A novel binding pocket in the D2 domain of protein tyrosine phosphatase mu (PTPmu) guides AI screen to identify small molecules that modulate tumour cell adhesion, growth and migration.

Approximately 40% of people will get cancer in their lifetime in the US, and 20% are predicted to die from the condition when it is invasive and metastatic. Targeted screening for drugs that interact with proteins that drive cancer cell growth and migration can lead to new therapies. We screened molecular libraries with the AtomNet® AI-based drug design tool to identify compounds predicted to interact with the cytoplasmic domain of protein tyrosine phosphatase mu. Protein tyrosine phosphatase mu (PTPmu) is proteolytically downregulated in cancers such as glioblastoma generating fragments that stimulate cell survival and migration. Aberrant nuclear localization of PTPmu intracellular fragments drives cancer progression, so we targeted a predicted drug-binding site between the two cytoplasmic phosphatase domains we termed a D2 binding pocket. The function of the D2 domain is controversial with various proposed regulatory functions, making the D2 domain an attractive target for the development of allosteric drugs. Seventy-five of the best-scoring and chemically diverse computational hits predicted to interact with the D2 binding pocket were screened for effects on tumour cell motility and growth in 3D culture as well as in a direct assay for PTPmu-dependent adhesion. We identified two high-priority hits that inhibited the migration and glioma cell sphere formation of multiple glioma tumour cell lines as well as aggregation. We also identified one activator of PTPmu-dependent aggregation, which was able to stimulate cell migration. We propose that the PTPmu D2 binding pocket represents a novel regulatory site and that inhibitors targeting this region may have therapeutic potential for treating cancer.

Small molecule antagonists of PTPmu identified by artificial intelligence-based computational screening block glioma cell migration and growth.

PTPmu (PTPµ) is a member of the receptor protein tyrosine phosphatase IIb family that participates in both homophilic cell-cell adhesion and signaling. PTPmu is proteolytically downregulated in glioblastoma generating extracellular and intracellular fragments that have oncogenic activity. The intracellular fragments, in particular, are known to accumulate in the cytoplasm and nucleus where they interact with inappropriate binding partners/substrates generating signals required for glioma cell migration and growth. Thus, interfering with these fragments is an attractive therapeutic strategy. To develop agents that target these fragments, we used the AI-based AtomNetⓇ model, a drug design and discovery tool, to virtually screen molecular libraries for compounds able to target a binding pocket bordered by the wedge domain, a known regulatory motif located within the juxtamembrane portion of the protein. Seventy-four high-scoring and chemically diverse virtual hits were then screened in multiple cell-based assays for effects on glioma cell motility (scratch assays) and growth in 3D culture (sphere assays), and PTPmu-dependent adhesion (Sf9 aggregation). We identified three inhibitors (247678835, 247682206, 247678791) that affected the motility of multiple glioma cell lines (LN229, U87MG, and Gli36delta5), the growth of LN229 and Gli36 spheres, and PTPmu-dependent Sf9 aggregation. Compound 247678791 was further shown to suppress PTPmu enzymatic activity in an in vitro phosphatase assay, and 247678835 was able to inhibit the growth of human glioma tumors in mice. We propose that these three compounds are PTPmu-targeting agents with therapeutic potential for treating glioblastoma.

Not Every Hit-Identification Technique Works on 1-Deoxy-d-Xylulose 5-Phosphate Synthase (DXPS): Making the Most of a Virtual Screening Campaign.

In this work, we demonstrate how important it is to investigate not only on-target activity but to keep antibiotic activity against critical pathogens in mind. Since antimicrobial resistance is spreading in bacteria such as Mycobacterium tuberculosis, investigations into new targets are urgently needed. One promising new target is 1-deoxy-d-xylulose 5-phosphate synthase (DXPS) of the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway. We have recently solved the crystal structure of truncated M. tuberculosis DXPS and used it to perform a virtual screening in collaboration with Atomwise Inc. using their deep convolutional neural network-based AtomNet® platform. Of 94 virtual hit compounds only one showed interesting results in binding and activity studies. We synthesized 30 close derivatives using a straightforward synthetic route that allowed for easy derivatization. However, no improvement in activity was observed for any of the derivatives. Therefore, we tested them against a variety of pathogens and found them to be good inhibitors against Escherichia coli.

Artificial Intelligence-Based Computational Screening and Functional Assays Identify Candidate Small Molecule Antagonists of PTPmu-Dependent Adhesion.

PTPmu (PTPµ) is a member of the receptor protein tyrosine phosphatase IIb family that participates in cell-cell adhesion and signaling. PTPmu is proteolytically downregulated in glioblastoma (glioma), and the resulting extracellular and intracellular fragments are believed to stimulate cancer cell growth and/or migration. Therefore, drugs targeting these fragments may have therapeutic potential. Here, we used the AtomNet® platform, the first deep learning neural network for drug design and discovery, to screen a molecular library of several million compounds and identified 76 candidates predicted to interact with a groove between the MAM and Ig extracellular domains required for PTPmu-mediated cell adhesion. These candidates were screened in two cell-based assays: PTPmu-dependent aggregation of Sf9 cells and a tumor growth assay where glioma cells grow in three-dimensional spheres. Four compounds inhibited PTPmu-mediated aggregation of Sf9 cells, six compounds inhibited glioma sphere formation/growth, while two priority compounds were effective in both assays. The stronger of these two compounds inhibited PTPmu aggregation in Sf9 cells and inhibited glioma sphere formation down to 25 micromolar. Additionally, this compound was able to inhibit the aggregation of beads coated with an extracellular fragment of PTPmu, directly demonstrating an interaction. This compound presents an interesting starting point for the development of PTPmu-targeting agents for treating cancer including glioblastoma.

AtomNet-Aided OTUD7B Inhibitor Discovery and Validation.

Protein deubiquitinases play critical pathophysiological roles in cancer. Among all deubiquitinases, an oncogenic function for OTUD7B has been established in genetic NSCLC murine models. However, few deubiquitinase inhibitors have been developed due to technical challenges. Here, we report a putative small molecule OTUD7B inhibitor obtained from an AI-aided screen of a 4 million compound library. We validated the effects of the OTUD7B inhibitor (7Bi) in reducing Akt-pS473 signals in multiple NSCLC and HEK293 cells by blocking OTUD7B-governed GßL deubiquitination in cells, as well as inhibiting OTUD7B-mediated cleavage of K11-linked di-ub in an in vitro enzyme assay. Furthermore, we report in leukemia cells, either genetic depletion or 7Bi-mediated pharmacological inhibition of OTUD7B reduces Akt-pS473 via inhibiting the OTUD7B/GßL signaling axis. Together, our study identifies the first putative OTUD7B inhibitor showing activities both in cells and in vitro, with promising applications as a therapeutic agent in treating cancer with OTUD7B overexpression.

SPOP and OTUD7A Control EWS-FLI1 Protein Stability to Govern Ewing Sarcoma Growth.

Chromosomal translocation results in development of an Ewing sarcoma breakpoint region 1-Friend leukemia integration 1 (EWS-FLI1) fusion oncogene in the majority of Ewing sarcoma. The persistent dependence of the tumor for this oncoprotein points to EWS-FLI1 as an ideal drug target. Although EWS-FLI1 transcriptional targets and binding partners are evaluated, the mechanisms regulating EWS-FLI1 protein stability remain elusive. Speckle-type POZ protein (SPOP) and OTU domain-containing protein 7A (OTUD7A) are identified as the bona fide E3 ligase and deubiquitinase, respectively, that control EWS-FLI1 protein turnover in Ewing sarcoma. Casein kinase 1-mediated phosphorylation of the VTSSS degron in the FLI1 domain enhances SPOP activity to degrade EWS-FLI1. Opposing this process, OTUD7A deubiquitinates and stabilizes EWS-FLI1. Depletion of OTUD7A in Ewing sarcoma cell lines reduces EWS-FLI1 protein abundance and impedes Ewing sarcoma growth in vitro and in mice. Performing an artificial-intelligence-based virtual drug screen of a 4-million small molecule library, 7Ai is identified as a potential OTUD7A catalytic inhibitor. 7Ai reduces EWS-FLI1 protein levels and decreases Ewing sarcoma growth in vitro and in a xenograft mouse model. This study supports the therapeutic targeting of OTUD7A as a novel strategy for Ewing sarcoma bearing EWS-FLI1 and related fusions, and may also be applicable to other cancers dependent on aberrant FLI1 expression.

In silico molecular comparisons of C. elegans and mammalian pharmacology identify distinct targets that regulate feeding.

Phenotypic screens can identify molecules that are at once penetrant and active on the integrated circuitry of a whole cell or organism. These advantages are offset by the need to identify the targets underlying the phenotypes. Additionally, logistical considerations limit screening for certain physiological and behavioral phenotypes to organisms such as zebrafish and C. elegans. This further raises the challenge of elucidating whether compound-target relationships found in model organisms are preserved in humans. To address these challenges we searched for compounds that affect feeding behavior in C. elegans and sought to identify their molecular mechanisms of action. Here, we applied predictive chemoinformatics to small molecules previously identified in a C. elegans phenotypic screen likely to be enriched for feeding regulatory compounds. Based on the predictions, 16 of these compounds were tested in vitro against 20 mammalian targets. Of these, nine were active, with affinities ranging from 9 nM to 10 µM. Four of these nine compounds were found to alter feeding. We then verified the in vitro findings in vivo through genetic knockdowns, the use of previously characterized compounds with high affinity for the four targets, and chemical genetic epistasis, which is the effect of combined chemical and genetic perturbations on a phenotype relative to that of each perturbation in isolation. Our findings reveal four previously unrecognized pathways that regulate feeding in C. elegans with strong parallels in mammals. Together, our study addresses three inherent challenges in phenotypic screening: the identification of the molecular targets from a phenotypic screen, the confirmation of the in vivo relevance of these targets, and the evolutionary conservation and relevance of these targets to their human orthologs.

Carbamoylation abrogates the antioxidant potential of hydrogen sulfide.

Hydrogen sulfide (H2S) has been identified as the third gasotransmitter. Beside its role as signaling molecule in the cardiovascular and nervous system the antioxidant and cyto-protective properties of H2S have gained much attention. In the present study we show that cyanate, an uremic toxin which is found in abundant concentration in sera of patients suffering from chronic kidney disease (CKD), can abrogate the antioxidant and cytoprotective activity of H2S via S-carbamoylation reaction, a reaction that previously has only been shown to have a physiological effect on cysteine groups, but not on H2S. Carbamoylation strongly inhibited the free radical scavenging (ABTS(+·) and alkylperoxyl ROO(·)) properties of H2S. The extent of intracellular ROS formation induced by ROO(·) was diminished by H2S whereas carbamoylation counteracted the protective effect. Reagent HOCl was rapidly inactivated by H2S in contrast to the carbamoylated compound. Protein modification by HOCl was inhibited by H2S but carbamoylation significantly reduced the effect. Thus, S-carbamoylation of low molecular weight thiols by abrogating their antioxidant potential may contribute to the higher oxidative stress observed in CKD.

Synthesis and biological evaluation of the 1-arylpyrazole class of σ(1) receptor antagonists: identification of 4-{2-[5-methyl-1-(naphthalen-2-yl)-1H-pyrazol-3-yloxy]ethyl}morpholine (S1RA, E-52862).

The synthesis and pharmacological activity of a new series of 1-arylpyrazoles as potent σ(1) receptor (σ(1)R) antagonists are reported. The new compounds were evaluated in vitro in human σ(1)R and guinea pig σ(2) receptor (σ(2)R) binding assays. The nature of the pyrazole substituents was crucial for activity, and a basic amine was shown to be necessary, in accordance with known receptor pharmacophores. A wide variety of amines and spacer lengths between the amino and pyrazole groups were tolerated, but only the ethylenoxy spacer and small cyclic amines provided compounds with sufficient selectivity for σ(1)R vs σ(2)R. The most selective compounds were further profiled, and compound 28, 4-{2-[5-methyl-1-(naphthalen-2-yl)-1H-pyrazol-3-yloxy]ethyl}morpholine (S1RA, E-52862), which showed high activity in the mouse capsaicin model of neurogenic pain, emerged as the most interesting candidate. In addition, compound 28 exerted dose-dependent antinociceptive effects in several neuropathic pain models. This, together with its good physicochemical, safety, and ADME properties, led compound 28 to be selected as clinical candidate.

Chemical informatics and target identification in a zebrafish phenotypic screen.

Target identification is a core challenge in chemical genetics. Here we use chemical similarity to computationally predict the targets of 586 compounds that were active in a zebrafish behavioral assay. Among 20 predictions tested, 11 compounds had activities ranging from 1 nM to 10,000 nM on the predicted targets. The roles of two of these targets were tested in the original zebrafish phenotype. Prediction of targets from chemotype is rapid and may be generally applicable.

Identification of chemically diverse, novel inhibitors of 17ß-hydroxysteroid dehydrogenase type 3 and 5 by pharmacophore-based virtual screening.

17ß-Hydroxysteroid dehydrogenase type 3 and 5 (17ß-HSD3 and 17ß-HSD5) catalyze testosterone biosynthesis and thereby constitute therapeutic targets for androgen-related diseases or endocrine-disrupting chemicals. As a fast and efficient tool to identify potential ligands for 17ßHSD3/5, ligand- and structure-based pharmacophore models for both enzymes were developed. The models were evaluated first by in silico screening of commercial compound databases and further experimentally validated by enzymatic efficacy tests of selected virtual hits. Among the 35 tested compounds, 11 novel inhibitors with distinct chemical scaffolds, e.g. sulfonamides and triazoles, and with different selectivity properties were discovered. Thereby, we provide several potential starting points for further 17ß-HSD3 and 17ß-HSD5 inhibitor development. Article from the Special issue on Targeted Inhibitors.

Structure-activity relationship and multidrug resistance study of new S-trityl-L-cysteine derivatives as inhibitors of Eg5.

The mitotic spindle is a validated target for cancer chemotherapy. Drugs such as taxanes and vinca alkaloids specifically target microtubules and cause the mitotic spindle to collapse. However, toxicity and resistance are problems associated with these drugs. Thus, alternative approaches to inhibiting the mitotic spindle are being pursued. These include targeting Eg5, a human kinesin involved in the formation of the bipolar spindle. We previously identified S-trityl-L-cysteine (STLC) as a potent allosteric inhibitor of Eg5. Here, we report the synthesis of a new series of STLC-like compounds with in vitro inhibition in the low nanomolar range. We also performed a multidrug resistance study in cell lines overexpressing P-glycoprotein and showed that some of these inhibitors may have the potential to overcome susceptibility to this efflux pump. Finally, we performed molecular docking of the compounds and determined the structures of two Eg5-inhibitor complexes to explain the structure-activity relationship of these compounds.

Structure-activity relationships and molecular docking of novel dihydropyrimidine-based mitotic Eg5 inhibitors.

Dihydropyrimidine-based compounds belong to the first discovered inhibitors of the human mitotic kinesin Eg5. Although they are used by many research groups as model compounds for chemical genetics, considerably less emphasis has been placed on the improvement of this type of inhibitor, with the exception of two recent studies. Dihydropyrimidines can be divided into class I (analogues that bind in the S configuration) and class II type inhibitors, which bind in the R configuration. Herein we report the synthesis and optimization of novel class II type dihydropyrimidines using a combination of in vitro and docking techniques.

Applications of integrated data mining methods to exploring natural product space for acetylcholinesterase inhibitors.

Nature, especially the plant kingdom, is a rich source for novel bioactive compounds that can be used as lead compounds for drug development. In order to exploit this resource, the two neural network-based virtual screening techniques novelty detection with self-organizing maps (SOMs) and counterpropagation neural network were evaluated as tools for efficient lead structure discovery. As application scenario, significant descriptors for acetylcholinesterase (AChE) inhibitors were determined and used for model building, theoretical model validation, and virtual screening. Top-ranked virtual hits from both approaches were docked into the AChE binding site to approve the initial hits. Finally, in vitro testing of selected compounds led to the identification of forsythoside A and (+)-sesamolin as novel AChE inhibitors.

Design, synthesis and SAR analysis of novel selective sigma1 ligands (Part 2).

In order to investigate the molecular features involved in sigma receptors (sigma-Rs) binding, new compounds based on arylalkylaminoalcoholic, arylalkenyl- and arylalkylaminic scaffolds were synthesized and their affinity towards sigma(1)- and sigma(2)-Rs subtypes was evaluated. The most promising compounds were also screened for their affinity at micro-opioid, delta-opioid and kappa-opioid receptors. Biological results are herein presented and discussed.

Rapid behavior-based identification of neuroactive small molecules in the zebrafish.

Neuroactive small molecules are indispensable tools for treating mental illnesses and dissecting nervous system function. However, it has been difficult to discover novel neuroactive drugs. Here, we describe a high-throughput, behavior-based approach to neuroactive small molecule discovery in the zebrafish. We used automated screening assays to evaluate thousands of chemical compounds and found that diverse classes of neuroactive molecules caused distinct patterns of behavior. These 'behavioral barcodes' can be used to rapidly identify new psychotropic chemicals and to predict their molecular targets. For example, we identified new acetylcholinesterase and monoamine oxidase inhibitors using phenotypic comparisons and computational techniques. By combining high-throughput screening technologies with behavioral phenotyping in vivo, behavior-based chemical screens can accelerate the pace of neuroactive drug discovery and provide small-molecule tools for understanding vertebrate behavior.

The UV-filter benzophenone-1 inhibits 17beta-hydroxysteroid dehydrogenase type 3: Virtual screening as a strategy to identify potential endocrine disrupting chemicals.

The prevalence of male reproductive disorders and testicular cancer is steadily increasing. Because the exposure to chemicals disrupting natural hormone action has been associated with these diseases, it is important to identify endocrine disrupting chemicals (EDCs) and their targets of action. Here, a 3D-structural database that can be applied for virtual screening approaches to facilitate the identification of EDCs was constructed. The database was screened using pharmacophores of 17beta-hydroxysteroid dehydrogenase type 3 (17beta-HSD3), which catalyzes the last step of testosterone synthesis in testicular Leydig cells and plays an essential role during male sexual development. Among other chemicals, benzophenone (BP) UV-filters were predicted as potential 17beta-HSD3 inhibitors. Biological analyses revealed (2,4-dihydroxyphenyl)-phenylmethanone (also known as benzophenone-1, BP-1) as an inhibitor of human 17beta-HSD3 (IC(50) 1.05microM). BP-1 also efficiently blocked conversion of androstenedione to testosterone by mouse and rat 17beta-HSD3 in whole-organ enzyme assays. Moreover, BP-1 antagonized the testosterone-dependent activation of androgen receptors (IC(50) 5.7microM), suggesting synergistic anti-androgenic effects of BP-1 by preventing testosterone formation and blocking receptor activation. In addition, analyses of several commonly used UV-filters on estrogen- and androgen-metabolizing 17beta-HSD enzymes revealed 3-benzylidene camphor (3-BC) and 4-methylbenzylidene camphor (4-MBC) as low micromolar 17beta-HSD2 inhibitors. In conclusion, screening of virtual chemical structure libraries can facilitate the identification of compounds interfering with hormone action. The potential disruption of 17beta-HSD enzyme function by the UV-filters BP-1, 3-BC and 4-MBC requires further investigation and should be considered for safety assessment of these chemicals.

Predicting new molecular targets for known drugs.

Although drugs are intended to be selective, at least some bind to several physiological targets, explaining side effects and efficacy. Because many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here we compared 3,665 US Food and Drug Administration (FDA)-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the beta(1) receptor by the transporter inhibitor Prozac, the inhibition of the 5-hydroxytryptamine (5-HT) transporter by the ion channel drug Vadilex, and antagonism of the histamine H(4) receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug-target associations were confirmed, five of which were potent (<100 nM). The physiological relevance of one, the drug N,N-dimethyltryptamine (DMT) on serotonergic receptors, was confirmed in a knockout mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.

Quantifying biogenic bias in screening libraries.

In lead discovery, libraries of 10(6) molecules are screened for biological activity. Given the over 10(60) drug-like molecules thought possible, such screens might never succeed. The fact that they do, even occasionally, implies a biased selection of library molecules. We have developed a method to quantify the bias in screening libraries toward biogenic molecules. With this approach, we consider what is missing from screening libraries and how they can be optimized.