Mapping small molecule binding data to structural domains.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. RESULTS: In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. CONCLUSIONS: Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes following the Pfam-A specifications of protein domains. This is valuable for data-focused approaches in drug discovery, for example when extrapolating potential targets of a small molecule with known activity against one or few targets, or in the assessment of a potential target for drug discovery or screening studies

Integration and analysis of protein evolutionary relationships and small molecule bioactivity data

RT-158623Interactions of small organic molecules and proteins have been studied extensively in the search of therapeutic drugs. Historically, the interaction partners have been attributed to separate scientific disciplines: small organic molecules to the domain of chemistry, proteins to the domain of biology. Likewise, chemical and biological data have been stored and maintained separately. The aim of my thesis was to integrate the ChEMBL database, a public repository of small molecule bioactivity measurements, with resources of protein evolutionary relationships, and exploit these new links to further our understanding of small molecule bioactivity. In order to link biological assays via the evolutionary relationships of their protein targets, I established a mapping of small molecule binding to specific structural protein domains - the fundamental building blocks of protein architecture and evolution. By mapping small molecule binding to protein domains, I was able to examine links between the properties of small molecules and the evolutionary units that mediate their binding. I used domain definitions from Pfam, a database of protein domains derived from conserved sequence blocks. The mapping is now an integral part of the ChEMBL database and can be used to limit sequence-based queries to sequence partitions that are relevant to small molecule binding. Further, I integrated information from the homology resource EnsemblCompara Genetrees with bioactivity data from ChEMBL to examine the conservation of small molecule potency between homologous proteins within and across species. Potency differences between related proteins are a useful indicator of small molecule specificity. Specificity is an early milestone for most drug discovery projects as it allows for the manipulation of a desired process in a targeted manner, with side effects reduced to a minimum. I examined pairs of closely related human proteins and found that potency differences were overall greater than the estimated background noise. Using the outlined integration approach in a cross-species comparison, I also observed that potency differences between pairs of related proteins in human and rat were overall no greater than the background noise. This is relevant to the use of model organisms for drug discovery, which relies on extrapolation from a measured response in one species to a therapeutic effect in humans. Taken together I have integrated small molecule bioactivity and protein evolutionary data from two resources, Pfam and EnsemblCompara Genetrees. This has provided a framework for studying small molecule binding in the context of protein evolution

Analysis of Binding Site Hot Spots on the Surface of Ras GTPase

We have recently discovered an allosteric switch in Ras, bringing an additional level of complexity to this GTPase whose mutants are involved in nearly 30% of cancers. Upon activation of the allosteric switch, there is a shift in helix 3/loop 7 associated with a disorder to order transition in the active site. Here, we use a combination of multiple solvent crystal structures and computational solvent mapping (FTMap) to determine binding site hot spots in the “off” and “on” allosteric states of the GTP-bound form of H-Ras. Thirteen sites are revealed, expanding possible target sites for ligand binding well beyond the active site. Comparison of FTMaps for the H and K isoforms reveals essentially identical hot spots. Furthermore, using NMR measurements of spin relaxation, we determined that K-Ras exhibits global conformational dynamics very similar to those we previously reported for H-Ras. We thus hypothesize that the global conformational rearrangement serves as a mechanism for allosteric coupling between the effector interface and remote hot spots in all Ras isoforms. At least with respect to the binding sites involving the G domain, H-Ras is an excellent model for K-Ras and probably N-Ras as well. Ras has so far been elusive as a target for drug design. The present work identifies various unexplored hot spots throughout the entire surface of Ras, extending the focus from the disordered active site to well-ordered locations that should be easier to target

The complement binding-like domains of the murine homing receptor facilitate lectin activity.

The leukocyte homing receptor (HR), the endothelial leukocyte adhesion molecule, and gmp140/platelet activation-dependent granule membrane protein are members of a family of adhesion molecules, termed the lectin cell adhesion molecules (LEC-CAMS) which are unified by a multi-domain structure containing a lectin motif, an epidermal growth factor-like (egf) motif, and variable numbers of a complement binding-like (CB) motif. Previous data have indicated a predominant role for the lectin motif in cell adhesion directed by the LEC-CAMS, although the egf-like domain of the HR may also play a potential role in cell binding. While the role(s) of the CB domains in the LEC-CAMS is currently not understood, they have been hypothesized to act as rigid spacers or stalks for lectin and perhaps, egf domain presentation. In this paper, we analyze the functional characteristics of murine HR-IgG chimeras containing the lectin, lectin plus egf, and lectin plus egf plus CB domains. The Mel 14 mAb, an adhesion blocking antibody which recognizes a conformational determinant in the N-terminus of the HR lectin domain, shows a significantly decreased affinity for a HR construct which lacks the CB motifs, consistent with the possibility that the CB domains are involved with lectin domain structure. In agreement with this conjecture, HR mutants lacking the CB domains show a profound decrease in lectin-specific interaction with the carbohydrate polyphosphomannan ester, suggesting that the changes in Mel 14 affinity for the lectin domain are reflected in lectin functionality. Various assays investigating the interactions between the HR deletion mutants and the peripheral lymph node high endothelium, including cell blocking, immunohistochemical staining, and radioactively labeled ligand binding, all showed that removal of the CB domains results in a lack of HR adhesive function. These results imply that the CB domains of the HR, and, by analogy, the other members of the LEC-CAM family, may play important structural roles involving induction of lectin domain conformation and resultant functionality

The Interplay between Chemistry and Mechanics in the Transduction of a Mechanical Signal into a Biochemical Function

There are many processes in biology in which mechanical forces are generated. Force-bearing networks can transduce locally developed mechanical signals very extensively over different parts of the cell or tissues. In this article we conduct an overview of this kind of mechanical transduction, focusing in particular on the multiple layers of complexity displayed by the mechanisms that control and trigger the conversion of a mechanical signal into a biochemical function. Single molecule methodologies, through their capability to introduce the force in studies of biological processes in which mechanical stresses are developed, are unveiling subtle intertwining mechanisms between chemistry and mechanics and in particular are revealing how chemistry can control mechanics. The possibility that chemistry interplays with mechanics should be always considered in biochemical studies.Comment: 50 pages, 18 figure

Structural analysis of the adenovirus type 2 E3/19K protein using mutagenesis and a panel of conformation-sensitive monoclonal antibodies

The E3/19K protein of human adenovirus type 2 (Ad2) was the first viral protein shown to interfere with antigen presentation. This 25 kDa transmembrane glycoprotein binds to major histocompatibility complex (MHC) class I molecules in the endoplasmic reticulum (ER), thereby preventing transport of newly synthesized peptide–MHC complexes to the cell surface and consequently T cell recognition. Recent data suggest that E3/19K also sequesters MHC class I like ligands intracellularly to suppress natural killer (NK) cell recognition. While the mechanism of ER retention is well understood, the structure of E3/19K remains elusive. To further dissect the structural and antigenic topography of E3/19K we carried out site-directed mutagenesis and raised monoclonal antibodies (mAbs) against a recombinant version of Ad2 E3/19K comprising the lumenal domain followed by a C-terminal histidine tag. Using peptide scanning, the epitopes of three mAbs were mapped to different regions of the lumenal domain, comprising amino acids 3–13, 15–21 and 41–45, respectively. Interestingly, mAb 3F4 reacted only weakly with wild-type E3/19K, but showed drastically increased binding to mutant E3/19K molecules, e.g. those with disrupted disulfide bonds, suggesting that 3F4 can sense unfolding of the protein. MAb 10A2 binds to an epitope apparently buried within E3/19K while that of 3A9 is exposed. Secondary structure prediction suggests that the lumenal domain contains six β-strands and an α-helix adjacent to the transmembrane domain. Interestingly, all mAbs bind to non-structured loops. Using a large panel of E3/19K mutants the structural alterations of the mutations were determined. With this knowledge the panel of mAbs will be valuable tools to further dissect structure/function relationships of E3/19K regarding down regulation of MHC class I and MHC class I like molecules and its effect on both T cell and NK cell recognition

Using molecular mechanics to predict bulk material properties of fibronectin fibers

The structural proteins of the extracellular matrix (ECM) form fibers with finely tuned mechanical properties matched to the time scales of cell traction forces. Several proteins such as fibronectin (Fn) and fibrin undergo molecular conformational changes that extend the proteins and are believed to be a major contributor to the extensibility of bulk fibers. The dynamics of these conformational changes have been thoroughly explored since the advent of single molecule force spectroscopy and molecular dynamics simulations but remarkably, these data have not been rigorously applied to the understanding of the time dependent mechanics of bulk ECM fibers. Using measurements of protein density within fibers, we have examined the influence of dynamic molecular conformational changes and the intermolecular arrangement of Fn within fibers on the bulk mechanical properties of Fn fibers. Fibers were simulated as molecular strands with architectures that promote either equal or disparate molecular loading under conditions of constant extension rate. Measurements of protein concentration within micron scale fibers using deep ultraviolet transmission microscopy allowed the simulations to be scaled appropriately for comparison to in vitro measurements of fiber mechanics as well as providing estimates of fiber porosity and water content, suggesting Fn fibers are approximately 75% solute. Comparing the properties predicted by single molecule measurements to in vitro measurements of Fn fibers showed that domain unfolding is sufficient to predict the high extensibility and nonlinear stiffness of Fn fibers with surprising accuracy, with disparately loaded fibers providing the best fit to experiment. This work shows the promise of this microstructural modeling approach for understanding Fn fiber properties, which is generally applicable to other ECM fibers, and could be further expanded to tissue scale by incorporating these simulated fibers into three dimensional network models