Discovery of novel fatty acid synthase (FAS) inhibitors based on the structure of ketoaceyl synthase (KS) domain

Development of fatty acid synthase (FAS) inhibitors has increasingly attracted much attention in recent years due to their potential therapeutic use in obesity and cancers. In this investigation, pharmacophore modeling based on the first crystal structure of human KS domain of FAS was carried out. The established pharmacophore model was taken as a 3D query for retrieving potent FAS inhibitors from the chemical database Specs. Docking study was further carried out to refine the obtained hit compounds. Finally, a total of 28 compounds were selected based on the ranking order and visual examination, which were first evaluated by a cell line-based assay. Seven compounds that have good inhibition activity against two FAS overexpressing cancer cell lines were further evaluated by an enzyme-based assay. One compound with a new chemical scaffold was found to have low micromolar inhibition potency against FAS, which has been subjected to further chemical structural modification.     

Pharmacophore modeling and in silico screening for new KDR kinase inhibitors

In order to elucidate the essential structural features for KDR kinase inhibitors, three-dimensional pharmacophore hypotheses were built on the basis of a set of known KDR kinase inhibitors selected from the literature with CATALYST program. Several methods tools used in validation of pharmacophore hypothsis were presented, and the first hypothesis (Hypo1) was considered to be the best pharmacophore hypothesis. The model (Hypo1) was then employed as 3D search query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit illustrated high binding affinity with KDR kinase measured by the surface plasmon resonance biosensor. Docking studies may help elucidate the mechanisms of KDR kinase receptor-ligand interactions.     

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer’s randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski’s rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation.     

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r?=?0.96) and Fisher’s randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski’s rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.     

Ligand-based and e-pharmacophore modeling, 3D-QSAR and hierarchical virtual screening to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3)

The clinical efficacy of multiple kinase inhibitors has caught the interest of Pharmaceutical and Biotech researchers to develop potential drugs with multi-kinase inhibitory activity for complex diseases. In the present work, we attempted to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3), keys players in immune signaling, by developing ideal pharmacophores integrating Ligand-based pharmacophore models (LBPMs) and Structure-based pharmacophore models (SBPMs), thereby projecting the optimum pharmacophoric required for inhibition of both the kinases. The four point LBPM; ADPR.14 suggested the presence of one hydrogen bond acceptor, one hydrogen bond donor, one positive ionizable, and one ring aromatic feature for Syk inhibitory activity and AADH.54 proposed the necessity of two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature for JAK3 inhibitory activity. To our interest, SBPMs identified additional ring aromatic features required for inhibition of both the kinases. For Syk inhibitory activity, the hydrogen bond acceptor feature indicated by LBPM was devoid of forming hydrogen bonding interaction with the hinge region amino acid residue (Ala451). Thus merging the information revealed by both LBPMs and SBPMs, ideal pharmacophore models i.e. ADPRR.14 (Syk) and AADHR.54 (JAK3) were generated. These models after rigorous statistical validation were used for screening of Asinex database. The systematic virtual screening protocol, including pharmacophore and docking-based screening, ADME property, and MM-GBSA energy calculations, retrieved final 10 hits as dual inhibitors of Syk and JAK3. Final 10 hits thus obtained can aid in the development of potential therapeutic agents for autoimmune disorders. Also the top two hits were evaluated against both the enzymes.     

Novel GSK-3beta inhibitors from sequential virtual screening

Glycogen synthase kinase-3 (GSK-3beta) has been emerging as a key therapeutic target for type-2 diabetics, Alzheimer's disease, cancer, and chronic inflammation. For the purpose of finding biologically active and novel compounds and providing new idea for drug-design, we performed virtual screening using commercially available database. Three-dimensional common feature pharmacophore model was developed by using HipHop program provided in Catalyst software and it was used as a query for screening database. Recursive partitioning (RP) model was developed as a filtering system, which was able to classify active and inactive compounds. Eventually, a sequential virtual screening procedure (SQSP) was conducted by applying the common feature pharmacophore and RP model in succession to discover novel potent GSK-3beta inhibitors. The final 56 hit compounds were carefully selected considering predicted docking mode in crystal structures. Subsequent enzyme assay for human GSK-3beta protein confirmed that three compounds of these hit compounds exhibit micromolar inhibitory activity. Here, we report novel hit compounds and their binding mode in the active site of GSK-3beta crystal structure.     

Discovery of dual ZAP70 and Syk kinases inhibitors by docking into a rare C-helix-out conformation of Syk

The non-receptor tyrosine kinase Syk (spleen tyrosine kinase) is a pharmaceutical relevant target because its over-activation is observed in several autoimmune diseases, allergy, and asthma. Here we report the identification of two novel inhibitors of Syk by high-throughput docking into a rare C-helix-out conformation published recently. Interestingly, both compounds are slightly more active on ZAP70 (Zeta-chain-associated protein kinase 70), which is the kinase closest to Syk in the phylogenetic tree of human kinases. Taken together, the docking pose and experimental results suggest that the higher affinity of the inhibitors for ZAP70 than Syk originates from a more populated C-helix-out conformation in ZAP70. The latter observation is congruent with the 100-fold lower intrinsic activity of ZAP70 than Syk, as the C-helix-out conformation is inactive. The pharmacophore features of DFG-in, C-helix-out compounds are analyzed in relation to DFG-out inhibitors.     

Pharmacophore and Virtual Screening of JAK3 inhibitors

Janus kinase 3 (JAK3) is a non-receptor tyrosine kinases family of protein which is comprised of JAK1, JAK2, JAK3 and TYK2. It plays an important role in immune function and lymphoid development and it only resides in the hematopoietic system. Therefore, selective targeting JAK3 is a rational approach in developing new therapeutic molecule. In this study, about 116 JAK3 inhibitors were collected from the literature and were used to build four-point pharmacophore model using Phase (Schrodinger module). The statistically significant pharmacophore hypothesis of AAHR.92 with r2 value of 0.942 was used as 3D query to search against 3D database namely Zincpharmer. A total of 2, 27,483 compounds obtained as hit were subjected to high throughput virtual screening (HTVS module of Schrodinger). Among the hits, ten compounds with good G-score ranging from -12.96 to -11.18 with good binding energy to JAK3 were identified.     

Pharmacophore modeling and virtual screening for designing potential 5-Lipoxygenase inhibitors

Inhibitors of the 5-Lipoxygenase (5-LOX) pathway have a therapeutic potential in a variety of inflammatory disorders such as asthma. In this study, chemical feature based pharmacophore models of inhibitors of 5-LOX have been developed with the aid of HipHop and HypoGen modules within Catalyst program package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.97), consists of two hydrogen-bond acceptors, one hydrophobic feature and one ring aromatic feature. Hypo1 was further validated by test set and cross validation method. The application of the model shows great success in predicting the activities of 65 known 5-LOX inhibitors in our test set with a correlation coefficient of 0.85 with a cross validation of 95% confidence level, proving that the model is reliable in identifying structurally diverse compounds for inhibitory activity against 5-LOX. Furthermore, Hypo1 was used as a 3D query for screening Maybridge and NCI databases within catalyst and also drug like compounds obtained from Enamine Ltd, which follow Lipinski’s rule of five. The hit compounds were subsequently subjected to filtering by docking and visualization, to identify the potential lead molecules. Finally 5 potential lead compounds, identified in the above process, were evaluated for their inhibitory activities. These studies resulted in the identification of two compounds with potent inhibition of 5-LOX activity with IC₅₀ of 14 μM and 35 μM, respectively. These studies thus validate the pharmacophore model generated and suggest the usefulness of the model in screening of various small molecule libraries and identification of potential lead compounds for 5-LOX inhibition.     

Pharmacophore modeling and hybrid virtual screening for the discovery of novel IκB kinase 2 (IKK2) inhibitors

IKK2 (IκB kinase 2) inhibitors have been identified as potential drug candidates in the treatment of various immune/inflammatory disorders as well as cancer. So far more than one hundred small molecule inhibitors against IKK2 have been reported publicly. In this investigation, pharmacophore modeling was carried out to clarify the essential structure-activity relationship for the known IKK2 inhibitors. One of the established pharmacophore hypotheses, namely Hypo8, which has the best prediction ability to an external test data set, was suggested as a template for virtual screening. Evaluation of the performances of Hypo8 and a hybrid method (Hypo81docking) in virtual screening indicated that the use of the hybrid virtual screening considerably increased the hit rate and enrichment factor. The hybrid method was therefore adopted for screening several commercially available chemical databases, including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD), for novel potent IKK2 inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five. Finally some of the final hit compounds were selected and suggested for further experimental investigations.     

Discovery of potential pancreatic cholesterol esterase inhibitors using pharmacophore modelling, virtual screening, and optimization studies

Pancreatic cholesterol esterase (CEase) is a serine hydrolase involved in the hydrolysis of variety of lipids and transport of free cholesterol. In this study, pharmacophore hypotheses based on known inhibitors were generated using common feature pharmacophore generation protocol available in Discovery Studio program. The best pharmacophore model containing two hydrogen bond acceptor and three hydrophobic features was selected and validated. It was further used in screening three diverse chemical databases. Hit compounds were subjected to drug-likeness and molecular docking studies. Four hits, namely SEW00846, NCI0040784, GK03167, and CD10645, were selected based on the GOLD fitness score and interaction with active site amino acids. All hit compounds were further optimized to improve their binding in the active site. The optimized compounds were found to have improved binding at the active site. Strongly binding optimized hits at the active site can act as virtual leads in potent CEase inhibitor designing.     

Discovery of Potent ALK Inhibitors Using Pharmacophore-Informatics Strategy

Anaplastic lymphoma kinase is a tyrosine kinase receptor protein belonging to insulin receptor superfamily. Gene fusions in anaplastic lymphoma kinase are associated with non-small cell lung cancer development. Hence, they are of immense importance in targeted therapies. Thus, for the treatment of non-small cell lung cancer, effective anaplastic lymphoma kinase inhibitors are of great significance. Therefore, our objective is to find hit compounds that could have better inhibitory activity than the existing anaplastic lymphoma kinase inhibitors. Keeping this in mind, in the present study pharmacophore based virtual screening was performed to identify possible anaplastic lymphoma kinase inhibitors. Initially, a five-point common pharmacophore hypothesis was generated based on twelve anaplastic lymphoma kinase inhibitors using PHASE module of Schrödinger. Subsequently, common pharmacophore hypothesis-based screening was conducted against in-trials subset of ZINC database and a total of 1000 hits were identified. The molecules obtained were further screened by three stages of docking using GLIDE software. The docking results reveal that six hit molecules showed higher glide score in comparison with the reference molecules. Finally, pharmacokinetic properties of the hit molecules were also analysed using QikProp programme. The results indicate that molecules namely videx, dexecadotril, chloramphenicol, naficillin were found to have good pharmacokinetic properties and human oral absorption. Moreover, videx, naficillin and chloramphenicol were found to have significant inhibitory activity for mutant (F1174L) anaplastic lymphoma kinase. It was also found that videx exhibited crucial interactions with the Met1199 residue of the native and mutant anaplastic lymphoma kinase protein. Furthermore, PASS algorithm predicted anti-neoplastic activity for all the four molecules. Thus these hits are found to be promising leads for anaplastic lymphoma kinase inhibitors. We believe that this study will be useful for the discovery and designing of more potent anaplastic lymphoma kinase inhibitors in the near future.     

Synthetic studies on novel Syk inhibitors. Part 1: Synthesis and structure-activity relationships of pyrimidine-5-carboxamide derivatives

Spleen tyrosine kinase (Syk) is a non-receptor-type tyrosine kinase which mediates diverse responses in haematopoietic cells. Therefore, Syk is an attractive therapeutic target, and in a study of Syk inhibitors as potentially new therapeutic agents, we discovered the 4-anilinopyrimidine-5-carboxamides. Enzyme screening indicated that an aminoethylamino moiety at the 2-position of the pyrimidine ring was important for Syk inhibitory activity, and an investigation of the substituents at the 4-position revealed that an anilino moiety substituted at the meta position was preferred. These compounds showed high selectivity for Syk, compared to other kinases, such as ZAP-70, c-Src, and PKC, and exhibited good inhibitory activities against 5-HT release from RBL-cells. Among them, compound 9a inhibited the passive cutaneous anaphylaxis reaction in mice, with an ID50 of 13 mg/kg following subcutaneous administration. These results suggest that our compounds are worthy of further evaluation as new anti-allergic agents.     

Pharmacophore-based discovery of 2-(phenylamino)aceto-hydrazides as potent eosinophil peroxidase (EPO) inhibitors

There is an increasing interest in developing novel eosinophil peroxidase (EPO) inhibitors, in order to provide new treatment strategies against chronic inflammatory and neurodegenerative diseases caused by eosinophilic disorder. Within this study, a ligand-based pharmacophore model for EPO inhibitors was generated and used for in silico screening of large 3?D molecular structure databases, containing more than 4 million compounds. Hits obtained were clustered and a total of 277 compounds were selected for biological assessment. A class of 2-(phenyl)amino-aceto-hydrazides with different substitution pattern on the aromatic ring was found to contain the most potent EPO inhibitors, exhibiting IC₅₀ values down to 10?nM. The generated pharmacophore model therefore, represents a valuable tool for the selection of compounds for biological testing. The compounds identified as potent EPO inhibitors will serve to initiate a hit to lead and lead optimisation program for the development of new therapeutics against eosinophilic disorders.     

Discovery and evaluation of potential sonic hedgehog signaling pathway inhibitors using pharmacophore modeling and molecular dynamics simulations

Sonic hedgehog (Shh) plays an important role in the activation of Shh signaling pathway that regulates preservation and rebirth of adult tissues. An abnormal activation of this pathway has been identified in hyperplasia and various tumorigenesis. Hence the inhibition of this pathway using a Shh inhibitor might be an efficient way to treat a wide range of malignancies. This study was done in order to develop a lead chemical candidate that has an inhibitory function in the Shh signaling pathway. We have generated common feature pharmacophore models using three-dimensional (3D) structural information of robotnikinin, an inhibitor of the Shh signaling pathway, and its analogs. These models have been validated with fit values of robotnikinin and its analogs, and the best model was used as a 3D structural query to screen chemical databases. The hit compounds resulted from the screening docked into a proposed binding site of the Shh named pseudo-active site. Molecular dynamics (MD) simulations were performed to investigate detailed binding modes and molecular interactions between the hit compounds and functional residues of the pseudo-active site. The results of the MD simulation analyses revealed that the hit compounds can bind the pseudo-active site with high affinity than robotnikinin. As a result of this study, a candidate inhibitor (GK 03795) was selected as a potential lead to be employed in future Shh inhibitor design.     

Exploration of Virtual Candidates for Human HMG-CoA Reductase Inhibitors Using Pharmacophore Modeling and Molecular Dynamics Simulations

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.     

Uncovering false positives on a virtual screening search for cruzain inhibitors

Some unexpected promiscuous inhibitors were observed in a virtual screening protocol applied to select cruzain inhibitors from the ZINC database. Physical-chemical and pharmacophore model filters were used to reduce the database size. The selected compounds were docked into the cruzain active site. Six hit compounds were tested as inhibitors. Although the compounds were designed to be nucleophilically attacked by the catalytic cysteine of cruzain, three of them showed typical promiscuous behavior, revealing that false positives are a prevalent concern in VS programs.     

Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors

Pharmacophore models of Polo-like kinase-1 (PLK1) inhibitors have been established by using the HipHop and HypoGen algorithms implemented in the Catalyst software package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9895), consists of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic feature, and one hydrophobic aliphatic feature. Hypo1 was further validated by test set and cross validation method. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, a total of 20 compounds were selected and have been shifted to in vitro and in vivo studies. As far as we know, this is the first report on the pharmacophore modeling even the first publicly reported virtual screening study of PLK1 inhibitors.     

X-ray crystallographic structure-based design of selective thienopyrazole inhibitors for interleukin-2-inducible tyrosine kinase

Beginning with a screening hit, unique thienopyrazole-indole inhibitors of Itk (interleukin-2-inducible tyrosine kinase) were designed, synthesized, and crystallized in the target kinase. Although initial compounds were highly active in Itk, they were not selective. Increasing the steric bulk around a tertiary alcohol at the 5-indole position dramatically improved selectivity toward Lyk and Syk, but not Txk. Substitutions at the 3- and 4-indole positions gave less active compounds that remained poorly selective. A difluoromethyl substitution at the 5-position of the thienopyrazole led to a highly potent and selective compound. Phenyl at this position reduced activity and selectivity while pushing the side-chains of Lys-391 and Asp-500 away from the binding pocket. Novel and selective thienopyrazole inhibitors of Itk were designed as a result of combining structure-based design and medicinal chemistry.     

Tyrosine kinase syk non-enzymatic inhibitors and potential anti-allergic drug-like compounds discovered by virtual and in vitro screening

In the past decade, the spleen tyrosine kinase (Syk) has shown a high potential for the discovery of new treatments for inflammatory and autoimmune disorders. Pharmacological inhibitors of Syk catalytic site bearing therapeutic potential have been developed, with however limited specificity towards Syk. To address this topic, we opted for the design of drug-like compounds that could impede the interaction of Syk with its cellular partners while maintaining an active kinase protein. To achieve this challenging task, we used the powerful potential of intracellular antibodies for the modulation of cellular functions in vivo, combined to structure-based in silico screening. In our previous studies, we reported the anti-allergic properties of the intracellular antibody G4G11. With the aim of finding functional mimics of G4G11, we developed an Antibody Displacement Assay and we isolated the drug-like compound C-13, with promising in vivo anti-allergic activity. The likely binding cavity of this compound is located at the close vicinity of G4G11 epitope, far away from the catalytic site of Syk. Here we report the virtual screen of a collection of 500,000 molecules against this new cavity, which led to the isolation of 1000 compounds subsequently evaluated for their in vitro inhibitory effects using the Antibody Displacement Assay. Eighty five compounds were selected and evaluated for their ability to inhibit the liberation of allergic mediators from mast cells. Among them, 10 compounds inhibited degranulation with IC₅₀ values ≤10 µM. The most bioactive compounds combine biological activity, significant inhibition of antibody binding and strong affinity for Syk. Moreover, these molecules show a good potential for oral bioavailability and are not kinase catalytic site inhibitors. These bioactive compounds could be used as starting points for the development of new classes of non-enzymatic inhibitors of Syk and for drug discovery endeavour in the field of inflammation related disorders.