Beyond the BET Family: Targeting CBP/p300 with 4‐Acyl Pyrroles

Bromodomain and extra‐terminal domain (BET) inhibitors are widely used both as chemical tools to study the biological role of their targets in living organisms and as candidates for drug development against several cancer variants and human disorders. However, non‐BET bromodomains such as those in p300 and CBP are less studied. XDM‐CBP is a highly potent and selective inhibitor for the bromodomains of CBP and p300 derived from a pan‐selective BET BRD‐binding fragment. Along with X‐ray crystal‐structure analysis and thermodynamic profiling, XDM‐CBP was used in screenings of several cancer cell lines in vitro to study its inhibitory potential on cancer cell proliferation. XDM‐CBP is demonstrated to be a potent and selective CBP/p300 inhibitor that acts on specific cancer cell lines, in particular malignant melanoma, breast cancer, and leukemia.     

LP99: Discovery and Synthesis of the First Selective BRD7/9 Bromodomain Inhibitor

The bromodomain‐containing proteins BRD9 and BRD7 are part of the human SWI/SNF chromatin‐remodeling complexes BAF and PBAF. To date, no selective inhibitor for BRD7/9 has been reported despite its potential value as a biological tool or as a lead for future therapeutics. The quinolone‐fused lactam LP99 is now reported as the first potent and selective inhibitor of the BRD7 and BRD9 bromodomains. Development of LP99 from a fragment hit was expedited through balancing structure‐based inhibitor design and biophysical characterization against tractable chemical synthesis: Complexity‐building nitro‐Mannich/lactamization cascade processes allowed for early structure–activity relationship studies whereas an enantioselective organocatalytic nitro‐Mannich reaction enabled the synthesis of the lead scaffold in enantioenriched form and on scale. This epigenetic probe was shown to inhibit the association of BRD7 and BRD9 to acetylated histones in vitro and in cells. Moreover, LP99 was used to demonstrate that BRD7/9 plays a role in regulating pro‐inflammatory cytokine secretion.     

The total synthesis and biological evaluation of nafuredin-γ and its analogues

Nafuredin (1) is converted to nafuredin-γ (2) under mild basic conditions and both compounds exhibit the same inhibitory activity and selectivity against NADH-fumarate reductase (complex I). The total synthesis of 2 was achieved by a convergent approach using Stille coupling. The structural elements required for inhibitory activity against NADH-fumarate reductase (complex I) were then investigated by evaluation of nafuredin-γ (2) and its structural analogues.     

The definition of the molecular structure for potential anti-malaria agents by the Monte Carlo method

A series of 53 endochin analogs (4(1-H)-quinolone derivatives) with anti-malarial activity against the clinically relevant multidrug resistant malarial strain TM-90-C2B has been studied. The CORAL (http://www.insilico.eu/coral) software has been used as a tool to build up the quantitative structure–activity relationships (QSAR) for the anti-malaria activity. The QSAR models were calculated with the representation of the molecular structure by simplified molecular input-line entry system and by the molecular graph of atomic orbitals. The method for splitting data into the sub-training set, the calibration set, the test set, and the validation set is suggested. Three various splits were examined. Statistical quality of models for the validation sets (which are not involved in the building up models) is good. Structural indicators (alerts) for increase and decrease of the anti-malaria activity are defined.     

Synthesis and antitumor activity of novel phenylhydrazonopyrazolone derivatives and molecular dynamics simulations

SHP2 is a new promising target for anti-cancer drug discovery. A series of novel phenylhydrazonopyrazolone derivatives was synthesized by a more convenient method, and their chemical structures were characterized by various spectroscopic methods. The inhibitory effects of these compounds on SHP2 enzyme and SHP2-dependent cancer cell H1975 were evaluated. The compound 11f with IC₅₀ value of 3.38 μmol/L exhibited more potent antitumor activity against H1975 cell than GS-493 (IC₅₀?=?20.92 μmol/L). Molecular dynamics simulation of compound 11f displayed a possible mode of interaction between this compound and SHP2 enzyme.     

Development of QSAR models for microsomal stability: identification of good and bad structural features for rat,human and mouse microsomal stability

High throughput microsomal stability assays have been widely implemented in drug discovery and many companies have accumulated experimental measurements for thousands of compounds. Such datasets have been used to develop in silico models to predict metabolic stability and guide the selection of promising candidates for synthesis. This approach has proven most effective when selecting compounds from proposed virtual libraries prior to synthesis. However, these models are not easily interpretable at the structural level, and thus provide little insight to guide traditional synthetic efforts. We have developed global classification models of rat, mouse and human liver microsomal stability using in-house data. These models were built with FCFP_6 fingerprints using a Naïve Bayesian classifier within Pipeline Pilot. The test sets were correctly classified as stable or unstable with satisfying accuracies of 78, 77 and 75% for rat, human and mouse models, respectively. The prediction confidence was assigned using the Bayesian score to assess the applicability of the models. Using the resulting models, we developed a novel data mining strategy to identify structural features associated with good and bad microsomal stability. We also used this approach to identify structural features which are good for one species but bad for another. With these findings, the structure-metabolism relationships are likely to be understood faster and earlier in drug discovery.     

Structure-based modelling,scoring, screening,and in vitro kinase assay of anesthetic pkc inhibitors against a natural medicine library

Protein kinase C (PKC) is an intracellular effector of the inositol phosphate-mediated signal transduction pathway. Evidence is emerging that certain general anaesthetics can influence the activity of PKC by interacting with the regulatory domain of the enzyme, and targeting PKC kinase domain is considered as a strategy to modulate the anaesthetic effects. Here, an integrated method was used to perform virtual screening against a large library of natural compounds for the discovery of new and potent PKC modulators. A number of hits were identified and their inhibitory activity against PKC kinase domain was measured by using a standard kinase assay protocol. Three and five compounds were determined to have high and moderate activities with IC₅₀ values at nanomolar and micromolar levels, respectively. These compounds can be considered as promising lead molecular entities to develop efficacious anaesthetic modulators. Structural examination revealed a variety of nonbonded interactions such as hydrogen bonds, cation-π contacts, and hydrophobic forces across the complex interface of PKC with the identified compounds. This study helps to establish an integrative approach to rational kinase inhibitor discovery by efficiently exploiting various existing natural products.     

Binary quantitative structure-activity relationship (QSAR) analysis of estrogen receptor ligands

The use of high throughput screening (HTS) to identify lead compounds has greatly challenged conventional quantitative structure-activity relationship (QSAR) techniques that typically correlate structural variations in similar compounds with continuous changes in biological activity. A new QSAR-like methodology that can correlate less quantitative assay data (i.e., "active" versus "inactive"), as initially generated by HTS, has been introduced. In the present study, we have, for the first time, applied this approach to a drug discovery problem; that is, the study of the estrogen receptor ligands. The binding affinities of 463 estrogen analogues were transformed into a binary data format, and a predictive binary QSAR model was derived using 410 estrogen analogues as a training set. The model was applied to predict the activity of 53 estrogen analogues not included in the training set. An overall accuracy of 94% was obtained.     

Design,Synthesis and Biological Evaluation of Novel Selective Thiol-based Histone Deacetylase(HDAC) VI InhibitorsBearing Indeno[1,2-c]pyrazole or Benzoindazole Scaffold

A series of thiol-based indeno[1,2-c]pyrazoles and benzoindazole compounds was designed and synthesized according to the structural specificity of histone deacetylase VI(HDAC6) and the structural characteristics of HDAC inhibitors. The inhibitory activities of the target compounds against HDAC6 and HDAC1 were screened by fluorescence analysis. Most of the target compounds showed moderate inhibitory activity against HDAC6(IC₅₀=44—598 nmol/L). Among them, compound A-4 displayed the highest selectivity against HDAC6 and similar inhibitory activity(IC₅₀=44 nmol/L) to that of the positive drug SAHA(IC₅₀=41 nmol/L) against HDAC6.     

Investigation of indirubin derivatives: a combination of 3D-QSAR,molecular docking,and ADMET towards the design of new DRAK2 inhibitors

Kinase-related apoptosis-inducing kinase 2 (DRAK2) is a serine/threonine kinase and belongs to the death-associated protein kinase DPAK family, which is responsible for induction of apoptosis in many cell types. Thus, DRAK2 is regarded as a promising target for treatment of autoimmune diseases. To investigate the binding between DRAK2 and indirubin inhibitors and design potent inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking were performed. Comparative Molecular Similarity Indices Analysis (CoMSIA) was developed using 33 molecules having pIC₅₀ ranging from 8.523 to 5.000 (IC₅₀ in nM). The best CoMSIA model gave a significant coefficient of determination (R²?=?0.93), as well as a (leave-one-out cross-validation coefficient Q² of 0.81. The predictive ability of this model was evaluated by external validation using a test set of eight compounds and yielded a predicted coefficient of determination R²_test of 0.94. The contour maps could provide structural features to improve inhibitory activity. Good consistency between contour maps and molecular docking strongly suggests that the molecular modeling is reliable. Based on these satisfactory results, we designed several new DRAK2 inhibitors and their inhibitory activities were predicted using different models, which are developed on different training and test sets. Additionally, these newly designed inhibitors showed promising results in the preliminary in silico ADMET evaluations compared to the best inhibitor from the studied dataset. This study could be useful in lead identification and optimization for early drug discovery of DRAK2 inhibitors.     

Lead validation and SAR development via chemical similarity searching; application to compounds targeting the pY+3 site of the SH2 domain of p56lck

Compound selection based on chemical similarity has been used to validate active "parent" compounds identified via database searching as viable lead compounds and to obtain initial structure-activity relationships for those leads. Twelve parent compounds that have inhibitory activity against the SH2 domain of the p56 T-cell tyrosine kinase (Lck) are the focus of this study. Lck is involved in the T-cell mediated immune response, and inhibitors of Lck protein-protein interactions could potentially be used to develop novel immunosuppressants. Similarity searches for each parent compound were performed using 2D structural fingerprints on a database containing 1,300,000 commercially available compounds. The inhibitory activity of the selected compounds was assessed using enzyme immunoassay (EIA). In general, the most active parent compounds yield the most high activity similar compounds; however, in two cases low activity parent compounds (i.e. inhibitory activity < 25% at 100 microM) yielded multiple similar compounds with activities > 60%. Such compounds may, therefore, be considered as viable lead compounds for optimization. Structure-activity relationships were explored by examining both ligand structures and their computed bound conformations to the protein. Functional groups common to the active compounds as well as key amino acid residues that form hydrogen bonds with the active compounds were identified. This information will act as the basis for the rational optimization of the lead compounds.     

High Throughput and High Speed Organic Synthesis in Drug Discovery: An Integration of Chemistry and Technology

Drug discovery is a complicated process that involves multiple synthetic chemistry tasks. Among them, lead generation and optimization is the core business in the discovery research. During the stage of lead generation, a large library of many thousands individual compounds will be screened against a biological target to identify a set of hits that showed desirable activity. Once a hit has been identified, analog synthesis and development of SAR around this hit and establishment of relationsh…     

An iridium(iii)-based irreversible protein–protein interaction inhibitor of BRD4 as a potent anticancer agent

Bromodomain-containing protein 4 (BRD4) has recently emerged as an attractive epigenetic target for anticancer therapy. In this study, an iridium(iii) complex is reported as the first metal-based, irreversible inhibitor of BRD4. Complex 1a is able to antagonize the BRD4-acetylated histone protein–protein interaction (PPI) in vitro, and to bind BRD4 and down-regulate c-myc oncogenic expression in cellulo. Chromatin immunoprecipitation (ChIP) analysis revealed that 1a could modulate the interaction between BRD4 and chromatin in melanoma cells, particular at the MYC promoter. Finally, the complex showed potent activity against melanoma xenografts in an in vivo mouse model. To our knowledge, this is the first report of a Group 9 metal complex inhibiting the PPI of a member of the bromodomain and extraterminal domain (BET) family. We envision that complex 1a may serve as a useful scaffold for the development of more potent epigenetic agents against cancers such as melanoma.     

Experimental determination and prediction of bilitranslocase transport activity

The transport activity of a membrane protein, bilitranslocase (T.C. # 2.A.65.1.1), which acts as a transporter of bilirubin from blood to liver cells, was experimentally determined for a large set of various endogenous compounds, drugs, purine and pyrimidine derivatives. On these grounds, the structure-activity models were developed following the OECD principles of QSAR models and their predictive ability for new chemicals was evaluated. The applicability domain of the models was estimated by Euclidean distances criteria according to the applied modeling method. The selection of the most influential structural variables was an important stage in the adopted modeling methodology. The interpretation of selected variables was performed in order to get an insight into the mechanism of transport through the cell membrane via bilitranslocase. Validation of the optimized models was performed by a previously determined validation set. The classification model was build to separate active from inactive compounds. The resulting accuracy, sensitivity, and specificity were 0.73, 0.89, and 0.64, respectively. Only active compounds were used to develop a predictive model for bilitranslocase inhibition constants. The model showed good predictive ability; Root Mean Squared error of the validation set, RMS(V)=0.29 log units.     

Identification of Non-Macrocyclic Small Molecule Inhibitors against the NS3/4A Serine Protease of Hepatitis C Virus through in Silico Screening

Drug discovery and design for inhibition of the Hepatitis C Virus (HCV) NS3/4A serine protease is a major challenge. The broad, shallow, and generally featureless nature of the active site makes it a difficult target for "hit" selection especially using standard docking programs. There are several macrocyclic NS3/4A protease inhibitors that have been approved or are in clinical trials to treat chronic HCV (alone or as combination therapy), but most of the current therapies for HCV infection have untoward side effects, indicating a continuing medical need for the discovery of novel therapeutics with improved efficacy. In this study, we designed and implemented a two-tiered and progressive docking regime that successfully identified five non-macrocyclic small molecules that show inhibitory activity in the low micromolar range. Of these, four compounds show varying inhibition against HCV subgenotypes 1b, 1a, 2a, and 4d. The top inhibitor (3) has an IC(50) value of 15 μM against both subgenotypes 1b and 2a of the NS3/4A protease enzyme. Another inhibitor, 1, inhibits all four subgenotypes with moderate activity, showing highest activity for genotype 2a (24 μM). The five inhibitors presented in this study could be valuable candidates for future hit to lead optimization. Additionally, enzyme-inhibitor interaction models presented herein provide key information regarding structural differences between the active sites of the NS3/4A protease of the HCV subgenotype 1a and 1b that might explain the variable inhibitory activity between subgenotypes of the small molecule inhibitors identified here.     

Machine-Learning-Enabled Virtual Screening for Inhibitors of Lysine-Specific Histone Demethylase 1

A machine learning approach has been applied to virtual screening for lysine specific demethylase 1 (LSD1) inhibitors. LSD1 is an important anti-cancer target. Machine learning models to predict activity were constructed using Morgan molecular fingerprints. The dataset, consisting of 931 molecules with LSD1 inhibition activity, was obtained from the ChEMBL database. An evaluation of several candidate algorithms on the main dataset revealed that the support vector regressor gave the best model, with a coefficient of determination (R2) of 0.703. Virtual screening, using this model, identified five predicted potent inhibitors from the ZINC database comprising more than 300,000 molecules. The virtual screening recovered a known inhibitor, RN1, as well as four compounds where activity against LSD1 had not previously been suggested. Thus, we performed a machine-learning-enabled virtual screening of LSD1 inhibitors using only the structural information of the molecules.     

Oleanane-Type Triterpene Conjugates with 1H-1,2,3-Triazole Possessing of Fungicidal Activity

The triazole pesticide is an organic nitrogen-containing heterocyclic compound with a 1,2,3-Triazole ring. In order to develop a potential glucosamine-6-phosphate synthase (GlmS) inhibitor bactericide, 18 triazole-derivative compounds were synthesized efficiently. In addition, these compounds have not been reported in the literature. The structure was confirmed by high-resolution mass spectrometry (HRMS), 1H NMR and 13C NMR. The potential use of the most promising derivatives has been investigated by testing their antifungal activity and enzyme inhibitory activity, revealing inhibitory activities in the low micromolar range. Among them, the antifungal effects of compounds 1e, 1f, 1g, 2e, 2f, and 2g on Sclerotinia sclerotiorum were particularly significant, all of which were above 83%. These compounds will be further investigated as potential antifungal lead compounds. Their structure–activity relationships are discussed based on the effects of substituted phenyl groups on compounds.