Insights from in silico exploration of major curcumin analogs targeting human dipeptidyl peptidase IV

References

• Abu Khalaf, R., Awad, M., Al-Essa, L., Mefleh, S., Sabbah, D., Al-Shalabi, E., & Shabeeb, I. (2021). Discovery, synthesis and in combo studies of Schiff’s bases as promising dipeptidyl peptidase-IV inhibitors. Molecular Diversity, 26(2), 1213–1225. https://doi.org/10.1007/s11030-021-10253-z
   PubMed Web of Science ®Google Scholar
• Adel, A., Elnaggar, M. S., Albohy, A., Elrashedy, A. A., Mostafa, A., Kutkat, O., Abdelmohsen, U. R., Al-Sayed, E., & Rabeh, M. A. (2022). Evaluation of antiviral activity of Carica papaya leaves against SARS-CoV-2 assisted by metabolomic profiling. RSC Advances, 12(51), 32844–32852. https://doi.org/10.1039/d2ra04600h
   PubMed Web of Science ®Google Scholar
• Akbik, D., Ghadiri, M., Chrzanowski, W., & Rohanizadeh, R. (2014). Curcumin as a wound healing agent. Life Sciences, 116(1), 1–7. https://doi.org/10.1016/j.lfs.2014.08.016
   PubMed Web of Science ®Google Scholar
• Antony, P., Baby, B., Aleissaee, H. M., & Vijayan, R. (2022). A molecular modeling investigation of the therapeutic potential of marine compounds as DPP-4 inhibitors. Marine Drugs, 20(12), 777. https://doi.org/10.3390/md20120777
   PubMed Web of Science ®Google Scholar
• Atiya, A., Das Gupta, D., Alsayari, A., Alrouji, M., Alotaibi, A., Sharaf, S. E., Abdulmonem, W. A., Alorfi, N. M., Abdullah, K. M., & Shamsi, A. (2023). Linagliptin and empagliflozin inhibit microtubule affinity regulatory kinase 4: Repurposing anti-diabetic drugs in neurodegenerative disorders using in silico and in vitro approaches. ACS Omega, 8(7), 6423–6430. https://doi.org/10.1021/acsomega.2c06634
   PubMed Web of Science ®Google Scholar
• Benet, L. Z., Hosey, C. M., Ursu, O., & Oprea, T. I. (2016). BDDCS, the Rule of 5 and drugability. Advanced Drug Delivery Reviews, 101, 89–98. https://doi.org/10.1016/j.addr.2016.05.007
   PubMed Web of Science ®Google Scholar
• Berendsen, H. J., Postma, J. V., Van Gunsteren, W. F., DiNola, A. R. H. J., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8), 3684–3690. https://doi.org/10.1063/1.448118
   Web of Science ®Google Scholar
• Bharadwaj, S., Dubey, A., Kamboj, N. K., Sahoo, A. K., Kang, S. G., & Yadava, U. (2021). Drug repurposing for ligand-induced rearrangement of Sirt2 active site-based inhibitors via molecular modeling and quantum mechanics calculations. Scientific Reports, 11(1), 10169. https://doi.org/10.1038/s41598-021-89627-0
   PubMed Web of Science ®Google Scholar
• Bharadwaj, S., Dubey, A., Yadava, U., Mishra, S. K., Kang, S. G., & Dwivedi, V. D. (2021). Exploration of natural compounds with anti-SARS-CoV-2 activity via inhibition of SARS-CoV-2 Mpro. Briefings in Bioinformatics, 22(2), 1361–1377. https://doi.org/10.1093/bib/bbaa382
   PubMed Web of Science ®Google Scholar
• Bibi, S., Khan, M. S., El-Kafrawy, S. A., Alandijany, T. A., El-Daly, M. M., Yousafi, Q., Fatima, D., Faizo, A. A., Bajrai, L. H., & Azhar, E. I. (2022). Virtual screening and molecular dynamics simulation analysis of Forsythoside A as a plant-derived inhibitor of SARS-CoV-2 3CLpro. Saudi Pharmaceutical Journal: SPJ: The Official Publication of the Saudi Pharmaceutical Society, 30(7), 979–1002. https://doi.org/10.1016/j.jsps.2022.05.003
   PubMed Web of Science ®Google Scholar
• Biovia, D. S. (2017).). Discovery studio visualizer. 936.
   Google Scholar
• Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7(1), 42717. https://doi.org/10.1038/srep42717
   PubMed Web of Science ®Google Scholar
• Dalal, M., Dubey, A., Tufail, A., Antil, N., Sehrawat, N., & Garg, S. (2023). Organyltellurium (IV) complexes incorporating Schiff base ligand derived from 2-hydroxy-1-naphthaldehyde: Preparation, spectroscopic investigations, antimicrobial, antioxidant activities, DFT, MESP, NBO, molecular docking and ADMET evaluation. Journal of Molecular Structure. 1287, 135590. https://doi.org/10.1016/j.molstruc.2023.135590
   Web of Science ®Google Scholar
• Dawar, N., Devi, J., Kumar, B., & Dubey, A. (2023). Synthesis, characterization, pharmacological screening, molecular docking, DFT, MESP, ADMET studies of transition metal (II) chelates of bidentate schiff base ligand. Inorganic Chemistry Communications, 151, 110567. https://doi.org/10.1016/j.inoche.2023.110567
   Web of Science ®Google Scholar
• Deswal, Y., Asija, S., Dubey, A., Deswal, L., Kumar, D., Jindal, D. K., & Devi, J. (2022). Cobalt (II), nickel (II), copper (II) and zinc (II) complexes of thiadiazole based Schiff base ligands: Synthesis, structural characterization, DFT, antidiabetic and molecular docking studies. Journal of Molecular Structure. 1253, 132266. https://doi.org/10.1016/j.molstruc.2021.132266
   Web of Science ®Google Scholar
• Dong, H.-H., Wang, Y.-H., Peng, X.-M., Zhou, H.-Y., Zhao, F., Jiang, Y.-Y., Zhang, D.-Z., & Jin, Y.-S. (2021). Synergistic antifungal effects of curcumin derivatives as fungal biofilm inhibitors with fluconazole. Chemical Biology & Drug Design, 97(5), 1079–1088. https://doi.org/10.1111/cbdd.13827
   PubMed Web of Science ®Google Scholar
• Gonnet, P. (2007). P-SHAKE: A quadratically convergent SHAKE in O (n2). Journal of Computational Physics, 220(2), 740–750. https://doi.org/10.1016/j.jcp.2006.05.032
   Web of Science ®Google Scholar
• Huang, Y., & Ferguson, N. (2021). Principal component analysis of the cross-axis apparent mass nonlinearity during whole-body vibration. Mechanical Systems and Signal Processing, 146, 107008. https://doi.org/10.1016/j.ymssp.2020.107008
   Web of Science ®Google Scholar
• Huang, P. K., Lin, S. R., Chang, C. H., Tsai, M. J., Lee, D. N., & Weng, C. F. (2019). Natural phenolic compounds potentiate hypoglycemia via inhibition of Dipeptidyl peptidase IV. Scientific Reports, 9(1), 15585. https://doi.org/10.1038/s41598-019-52088-7
   PubMedGoogle Scholar
• Ilyas, U., Nazir, B., Altaf, R., Muhammad, S. A., Zafar, H., Paiva-Santos, A. C., Abbas, M., & Duan, Y. (2022). Investigation of anti-diabetic potential and molecular simulation studies of dihydropyrimidinone derivatives. Frontiers in Endocrinology, 13, 1022623. https://doi.org/10.3389/fendo.2022.1022623
   PubMed Web of Science ®Google Scholar
• Issahaku, A. R., Salifu, E. Y., Agoni, C., Alahmdi, M. I., Abo‐Dya, N. E., Soliman, M. E., … Podila, N. (2023). Discovery of potential KRAS‐SOS1 inhibitors from South African natural compounds: An in silico approach. ChemistrySelect. 8(24), e202300277.
   Web of Science ®Google Scholar
• Jahanbakhshi, F., Maleki Dana, P., Badehnoosh, B., Yousefi, B., Mansournia, M. A., Jahanshahi, M., Asemi, Z., & Halajzadeh, J. (2021). Curcumin anti‐tumor effects on endometrial cancer with focus on its molecular targets. Cancer Cell International, 21(1), 120. https://doi.org/10.1186/s12935-021-01832-z
   PubMed Web of Science ®Google Scholar
• Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., & Klein, M. L. (1983). Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79(2), 926–935. https://doi.org/10.1063/1.445869
   Web of Science ®Google Scholar
• Kęska, P., Stadnik, J., Bąk, O., & Borowski, P. (2019). Meat proteins as dipeptidyl peptidase iv inhibitors and glucose uptake stimulating peptides for the management of a type 2 diabetes mellitus in silico study. Nutrients, 11(10), 2537. https://doi.org/10.3390/nu11102537
   PubMed Web of Science ®Google Scholar
• Lagunin, A., Zakharov, A., Filimonov, D., & Poroikov, V. (2011). QSAR modelling of rat acute toxicity on the basis of PASS prediction. Molecular Informatics, 30(2-3), 241–250. https://doi.org/10.1002/minf.201000151
   PubMed Web of Science ®Google Scholar
• Larini, L., Mannella, R., & Leporini, D. (2007). Langevin stabilization of molecular-dynamics simulations of polymers by means of quasisymplectic algorithms. The Journal of Chemical Physics, 126(10), 104101. https://doi.org/10.1063/1.2464095
   PubMed Web of Science ®Google Scholar
• Liu, Y., Grimm, M., Dai, W. T., Hou, M. C., Xiao, Z. X., & Cao, Y. (2020). CB-Dock: A web server for cavity detection-guided protein–ligand blind docking. Acta Pharmacologica Sinica, 41(1), 138–144. https://doi.org/10.1038/s41401-019-0228-6
   PubMed Web of Science ®Google Scholar
• Maier, J. A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K. E., & Simmerling, C. (2015). ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. Journal of Chemical Theory and Computation, 11(8), 3696–3713. https://doi.org/10.1021/acs.jctc.5b00255
   PubMed Web of Science ®Google Scholar
• Majumdar, D., Dubey, A., Tufail, A., Sutradhar, D., & Roy, S. (2023). Synthesis, spectroscopic investigation, molecular docking, ADME/T toxicity predictions, and DFT study of two trendy ortho vanillin-based scaffolds. Heliyon, 9(6), e16057. https://doi.org/10.1016/j.heliyon.2023.e16057
   PubMed Web of Science ®Google Scholar
• Majumdar, D., Philip, J. E., Dubey, A., Tufail, A., & Roy, S. (2023). Synthesis, spectroscopic findings, SEM/EDX, DFT, and single-crystal structure of Hg/Pb/Cu–SCN complexes: In silico ADME/T profiling and promising antibacterial activities. Heliyon, 9(5), e16103. https://doi.org/10.1016/j.heliyon.2023.e16103
   PubMed Web of Science ®Google Scholar
• Manjunatha, J. R., Bettadaiah, B. K., Negi, P. S., & Srinivas, P. (2013). Synthesis of amino acid conjugates of tetrahydrocurcumin and evaluation of their antibacterial and anti-mutagenic properties. Food Chemistry, 139(1–4), 332–338. https://doi.org/10.1016/j.foodchem.2013.01.081
   PubMed Web of Science ®Google Scholar
• Marton, L. T., Pescinini-E-Salzedas, L. M., Camargo, M. E. C., Barbalho, S. M., Haber, J. F. D. S., Sinatora, R. V., Detregiachi, C. R. P., Girio, R. J. S., Buchaim, D. V., & Cincotto Dos Santos Bueno, P. (2021). The effects of curcumin on diabetes mellitus: A systematic review. Frontiers in Endocrinology, 12, 669448. https://doi.org/10.3389/fendo.2021.669448
   PubMedGoogle Scholar
• Mathew, D., & Hsu, W. L. (2018). Antiviral potential of curcumin. Journal of Functional Foods. 40, 692–699. https://doi.org/10.1016/j.jff.2017.12.017
   Web of Science ®Google Scholar
• Maulana, A. F., Sriwidodo, S., Rukayadi, Y., & Maksum, I. P. (2022). In silico study of mangostin compounds and its derivatives as inhibitors of α-glucosidase enzymes for anti-diabetic studies. Biology, 11(12), 1837. https://doi.org/10.3390/biology11121837
   PubMedGoogle Scholar
• Mehrabi, M., Esmaeili, S., Ezati, M., Abassi, M., Rasouli, H., Nazari, D., Adibi, H., & Khodarahmi, R. (2021). Antioxidant and glycohydrolase inhibitory behavior of curcumin-based compounds: Synthesis and evaluation of anti-diabetic properties in vitro. Bioorganic Chemistry, 110, 104720. https://doi.org/10.1016/j.bioorg.2021.104720
   PubMed Web of Science ®Google Scholar
• Menon, V. P., & Sudheer, A. R. (2007). Antioxidant and anti-inflammatory properties of curcumin. The Molecular Targets and Therapeutic Uses of Curcumin in Health and Disease, 595, 105–125.
   Google Scholar
• Michaud‐Agrawal, N., Denning, E. J., Woolf, T. B., & Beckstein, O. (2011). MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. Journal of Computational Chemistry, 32(10), 2319–2327. https://doi.org/10.1002/jcc.21787
   PubMed Web of Science ®Google Scholar
• Moretti, S. (2011). In silico experiments in scientific papers on molecular biology. Science & Technology Studies, 24(2), 23–42. https://doi.org/10.23987/sts.55262
   Google Scholar
• Musoev, A., Numonov, S., You, Z., & Gao, H. (2019). Discovery of novel DPP-IV inhibitors as potential candidates for the treatment of type 2 diabetes mellitus predicted by 3D QSAR pharmacophore models, molecular docking and de novo evolution. Molecules (Basel, Switzerland), 24(16), 2870. https://doi.org/10.3390/molecules24162870
   PubMed Web of Science ®Google Scholar
• Neyestani, Z., Ebrahimi, S. A., Ghazaghi, A., Jalili, A., Sahebkar, A., & Rahimi, H. R. (2019). Review of anti-bacterial activities of curcumin against Pseudomonas aeruginosa. Crit. Rev. Eukaryot. Gene Exp, 29(5), 377–385.
   PubMed Web of Science ®Google Scholar
• Nikitin, S. (2014). Leap gradient algorithm. arXiv preprint arXiv:1405.5548
   Google Scholar
• Okechukwu, P., Sharma, M., Tan, W. H., Chan, H. K., Chirara, K., Gaurav, A., & Al-Nema, M. (2020). In-vitro anti-diabetic activity and in-silico studies of binding energies of palmatine with alpha-amylase, alpha-glucosidase and DPP-IV enzymes. Pharmacia, 67(4), 363–371. https://doi.org/10.3897/pharmacia.67.e58392
   Web of Science ®Google Scholar
• Oyebode, O. A., Erukainure, O. L., Chukwuma, C. I., Ibeji, C. U., Koorbanally, N. A., & Islam, S. (2018). Boerhaavia diffusa inhibits key enzymes linked to type 2 diabetes in vitro and in silico; and modulates abdominal glucose absorption and muscle glucose uptake ex vivo. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 106, 1116–1125. https://doi.org/10.1016/j.biopha.2018.07.053
   PubMed Web of Science ®Google Scholar
• Padhi, A. K., Seal, A., Khan, J. M., Ahamed, M., & Tripathi, T. (2021). Unraveling the mechanism of arbidol binding and inhibition of SARS-CoV-2: Insights from atomistic simulations. European Journal of Pharmacology, 894, 173836. https://doi.org/10.1016/j.ejphar.2020.173836
   PubMed Web of Science ®Google Scholar
• Paul, R. K., Nath, V., & Kumar, V. (2021). Structure based virtual screening of natural compounds and molecular dynamics simulation: Butirosin as Dipeptidyl peptidase (DPP-IV) inhibitor. Biocatalysis and Agricultural Biotechnology, 35, 102042. https://doi.org/10.1016/j.bcab.2021.102042
   Web of Science ®Google Scholar
• Petersen, H. G. (1995). Accuracy and efficiency of the particle mesh Ewald method. The Journal of Chemical Physics, 103(9), 3668–3679. https://doi.org/10.1063/1.470043
   Web of Science ®Google Scholar
• Ponnulakshmi, R., Shyamaladevi, B., Vijayalakshmi, P., & Selvaraj, J. (2019). In silico and in vivo analysis to identify the antidiabetic activity of beta sitosterol in adipose tissue of high fat diet and sucrose induced type-2 diabetic experimental rats. Toxicology Mechanisms and Methods, 29(4), 276–290. https://doi.org/10.1080/15376516.2018.1545815
   PubMed Web of Science ®Google Scholar
• Roe, D. R., & Cheatham, T. E. III, (2013). PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. Journal of Chemical Theory and Computation, 9(7), 3084–3095. https://doi.org/10.1021/ct400341p
   PubMed Web of Science ®Google Scholar
• Roney, M., Huq, A. K. M. M., Issahaku, A. R., Soliman, M. E. S., Hossain, M. S., Mustafa, A. H., Islam, M. A., Dubey, A., Tufail, A., Mohd Aluwi, M. F. F., & Tajuddin, S. N. (2023). Pharmacophore-based virtual screening and in-silico study of natural products as potential DENV-2 RdRp inhibitors. Journal of Biomolecular Structure & Dynamics, 41(21), 12186–12203.
   PubMedGoogle Scholar
• Roney, M., Singh, G., Huq, A. K. M. M., Forid, M. S., Ishak, W. M. B. W., Rullah, K., Aluwi, M. F. F. M., & Tajuddin, S. N. (2023). Identification of pyrazole derivatives of usnic acid as novel inhibitor of SARS-CoV-2 main protease through virtual screening approaches. Molecular Biotechnology, 1–11. https://doi.org/10.1007/s12033-023-00667-5
   PubMed Web of Science ®Google Scholar
• Rozano, L., Abdullah Zawawi, M. R., Ahmad, M. A., & Jaganath, I. B. (2017). Computational analysis of Gynura bicolor bioactive compounds as dipeptidyl peptidase-IV inhibitor. Advances in Bioinformatics, 2017, 5124165. https://doi.org/10.1155/2017/5124165
   PubMedGoogle Scholar
• Sadeghi, M., Khomartash, M. S., Gorgani-Firuzjaee, S., Vahidi, M., Khiavi, F. M., & Taslimi, P. (2022). α-glucosidase inhibitory, antioxidant activity, and GC/MS analysis of Descurainia sophia methanolic extract: In vitro, in vivo, and in silico studies. Arabian Journal of Chemistry, 15(9), 104055. https://doi.org/10.1016/j.arabjc.2022.104055
   Web of Science ®Google Scholar
• Saeed, M., Shoaib, A., Tasleem, M., Alabdallah, N. M., Alam, M. J., Asmar, Z. E., Jamal, Q. M. S., Bardakci, F., Alqahtani, S. S., Ansari, I. A., & Badraoui, R. (2021). Assessment of antidiabetic activity of the shikonin by allosteric inhibition of protein-tyrosine phosphatase 1B (PTP1B) using state of art: An in silico and in vitro tactics. Molecules, 26(13), 3996. https://doi.org/10.3390/molecules26133996
   PubMed Web of Science ®Google Scholar
• Sajal, H., Patil, S. M., Raj, R., Shbeer, A. M., Ageel, M., & Ramu, R. (2022). Computer-aided screening of phytoconstituents from Ocimum tenuiflorum against diabetes mellitus targeting DPP4 inhibition: A combination of molecular docking, molecular dynamics, and pharmacokinetics approaches. Molecules (Basel, Switzerland), 27(16), 5133. https://doi.org/10.3390/molecules27165133
   PubMed Web of Science ®Google Scholar
• Seifert, E. (2014). OriginPro 9.1: Scientific data analysis and graphing software-software review. Journal of Chemical Information and Modeling, 54(5), 1552–1552. https://doi.org/10.1021/ci500161d
   PubMed Web of Science ®Google Scholar
• Shaikh, S., Ali, S., Lim, J. H., Chun, H. J., Ahmad, K., Ahmad, S. S., Hwang, Y. C., Han, K. S., Kim, N. R., Lee, E. J., & Choi, I. (2022). Dipeptidyl peptidase-4 inhibitory potentials of Glycyrrhiza uralensis and its bioactive compounds licochalcone A and licochalcone B: An in silico and in vitro study. Frontiers in Molecular Biosciences, 9, 1024764. https://doi.org/10.3389/fmolb.2022.1024764
   PubMed Web of Science ®Google Scholar
• Sharma, N., Gupta, N., Orfali, R., Kumar, V., Patel, C. N., Peng, J., & Perveen, S. (2022). Evaluation of the antifungal, antioxidant, and anti-diabetic potential of the essential oil of Curcuma longa leaves from the North-Western Himalayas by in vitro and in silico analysis. Molecules, 27(22), 7664. https://doi.org/10.3390/molecules27227664
   PubMed Web of Science ®Google Scholar
• Son, Y., Lee, J. H., Cheong, Y. K., Chung, H. T., & Pae, H. O. (2013). Antidiabetic potential of the heme oxygenase-1 inducer curcumin analogues, BioMed. BioMed Research International, 2013, 918039. https://doi.org/10.1155/2013/918039
   PubMed Web of Science ®Google Scholar
• Sprenger, K. G., Jaeger, V. W., & Pfaendtner, J. (2015). The general AMBER force field (GAFF) can accurately predict thermodynamic and transport properties of many ionic liquids. The Journal of Physical Chemistry. B, 119(18), 5882–5895. https://doi.org/10.1021/acs.jpcb.5b00689
   PubMed Web of Science ®Google Scholar
• Sutton, J. M., Clark, D. E., Dunsdon, S. J., Fenton, G., Fillmore, A., Harris, N. V., Higgs, C., Hurley, C. A., Krintel, S. L., MacKenzie, R. E., Duttaroy, A., Gangl, E., Maniara, W., Sedrani, R., Namoto, K., Ostermann, N., Gerhartz, B., Sirockin, F., Trappe, J., Hassiepen, U., & Baeschlin, D. K. (2012). Novel heterocyclic DPP-4 inhibitors for the treatment of type 2 diabetes. Bioorganic & Medicinal Chemistry Letters, 22(3), 1464–1468. https://doi.org/10.1016/j.bmcl.2011.11.054
   PubMed Web of Science ®Google Scholar
• Tanwar, O., Tanwar, L., Shaquiquzzaman, M., Alam, M. M., & Akhter, M. (2014). Structure based virtual screening of MDPI database: Discovery of structurally diverse and novel DPP-IV inhibitors. Bioorganic & Medicinal Chemistry Letters, 24(15), 3447–3451. https://doi.org/10.1016/j.bmcl.2014.05.076
   PubMed Web of Science ®Google Scholar
• Tomeh, M. A., Hadianamrei, R., & Zhao, X. (2019). A review of curcumin and its derivatives as anticancer agents. International Journal of Molecular Sciences, 20(5), 1033. https://doi.org/10.3390/ijms20051033
   PubMed Web of Science ®Google Scholar
• Tong, F., Chai, R., Jiang, H., & Dong, B. (2018). In vitro/vivo drug release and anti-diabetic cardiomyopathy properties of curcumin/PBLG-PEG-PBLG nanoparticles. International Journal of Nanomedicine, 13, 1945–1962. https://doi.org/10.2147/IJN.S153763
   PubMed Web of Science ®Google Scholar
• Vaithiyalingam, M., Sumathi, D. L., & Sabarathinam, S. (2023). Isolation and in silico study of curcumin from Curcuma longa and its anti-diabetic activity. Applied Biochemistry and Biotechnology, 195(2), 947–957. https://doi.org/10.1007/s12010-022-04173-3
   PubMed Web of Science ®Google Scholar
• Walum, E. (1998). Acute oral toxicity. Environmental Health Perspectives, 106(Suppl 2), 497–503. https://doi.org/10.1289/ehp.98106497
   PubMed Web of Science ®Google Scholar
• Wang, J., Wang, W., Kollman, P. A., & Case, D. A. (2006). Automatic atom type and bond type perception in molecular mechanical calculations. Journal of Molecular Graphics & Modelling, 25(2), 247–260. https://doi.org/10.1016/j.jmgm.2005.12.005
   PubMed Web of Science ®Google Scholar
• WHO. (2016). World Health organization global report on diabetes.
   Google Scholar
• Woods, R. J., & Chappelle, R. (2000). Restrained electrostatic potential atomic partial charges for condensed-phase simulations of carbohydrates. THEOCHEM Journal of Molecular Structure. 527(1-3), 149–156. https://doi.org/10.1016/S0166-1280(00)00487-5
   PubMedGoogle Scholar
• Yang, H., Lou, C., Sun, L., Li, J., Cai, Y., Wang, Z., Li, W., Liu, G., & Tang, Y. (2019). admetSAR 2.0: Web-service for prediction and optimization of chemical ADMET properties. Bioinformatics (Oxford, England), 35(6), 1067–1069. https://doi.org/10.1093/bioinformatics/bty707
   PubMed Web of Science ®Google Scholar
• Yang, Y., Shi, C. Y., Xie, J., Dai, J. H., He, S. L., & Tian, Y. (2020). Identification of potential dipeptidyl peptidase (DPP)-IV inhibitors among Moringa oleifera phytochemicals by virtual screening, molecular docking analysis, ADME/T-based prediction, and in vitro analyses. Molecules (Basel, Switzerland), 25(1), 189. https://doi.org/10.3390/molecules25010189
   PubMed Web of Science ®Google Scholar
• Zhao, L., Zhang, M., Pan, F., Li, J., Dou, R., Wang, X., Wang, Y., He, Y., Wang, S., & Cai, S. (2021). In silico analysis of novel dipeptidyl peptidase-IV inhibitory peptides released from Macadamia integrifolia antimicrobial protein 2 (MiAMP2) and the possible pathways involved in diabetes protection. Current Research in Food Science, 4, 603–611. https://doi.org/10.1016/j.crfs.2021.08.008
   PubMedGoogle Scholar
• Zhao, Y., Zhao, Y., Xie, L., Li, Q., Zhang, Y., Zang, Y., Li, X., Zhang, L., & Yang, Z. (2023). Identification of potential lead compounds targeting novel druggable cavity of SARS-CoV-2 spike trimer by molecular dynamics simulations. International Journal of Molecular Sciences, 24(7), 6281. https://doi.org/10.3390/ijms24076281
   PubMed Web of Science ®Google Scholar