Biomedical subjects

Chern-Sing Goh

Publications and source records attributed to Chern-Sing Goh.

3 recordsLinked to original sources

PubMed2003

SPINE 2: a system for collaborative structural proteomics within a federated database framework.

We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at http://nesg.org. It serves as the central hub for the Northeast Structural Genomics Consortium, allowing collaborative structural proteomics to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for key bits of information related to the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The core database comprises a set of standard relational tables and a data dictionary that form an initial ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE sits at the center of a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories) and (iii) international archival resources that SPINE links to and passes on information to (e.g. TargetDB at the PDB).

Cooperative Behavior↗

PubMed2003

Molecular phylogeny and evolution of the plant-specific seven-transmembrane MLO family.

Homologues of barley Mlo encode the only family of seven-transmembrane (TM) proteins in plants. Their topology, subcellular localization, and sequence diversification are reminiscent of those of G-protein coupled receptors (GPCRs) from animals and fungi. We present a computational analysis of MLO family members based on 31 full-size and 3 partial sequences, which originate from several monocot species, the dicot Arabidopsis thaliana, and the moss Ceratodon purpureus. This enabled us to date the origin of the Mlo gene family back at least to the early stages of land plant evolution. The genomic organization of the corresponding genes supports a monophyletic origin of the Mlo gene family. Phylogenetic analysis revealed five clades, of which three contain both monocot and dicot members, while two indicate class-specific diversification. Analysis of the ratio of nonsynonymous-to-synonymous changes in coding sequences provided evidence for functional constraint on the evolution of the DNA sequences and purifying selection, which appears to be reduced in the first extracellular loop of 12 closely related orthologues. The 31 full-size sequences were examined for potential domain-specific intramolecular coevolution. This revealed evidence for concerted evolution of all three cytoplasmic domains with each other and the C-terminal cytoplasmic tail, suggesting interplay of all intracellular domains for MLO function.

Amino Acid Sequence↗

PubMed2002

Co-evolutionary analysis reveals insights into protein-protein interactions.

Protein-protein interactions play crucial roles in biological processes. Experimental methods have been developed to survey the proteome for interacting partners and some computational approaches have been developed to extend the impact of these experimental methods. Computational methods are routinely applied to newly discovered genes to infer protein function and plausible protein-protein interactions. Here, we develop and extend a quantitative method that identifies interacting proteins based upon the correlated behavior of the evolutionary histories of protein ligands and their receptors. We have studied six families of ligand-receptor pairs including: the syntaxin/Unc-18 family, the GPCR/G-alpha's, the TGF-beta/TGF-beta receptor system, the immunity/colicin domain collection from bacteria, the chemokine/chemokine receptors, and the VEGF/VEGF receptor family. For correlation scores above a defined threshold, we were able to find an average of 79% of all known binding partners. We then applied this method to find plausible binding partners for proteins with uncharacterized binding specificities in the syntaxin/Unc-18 protein and TGF-beta/TGF-beta receptor families. Analysis of the results shows that co-evolutionary analysis of interacting protein families can reduce the search space for identifying binding partners by not only finding binding partners for uncharacterized proteins but also recognizing potentially new binding partners for previously characterized proteins. We believe that correlated evolutionary histories provide a route to exploit the wealth of whole genome sequences and recent systematic proteomic results to extend the impact of these studies and focus experimental efforts to categorize physiologically or pathologically relevant protein-protein interactions.

Algorithms↗