High-throughput virtual screening approach of natural compounds as target inhibitors of plasmepsin-II

References

• Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindah, E. (2015). Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1–2, 19–25. https://doi.org/10.1016/j.softx.2015.06.001
   Google Scholar
• Abrigach, F., Rokni, Y., Takfaoui, A., Khoutoul, M., Doucet, H., Asehraou, A., & Touzani, R. (2018, April). In vitro screening, homology modeling and molecular docking studies of some pyrazole and imidazole derivatives. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 103, 653–661. https://doi.org/10.1016/j.biopha.2018.04.061
   PubMed Web of Science ®Google Scholar
• Ahmad, S. S., Rahi, M., Ranjan, V., & Sharma, A. (2021, June). Mefloquine as a prophylaxis for malaria needs to be revisited. International Journal for Parasitology. Drugs and Drug Resistance, 17, 23–26. https://doi.org/10.1016/j.ijpddr.2021.06.003
   PubMed Web of Science ®Google Scholar
• Alhadrami, H. A., Sayed, A. M., El-Gendy, A. O., Shamikh, Y. I., Gaber, Y., Bakeer, W., Sheirf, N. H., Attia, E. Z., Shaban, G. M., Khalifa, B. A., Ngwa, C. J., Pradel, G., Rateb, M. E., Hassan, H. M., Alkhalifah, D. H. M., Abdelmohsen, U. R., & Hozzein, W. N. (2021). A metabolomic approach to target antimalarial metabolites in the Artemisia annua fungal endophytes. Scientific Reports, 11(1), 1–11. https://doi.org/10.1038/s41598-021-82201-8
   PubMed Web of Science ®Google Scholar
• Baammi, S., Daoud, R., & El Allali, A. (2022). Assessing the effect of a series of mutations on the dynamic behavior of phosphite dehydrogenase using molecular docking, molecular dynamics and quantum mechanics/molecular mechanics simulations. Journal of Biomolecular Structure and Dynamics, 1–13. https://doi.org/10.1080/07391102.2022.2064912
   PubMed Web of Science ®Google Scholar
• Bao, Y., Zhou, L., Dai, D., Zhu, X., Hu, Y., & Qiu, Y. (2018). Discover potential inhibitors for PFKFB3 using 3D-QSAR, virtual screening, molecular docking and molecular dynamics simulation. Journal of Receptor and Signal Transduction Research, 38(5–6), 413–431. https://doi.org/10.1080/10799893.2018.1564150
   PubMed Web of Science ®Google Scholar
• Benkert, P., Tosatto, S. C. E., & Schomburg, D. (2008). QMEAN: A comprehensive scoring function for model quality assessment. Proteins, 71(1), 261–277. https://doi.org/10.1002/prot.21715
   PubMed Web of Science ®Google Scholar
• Bhardwaj, V. K., Singh, R., Sharma, J., Rajendran, V., Purohit, R., & Kumar, S. (2021). Identification of bioactive molecules from tea plant as SARS-CoV-2 main protease inhibitors. Journal of Biomolecular Structure and Dynamics, 39(10), 3449–3458. https://doi.org/10.1080/07391102.2020.1766572
   PubMed Web of Science ®Google Scholar
• Boss, C., Richard-Bildstein, S., Weller, T., Fischli, W., Meyer, S., & Binkert, C. (2003). Inhibitors of the Plasmodium falciparum parasite aspartic protease plasmepsin II as potential antimalarial agents. Current Medicinal Chemistry, 10(11), 883–907. https://doi.org/10.2174/0929867033457674
   PubMed Web of Science ®Google Scholar
• Bruneel, F. (2019). Human cerebral malaria: 2019 mini review. Revue Neurologique, 175(7–8), 445–450. https://doi.org/10.1016/j.neurol.2019.07.008
   PubMed Web of Science ®Google Scholar
• Cavasotto, C. N., & Phatak, S. S. (2009). Homology modeling in drug discovery: Current trends and applications. Drug Discovery Today, 14(13–14), 676–683. https://doi.org/10.1016/j.drudis.2009.04.006
   PubMed Web of Science ®Google Scholar
• Chandrasekaran, B., Abed, S. N., Al-Attraqchi, O., Kuche, K., & Tekade, R. K. (2018). Computer-aided prediction of pharmacokinetic (ADMET) properties. In Dosage form design parameters (Vol. 2). Elsevier Inc. https://doi.org/10.1016/B978-0-12-814421-3.00021-X
   Google Scholar
• Childers, M. C., & Daggett, V. (2018). Validating molecular dynamics simulations against experimental observables in light of underlying conformational ensembles. The Journal of Physical Chemistry B, 122(26), 6673–6689. https://doi.org/10.1021/acs.jpcb.8b02144
   PubMed Web of Science ®Google Scholar
• Dallakyan, S., & Olson, A. (2015). Small-molecule library screening by docking with PyRx. Global Food Security Governance, 1263, 1–11. https://doi.org/10.1007/978-1-4939-2269-7
   Google Scholar
• Dan, N., & Bhakat, S. (2015). New paradigm of an old target: An update on structural biology and current progress in drug design towards plasmepsin II. European Journal of Medicinal Chemistry, 95, 324–348. https://doi.org/10.1016/j.ejmech.2015.03.049
   PubMed Web of Science ®Google Scholar
• de Sousa, A. C. C., Combrinck, J. M., Maepa, K., & Egan, T. J. (2020). Virtual screening as a tool to discover new β-haematin inhibitors with activity against malaria parasites. Scientific Reports, 10(1), 3374. https://doi.org/10.1038/s41598-020-60221-0
   PubMed Web of Science ®Google Scholar
• Dong, S., Sun, J., Mao, Z., Wang, L., Lu, Y. L., & Li, J. (2020). A guideline for homology modeling of the proteins from newly discovered betacoronavirus, 2019 novel coronavirus (2019-nCoV). Journal of Medical Virology, 92(9), 1542–1548. https://doi.org/10.1002/jmv.25768
   PubMed Web of Science ®Google Scholar
• El Aissouq, A., Chedadi, O., Bouachrine, M., & Ouammou, A. (2021). Identification of novel SARS-CoV-2 inhibitors: A structure-based virtual screening approach. Journal of Chemistry, 2021, 1–7. https://doi.org/10.1155/2021/1901484
   Web of Science ®Google Scholar
• En-Nahli, F., Belhassan, A., Zaki, H., Aissouq, A., El Lakhlifi, T., & Bouachrine, M. (2023). Thiazinoquinones derivatives as antimalarial agents : 3D- QSAR studies, molecular docking and molecular dynamics simulations. 12(3).
   Google Scholar
• Ho, B. K., & Brasseur, R. (2005). The Ramachandran plots of glycine and pre-proline. BMC Structural Biology, 5, 14–11. https://doi.org/10.1186/1472-6807-5-14
   PubMed Web of Science ®Google Scholar
• Hyde, J. E. (2002). Mechanisms of resistance of Plasmodium falciparum to antimalarial drugs. Microbes and Infection, 4(2), 165–174. https://doi.org/10.1016/S1286-4579(01)01524-6
   PubMed Web of Science ®Google Scholar
• Ibrahim Uba, A., & Yelekçi, K. (2019). Homology modeling of human histone deacetylase 10 and design of potential selective inhibitors. Journal of Biomolecular Structure & Dynamics, 37(14), 3627–3636. https://doi.org/10.1080/07391102.2018.1521747
   PubMed Web of Science ®Google Scholar
• Kaur, K., Jain, M., Reddy, R. P., & Jain, R. (2010). Quinolines and structurally related heterocycles as antimalarials. European Journal of Medicinal Chemistry, 45(8), 3245–3264. https://doi.org/10.1016/j.ejmech.2010.04.011
   PubMed Web of Science ®Google Scholar
• Lee, J., Cheng, X., Swails, J. M., Yeom, M. S., Eastman, P. K., Lemkul, J. A., Wei, S., Buckner, J., Jeong, J. C., Qi, Y., Jo, S., Pande, V. S., Case, D. A., Brooks, C. L., MacKerell, A. D., Klauda, J. B., & Im, W. (2016). CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. Journal of Chemical Theory and Computation, 12(1), 405–413. https://doi.org/10.1021/acs.jctc.5b00935
   PubMed Web of Science ®Google Scholar
• Matada, B. S., Pattanashettar, R., & Yernale, N. G. (2021). A comprehensive review on the biological interest of quinoline and its derivatives. Bioorganic & Medicinal Chemistry, 32, 115973. (August 2020), https://doi.org/10.1016/j.bmc.2020.115973
   PubMed Web of Science ®Google Scholar
• Muhammed, M. T., & Aki-Yalcin, E. (2019). Homology modeling in drug discovery: Overview, current applications, and future perspectives. Chemical Biology & Drug Design, 93(1), 12–20. https://doi.org/10.1111/cbdd.13388
   PubMed Web of Science ®Google Scholar
• Neafsey, D. E., Taylor, A. R., & MacInnis, B. L. (2021). Advances and opportunities in malaria population genomics. Nature Reviews. Genetics, 22(8), 502–517. https://doi.org/10.1038/s41576-021-00349-5
   PubMed Web of Science ®Google Scholar
• Nikolaev, D. M., Shtyrov, A. A., Panov, M. S., Jamal, A., Chakchir, O. B., Kochemirovsky, V. A., Olivucci, M., & Ryazantsev, M. N. (2018). A comparative study of modern homology modeling algorithms for rhodopsin structure prediction. ACS Omega, 3(7), 7555–7566. https://doi.org/10.1021/acsomega.8b00721
   PubMed Web of Science ®Google Scholar
• Pal, S., Kumar, V., Kundu, B., Bhattacharya, D., Preethy, N., Reddy, M. P., & Talukdar, A. (2019). Ligand-based pharmacophore modeling, virtual screening and molecular docking studies for discovery of potential topoisomerase I inhibitors. Computational and Structural Biotechnology Journal, 17, 291–310. https://doi.org/10.1016/j.csbj.2019.02.006
   PubMed Web of Science ®Google Scholar
• Quimque, M. T. J., Notarte, K. I. R., Fernandez, R. A. T., Mendoza, M. A. O., Liman, R. A. D., Lim, J. A. K., Pilapil, L. A. E., Ong, J. K. H., Pastrana, A. M., Khan, A., Wei, D. Q., & Macabeo, A. P. G. (2021). Virtual screening-driven drug discovery of SARS-CoV2 enzyme inhibitors targeting viral attachment, replication, post-translational modification and host immunity evasion infection mechanisms. Journal of Biomolecular Structure & Dynamics, 39(12), 4316–4333. https://doi.org/10.1080/07391102.2020.1776639
   PubMed Web of Science ®Google Scholar
• Ramanathan, K., Verma, K., Gupta, N., & Shanthi, V. (2018). Discovery of therapeutic lead molecule against β-tubulin using computational approach. Interdisciplinary Sciences, Computational Life Sciences, 10(4), 734–747. https://doi.org/10.1007/s12539-017-0233-8
   PubMed Web of Science ®Google Scholar
• Saih, A., Baba, H., Bouqdayr, M., Ghazal, H., Hamdi, S., Kettani, A., & Wakrim, L. (2021). In Silico analysis of high-risk missense variants in human ACE2 gene and susceptibility to SARS-CoV-2 infection. BioMed Research International, 2021, 6685840. https://doi.org/10.1155/2021/6685840
   PubMed Web of Science ®Google Scholar
• Shang, X.-F., Morris-Natschke, S. L., Liu, Y.-Q., Guo, X., Xu, X.-S., Goto, M., Li, J.-C., Yang, G.-Z., & Lee, K.-H. (2018). Biologically active quinoline and quinazoline alkaloids part I. Medicinal Research Reviews, 38(3), 775–828. https://doi.org/10.1002/med.21466
   PubMed Web of Science ®Google Scholar
• Shang, X.-F., Morris-Natschke, S. L., Yang, G.-Z., Liu, Y.-Q., Guo, X., Xu, X.-S., Goto, M., Li, J.-C., Zhang, J.-Y., & Lee, K.-H. (2018). Biologically active quinoline and quinazoline alkaloids part II. Medicinal Research Reviews, 38(5), 1614–1660. https://doi.org/10.1002/med.21492
   PubMed Web of Science ®Google Scholar
• Sonawane, K. D., Barale, S. S., Dhanavade, M. J., Waghmare, S. R., Nadaf, N. H., Kamble, S. A., Mohammed, A. A., Makandar, A. M., Fandilolu, P. M., Dound, A. S., & Naik, N. M. (2020). Homology modeling and docking studies of TMPRSS2 with experimentally known inhibitors Camostat mesylate. Nafamostat and Bromhexine Hydrochloride to Control SARS-Coronavirus-2, https://doi.org/10.26434/chemrxiv.12162360
   Google Scholar
• Stevenson, M. M., & Riley, E. M. (2004). Innate immunity to malaria. Nature Reviews. Immunology, 4(3), 169–180. https://doi.org/10.1038/nri1311
   PubMed Web of Science ®Google Scholar
• Stitou, M., Toufik, H., Bouachrine, M., & Lamchouri, F. (2021). Quantitative structure–activity relationships analysis, homology modeling, docking and molecular dynamics studies of triterpenoid saponins as Kirsten rat sarcoma inhibitors. Journal of Biomolecular Structure & Dynamics, 39(1), 152–170. https://doi.org/10.1080/07391102.2019.1707122
   PubMed Web of Science ®Google Scholar
• Tareq, M., & Khan, H. (2010). Predictions of the ADMET properties of candidate drug molecules utilizing different QSAR/QSPR modelling approaches. Current Drug Metabolism, 11(4), 285–295.
   PubMed Web of Science ®Google Scholar
• Verma, K., Mahalapbutr, P., Auepattanapong, A., Khaikate, O., Kuhakarn, C., Takahashi, K., & Rungrotmongkol, T. (2022). Molecular dynamics simulations of sulfone derivatives in complex with DNA topoisomerase IIα ATPase domain. Journal of Biomolecular Structure & Dynamics, 40(4), 1692–1701. https://doi.org/10.1080/07391102.2020.1831961
   PubMed Web of Science ®Google Scholar
• Wang, Z., Sun, H., Shen, C., Hu, X., Gao, J., Li, D., Cao, D., & Hou, T. (2020). Combined strategies in structure-based virtual screening. Physical Chemistry Chemical Physics, 22(6), 3149–3159. https://doi.org/10.1039/C9CP06303J
   PubMed Web of Science ®Google Scholar
• Wani, W. A., Jameel, E., Baig, U., Mumtazuddin, S., & Hun, L. T. (2015). Ferroquine and its derivatives: New generation of antimalarial agents. European Journal of Medicinal Chemistry, 101, 534–551. https://doi.org/10.1016/j.ejmech.2015.07.009
   PubMed Web of Science ®Google Scholar
• Wicht, K. J., Mok, S., & Fidock, D. A. (2020). Molecular mechanisms of drug resistance in Plasmodium falciparum malaria. Annual Review of Microbiology, 74, 431–454. https://doi.org/10.1146/annurev-micro-020518-115546
   PubMed Web of Science ®Google Scholar