Prediction of specificity-determining residues for small-molecule kinase inhibitors

<p>Abstract</p> <p>Background</p> <p>Designing small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery. A high-throughput screen for inhibitors of a given kinase will typically yield many compounds that inhibit more than one kinase. A series of chemical modifications are usually required before a compound exhibits an acceptable selectivity profile. Rationalizing the selectivity profile for a small-molecule inhibitor in terms of the specificity-determining kinase residues for that molecule can be an important step toward the goal of developing selective kinase inhibitors.</p> <p>Results</p> <p>Here we describe S-Filter, a method that combines sequence and structural information to predict specificity-determining residues for a small molecule and its kinase selectivity profile. Analysis was performed on seven selective kinase inhibitors where a structural basis for selectivity is known. S-Filter correctly predicts specificity determinants that were described by independent groups. S-Filter also predicts a number of novel specificity determinants that can often be justified by further structural comparison.</p> <p>Conclusion</p> <p>S-Filter is a valuable tool for analyzing kinase selectivity profiles. The method identifies potential specificity determinants that are not readily apparent, and provokes further investigation at the structural level.</p

Crystallizing membrane proteins using lipidic mesophases

peer-reviewedThis paper was obtained through PEER (Publishing and the Ecology of European Research) http://www.peerproject.euA detailed protocol for crystallizing membrane proteins that makes use of lipidic mesophases is described. This has variously been referred to as the lipid cubic phase or in meso method. The method has been shown to be quite general in that it has been used to solve X-ray crystallographic structures of prokaryotic and eukaryotic proteins, proteins that are monomeric, homo- and hetero-multimeric, chromophore-containing and chromophore-free, and α-helical and β-barrel proteins. Its most recent successes are the human engineered β2-adrenergic and adenosine A2A G protein-coupled receptors. Protocols are provided for preparing and characterizing the lipidic mesophase, for reconstituting the protein into the monoolein-based mesophase, for functional assay of the protein in the mesophase, and for setting up crystallizations in manual mode. Methods for harvesting micro-crystals are also described. The time required to prepare the protein-loaded mesophase and to set up a crystallization plate manually is about one hour

Assessing the ecological impacts of invasive species based on their functional responses and abundances

Invasive species management requires allocation of limited resources towards the proactive mitigation of those species that could elicit the highest ecological impacts. However, we lack predictive capacity with respect to the identities and degree of ecological impacts of invasive species. Here, we combine the relative per capita effects and relative field abundances of invader as compared to native species into a new metric, “Relative Impact Potential” (RIP), and test whether this metric can reliably predict high impact invaders. This metric tests the impact of invaders relative to the baseline impacts of natives on the broader ecological community. We first derived the functional responses (i.e. per capita effects) of two ecologically damaging invasive fish species in Europe, the Ponto-Caspian round goby (Neogobius melanostomus) and Asian topmouth gudgeon (Pseudorasbora parva), and their native trophic analogues, the bullhead (Cottus gobio; also C. bairdi) and bitterling (Rhodeus amarus), towards several prey species. This establishes the existence and relative strengths of the predator-prey relationships. Then, we derived ecologically comparable field abundance estimates of the invader and native fish from surveys and literature. This establishes the multipliers for the above per capita effects. Despite both predators having known severe detrimental field impacts, their functional responses alone were of modest predictive power in this regard; however, incorporation of their abundances relative to natives into the RIP metric gave high predictive power. We present invader/native RIP biplots that provide an intuitive visualisation of comparisons among the invasive and native species, reflecting the known broad ecological impacts of the invaders. Thus, we provide a mechanistic understanding of invasive species impacts and a predictive tool for use by practitioners, for example, in risk assessments

Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling

The Joint Evolutionary Trees (JET) method detects protein interfaces, the core residues involved in the folding process, and residues susceptible to site-directed mutagenesis and relevant to molecular recognition. The approach, based on the Evolutionary Trace (ET) method, introduces a novel way to treat evolutionary information. Families of homologous sequences are analyzed through a Gibbs-like sampling of distance trees to reduce effects of erroneous multiple alignment and impacts of weakly homologous sequences on distance tree construction. The sampling method makes sequence analysis more sensitive to functional and structural importance of individual residues by avoiding effects of the overrepresentation of highly homologous sequences and improves computational efficiency. A carefully designed clustering method is parametrized on the target structure to detect and extend patches on protein surfaces into predicted interaction sites. Clustering takes into account residues' physical-chemical properties as well as conservation. Large-scale application of JET requires the system to be adjustable for different datasets and to guarantee predictions even if the signal is low. Flexibility was achieved by a careful treatment of the number of retrieved sequences, the amino acid distance between sequences, and the selective thresholds for cluster identification. An iterative version of JET (iJET) that guarantees finding the most likely interface residues is proposed as the appropriate tool for large-scale predictions. Tests are carried out on the Huang database of 62 heterodimer, homodimer, and transient complexes and on 265 interfaces belonging to signal transduction proteins, enzymes, inhibitors, antibodies, antigens, and others. A specific set of proteins chosen for their special functional and structural properties illustrate JET behavior on a large variety of interactions covering proteins, ligands, DNA, and RNA. JET is compared at a large scale to ET and to Consurf, Rate4Site, siteFiNDER|3D, and SCORECONS on specific structures. A significant improvement in performance and computational efficiency is shown

Using structural motif descriptors for sequence-based binding site prediction

All authors are with the Biotechnological Center, TU Dresden, Tatzberg 47-51, 01307 Dresden, Germany and -- Wan Kyu Kim is with the Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USABackground: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, we aim to predict protein-protein interactions (PPI) and protein-ligand interactions (PLI) on sequence level using 3D information. To this end, we use machine learning to compile sequential segments that constitute structural features of an interaction site into one profile Hidden Markov Model descriptor. The resulting collection of descriptors can be used to screen sequence databases in order to predict functional sites. -- Results: We generate descriptors for 740 classified types of protein-protein binding sites and for more than 3,000 protein-ligand binding sites. Cross validation reveals that two thirds of the PPI descriptors are sufficiently conserved and significant enough to be used for binding site recognition. We further validate 230 PPIs that were extracted from the literature, where we additionally identify the interface residues. Finally we test ligand-binding descriptors for the case of ATP. From sequences with Swiss-Prot annotation "ATP-binding", we achieve a recall of 25% with a precision of 89%, whereas Prosite's P-loop motif recognizes an equal amount of hits at the expense of a much higher number of false positives (precision: 57%). Our method yields 771 hits with a precision of 96% that were not previously picked up by any Prosite-pattern. -- Conclusion: The automatically generated descriptors are a useful complement to known Prosite/InterPro motifs. They serve to predict protein-protein as well as protein-ligand interactions along with their binding site residues for proteins where merely sequence information is available.Institute for Cellular and Molecular [email protected]

Higher body mass index may induce asthma among adolescents with pre-asthmatic symptoms: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Limited studies have prospectively examined the role of body mass index (BMI) as a major risk factor for asthma during adolescence. This study investigates whether BMI is associated with increased risk of developing physician-diagnosed asthma during 12-month follow-up among adolescents with undiagnosed asthma-like symptoms at baseline.</p> <p>Methods</p> <p>A total of 4,052 adolescents with undiagnosed asthma-like symptoms at baseline were re-examined after a 12-month follow-up. Asthma cases were considered confirmed only after diagnosis by a physician based on the New England core and International Study of Asthma and Allergies in Childhood (ISAAC) criteria video questionnaires, and accompanying pulmonary function tests. Logistic regression analyses were used to evaluate the relationship of BMI and the risk of acquiring asthma.</p> <p>Results</p> <p>The results indicated that girls with higher BMI were at an increased risk of developing asthma during the 12-month follow-up. The odds ratios for girls developing physician-diagnosed asthma were 1.75 (95% CI = 1.18-2.61) and 1.12 (95% CI = 0.76-1.67), respectively, for overweight and obesity as compared to the normal weight reference group after adjustment for other covariates. A similar relationship was not observed for overweight and obese boys who were also significantly more active than their female counterparts.</p> <p>Conclusions</p> <p>Increased BMI exaggerates the risk of acquiring asthma in symptomatic adolescent females but not in adolescent males. Thus, gender is an important modifier of BMI-related asthma risk. Additional research will be required to determine whether the increased asthma risk results from genetic, physiological or behavioural differences.</p

H2r: Identification of evolutionary important residues by means of an entropy based analysis of multiple sequence alignments

BACKGROUND: A multiple sequence alignment (MSA) generated for a protein can be used to characterise residues by means of a statistical analysis of single columns. In addition to the examination of individual positions, the investigation of co-variation of amino acid frequencies offers insights into function and evolution of the protein and residues. RESULTS: We introduce conn(k), a novel parameter for the characterisation of individual residues. For each residue k, conn(k) is the number of most extreme signals of co-evolution. These signals were deduced from a normalised mutual information (MI) value U(k, l) computed for all pairs of residues k, l. We demonstrate that conn(k) is a more robust indicator than an individual MI-value for the prediction of residues most plausibly important for the evolution of a protein. This proposition was inferred by means of statistical methods. It was further confirmed by the analysis of several proteins. A server, which computes conn(k)-values is available at http://www-bioinf.uni-regensburg.de. CONCLUSION: The algorithms H2r, which analyses MSAs and computes conn(k)-values, characterises a specific class of residues. In contrast to strictly conserved ones, these residues possess some flexibility in the composition of side chains. However, their allocation is sensibly balanced with several other positions, as indicated by conn(k)

Perturbation of the Dimer Interface of Triosephosphate Isomerase and its Effect on Trypanosoma cruzi

Most of the enzymes of parasites have their counterpart in the host. Throughout evolution, the three-dimensional architecture of enzymes and their catalytic sites are highly conserved. Thus, identifying molecules that act exclusively on the active sites of the enzymes from parasites is a difficult task. However, it is documented that the majority of enzymes consist of various subunits, and that conservation in the interface of the subunits is lower than in the catalytic site. Indeed, we found that there are significant differences in the interface between the two subunits of triosephosphate isomerase from Homo sapiens and Trypanosoma cruzi (TcTIM), which causes Chagas disease in the American continent. In the search for agents that specifically inhibit TcTIM, we found that 2,2′-dithioaniline (DTDA) is far more effective in inactivating TcTIM than the human enzyme, and that its detrimental effect is due to perturbation of the dimer interface. Remarkably, DTDA prevented the growth of Escherichia coli cells that had TcTIM instead of their own TIM and killed T. cruzi epimastigotes in culture. Thus, this study highlights a new approach base of targeting molecular interfaces of dimers

Receptor-targeted liposome-peptide-siRNA nanoparticles represent a novel and efficient therapeutic approach to prevent conjunctival fibrosis.

There is increasing evidence that the Myocardin-related transcription factor/Serum response factor (MRTF/SRF) pathway plays a key role in fibroblast activation and that knocking down MRTF can lead to reduced scarring and fibrosis. Here, we have developed a receptor-targeted liposome-peptide-siRNA nanoparticle as a non-viral delivery system for MRTF-B siRNA in conjunctival fibrosis. Using 50 nM siRNA, the MRTF-B gene was efficiently silenced by 76% and 72% with LYR and LER nanoparticles, respectively. The silencing efficiency was low when non-targeting peptides or siRNA alone or liposome-siRNA alone were used. LYR and LER nanoparticles also showed higher silencing efficiency than PEGylated LYR-P and LER-P nanoparticles. The nanoparticles were not cytotoxic using different liposomes, targeting peptides, and 50 nM siRNA. Three-dimensional fibroblast-populated collagen matrices were also used as a functional assay to measure contraction in vitro, and showed that MRTF-B LYR nanoparticles completely blocked matrix contraction after a single transfection treatment. In conclusion, this is the first study to develop and show that receptor-targeted liposome-peptide-siRNA nanoparticles represent an efficient and safe non-viral siRNA delivery system that could be used to prevent fibrosis after glaucoma filtration surgery and other contractile scarring conditions in the eye

The Overlap of Small Molecule and Protein Binding Sites within Families of Protein Structures

Protein–protein interactions are challenging targets for modulation by small molecules. Here, we propose an approach that harnesses the increasing structural coverage of protein complexes to identify small molecules that may target protein interactions. Specifically, we identify ligand and protein binding sites that overlap upon alignment of homologous proteins. Of the 2,619 protein structure families observed to bind proteins, 1,028 also bind small molecules (250–1000 Da), and 197 exhibit a statistically significant (p<0.01) overlap between ligand and protein binding positions. These “bi-functional positions”, which bind both ligands and proteins, are particularly enriched in tyrosine and tryptophan residues, similar to “energetic hotspots” described previously, and are significantly less conserved than mono-functional and solvent exposed positions. Homology transfer identifies ligands whose binding sites overlap at least 20% of the protein interface for 35% of domain–domain and 45% of domain–peptide mediated interactions. The analysis recovered known small-molecule modulators of protein interactions as well as predicted new interaction targets based on the sequence similarity of ligand binding sites. We illustrate the predictive utility of the method by suggesting structural mechanisms for the effects of sanglifehrin A on HIV virion production, bepridil on the cellular entry of anthrax edema factor, and fusicoccin on vertebrate developmental pathways. The results, available at http://pibase.janelia.org, represent a comprehensive collection of structurally characterized modulators of protein interactions, and suggest that homologous structures are a useful resource for the rational design of interaction modulators