Discovery of novel biomarkers and phenotypes by semantic technologies.

Biomarkers and target-specific phenotypes are important to targeted drug design and individualized medicine, thus constituting an important aspect of modern pharmaceutical research and development. More and more, the discovery of relevant biomarkers is aided by in silico techniques based on applying data mining and computational chemistry on large molecular databases. However, there is an even larger source of valuable information available that can potentially be tapped for such discoveries: repositories constituted by research documents

Interaction of the globular domain of human C1q with Salmonella typhimurium lipopolysaccharide

Gram-negative bacteria can bind complement protein C1q in an antibody-independent manner and activate classical pathway via their lipopolysaccharides (LPS). Earlier studies have implicated the collagen-like region of human C1q in binding LPS. In recent years, a number of C1q target molecules, previously considered to interact with collagen-like region of C1q, have been shown to bind via the globular domain (gC1q). Here we report, using recombinant forms of the globular head regions of C1q A, B and C chains, that LPS derived from Salmonella typhimurium interact specifically with the B-chain of the gC1q domain in a calcium-dependent manner. LPS and IgG-binding sites on the gC1q domain appear to be overlapping and this interaction can be inhibited by a synthetic C1q inhibitor, suggesting common interacting mechanisms

A Systems Biology Strategy for Predicting Similarities and Differences of Drug Effects: Evidence for Drug-specific Modulation of Inflammation in Atherosclerosis

Vascular Surger