Abstract
Medicinal plants are the source of various therapeutic agents, including crude extracts and pharmacologically active compounds. Many novel targets and ligands are being identified daily to treat various diseases from AIDS to Alzheimer’s to cancer with the application and techniques of drug designing. Natural products act as pillars for traditional medicine and are involved in the identification of lead compounds which could plausibly act as potential drugs in the area of parasitology. Computational biology has successfully expanded its arms in numerous ways in the process of drug discovery, from the identification of novel targets and biomarkers for rapid screening of large compounds to drug design assistance in clinical trials. The use of in silico suites like Schrodinger’s Maestro, Discovery Studio, and software like grid computing and window-based general PBPK/PD modelling for visualization software along with these, the explosion of biological data (genome sequences and information on proteins, etc.) has also led to the enhancement in the designing of effective treatment methodologies. In this chapter, we explicitly focus on the ancient drug discovery methods to advanced computational methods, which have led to an inclination of drug discovery towards a data-driven approach and using natural products to identify lead molecules and small molecule drug candidates for parasitic disease. It will also deal with the present informatics knowledge gaps and other barriers that need to be overcome for the complete reliability of computationally generated leads for drug discovery in pathogenesis. Finally, this chapter will provide a summary of commercially available important nature-based drugs and helpful software.
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Ahmad, S. et al. (2023). Natural Product-Based Drug Designing for Treatment of Human Parasitic Diseases. In: Singh, A., Rathi, B., Verma, A.K., Singh, I.K. (eds) Natural Product Based Drug Discovery Against Human Parasites. Springer, Singapore. https://doi.org/10.1007/978-981-19-9605-4_3
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DOI: https://doi.org/10.1007/978-981-19-9605-4_3
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