Inhibitor binding to mutants of protein kinase A with GGGxxG and GxGxxA glycine-rich loop motifs.

The conserved GxGxxG motif of protein kinases forms a beta turn at the tip of the flexible glycine-rich loop and creates much of the ATP pocket binding surface. Notable exceptions to this sequence include GGGxxG in ABL kinase and GxGxxA in protein kinase C isoforms. We constructed the corresponding mutants of PKA, T51G, and G55A, and tested quinazoline inhibitors that were designed to bind via glycine-rich loop interactions, testing also staurosporine for comparison. The quinazoline inhibitors have significantly reduced binding strengths in both mutants. In striking contrast to these results, the binding of the "pan-kinome" inhibitor staurosporine is strengthened in the mutants. Surface plasmon resonance (SPR) shows that the tightened binding of staurosporine arises from increased kon rates, changes not offset by more moderately increased koff rates. The SPR results fit best to a two step binding process for staurosporine in wild type PKA, but not the mutants.

Assessing protein kinase target similarity: Comparing sequence, structure, and cheminformatics approaches.

In just over two decades, structure based protein kinase inhibitor discovery has grown from trial and error approaches, using individual target structures, to structure and data driven approaches that may aim to optimize inhibition properties across several targets. This is increasingly enabled by the growing availability of potent compounds and kinome-wide binding data. Assessing the prospects for adapting known compounds to new therapeutic uses is thus a key priority for current drug discovery efforts. Tools that can successfully link the diverse information regarding target sequence, structure, and ligand binding properties now accompany a transformation of protein kinase inhibitor research, away from single, block-buster drug models, and toward "personalized medicine" with niche applications and highly specialized research groups. Major hurdles for the transformation to data driven drug discovery include mismatches in data types, and disparities of methods and molecules used; at the core remains the problem that ligand binding energies cannot be predicted precisely from individual structures. However, there is a growing body of experimental data for increasingly successful focussing of efforts: focussed chemical libraries, drug repurposing, polypharmacological design, to name a few. Protein kinase target similarity is easily quantified by sequence, and its relevance to ligand design includes broad classification by key binding sites, evaluation of resistance mutations, and the use of surrogate proteins. Although structural evaluation offers more information, the flexibility of protein kinases, and differences between the crystal and physiological environments may make the use of crystal structures misleading when structures are considered individually. Cheminformatics may enable the "calibration" of sequence and crystal structure information, with statistical methods able to identify key correlates to activity but also here, "the devil is in the details." Examples from specific repurposing and polypharmacology applications illustrate these points. This article is part of a Special Issue entitled: Inhibitors of Protein Kinases.

Structural origins of AGC protein kinase inhibitor selectivities: PKA as a drug discovery tool.

The era of structure-based protein kinase inhibitor design began in the early 1990s with the determination of crystal structures of protein kinase A (PKA, or cyclic AMP-dependent kinase). Although many other protein kinases have since been extensively characterized, PKA remains a prototype for studies of protein kinase active conformations. It serves well as a model for the structural properties of AGC subfamily protein kinases, clarifying inhibitor selectivity profiles. Its reliable expression, constitutive activity, simple domain structure, and reproducible crystallizability have also made it a useful surrogate for the discovery of inhibitors of both established and emerging AGC kinase targets.

Protein kinase inhibition of clinically important staurosporine analogues.

The isolation in 1977 of the microbial alkaloid staurosporine inaugurated research into several distinct series of related natural and synthetic compounds. This has especially included research into applications as anticancer drugs, beginning with the observation of low nanomolar inhibition of protein kinases. At present, several staurosporine cognates are in advanced clinical trials as anticancer agents, with the potential to join the 10 other protein kinase inhibitors now approved for clinical use. Staurosporine is a broadly selective and potent protein kinase inhibitor, with submicromolar binding to the vast majority of the protein kinases tested, and binding most of them more tightly than 100 nM. Crystal structures have shown the extended buried surface area interactions between the protein kinase adenine binding site and the extended aromatic plane of the inhibitor, together with protein-saccharide interactions in the ribose binding site. Together with structures of closely related analogues, there are now some 70 X-ray crystal structures in the Protein Data Bank that enable analysis of target binding properties of the clinical compounds. In this manuscript we review the discovery of these compounds, revisit crystal structures and review the observed interactions. These support the interpretation of kinase selectivity profiles of staurosporine and its analogues, including midostaurin (PKC412), for which a co-crystal structure is not yet available. Further, the mix of purely natural, biosynthetically and chemically modified compounds described here offer insights into prospects and strategies for drug discovery via bioprospecting.

1,2,3-triazole analogs of combretastatin A-4 as potential microtubule-binding agents.

A series of cis-restricted 1,4- and 1,5-disubstituted 1,2,3-triazole analogs of combretastatin A-4 (1) have been prepared. Cytotoxicity and tubulin inhibition studies showed that 2-methoxy-5-((5-(3,4,5-trimethoxyphenyl)-1H-1,2,3-triazol-1-yl)methyl)aniline (5e) and 2-methoxy-5-(1-(3,4,5-trimethoxybenzyl)-1H-1,2,3-triazol-5-yl)aniline (6e) were two of the most active compounds. Molecular modeling studies revealed that the N-2 and N-3 atoms in the triazole rings in 5e and 6e did not form hydrogen bonds with the amino acids in the anticipated pharmacophore.

Theoretical calculations of the catalytic triad in short-chain alcohol dehydrogenases/reductases.

Three highly conserved active site residues (Ser, Tyr, and Lys) of the family of short-chain alcohol dehydrogenases/reductases (SDRs) were demonstrated to be essential for catalytic activity and have been denoted the catalytic triad of SDRs. In this study computational methods were adopted to study the ionization properties of these amino acids in SDRs from Drosophila melanogaster and Drosophila lebanonensis. Three enzyme models, with different ionization scenarios of the catalytic triad that might be possible when inhibitors bind to the enzyme cofactor complex, were constructed. The binding of the two alcohol competitive inhibitors were studied using automatic docking by the Internal Coordinate Mechanics program, molecular dynamic (MD) simulations with the AMBER program package, calculation of the free energy of ligand binding by the linear interaction energy method, and the hydropathic interactions force field. The calculations indicated that deprotonated Tyr acts as a strong base in the binary enzyme-NAD(+) complex. Molecular dynamic simulations for 5 ns confirmed that deprotonated Tyr is essential for anchoring and orientating the inhibitors at the active site, which might be a general trend for the family of SDRs. The findings here have implications for the development of therapeutically important SDR inhibitors.

Are fish oil omega-3 long-chain fatty acids and their derivatives peroxisome proliferator-activated receptor agonists?

BACKGROUND: Peroxisome proliferator-activated receptors (PPARalpha, PPARgamma, and PPARdelta) are physiological sensors for glucose and lipid homeostasis. They are also the targets of synthetic drugs; such as fibrates as PPARalpha agonists which lower lipid level, and glitazones as PPARgamma agonists which lower glucose level. As diabetes and metabolic diseases are often associated with high blood glucose and lipid levels, drugs that activate both PPARalpha/gamma would be a logical approach. But synthetically developed PPARalpha/gamma dual agonists and glitazones are showing side effects such as weight gain and edema. Therefore, natural compounds and their close derivatives are focused as future drugs against metabolic diseases. PRESENTATION OF HYPOTHESIS: Docosahexaenoic acid and eicosapentaenoic acid, which are the fatty acids abundant in fish oil, are traditionally used against metabolic diseases. These fatty acids act as PPAR agonists that transcript the genes involved in glucose and lipid homeostasis. Present hypothesis suggests that the derivatives of these fatty acids are stronger PPAR agonists than the parent compounds. X-ray structures of PPARs indicate that alpha or beta derivatives of fatty acids would fit into PPARalpha/gamma binding cavity. Therefore, the derivatives will exhibit stronger affinities and activities than the parent compounds. TESTING OF THE HYPOTHESIS: Ligand binding assays and gene transactivation assays should be performed to test the hypothesis. Fluorescence-based methods are advantageous in binding assays, because they were found more suitable for fatty acid binding assays. In transactivation assays, care should be taken to remove contaminants from recombinant proteins. IMPLICATIONS OF THE HYPOTHESIS: Present hypothesis is framed on the basis of molecular structure of natural PPAR agonists. Small structural changes in the molecular structure of fatty acids have a great influence on activating different PPARs. Therefore, this hypothesis bridges the concept of natural PPAR agonists and the use of structural information in designing new drugs against diabetes and metabolic syndrome. The derivatives may also be used as anti-inflammatory and anticancer agents.

1,5-Disubstituted 1,2,3-triazoles as cis-restricted analogues of combretastatin A-4: Synthesis, molecular modeling and evaluation as cytotoxic agents and inhibitors of tubulin.

A series of cis-restricted 1,5-disubstituted 1,2,3-triazole analogues of combretastatin A-4 (1) have been prepared. The triazole 12f, 2-methoxy-5-(1-(3,4,5-trimethoxyphenyl)-1H-1,2,3-triazol-5-yl)aniline, displayed potent cytotoxic activity against several cancer cell lines with IC(50) values in the nanomolar range. The ability of triazoles to inhibit tubulin polymerization has been evaluated, and 12f inhibited tubulin polymerization with IC(50)=4.8microM. Molecular modeling experiments involving 12f and the colchicine binding site of alpha,beta-tubulin showed that the triazole moiety interacts with beta-tubulin via hydrogen bonding with several amino acids.

Data driven polypharmacological drug design for lung cancer: analyses for targeting ALK, MET, and EGFR.

Drug design of protein kinase inhibitors is now greatly enabled by thousands of publicly available X-ray structures, extensive ligand binding data, and optimized scaffolds coming off patent. The extensive data begin to enable design against a spectrum of targets (polypharmacology); however, the data also reveal heterogeneities of structure, subtleties of chemical interactions, and apparent inconsistencies between diverse data types. As a result, incorporation of all relevant data requires expert choices to combine computational and informatics methods, along with human insight. Here we consider polypharmacological targeting of protein kinases ALK, MET, and EGFR (and its drug resistant mutant T790M) in non small cell lung cancer as an example. Both EGFR and ALK represent sources of primary oncogenic lesions, while drug resistance arises from MET amplification and EGFR mutation. A drug which inhibits these targets will expand relevant patient populations and forestall drug resistance. Crizotinib co-targets ALK and MET. Analysis of the crystal structures reveals few shared interaction types, highlighting proton-arene and key CH-O hydrogen bonding interactions. These are not typically encoded into molecular mechanics force fields. Cheminformatics analyses of binding data show EGFR to be dissimilar to ALK and MET, but its structure shows how it may be co-targeted with the addition of a covalent trap. This suggests a strategy for the design of a focussed chemical library based on a pan-kinome scaffold. Tests of model compounds show these to be compatible with the goal of ALK, MET, and EGFR polypharmacology.

Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance.

Virtual screening methods are now widely used in early stages of drug discovery, aiming to rank potential inhibitors. However, any practical ligand set (of active or inactive compounds) chosen for deriving new virtual screening approaches cannot fully represent all relevant chemical space for potential new compounds. In this study, we have taken a retrospective approach to evaluate virtual screening methods for the leukemia target kinase ABL1 and its drug-resistant mutant ABL1-T315I. 'Dual active' inhibitors against both targets were grouped together with inactive ligands chosen from different decoy sets and tested with virtual screening approaches with and without explicit use of target structures (docking). We show how various scoring functions and choice of inactive ligand sets influence overall and early enrichment of the libraries. Although ligand-based methods, for example principal component analyses of chemical properties, can distinguish some decoy sets from active compounds, the addition of target structural information via docking improves enrichment, and explicit consideration of multiple target conformations (i.e. types I and II) achieves best enrichment of active versus inactive ligands, even without assuming knowledge of the binding mode. We believe that this study can be extended to other therapeutically important kinases in prospective virtual screening studies.

Molecular recognition of docosahexaenoic acid by peroxisome proliferator-activated receptors and retinoid-X receptor alpha.

The family of peroxisome proliferator-activated receptors (PPARs) is the molecular target of synthetic antidiabetic and hypolipidemic drugs. The side effects of these drugs are limiting their use in patients with high lipid levels. Natural compounds, like Docosahexaenoic acid (DHA) from fish oil, have beneficial effects in the treatment of metabolic diseases, and several DHA derivatives are known to activate PPAR genes. Experimental studies on affinities of DHA and its derivatives for PPARs are not available. In the present study we are therefore using computational docking, molecular dynamics simulation, and several scoring programs to predict affinities and binding modes of DHA for PPARs and retinoid-X receptor alpha, which is the DNA binding partner of PPARs. The calculations indicated that DHA binds to PPARs and the retinoid-X receptor alpha with high affinity, and that different PPARs exhibited different structural effects on the first four carbons atoms of DHA. Our data indicate that the beneficial health effects of DHA may be obtained by high affinity binding to the PPARs.

Ligand-induced stabilization and activation of peroxisome proliferator-activated receptor gamma.

Peroxisome proliferator-activated receptor gamma belongs to the nuclear receptor superfamily and is activated by the antidiabetic drugs rosiglitazone and pioglitazone. Ligand-independent constitutive activity of peroxisome proliferator-activated receptor gamma is also demonstrated. X-ray crystallographic structures show that the active or inactive conformations of the receptor are determined by the position of helix 12 in the C-terminal end. In this study, molecular dynamics simulations were used to gain molecular insight into the activation process and the structural stability of inactive and active peroxisome proliferator-activated receptor gamma receptor structure. The simulations showed: (i) during molecular dynamics simulations without agonist at the active site, the receptor structure with helix 12 in a position corresponding to activated receptor structure was structurally more stable than with helix 12 in a position corresponding to inactive receptor structure, which may contribute to the constitutive activity of the receptor; (ii) docosahexenoic acid stabilized the active receptor conformation more efficiently than the glitazones; (iii) docosahexenoic acid, but not glitazones, induced structural changes into the inactive receptor structure such that helix 12 was shifted into a position more similar to that of an active receptor structure, which indicate that docosahexenoic acid is a more effective peroxisome proliferator-activated receptor gamma agonist than the glitazones.

Signposts of docking and scoring in drug design.

Docking and scoring tools are often used in the early stages of drug discovery projects today. Because the language of this field of drug design often includes intermingled terms of physics, chemistry, biology, and medicine, the significant developments of docking and scoring are challenging to follow for non-experts. In this Science Philosophy article, I attempt to clarify the concepts used in docking and scoring to help articulate the successes and limitations of this multidisciplinary field in more comprehensible manner.