Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Synthesis of Complex Druglike Molecules by the Use of Highly Functionalized Bench-Stable Organozinc Reagents.

The reactivity of a representative set of 17 organozinc pivalates with 18 polyfunctional druglike electrophiles (informers) in Negishi cross-coupling reactions was evaluated by high-throughput experimentation protocols. The high-fidelity scaleup of successful reactions in parallel enabled the isolation of sufficient material for biological testing, thus demonstrating the high value of these new solid zinc reagents in a drug-discovery setting and potentially for many other applications in chemistry. Principal component analysis (PCA) clearly defined the independent roles of the zincates and the informers toward druggable-space coverage.

Stitched α-helical peptides via bis ring-closing metathesis.

Conformationally stabilized α-helical peptides are capable of inhibiting disease-relevant intracellular or extracellular protein-protein interactions in vivo. We have previously reported that the employment of ring-closing metathesis to introduce a single all-hydrocarbon staple along one face of an α-helical peptide greatly increases α-helical content, binding affinity to a target protein, cell penetration through active transport, and resistance to proteolytic degradation. In an effort to improve upon this technology for stabilizing a peptide in a bioactive α-helical conformation, we report the discovery of an efficient and selective bis ring-closing metathesis reaction leading to peptides bearing multiple contiguous staples connected by a central spiro ring junction. Circular dichroism spectroscopy, NMR, and computational analyses have been used to investigate the conformation of these "stitched" peptides, which are shown to exhibit remarkable thermal stabilities. Likewise, trypsin proteolysis assays confirm the achievement of a structural rigidity unmatched by peptides bearing a single staple. Furthermore, fluorescence-activated cell sorting (FACS) and confocal microscopy assays demonstrate that stitched peptides display superior cell penetrating ability compared to their stapled counterparts, suggesting that this technology may be useful not only in the context of enhancing the drug-like properties of α-helical peptides but also in producing potent agents for the intracellular delivery of proteins and oligonucleotides.

Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery.

We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug discovery process. This workflow utilized a three-dimensional (3D) generative modeling method Pocket2Mol, for the de novo design of molecules in spatial perspective for the targeted protein structures, followed by filters for chemical-physical properties and drug-likeness, structure-activity relationship analysis, and clustering to generate top virtual hit scaffolds. In our WDR5 case study, we acquired a focused set of 2029 compounds after a targeted searching within Novartis archived library based on the virtual scaffolds. Subsequently, we experimentally profiled these compounds, resulting in a novel chemical scaffold series that demonstrated activity in biochemical and biophysical assays. Pocket Crafter successfully prototyped an effective end-to-end 3D generative chemistry-based workflow for the exploration of new chemical scaffolds, which represents a promising approach in early drug discovery for hit identification.

Enhancing the Small-Scale Screenable Biological Space beyond Known Chemogenomics Libraries with Gray Chemical Matter─Compounds with Novel Mechanisms from High-Throughput Screening Profiles.

Phenotypic assays have become an established approach to drug discovery. Greater disease relevance is often achieved through cellular models with increased complexity and more detailed readouts, such as gene expression or advanced imaging. However, the intricate nature and cost of these assays impose limitations on their screening capacity, often restricting screens to well-characterized small compound sets such as chemogenomics libraries. Here, we outline a cheminformatics approach to identify a small set of compounds with likely novel mechanisms of action (MoAs), expanding the MoA search space for throughput limited phenotypic assays. Our approach is based on mining existing large-scale, phenotypic high-throughput screening (HTS) data. It enables the identification of chemotypes that exhibit selectivity across multiple cell-based assays, which are characterized by persistent and broad structure activity relationships (SAR). We validate the effectiveness of our approach in broad cellular profiling assays (Cell Painting, DRUG-seq, and Promotor Signature Profiling) and chemical proteomics experiments. These experiments revealed that the compounds behave similarly to known chemogenetic libraries, but with a notable bias toward novel protein targets. To foster collaboration and advance research in this area, we have curated a public set of such compounds based on the PubChem BioAssay dataset and made it available for use by the scientific community.

Mapping targetable sites on human telomerase RNA pseudoknot/template domain using 2'-OMe RNA-interacting polynucleotide (RIPtide) microarrays.

Most cellular RNAs engage in intrastrand base-pairing that gives rise to complex three-dimensional folds. This self-pairing presents an impediment toward binding of the RNA by nucleic acid-based ligands. An important step in the discovery of RNA-targeting ligands is therefore to identify those regions in a folded RNA that are accessible toward the nucleic acid-based ligand. Because the folding of RNA targets can involve interactions between nonadjacent regions and employ both Watson-Crick and non-Watson-Crick base-pairing, screening of candidate binder ensembles is typically necessary. Microarray-based screening approaches have shown great promise in this regard and have suggested that achieving complete sequence coverage would be a valuable attribute of a next generation system. Here, we report a custom microarray displaying a library of RNA-interacting polynucleotides comprising all possible 2'-OMe RNA sequences from 4- to 8-nucleotides in length. We demonstrate the utility of this array in identifying RNA-interacting polynucleotides that bind tightly and specifically to the highly conserved, functionally essential template/pseudoknot domain of human telomerase RNA and that inhibit telomerase function in vitro.

Enforced presentation of an extrahelical guanine to the lesion recognition pocket of human 8-oxoguanine glycosylase, hOGG1.

A poorly understood aspect of DNA repair proteins is their ability to identify exceedingly rare sites of damage embedded in a large excess of nearly identical undamaged DNA, while catalyzing repair only at the damaged sites. Progress toward understanding this problem has been made by comparing the structures and biochemical behavior of these enzymes when they are presented with either a target lesion or a corresponding undamaged nucleobase. Trapping and analyzing such DNA-protein complexes is particularly difficult in the case of base extrusion DNA repair proteins because of the complexity of the repair reaction, which involves extrusion of the target base from DNA followed by its insertion into the active site where glycosidic bond cleavage is catalyzed. Here we report the structure of a human 8-oxoguanine (oxoG) DNA glycosylase, hOGG1, in which a normal guanine from DNA has been forcibly inserted into the enzyme active site. Although the interactions of the nucleobase with the active site are only subtly different for G versus oxoG, hOGG1 fails to catalyze excision of the normal nucleobase. This study demonstrates that even if hOGG1 mistakenly inserts a normal base into its active site, the enzyme can still reject it on the basis of catalytic incompatibility.

Structure of the stapled p53 peptide bound to Mdm2.

Mdm2 is a major negative regulator of the tumor suppressor p53 protein, a protein that plays a crucial role in maintaining genome integrity. Inactivation of p53 is the most prevalent defect in human cancers. Inhibitors of the Mdm2-p53 interaction that restore the functional p53 constitute potential nongenotoxic anticancer agents with a novel mode of action. We present here a 2.0 Å resolution structure of the Mdm2 protein with a bound stapled p53 peptide. Such peptides, which are conformationally and proteolytically stabilized with all-hydrocarbon staples, are an emerging class of biologics that are capable of disrupting protein-protein interactions and thus have broad therapeutic potential. The structure represents the first crystal structure of an i, i + 7 stapled peptide bound to its target and reveals that rather than acting solely as a passive conformational brace, a staple can intimately interact with the surface of a protein and augment the binding interface.

Discovery of an Anion-Dependent Farnesyltransferase Inhibitor from a Phenotypic Screen.

By employing a phenotypic screen, a set of compounds, exemplified by 1, were identified which potentiate the ability of histone deacetylase inhibitor vorinostat to reverse HIV latency. Proteome enrichment followed by quantitative mass spectrometric analysis employing a modified analogue of 1 as affinity bait identified farnesyl transferase (FTase) as the primary interacting protein in cell lysates. This ligand-FTase binding interaction was confirmed via X-ray crystallography and temperature dependent fluorescence studies, despite 1 lacking structural and binding similarity to known FTase inhibitors. Although multiple lines of evidence established the binding interaction, these ligands exhibited minimal inhibitory activity in a cell-free biochemical FTase inhibition assay. Subsequent modification of the biochemical assay by increasing anion concentration demonstrated FTase inhibitory activity in this novel class. We propose 1 binds together with the anion in the active site to inhibit farnesyl transferase. Implications for phenotypic screening deconvolution and HIV reactivation are discussed.