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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Synthesis, activity and molecular modeling of a new series of chromones as low molecular weight protein tyrosine phosphatase inhibitors.

Protein tyrosine phosphatases (PTP) are crucial elements in eukaryotic signal transduction. Several reports suggested that the LMW-PTP family has oncogenic relevance. Moreover, LMW-PTP has been recognized as a negative regulator of insulin-mediated mitotic and metabolic signaling. Thus, inhibition of the LMW-PTP can be considered an attractive approach for the design of new therapeutic agents for the treatment of type II diabetes and for new antitumoral drugs. To date very few (and weak) inhibitors of LMW-PTP have been identified. On the basis of the reported weak activity of some flavonoids on phosphatases, we discovered a lead that originated a new class of highly active LMW-PTP inhibitors; these compounds inhibit also PTP-1B and are active in cellular assays. Docking experiments and SAR highlighted the possible binding mode of these compounds to the enzyme, putting the background for the future optimization of their inhibitory activity and selectivity towards the closely related enzyme PTP-1B.

5-Arylidene-2-phenylimino-4-thiazolidinones as PTP1B and LMW-PTP inhibitors.

As part of a project aimed at identifying effective low molecular weight nonphosphorus monoanionic inhibitors of PTPs, we have synthesized 4-[(5-arylidene-4-oxo-2-phenyliminothiazolidin-3-yl)methyl]benzoic acids (4) and evaluated their inhibitory activity against human PTP1B and LMW-PTP enzymes. The introduction of a 2-phenylimino moiety onto the 4-thiazolidinone ring was designed to enhance the inhibitor/enzyme affinity by means of further favourable interactions with residues of the active site and the surrounding loops. Some of the compounds (4a-d, f) showed interesting inhibition levels in the low micromolar range. The 5-arylidene moiety of acids 4 proved to markedly influence the potency of these inhibitors. Molecular modeling experiments inside the binding sites of both enzymes were performed.

Structure-activity relationship of S-trityl-L-cysteine analogues as inhibitors of the human mitotic kinesin Eg5.

The human kinesin Eg5 is a potential drug target for cancer chemotherapy. Eg5 specific inhibitors cause cells to block in mitosis with a characteristic monoastral spindle phenotype. Prolonged metaphase block eventually leads to apoptotic cell death. S-trityl-L-cysteine (STLC) is a tight-binding inhibitor of Eg5 that prevents mitotic progression. It has proven antitumor activity as shown in the NCI 60 tumor cell line screen. It is of considerable interest to define the minimum chemical structure that is essential for Eg5 inhibition and to develop more potent STLC analogues. An initial structure-activity relationship study on a series of STLC analogues reveals the minimal skeleton necessary for Eg5 inhibition as well as indications of how to obtain more potent analogues. The most effective compounds investigated with substitutions at the para-position of one phenyl ring have an estimated K i (app) of 100 nM in vitro and induce mitotic arrest with an EC 50 of 200 nM.

Synthesis, induced-fit docking investigations, and in vitro aldose reductase inhibitory activity of non-carboxylic acid containing 2,4-thiazolidinedione derivatives.

In continuation of our studies, we here report a series of non-carboxylic acid containing 2,4-thiazolidinedione derivatives, analogues of previously synthesized carboxylic acids which we had found to be very active in vitro aldose reductase (ALR2) inhibitors. Although the replacement of the carboxylic group with the carboxamide or N-hydroxycarboxamide one decreased the in vitro ALR2 inhibitory effect, this led to the identification of mainly non-ionized derivatives with micromolar ALR2 affinity. The 5-arylidene moiety deeply influenced the activity of these 2,4-thiazolidinediones. Our induced-fit docking studies suggested that 5-(4-hydroxybenzylidene)-substituted derivatives may bind the polar recognition region of the ALR2 active site by means of the deprotonated phenol group, while their acetic chain and carbonyl group at position 2 of the thiazolidinedione ring form a tight net of hydrogen bonds with amino acid residues of the lipophilic specificity pocket of the enzyme.

The discovery of new 11beta-hydroxysteroid dehydrogenase type 1 inhibitors by common feature pharmacophore modeling and virtual screening.

11beta-Hydroxysteroid dehydrogenase (11beta-HSD) enzymes catalyze the conversion of biologically inactive 11-ketosteroids into their active 11beta-hydroxy derivatives and vice versa. Inhibition of 11beta-HSD1 has considerable therapeutic potential for glucocorticoid-associated diseases including obesity, diabetes, wound healing, and muscle atrophy. Because inhibition of related enzymes such as 11beta-HSD2 and 17beta-HSDs causes sodium retention and hypertension or interferes with sex steroid hormone metabolism, respectively, highly selective 11beta-HSD1 inhibitors are required for successful therapy. Here, we employed the software package Catalyst to develop ligand-based multifeature pharmacophore models for 11beta-HSD1 inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed several selective inhibitors. Efficient inhibition of recombinant human 11beta-HSD1 in intact transfected cells as well as endogenous enzyme in mouse 3T3-L1 adipocytes and C2C12 myotubes was demonstrated for compound 27, which was able to block subsequent cortisol-dependent activation of glucocorticoid receptors with only minor direct effects on the receptor itself. Our results suggest that inhibitor-based pharmacophore models for 11beta-HSD1 in combination with suitable cell-based activity assays, including such for related enzymes, can be used for the identification of selective and potent inhibitors.

Development and validation of an in silico P450 profiler based on pharmacophore models.

In today's drug discovery process, the very early consideration of ADME properties is aimed at a reduction of drug candidate drop out rate in later development stages. Apart from in vitro testing, in silico methods are evaluated as complementary screening tools for compounds with unfavorable ADME attributes. Especially members of the cytochrome P450 (P450) enzyme superfamily-- e.g. P450 1A2, P450 2C9, P450 2C19, P450 2D6, and P450 3A4-- contribute to xenobiotic metabolism, and compound interaction with one of these enzymes is therefore critically evaluated. Pharmacophore models are widely used to identify common features amongst ligands for any target. In this study, both structure-based and ligand-based models for prominent drug-metabolizing members of the P450 family were generated employing the software packages LigandScout and Catalyst. Essential chemical ligand features for substrate and inhibitor activity for all five P450 enzymes investigated were determined and analyzed. Finally, a collection of 11 pharmacophores for substrates and inhibitors was evaluated as an in silico P450 profiling tool that could be used for early ADME estimation of new chemical entities.

Discovery of high-affinity ligands of sigma1 receptor, ERG2, and emopamil binding protein by pharmacophore modeling and virtual screening.

ERG2, emopamil binding protein (EBP), and sigma-1 receptor (sigma(1)) are enzymes of sterol metabolism and an enzyme-related protein, respectively, that share high affinity for various structurally diverse compounds. To discover novel high-affinity ligands, pharmacophore models were built with Catalyst based upon a series of 23 structurally diverse chemicals exhibiting K(i) values from 10 pM to 100 microM for all three proteins. In virtual screening experiments, we retrieved drugs that were previously reported to bind to one or several of these proteins and also tested 11 new hits experimentally, of which three, among them raloxifene, had affinities for sigma(1) or EBP of <60 nM. When used to search a database of 3525 biochemicals of intermediary metabolism, a slightly modified ERG2 pharmacophore model successfully retrieved 10 substrate candidates among the top 28 hits. Our results indicate that inhibitor-based pharmacophore models for sigma(1), ERG2, and EBP can be used to screen drug and metabolite databases for chemically diverse compounds and putative endogenous ligands.

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.