Unveiling Taenia solium kinome profile and its potential for new therapeutic targets.

Background: Helminth infections cause widespread morbidity and are a significant global disease burden. One among them is Neurocysticercosis, a central nervous system infection caused by the larvae Taenia solium, leading to epilepsy. Helminths are strong immune modulators and can survive for a long time in adverse host environments. Kinases are molecular switches and are essential to initiate/propagate signaling cascades and are detrimental to the regulation of homeostasis. They have been implicated in the progression of many diseases and are potentially lucrative drug targets.Objective: To identify kinases in T. solium proteome and prioritize them as drug targets.Methodology: A Hidden Markov Model (HMM) was used to curate and classify kinases into families based on sequence homology to model organisms followed by phylogenetic analysis of each family. To predict potential drug targets, kinases were identified based on a homologically lethal relationship to C. elegans but non-lethal to humans. Kinases thus selected were searched for matching ligands in SARFkinase and DrugBank databases.Result and conclusion: T. solium kinases make up 1.8% of its proteome, CMGC is the largest kinase family and RGC is the smallest and catalytically inactive family. We predict 23-potential kinases to be drug targets for T. solium.[Figure: see text].

A Structurally-Validated Multiple Sequence Alignment of 497 Human Protein Kinase Domains.

Studies on the structures and functions of individual kinases have been used to understand the biological properties of other kinases that do not yet have experimental structures. The key factor in accurate inference by homology is an accurate sequence alignment. We present a parsimonious, structure-based multiple sequence alignment (MSA) of 497 human protein kinase domains excluding atypical kinases. The alignment is arranged in 17 blocks of conserved regions and unaligned blocks in between that contain insertions of varying lengths present in only a subset of kinases. The aligned blocks contain well-conserved elements of secondary structure and well-known functional motifs, such as the DFG and HRD motifs. From pairwise, all-against-all alignment of 272 human kinase structures, we estimate the accuracy of our MSA to be 97%. The remaining inaccuracy comes from a few structures with shifted elements of secondary structure, and from the boundaries of aligned and unaligned regions, where compromises need to be made to encompass the majority of kinases. A new phylogeny of the protein kinase domains in the human genome based on our alignment indicates that ten kinases previously labeled as "OTHER" can be confidently placed into the CAMK group. These kinases comprise the Aurora kinases, Polo kinases, and calcium/calmodulin-dependent kinase kinases.

KinaMetrix: a web resource to investigate kinase conformations and inhibitor space.

Protein kinases are among the most explored protein drug targets. Visualization of kinase conformations is critical for understanding structure-function relationship in this family and for developing chemically unique, conformation-specific small molecule drugs. We have developed Kinformation, a random forest classifier that annotates the conformation of over 3500 protein kinase structures in the Protein Data Bank. Kinformation was trained on structural descriptors derived from functionally important motifs to automatically categorize kinases into five major conformations with pharmacological relevance. Here we present KinaMetrix (http://KinaMetrix.com), a web resource enabling researchers to investigate the protein kinase conformational space as well as a subset of kinase inhibitors that exhibit conformational specificity. KinaMetrix allows users to classify uploaded kinase structures, as well as to derive structural descriptors of protein kinases. Uploaded structures can then be compared to atomic structures of other kinases, enabling users to identify kinases that occupy a similar conformational space to their uploaded structure. Finally, KinaMetrix also serves as a repository for both small molecule substructures that are significantly associated with each conformation type, and for homology models of kinases in inactive conformations. We expect KinaMetrix to serve as a resource for researchers studying kinase structural biology or developing conformation-specific kinase inhibitors.

Determination of a Focused Mini Kinase Panel for Early Identification of Selective Kinase Inhibitors.

We analyzed an extensive data set of 3000 Janssen kinase inhibitors (spanning some 40 therapeutic projects) profiled at 414 kinases in the DiscoverX KINOME scan to better understand the necessity of using such a full kinase panel versus simply profiling one's compound at a much smaller number of kinases, or mini kinase panel (MKP), to assess its selectivity. To this end, we generated a series of MKPs over a range of sizes and of varying kinase membership using Monte Carlo simulations. By defining the kinase hit index (KHI), we quantified a compound's selectivity based on the number of kinases it hits. We find that certain combinations (rather than a random selection) of kinases can result in a much lower average error. Indeed, we identified a focused MKP with a 45.1% improvement in the average error (compared to random) that yields an overall correlation of R2 = 0.786-0.826 for the KHI compared to the full kinase panel value. Unlike using a full kinase panel, which is both time and cost restrictive, a focused MKP is amenable to the triaging of all early stage compounds. In this way, promiscuous compounds are filtered out early on, leaving the most selective compounds for lead optimization.

Coevolutionary Landscape of Kinase Family Proteins: Sequence Probabilities and Functional Motifs.

The protein kinase catalytic domain is one of the most abundant domains across all branches of life. Although kinases share a common core function of phosphoryl-transfer, they also have wide functional diversity and play varied roles in cell signaling networks, and for this reason are implicated in a number of human diseases. This functional diversity is primarily achieved through sequence variation, and uncovering the sequence-function relationships for the kinase family is a major challenge. In this study we use a statistical inference technique inspired by statistical physics, which builds a coevolutionary "Potts" Hamiltonian model of sequence variation in a protein family. We show how this model has sufficient power to predict the probability of specific subsequences in the highly diverged kinase family, which we verify by comparing the model's predictions with experimental observations in the Uniprot database. We show that the pairwise (residue-residue) interaction terms of the statistical model are necessary and sufficient to capture higher-than-pairwise mutation patterns of natural kinase sequences. We observe that previously identified functional sets of residues have much stronger correlated interaction scores than are typical.

A glimpse of structural biology through X-ray crystallography.

Since determination of the myoglobin structure in 1957, X-ray crystallography, as the anchoring tool of structural biology, has played an instrumental role in deciphering the secrets of life. Knowledge gained through X-ray crystallography has fundamentally advanced our views on cellular processes and greatly facilitated development of modern medicine. In this brief narrative, I describe my personal understanding of the evolution of structural biology through X-ray crystallography-using as examples mechanistic understanding of protein kinases and integral membrane proteins-and comment on the impact of technological development and outlook of X-ray crystallography.

Single molecule force spectroscopy on titin implicates immunoglobulin domain stability as a cardiac disease mechanism.

Titin plays crucial roles in sarcomere organization and cardiac elasticity by acting as an intrasarcomeric molecular spring. A mutation in the tenth Ig-like domain of titin's spring region is associated with arrhythmogenic cardiomyopathy, a disease characterized by ventricular arrhythmias leading to cardiac arrest and sudden death. Titin is the first sarcomeric protein linked to arrhythmogenic cardiomyopathy. To characterize the disease mechanism, we have used atomic force microscopy to directly measure the effects that the disease-linked point mutation (T16I) has on the mechanical and kinetic stability of Ig10 at the single molecule level. The mutation decreases the force needed to unfold Ig10 and increases its rate of unfolding 4-fold. We also found that T16I Ig10 is more prone to degradation, presumably due to compromised local protein structure. Overall, the disease-linked mutation weakens the structural integrity of titin's Ig10 domain and suggests an Ig domain disease mechanism.

Integrating ligand-based and protein-centric virtual screening of kinase inhibitors using ensembles of multiple protein kinase genes and conformations.

The rapidly growing wealth of structural and functional information about kinase genes and kinase inhibitors that is fueled by a significant therapeutic role of this protein family provides a significant impetus for development of targeted computational screening approaches. In this work, we explore an ensemble-based, protein-centric approach that allows for simultaneous virtual ligand screening against multiple kinase genes and multiple kinase receptor conformations. We systematically analyze and compare the results of ligand-based and protein-centric screening approaches using both single-receptor and ensemble-based docking protocols. A panel of protein kinase targets that includes ABL, EGFR, P38, CDK2, TK, and VEGFR2 kinases is used in this comparative analysis. By applying various performance metrics we have shown that ligand-centric shape matching can provide an effective enrichment of active compounds outperforming single-receptor docking screening. However, ligand-based approaches can be highly sensitive to the choice of inhibitor queries. Employment of multiple inhibitor queries combined with parallel selection ranking criteria can improve the performance and efficiency of ligand-based virtual screening. We also demonstrated that replica-exchange Monte Carlo docking with kinome-based ensembles of multiple crystal structures can provide a superior early enrichment on the kinase targets. The central finding of this study is that incorporation of the template-based structural information about kinase inhibitors and protein kinase structures in diverse functional states can significantly enhance the overall performance and robustness of both ligand and protein-centric screening strategies. The results of this study may be useful in virtual screening of kinase inhibitors potentially offering a beneficial spectrum of therapeutic activities across multiple disease states.

Price to be paid for two-metal catalysis: magnesium ions that accelerate chemistry unavoidably limit product release from a protein kinase.

Incorporation of divalent metal ions into an active site is a fundamental catalytic tool used by diverse enzymes. Divalent cations are used by protein kinases to both stabilize ATP binding and accelerate chemistry. Kinetic analysis establishes that Cyclin-dependent kinase 2 (CDK2) requires simultaneous binding of two Mg(2+) ions for catalysis of phosphoryl transfer. This tool, however, comes with a price: the rate-acceleration effects are opposed by an unavoidable rate-limiting consequence of the use of two Mg(2+) ions by CDK2. The essential metal ions stabilize ADP product binding and limit the overall rate of the reaction. We demonstrate that product release is rate limiting for activated CDK2 and evaluate the effects of the two catalytically essential Mg(2+) ions on the stability of the ADP product within the active site. We present two new crystal structures of CDK2 bound to ADP showing how the phosphate groups can be coordinated by either one or two Mg(2+) ions, with the occupancy of one site in a weaker equilibrium. Molecular dynamics simulations indicate that ADP phosphate mobility is more restricted when ADP is coordinated by two Mg(2+) ions compared to one. The structural similarity between the rigid ADP·2Mg product and the cooperatively assembled transition state provides a mechanistic rational for the rate-limiting ADP release that is observed. We demonstrate that although the simultaneous binding of two Mg(2+) ions is essential for efficient phosphoryl transfer, the presence of both Mg(2+) ions in the active site also cooperatively increases ADP affinity and opposes its release. Evolution of protein kinases must have involved careful tuning of the affinity for the second Mg(2+) ion in order to balance the needs to stabilize the chemical transition state and allow timely product release. The link between Mg(2+) site affinity and activity presents a chemical handle that may be used by regulatory factors as well as explain some mutational effects.

Rapid determination of multiple linear kinase substrate motifs by mass spectrometry.

Kinase-substrate recognition depends on the chemical properties of the phosphorylatable residue as well as the surrounding linear sequence motif. Detailed knowledge of these characteristics increases the confidence of linking identified phosphorylation sites to kinases, predicting phosphorylation sites, and designing optimal peptide substrates. Here, we present a mass spectrometry-based approach for determining linear kinase substrate motifs by elaborating the positional and chemical preference of the kinase for a phosphorylatable residue using libraries of naturally-occurring peptides that are amenable to peptide identification by commonly used proteomics platforms. We applied this approach to a structurally and functionally diverse set of purified kinases, which recapitulated their previously described substrate motifs and discovered additional ones, including preferences of certain kinases for phosphorylatable residues adjacent to peptide termini. Furthermore, we identify specific and distinguishable motif elements for the four members of the polo-like kinase (Plk) family and verify members of these motif elements for Plk1 in vivo.

Large-scale analysis of phosphorylation site occupancy in eukaryotic proteins.

Many recent high throughput technologies have enabled large-scale discoveries of new phosphorylation sites and phosphoproteins. Although they have provided a number of insights into protein phosphorylation and the related processes, an inclusive analysis on the nature of phosphorylated sites in proteins is currently lacking. We have therefore analyzed the occurrence and occupancy of phosphorylated sites (~100,281) in a large set of eukaryotic proteins (~22,995). Phosphorylation probability was found to be much higher in both the termini of protein sequences and this is much pronounced in transmembrane proteins. A large proportion (51.3%) of occupied sites had a nearby phosphorylation within a distance of 10 amino acids; however, this proportion is very high compared to the expected one (16.9%). The distribution of phosphorylated sites in proteins showed a strong deviation from the expected maximum randomness. An analysis of phosphorylation motifs indicated that just 40 motifs and a much lower number of associated kinases might account for nearly 50% of the known phosphorylations in eukaryotic proteins. Our results provide a broad picture of the phosphorylation sites in eukaryotic proteins.

A conditional gating mechanism assures the integrity of the molecular force-sensor titin kinase.

As more and more recent investigations point out, force plays an important role in cellular regulation mechanisms. Biological responses to mechanical stress are often based on force-induced conformational changes of single molecules. The force sensor, titin kinase, is involved in a signaling complex that regulates protein turnover and transcriptional adaptation in striated muscle. The structural architecture of such a force sensor determines its response to force and must assure both activity and mechanical integrity, which are prerequisites for its function. Here, we use single-molecule force-clamp spectroscopy to show that titin kinase is organized in such a way that the regulatory domains have to unfold before secondary structure elements that determine the overall fold and catalytic function. The stepwise unfolding over many barriers with a topologically determined sequence assures that the protein can react to force by conformational changes while maintaining its structural integrity.

Eukaryotic protein kinases (ePKs) of the helminth parasite Schistosoma mansoni.

BACKGROUND: Schistosomiasis remains an important parasitic disease and a major economic problem in many countries. The Schistosoma mansoni genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the S. mansoni predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets. RESULTS: We have identified 252 ePKs, which corresponds to 1.9% of the S. mansoni predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that S. mansoni has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in S. mansoni or belong to an expanded family in this parasite. Only 16 S. mansoni ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite. CONCLUSIONS: Our approach has improved the functional annotation of 40% of S. mansoni ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of S. mansoni in response to diverse environments during the parasite development, vector interaction, and host infection.

Computational approach to de novo discovery of fragment binding for novel protein states.

In silico fragment-based drug discovery has become an integral component of the new fragment-based approach that has evolved over the past decade. Protein structure of high quality is essential in carrying out computational designs, and protein flexibility has been shown to impact prospective designs or docking experiments. Here we introduce methodology to calculate protein normal modes and protein molecular dynamics in torsion space which enable the development of multiple protein states to address the natural flexibility of proteins. We also present two fragment-based sampling methods, grand canonical Monte Carlo and systematic sampling, which are used to study protein-fragment interactions by generating fragment ensembles and we discuss the process by which these ensembles are linked to design ligands.

Building interacting partner predictors using co-varying residue pairs between histidine kinase and response regulator pairs of 48 bacterial two-component systems.

The two-component system (TCS) is a signal transduction system that involves a histidine kinase (HK) and a response regulator (RR). Although up to hundreds of TCSs may operate in parallel in a bacterial cell, the high-fidelity of a TCS signaling is well maintained, minimizing irrelevant crosstalk between TCSs. When a HK gene and a RR gene in a given TCS system exist in neighboring positions, it is almost certain that their protein products (i.e., HK and RR) are interacting partners. However, large bacterial genomes often have multiple HK genes and/or cognate RR genes that are not neighboring positions. In many partially assembled genomes, some HK genes and RR genes belong to different contigs. In these cases, it is not clear which HK(s) and RR(s) interact. By combining information-theoretic and graph-theoretic approaches, we developed a computational method identifying co-evolving residue pairs between HKs and cognate RRs and predicting the interacting HK:RR pairs for each TCS. In addition, we built a TCSppWWW webserver (http://compath.org/platcom/tcs) that takes query sequences of pairing candidates and predicts their HK:RR pairing using precomputed models. The current release of TCSppWWW provides predictors for 48 TCSs using over 20,000 protein sequences from about 900 bacterial genomes. Three different types of predictors using Random Forest, RBF Network, and Naïve Bayes are provided. Once a set of HK and RR candidate sequences are submitted, TCSppWWW aligns query sequences to the precomputed multiple sequence alignment of HK:RR pairs, extracts co-evolving column positions, then returns prediction results with prediction margin and additional information.

Design of targeted libraries against the human Chk1 kinase using PGVL Hub.

PGVL Hub is a Pfizer internal desktop tool for chemical library and singleton design. In this chapter, we give a short introduction to PGVL Hub, the core workflow it supports, and the rich design capabilities it provides. By re-creating two legacy targeted libraries against the human checkpoint kinase 1 (Chk1) as a showcase, we illustrate how PGVL Hub could be used to help library designers carry out the steps in library design and realize design objectives such as SAR expansion and improvement in both kinase selectivity and compound aqueous solubility. Finally we share several tips about library design and usage of PGVL Hub.

Dynamic strength of titin's Z-disk end.

Titin is a giant filamentous protein traversing the half sarcomere of striated muscle with putative functions as diverse as providing structural template, generating elastic response, and sensing and relaying mechanical information. The Z-disk region of titin, which corresponds to the N-terminal end of the molecule, has been thought to be a hot spot for mechanosensing while also serving as anchorage for its sarcomeric attachment. Understanding the mechanics of titin's Z-disk region, particularly under the effect of binding proteins, is of great interest. Here we briefly review recent findings on the structure, molecular associations, and mechanics of titin's Z-disk region. In addition, we report experimental results on the dynamic strength of titin's Z1Z2 domains measured by nanomechanical manipulation of the chemical dimer of a recombinant protein fragment.

Advances and Progress in Drug Design - SMi's ninth annual meeting.

SMi's Advances and Progress in Drug Design, held in London, included topics covering new developments in the field of drug design. This conference report highlights selected presentations on targeting GPCRs and kinases, virtual screening for hit and lead identification, and the ChEMBL database for drug discovery. One investigational drug, losmapimod (GlaxoSmithKline plc), was discussed.

Markov random fields reveal an N-terminal double beta-propeller motif as part of a bacterial hybrid two-component sensor system.

The recent explosion in newly sequenced bacterial genomes is outpacing the capacity of researchers to try to assign functional annotation to all the new proteins. Hence, computational methods that can help predict structural motifs provide increasingly important clues in helping to determine how these proteins might function. We introduce a Markov Random Field approach tailored for recognizing proteins that fold into mainly beta-structural motifs, and apply it to build recognizers for the beta-propeller shapes. As an application, we identify a potential class of hybrid two-component sensor proteins, that we predict contain a double-propeller domain.

Bisubstrate inhibitors of protein kinases: from principle to practical applications.

Bisubstrate inhibitors consist of two conjugated fragments, each targeted to a different binding site of a bisubstrate enzyme. The design of bisubstrate inhibitors presupposes the formation of the ternary complex in the course of the catalyzed reaction. The principle advantage of bisubstrate inhibitors is their ability to generate more interactions with the target enzyme that could result in improved affinity and selectivity of the conjugates, when compared with single-site inhibitors. Among phosphotransferases, the approach was first successfully used for adenylate kinase in 1973. Since then, several types of bisubstrate inhibitors have been developed for protein kinases, including conjugates of peptides with nucleotides, adenosine derivatives and potent ATP-competitive inhibitors. Earlier bisubstrate inhibitors had pharmacokinetic qualities that were unsuitable for cellular experiments and hence were mostly used for in vitro studies. The recently constructed conjugates of adenosine derivatives and D-arginine-rich peptides (ARCs) possess high kinase affinity, high biological and chemical stability and good cell plasma membrane penetrative properties that enable their application in the regulation of cellular protein phosphorylation balances in cell and tissue experiments.