Applying conformational selection theory to improve crossdocking efficiency in 3-phosphoinositide dependent protein kinase-1.

The emerging picture of biomolecular recognition is that of conformational selection followed by induced-fit. Conformational selection theory states that binding partners exist in various conformations in solution, with binding involving a "selection" between complementary conformers. In this study, we devise a docking protocol that mimics conformational selection in protein-ligand binding and demonstrate that it significantly enhances crossdocking accuracy over Glide's flexible docking protocol, which is widely used in the pharmaceutical industry. Our protocol uses a pregenerated conformational ensemble to simulate ligand flexibility. The ensemble was generated by thorough conformational sampling coupled with conformer minimization. The generated conformers were then rigidly docked in the active site of the protein along with a postdocking minimization step that allows limited induced fit effects to be modeled for the ligand. We illustrate the improved performance of our protocol through crossdocking of 31 ligands to cocomplexed proteins of the kinase 3-phosphoinositide dependent protein kinase-1 extracted from the crystal structures 1H1W (ATP bound), 1OKY (staurosporine bound) and 3QD0 (bound to a potent inhibitor). Consistent with conformational selection theory, the performance of our protocol was the best for crossdocking to the cognate protein bound to the natural ligand, ATP.

Pyrid-2-yl and 2-CyanoPhenyl fused heterocyclic compounds as human P2X3 inhibitors: a combined approach based on homology modelling, docking and QSAR analysis.

P2X receptors are hetero-oligomeric proteins that function as membrane ion channels and are gated by extracellular ATP. The hP2X[Formula: see text] subunit is a constituent of the channels on a subset of sensory neurons involved in pain signaling, where ATP released by damaged and inflamed tissue can initiate action potentials. Hence, the inhibition of ATP-activated P2X3 receptor is an exciting approach for the treatment of inflammatory and neuropathic pain. Recently, the crystal structures of zebrafish P2X4 (zP2X4) were obtained in closed, apo state (PDB ID: 3I5D) and ATP-bound, open state (PDB ID: 4DW1). These structures were used to develop a homology model of human P2X3 (hP2X3 in order to identify through docking studies, the binding modes of known P2X3 inhibitors and their key active site interactions, along with a pharmacophore-based 3D-QSAR model for a series of 136 Pyrid-2-yl and 2-CyanoPhenyl fused heterocyclic compounds. These 3D-QSAR models have been developed with different combinations of training and test set divisions obtained by random separation, Jarvis-Patrick clustering, K-means clustering and sphere exclusion methods. The best predictive 3D-QSAR model resulted in training set R2 of 0.75, internal test set Q2 of 0.74, Pearson-R value of 0.87 and root mean square error of 0.37. The information generated by the pharmacophore model and docking analyses using the homology model provides valuable clues to design novel potent hP2X3 inhibitors.

Toward a general predictive QSAR model for gamma-secretase inhibitors.

Gamma secretase (GS) is an appealing drug target for Alzheimer disease and cancer because of its central role in the processing of amyloid precursor protein and the notch family of proteins. In the absence of three-dimensional structure of GS, there is an urgent need for new methods for the prediction and screening of GS inhibitors, for facilitating discovery of novel GS inhibitors. The present study reports QSAR studies on diverse chemical classes comprising 233 compounds collected from the ChEMBL database. Herein, continuous [PLS regression and neural-network (NN)] and categorical QSAR models (NN and linear discriminant analysis) were developed to obtain pertinent descriptors responsible for variation of GS inhibitor potency. Also, SAR within various chemical classes of compounds is analyzed with respect to important QSAR descriptors, which revealed the significance of electronegative substitutions on aryl rings (PEOE3) in determining variation of GS inhibitor potency. Furthermore, substitution of acyclic amines with N-substituted cyclic amines appears to be favorable for enhancing GS inhibitor potency by increasing the values of sssN_Cnt and number of aliphatic rings. The models developed are statistically significant and improve our understanding of compounds contributing toward GS inhibitor potency and aid in the rational design of novel potent GS inhibitors.

2-Aminothiadiazole inhibitors of AKT1 as potential cancer therapeutics.

A series of 2-aminothiadiazole of inhibitors of AKT1 is described. SAR relationships are discussed, along with selectivity for protein kinase A (PKA) and cyclin-dependent kinase 2 (CDK2). Moderate selectivity observed in several compounds for AKT1 versus PKA is rationalized by X-ray crystallographic analysis. Key compounds showed activity in cellular assays measuring phosphorylation of two AKT substrates, PRAS40 and FKHRL1. Compound 30 was advanced to a mouse liver PD assay, where it showed dose-dependent inhibition of AKT activity, as measured by the inhibition of phospho-PRAS40.

Dipeptidyl-quinolone derivatives inhibit hypoxia inducible factor-1α prolyl hydroxylases-1, -2, and -3 with altered selectivity.

Intracellular levels of the hypoxia-inducible transcription factor (HIF) are regulated under normoxic conditions by prolyl hydroxylases (PHD1, 2, and 3). Treatment of cells with PHD inhibitors stabilizes HIF-1α, eliciting an artificial hypoxic response that includes the transcription of genes involved in erythropoiesis, angiogenesis, and glycolysis. The different in vivo roles of the three PHD isoforms are not yet known, making a PHD-selective inhibitor useful as a biological tool. Although several chemical series of PHD inhibitors have been described, significant isoform selectivity has not been reported. Here we report the synthesis and activity of dipeptidyl analogues derived from a potent but non-selective quinolone scaffold. The compounds were prepared by Pd-catalyzed reductive carbonylation of the 6-iodoquinolone derivative to form the aldehyde directly, which was then attached to a solid support via reductive amination. Amino acids were coupled, and the resulting dipeptidyl-quinolone derivatives were screened, revealing retention of PHD inhibitory activity but an altered PHD1, 2, and 3 selectivity profile. The compounds were found to be ∼10-fold more potent against PHD1 and PHD3 than against PHD2, whereas the specific parent compound had shown no appreciable selectivity among the different PHD isoforms.

Discovery of dihydroquinoxalinone acetamides containing bicyclic amines as potent Bradykinin B1 receptor antagonists.

Replacement of the core beta-amino acid in our previously reported piperidine acetic acid and beta-phenylalanine-based Bradykinin B1 antagonists by dihydroquinoxalinone acetic acid increases the in vitro potency and metabolic stability. The most potent compounds from this series have IC(50)s<0.2 nM in a human B1 receptor functional assay. A molecular modeling study of the binding modes of key compounds, based on a B1 homology model, explains the structure-activity relationship (SAR) for these analogs.

Structure-guided design of substituted aza-benzimidazoles as potent hypoxia inducible factor-1alpha prolyl hydroxylase-2 inhibitors.

We report the structure-based design and synthesis of a novel series of aza-benzimidazoles as PHD2 inhibitors. These efforts resulted in compound 22, which displayed highly potent inhibition of PHD2 function in vitro.

Discovery of novel hydroxy-thiazoles as HIF-alpha prolyl hydroxylase inhibitors: SAR, synthesis, and modeling evaluation.

Inhibition of the PHD2 enzyme has been associated with increased red blood cell levels. From a screening hit, a series of novel hydroxyl-thiazoles were developed as potent PHD2 inhibitors.

Three-dimensional quantitative structure-activity relationships and activity predictions of human TRPV1 channel antagonists: comparative molecular field analysis and comparative molecular similarity index analysis of cinnamides.

3D-QSAR models for human TRPV1 channel antagonists were developed based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA), using a training set of 61 cinnamide TRPV1 antagonists and tested on an independent test set of 47 antagonists. Molecular alignment procedure included weights for both internal energy and atom-to-atom matching against a reference or probe. Sensitivity of results on partial charge assignments was explored using multiple charge sets. AM1-BCC charge assignments gave better results for both CoMFA and CoMSIA models. For the best CoMFA model, the statistics are, r2 = 0.96, q2 = 0.58, n = 61 for the training set and r2 = 0.50, n = 47 for the test set. For the best CoMSIA model, the statistics are r2 = 0.95, q2 = 0.57, n = 61 for the training set and r2 = 0.48, n = 47 for the test set. These models are consistent with the proposed binding modes and interactions of known activators of the TRPV1 channel such as capsaicin, in a structural model of the TM3/4 helical region of TRPV1.

Novel vanilloid receptor-1 antagonists: 1. Conformationally restricted analogues of trans-cinnamides.

The vanilloid receptor-1 (VR1 or TRPV1) is a member of the transient receptor potential (TRP) family of ion channels and plays a role as an integrator of multiple pain-producing stimuli. From a high-throughput screening assay, measuring calcium uptake in TRPV1-expressing cells, we identified an N-aryl trans-cinnamide (AMG9810, compound 9) that acts as a potent TRPV1 antagonist. We have demonstrated the antihyperalgesic properties of 9 in vivo and have also reported the discovery of novel, orally bioavailable cinnamides derived from this lead. Herein, we expand our investigations and describe the synthesis and biological evaluation of a series of conformationally constrained analogues of the s-cis conformer of compound 9. These investigations resulted in the identification of 4-amino- and 4-oxopyrimidine cores as suitable isosteric replacements for the trans-acrylamide moiety. The best examples from this series, pyrimidines 79 and 74, were orally bioavailable and exhibited potent antagonism of both rat (IC50 = 4.5 and 0.6 nM, respectively) and human TRPV1 (IC50 = 7.4 and 3.7 nM, respectively). In addition, compound 74 was shown to be efficacious at blocking a TRPV1-mediated physiological response in vivo in the capsaicin-induced hypothermia model in rats; however, it was ineffective at preventing thermal hyperalgesia induced by complete Freund's adjuvant in rats.

Identification of a nonpeptidic and conformationally restricted bradykinin B1 receptor antagonist with anti-inflammatory activity.

We report the discovery of chroman 28, a potent and selective antagonist of human, nonhuman primate, rat, and rabbit bradykinin B1 receptors (0.4-17 nM). At 90 mg/kg s.c., 28 decreased plasma extravasation in two rodent models of inflammation. A novel method to calculate entropy is introduced and ascribed approximately 30% of the gained affinity between "flexible" 4 (Ki = 132 nM) and "rigid" 28 (Ki = 0.77 nM) to decreased conformational entropy.

TRPV1 antagonism by piperazinyl-aryl compounds: A Topomer-CoMFA study and its use in virtual screening for identification of novel antagonists.

Transient Receptor Potential Vanilloid, member 1 (TRPV1), is a non-selective cation channel belonging to the transient receptor potential (TRP) family of ion channels. It occurs in the peripheral and central nervous system, activated by a variety of exogenous and endogenous stimuli, thus playing a key role in transmission of pain. This has been a target for chronic pain since more than a decade and a number of antagonists that progressed into clinical trials have failed due to the unexpected side effect of core body temperature rise, thus halting progress in this field. Of late, there has been an upsurge in research on this target, with the rat TRPV1 structure being determined, many new antagonists discovered that are temperature-neutral and many new therapeutic avenues being discovered for TRPV1, including diseases of respiratory and digestive systems, skin and bladder. Towards identifying diverse compounds to decipher the role of this target in various indications, here we report a 3D-QSAR model built using the new topomer-CoMFA methodology on a series of piperazinyl-aryl TRPV1 antagonists and the use of this model, along with a pharmacophore model and the shape of one of the potent compounds of this series, to virtually screen a subset of the ZINC database to find novel and diverse hits. These can serve as starting points to develop modality-selective antagonists for chronic pain and to elucidate the critical role of TRPV1 in the various new therapeutic areas.

A New Series of Orally Bioavailable Chemokine Receptor 9 (CCR9) Antagonists; Possible Agents for the Treatment of Inflammatory Bowel Disease.

Chemokine receptor 9 (CCR9), a cell surface chemokine receptor which belongs to the G protein-coupled receptor, 7-trans-membrane superfamily, is expressed on lymphocytes in the circulation and is the key chemokine receptor that enables these cells to target the intestine. It has been proposed that CCR9 antagonism represents a means to prevent the aberrant immune response of inflammatory bowel disease in a localized and disease specific manner and one which is accessible to small molecule approaches. One possible reason why clinical studies with vercirnon, a prototype CCR9 antagonist, were not successful may be due to a relatively poor pharmacokinetic (PK) profile for the molecule. We wish to describe work aimed at producing new, orally active CCR9 antagonists based on the 1,3-dioxoisoindoline skeleton. This study led to a number of compounds that were potent in the nanomolar range and which, on optimization, resulted in several possible preclinical development candidates with excellent PK properties.

Knowledge-based approaches in the design and selection of compound libraries for drug discovery.

In the past decade, the pharmaceutical industry has realized the increasing significance of impacting the early phase hit-to-lead development in the drug discovery process. In particular, knowledge-based approaches emerged and evolved to address a multitude of issues such as absorption, distribution, metabolism and excretion (ADME), potency, toxicity and overall drugability. Each of these approaches seeks to bring together all relevant pieces of information and create a knowledge-oriented process to deploy such information in drug discovery. This review focuses on work relating to drugability, which aims at obtaining hits (or leads) that have enhanced likelihoods of leading to successful clinical candidates by medicinal chemistry efforts. The period covered in this review is from 1997 (since the publication of Lipinski's rule of 5) to March 2002.

Small molecule inhibitors of PIM1 kinase: July 2009 to February 2013 patent update.

INTRODUCTION: The proviral insertion in murine (PIM) lymphoma proteins for which three isoforms, PIM1, PIM2 and PIM3 have been identified, belonging to the family of serine/threonine kinases has emerged recently as an important therapeutic target for the development of selective inhibitors as the new drugs for treating hematological malignancies and solid tumors. The small molecules developed by academia and the pharmaceutical industry have steadily increased in the last few years. Several drug discovery groups focus on treating disorders, such as cancer mediated by PIM kinase, have provided preclinical evidence suggesting that PIM inhibitor provides anti-apoptotic activity, inhibit cell survival and cell proliferation. AREAS COVERED: This article discloses recent reviews on research and advances published in the patent literature and scientific publications from July 2009 to February 2013, highlighting discoveries on PIM1 kinase. EXPERT OPINION: Several PIM1 kinase small molecule inhibitors are now at the pre-clinical research stage, development and testing. Though nearly 40 patents emerged in the last 3 years, greater efforts towards additional designs and medicinal chemistry continues for developing clinically efficacious PIM1 inhibitors, due to the significance of the target for cancer and the potential for novel and diverse inhibitors as drug candidates.

Focal adhesion kinase inhibitors in the treatment of metastatic cancer: a patent review.

INTRODUCTION: Focal adhesion kinase (FAK) plays a prominent role in integrin signaling. FAK activation increases phosphorylation of Tyr397 and other sites of the protein. FAK-dependent activation of signaling pathways implicated in controlling essential cellular functions including growth, proliferation, survival and migration. FERM (F for the 4.1 protein, ezrin, radixin and moesin) domain-enhanced p53 degradation plays a critical role in proliferation and survival. FAK, overexpressed in metastatic tumors, has emerged as an important therapeutic target for the development of selective inhibitors. FAK inhibitors achieved tumor growth inhibition and induced apoptosis. Strategies targeting FAK inhibition using novel compounds have created an exciting opportunity for anticancer therapy. AREAS COVERED: This review summarizes the current research with available data from early phase clinical trials and discusses the available small-molecule inhibitors of FAK from patents. The importance of inhibiting FAK activity in cancer patients is discussed. EXPERT OPINION: Emerging data from clinical trials with orally available small-molecule inhibitors of FAK are promising. Although this approach is appropriate as a targeted therapeutic approach against several metastatic cancer types, several compounds in research are yet to prove their preclinical efficacy. This report lays special emphasis on the available patent data of FAK inhibitors for such targeted molecular therapies. This review summarizes current knowledge about FAK inhibition in cancer therapy.

Could MM-GBSA be accurate enough for calculation of absolute protein/ligand binding free energies?

Implicit solvation methods such as MM-GBSA, when applied to evaluating protein/ligand binding free energies, are widely believed to be accurate only for the estimation of relative binding free energies for a congeneric series of ligands. In this work, we show that the MM-GBSA flavor of Prime 3.0, VSGB-2.0, with a variable dielectric model and a novel energy function, could be approaching the accuracy required for evaluating absolute binding free energies, albeit, through a linear regression fit. The data-set used for validation includes 106 protein-ligand complexes that were carefully selected to control for variability in the affinity data as well as error in the modeled complexes. Through systematic analysis, we also quantify the degradation in the R(2) of fit between experimental and calculated values with either greater variability in the affinity data or an increase in error in the modeled protein/ligand complexes. Limitations for its application in drug discovery are discussed along with the identification of areas for future development.

A neural network-based QSAR approach for exploration of diverse multi-tyrosine kinase inhibitors and its comparison with a fragment- based approach.

Receptor and non-receptor tyrosine kinases have emerged as clinically useful drug target for treating certain types of cancer. It is well known that tyrosine kinase inhibitors with multi-kinases inhibitory potency are useful in anticancer therapy. In recent study, we have demonstrated application of a novel Group based QSAR (GQSAR) method to assist in lead optimization of multi-tyrosine kinase (PDGFR-beta, FGFR-1 and SRC) inhibitors. Although GQSAR method provides an alternative way to design new compounds, it could not be applied for virtual screening of large databases, because of its limitation to fragment each of the compound in the diverse database. So to circumvent this limitation of GQSAR method, herein we present the development of multi-kinase QSAR model using artificial neural networks. Various simple, easy and fast to calculate 2D/3D descriptors were used in the present analysis. The resulting neural network based QSAR (NN-QSAR) model was found to be statistically significant and provided insight into common structural requirements to inhibit different tyrosine kinases. The NN-QSAR model suggests five descriptors viz. number of rotatable bonds, number of hydrogen bond donors, number of building blocks, polar surface area and sum of nitrogen and oxygen atoms to be of major importance in explaining the activity variation in all the three kinases. In addition, this multi-target QSAR model could be useful to predict the activities of new compounds designed as tyrosine kinase inhibitors.

3D-QSAR analysis of TRPV1 inhibitors reveals a pharmacophore applicable to diverse scaffolds and clinical candidates.

TRPV1 (Transient Receptor Potential Vanilloid Type 1) receptor, a member of Transient Receptor Potential Vanilloid subfamily of ion channels, occurs in the peripheral and central nervous system, and plays a key role in transmission of pain. Consequently, this has been the target for discovery of several pain relieving agents which have undergone clinical trials. Though several TRPV1 antagonists have progressed to become clinical candidates, many are known to cause temperature elevation in humans, halting their further advancement, and signifying the need for new chemotypes. Different chemical classes of TRPV1 antagonists share three important features: an amide or an isostere flanked by an aromatic (or fused aromatic) ring with polar substitutions on one side, and a hydrophobic group on the other. Recent work identified new series of compounds with these and additional features, leading to improvement of properties, and development of clinical candidates. Herein, we describe a 3D-QSAR model (n=62; R(2)=0.9 and Q(2)=0.75) developed from the piperazinyl-aryl series of compounds and a novel 5-point pharmacophore model is shown to fit several diverse scaffolds, six clinical candidates, five pre-clinical candidates and three lead compounds. The pharmacophore model can aid in finding new chemotypes as starting points that can be developed further.

Atom type preferences, structural diversity, and property profiles of known drugs, leads, and nondrugs: a comparative assessment.

A new characterization of known drug, lead, and representative nondrug databases was performed taking into account several properties at the atomic and molecular levels. This characterization included atom type preferences, intrinsic structural diversity (Atom Type Diversity, ATD), and other well-known physicochemical properties, as an approach for rapid assessment of druglikeness for small molecule libraries. To characterize ATD, an elaborate united atom classification, UALOGP (United Atom Log P), with 148 atom types, was developed along with associated atomic physicochemical parameters. This classification also enabled an analysis of atom type and physicochemical property distributions (for calculated log P, molar refractivity, molecular weight, total atom count, and ATD) of drug, lead, and nondrug databases, a reassessment of the Ro5 (Rule of Five) and GVW (Ghose−Viswanadhan−Wendoloski) criteria, and development of new criteria and ranges more accurately reflecting the chemical space occupied by small molecule drugs. A relative druglikeness parameter was defined for atom types in drugs, identifying the most preferred types. The present work demonstrates that drug molecules are constitutionally more diverse relative to nondrugs, while being less diverse than leads.