Discovery and Development Strategies for SARS-CoV-2 NSP3 Macrodomain Inhibitors.

The worldwide public health and socioeconomic consequences caused by the COVID-19 pandemic highlight the importance of increasing preparedness for viral disease outbreaks by providing rapid disease prevention and treatment strategies. The NSP3 macrodomain of coronaviruses including SARS-CoV-2 is among the viral protein repertoire that was identified as a potential target for the development of antiviral agents, due to its critical role in viral replication and consequent pathogenicity in the host. By combining virtual and biophysical screening efforts, we discovered several experimental small molecules and FDA-approved drugs as inhibitors of the NSP3 macrodomain. Analogue characterisation of the hit matter and crystallographic studies confirming binding modes, including that of the antibiotic compound aztreonam, to the active site of the macrodomain provide valuable structure-activity relationship information that support current approaches and open up new avenues for NSP3 macrodomain inhibitor development.

Ipso-Nitration of calix[6]azacryptands: intriguing effect of the small rim capping pattern on the large rim substitution selectivity.

The ipso-nitration of calix[6]arene-based molecular receptors is a important synthetic pathway for the elaboration of more sophisticated systems. This reaction has been studied for a variety of capped calixarenes, and a general trend for the regioselective nitration of three aromatic units out of six in moderate to high yield has been observed. This selectivity is, in part, attributed to the electronic connection between the protonated cap at the small rim and the reactive sites at the large rim. In addition, this work highlights the fact that subtle conformational properties can drastically influence the outcome of this reaction.

Accelerating GPCR Drug Discovery With Conformation-Stabilizing VHHs.

The human genome encodes 850 G protein-coupled receptors (GPCRs), half of which are considered potential drug targets. GPCRs transduce extracellular stimuli into a plethora of vital physiological processes. Consequently, GPCRs are an attractive drug target class. This is underlined by the fact that approximately 40% of marketed drugs modulate GPCRs. Intriguingly 60% of non-olfactory GPCRs have no drugs or candidates in clinical development, highlighting the continued potential of GPCRs as drug targets. The discovery of small molecules targeting these GPCRs by conventional high throughput screening (HTS) campaigns is challenging. Although the definition of success varies per company, the success rate of HTS for GPCRs is low compared to other target families (Fujioka and Omori, 2012; Dragovich et al., 2022). Beyond this, GPCR structure determination can be difficult, which often precludes the application of structure-based drug design approaches to arising HTS hits. GPCR structural studies entail the resource-demanding purification of native receptors, which can be challenging as they are inherently unstable when extracted from the lipid matrix. Moreover, GPCRs are flexible molecules that adopt distinct conformations, some of which need to be stabilized if they are to be structurally resolved. The complexity of targeting distinct therapeutically relevant GPCR conformations during the early discovery stages contributes to the high attrition rates for GPCR drug discovery programs. Multiple strategies have been explored in an attempt to stabilize GPCRs in distinct conformations to better understand their pharmacology. This review will focus on the use of camelid-derived immunoglobulin single variable domains (VHHs) that stabilize disease-relevant pharmacological states (termed ConfoBodies by the authors) of GPCRs, as well as GPCR:signal transducer complexes, to accelerate drug discovery. These VHHs are powerful tools for supporting in vitro screening, deconvolution of complex GPCR pharmacology, and structural biology purposes. In order to demonstrate the potential impact of ConfoBodies on translational research, examples are presented of their role in active state screening campaigns and structure-informed rational design to identify de novo chemical space and, subsequently, how such matter can be elaborated into more potent and selective drug candidates with intended pharmacology.

Computational Chemistry on a Budget: Supporting Drug Discovery with Limited Resources.

An increasing number of new drugs have their origin in small biotech or academia. In contrast to big pharma, these environments are often more limited in terms of resources, and this necessitates different approaches to the drug discovery process. In this review, we outline how computational methods can help advance drug discovery in a setting with more limited resources and we share what, based on our experience, are the best practices for these methods.

TargetDB: A target information aggregation tool and tractability predictor.

When trying to identify new potential therapeutic protein targets, access to data and knowledge is increasingly important. In a field where new resources and data sources become available every day, it is crucial to be able to take a step back and look at the wider picture in order to identify potential drug targets. While this task is routinely performed by bespoke literature searches, it is often time-consuming and lacks uniformity when comparing multiple targets at one time. To address this challenge, we developed TargetDB, a tool that aggregates public information available on given target(s) (links to disease, safety, 3D structures, ligandability, novelty, etc.) and assembles it in an easy to read output ready for the researcher to analyze. In addition, we developed a target scoring system based on the desirable attributes of good therapeutic targets and machine learning classification system to categorize novel targets as having promising or challenging tractrability. In this manuscript, we present the methodology used to develop TargetDB as well as test cases.

Selective inhibition of the K+ efflux sensitive NLRP3 pathway by Cl- channel modulation.

The NLRP3 inflammasome regulates production of the pro-inflammatory cytokines interleukin-1ß (IL-1ß) and IL-18, and contributes to inflammation exacerbating disease. Fenamate non-steroidal anti-inflammatory drugs (NSAIDs) were recently described as NLRP3 inflammasome inhibitors via chloride channel inhibition. Fenamate NSAIDs inhibit cyclooxygenase (COX) enzymes, limiting their potential as therapeutics for NLRP3-associated diseases due to established side effects. The aim here was to develop properties of the fenamates that inhibit NLRP3, and at the same time to reduce COX inhibition. We synthesised a library of analogues, with feedback from in silico COX docking potential, and IL-1ß release inhibitory activity. Through iterative screening and rational chemical design, we established a collection of chloride channel inhibiting active lead molecules with potent activity at the canonical NLRP3 inflammasome and no activity at COX enzymes, but only in response to stimuli that activated NLRP3 by a K+ efflux-dependent mechanism. This study identifies a model for the isolation and removal of unwanted off-target effects, with the enhancement of desired activity, and establishes a new chemical motif for the further development of NLRP3 inflammasome inhibitors.

Integrated Synthetic, Biophysical, and Computational Investigations of Covalent Inhibitors of Prolyl Oligopeptidase and Fibroblast Activation Protein α.

Over the past decade, there has been increasing interest in covalent inhibition as a drug design strategy. Our own interest in the development of prolyl oligopeptidase (POP) and fibroblast activation protein α (FAP) covalent inhibitors has led us to question whether these two serine proteases were equal in terms of their reactivity toward electrophilic warheads. To streamline such investigations, we exploited both computational and experimental methods to investigate the influence of different reactive groups on both potency and binding kinetics using both our own series of POP inhibitors and others' discovered hits. A direct correlation between inhibitor reactivity and residence time was demonstrated through quantum mechanics methods and further supported by experimental studies. This computational method was also successfully applied to FAP, as an overview of known FAP inhibitors confirmed our computational predictions that more reactive warheads (e.g., boronic acids) must be employed to inhibit FAP than for POP.

A genetics-led approach defines the drug target landscape of 30 immune-related traits.

Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection1. Drug targets with genetic support are more likely to be therapeutically valid2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging4-6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority index) successfully identifies current therapeutics, predicts activity in high-throughput cellular screens (including L1000, CRISPR, mutagenesis and patient-derived cell assays), enables prioritization of under-explored targets and allows for determination of target-level trait relationships. The priority index is an open-access, scalable system accelerating early-stage drug target selection for immune-mediated disease.

Rapid measurement of inhibitor binding kinetics by isothermal titration calorimetry.

Although drug development typically focuses on binding thermodynamics, recent studies suggest that kinetic properties can strongly impact a drug candidate's efficacy. Robust techniques for measuring inhibitor association and dissociation rates are therefore essential. To address this need, we have developed a pair of complementary isothermal titration calorimetry (ITC) techniques for measuring the kinetics of enzyme inhibition. The advantages of ITC over standard techniques include speed, generality, and versatility; ITC also measures the rate of catalysis directly, making it ideal for quantifying rapid, inhibitor-dependent changes in enzyme activity. We used our methods to study the reversible covalent and non-covalent inhibitors of prolyl oligopeptidase (POP). We extracted kinetics spanning three orders of magnitude, including those too rapid for standard methods, and measured sub-nM binding affinities below the typical ITC limit. These results shed light on the inhibition of POP and demonstrate the general utility of ITC-based enzyme inhibition kinetic measurements.

Covalent inhibitors design and discovery.

In the history of therapeutics, covalent drugs occupy a very distinct category. While representing a significant fraction of the drugs on the market, very few have been deliberately designed to interact covalently with their biological target. In this review, the prevalence of covalent drugs will first be briefly covered, followed by an introduction to their mechanisms of action and more detailed discussions of their discovery and the development of safe and efficient covalent enzyme inhibitors. All stages of a drug discovery program will be covered, from target considerations to lead optimization, strategies to tune reactivity and computational methods. The goal of this article is to provide an overview of the field and to outline good practices that are needed for the proper assessment and development of covalent inhibitors as well as a good understanding of the potential and limitations of current computational methods for the design of covalent drugs.

3-Oxo-hexahydro-1H-isoindole-4-carboxylic Acid as a Drug Chiral Bicyclic Scaffold: Structure-Based Design and Preparation of Conformationally Constrained Covalent and Noncovalent Prolyl Oligopeptidase Inhibitors.

Bicyclic chiral scaffolds are privileged motifs in medicinal chemistry. Over the years, we have reported covalent bicyclic prolyl oligopeptidase inhibitors that were highly selective for POP over a number of homologous proteins. Herein, we wish to report the structure-based design and synthesis of a novel class of POP inhibitors based on hexahydroisoindoles. A docking study guided the selection of structures for synthesis. The stereochemistry, decoration, and position within the molecule of the bicyclic scaffolds were assessed virtually. Following the synthesis of the best candidates, in vitro assays revealed that one member of this chemical series was more active than any of our previous inhibitors with a Ki of 1.0 nM. Additional assays also showed that the scaffold of this potent inhibitor, in contrast to one of our previously reported chemical series, is highly metabolically stable, despite the foreseen potential sites of metabolism. Interestingly, computer docking calculations accurately predicted the optimal features of the inhibitors.

Virtual screening and computational optimization for the discovery of covalent prolyl oligopeptidase inhibitors with activity in human cells.

Our docking program, Fitted, implemented in our computational platform, Forecaster, has been modified to carry out automated virtual screening of covalent inhibitors. With this modified version of the program, virtual screening and further docking-based optimization of a selected hit led to the identification of potential covalent reversible inhibitors of prolyl oligopeptidase activity. After visual inspection, a virtual hit molecule together with four analogues were selected for synthesis and made in one-five chemical steps. Biological evaluations on recombinant POP and FAPα enzymes, cell extracts, and living cells demonstrated high potency and selectivity for POP over FAPα and DPPIV. Three compounds even exhibited high nanomolar inhibitory activities in intact living human cells and acceptable metabolic stability. This small set of molecules also demonstrated that covalent binding and/or geometrical constraints to the ligand/protein complex may lead to an increase in bioactivity.