A study on non-linear regression of the energy scoring function for molecular docking

• Main Authors: Chih-Peng Wu, 吳智棚
• Other Authors: Yen-Jen Oyang
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/24631710427100302338

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 95 === Virtual screening by molecular docking has become a crucial component for hit identification and lead optimization against very large libraries of compounds, but there is still much room for improvement in design of scoring function. The most common problem of existing scoring functions is the existence of “outliers”. Outliers of molecular docking can be very important and interesting especially when the observed biological activity is higher than the predicted one by scoring function. This article proposes a non-linear scoring function along with outlier detection. The evaluation is conducted with a comparison against the scoring function incorporated in the well-known AutoDock docking package. Based on the testing dataset from 607 protein-ligand complexes, the proposed non-linear scoring function has RMSE (root-mean-squared-error) equal to 2.13 kcal/mol that is comparable with the scoring function in AutoDock (3.453 kcal/mol). Moreover, with the proposed outlier detection mechanism, the RMSE could improve to 2.0 kcal/mol. As a result, the proposed scoring function with outlier detection helps the scoring quality and provides valuable clues for further biochemical analysis.