On the origin of distribution patterns of motifs in biological networks

<p>Abstract</p> <p>Background</p> <p>Inventories of small subgraphs in biological networks have identified commonly-recurring patterns, called motifs. The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random.</p> <p>Results</p> <p>Our analysis of several large biological networks suggests, in contrast, that the frequencies of appearance of common subgraphs are similar in natural and corresponding random networks.</p> <p>Conclusion</p> <p>Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs. We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.</p

What determines the spectrum of protein native state structures

AbstractWe present a brief summary of the key factors underlying protein structure, as developed in the investigations of Pauling, Ramachandran, and Rose. We then outline a simplified physical model of proteins that focusses on geometry and symmetry. Although this model superficially appears unrelated to the detailed chemical descriptions commonly applied to proteins, we show that it captures the essential elements of the chemistry and provides a unified framework for understanding the common characteristics of folded proteins. We suggest that the spectrum of protein native state structures is determined by geometry and symmetry and the role of the sequence is to choose its native state structure from this predetermined menu. Proteins 2006. © 2006 Wiley‐Liss, Inc

How precise are reported protein coordinate data?

Atomic coordinates in the Worldwide Protein Data Bank (wwPDB) are generally reported to greater precision than the experimental structure determinations have actually achieved. By using information theory and data compression to study the compressibility of protein atomic coordinates, it is possible to quantify the amount of randomness in the coordinate data and thereby to determine the realistic precision of the reported coordinates. On average, the value of each Cα coordinate in a set of selected protein structures solved at a variety of resolutions is good to about 0.1 Å

Quantitative sequence-function relationships in proteins based on gene ontology

<p>Abstract</p> <p>Background</p> <p>The relationship between divergence of amino-acid sequence and divergence of function among homologous proteins is complex. The assumption that homologs share function – the basis of transfer of annotations in databases – must therefore be regarded with caution. Here, we present a quantitative study of sequence and function divergence, based on the Gene Ontology classification of function. We determined the relationship between sequence divergence and function divergence in 6828 protein families from the PFAM database. Within families there is a broad range of sequence similarity from very closely related proteins – for instance, orthologs in different mammals – to very distantly-related proteins at the limit of reliable recognition of homology.</p> <p>Results</p> <p>We correlated the divergence in sequences determined from pairwise alignments, and the divergence in function determined by path lengths in the Gene Ontology graph, taking into account the fact that many proteins have multiple functions. Our results show that, among homologous proteins, the proportion of divergent functions decreases dramatically above a threshold of sequence similarity at about 50% residue identity. For proteins with more than 50% residue identity, transfer of annotation between homologs will lead to an erroneous attribution with a totally dissimilar function in fewer than 6% of cases. This means that for very similar proteins (about 50 % identical residues) the chance of completely incorrect annotation is low; however, because of the phenomenon of recruitment, it is still non-zero.</p> <p>Conclusion</p> <p>Our results describe general features of the evolution of protein function, and serve as a guide to the reliability of annotation transfer, based on the closeness of the relationship between a new protein and its nearest annotated relative.</p

Introduction to protein architecture : the structural biology of proteins

xii, 347 p. : ill. (chiefly col.) ; 25 cm

Introduction To symmetry And Group Theory for Chemists

ix;ill.;122hal.;22c

Bioinformatics

Lesk provides an accessible and thorough introduction to a subject which is becoming a fundamental part of biological science today. The text generates an understanding of the biological background of bioinformatics