In Silicon Approach for Discovery of Chemopreventive Agents

Facile and divergent optimization of chromazonarol enabled the identification of simplified drimane meroterpenoids as novel pharmaceutical leads

The diversity of drimane hydroquinones was significantly expanded by the facile construction of (+)-chromazonarol relevant natural products, isomers, and analogues for the discovery of new pharmaceutical leads. The structure-activity relationship of (+)-chromazonarol relevant (non)-natural products was delineated via the synergistic interaction of the programmable synthesis and bioactivity-guided screening. The first divergent derivatization of (+)-chromazonarol demonstrated that the phenolic hydroxyl group is one inviolable requirement for antifungal effect. Pinpoint modification of (+)-yahazunol manifested the position of hydroxyl group was crucial for both antifungal and antitumor activities. (+)-Albaconol, (+)-neoalbaconol, and two (+)-yahazunol isomers (24 and 25) proved to be the novel pharmaceutical leads. The probable macromolecular targets were estimated to deliver new information about the biological potentials resident in (+)-yahazunol relevant products. This work also featured the first synthesis of (+)-albaconol and (+)-neoalbaconol, the first biological exploration of (+)-dictyvaric acid and improved preparation of (+)-8-epi-puupehedione and a promising pelorol analogue.

Homology modeling in drug discovery: Overview, current applications, and future perspectives

Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.