Moiety-based Site-moiety Map

• Main Authors: Hsu, Yen-Chao, 許彥超
• Other Authors: Yang, Jinn-moon
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/66756137756174481558

碩士 === 國立交通大學 === 生物資訊及系統生物研究所 === 100 === Understanding the mechanism of protein-ligand interaction is helpful for drug design. Currently, the virtual screening technique is widely used to predict protein-ligand interactions for reducing the cost and time of drug development. In addition, the rapid increase in the number of protein structures has made the success of virtual screening. However, the accuracy of virtual screening remained intensive. One of the major reasons is our incomplete understanding of protein-ligand interactions involved in biological functions and the imprecise scoring functions. Scoring functions used in virtual screening often ignore key interactions between moieties of compounds and pockets of protein-binding sites, leading a low hit rate. To address this issue, our lab developed a new method, namely compound-based site-moiety map (compound-based SiMMap), to understand the mechanism of protein-ligand interactions and identify the key interactions. A SiMMap utilizes protein structures and numerous docked compounds to describe the relationship between the moiety preferences and the physico-chemical properties of binding site. A SiMMap is composed of several anchors, and each anchor includes three elements: (1) binding pockets (a part of the binding site), (2) moiety preference of the pockets, and (3) pocket-moiety interaction types. SiMMap provides clues to understand key interactions in protein-ligand binding site and their mechanism. However, constructing a SiMMap requires at least 1,000 docked compounds, which is a time-consuming procedure. In addition, the compound-based SiMMap may be biased by moiety compositions of docked compounds. To address these two issues, we propose a novel method namely moiety-based site-moiety map. We firstly identified the 34 most common moieties in 1,382 FDA-approved drugs or 6,163 metabolites. Then, we replaced the compound docking procedure by docking the 34 relevant moieties to save time. Furthermore, the anchors of the moiety-based site-moiety map could be useful to drug discovery and lead optimization because the moieties are the key features of drug actions and metabolisms. We initially tested moiety-based site-moiety map on five important disease target proteins: (1) Thymidine kinase, (2) Estrogen receptor, (3) Shikimate kinase, (4) iii Dihydrofolate reductase and (5) Rho-associated protein kinase 1. We then examined the anchors of the moiety-based site-moiety maps derived by the docked moieties by biological functions or binding mechanisms. Our results reveal that the anchors often located in key interaction areas of protein-ligand binding sites. For example, in the five target proteins, 82% of anchors are involved in the substrate binding or inhibitor binding, and 98% of anchor residues are highly conserved. These suggest that the anchors may play important roles in biological functions and drug design. In addition, we found that the compounds matching more anchors often have better activities. We believe the moiety-based site-moiety map is useful for drug development, drug optimization, and understanding the mechanism of protein-ligand interaction.