Virtual Hits Research Articles

Characterization of a Structural Leoligin Analog as Farnesoid X Receptor Agonist and Modulator of Cholesterol Transport.

The ligand-activated farnesoid X receptor is an emerging therapeutic target for the development of drugs against metabolic syndrome-related diseases. In this context, selective bile acid receptor modulators represent a novel concept for drug development. Selective bile acid receptor modulators act in a target gene- or tissue-specific way and are therefore considered less likely to elicit unwanted side effects. Based on leoligin, a lignan-type secondary plant metabolite from the alpine plant Leontopodium nivale ssp. alpinum, 168 synthesized structural analogs were screened in a farnesoid X receptor in silico pharmacophore-model. Fifty-six virtual hits were generated. These hits were tested in a cell-based farnesoid X receptor transactivation assay and yielded 7 farnesoid X receptor-activating compounds. The most active one being LT-141A, with an EC50 of 6 µM and an Emax of 4.1-fold. This analog did not activate the G protein-coupled bile acid receptor, TGR5, and the metabolic nuclear receptors retinoid X receptor α, liver X receptors α/β, and peroxisome proliferator-activated receptors β/γ. Investigation of different farnesoid X receptor target genes characterized LT-141A as selective bile acid receptor modulators. Functional studies revealed that LT-141A increased cholesterol efflux from THP-1-derived macrophages via enhanced ATP-binding cassette transporter 1 expression. Moreover, cholesterol uptake in differentiated Caco-2 cells was significantly decreased upon LT-141A treatment. In conclusion, the leoligin analog LT-141A selectively activates the nuclear receptor farnesoid X receptor and has an influence on cholesterol transport in 2 model systems.

In silico study reveals existing drugs as α-glucosidase inhibitors: Structure-based virtual screening validated by experimental investigation

Drug repositioning is a popular method of making drug discovery less costly and more efficient. Computational methods such as pharmacophore-based virtual screening, molecular docking, and molecular dynamics (MD) simulations have been widely utilized to make the process of finding drugs more efficient and accurate. In this study, “in silico repositioning” was performed to identify promising α-glucosidase inhibitors among existing drugs. Based on molecular dynamics simulations analysis of 3TOP-acarbose and 6C9X-voglibose complexes, we built structure-based pharmacophore models, and then we screened FDA-approved drugs with good pharmacophore-fit scores. Subsequently, we performed a molecular docking study to understand the binding modes of α-glucosidase and virtual screening hits. We chose three hits to assess the stability of the protein-hit interactions in physiological conditions using molecular dynamics simulations. We calculated the binding free energy using the molecular mechanics generalized born surface area (MM-GBSA) method. We also performed toxicity prediction of the three hits to analyze their potential toxicities, and found that they were relatively safe. Finally, α-glucosidase inhibitory activity assays of the three hits in vitro revealed that benserazide exhibited inhibitory effects towards α-glucosidase, confirming the computational results. In summary, we identified a method for further research on the “in silico repositioning” of existing drugs that may affect a specific molecular target.

Molecular dynamics, MM/PBSA and in vitro validation of a novel quinazoline-based EGFR tyrosine kinase inhibitor identified using structure-based in silico screening

EGFR-TK has been a target strongly associated with the development of NSCLCs. A structure-based virtual screening campaign was launched against EGFR-TK by virtual screening a 3D library of 167 commercially available small molecules downloaded from ChemBridge Corporation. The virtual screen identified 12 virtual hit molecules, which were biologically evaluated against an EGFR-TK inhibitor-sensitive NSCLC cell line, A549. A quinazoline-based molecule 1, was most active and displayed ∼58% cytotoxicity at 20 μM single dose. The mode of cell death suggests molecule 1 induced apoptosis, which is characteristic of EGFR-TK pathway inhibition. A 50 ns MD simulation was conducted on three different systems: free EGFR-TK, molecule 1 complexed to EGFR-TK, and the positive control, lapatinib, complexed to EGFR-TK. The MD simulations showed increase in stabilisation of the EGFR-TK structure for the complexed systems, i.e., lower RMSDs and RMSFs for complexed EGFR-TK structures compared to the free EGFR-TK system. The binding affinities were estimated using MM/PBSA in the last 10 ns of the MD simulation that revealed comparable binding free energies between molecule 1 and lapatinib, ΔGbind = −25.0 and −23.9 kcal/mol, respectively. Per residue binding free energy decomposition studies revealed non-polar interactions contributed mostly to the binding free energies. Residues Leu718, Arg841 and Phe856 were predicted to contribute most to the binding free energies for molecule 1.

Structure-based virtual screening, biological evaluation and biophysical study of novel Mcl-1 inhibitors.

Aim: Targeting the protein-protein interactions (PPIs) associated with Mcl-1 has become a promising therapeutic approach for cancer. Herein, we reported the discovery of novel Mcl-1 inhibitors using an integrated computational approach. Results: Among 30 virtual screening hits, five compounds show inhibitory activities against Mcl-1. The most potent inhibitors M02 (Ki =5.4μM) and M08 (Ki=0.53μM) exhibit good selectivity against Bcl-2 and Bcl-xL. Compound M08 exhibits anti-proliferation activity and induces caspase-3 activation in Jurkat cancer cells. Moreover, 1H⁄15N HSQC NMR experiments suggested that compound M08 likely binds in the P2 pocket of Mcl-1 and engages R263 in a salt bridge. Conclusion: Our study provides a good starting point for future discovery of more potent Mcl-1 selective inhibitors.

The effects of sleep deprivation and text messaging on pedestrian safety in university students.

This study assesses the impact of sleep deprivation and text messaging on pedestrian injury risk. A total of 36 university students engaged in a virtual reality pedestrian environment in two conditions: sleep deprived (no sleep previous night) and normal sleep (normal sleep routine). Sleep was assessed using actigraphy and pedestrian behavior via four outcomes: time to initiate crossing, time before contact with oncoming vehicle, hits/close calls, and looks left/right. During each condition, participants made half the crossings while text messaging. Participants also completed the Useful Field of View test, the Psychomotor Vigilance Test, and Conners' Continuous Performance Test in both conditions. While sleep deprived, students crossed significantly closer to oncoming vehicles compared with after normal sleep. While text messaging, crossed closer to vehicles and took longer to initiate crossings. Safety risks were amplified through combined sleep deprivation plus text messaging, leading to more virtual hits and close calls and shorter time before vehicle contact while crossing. Sleep-deprived students demonstrated impairments in functioning on cognitive tests. University students' pedestrian behavior was generally riskier, and their cognitive functioning was impaired, when sleep deprived compared with after normal sleep. This effect was exacerbated when distracted by text messaging.

A novel potent metal-binding NDM-1 inhibitor was identified by fragment virtual, SPR and NMR screening

NDM-1 can hydrolyze nearly all available β-lactam antibiotics, including carbapenems. NDM-1 producing bacterial strains are worldwide threats. It is still very challenging to find a potent NDM-1 inhibitor for clinical use. In our study, we used a metal-binding pharmacophore (MBP) enriched virtual fragment library to screen NDM-1 hits. SPR screening helped to verify the MBP virtual hits and identified a new NDM-1 binder and weak inhibitor A1. A solution NMR study of 15N-labeled NDM-1 showed that A1 disturbed all three residues coordinating the second zinc ion (Zn2) in the active pocket of NDM-1. The perturbation only happened in the presence of zinc ion, indicating that A1 bound to Zn2. Based on the scaffold of A1, we designed and synthesized a series of NDM-1 inhibitors. Several compounds showed synergistic antibacterial activity with meropenem against NDM-1 producing K. pneumoniae.

Refined pharmacophore features for virtual screening of human thromboxane A2 receptor antagonists

For a long time, the structural basis of TXA2 receptor is limited due to the lack of crystal structure information, till the release of the crystal structure of TXA2 receptor, which deepens our understanding about ligand recognition and selectivity mechanisms of this physiologically important receptor. In this research, we report the successful implementation in the discovery of an optimal pharmacophore model of human TXA2 receptor antagonists through virtual screening. Structure-based pharmacophore models were generated based on two crystal structures of human TXA2 receptor (PDB entry 6IIU and 6IIV). Docking simulation revealed interaction modes of the virtual screening hits against TXA2 receptor, which was validated through molecular dynamics simulation and binding free energy calculation. ADMET properties were also analyzed to evaluate the toxicity and physio-chemical characteristics of the hits. The research would provide valuable insight into the binding mechanisms of TXA2 receptor antagonists and thus be helpful for designing novel antagonists.

Discovery and Optimization of wt-RET/KDR-Selective Inhibitors of RETV804M Kinase

A combination of focused library and virtual screening, hit expansion, and rational design has resulted in the development of a series of inhibitors of RETV804M kinase, the anticipated drug-resistant mutant of RET kinase. These agents do not inhibit the wild type (wt) isoforms of RET or KDR and therefore offer a potential adjunct to RET inhibitors currently undergoing clinical evaluation.

N-(2-Hydroxyphenyl)-1-[3-(2-oxo-2,3-dihydro-1H- benzimidazol-1-yl)propyl]piperidine-4-Carboxamide (D2AAK4), a Multi-Target Ligand of Aminergic GPCRs, as a Potential Antipsychotic.

N-(2-hydroxyphenyl)-1-[3-(2-oxo-2,3-dihydro-1H-benzimidazol -1-yl)propyl]piperidine-4-carboxamide (D2AAK4) is a multitarget ligand of aminergic G protein-coupled receptors (GPCRs) identified in structure-based virtual screening. Here we present detailed in vitro, in silico and in vivo investigations of this virtual hit. D2AAK4 has an atypical antipsychotic profile and low affinity to off-targets. It interacts with aminergic GPCRs, forming an electrostatic interaction between its protonatable nitrogen atom and the conserved Asp 3.32 of the receptors. At the dose of 100 mg/kg D2AAK4 decreases amphetamine-induced hyperactivity predictive of antipsychotic activity, improves memory consolidation in passive avoidance test and has anxiogenic properties in elevated plus maze test (EPM). Further optimization of the virtual hit D2AAK4 will be aimed to balance its multitarget profile and to obtain analogs with anxiolytic activity.

Investigation of New Inhibitors of UDP-N-Acetylglucosamine Enolpyruvyl Transferase (MurA) by Virtual Screening with Antibacterial Assessment.

Considering the interesting role in the peptidoglycan biosynthesis pathway, the enzyme UDP-N-acetylglucosamine enolpyruvyl transferase is an attractive target to develop new antibacterial agents. It catalyzes the first key step of this pathway and its inhibition leads to bacterial cell death. Fosfomycin is known as the natural inhibitor of MurA. The study aimed to introduce new inhibitors of MurA by virtual screening of different chemical compounds libraries, and test the best scored "virtual hits" against three pathogenic bacteria: Escherichia coli, Bacillus subtilis and Staphylococcus aureus. A virtual screening of the structural analogues of fosfomycin downloaded from the Pub- Chem database was performed. Moreover, French National Chemical Library and ZINC database were also utilized to identify new structures different from fosfomycin. FlexX was the software used for this study. The antibacterial testing was divided into two methods: disk diffusion and broth dilution. A set of virtual hits was found to have better energy score than that of fosfomycin, seven of them were tested in vitro. In addition, the disk diffusion method explored four compounds that exhibited antibacterial activity: CID-21680357 (fosfomycin analogue), AB-00005001, ZINC04658565, and ZINC901335. The testing was continued by broth dilution method for both compounds CID-21680357 and ZINC901335 to determine their minimum inhibitory concentrations, and ZINC901335 had the best value with 457μg/ml against Staphylococcus aureus. Four compounds were found and proven in silico and in vitro to have antibacterial activity, namely CID-21680357, AB-00005001, ZINC04658565, and ZINC901335.

Identification of DOT1L inhibitors by structure-based virtual screening adapted from a nucleoside-focused library

Disruptor of Telomeric Silencing 1-Like (DOT1L), the sole histone H3 lysine 79 (H3K79) methyltransferase, is required for leukemogenic transformation in a subset of leukemias bearing chromosomal translocations of the Mixed Lineage Leukemia (MLL) gene, as well as other cancers. Thus, DOT1L is an attractive therapeutic target and discovery of small molecule inhibitors remain of high interest. Herein, we are presenting screening results for a unique focused library of 1200 nucleoside analogs originally produced under the aegis of the NIH Pilot Scale Library Program. The complete nucleoside set was screened virtually against DOT1L, resulting in 210 putative hits. In vitro screening of the virtual hits resulted in validation of 11 compounds as DOT1L inhibitors clustered into two distinct chemical classes, adenosine-based inhibitors and a new chemotype that lacks adenosine. Based on the developed DOT1L ligand binding model, a structure-based design strategy was applied and a second-generation of non-nucleoside DOT1L inhibitors was developed. Newly synthesized compound 25 was the most potent DOT1L inhibitor in the new series with an IC50 of 1.0 μM, showing 40-fold improvement in comparison with hit 9 and exhibiting reasonable on target effects in a DOT1L dependent murine cell line. These compounds represent novel chemical probes with a unique non-nucleoside scaffold that bind and compete with the SAM binding site of DOT1L, thus providing foundation for further medicinal chemistry efforts to develop more potent compounds.

Consensus virtual screening of dark chemical matter and food chemicals uncover potential inhibitors of SARS-CoV-2 main protease.

The pandemic caused by SARS-CoV-2 (COVID-19 disease) has claimed more than 500 000 lives worldwide, and more than nine million people are infected. Unfortunately, an effective drug or vaccine for its treatment is yet to be found. The increasing information available on critical molecular targets of SARS-CoV-2 and active compounds against related coronaviruses facilitates the proposal (or repurposing) of drug candidates for the treatment of COVID-19, with the aid of in silico methods. As part of a global effort to fight the COVID-19 pandemic, herein we report a consensus virtual screening of extensive collections of food chemicals and compounds known as dark chemical matter. The rationale is to contribute to global efforts with a description of currently underexplored chemical space regions. The consensus approach included combining similarity searching with various queries and fingerprints, molecular docking with two docking protocols, and ADMETox profiling. We propose compounds commercially available for experimental testing. The full list of virtual screening hits is disclosed.

Pharmacoinformatics approaches to identify potential hits against tetraacyldisaccharide 4'-kinase (LpxK) of Pseudomonas aeruginosa.

Pseudomonas aeruginosa infection can cause pneumonia and urinary tract infection and the management of Pseudomonas aeruginosa infection is critical in multidrug resistance, hospital-acquired bacteremia and ventilator-associated pneumonia. The key enzymes of lipid A biosynthesis in Pseudomonas aeruginosa are promising drug targets. However, the enzyme tetraacyldisaccharide 4′-kinase (LpxK) has not been explored as a drug target so far. Several pharmacoinformatics tools such as comparative metabolic pathway analysis (Metacyc), data mining from a database of essential genes (DEG), homology modeling, molecular docking, pharmacophore based virtual screening, ADMET prediction and molecular dynamics simulation were used in identifying novel lead compounds against this target. The top virtual hits STOCK6S-33288, 43621, 39892, 37164 and 35740 may serve as the templates for the design and synthesis of potent LpxK inhibitors in the management of serious Pseudomonas aeruginosa infection.

Pharmacophore modeling, atom based 3D-QSAR, molecular docking and molecular dynamics studies on Escherichia coli ParE inhibitors

ATP dependent ParE enzyme is as an attractive target for the development of antibacterial agents. Atom based 3D-QSAR model AADHR.187 was developed based on the thirty eight Escherichia coli ParE inhibitors. The generated model showed statistically significant coefficient of determinations for the training (R2 = 0.985) and test (R2 = 0.86) sets. The cross-validated correlation coefficient (q2) was 0.976. The utility of the generated model was validated by the enrichment study. The model was also validated with structurally diverse external test set of ten compounds. Contour plot analysis of the generated model unveiled the chemical features necessary for the E. coli ParE enzyme inhibition. Extra-precision docking result revealed that hydrogen bonding and ionic interactions play a major role in ParE protein-ligand binding. Binding free energy was computed for the data set inhibitors to validate the binding affinity. A 30-ns molecular dynamics simulation showed high stability and effective binding of inhibitor 34 within the active site of ParE enzyme. Using the best fitted model AADHR.187, pharmacophore-based high-throughput virtual screening was performed to identify virtual hits. Based on the above studies three new molecules are proposed as E. coli ParE inhibitors with high binding affinity and favourable ADME properties.

Combined Ligand-Based and Structure-Based Virtual Screening Approach for Identification of New Dipeptidyl Peptidase 4 Inhibitors.

Dipeptidyl Peptidase 4 (DPP 4) enzyme cleaves an incretin-based glucoregulatory hormone Glucagon Like Peptide -1 from N-terminal where penultimate amino acid is either alanine or proline. Several DPP 4 inhibitors, "gliptins", are approved for the management of Type 2 Diabetes or are under clinical trial. In the present study, combined pharmacophore and docking-based virtual screening protocol were used for the identification of new hits from the Specs Database, which would inhibit DPP 4. The entire computational studies were performed using the Discovery Studio v. 4.1 software package, Pipeline Pilot v. 9.2 (Accelrys Inc.) and FRED v. 2.2.5 (OpenEye Scientific Software). Common feature pharmacophore model was generated from known DPP 4 inhibitors and validated by Receiver Operating curve analysis and GH-scoring method. Database search of Specs commercial database was performed using validated pharmacophore. Hits obtained from pharmacophore search were further docked into the binding site of DPP 4. Based on the analysis of docked poses of hits, 10 compounds were selected for in- vitro DPP 4 enzyme inhibition assay. Based on docking studies, virtual hits were predicted to form interaction with essential amino acid residues of DPP 4 and have an almost similar binding orientation as that of the reference molecule. Three compounds having Specs database ID- AN-465/42837213, AP-064/42049348 and AN- 465/43369427 were found to inhibit DPP 4 enzyme moderately. The present study demonstrates a successful utilization of in-silico tools in the identification of new DPP 4 inhibitor, which can serve as a starting point for the development of novel DPP 4 inhibitors.

Identification of novel inhibitors for the tyrosyl-DNA-phosphodiesterase 1 (Tdp1) mutant SCAN1 using virtual screening

Spinocerebellar ataxia syndrome with axonal neuropathy (SCAN1) is a debilitating neurological disease that is caused by the mutation the Tyrosyl-DNA phosphodiesterase 1 (TDP1) DNA repair enzyme. The crucial His493 in TDP1′s binding site is replaced with an arginine amino acid residue rendering the enzyme dysfunctional. A virtual screen was performed against the homology model of SCAN1 and seventeen compounds were identified and tested in a novel SCAN1 specific biochemical assay. Six compounds showed activity with IC50 values between 3.5 and 25.1 µM. The most active ligand 5 (3.5 µM) is a dicoumarin followed by a close structural analogue 6 at 6.0 µM. A less potent series of β-carbolines (14 and 15) was found with potency in the mid-teens. According to molecular modelling an excellent fit for the active ligands into the binding pocket is predicted. To the best of our knowledge, data on inhibitors of the mutant form of TDP1 has not been reported previously. The virtual hits were also tested for wild type TDP1 activity and all six SCAN1 inhibitors are potent for the former, e.g., ligand 5 has a measured IC50 at 99 nM.In the last decade, TDP1 is considered as a promising target for adjuvant therapy against cancer in combination with Topoisomerase 1 poisons. The active ligands are mostly non-toxic to cancer cell lines A-549, T98G and MCF-7 as well as the immortalized WI-38 human fetal lung cells. Furthermore, ligands 5 and 7, show promising synergy in conjunction with topotecan, a clinically used topoisomerase 1 anticancer drug. The active ligands 5, 7, 14 and 15 have a good balance of the physicochemical properties required for oral bioavailability making the excellent candidates for further development.

Discovery and Characterisation of Dual Inhibitors of Tryptophan 2,3-Dioxygenase (TDO2) and Indoleamine 2,3-Dioxygenase 1 (IDO1) Using Virtual Screening.

Cancers express tryptophan catabolising enzymes indoleamine 2,3-dioxygenase 1 (IDO1) and tryptophan 2,3-dioxygenase (TDO2) to produce immunosuppressive tryptophan metabolites that undermine patients’ immune systems, leading to poor disease outcomes. Both enzymes are validated targets for cancer immunotherapy but there is a paucity of potent TDO2 and dual IDO1/TDO2 inhibitors. To identify novel dual IDO1/TDO2 scaffolds, 3D shape similarity and pharmacophore in silico screening was conducted using TDO2 as a model for both systems. The obtained hits were tested in cancer cell lines expressing mainly IDO1 (SKOV3—ovarian), predominantly TDO2 (A172—brain), and both IDO1 and TDO2 (BT549—breast). Three virtual screening hits were confirmed as inhibitors (TD12, TD18 and TD34). Dose response experiments showed that TD34 is the most potent inhibitor capable of blocking both IDO1 and TDO2 activity, with the IC50 value for BT549 at 3.42 µM. This work identified new scaffolds able to inhibit both IDO1 and TDO2, thus enriching the collection of dual IDO1/TDO2 inhibitors and providing chemical matter for potential development into future anticancer drugs.

Virtual screening to identify potent sepiapterin reductase inhibitors

Sepiapterin reductase has been identified as a potential drug target for neuropathic and inflammatory pain. Virtual screening was executed against a publicly available x-ray crystal structure of sepiapterin reductase. A set of structurally diverse and potent sepiapterin reductase inhibitors was identified. This set of compounds with favorable ligand efficiency and lipophilic efficiency are tractable for further optimization. An SAR follow-up library was synthesized based on one of the virtual screening hits exploring SAR.

A War at All Costs?

War between the two worlds Eminiar VII and Vendikar had gone on for 500 years with no cessation in sight. This war was conducted by computer simulation, so that a virtual hit on one planet was retaliated by a computer-generated strike on the other. This avoided the large-scale death and destruction normally suffered during real wartime. To compensate for a war of this surgical nature, a segment of the population of a virtually stricken planet had to be assigned to die in disintegration chambers once the planet was targeted. People dutifully reported to these chambers once their fates were assigned. This was the basis of the episode titled "A Taste of Armageddon" of season one of the original Star Trek television series.

Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents.

Two isoforms of extracellular regulated kinase (ERK), namely ERK-1 and ERK-2, are associated with several cellular processes, the aberration of which leads to cancer. The ERK-1/2 inhibitors are thus considered as potential agents for cancer therapy. Multitarget quantitative structure–activity relationship (mt-QSAR) models based on the Box–Jenkins approach were developed with a dataset containing 6400 ERK inhibitors assayed under different experimental conditions. The first mt-QSAR linear model was built with linear discriminant analysis (LDA) and provided information regarding the structural requirements for better activity. This linear model was also utilised for a fragment analysis to estimate the contributions of ring fragments towards ERK inhibition. Then, the random forest (RF) technique was employed to produce highly predictive non-linear mt-QSAR models, which were used for screening the Asinex kinase library and identify the most potential virtual hits. The fragment analysis results justified the selection of the hits retrieved through such virtual screening. The latter were subsequently subjected to molecular docking and molecular dynamics simulations to understand their possible interactions with ERK enzymes. The present work, which utilises in-silico techniques such as multitarget chemometric modelling, fragment analysis, virtual screening, molecular docking and dynamics, may provide important guidelines to facilitate the discovery of novel ERK inhibitors.