Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques

c-Yes kinase is considered as one of the attractive targets for anti-cancer drug design. The DFG (Asp-Phe-Gly) motif present in most of the kinases will adopt active and inactive conformations, known as DFG-in and DFG-out and their inhibitors are classified into type I and type II, respectively. In the present study, two screening protocols were followed for identification of c-Yes kinase inhibitors. (i) Structure-based virtual screening (SBVS) and (ii) Structure-based (SB) and Pharmacophore-based (PB) tandem screening. In SBVS, the c-Yes kinase structure was obtained from homology modeling and seven ensembles with different active site scaffolds through molecular dynamics (MD) simulations. For SB-PB tandem screening, we modeled ligand bound active and inactive conformations. Physicochemical properties of inhibitors of Src kinase family and c-Yes kinase were used to prepare target focused libraries for screenings. Our screening procedure along with docking showed 520 probable hits in SBVS and tandem screening (120 and 400, respectively). Out of 5000 compounds identified from different computational methods, 2410 were examined using kinase inhibition assays. It includes 266 compounds (5.32%) identified from our method. We observed that 14 compounds (12%) are identified by the present method out of 168 that showed > 30% inhibition. Among them, three compounds are novel, unique, and showed good inhibition. Further, we have studied the binding of these compounds at the DFG-in and DFG-out conformations and reported the probable class (type I or type II). Hence, we suggest that these compounds could be novel drug leads for regulation of colorectal cancer.     

High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.     

Combinatorial computational approaches to identify tetracycline derivatives as flavivirus inhibitors

Limited structural information of drug targets, cellular toxicity possessed by lead compounds, and large amounts of potential leads are the major issues facing the design-oriented approach of discovering new leads. In an attempt to tackle these issues, we have developed a process of virtual screening based on the observation that conformational rearrangements of the dengue virus envelope protein are essential for the mediation of viral entry into host cells via membrane fusion. Screening was based solely on the structural information of the Dengue virus envelope protein and was focused on a target site that is presumably important for the conformational rearrangements necessary for viral entry. To circumvent the issue of lead compound toxicity, we performed screening based on molecular docking using structural databases of medical compounds. To enhance the identification of hits, we further categorized and selected candidates according to their novel structural characteristics. Finally, the selected candidates were subjected to a biological validation assay to assess inhibition of Dengue virus propagation in mammalian host cells using a plaque formation assay. Among the 10 compounds examined, rolitetracycline and doxycycline significantly inhibited plaque formation, demonstrating their inhibitory effect on dengue virus propagation. Both compounds were tetracycline derivatives with IC(50)s estimated to be 67.1 microM and 55.6 microM, respectively. Their docked conformations displayed common hydrophobic interactions with critical residues that affected membrane fusion during viral entry. These interactions will therefore position the tetracyclic ring moieties of both inhibitors to bind firmly to the target and, subsequently, disrupt conformational rearrangement and block viral entry. This process can be applied to other drug targets in which conformational rearrangement is critical to function.     

Docking and scoring with alternative side-chain conformations

We describe a scoring and modeling procedure for docking ligands into protein models that have either modeled or flexible side-chain conformations. Our methodical contribution comprises a procedure for generating new potentials of mean force for the ROTA scoring function which we have introduced previously for optimizing side-chain conformations with the tool IRECS. The ROTA potentials are specially trained to tolerate small-scale positional errors of atoms that are characteristic of (i) side-chain conformations that are modeled using a sparse rotamer library and (ii) ligand conformations that are generated using a docking program. We generated both rigid and flexible protein models with our side-chain prediction tool IRECS and docked ligands to proteins using the scoring function ROTA and the docking programs FlexX (for rigid side chains) and FlexE (for flexible side chains). We validated our approach on the forty screening targets of the DUD database. The validation shows that the ROTA potentials are especially well suited for estimating the binding affinity of ligands to proteins. The results also show that our procedure can compensate for the performance decrease in screening that occurs when using protein models with side chains modeled with a rotamer library instead of using X-ray structures. The average runtime per ligand of our method is 168 seconds on an Opteron V20z, which is fast enough to allow virtual screening of compound libraries for drug candidates.     

Systematic exploitation of multiple receptor conformations for virtual ligand screening

The role of virtual ligand screening in modern drug discovery is to mine large chemical collections and to prioritize for experimental testing a comparatively small and diverse set of compounds with expected activity against a target. Several studies have pointed out that the performance of virtual ligand screening can be improved by taking into account receptor flexibility. Here, we systematically assess how multiple crystallographic receptor conformations, a powerful way of discretely representing protein plasticity, can be exploited in screening protocols to separate binders from non-binders. Our analyses encompass 36 targets of pharmaceutical relevance and are based on actual molecules with reported activity against those targets. The results suggest that an ensemble receptor-based protocol displays a stronger discriminating power between active and inactive molecules as compared to its standard single rigid receptor counterpart. Moreover, such a protocol can be engineered not only to enrich a higher number of active compounds, but also to enhance their chemical diversity. Finally, some clear indications can be gathered on how to select a subset of receptor conformations that is most likely to provide the best performance in a real life scenario.     

Virtual screening of a natural compound library at orthosteric and allosteric binding sites of the neurotensin receptor

Abstract

Molecular dynamics (MD) simulation using the AMBER force field has been performed on the neurotensin (NT) receptor, a class A type G-protein-coupled receptor in its activated conformation co-crystallized with the non-peptide agonists. For structure-based hit molecule identification via natural chemical compound library, orthosteric sites on NT receptor have been mapped by docking using AutoDock4.0 and Vina with the known agonists and antagonists SR48692, SR142948, ML301 and ML314 of the receptor. Furthermore, clustering analysis on the MD trajectories by SIMULAID has been performed to filter receptor conformations for the allosteric binders from the Otava natural compound library. Comparative mappings of contrasting binding region patterns have been done between the crystal structure orthosteric sites as well as the binding regions in the SIMULAID-based cluster center conformations from MD trajectories with the FTmap server using the small organic molecule fragments as the probes. The distinct binding region in the cluster-based conformations in the extracellular region of the receptor has been identified for targeted docking by Otava natural chemical compound library using AutoDock4.0 and Vina docking suites to obtain putative allosteric binders. A group of compounds from the Otava library has been identified as showing high free energy in both AutoDock4.0 and Vina docking suites. Biophysical assessments on the natural compound computational hit molecules will be done to identify lead structures from the hit molecules.

Communicated by Ramaswamy H. Sarma     

Identification of novel chemical inhibitors for ubiquitin C-terminal hydrolase-L3 by virtual screening

UCH-L3 (ubiquitin C-terminal hydrolase-L3) is a de-ubiquitinating enzyme that is a component of the ubiquitin-proteasome system and known to be involved in programmed cell death. A previous study of high-throughput drug screening identified an isatin derivative as a UCH-L3 inhibitor. In this study, we attempted to identify a novel inhibitor with a different structural basis. We performed in silico structure-based drug design (SBDD) using human UCH-L3 crystal structure data (PDB code; 1XD3) and the virtual compound library (ChemBridge CNS-Set), which includes 32,799 chemicals. By a two-step virtual screening method using DOCK software (first screening) and GOLD software (second screening), we identified 10 compounds with GOLD scores of over 60. To address whether these compounds exhibit an inhibitory effect on the de-ubiquitinating activity of UCH-L3, we performed an enzymatic assay using ubiquitin-7-amido-4-methylcoumarin (Ub-AMC) as the substrate. As a result, we identified three compounds with similar basic dihydro-pyrrole skeletons as UCH-L3 inhibitors. These novel compounds may be useful for the research of UCH-L3 function, and in drug development for UCH-L3-associated diseases.     

In silico multi-filter screening approaches for developing novel beta-secretase inhibitors

A large database of chemical structures was screened for potential inhibitors of β-secretase was carried out using in silico multi-filter techniques. Substructure screening, computer-aided ligand docking, binding free energy calculations, and partial interaction energy analyses were performed successively to identify chemical compounds which could serve as different scaffolds from known β-secretase inhibitors for future drug design. We showed that our in silico multi-filter screening retrieved all known inhibitors from the compound database investigated, which suggests that the other compounds identified as inhibitors by this computerized screening process are potential β-secretase inhibitors.     

Sulphated tyrosines mediate association of chemokines and Plasmodium vivax Duffy binding protein with the Duffy antigen/receptor for chemokines (DARC)

Plasmodium vivax is one of four Plasmodium species that cause human malaria. P. vivax and a related simian malaria parasite, Plasmodium knowlesi, invade erythrocytes by binding the Duffy antigen/receptor for chemokines (DARC) through their respective Duffy binding proteins. Here we show that tyrosines 30 and 41 of DARC are modified by addition of sulphate groups, and that the sulphated tyrosine 41 is essential for association of the Duffy binding proteins of P. vivax (PvDBP) and P. knowlesi (PkDaBP) with DARC-expressing cells. These sulphated tyrosines also participate in the association of DARC with each of its four known chemokine ligands. Alteration of tyrosine 41 to phenylalanine interferes with MCP-1, RANTES and MGSA association with DARC, but not with that of IL8. In contrast, alteration of tyrosine 30 to phenylalanine interferes with the association of IL8 with DARC. A soluble sulphated amino-terminal domain of DARC, but not one modified to phenylalanine at residue 41, can be used to block the association of PvDBP and PkDaBP with red blood cells, with an IC50 of approximately 5 nM. These data are consistent with a role for tyrosine sulphation in the association of many or most chemokines with their receptors, and identify a key molecular determinant of erythrocyte invasion by P. vivax.     

Development of a fluorescence polarization bead-based coupled assay to target different activity/conformation states of a protein kinase

Most of the protein kinase inhibitors being developed are directed toward the adenosine triphosphate (ATP) binding site that is highly conserved in many kinases. A major issue with these inhibitors is the specificity for a given kinase. Structure determination of several kinases has shown that protein kinases adopt distinct conformations in their inactive state, in contrast to their strikingly similar conformations in their active states. Hence, alternative assay formats that can identify compounds targeting the inactive form of a protein kinase are desirable. The authors describe the development and optimization of an Immobilized Metal Assay for Phosphochemicals (IMAP)-based couple d assay using PDK1 and inactive Akt-2 enzymes. PDK1 phosphorylates Akt-2 at Thr 309 in the catalytic domain, leading to enzymatic activation. Activation of Akt by PDK1 is measured by quantitating the phosphorylation of Akt-specific substrate peptide using the IMAP assay format. This IMAP-coupled assay has been formatted in a 384-well microplate format with a Z' of 0.73 suitable for high-throughput screening. This assay was evaluated by screening the biologically active sample set LOPAC trade mark and validated with the protein kinase C inhibitor staurosporine. The IC(50) value generated was comparable to the value obtained by the radioactive (33)P-gamma-ATP flashplate transfer assay. This coupled assay has the potential to identify compounds that target the inactive form of Akt and prevent its activation by PDK1, in addition to finding inhibitors of PDK1 and activated Akt enzymes.     

Application of a homogenous membrane potential assay to assess mitochondrial function

Decreases in mitochondrial membrane potential (MMP) have been associated with mitochondrial dysfunction that could lead to cell death. The MMP is generated by an electrochemical gradient via the mitochondrial electron transport chain coupled to a series of redox reactions. Measuring the MMP in living cells is commonly used to assess the effect of chemicals on mitochondrial function; decreases in MMP can be detected using lipophilic cationic fluorescent dyes. To identify an optimal dye for use in a high-throughput screening (HTS) format, we compared the ability of mitochondrial membrane potential sensor (Mito-MPS), 5,5',6,6'-tetrachloro-1,1',3,3' tetraethylbenzimidazolylcarbocyanine iodide, rhodamine 123, and tetramethylrhodamine to quantify a decrease in MMP in chemically exposed HepG2 cells cultured in 1,536-well plates. Under the conditions used, the optimal dye for this purpose is Mito-MPS. Next, we developed and optimized a homogenous cell-based Mito-MPS assay for use in 1,536-well plate format and demonstrated the utility of this assay by screening 1,280 compounds in the library of pharmacologically active compounds in HepG2 cells using a quantitative high-throughput screening platform. From the screening, we identified 14 compounds that disrupted the MMP, with half-maximal potencies ranging from 0.15 to 18 μM; among these, compound clusters that contained tyrphostin and 3'-substituted indolone analogs exhibited a structure-activity relationship. Our results demonstrate that this homogenous cell-based Mito-MPS assay can be used to evaluate the ability of large numbers of chemicals to decrease mitochondrial function.     

Efficient hit-finding approaches for histone methyltransferases: the key parameters

For many novel epigenetics targets the chemical ligand space and structural information were limited until recently and are still largely unknown for some targets. Hit-finding campaigns are therefore dependent on large and chemically diverse libraries. In the specific case of the histone methyltransferase G9a, the authors have been able to apply an efficient process of intelligent selection of compounds for primary screening, rather than screening the full diverse deck of 900 000 compounds to identify hit compounds. A number of different virtual screening methods have been applied for the compound selection, and the results have been analyzed in the context of their individual success rates. For the primary screening of 2112 compounds, a FlashPlate assay format and full-length histone H3.1 substrate were employed. Validation of hit compounds was performed using the orthogonal fluorescence lifetime technology. Rated by purity and IC(50) value, 18 compounds (0.9% of compound screening deck) were finally considered validated primary G9a hits. The hit-finding approach has led to novel chemotypes being identified, which can facilitate hit-to-lead projects. This study demonstrates the power of virtual screening technologies for novel, therapeutically relevant epigenetics protein targets.     

Analysis of multiple compound–protein interactions reveals novel bioactive molecules

The discovery of novel bioactive molecules advances our systems‐level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound–protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Herein, we demonstrate that machine learning of multiple CPIs can not only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold‐hopping compounds. Through a machine‐learning technique that uses multiple CPIs, we have successfully identified novel lead compounds for two pharmaceutically important protein families, G‐protein‐coupled receptors and protein kinases. These novel compounds were not identified by existing computational ligand‐screening methods in comparative studies. The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.     

PREDICT modeling and in-silico screening for G-protein coupled receptors

G-protein coupled receptors (GPCRs) are a major group of drug targets for which only one x-ray structure is known (the nondrugable rhodopsin), limiting the application of structure-based drug discovery to GPCRs. In this paper we present the details of PREDICT, a new algorithmic approach for modeling the 3D structure of GPCRs without relying on homology to rhodopsin. PREDICT, which focuses on the transmembrane domain of GPCRs, starts from the primary sequence of the receptor, simultaneously optimizing multiple 'decoy' conformations of the protein in order to find its most stable structure, culminating in a virtual receptor-ligand complex. In this paper we present a comprehensive analysis of three PREDICT models for the dopamine D2, neurokinin NK1, and neuropeptide Y Y1 receptors. A shorter discussion of the CCR3 receptor model is also included. All models were found to be in good agreement with a large body of experimental data. The quality of the PREDICT models, at least for drug discovery purposes, was evaluated by their successful utilization in in-silico screening. Virtual screening using all three PREDICT models yielded enrichment factors 9-fold to 44-fold better than random screening. Namely, the PREDICT models can be used to identify active small-molecule ligands embedded in large compound libraries with an efficiency comparable to that obtained using crystal structures for non-GPCR targets.     

Comparison of Microscopy and Alamar Blue Reduction in a Larval Based Assay for Schistosome Drug Screening

Background

In view of the current widespread use of and reliance on a single schistosomicide, praziquantel, there is a pressing need to discover and develop alternative drugs for schistosomiasis. One approach to this is to develop High Throughput in vitro whole organism screens (HTS) to identify hits amongst large compound libraries.

Methodology/Principal Findings

We have been carrying out low throughput (24-well plate) in vitro testing based on microscopic evaluation of killing of ex-vivo adult S. mansoni worms using selected compound collections mainly provided through the WHO-TDR Helminth Drug Initiative. To increase throughput, we introduced a similar but higher throughput 96-well primary in vitro assay using the schistosomula stage which can be readily produced in vitro in large quantities. In addition to morphological readout of viability we have investigated using fluorometric determination of the reduction of Alamar blue (AB), a redox indicator of enzyme activity widely used in whole organism screening. A panel of 7 known schistosome active compounds including praziquantel, produced diverse effects on larval morphology within 3 days of culture although only two induced marked larval death within 7 days. The AB assay was very effective in detecting these lethal compounds but proved more inconsistent in detecting compounds which damaged but did not kill. The utility of the AB assay in detecting compounds which cause severe morbidity and/or death of schistosomula was confirmed in testing a panel of compounds previously selected in library screening as having activity against the adult worms. Furthermore, in prospective library screening, the AB assay was able to detect all compounds which induced killing and also the majority of compounds designated as hits based on morphological changes.

Conclusion

We conclude that an HTS combining AB readout and image-based analysis would provide an efficient and stringent primary assay for schistosome drug discovery.     

High-throughput assay for the identification of Hsp90 inhibitors based on Hsp90-dependent refolding of firefly luciferase

Previously, we have demonstrated that the renaturation of heat denatured firefly luciferase is dependent upon the activity of Hsp90 in rabbit reticulocyte lysate. Here, we demonstrate that this assay may identify inhibitors that obstruct the chaperone activity of Hsp90 either by direct binding to its N-terminal or C-terminal nucleotide binding sites or by interference with the ability of the chaperone to switch conformations. The assay was adapted and optimized for high-throughput screening. Greater than 20,000 compounds were screened to demonstrate the feasibility of using this assay on a large scale. The assay was reproducible (av Z-factor=0.62) and identified 120 compounds that inhibited luciferase renaturation by greater than 70% at a concentration of 12.5 microg/mL. IC50 values for twenty compounds with varying structures were determined for inhibition of luciferase refolding and in cell-based assays for Hsp90 inhibition. Several compounds had IC50 values <10 microM and represent a number of new lead structures with the potential for further development and optimization as potent Hsp90 inhibitors.     

Computational selection of inhibitors of Aβ aggregation and neuronal toxicity

Alzheimer’s disease (AD) is characterized by the cerebral accumulation of misfolded and aggregated amyloid-β protein (Aβ). Disease symptoms can be alleviated, in vitro and in vivo, by ‘β-sheet breaker’ pentapeptides that reduce plaque load. However the peptide nature of these compounds, made them biologically unstable and unable to penetrate membranes with high efficiency. The main goal of this study was to use computational methods to identify small molecule mimetics with better drug-like properties. For this purpose, the docked conformations of the active peptides were used to identify compounds with similar activities. A series of related β-sheet breaker peptides were docked to solid state NMR structures of a fibrillar form of Aβ. The lowest energy conformations of the active peptides were used to design three dimensional (3D)-pharmacophores, suitable for screening the NCI database with Unity. Small molecular weight compounds with physicochemical features and a conformation similar to the active peptides were selected, ranked by docking and biochemical parameters. Of 16 diverse compounds selected for experimental screening, 2 prevented and reversed Aβ aggregation at 2–3 μM concentration, as measured by Thioflavin T (ThT) fluorescence and ELISA assays. They also prevented the toxic effects of aggregated Aβ on neuroblastoma cells. Their low molecular weight and aqueous solubility makes them promising lead compounds for treating AD.     

Identification of Novel Inhibitors of 1-Aminocyclopropane-1-carboxylic Acid Synthase by Chemical Screening in Arabidopsis thaliana

Ethylene is a gaseous hormone important for adaptation and survival in plants. To further understand the signaling and regulatory network of ethylene, we used a phenotype-based screening strategy to identify chemical compounds interfering with the ethylene response in Arabidopsis thaliana. By screening a collection of 10,000 structurally diverse small molecules, we identified compounds suppressing the constitutive triple response phenotype in the ethylene overproducer mutant eto1-4. The compounds reduced the expression of a reporter gene responsive to ethylene and the otherwise elevated level of ethylene in eto1-4. Structure and function analysis revealed that the compounds contained a quinazolinone backbone. Further studies with genetic mutants and transgenic plants involved in the ethylene pathway showed that the compounds inhibited ethylene biosynthesis at the step of converting S-adenosylmethionine to 1-aminocyclopropane-1-carboxylic acid (ACC) by ACC synthase. Biochemical studies with in vitro activity assay and enzyme kinetics analysis indicated that a representative compound was an uncompetitive inhibitor of ACC synthase. Finally, global gene expression profiling uncovered a significant number of genes that were co-regulated by the compounds and aminoethoxyvinylglycine, a potent inhibitor of ACC synthase. The use of chemical screening is feasible in identifying small molecules modulating the ethylene response in Arabidopsis seedlings. The discovery of such chemical compounds will be useful in ethylene research and can offer potentially useful agrochemicals for quality improvement in post-harvest agriculture.     

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.     

Red Blood Cell Invasion by Plasmodium vivax: Structural Basis for DBP Engagement of DARC

Plasmodium parasites use specialized ligands which bind to red blood cell (RBC) receptors during invasion. Defining the mechanism of receptor recognition is essential for the design of interventions against malaria. Here, we present the structural basis for Duffy antigen (DARC) engagement by P. vivax Duffy binding protein (DBP). We used NMR to map the core region of the DARC ectodomain contacted by the receptor binding domain of DBP (DBP-RII) and solved two distinct crystal structures of DBP-RII bound to this core region of DARC. Isothermal titration calorimetry studies show these structures are part of a multi-step binding pathway, and individual point mutations of residues contacting DARC result in a complete loss of RBC binding by DBP-RII. Two DBP-RII molecules sandwich either one or two DARC ectodomains, creating distinct heterotrimeric and heterotetrameric architectures. The DARC N-terminus forms an amphipathic helix upon DBP-RII binding. The studies reveal a receptor binding pocket in DBP and critical contacts in DARC, reveal novel targets for intervention, and suggest that targeting the critical DARC binding sites will lead to potent disruption of RBC engagement as complex assembly is dependent on DARC binding. These results allow for models to examine inter-species infection barriers, Plasmodium immune evasion mechanisms, P. knowlesi receptor-ligand specificity, and mechanisms of naturally acquired P. vivax immunity. The step-wise binding model identifies a possible mechanism by which signaling pathways could be activated during invasion. It is anticipated that the structural basis of DBP host-cell engagement will enable development of rational therapeutics targeting this interaction.