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

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 tha t is only referenced implicitly, through its product with a series of vecto rs. The Hessian x vector product is calculated utilizing a finite differenc e formula based on gradients. LLMOD is the first conformational search meth od that can be applied to fully flexible, unconstrained protein structures for complex loop optimization problems. LLMOD has been tested on a particul arly difficult model system, c-jun N-terminal kinase JNK3. We demonstrate t hat LLMOD was able to correct a P38/ERK2/HCL-based homology model that gros sly misplaced the crucial glycine-rich loop in the ATP-binding site. (C) 20 00 John Wiley & Sons, Inc.