Virtual screening studies to design potent CDK2-cyclin A inhibitors

Application of computational methods for class A GPCR Ligand discovery

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development due to their role in transmitting cellular signals in a multitude of biological processes. Of the six classes categorizing GPCR (A, B, C, D, E, and F), class A contains the largest number of therapeutically relevant GPCR. Despite their importance as drug targets, many challenges exist for the discovery of novel class A GPCR ligands serving as drug precursors. Though knowledge of the structural and functional characteristics of GPCR has grown significantly over the past 20 years, a large portion of GPCR lack reported, experimentally determined structures. Furthermore, many GPCR have no known endogenous and/or synthetic ligands, limiting further exploration of their biochemical, cellular, and physiological roles. While many successes in GPCR ligand discovery have resulted from experimental high-throughput screening, computational methods have played an increasingly important role in GPCR ligand identification in the past decade. Here we discuss computational techniques applied to GPCR ligand discovery. This review summarizes class A GPCR structure/function and provides an overview of many obstacles currently faced in GPCR ligand discovery. Furthermore, we discuss applications and recent successes of computational techniques used to predict GPCR structure as well as present a summary of ligand- and structure-based methods used to identify potential GPCR ligands. Finally, we discuss computational hit list generation and refinement and provide comprehensive workflows for GPCR ligand identification.

Computational discovery of novel anthelmintic natural compounds from Agave Brittoniana trel. Spp. Brachypus

Helminth infections are a medical problem in the world nowadays. This report used bond-based 2D quadratic indices, a bond-level QuBiLs-MAS molecular descriptor family, and Linear Discriminant Analysis (LDA) to obtain a quantitative linear model that discriminates between anthelmintic and non-anthelmintic drug-like organic-compounds. The model obtained correctly classified 87.46% and 81.82% of the training and external data sets, respectively. The developed model was used in a virtual screening to predict the biological activity of all chemicals (19) previously obtained and chemically characterized by some authors of this report from Agave brittoniana Trel. spp. Brachypus. The model identified several metabolites (12) as possible anthelmintics, and a group of 5 novel natural products was tested in an in vitro assay against Fasciola hepatica (100% effectivity at 500 µg/mL). Finally, the two best hits were evaluated in vivo in bald/c mice and the same helminth parasite using a 25 mg/kg dose. Compound 8 (Karatavinoside A) showed an efficacy of 92.2% in vivo. It is important to remark that this natural compound exhibits similar-to-superior activity as triclabendazole, the best human fasciolicide available in the market against Fasciola hepatica, resulting in a novel lead scaffold with anti-helminthic activity. Keywords: TOMOCOMD-CARDD Software; QuBiLs-MAS, nonstochastic and stochastic bond-based quadratic indices; LDA-based QSAR model; Computational Screening, Anthelmintic Agent; Agave brittoniana Trel. spp. Brachypus, Fasciola hepatica.

Efficient regioselective five-component synthesis of novel thiazolo[3,2-a]pyridine carbohydrazides and oxazolo[3,2-a]pyridine carbohydrazides

Two new categories of fused pyridines include 2H-thiazolo[3,2-a]pyridine-6-carbohydrazides and 2H-oxazolo[3,2-a]pyridine-6-carbohydrazides have been successfully synthesized via five-component cascade reactions using 9-fluorenone, cyanoacetohydrazide, 1,1-bis(methylthio)-2-nitroethene, aromatic aldehydes and cysteamine hydrochloride or ethanol amine as starting materials. This new approach involves a subsequence of key steps: N,S-acetal or N,O-acetal formation, Knoevenagel condensation, Michael addition, tautomerization and N-cyclization. It also has some advantages, such as convenience of operation, tolerance of a wide diversity of functional groups, use of green solvent and ease of purification by washing the crude products with ethanol.

Synthesis of highly functionalized thiazolo[3,2-a]pyridine derivatives via a five-component cascade reaction based on nitroketene N,S-acetal

A highly efficient and straightforward synthesis of N-fused heterocyclic compounds including 5-amino-7-(aryl)-8-nitro-N'-(1-(aryl)ethylidene)-3,7-dihydro-2H-thiazolo[3,2-a]pyridine-6-carbohydrazide derivatives is successfully achieved via a five-component cascade reaction utilizing cyanoacetohydrazide, various acetophenones, aromatic aldehydes, 1,1-bis(methylthio)-2-nitroethylene and cysteamine hydrochloride in ethanol at reflux conditions. The new approach involves domino N,S-acetal formation, Knoevenagel condensation, Michael reaction, imine–enamine tautomerization and N-cyclization sequences. The prominent advantages of this protocol include: facility of operation, available and economical starting materials, no need for toxic solvents, high yields and tolerance of a wide variety of functional groups.

Easy construction of novel and highly substituted thiazolo[3,2-a]pyridine hydrazone compounds using keten N,S-acetals.

Discovery of Novel Neuraminidase Inhibitors by Structure-Based Virtual Screening, Structural Optimization, and Bioassay

Neuraminidase (NA) is a significant therapeutic target for treating influenza. In this study, a new lead NA inhibitor AN-329/10738021 was discovered by structure-based virtual screening, molecular dynamics simulations, and bioassay validation. Optimization of lead AN-329/10738021, which holds a novel scaffold of N'-benzylidene benzohydrazone, leads to discovery of some novel NA inhibitors Y-1-Y-11. Compound Y-1 exerts the best inhibition activity (IC₅₀ = 0.21 μM) against NA, which is better than oseltamivir carboxylate (OSC) (IC₅₀ = 3.04 μM) and lead AN-329/10738021 (IC₅₀ = 1.92 μM). Molecular docking analysis indicates that the good potency of Y-1 may be ascribed to the elongation of the benzylidene moiety of the molecule to the 430-cavity. The results of this study may offer useful reference for development of novel NA inhibitors.

Molecular docking and biological evaluation of some thioxoquinazolin-4(3H)-one derivatives as anticancer, antioxidant and anticonvulsant agents

Background

The quinazoline are an important class of medicinal compounds that possess a number of biological activities like anticancer, anticonvulsant and antioxidant etc.

Results

We evaluated the previously synthesized quinazoline derivatives 1–3 for their anticancer activities against three cancer cell lines (HepG2, MCF-7, and HCT-116). Among the tested compounds, quinazolines 1 and 3 were found to be more potent than the standard drug Vinblastine against HepG2 and MCF-7 cell lines. All the tested compounds had less antioxidant activity and did not exhibit any anticonvulsant activity. Also, molecular docking studies were performed to get an insight into the binding modes of the compounds with human cyclin-dependent kinase 2, butyrylcholinesterase enzyme, human gamma-aminobutyric acid receptor. These compounds showed better docking properties with the CDK2 as compared to the other two enzymes.

Conclusions

The overall study showed that thioxoquinazolines are suitable antitumor agents and they should be explored for other biological activities. Modification in the available lot of quinazoline and synthesis of its novel derivatives is essential to explore the potential of this class of compounds. The increase in the threat and with the emergence of drug resistance, it is important to explore and develop more efficacious drugs.

Identification of an Inhibitor of the Aminoglycoside 6'-N-Acetyltransferase type Ib [AAC(6')-Ib] by Glide Molecular Docking

The aminoglycoside 6'-N-acetyltransferase type Ib, AAC(6')-Ib, confers resistance to clinically relevant aminoglycosides and is the most widely distributed enzyme among AAC(6')-I-producing Gram-negative pathogens. An alternative to counter the action of this enzyme is the development of inhibitors. Glide is a computational strategy for rapidly docking ligands to protein sites and estimating their binding affinities. We docked a collection of 280,000 compounds from 7 sub-libraries of the Chembridge library as ligands to the aminoglycoside binding site of AAC(6')-Ib. We identified a compound, 1-[3-(2-aminoethyl)benzyl]-3-(piperidin-1-ylmethyl)pyrrolidin-3-ol (compound 1), that inhibited the acetylation of aminoglycosides in vitro with IC50 values of 39.7 and 34.9 µM when the aminoglycoside substrates assayed were kanamycin A or amikacin, respectively. The growth of an amikacin-resistant Acinetobacter baumannii clinical strain was inhibited in the presence of a combination of amikacin and compound 1.

Insights into the structural basis of 3,5-diaminoindazoles as CDK2 inhibitors: prediction of binding modes and potency by QM-MM interaction, MESP and MD simulation

The novel 3,5-diaminoindazole derivatives are well-known as potent and anti-proliferative cyclin-dependent kinase 2 inhibitors. We report a combined quantum mechanics/molecular mechanics study to determine the protein-ligand interaction energy, and some quantum chemical descriptors to successfully rank these inhibitors. The results in this work show that the QM-MM interaction energy is strongly correlated to the biological activity and can be used as a predictor, which was further validated by Spearman's rank correlation coefficient. An exhaustive analysis of the protein-ligand structures obtained from molecular dynamics simulations shows specific interactions within the active site. Furthermore, the docking study was supported by electronic property analysis using density functional theory at the B3LYP/3-21*G level. The results obtained from molecular docking and surface analysis shed some insight on steric and electronic complementarities of these molecules to CDK2. Aqueous solvation energy values give an indication of the solubility and can be used as a guide for the pharmacokinetic optimization of these molecules. Furthermore, ADME/T properties calculated are in the desirable range, so these compounds are predicted to be drug like with low toxicity potential. Overall, the approach was successful in the cases considered, and it could be useful for the design of inhibitors in the lead optimization phase of drug discovery against CDK2.

Pharmacophore approaches in protein kinase inhibitors design

Protein kinases constitute a superfamily of therapeutic targets for a number of human and animal diseases that include more than 500 members accordingly to sequencing data of the human genome. The well characterized nature of protein kinases makes them excellent targets for drug development. Pharmacophore approaches have become one of the major tools in the area of drug discovery. Application of pharmacophore modeling approaches allows reducing of expensive overall cost associated with drug development project. Pharmacophore models are important functional groups of atoms in the proper spatial position for interaction with target protein. Various ligand-based and structure-based methods have been developed for pharmacophore model generation. Despite the successes in pharmacophore models generation these approaches have not reached their full capacity in application for drug discovery. In the following review, we summarize the published data on pharmacophore models for inhibitors of tyrosine protein kinases (EGFR, HER2, VEGFR, JAK2, JAK3, Syk, ZAP-70, Tie2) and inhibitors of serine/threonine kinases (Clk, Dyrk, Chk1, IKK2, CDK1, CDK2, PLK, JNK3, GSK3, mTOR, p38 MAPK, PKB). Here, we have described the achievements of pharmacophore modeling for protein kinase inhibitors, which provide key points for further application of generated pharmacophore hypotheses in virtual screening, de novo design and lead optimization.

Molecular dynamics-based discovery of novel phosphodiesterase-9A inhibitors with non-pyrazolopyrimidinone scaffolds

Phosphodiesterase-9A (PDE9A) is a promising therapeutic target for the treatment of diabetes and Alzheimer's disease (AD). The Pfizer PDE9A inhibitor PF-04447943 has completed Phase II clinical trials in subjects with mild to moderate AD in 2013. However, most of the reported PDE9A inhibitors share the same scaffold as pyrazolopyrimidinone, which lacks structural diversity and is unfavorable for the development of novel PDE9A inhibitors. In the present study, a combinatorial method including pharmacophores, molecular docking, molecular dynamics simulations, binding free energy calculations, and bioassay was used to discover novel PDE9A inhibitors with new scaffolds rather than pyrazolopyrimidinones from the SPECS database containing about 200,000 compounds. As a result, 15 hits out of 29 molecules (a hit rate of 52%) with five novel scaffolds were identified to be PDE9A inhibitors with inhibitory affinities no more than 50 μM to enrich the structural diversity, different from the pyrazolopyrimidinone-derived family. The high hit ratio of 52% for this virtual screening method indicated that the combinatorial method is a good compromise between computational cost and accuracy. Binding pattern analyses indicate that those hits with non-pyrazolopyrimidinone scaffolds can bind the same active site pocket of PDE9A as classical PDE9A inhibitors. In addition, structural modification of compound AG-690/40135604 (IC50=8.0 μM) led to a new one, 16, with an improved inhibitory affinity of 2.1 μM as expected. The five novel scaffolds discovered in the present study can be used for the rational design of PDE9A inhibitors with higher affinities.

ATP-noncompetitive CDK inhibitors for cancer therapy: an overview

INTRODUCTION

Cyclin-dependent kinases (CDKs) are the key drivers of cell cycle progression and are often deregulated in cancer, therefore, targeting CDKs has long been pursued as a therapeutic strategy to tackle cancer. Unfortunately, however, none of the first-generation CDK inhibitors has yielded the expected efficacy to be successfully translated to the clinic mostly because, by targeting the very conserved kinase ATP-binding site resulted to be poorly specific and quite toxic.

AREAS COVERED

Here, the authors review recent approaches aimed at developing more specific CDK inhibitors mostly through the aid of computational drug design studies and report various small molecules and peptides, which resulted in promising CDK ATP-noncompetitive inhibitors.

EXPERT OPINION

Despite few successes, these new approaches still need additional considerations to generate effective antitumoral agents. The authors discuss some of the hurdles to overcome for a successful clinical translation.

Extra precision docking, free energy calculation and molecular dynamics simulation studies of CDK2 inhibitors

Molecular docking, free energy calculation and molecular dynamics (MD) simulation studies have been performed, to explore the putative binding modes of 3,5-diaminoindazoles, imidazo(1,2-b)pyridazines and triazolo(1,5-a) pyridazines series of Cyclin-dependent kinase (CDK2) inhibitors. To evaluate the effectiveness of docking protocol in flexible docking, we have selected crystallographic bound compound to validate our docking procedure as evident from root mean square deviations (RMSDs). We found different binding sites namely catalytic, inhibitory phosphorylation, cyclin binding and CKS-binding site of the CDK2 contributing towards the binding of these compounds. Moreover, correlation between free energy of binding and biological activity yielded a statistically significant correlation coefficient. Finally, three representative protein-ligand complexes were subjected to molecular dynamics simulation to determine the stability of the predicted conformations. The low value of the RMSDs between the initial complex structure and the energy minimized final average complex structure suggests that the derived docked complexes are close to equilibrium. We suggest that the phenylacetyl type of substituents and cyclohexyl moiety make the favorable interactions with a number of residues in the active site, and show better inhibitory activity to improve the pharmacokinetic profile of compounds against CDK2. The structure-based drug design strategy described in this study will be highly useful for the development of new inhibitors with high potency and selectivity.

Pharmacophore Identification, Molecular Docking, Virtual Screening, and In Silico ADME Studies of Non-Nucleoside Reverse Transcriptase Inhibitors

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) have gained a definitive place due to their unique antiviral potency, high specificity and low toxicity in antiretroviral combination therapies used to treat HIV. In this study, chemical feature based pharmacophore models of different classes of NNRT inhibitors of HIV-1 have been developed. The best HypoRefine pharmacophore model, Hypo 1, which has the best correlation coefficient (0.95) and the lowest RMS (0.97), contains two hydrogen bond acceptors, one hydrophobic and one ring aromatic feature, as well as four excluded volumes. Hypo 1 was further validated by test set and Fischer validation method. The best pharmacophore model was then utilized as a 3D search query to perform a virtual screening to retrieve potential inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies by Libdock and Gold methods to refine the retrieved hits. Finally, 7 top ranked compounds based on Gold score fitness function were subjected to in silico ADME studies to investigate for compliance with the standard ranges.

An alphabetic code based atomic level molecular similarity search in databases

Atomic level molecular similarity and diversity studies have gained considerable importance through their wide application in Bioinformatics and Chemo-informatics for drug design. The availability of large volumes of data on chemical compounds requires new methodologies for efficient and effective searching of its archives in less time with optimal computational power. We describe an alphabetic algorithm for similarity searching based on atom-atom bonding preference for ligands. We represented 170 cyclindependent kinase 2 inhibitors using strings of pre-defined alphabets for searching using known protein sequence alignment tools. Thus, a common pattern was extracted using this set of compounds for database searching to retrieve similar active compounds. Area under the receiver operating characteristic (ROC) curve was used for the discrimination of similar and dissimilar compounds in the databases. An average retrieval rate of about 60% is obtained in cross-validation using the home-grown dataset and the directory of useful decoys (DUD, formally known as the ZINC database) data. This will help in the effective retrieval of similar compounds using database search.

One-Pot Synthesis of Thiazolo[3,2-α]Pyridine Derivatives Catalysed by Ionic Liquids

A green method for the synthesis of thiazolo[3,2-α]pyridine derivatives via the coupling of malononitrile, an aryl aldehyde and methyl thioglycolate in an ionic liquid has been developed. The advantages of this protocol are that it is non-toxic, no by-products are formed, short reaction times are required and high yields are obtained. Thiazolo [3,2-α]pyridines have important biological and medical applications.

PhDD: a new pharmacophore-based de novo design method of drug-like molecules combined with assessment of synthetic accessibility

This account describes a new pharmacophore-based de novo design method of drug-like molecules (PhDD). The method PhDD first generates a set of new molecules that completely conform to the requirements of a given pharmacophore model, followed by a series of assessments to the generated molecules, including assessments of drug-likeness, bioactivity, and synthetic accessibility. PhDD is tested on three typical examples, namely, pharmacophore hypotheses of histone deacetylase (HDAC), cyclin-dependent kinase 2 (CDK2) and HIV-1 integrase (IN) inhibitors. The test results demonstrate that PhDD is able to generate molecules with novel structures but having similar biological functions with existing inhibitors. The validity of PhDD together with its ability of assessing synthetic accessibility makes it a useful tool in rational drug design.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Pharmacophore modeling studies of type I and type II kinase inhibitors of Tie2

In this study, chemical feature based pharmacophore models of type I and type II kinase inhibitors of Tie2 have been developed with the aid of HipHop and HypoRefine modules within Catalyst program package. The best HipHop pharmacophore model Hypo1_I for type I kinase inhibitors contains one hydrogen-bond acceptor, one hydrogen-bond donor, one general hydrophobic, one hydrophobic aromatic, and one ring aromatic feature. And the best HypoRefine model Hypo1_II for type II kinase inhibitors, which was characterized by the best correlation coefficient (0.976032) and the lowest RMSD (0.74204), consists of two hydrogen-bond donors, one hydrophobic aromatic, and two general hydrophobic features, as well as two excluded volumes. These pharmacophore models have been validated by using either or both test set and cross validation methods, which shows that both the Hypo1_I and Hypo1_II have a good predictive ability. The space arrangements of the pharmacophore features in Hypo1_II are consistent with the locations of the three portions making up a typical type II kinase inhibitor, namely, the portion occupying the ATP binding region (ATP-binding-region portion, AP), that occupying the hydrophobic region (hydrophobic-region portion, HP), and that linking AP and HP (bridge portion, BP). Our study also reveals that the ATP-binding-region portion of the type II kinase inhibitors plays an important role to the bioactivity of the type II kinase inhibitors. Structural modifications on this portion should be helpful to further improve the inhibitory potency of type II kinase inhibitors.

Synthesis and evaluation of pyrazolo[1,5-b]pyridazines as selective cyclin dependent kinase inhibitors

A novel series of pyrazolo[1,5-b]pyridazines have been synthesized and identified as cyclin dependant kinase inhibitors potentially useful for the treatment of solid tumors. Modification of the hinge-binding amine or the C(2)- and C(6)-substitutions on the pyrazolopyridazine core provided potent inhibitors of CDK4 and demonstrated enzyme selectivity against VEGFR-2 and GSK3beta.

Identification of novel cannabinoid CB1 receptor antagonists by using virtual screening with a pharmacophore model

CB1 receptor antagonists have proven to be clinically effective in treating obesity and related disorders. We report here the identification of a novel class of azetidinone CB1 antagonists by using virtual screening methods. For this purpose, we developed a pharmacophore model based on known representative CB1 antagonists and employed it to screen a database of about a half million Schering-Plough compounds. We applied a stepwise filtering protocol based on molecular weight, compound availability, and a modified rule-of-five to reduce the number of hits. We then combined Bayesian modeling and clustering techniques to select a final set of 420 compounds for in vitro testing. Five compounds were found to have >50% inhibition at 100 nM in a CB1 competitive binding assay and were further characterized by using both CB1 and CB2 assays. The most potent compound has a CB1 K i of 53 nM and >5-fold selectivity against the CB2 receptor.