AIScore  Chemically Diverse Empirical Scoring Function Employing Quantum Chemical Binding Energies of Hydrogen-Bonded Complexes

详细信息    查看全文

• 作者：Stephan Raub ; Andreas Steffen ; Andreas Kä ; mper ; Christel M. Marian
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2008
• 出版时间：July 2008
• 年：2008
• 卷：48
• 期：7
• 页码：1492-1510
• 全文大小：680K
• 年卷期：v.48,no.7(July 2008)
• ISSN：1549-960X

文摘

In this work we report on a novel scoring function that is based on the LUDI model and focuses on the prediction of binding affinities. AIScore extends the original FlexX scoring function using a chemically diverse set of hydrogen-bonded interactions derived from extensive quantum chemical ab initio calculations. Furthermore, we introduce an algorithmic extension for the treatment of multifurcated hydrogen bonds (XFurcate). Charged and resonance-assisted hydrogen bond energies and hydrophobic interactions as well as a scaling factor for implicit solvation were fitted to experimental data. To this end, we assembled a set of 101 protein−ligand complexes with known experimental binding affinities. Tightly bound water molecules in the active site were considered to be an integral part of the binding pocket. Compared to the original FlexX scoring function, AIScore significantly improves the prediction of the binding free energies of the complexes in their native crystal structures. In combination with XFurcate, AIScore yields a Pearson correlation coefficient of R_P = 0.87 on the training set. In a validation run on the PDBbind test set we achieved an R_P value of 0.46 for 799 attractively scored complexes, compared to a value of R_P = 0.17 and 739 bound complexes obtained with the FlexX original scoring function. The redocking capability of AIScore, on the other hand, does not fully reach the good performance of the original FlexX scoring function. This finding suggests that AIScore should rather be used for postscoring in combination with the standard FlexX incremental ligand construction scheme.