Chapters authored
Computational Studies and Biosynthesis of Natural Products with Promising Anticancer Properties
We present an overview of computational approaches for the prediction of metabolic pathways by which plants biosynthesise compounds, with a focus on selected very promising anticancer secondary metabolites from floral sources. We also provide an overview of databases for the retrieval of useful genomic data, discussing the strengths and limitations of selected prediction software and the main computational tools (and methods), which could be employed for the investigation of the uncharted routes towards the biosynthesis of some of the identified anticancer metabolites from plant sources, eventually using specific examples to address some knowledge gaps when using these approaches.
Part of the book: Natural Products and Cancer Drug Discovery
Application of Computer Modeling to Drug Discovery: Case Study of PRK1 Kinase Inhibitors as Potential Drugs in Prostate Cancer Treatment
Computer modeling of natural products (NPs) and NP scaffolds is increasingly gaining importance in drug discovery, particularly in hit/lead discovery programs and at the lead optimization stage. Even though industry had lost interest in the implication of NPs in hit/lead searches, recent reports still show that computer modeling could be a useful assert for the identification of starting scaffolds from nature, which could be further exploited by synthetic modifications. In this chapter, the focus is on some useful tools for computer modeling aimed at the discovery of anticancer drugs from NP scaffolds. We also focus on some recent developments toward the identification of potential anticancer agents by the application of computer modeling. The chapter will lay emphasis on natural sources of anticancer compounds, present some useful databases and computational tools for anticancer drug discovery, and show some recent case studies of the application of computational modeling in anticancer drug discovery, as well as some success stories in virtual screening applications in anticancer drug discovery, highlighting some useful results on the application of on lead discovery (including promising NP scaffolds) against an interesting anticancer drug target, the protein kinase C-related kinase (PRK1).
Part of the book: Unique Aspects of Anti-cancer Drug Development