Review of Modern Computer-aided Drug Design Methods
DOI:
https://doi.org/10.54097/ijbls.v1i1.3230Keywords:
High-throughput screening (HTS), Structure-based drug design (SBDD), Ligand-based drug design (LBDD), Structure-based virtual screening (SBVS), Ligand-based virtual screening (LBVS)Abstract
Computer technology has developed rapidly in recent decades, and it is also widely used in the field of drug research and development. Computer-aided drug design (CADD) has appeared in the form of assistance to drug discovery process in this background. Computer-aided drug design can save time which is spent in the experimental process in the real world. Since appearance of computer-based drug design strategies, the concepts of HTS, structure-based and ligand-based drug design (SBDD and LBDD), and virtual screening (VS) have been proposed. These technologies have their own advantages and disadvantages, and have different scope of application. This review provides an introduction of modern drug design strategies which are based on computer technology, classifies different methods and finds out the basic working principle of each one, the applicability and limitations of these methods are discussed and recommendations are provided in the application of each method.
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Gibb, S. (2008). Toxicity testing in the 21st century: A vision and a strategy. Reproductive Toxicology, 25: 136-138.
Ferreira, L., dos Santos, R., Oliva, G., & Andricopulo, A. (2015). Molecular Docking and Structure-Based Drug Design Strategies. Molecules, 20: 13384-13421.
Andricopulo, A., Guido, R., & Oliva, G. (2008). Virtual Screening and Its Integration with Modern Drug Design Technologies. Current Medicinal Chemistry, 15: 37-46.
Liu, T., Lu, D., Zhang, H., Zheng, M., Yang, H., & Xu, Y. et al. (2016). Applying high-performance computing in drug discovery and molecular simulation. National Science Review, 3: 49-63.
Szymański, P., Markowicz, M., & Mikiciuk-Olasik, E. (2011). Adaptation of High-Throughput Screening in Drug Discovery—Toxicological Screening Tests. International Journal Of Molecular Sciences, 13: 427-452.
O’Connell, T., Ramsay, J., Rieth, S., Shapiro, M., & Stroh, J. (2014). Solution-Based Indirect Affinity Selection Mass Spectrometry—A General Tool For High-Throughput Screening Of Pharmaceutical Compound Libraries. Analytical Chemistry, 86: 7413-7420.
Cheng, T., Li, Q., Zhou, Z., Wang, Y., & Bryant, S. (2012). Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review. The AAPS Journal, 14: 133-141.
Akabli, T., Toufik, H., Yasri, A., Bih, H., & Lamchouri, F. (2018). Combining ligand-based and structure-based drug design approaches to study the structure-activity relationships of a β-carboline derivative series. Structural Chemistry, 29: 1637-1645.
Guido, R., Oliva, G., & Andricopulo, A. (2012). Structure- and ligand-based drug design approaches for neglected tropical diseases. Pure And Applied Chemistry, 84: 1857-1866.
Leelananda, S., & Lindert, S. (2016). Computational methods in drug discovery. Beilstein Journal Of Organic Chemistry, 12: 2694-2718.
Lee, C., Huang, H., & Juan, H. (2011). Reviewing Ligand-Based Rational Drug Design: The Search for an ATP Synthase Inhibitor. International Journal Of Molecular Sciences, 12: 5304-5318.
Do, P., Lee, E., & Le, L. (2018). Steered Molecular Dynamics Simulation in Rational Drug Design. Journal Of Chemical Information And Modeling, 58: 1473-1482.
Li, D., Deng, Y., Achab, A., Bharathan, I., Hopkins, B. A., Yu, W., Zhang, H., Sanyal, S., Pu, Q., Zhou, H., Liu, K., Lim, J., Fradera, X., Lesburg, C. A., Lammens, A., Martinot, T. A., Cohen, R. D., Doty, A. C., Ferguson, H., Nickbarg, E. B., … Han, Y. (2021). Carbamate and N-Pyrimidine Mitigate Amide Hydrolysis: Structure-Based Drug Design of Tetrahydroquinoline IDO1 Inhibitors. ACS medicinal chemistry letters, 12: 389–396.
McKay, P., Fayne, D., Horn, H., James, T., Peters, M., & Carta, G. et al. (2012). Consensus Computational Ligand-Based Design for the Identification of Novel Modulators of Human Estrogen Receptor Alpha. Molecular Informatics, 31: 246-258.
Darshit, B., Balaji, B., Rani, P., & Ramanathan, M. (2014). Identification and in vitro evaluation of new leads as selective and competitive glycogen synthase kinase-3β inhibitors through ligand and structure based drug design. Journal Of Molecular Graphics And Modelling, 53: 31-47.
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: 10-22.
Hirono, S., Nakagome, I., Imai, R., Maeda, K., Kusuhara, H., & Sugiyama, Y. (2005). Estimation of the Three-Dimensional Pharmacophore of Ligands for Rat Multidrug-Resistance?Associated Protein 2 Using Ligand-Based Drug Design Techniques. Pharmaceutical Research, 22: 260-269.
Wu, K., Lei, P., Liu, H., Wu, C., Leung, C., & Ma, D. (2019). Mimicking Strategy for Protein–Protein Interaction Inhibitor Discovery by Virtual Screening. Molecules, 24: 4428.
Reid, D., Sadjad, B., Zsoldos, Z., & Simon, A. (2008). LASSO—ligand activity by surface similarity order: a new tool for ligand based virtual screening. Journal Of Computer-Aided Molecular Design, 22: 479-487.
Reynolds, C., Muggleton, S., & Sternberg, M. (2015). Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads. Molecular Informatics, 34: 615-625.
Wang, Z., Sun, H., Shen, C., Hu, X., Gao, J., & Li, D. et al. (2020). Combined strategies in structure-based virtual screening. Physical Chemistry Chemical Physics, 22: 3149-3159.
Lim, S., Rahman, M., & Tejo, B. (2011). Structure-based and ligand-based virtual screening of novel methyltransferase inhibitors of the dengue virus. BMC Bioinformatics, 12.
Chen, C., Chang, Y., Bau, D., Huang, H., Tsai, F., Tsai, C., & Chen, C. (2009). Ligand-Based Dual Target Drug Design for H1N1: Swine Flu- A Preliminary First Study. Journal Of Biomolecular Structure And Dynamics, 27: 171-178.
Muratov, E., Bajorath, J., Sheridan, R., Tetko, I., Filimonov, D., & Poroikov, V. et al. (2020). QSAR without borders. Chemical Society Reviews, 49: 3525-3564.
Ghosh S., Nie, A., An, J., & Huang, Z. (2006). Structure-based virtual screening of chemical libraries for drug discovery. Current Opinion In Chemical Biology, 10: 194-202.
Irwin, J. J., & Shoichet, B. K. (2005). ZINC--a free database of commercially available compounds for virtual screening. Journal of chemical information and modeling, 45: 177–182.
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