PTX80, a novel compound targeting the autophagy receptor p62/SQSTM1 for treatment of cancer.

Cancer cells are dependent on protein quality-control mechanisms, including protein chaperones, the ubiquitin-proteasome system, and autophagy. The p62 receptor is a classical, ubiquitously expressed receptor, involved in many signal transduction pathways. Upregulation and/or reduced degradation of p62 have been implicated in tumor formation and resistance to therapy. PTX80 is a first-in-class novel inhibitor of protein degradation, developed by Pi Therapeutics for the treatment of cancer. PTX80 binds to p62, inducing a decrease in soluble p62 and formation of insoluble p62 aggregates, and failure of polyubiquitinated proteins to colocalize with p62. PTX80 induces proteotoxic stress and activation of unfolded protein response, which, in turn, leads to apoptosis. Targeting p62, which is a major protein degradation hub, may serve as a novel and beneficial strategy for the treatment of cancer.

Conserved interactions required for inhibition of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The COVID-19 pandemic caused by the SARS-CoV-2 requires a fast development of antiviral drugs. SARS-CoV-2 viral main protease (Mpro, also called 3C-like protease, 3CLpro) is a potential target for drug design. Crystal and co-crystal structures of the SARS-CoV-2 Mpro have been solved, enabling the rational design of inhibitory compounds. In this study we analyzed the available SARS-CoV-2 and the highly similar SARS-CoV-1 crystal structures. We identified within the active site of the Mpro, in addition to the inhibitory ligands' interaction with the catalytic C145, two key H-bond interactions with the conserved H163 and E166 residues. Both H-bond interactions are present in almost all co-crystals and are likely to occur also during the viral polypeptide cleavage process as suggested from docking of the Mpro cleavage recognition sequence. We screened in silico a library of 6900 FDA-approved drugs (ChEMBL) and filtered using these key interactions and selected 29 non-covalent compounds predicted to bind to the protease. Additional screen, using DOCKovalent was carried out on DrugBank library (11,414 experimental and approved drugs) and resulted in 6 covalent compounds. The selected compounds from both screens were tested in vitro by a protease activity inhibition assay. Two compounds showed activity at the 50 µM concentration range. Our analysis and findings can facilitate and focus the development of highly potent inhibitors against SARS-CoV-2 infection.

A covalent PIN1 inhibitor selectively targets cancer cells by a dual mechanism of action.

The prolyl isomerase PIN1, a critical modifier of multiple signalling pathways, is overexpressed in the majority of cancers and its activity strongly contributes to tumour initiation and progression. Inactivation of PIN1 function conversely curbs tumour growth and cancer stem cell expansion, restores chemosensitivity and blocks metastatic spread, thus providing the rationale for a therapeutic strategy based on PIN1 inhibition. Notwithstanding, potent PIN1 inhibitors are still missing from the arsenal of anti-cancer drugs. By a mechanism-based screening, we have identified a novel covalent PIN1 inhibitor, KPT-6566, able to selectively inhibit PIN1 and target it for degradation. We demonstrate that KPT-6566 covalently binds to the catalytic site of PIN1. This interaction results in the release of a quinone-mimicking drug that generates reactive oxygen species and DNA damage, inducing cell death specifically in cancer cells. Accordingly, KPT-6566 treatment impairs PIN1-dependent cancer phenotypes in vitro and growth of lung metastasis in vivo.

Deciphering mechanisms of drug sensitivity and resistance to Selective Inhibitor of Nuclear Export (SINE) compounds.

BACKGROUND: Exportin 1 (XPO1) is a well-characterized nuclear export protein whose expression is up-regulated in many types of cancers and functions to transport key tumor suppressor proteins (TSPs) from the nucleus. Karyopharm Therapeutics has developed a series of small-molecule Selective Inhibitor of Nuclear Export (SINE) compounds, which have been shown to block XPO1 function both in vitro and in vivo. The drug candidate, selinexor (KPT-330), is currently in Phase-II/IIb clinical trials for treatment of both hematologic and solid tumors. The present study sought to decipher the mechanisms that render cells either sensitive or resistant to treatment with SINE compounds, represented by KPT-185, an early analogue of KPT-330. METHODS: Using the human fibrosarcoma HT1080 cell line, resistance to SINE was acquired over a period of 10 months of constant incubation with increasing concentration of KPT-185. Cell viability was assayed by MTT. Immunofluorescence was used to compare nuclear export of TSPs. Fluorescence activated cell sorting (FACS), quantitative polymerase chain reaction (qPCR), and immunoblots were used to measure effects on cell cycle, gene expression, and cell death. RNA from naïve and drug treated parental and resistant cells was analyzed by Affymetrix microarrays. RESULTS: Treatment of HT1080 cells with gradually increasing concentrations of SINE resulted in >100 fold decrease in sensitivity to SINE cytotoxicity. Resistant cells displayed prolonged cell cycle, reduced nuclear accumulation of TSPs, and similar changes in protein expression compared to parental cells, however the magnitude of the protein expression changes were more significant in parental cells. Microarray analyses comparing parental to resistant cells indicate that a number of key signaling pathways were altered in resistant cells including expression changes in genes involved in adhesion, apoptosis, and inflammation. While the patterns of changes in transcription following drug treatment are similar in parental and resistant cells, the extent of response was more robust in the parental cells. CONCLUSIONS: These results suggest that SINE resistance is conferred by alterations in signaling pathways downstream of XPO1 inhibition. Modulation of these pathways could potentially overcome the resistance to nuclear export inhibitors.

Structure-based virtual screening approach for discovery of covalently bound ligands.

We present a fast and effective covalent docking approach suitable for large-scale virtual screening (VS). We applied this method to four targets (HCV NS3 protease, Cathepsin K, EGFR, and XPO1) with known crystal structures and known covalent inhibitors. We implemented a customized "VS mode" of the Schrödinger Covalent Docking algorithm (CovDock), which we refer to as CovDock-VS. Known actives and target-specific sets of decoys were docked to selected X-ray structures, and poses were filtered based on noncovalent protein-ligand interactions known to be important for activity. We were able to retrieve 71%, 72%, and 77% of the known actives for Cathepsin K, HCV NS3 protease, and EGFR within 5% of the decoy library, respectively. With the more challenging XPO1 target, where no specific interactions with the protein could be used for postprocessing of the docking results, we were able to retrieve 95% of the actives within 30% of the decoy library and achieved an early enrichment factor (EF1%) of 33. The poses of the known actives bound to existing crystal structures of 4 targets were predicted with an average RMSD of 1.9 Å. To the best of our knowledge, CovDock-VS is the first fully automated tool for efficient virtual screening of covalent inhibitors. Importantly, CovDock-VS can handle multiple chemical reactions within the same library, only requiring a generic SMARTS-based predefinition of the reaction. CovDock-VS provides a fast and accurate way of differentiating actives from decoys without significantly deteriorating the accuracy of the predicted poses for covalent protein-ligand complexes. Therefore, we propose CovDock-VS as an efficient structure-based virtual screening method for discovery of novel and diverse covalent ligands.

Genomic and molecular characterization of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is prevalent worldwide and particularly common in certain regions of Asia. Here we report the whole-exome or targeted deep sequencing of 139 paired ESCC cases, and analysis of somatic copy number variations (SCNV) of over 180 ESCCs. We identified previously uncharacterized mutated genes such as FAT1, FAT2, ZNF750 and KMT2D, in addition to those already known (TP53, PIK3CA and NOTCH1). Further SCNV evaluation, immunohistochemistry and biological analysis suggested their functional relevance in ESCC. Notably, RTK-MAPK-PI3K pathways, cell cycle and epigenetic regulation are frequently dysregulated by multiple molecular mechanisms in this cancer. Our approaches also uncovered many druggable candidates, and XPO1 was further explored as a therapeutic target because it showed both gene mutation and protein overexpression. Our integrated study unmasks a number of novel genetic lesions in ESCC and provides an important molecular foundation for understanding esophageal tumors and developing therapeutic targets.

Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors.

We present the Consensus Induced Fit Docking (cIFD) approach for adapting a protein binding site to accommodate multiple diverse ligands for virtual screening. This novel approach results in a single binding site structure that can bind diverse chemotypes and is thus highly useful for efficient structure-based virtual screening. We first describe the cIFD method and its validation on three targets that were previously shown to be challenging for docking programs (COX-2, estrogen receptor, and HIV reverse transcriptase). We then demonstrate the application of cIFD to the challenging discovery of irreversible Crm1 inhibitors. We report the identification of 33 novel Crm1 inhibitors, which resulted from the testing of 402 purchased compounds selected from a screening set containing 261,680 compounds. This corresponds to a hit rate of 8.2 %. The novel Crm1 inhibitors reveal diverse chemical structures, validating the utility of the cIFD method in a real-world drug discovery project. This approach offers a pragmatic way to implicitly account for protein flexibility without the additional computational costs of ensemble docking or including full protein flexibility during virtual screening.

New model of cystic fibrosis transmembrane conductance regulator proposes active channel-like conformation.

The cystic fibrosis transmembrane conductance regulator (CFTR) is an unusual ABC transporter, functioning as a chloride channel critical for fluid homeostasis in multiple organs. Disruption of CFTR function is associated with cystic fibrosis making it an attractive therapeutic target. In addition, CFTR blockers are being developed as potential antidiarrheals. CFTR drug discovery is hampered by the lack of high resolution structural data, and considerable efforts have been invested in modeling the channel structure. Although previously published CFTR models that have been made publicly available mostly agree with experimental data relating to the overall structure, they present the channel in an outward-facing conformation that does not agree with expected properties of a "channel-like" structure. Here, we make available a model of CFTR in such a "channel-like" conformation, derived by a unique modeling approach combining restrained homology modeling and ROSETTA refinement. In contrast to others, the present model is in agreement with expected channel properties such as pore shape, dimensions, solvent accessibility, and experimentally derived distances. We have used the model to explore the interaction of open channel blockers within the pore, revealing a common binding mode and ionic interaction with K95, in agreement with experimental data. The binding-site was further validated using a virtual screening enrichment experiment, suggesting the model might be suitable for drug discovery. In addition, we subjected the model to a molecular dynamics simulation, revealing previously unaddressed salt-bridge interactions that may be important for structure stability and pore-lining residues that may take part in Cl(-) conductance.

Conformational changes relevant to channel activity and folding within the first nucleotide binding domain of the cystic fibrosis transmembrane conductance regulator.

Deletion of Phe-508 (F508del) in the first nucleotide binding domain (NBD1) of the cystic fibrosis transmembrane conductance regulator (CFTR) leads to defects in folding and channel gating. NMR data on human F508del NBD1 indicate that an H620Q mutant, shown to increase channel open probability, and the dual corrector/potentiator CFFT-001 similarly disrupt interactions between ß-strands S3, S9, and S10 and the C-terminal helices H8 and H9, shifting a preexisting conformational equilibrium from helix to coil. CFFT-001 appears to interact with ß-strands S3/S9/S10, consistent with docking simulations. Decreases in T(m) from differential scanning calorimetry with H620Q or CFFT-001 suggest direct compound binding to a less thermostable state of NBD1. We hypothesize that, in full-length CFTR, shifting the conformational equilibrium to reduce H8/H9 interactions with the uniquely conserved strands S9/S10 facilitates release of the regulatory region from the NBD dimerization interface to promote dimerization and thereby increase channel open probability. These studies enabled by our NMR assignments for F508del NBD1 provide a window into the conformational fluctuations within CFTR that may regulate function and contribute to folding energetics.

Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening.

Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, ~tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators.

5-OMe-UDP is a potent and selective P2Y(6)-receptor agonist.

P2Y nucleotide receptors (P2Y-Rs) play important physiological roles. However, most of the P2Y-R subtypes are still lacking potent and selective agonists and antagonists. Based on data mining analysis of binding interactions in 44 protein-uridine nucleos(t)ides complexes, we designed uracil nucleotides, substituted at the C5/C6 position. All C6-substituted derivatives were inactive at the P2Y(2,4,6)-Rs, while out of the C5-substituted analogues, only 5-OMe-UD(T)P showed activity. To rationalize the data, the ionization and conformation of these analogues were evaluated. The pK(a) values of most analogues substituted at the C5/C6 positions were unaltered compared to UTP (pK(a) 9.42), except for 5-F-UTP nucleotide (pK(a) 7.85). C6-substituted analogues adopt the syn or high-syn conformations, which are disfavored by the receptors, while 5-OMe-UD(T)P adopt the favored anti conformation. Furthermore, 5-OMe-UDP adopts the S sugar puckering, which is the conformation preferred by the P2Y(6)-R, but not the P2Y(2)- or P2Y(4)-Rs. 5-OMe-UDP fulfills the conformational and H-bonding requirements of P2Y(6)-R, thus, making a potent P2Y(6)-R agonist (EC(50) 0.08 microM), more than UDP (EC(50) 0.14 microM).

Study of MDM2 binding to p53-analogues: affinity, helicity, and applicability to drug design.

MDM2 is a key regulator of the p53 tumor-suppressor protein. Here we study the effect of modifications of a p53 N-terminal fragment on its binding to MDM2, using implicit-solvent MD and MM-GB/SA calculations. We provide interpretation of existing experimental data and predict the effect of mutations on binding. Notably 1) We analyze the effect of regulatory phosphorylations at Ser/Thr residues and suggest that a balance between favorable electrostatics and desolvation penalties determines the effect of phosphorylation; 2) We compare the helical stability in solution of p53 alanine mutants and propose a helix stabilizing role for several residues involved in hydrogen bonding and hydrophobic packing; 3) We obtain good correlations between calculated and experimental affinities for a set of peptidomimetic inhibitors, both alone and in combination with p53 analogues, demonstrating potential applicability to drug design. From the technical aspect, protocol optimization and selection of simulation tools are addressed in detail. To the best of our knowledge this is the first published example of MM-GB/SA calculations utilizing a conformational ensemble generated with implicit solvent MD. Our results suggest that this highly efficient variant of classical explicit-solvent MM-GB/SA may be used for studying protein-protein interactions and for the design of peptidomimetic drugs.

PREDICT modeling and in-silico screening for G-protein coupled receptors.

G-protein coupled receptors (GPCRs) are a major group of drug targets for which only one x-ray structure is known (the nondrugable rhodopsin), limiting the application of structure-based drug discovery to GPCRs. In this paper we present the details of PREDICT, a new algorithmic approach for modeling the 3D structure of GPCRs without relying on homology to rhodopsin. PREDICT, which focuses on the transmembrane domain of GPCRs, starts from the primary sequence of the receptor, simultaneously optimizing multiple 'decoy' conformations of the protein in order to find its most stable structure, culminating in a virtual receptor-ligand complex. In this paper we present a comprehensive analysis of three PREDICT models for the dopamine D2, neurokinin NK1, and neuropeptide Y Y1 receptors. A shorter discussion of the CCR3 receptor model is also included. All models were found to be in good agreement with a large body of experimental data. The quality of the PREDICT models, at least for drug discovery purposes, was evaluated by their successful utilization in in-silico screening. Virtual screening using all three PREDICT models yielded enrichment factors 9-fold to 44-fold better than random screening. Namely, the PREDICT models can be used to identify active small-molecule ligands embedded in large compound libraries with an efficiency comparable to that obtained using crystal structures for non-GPCR targets.

G protein-coupled receptors: in silico drug discovery in 3D.

The application of structure-based in silico methods to drug discovery is still considered a major challenge, especially when the x-ray structure of the target protein is unknown. Such is the case with human G protein-coupled receptors (GPCRs), one of the most important families of drug targets, where in the absence of x-ray structures, one has to rely on in silico 3D models. We report repeated success in using ab initio in silico GPCR models, generated by the predict method, for blind in silico screening when applied to a set of five different GPCR drug targets. More than 100,000 compounds were typically screened in silico for each target, leading to a selection of <100 "virtual hit" compounds to be tested in the lab. In vitro binding assays of the selected compounds confirm high hit rates, of 12-21% (full dose-response curves, Ki < 5 microM). In most cases, the best hit was a novel compound (New Chemical Entity) in the 1- to 100-nM range, with very promising pharmacological properties, as measured by a variety of in vitro and in vivo assays. These assays validated the quality of the hits as lead compounds for drug discovery. The results demonstrate the usefulness and robustness of ab initio in silico 3D models and of in silico screening for GPCR drug discovery.