Basis for substrate recognition and distinction by matrix metalloproteinases.

Genomic sequencing and structural genomics produced a vast amount of sequence and structural data, creating an opportunity for structure-function analysis in silico [Radivojac P, et al. (2013) Nat Methods 10(3):221-227]. Unfortunately, only a few large experimental datasets exist to serve as benchmarks for function-related predictions. Furthermore, currently there are no reliable means to predict the extent of functional similarity among proteins. Here, we quantify structure-function relationships among three phylogenetic branches of the matrix metalloproteinase (MMP) family by comparing their cleavage efficiencies toward an extended set of phage peptide substrates that were selected from ∼ 64 million peptide sequences (i.e., a large unbiased representation of substrate space). The observed second-order rate constants [k(obs)] across the substrate space provide a distance measure of functional similarity among the MMPs. These functional distances directly correlate with MMP phylogenetic distance. There is also a remarkable and near-perfect correlation between the MMP substrate preference and sequence identity of 50-57 discontinuous residues surrounding the catalytic groove. We conclude that these residues represent the specificity-determining positions (SDPs) that allowed for the expansion of MMP proteolytic function during evolution. A transmutation of only a few selected SDPs proximal to the bound substrate peptide, and contributing the most to selectivity among the MMPs, is sufficient to enact a global change in the substrate preference of one MMP to that of another, indicating the potential for the rational and focused redesign of cleavage specificity in MMPs.

Proteins and an inflammatory network expressed in colon tumors.

The adenomatous polyposis coli (APC) protein is crucial to homeostasis of normal intestinal epithelia because it suppresses the ß-catenin/TCF pathway. Consequently, loss or mutation of the APC gene causes colorectal tumors in humans and mice. Here, we describe our use of multidimensional protein identification technology (MudPIT) to compare protein expression in colon tumors to that of adjacent healthy colon tissue from Apc(Min/+) mice. Twenty-seven proteins were found to be up-regulated in colon tumors and 25 were down-regulated. As an extension of the proteomic analysis, the differentially expressed proteins were used as "seeds" to search for coexpressed genes. This approach revealed a coexpression network of 45 genes that is up-regulated in colon tumors. Members of the network include the antibacterial peptide cathelicidin (CAMP), Toll-like receptors (TLRs), IL-8, and triggering receptor expressed on myeloid cells 1 (TREM1). The coexpression network is associated with innate immunity and inflammation, and there is significant concordance between its connectivity in humans versus mice (Friedman: p value = 0.0056). This study provides new insights into the proteins and networks that are likely to drive the onset and progression of colon cancer.

PMAP: databases for analyzing proteolytic events and pathways.

The Proteolysis MAP (PMAP, http://www.proteolysis.org) is a user-friendly website intended to aid the scientific community in reasoning about proteolytic networks and pathways. PMAP is comprised of five databases, linked together in one environment. The foundation databases, ProteaseDB and SubstrateDB, are driven by an automated annotation pipeline that generates dynamic 'Molecule Pages', rich in molecular information. PMAP also contains two community annotated databases focused on function; CutDB has information on more than 5000 proteolytic events, and ProfileDB is dedicated to information of the substrate recognition specificity of proteases. Together, the content within these four databases will ultimately feed PathwayDB, which will be comprised of known pathways whose function can be dynamically modeled in a rule-based manner, and hypothetical pathways suggested by semi-automated culling of the literature. A Protease Toolkit is also available for the analysis of proteases and proteolysis. Here, we describe how the databases of PMAP can be used to foster understanding of proteolytic pathways, and equally as significant, to reason about proteolysis.

CutDB: a proteolytic event database.

Beyond the well-known role of proteolytic machinery in protein degradation and turnover, many specialized proteases play a key role in various regulatory processes. Thousands of highly specific proteolytic events are associated with normal and pathological conditions, including bacterial and viral infections. However, the information about individual proteolytic events is dispersed over multiple publications and is not easily available for large-scale analysis. CutDB is one of the first systematic efforts to build an easily accessible collection of documented proteolytic events for natural proteins in vivo or in vitro. A CutDB entry is defined by a unique combination of these three attributes: protease, protein substrate and cleavage site. Currently, CutDB integrates 3070 proteolytic events for 470 different proteases captured from public archives (such as MEROPS and HPRD) and publications. CutDB supports various types of data searches and displays, including clickable network diagrams. Most importantly, CutDB is a community annotation resource based on a Wikipedia approach, providing a convenient user interface to input new data online. A recent contribution of 568 proteolytic events by several experts in the field of matrix metallopeptidases suggests that this approach will significantly accelerate the development of CutDB content. CutDB is publicly available at http://cutdb.burnham.org.

Immunoaffinity separation of plasma proteins by IgY microbeads: meeting the needs of proteomic sample preparation and analysis.

Separation of complex protein mixtures that have a wide dynamic range of concentration, such as plasma or serum, is a challenge for proteomic analysis. Sample preparation to remove high-abundant proteins is essential for proteomics analysis. Immunoglobulin yolk (IgY) antibodies have unique and advantageous features that enable specific protein removal to aid in the detection of low-abundant proteins and biomarker discovery. This report describes the efficiency and effectiveness of IgY microbeads in separating 12 abundant proteins from plasma with an immunoaffinity spin column or LC column. The protein separation and sample preparation process was monitored via SDS-PAGE, 2-DE, LC-MS/MS, or clinical protein assays. The data demonstrate the high specificity of the protein separation, with removal of 95-99.5% of the abundant proteins. IgY microbeads against human proteins can also selectively remove orthologous proteins of other mammals such as mouse, rat, etc. Besides the specificity and reproducibility of the IgY microbeads, the report discusses the factors that may cause potential variations in protein separation such as protein-protein interactions (known as "Interactome"), binding and washing conditions of immunoaffinity reagents, etc. A novel concept of Seppromics is introduced to address methodologies and science of protein separation in a context of proteomics.

The SARS-CoV S glycoprotein: expression and functional characterization.

We have cloned, expressed, and characterized the full-length and various soluble fragments of the SARS-CoV (Tor2 isolate) S glycoprotein. Cells expressing S fused with receptor-expressing cells at neutral pH suggesting that the recombinant glycoprotein is functional, its membrane fusogenic activity does not require other viral proteins, and that low pH is not required for triggering membrane fusion; fusion was not observed at low receptor concentrations. S and its soluble ectodomain, S(e), were not cleaved to any significant degree. They ran at about 180-200kDa in SDS gels suggesting post-translational modifications as predicted by previous computer analysis and observed for other coronaviruses. Fragments containing the N-terminal amino acid residues 17-537 and 272-537 but not 17-276 bound specifically to Vero E6 cells and purified soluble receptor, ACE2, recently identified by M. Farzan and co-workers [Nature 426 (2003) 450-454]. Together with data for inhibition of binding by antibodies developed against peptides from S, these findings suggest that the receptor-binding domain is located between amino acid residues 303 and 537. These results also confirm that ACE2 is a functional receptor for the SARS virus and may help in the elucidation of the mechanisms of SARS-CoV entry and in the development of vaccine immunogens and entry inhibitors.