., Brown-Frandsen, K., Kristensen, P., Mann, J. F. E., Nauck, M. A., Nissen, S. E., Pocock, S., Poulter, N. R., Ravn, L. S., Steinberg, W. M., Stockner, M., Zinman, B., Bergenstal, R. M., & Buse, J. B. (2016). Liraglutide and cardiovascular outcomes in type 2 diabetes. The New England Journal of Medicine, 375(4), 311–322. https://doi.org/10.1056/NEJMoa1603827
   PubMed Web of Science ®Google Scholar
• Meghashree, J. R., Ganiger, V. M., Kumar, J. S. A., Bhuvaneshwari, G., Gopali, J. B., Evoor, S., Cholin, S. S., Gunnaiah, R., Shankarappa, T. H., Krishnamurthy, S. L., & Lokeshkumar, B. M. (2023). Genetic diversity and population structure assessment of Indian bitter gourd accessions using nutritional content and molecular markers. Genetic Resources and Crop Evolution, 1–17. https://doi.org/10.1007/s10722-023-01709-2
   Web of Science ®Google Scholar
• Méndez, M., Matter, H., Defossa, E., Kurz, M., Lebreton, S., Li, Z., Lohmann, M., Löhn, M., Mors, H., Podeschwa, M., Rackelmann, N., Riedel, J., Safar, P., Thorpe, D. S., Schäfer, M., Weitz, D., & Breitschopf, K. (2019). Design, synthesis, and pharmacological evaluation of potent positive allosteric modulators of the glucagon-like peptide-1 receptor (GLP-1R). Journal of Medicinal Chemistry, 63(5), 2292–2307. https://doi.org/10.1021/acs.jmedchem.9b01071
   PubMed Web of Science ®Google Scholar
• Merza, N., Akram, M., Mengal, A., Rashid, A. M., Mahboob, A., Faryad, M., Fatima, Z., Ahmed, M., & Ansari, S. A. (2023). The safety and efficacy of GLP-1 receptor agonists in heart failure patients: A systematic review and meta-analysis. Current Problems in Cardiology, 48(5), 101602. https://doi.org/10.1016/j.cpcardiol.2023.101602
   PubMed Web of Science ®Google Scholar
• Meyer, T., Ferrer-Costa, C., Pérez, A., Rueda, M., Bidon-Chanal, A., Luque, F. J., Laughton, C. A., & Orozco, M. (2006). Essential dynamics: A tool for efficient trajectory compression and management. Journal of Chemical Theory and Computation, 2(2), 251–258. https://doi.org/10.1021/ct050285b
   PubMed Web of Science ®Google Scholar
• Nauck, M. (2016). Incretin therapies: Highlighting common features and differences in the modes of action of glucagon‐like peptide‐1 receptor agonists and dipeptidyl peptidase‐4 inhibitors. Diabetes, Obesity & Metabolism, 18(3), 203–216. https://doi.org/10.1111/dom.12591
   PubMed Web of Science ®Google Scholar
• Nauck, M. A., Meier, J. J., Cavender, M. A., Abd El Aziz, M., & Drucker, D. J. (2017). Cardiovascular actions and clinical outcomes with glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors. Circulation, 136(9), 849–870. https://doi.org/10.1161/CIRCULATIONAHA.117.028136
   PubMed Web of Science ®Google Scholar
• Odoemelam, C. S., Hunter, E., Simms, J., Ahmad, Z., Chang, M.-W., Percival, B., Williams, I. H., Molinari, M., Kamerlin, S. C. L., & Wilson, P. B. (2022). In silico ligand docking approaches to characterise the binding of known allosteric modulators to the glucagon-like peptide 1 receptor and prediction of ADME/Tox properties. Applied Biosciences, 1(2), 143–162. https://doi.org/10.3390/applbiosci1020010
   Google Scholar
• Parikh, P. K., Savjani, J. K., Gajjar, A. K., & Chhabria, M. T. (2023). Bioinformatics and cheminformatics tools in early drug discovery. In Bioinformatics Tools for pharmaceutical drug product development, 147–181. Scrivener Publishing LLC, USA.
   Google Scholar
• Pauling, L., Corey, R. B., & Branson, H. R. (1951). The structure of proteins: Two hydrogen-bonded helical configurations of the polypeptide chain. Proceedings of the National Academy of Sciences of the United States of America, 37(4), 205–211. https://doi.org/10.1073/pnas.37.4.205
   PubMed Web of Science ®Google Scholar
• Perola, E., & Charifson, P. S. (2004). Conformational analysis of drug-like molecules bound to proteins: An extensive study of ligand reorganization upon binding. Journal of Medicinal Chemistry, 47(10), 2499–2510. https://doi.org/10.1021/jm030563w
   PubMed Web of Science ®Google Scholar
• Pfeffer, M. A., Claggett, B., Diaz, R., Dickstein, K., Gerstein, H. C., Køber, L. V., Lawson, F. C., Ping, L., Wei, X., Lewis, E. F., Maggioni, A. P., McMurray, J. J. V., Probstfield, J. L., Riddle, M. C., Solomon, S. D., & Tardif, J.-C. (2015). Lixisenatide in patients with type 2 diabetes and acute coronary syndrome. The New England Journal of Medicine, 373(23), 2247–2257. https://doi.org/10.1056/NEJMoa1509225
   PubMed Web of Science ®Google Scholar
• Piché, M.-E., Tchernof, A., & Després, J.-P. (2020). Obesity phenotypes, diabetes, and cardiovascular diseases. Circulation Research, 126(11), 1477–1500. https://doi.org/10.1161/CIRCRESAHA.120.316101
   PubMed Web of Science ®Google Scholar
• Pignone, M., Alberts, M. J., Colwell, J. A., Cushman, M., Inzucchi, S. E., Mukherjee, D., Rosenson, R. S., Williams, C. D., Wilson, P. W., & Kirkman, M. S. (2010). Aspirin for primary prevention of cardiovascular events in people with diabetes: A position statement of the American Diabetes Association, a scientific statement of the American Heart Association, and an expert consensus document of the American College of Cardiology Foundation. Circulation, 121(24), 2694–2701. https://doi.org/10.1161/CIR.0b013e3181e3b133
   PubMed Web of Science ®Google Scholar
• Powell-Wiley, T. M., Poirier, P., Burke, L. E., Després, J.-P., Gordon-Larsen, P., Lavie, C. J., Lear, S. A., Ndumele, C. E., Neeland, I. J., Sanders, P., & St-Onge, M.-P, American Heart Association Council on Lifestyle and Cardiometabolic Health; Council on Cardiovascular and Stroke Nursing; Council on Clinical Cardiology; Council on Epidemiology and Prevention; and Stroke Council. (2021). Obesity and cardiovascular disease: A scientific statement from the American Heart Association. Circulation, 143(21), e984–e1010. https://doi.org/10.1161/CIR.0000000000000973
   PubMed Web of Science ®Google Scholar
• Ramanathan, A., Savol, A., Agarwal, P., & Chennubhotla, C. S. (2011). Discovering conformational sub-states relevant to protein function. Biophysical Journal, 100(3), 172a. https://doi.org/10.1016/j.bpj.2010.12.1162
   Web of Science ®Google Scholar
• Raut, V. V., Bhandari, S. V., Patil, S. M., & Sarkate, A. P. (2023). A rational approach to anticancer drug design: 2D and 3D-QSAR, molecular docking and prediction of ADME properties using silico studies of thymidine phosphorylase inhibitors. Letters in Drug Design & Discovery, 20(2), 153–166. https://doi.org/10.2174/1570180819666220215115633
   Web of Science ®Google Scholar
• Redij, T., Chaudhari, R., Li, Z., Hua, X., & Li, Z. (2019). Structural modeling and in silico screening of potential small-molecule allosteric agonists of a glucagon-like peptide 1 receptor. ACS Omega, 4(1), 961–970. https://doi.org/10.1021/acsomega.8b03052
   PubMed Web of Science ®Google Scholar
• Ryde, U., & Söderhjelm, P. (2016). Ligand-binding affinity estimates supported by quantum-mechanical methods. Chemical Reviews, 116(9), 5520–5566. https://doi.org/10.1021/acs.chemrev.5b00630
   PubMed Web of Science ®Google Scholar
• Şahin, İ., Çeşme, M., Özgeriş, F. B., & Tümer, F. (2023). Triazole based novel molecules as potential therapeutic agents: Synthesis, characterization, biological evaluation, in-silico ADME profiling and molecular docking studies. Chemico-Biological Interactions, 370, 110312. https://doi.org/10.1016/j.cbi.2022.110312
   PubMed Web of Science ®Google Scholar
• Samuel, V. T., & Shulman, G. I. (2018). Nonalcoholic fatty liver disease as a nexus of metabolic and hepatic diseases. Cell Metabolism, 27(1), 22–41. https://doi.org/10.1016/j.cmet.2017.08.002
   PubMed Web of Science ®Google Scholar
• Shakour, N., Cabezas, R., Santos, J. G., Barreto, G. E., Jamialahmadi, T., & Hadizadeh, F. (2021). Curcumin can bind and interact with CRP: An in silico study. In Pharmacological properties of plant-derived natural products and implications for human health (pp. 91–100). Springer.
   Google Scholar
• Shakour, N., Hadizadeh, F., Kesharwani, P., & Sahebkar, A. (2021). 3D-QSAR studies of 1, 2, 4-oxadiazole derivatives as sortase A inhibitors. BioMed Research International, 2021, 6380336–6380310. https://doi.org/10.1155/2021/6380336
   PubMed Web of Science ®Google Scholar
• Shakour, N., Sahebkar, A., Karimi, G., Paseban, M., Tasbandi, A., Mosaffa, F., Tayarani-Najaran, Z., Ghodsi, R., & Hadizadeh, F. (2021). Design, synthesis and biological evaluation of novel 5-(imidazolyl-methyl) thiazolidinediones as antidiabetic agents. Bioorganic Chemistry, 115, 105162. https://doi.org/10.1016/j.bioorg.2021.105162
   PubMed Web of Science ®Google Scholar
• Shakour, N., Taheri, E., Rajabian, F., Tarighi, S., Soheili, V., & Hadizadeh, F. (2022). Evaluating the Antivirulence Effects of New Thiazolidinedione Compounds Against Pseudomonas aeruginosa PAO1. Microbial Drug Resistance (Larchmont, N.Y.), 28(11), 1003–1018. https://doi.org/10.1089/mdr.2022.0134
   PubMed Web of Science ®Google Scholar
• Sharma, S., & Bhatia, V. (2021). Drug design of GLP-1 receptor agonists: Importance of in silico methods. Current Pharmaceutical Design, 27(8), 1015–1024. https://doi.org/10.2174/1381612826666201118094502
   PubMed Web of Science ®Google Scholar
• Sharma, N., Sharma, M., Faisal, M., Alatar, A. A., Kumar, R., Ahmad, S., & Akhtar, S. (2023). Ligand-based pharmacophore modeling, molecular docking and simulation studies for the exploration of natural potent antiangiogenic inhibitors targeting heat shock protein 90. Letters in Drug Design & Discovery, 20(1), 95–109. https://doi.org/10.2174/1570180819666220921165802
   Web of Science ®Google Scholar
• Shinde, S., Mol, M., Jamdar, V., & Singh, S. (2014). Molecular modeling and molecular dynamics simulations of GPI 14 in Leishmania major: Insight into the catalytic site for active site directed drug design. Journal of Theoretical Biology, 351, 37–46. https://doi.org/10.1016/j.jtbi.2014.02.017
   PubMed Web of Science ®Google Scholar
• Shukla, R., & Singh, T. R. (2021). High-throughput screening of natural compounds and inhibition of a major therapeutic target HsGSK-3β for Alzheimer’s disease using computational approaches. Journal of Genetic Engineering and Biotechnology, 19(1), 17–11. 19, https://doi.org/10.1186/s43141-021-00163-w
   PubMed Web of Science ®Google Scholar
• Singh, V. K., Chaurasia, H., Kumari, P., Som, A., Mishra, R., Srivastava, R., Naaz, F., Singh, A., & Singh, R. K. (2022). Design, synthesis, and molecular dynamics simulation studies of quinoline derivatives as protease inhibitors against SARS-CoV-2. Journal of Biomolecular Structure & Dynamics, 40(21), 10519–10542. https://doi.org/10.1080/07391102.2021.1946716
   PubMed Web of Science ®Google Scholar
• Singh, V. K., Srivastava, R., Gupta, P. S. S., Naaz, F., Chaurasia, H., Mishra, R., Rana, M. K., & Singh, R. K. (2021). Anti-HIV potential of diarylpyrimidine derivatives as non-nucleoside reverse transcriptase inhibitors: Design, synthesis, docking, TOPKAT analysis and molecular dynamics simulations. Journal of Biomolecular Structure & Dynamics, 39(7), 2430–2446. https://doi.org/10.1080/07391102.2020.1748111
   PubMed Web of Science ®Google Scholar
• Stefan, N., Häring, H.-U., & Cusi, K. (2019). Non-alcoholic fatty liver disease: Causes, diagnosis, cardiometabolic consequences, and treatment strategies. The Lancet. Diabetes & Endocrinology, 7(4), 313–324. https://doi.org/10.1016/S2213-8587(18)30154-2
   PubMed Web of Science ®Google Scholar
• Sumaryada, T., Roslia, A. W., Afifah, A., Wahyudi, S. T., & Kartono, A. (2021). In-silico design of novel glucagon-like peptide 1 mutants as candidate for new peptide agonist drugs. Hayati Journal of Biosciences, 28(1), 92. https://doi.org/10.4308/hjb.28.1.92
   Google Scholar
• Tang, H.-C., & Chen, C. Y.-C. (2014). Design of Glucagon-like peptide-1 receptor agonist for diabetes mellitus from traditional Chinese medicine. Evidence-Based Complementary and Alternative Medicine, 2014, 1–17. https://doi.org/10.1155/2014/385120
   Web of Science ®Google Scholar
• Tharwat, A. (2016). Principal component analysis-a tutorial. International Journal of Applied Pattern Recognition, 3(3), 197–240. https://doi.org/10.1504/IJAPR.2016.10000630
   Web of Science ®Google Scholar
• Thorat, B., Purohit, V. P., Yamgar, R., Bhagat, D., Wavhal, S., & Mali, S. N. (2023). Structural insight into 2-aryl-4-quinoline carboxylic acid-based dihydroorotate dehydrogenase (DHODH) and its potential anti-SARS-CoV-2 activity through pharmacophore modeling, multidimensional QSAR, ADME, and docking studies. Physical Chemistry Research, 11, 783–800.
   Google Scholar
• Ussher, J. R., & Drucker, D. J. (2014). Cardiovascular actions of incretin-based therapies. Circulation Research, 114(11), 1788–1803. https://doi.org/10.1161/CIRCRESAHA.114.301958
   PubMed Web of Science ®Google Scholar
• Ussher, J. R., & Drucker, D. J. (2023). Glucagon-like peptide 1 receptor agonists: Cardiovascular benefits and mechanisms of action. Nature Reviews. Cardiology, 20(7), 463–474. https://doi.org/10.1038/s41569-023-00849-3
   PubMed Web of Science ®Google Scholar
• Verma, S., Poulter, N. R., Bhatt, D. L., Bain, S. C., Buse, J. B., Leiter, L. A., Nauck, M. A., Pratley, R. E., Zinman, B., Ørsted, D. D., Monk Fries, T., Rasmussen, S., & Marso, S. P. (2018). Effects of liraglutide on cardiovascular outcomes in patients with type 2 diabetes mellitus with or without history of myocardial infarction or stroke: Post hoc analysis from the leader trial. Circulation, 138(25), 2884–2894. https://doi.org/10.1161/CIRCULATIONAHA.118.034516
   PubMed Web of Science ®Google Scholar
• Weiss, D. R., Bortolato, A., Tehan, B., & Mason, J. S. (2016). GPCR-bench: A benchmarking set and practitioners’ guide for G protein-coupled receptor docking. Journal of Chemical Information and Modeling, 56(4), 642–651. https://doi.org/10.1021/acs.jcim.5b00660
   PubMed Web of Science ®Google Scholar
• Yahyavi, M., Falsafi-Zadeh, S., Karimi, Z., Kalatarian, G., & Galehdari, H. (2014). VMD-SS: A graphical user interface plug-in to calculate the protein secondary structure in VMD program. Bioinformation, 10(8), 548–550. https://doi.org/10.6026/97320630010548
   PubMedGoogle Scholar
• Yamamoto, Y., & Shigeta, Y. (2023). Theoretical study on the regulating mechanism of the transition between the open-closed state of hCtBP2: A combined molecular dynamics and quantum mechanical interaction analysis. Chemistry Letters, 52(2), 120–123. https://doi.org/10.1246/cl.220503
   Google Scholar
• Yang, Y., Lee, C., Reddy, R. R., Huang, D. J., Zhong, W., Nguyen-Tran, V. T. B., Shen, W., & Lin, Q. (2022). Design of potent and proteolytically stable biaryl-stapled GLP-1R/GIPR peptide dual agonists. ACS Chemical Biology, 17(5), 1249–1258. https://doi.org/10.1021/acschembio.2c00175
   PubMed Web of Science ®Google Scholar
• Zvelindovsky, A. V. (2007). Nanostructured soft matter: Experiment, theory, simulation and perspectives. Springer Science & Business Media.
   Google Scholar