this paper is concerned, have been derived in several ways. Levitt (1976) generated potentials of mean force by averaging energies over all relative orientations of pairs of side-chains. More recently these kinds of energy functions have been derived as potentials of mean force from the ever-growing database of known protein structures (see the references in Sippl, 1995). Huang et al. (1995) have devised a potential which does not explicitly use the database of known structures; they use only a simple classification of different residues as hydrophobic or hydrophilic, reminiscent of the theoretical energy models of Dill et al. (reviewed by Dill et al., 1995; Yue & Dill, 1995). Maiorov & Crippen (1992) generated a potential function by an optimization procedure which sought to maximize the difference in energy between correct and incorrect protein conformations.

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this paper, we examine the relationship between the complexity and

The structural comparison of proteins has become increasingly important as a means to identify protein motifs and fold families. In this paper we present a new algorithm for the comparison of proteins based on a hierarchy of structural representations, from the secondary structure level to the atomic level. Our technique represents a-helices and b-strands as vectors and uses a set of seven scoring functions to compare pairs of vectors from different proteins. The scores obtained are used in a dynamic programming algorithm that finds the best local alignment of the two sets of vectors. The second step in our algorithm is based on the atomic coordinates of the protein structures and improves the initial vector alignment by iteratively minimizing the RMSD between pairs of nearest atoms from the two proteins. We refine the final alignment by determining a core of well aligned atoms and minimizing the RMSD of this core. In a comparison of our method to Holm and Sander's DA...

We present an automatic method for docking organic ligands into protein Center for Information binding sites. The method can be used in the design process of specific Technology (GMD), Institute protein ligands. It combines an appropriate model of the physico-chemical for Algorithms and Scientific properties of the docked molecules with efficient methods for sampling the Computing (SCAI), Schloß conformational space of the ligand. If the ligand is flexible, it can adopt

The problem of aligning, or establishing a correspondence between, residues of two protein Abbreviations used: ROC, receiver operating

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ABSTRACT Multiple sequence alignment is one of the cornerstones of modern molecular biology. It is used to identify conserved motifs, to determine protein domains, in 2D/3D structure prediction by homology and in evolutionary studies. Recently, high-throughput technologies such as genome sequencing and structural proteomics have lead to an explosion in the amount of sequence and structure information available. In response, several new multiple alignment methods have been developed that improve both the efficiency and the quality of protein alignments. Consequently, the benchmarks used to evaluate and compare these methods must also evolve. We present here the latest release of the most widely used multiple alignment benchmark, BAliBASE, which provides high quality, manually refined, reference alignments based on 3D structural superpositions. Version 3.0 of BAliBASE includes new, more challenging test cases, representing the real problems encountered when aligning large sets of complex sequences. Using a novel, semiautomatic update protocol, the number of protein families in the benchmark has been increased and representative test cases are now available that cover most of the protein fold space. The total number of proteins in BAliBASE has also been significantly increased from 1444 to 6255 sequences. In addition, full-length sequences are now provided for all test cases, which represent difficult cases for both global and local alignment programs. Finally, the BAliBASE Web site

We show that calculating contact map overlap (a measure of similarity of protein structures) is NPhard, but can be solved in polynomial time for several interesting and relevant special cases. We identify an important special case of this problem corresponding to self-avoiding walks, and prove a decomposition theorem and a corollary approximation result for this special case. These are the rst approximation algorithms with guaranteed error bounds, and NPcompleteness results in the literature in the area of protein structure alignment/fold recognition for measures of structure similarity of practical interest. A

. This paper discusses the mathematical formulation of and solution attempts for the so-called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possible pathways to folding and unfolding, including the stability of the folded protein. From a mathematical point of view, there are several main sides to the static problem: -- the selection of an appropriate potential energy function; -- the parameter identification by fitting to experimental data; and -- the global optimization of the potential. The dynamic problem entails, in addition, the solution of (because of multiple time scales very stiff) ordinary or stochastic differential equations (molecular dynamics simulation), or (in case of constrained molecular dynamics) of differential-algebraic equations. A theme connecting the static and dynamic aspect is the determination and formation of...