A drug discovery-oriented non-invasive protocol for protein crystal cryoprotection by dehydration, with application for crystallization screening.

In X-ray macromolecular crystallography, cryoprotection of crystals mounted on harvesting loops is achieved when the water in the sample solvent transitions to vitreous ice before crystalline ice forms. This is achieved by rapid cooling in liquid nitrogen or propane. Protocols for protein crystal cryoprotection are based on either increasing environmental pressure or reducing the water fraction in the solvent. This study presents a new protocol for cryoprotecting crystals. It is based on vapour diffusion dehydration of the crystal drop to reduce the water fraction in the solvent by adding a highly concentrated salt solution, 13 M potassium formate (KF13), directly to the reservoir. Cryoprotection by the KF13 protocol is non-invasive to the crystal, high throughput, not labour intensive, can benefit diffraction resolution and ligand binding, and is very useful in cases with high redundancy such as drug discovery projects which utilize very large compound or fragment libraries. Moreover, an application of KF13 to discover new crystal hits from clear drops of equilibrated crystallization screening plates is also shown.

Stable Cell Clones Harboring Self-Replicating SARS-CoV-2 RNAs for Drug Screen

The development of antivirals against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been hampered by the lack of efficient cell-based replication systems that are amenable to high-throughput screens in biosafety level 2 laboratories. Here we report that stable cell clones harboring autonomously replicating SARS-CoV-2 RNAs without S, M, E genes can be efficiently derived from the baby hamster kidney (BHK-21) cell line when a pair of mutations were introduced into the non-structural protein 1 (Nsp1) of SARS-CoV-2 to ameliorate cellular toxicity associated with virus replication. In a proof-of-concept experiment we screened a 273-compound library using replicon cells and identified three compounds as novel inhibitors of SARS-CoV-2 replication. Altogether, this work establishes a robust, cell-based system for genetic and functional analyses of SARS-CoV-2 replication and for the development of antiviral drugs. IMPORTANCE: SARS-CoV-2 replicon systems that have been reported up to date were unsuccessful in deriving stable cell lines harboring non-cytopathic replicons. The transient expression of viral sgmRNA or a reporter gene makes it impractical for industry-scale screening of large compound libraries using these systems. Here, for the first time, we derived stable cell clones harboring the SARS-CoV-2 replicon. These clones may now be conveniently cultured in a standard BSL-2 laboratory for high throughput screen of compound libraries. This achievement represents a ground-breaking discovery that will greatly accelerate the pace of developing treatments for COVID-19.

High-throughput Activity Assay for Screening Inhibitors of the SARS-CoV-2 Mac1 Macrodomain

Macrodomains are a class of conserved ADP-ribosylhydrolases expressed by viruses of pandemic concern, including coronaviruses and alphaviruses. Viral macrodomains are critical for replication and virus-induced pathogenesis; therefore, these enzymes are a promising target for antiviral therapy. However, no potent or selective viral macrodo-main inhibitors currently exist, in part due to the lack of a high-throughput assay for this class of enzymes. Here, we developed a high-throughput ADP-ribosylhydrolase assay using the SARS-CoV-2 macrodomain Mac1. We performed a pilot screen which identified dasatinib and dihydralazine as ADP-ribosylhydrolase inhibitors. Importantly, dasatinib does not inhibit MacroD2, the closest Mac1 homolog in humans. Our study demonstrates the feasibility of identifying selective inhibitors based on ADP-ribosylhydrolase activity, paving the way for screening large compound libraries to identify improved macrodomain inhibitors and explore their potential as antiviral therapies for SARS-CoV-2 and future viral threats.

Automatic Identification of Analogue Series form Large Compound Data Sets: Methods and Applications

Analogue series play a key role in drug discovery. They arise naturally in lead optimization efforts where analogues are explored based on one or a few core structures. However, it is much harder to accurately identify and extract pairs or series of analogue molecules in large compound databases with no predefined core structures. This methodological review outlines the most common and recent methodological developments to automatically identify analogue series in large libraries. Initial approaches focused on using predefined rules to extract scaffold structures, such as the popular Bemis–Murcko scaffold. Later on, the matched molecular pair concept led to efficient algorithms to identify similar compounds sharing a common core structure by exploring many putative scaffolds for each compound. Further developments of these ideas yielded, on the one hand, approaches for hierarchical scaffold decomposition and, on the other hand, algorithms for the extraction of analogue series based on single-site modifications (so-called matched molecular series) by exploring potential scaffold structures based on systematic molecule fragmentation. Eventually, further development of these approaches resulted in methods for extracting analogue series defined by a single core structure with several substitution sites that allow convenient representations, such as R-group tables. These methods enable the efficient analysis of large data sets with hundreds of thousands or even millions of compounds and have spawned many related methodological developments.

Rate-of-Kill (RoK) assays to triage large compound sets for Chagas disease drug discovery: Application to GSK Chagas Box

Chagas disease (CD) is a human disease caused by Trypanosoma cruzi. Whilst endemic in Latin America, the disease is spread around the world due to migration flows, being estimated that 8 million people are infected worldwide and over 10,000 people die yearly of complications linked to CD. Current chemotherapeutics is restricted to only two drugs, i.e. benznidazole (BNZ) and nifurtimox (NIF), both being nitroaromatic compounds sharing mechanism of action and exerting suboptimal efficacy and serious adverse effects. Recent clinical trials conducted to reposition antifungal azoles have turned out disappointing due to poor efficacy outcomes despite their promising preclinical profile. This apparent lack of translation from bench models to the clinic raises the question of whether we are using the right in vitro tools for compound selection. We propose that speed of action and cidality, rather than potency, are properties that can differentiate those compounds with better prospect of success to show efficacy in animal models of CD. Here we investigate the use of in vitro assays looking at the kinetics of parasite kill as a valuable surrogate to tell apart slow- (i.e. azoles targeting CYP51) and fast-acting (i.e. nitroaromatic) compounds. Data analysis and experimental design have been optimised to make it amenable for high-throughput compound profiling. Automated data reduction of experimental kinetic points to tabulated curve descriptors in conjunction with PCA, k-means and hierarchical clustering provide drug discoverers with a roadmap to guide navigation from hit qualification of a screening campaign to compound optimisation programs and assessment of combo therapy potential. As an example, we have studied compounds belonging to the GSK Chagas Box stemmed from the HTS campaign run against the full GSK 1.8 million compounds collection [1].

Identification of Compounds for Butyrylcholinesterase Inhibition

Butyrylcholinesterase (BChE) is a nonspecific cholinesterase enzyme that hydrolyzes choline-based esters. BChE plays a critical role in maintaining normal cholinergic function like acetylcholinesterase (AChE) through hydrolyzing acetylcholine (ACh). Selective BChE inhibition has been regarded as a viable therapeutic approach in Alzheimer’s disease. As of now, a limited number of selective BChE inhibitors are available. To identify BChE inhibitors rapidly and efficiently, we have screened 8998 compounds from several annotated libraries against an enzyme-based BChE inhibition assay in a quantitative high-throughput screening (qHTS) format. From the primary screening, we identified a group of 125 compounds that were further confirmed to inhibit BChE activity, including previously reported BChE inhibitors (e.g., bambuterol and rivastigmine) and potential novel BChE inhibitors (e.g., pancuronium bromide and NNC 756), representing diverse structural classes. These BChE inhibitors were also tested for their selectivity by comparing their IC50 values in BChE and AChE inhibition assays. The binding modes of these compounds were further studied using molecular docking analyses to identify the differences between the interactions of these BChE inhibitors within the active sites of AChE and BChE. Our qHTS approach allowed us to establish a robust and reliable process to screen large compound collections for potential BChE inhibitors.

Engineering ‘Enzymelink’ for screening lead compounds to inhibit mPGES-1 while maintaining prostacyclin synthase activity

Aim: This study investigated our Enzymelinks, COX-2-10aa-mPGES-1 and COX-2-10aa-PGIS, as cellular cross-screening targets for quick identification of lead compounds to inhibit inflammatory PGE2 biosynthesis while maintaining prostacyclin synthesis. Methods: We integrated virtual and wet cross-screening using Enzymelinks to rapidly identify lead compounds from a large compound library. Results: From 380,000 compounds virtually cross-screened with the Enzymelinks, 1576 compounds were identified and used for wet cross-screening using HEK293 cells that overexpressed individual Enzymelinks as targets. The top 15 lead compounds that inhibited mPGES-1 activity were identified. The top compound that specifically inhibited inflammatory PGE2 biosynthesis alone without affecting COX-2 coupled to PGI2 synthase (PGIS) for PGI2 biosynthesis was obtained. Conclusion: Enzymelink technology could advance cyclooxygenase pathway-targeted drug discovery to a significant degree.

High-genus multicompartment vesicles evolved from large compound micelles

We report a high-genus multicompartment vesicle (HGMV) that is self-assembled from poly(ethylene oxide)-block-poly[4-azophenyl-(2-carbamoyloxymethyl)ethyl methacrylate] (PEO43-b-PACEMA10). The formation process of these HGMVs was investigated by transmission electron microscopy (TEM), fluorescence spectroscopy,...

Bio-instructive materials on-demand – combinatorial chemistry of peptoids, foldamers, and beyond

Combinatorial chemistry allows for the rapid synthesis of large compound libraries for high throughput screenings in biology, medicinal chemistry, or materials science. Especially compounds from a highly modular design are...