Hessian-free low-mode conformational search for large-scale protein loop optimization: application to c-jun N-terminal kinase JNK3

Abstract

A Hessian-free low-mode search algorithm has been developed for large-scale conformational searching. The new method is termed LLMOD, and it utilizes the ARPACK package to compute low-mode eigenvectors of a Hessian matrix that is only referenced implicitly, through its product with a series of vectors. The Hessian × vector product is calculated utilizing a finite difference formula based on gradients. LLMOD is the first conformational search method that can be applied to fully flexible, unconstrained protein structures for complex loop optimization problems. LLMOD has been tested on a particularly difficult model system, c-jun N-terminal kinase JNK3. We demonstrate that LLMOD was able to correct a P38/ERK2/HCL-based homology model that grossly misplaced the crucial glycine-rich loop in the ATP-binding site. © 2000 John Wiley & Sons, Inc. J Comput Chem 22: 21–30, 2001