کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5372116 | 1503979 | 2007 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A novel empirical free energy function that explains and predicts protein-protein binding affinities
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی تئوریک و عملی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A free energy function can be defined as a mathematical expression that relates macroscopic free energy changes to microscopic or molecular properties. Free energy functions can be used to explain and predict the affinity of a ligand for a protein and to score and discriminate between native and non-native binding modes. However, there is a natural tension between developing a function fast enough to solve the scoring problem but rigorous enough to explain and predict binding affinities. Here, we present a novel, physics-based free energy function that is computationally inexpensive, yet explanatory and predictive. The function results from a derivation that assumes the cost of polar desolvation can be ignored and that includes a unique and implicit treatment of interfacial water-bridged interactions. The function was parameterized on an internally consistent, high quality training set giving R2 = 0.97 and Q2 = 0.91. We used the function to blindly and successfully predict binding affinities for a diverse test set of 31 wild-type protein-protein and protein-peptide complexes (R2 = 0.79, rmsd = 1.2 kcal molâ 1). The function performed very well in direct comparison with a recently described knowledge-based potential and the function appears to be transferable. Our results indicate that our function is well suited for solving a wide range of protein/peptide design and discovery problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biophysical Chemistry - Volume 129, Issues 2â3, September 2007, Pages 198-211
Journal: Biophysical Chemistry - Volume 129, Issues 2â3, September 2007, Pages 198-211
نویسندگان
Joseph Audie, Suzanne Scarlata,