Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, 11794, USA.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA.
J Comput Aided Mol Des. 2018 Jan;32(1):225-230. doi: 10.1007/s10822-017-0069-7. Epub 2017 Nov 3.
Fast Fourier transform (FFT) based approaches have been successful in application to modeling of relatively rigid protein-protein complexes. Recently, we have been able to adapt the FFT methodology to treatment of flexible protein-peptide interactions. Here, we report our latest attempt to expand the capabilities of the FFT approach to treatment of flexible protein-ligand interactions in application to the D3R PL-2016-1 challenge. Based on the D3R assessment, our FFT approach in conjunction with Monte Carlo minimization off-grid refinement was among the top performing methods in the challenge. The potential advantage of our method is its ability to globally sample the protein-ligand interaction landscape, which will be explored in further applications.
基于快速傅里叶变换（FFT）的方法已成功应用于相对刚性的蛋白质-蛋白质复合物的建模。最近，我们已经能够将 FFT 方法应用于柔性蛋白质-肽相互作用的处理。在这里，我们报告了我们最新的尝试，即将 FFT 方法的功能扩展到处理应用于 D3R PL-2016-1 挑战的柔性蛋白质-配体相互作用。基于 D3R 的评估，我们的 FFT 方法与蒙特卡罗非网格细化最小化相结合，是挑战中表现最好的方法之一。我们的方法的潜在优势在于其能够全局采样蛋白质-配体相互作用景观，这将在进一步的应用中进行探索。
