DFT study of the Lewis acid mediated synthesis of 3-acyltetramic acids

The recent emergence and re-emergence of alphaviruses, in particular the chikungunya virus (CHIKV), in numerous countries has invoked a worldwide threat to human health, while simultaneously generating an economic burden on affected countries. There are currently no vaccines or effective drugs available for the treatment of the CHIKV, and with few lead compounds reported, the vital medicinal chemistry is significantly more challenging. This study reports on the discovery of potential inhibitors for the nsP3 macro domain of CHIKV using molecular docking, virtual screening, and molecular dynamics simulations, as well as work done to evaluate and confirm the active site of nsP3. Virtual screening was carried out based on blind docking as well as focused docking, using the database of 1541 compounds from NCI Diversity Set II, to identify hit compounds for nsP3. The top hit compounds were further subjected to molecular dynamic simulations, yielding a greater understanding of the dynamic behavior of nsP3 and its complexes with various ligands, concurrently confirming the outcomes of docking, and establishing in silico lead compounds which target the CHIKV nsP3 enzyme.

Discovery of novel HCV polymerase inhibitors using pharmacophore-based virtual screening

We report the use of pharmacophore-based virtual screening as an efficient tool for the discovery of novel HCV polymerase inhibitors. A three-dimensional pharmacophore model for the HCV-796 binding site, NNI site IV inhibitor, to the enzyme was built by means of the structure-based focusing module in Cerius2 program. Using these models as a query for virtual screening, we produced a successful example of using pharmacophore-based virtual screening to identify novel compounds with HCV replicon assay through inhibition of HCV polymerization. Among the hit compounds, compounds 1 and 2 showed 56% and 48% inhibition of NS5B polymerization activity at 20 μM, respectively. In addition, compound 1 also exhibited replicon activity with EC₅₀ value of 2.16 μM. Following up the initial hit, we obtained derivatives of compound 1 and evaluated polymerization inhibition activity and HCV replicon assay. These results provide information necessary for the development of more potent NS5B inhibitors.     

Discovery of a potent and selective adenylyl cyclase type 8 agonist by docking-based virtual screening

Adenylyl cyclases (ACs), which are responsible for catalyzing the conversion of adenosine triphosphate (ATP) into the second messenger cyclic adenosine monophosphate (cAMP), play a critical role in cell signal transduction. In this study, a combined approach involving docking-based virtual screening, with the combination of homology modeling followed by an in-vitro, and cell-based biological assay have been performed for discovering a class of novel potent and selective isoform adenylyl cyclase type 8 (AC8) agonist. The computer-aided virtual screening was used to identify fourteen virtual cluster compounds as potential hits which were further subjected to rigorous bioassays. A novel hit compound VHC-7 (ethyl 3-(2,4-dichlorobenzyl)-2-oxoindoline-3-carboxylate) was identified as a highly potent selective AC8 agonist with EC₅₀ value of 0.1052 ± 0.038 µM. Remarkably, the molecule herein reported can be explored further to discover greater number of hit compounds with better pharmacokinetic properties as well as to serve as a promising novel hit agonist of AC8 for the treatment of various central nervous system disorders and its associated diseases.     

Design and synthesis of aryl sulfonamide-based nonsteroidal mineralocorticoid receptor antagonists

Hit-to-lead medicinal chemistry efforts are described starting from a screening hit 1, leading to a new class of aryl sulfonamide-based MR antagonist, exemplified by 17, that possesses favourable MR binding affinity, selectivity profile against closely related NHRs, physicochemical properties and metabolic stability.     

Identification of free fatty acid receptor 2 agonists using virtual screening

Structure- and ligand-based virtual-screening methods (docking, 2D- and 3D-similarity searching) were analyzed for their effectiveness in virtual screening against FFAR2. To evaluate the performance of these methods, retrospective virtual screening was performed. Statistical quality of the methods was evaluated by BEDROC and RIE. The results revealed that electrostatic similarity search protocol using EON (ET combo) outperformed all other protocols with outstanding enrichment of >95% in top 1% and 2% of the dataset with an AUC of 0.958. Interestingly, the hit lists that are obtained from different virtual-screening methods are generally highly complementary to hits found from electrostatic similarity searching. These results suggest that considering electrostatic similarity searching first increases the chance of identifying more (and more diverse) active compounds from a virtual-screening campaign. Accordingly, prospective virtual screening using electrostatic similarity searching was used to identify novel FFAR2 ligands. The discovered compounds provide new chemical matter starting points for the initiation of a medicinal chemistry campaign.     

Discovery of LRRK2 inhibitors by using an ensemble of virtual screening methods

In this paper, we present the results of a ligand- and structure-based virtual screen targeting LRRK2, a kinase that has been implicated in Parkinson’s disease. For the ligand-based virtual screen, the structures of 12 competitor compounds were used as queries for a variety of 2D and 3D searches. The structure-based virtual screen relied on homology models of LRRK2, as no X-ray structure is currently available in the public domain. From the virtual screening, 662 compounds were purchased, of which 35 showed IC₅₀ values below 10 μM in wild-type and/or mutant LRRK2 (a hit rate of 5.3%). Of these 35 hits, four were deemed to have potential for medicinal chemistry follow-up.     

Discovery of a novel pyrazole series of group X secreted phospholipase A2 inhibitor (sPLA2X) via fragment based virtual screening

The discovery of potent novel pyrazole containing group X secreted phospholipase A2 inhibitors via structure based virtual screening is reported. Docking was applied on a large set of in-house fragment collection and pharmacophore feature matching was used to filter docking poses. The selected virtual screening hits was run in NMR screening, a potent pyrazole containing fragment hit was identified and confirmed by its complex X-ray structure and the following biochemical assay result. Expansion on the fragment hit has led to further improvement of potency while maintaining high ligand efficiency, thus supporting the further development of this chemical series.     

A novel class of potent NF-kappaB signaling inhibitors

A novel class of NF-kappaB pathway signaling inhibitors was discovered by virtual screening, medicinal chemistry, and QSAR analysis. An initial set of compounds inhibited NF-kappaB signaling in a whole cell reporter gene assay in the micro-molar range. Activity was improved step by step by medicinal chemistry to yield nano-molar signaling inhibitors.     

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.     

Identification of novel serotonin 2C receptor ligands by sequential virtual screening

Pharmacophore modelling, docking and virtual screening have become important tool in drug discovery process. Serotonin 2C (5-HT_2C) receptor ligands have got major attention for their therapeutic uses as antidepressant and anorectic agents. Two step pharmacophore and docking based virtual screening was done using 5-HT_2C agonists. Two common feature pharmacophore directed virtual hits had submicromolar activity. Refined pharmacophore with excluded volumes was constructed and combined with homology model based docking. Best hit from this virtual screening showed IC₅₀ of 20.1 nM. Similarity search of this hit compound resulted more active ligand with 7.8 nM activity.     

Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists

Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure.     

Identification and hit-to-lead exploration of a novel series of histamine H4 receptor inverse agonists

The identification and hit-to-lead exploration of a novel, potent and selective series of histamine H₄ receptor inverse agonists is described. The initial hit, 3A (IC₅₀ 19 nM) was identified by means of a ligand-based virtual screening approach. Subsequent medicinal chemistry exploration yielded 18I which possessed increased potency (R-enantiomer IC₅₀ 1 nM) as well as enhanced microsomal stability.     

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 and optimisation of a potent and selective tertiary sulfonamide oxytocin antagonist

The optimisation of a tertiary sulfonamide high-throughput screening hit is described. A combination of high-throughput chemistry, pharmacophore analysis and in silico PK profiling resulted in the discovery of potent sulfonamide oxytocin receptor antagonists with oral exposure and good selectivity over vasopressin receptors.     

Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches

Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein–protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.     

Integrating DNA-encoded chemical libraries with virtual combinatorial library screening: Optimizing a PARP10 inhibitor

Two critical steps in drug development are 1) the discovery of molecules that have the desired effects on a target, and 2) the optimization of such molecules into lead compounds with the required potency and pharmacokinetic properties for translation. DNA-encoded chemical libraries (DECLs) can nowadays yield hits with unprecedented ease, and lead-optimization is becoming the limiting step. Here we integrate DECL screening with structure-based computational methods to streamline the development of lead compounds. The presented workflow consists of enumerating a virtual combinatorial library (VCL) derived from a DECL screening hit and using computational binding prediction to identify molecules with enhanced properties relative to the original DECL hit. As proof-of-concept demonstration, we applied this approach to identify an inhibitor of PARP10 that is more potent and druglike than the original DECL screening hit.     

Toward novel HIV-1 integrase binding inhibitors: molecular modeling, synthesis, and biological studies

The identification of a novel hit compound as integrase binding inhibitor has been accomplished by means of virtual screening techniques. A small family of structurally related molecules has been synthesized and biologically evaluated with one of the compounds showing an IC(50)=12 microM.     

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.     

Pocket detection and interaction-weighted ligand-similarity search yields novel high-affinity binders for Myocilin-OLF,a protein implicated in glaucoma

Traditional structure and ligand based virtual screening approaches rely on the availability of structural and ligand binding information. To overcome this limitation, hybrid approaches were developed that relied on extraction of ligand binding information from proteins sharing similar folds and hence, evolutionarily relationship. However, they cannot target a chosen pocket in a protein. To address this, a pocket centric virtual ligand screening approach is required. Here, we employ a new, iterative implementation of a pocket and ligand-similarity based approach to virtual ligand screening to predict small molecule binders for the olfactomedin domain of human myocilin implicated in glaucoma. Small-molecule binders of the protein might prevent the aggregation of the protein, commonly seen during glaucoma. First round experimental assessment of the predictions using differential scanning fluorimetry with myoc-OLF yielded 7 hits with a success rate of 12.7%; the best hit had an apparent dissociation constant of 99 nM. By matching to the key functional groups of the best ligand that were likely involved in binding, the affinity of the best hit was improved by almost 10,000 fold from the high nanomolar to the low picomolar range. Thus, this study provides preliminary validation of the methodology on a medically important glaucoma associated protein.