Computer-Aided Drug Design in Anticancer Drugs
DOI:
https://doi.org/10.61173/j5m79556Keywords:
Anticancer Drugs, Cancer poses, molecular, bendamustine, Ligand-based drug designAbstract
The fight against cancer is a significant global health issue, and creating effective anticancer medications is crucial to addressing this challenge. Traditional methods of developing these drugs are time-consuming and require substantial financial investment. However, computer-aided drug design technology can reduce the time and cost associated with research and development. This paper summarizes various studies that have utilized computer-aided drug design technology to create anticancer drugs. It explores the application of this technology in cancer research and serves as a reference for future development of anticancer medications.
References
[1] Acharya, C., Coop, A., E. Polli, J., & D. MacKerell, A. (2011). Recent Advances in Ligand-Based Drug Design: Relevance and Utility of the Conformationally Sampled Pharmacophore Approach. Current Computer Aided-Drug Design, 7(1), 10–22.
[2] Ambure, P., & Roy, K. (2017). CADD Modeling of Multi- Target Drugs Against Alzheimer’s Disease. Current Drug Targets, 18(5), 522–533.
[3] Baig, M. H., Ahmad, K., Rabbani, G., Danishuddin, M., & Choi, I. (2018). Computer-Aided Drug Design and its Application to Developing Potential Drugs for Neurodegenerative Disorders. Current Neuropharmacology, 16(6), 740–748.
[4] Cheng, H., Orr, S. T. M., Bailey, S., Brooun, A., Chen, P., Deal, J. G., Deng, Y. L., Edwards, M. P., Gallego, G. M., Grodsky, N., Huang, B., Jalaie, M., Kaiser, S., Kania, R. S., Kephart, S. E., Lafontaine, J., Ornelas, M. A., Pairish, M., Planken, S., … Kath, J. C. (2021). Structure-Based Drug Design and Synthesis of PI3Kα-Selective Inhibitor (PF-06843195). Journal of Medicinal Chemistry, 64(1), 644–661.
[5] Clement, O. O., Freeman, C. M., Hartmann, R. W., Handratta, V. D., Vasaitis, T. S., Brodie, A. M. H., & Njar, V. C. O. (2003). Three-Dimensional Pharmacophore Modeling of Human CYP17 Inhibitors. Potential Agents for Prostate Cancer Therapy. Journal of Medicinal Chemistry, 46(12), 2345–2351.
[6] Ganji, M., Bakhshi, S., Shoari, A., & Ahangari Cohan, R.
[2023] . Discovery of potential FGFR3 inhibitors via QSAR, pharmacophore modeling, virtual screening and molecular docking studies against bladder cancer. Journal of Translational Medicine, 21(1), 111.
[7] Huang, H.-J., Kraevaya, O. A., Voronov, I. I., Troshin, P. A., & Hsu, S. (2020). Fullerene Derivatives as Lung Cancer Cell Inhibitors: Investigating Potential Descriptors Using QSAR Approaches. International Journal of Nanomedicine, Volume 15, 2485–2499.
[8] Kapetanovic, I. M. (2008). Computer-aided drug discovery and development (CADDD): In silico-chemico-biological approach. Chemico-Biological Interactions, 171(2), 165–176.
[9] Llorach-Pares, L., Nonell-Canals, A., Avila, C., & Sanchez- Martinez, M. (2022). Computer-Aided Drug Design (CADD) to De-Orphanize Marine Molecules: Finding Potential Therapeutic Agents for Neurodegenerative and Cardiovascular Diseases. Marine Drugs, 20(1), 53.
[10] McInnes, C. (2007). Virtual screening strategies in drug discovery. Current Opinion in Chemical Biology, 11(5), 494–
[502] https://doi.org/10.1016/j.cbpa.2007.08.033
[11] Russo Spena, C., De Stefano, L., Poli, G., Granchi, C., El Boustani, M., Ecca, F., Grassi, G., Grassi, M., Canzonieri, V., Giordano, A., Tuccinardi, T., Caligiuri, I., & Rizzolio, F. (2019). Virtual screening identifies a PIN1 inhibitor with possible antiovarian cancer effects. Journal of Cellular Physiology, 234(9), 15708–15716.
[12] Sharma, T., Saralamma, V. V. G., Lee, D. C., Imran, M. A., Choi, J., Baig, M. H., & Dong, J.-J. (2022). Combining structure-based pharmacophore modeling and machine learning for the identification of novel BTK inhibitors. International Journal of Biological Macromolecules, 222, 239–250.
[13] Song, Y.-Q., Wu, C., Wu, K.-J., Han, Q.-B., Miao, X.-M., Ma, D.-L., & Leung, C.-H. (2021). Ubiquitination Regulators Discovered by Virtual Screening for the Treatment of Cancer. Frontiers in Cell and Developmental Biology, 9, 665646.
[14] Tamanini, E., Buck, I. M., Chessari, G., Chiarparin, E., Day, J. E. H., Frederickson, M., Griffiths-Jones, C. M., Hearn, K., Heightman, T. D., Iqbal, A., Johnson, C. N., Lewis, E. J., Martins, V., Peakman, T., Reader, M., Rich, S. J., Ward, G. A., Williams, P. A., & Wilsher, N. E. (2017). Discovery of a Potent Nonpeptidomimetic, Small-Molecule Antagonist of Cellular Inhibitor of Apoptosis Protein 1 (cIAP1) and X-Linked Inhibitor of Apoptosis Protein (XIAP). Journal of Medicinal Chemistry, 60(11), 4611–4625.
[15] Van Montfort, R. L. M., & Workman, P. (2017). Structurebased drug design: Aiming for a perfect fit. Essays in Biochemistry, 61(5), 431–437. https://doi.org/10.1042/ EBC20170052
[16] WHO. (2023). The World Health Organization. www.who.int
[17] Yang, S.-Y. (2010). Pharmacophore modeling and applications in drug discovery: Challenges and recent advances. Drug Discovery Today, 15(11), 444–450.
[18] Zhang, N.-N., Ban, Y.-J., Wang, Y.-J., He, S.-Y., Qi, P.-P., Bi, T., Ma, Y.-F., Dong, Y.-X., Guo, B., Weng, J., Li, H.-L., Tang, L., & Zhang, J.-Q. (2023). Virtual screening of novel mTOR inhibitors for the potential treatment of human colorectal cancer. Bioorganic Chemistry, 140, 106781.
[19] Zhou, Y., Chen, Y., Huang, X., Tan, Y., Hu, R., Li, C., & Niu, M. (2021). A Supramolecular Nanomedicine Based on Bendamustine and MDM2‐Targeted D‐peptide Inhibitor for Breast Cancer Therapy. Advanced Healthcare Materials, 10(21), 2100980.
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