Algorithms for the Design of Maximum Hydropathic Complementarity Molecules
ABSTRACT In this article, we address the problem of designing a string with optimal complementarity properties with respect to another given string according to a given criterion. The motivation comes from a drug design application, in which the complementarity between two sequences (proteins) is measured according to the values of the hydropathic coefficients associated with the sequence elements (amino acids). We present heuristic and exact optimization algorithms, and we report on some computational experiments on amino peptides taken from Semaphorin and human Interleukin-1β, which have already been investigated in the literature using heuristic algorithms. With our techniques, we proved the optimality of a known solution for Semaphorin-3A, and we discovered several other optimal and near-optimal solutions in a short computing time; we also found in fractions of a second an optimal solution for human interleukin-1β, whose complementary value is one order of magnitude better than previously known ones. The source code of a prototype C++ implementation of our algorithms is freely available for noncommercial use on the web. As a main result, we showed that in this context mathematical programming methods are more successful than heuristics, such as simulated annealing. Our algorithm unfolds its potential, especially when different measures could be used for scoring peptides, and is able to provide not only a single optimal solution, but a ranking of provable good ones; this ranking can then be used by biologists as a starting basis for further refinements, simulations, or in vitro experiments.
SourceAvailable from: Johannes (Hans) C. van Houwelingen[Show abstract] [Hide abstract]
ABSTRACT: We describe the tripeptide neutrophil chemoattractant N-acetyl Pro-Gly-Pro (PGP), derived from the breakdown of extracellular matrix (ECM), which shares sequence and structural homology with an important domain on alpha chemokines. PGP caused chemotaxis and production of superoxide through CXC receptors, and administration of peptide caused recruitment of neutrophils (PMNs) into lungs of control, but not CXCR2-deficient mice. PGP was generated in mouse lung after exposure to lipopolysaccharide, and in vivo and in vitro blockade of PGP with monoclonal antibody suppressed PMN responses as much as chemokine-specific monoclonal antibody. Extended PGP treatment caused alveolar enlargement and right ventricular hypertrophy in mice. PGP was detectable in substantial concentrations in a majority of bronchoalveolar lavage samples from individuals with chronic obstructive pulmonary disease, but not control individuals. Thus, PGP's activity links degradation of ECM with neutrophil recruitment in airway inflammation, and PGP may be a biomarker and therapeutic target for neutrophilic inflammatory diseases.Nature Medicine 04/2006; 12(3):317-23. DOI:10.1038/nm1361 · 28.05 Impact Factor
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ABSTRACT: The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics.BMC Bioinformatics 02/2010; 11:97. DOI:10.1186/1471-2105-11-97 · 2.67 Impact Factor
01/1979; W. H. Freeman., ISBN: 0-7167-1044-7