The Pan-Canadian Chemical Library: A Mechanism to Open Academic Chemistry to High-Throughput Virtual Screening.

Computationally screening chemical libraries to discover molecules with desired properties is a common technique used in early-stage drug discovery. Recent progress in the field now enables the efficient exploration of billions of molecules within days or hours, but this exploration remains confined within the boundaries of the accessible chemistry space. While the number of commercially available compounds grows rapidly, it remains a limited subset of all druglike small molecules that could be synthesized. Here, we present a workflow where chemical reactions typically developed in academia and unconventional in drug discovery are exploited to dramatically expand the chemistry space accessible to virtual screening. We use this process to generate a first version of the Pan-Canadian Chemical Library, a collection of nearly 150 billion diverse compounds that does not overlap with other ultra-large libraries such as Enamine REAL or SAVI and could be a resource of choice for protein targets where other libraries have failed to deliver bioactive molecules.

Development of phenyl-urea-based small molecules that target penicillin-binding protein 4.

Staphylococcus aureus has the ability to invade cortical bone osteocyte lacuno-canalicular networks (OLCNs) and cause osteomyelitis. It was recently established that the cell wall transpeptidase, penicillin-binding protein 4 (PBP4), is crucial for this function, with pbp4 deletion strains unable to invade OLCNs and cause bone pathogenesis in a murine model of S. aureus osteomyelitis. Moreover, PBP4 has recently been found to modulate S. aureus resistance to ß-lactam antibiotics. As such, small molecule inhibitors of S. aureus PBP4 may represent dual functional antimicrobial agents that limit osteomyelitis and/or reverse antibiotic resistance. A high throughput screen recently revealed that the phenyl-urea 1 targets PBP4. Herein, we describe a structure-activity relationship (SAR) study on 1. Leveraging in silico docking and modeling, a set of analogs was synthesized and assessed for PBP4 inhibitory activities. Results revealed a preliminary SAR and identified lead compounds with enhanced binding to PBP4, more potent antibiotic resistance reversal, and diminished PBP4 cell wall transpeptidase activity in comparison to 1.

Highly pure DNA-encoded chemical libraries by dual-linker solid-phase synthesis.

The first drugs discovered using DNA-encoded chemical library (DEL) screens have entered late-stage clinical development. However, DEL technology as a whole still suffers from poor chemical purity resulting in suboptimal performance. In this work, we report a technique to overcome this issue through self-purifying release of the DEL after magnetic bead-based synthesis. Both the first and last building blocks of each assembled library member were linked to the beads by tethers that could be cleaved by mutually orthogonal chemistry. Sequential cleavage of the first and last tether, with washing in between, ensured that the final library comprises only the fully complete compounds. The outstanding purity attained by this approach enables a direct correlation of chemical display and encoding, allows for an increased chemical reaction scope, and facilitates the use of more diversity elements while achieving greatly improved signal-to-noise ratios in selections.

Development of small molecule-drug conjugates based on derivatives of natural proteasome inhibitors that exhibit selectivity for PSMA-expressing cancer cells.

In this study, we have developedsmall molecule drug conjugates (SMDCs)consisting ofa prostate specific membrane antigen (PSMA) ligandand syringolin derivatives, which are potent proteasome inhibitors, to selectively deliver syringolin derivatives to prostate cancer cells. Two parent compounds were used for syringolin derivatives with different linkage sites. These SMDCs exhibited PSMA-expressing cell-selective cytotoxicity and they could potentially be used for safer treatment of cancer.

Correlation of protein binding pocket properties with hits' chemistries used in generation of ultra-large virtual libraries.

Although the size of virtual libraries of synthesizable compounds is growing rapidly, we are still enumerating only tiny fractions of the drug-like chemical universe. Our capability to mine these newly generated libraries also lags their growth. That is why fragment-based approaches that utilize on-demand virtual combinatorial libraries are gaining popularity in drug discovery. These à la carte libraries utilize synthetic blocks found to be effective binders in parts of target protein pockets and a variety of reliable chemistries to connect them. There is, however, no data on the potential impact of the chemistries used for making on-demand libraries on the hit rates during virtual screening. There are also no rules to guide in the selection of these synthetic methods for production of custom libraries. We have used the SAVI (Synthetically Accessible Virtual Inventory) library, constructed using 53 reliable reaction types (transforms), to evaluate the impact of these chemistries on docking hit rates for 40 well-characterized protein pockets. The data shows that the virtual hit rates differ significantly for different chemistries with cross coupling reactions such as Sonogashira, Suzuki-Miyaura, Hiyama and Liebeskind-Srogl coupling producing the highest hit rates. Virtual hit rates appear to depend not only on the property of the formed chemical bond but also on the diversity of available building blocks and the scope of the reaction. The data identifies reactions that deserve wider use through increasing the number of corresponding building blocks and suggests the reactions that are more effective for pockets with certain physical and hydrogen bond-forming properties.

Using DNA-encoded libraries of fragments for hit discovery of challenging therapeutic targets.

INTRODUCTION: The effectiveness of Fragment-based drug design (FBDD) for targeting challenging therapeutic targets has been hindered by two factors: the small library size and the complexity of the fragment-to-hit optimization process. The DNA-encoded library (DEL) technology offers a compelling and robust high-throughput selection approach to potentially address these limitations. AREA COVERED: In this review, the authors propose the viewpoint that the DEL technology matches perfectly with the concept of FBDD to facilitate hit discovery. They begin by analyzing the technical limitations of FBDD from a medicinal chemistry perspective and explain why DEL may offer potential solutions to these limitations. Subsequently, they elaborate in detail on how the integration of DEL with FBDD works. In addition, they present case studies involving both de novo hit discovery and full ligand discovery, especially for challenging therapeutic targets harboring broad drug-target interfaces. EXPERT OPINION: The future of DEL-based fragment discovery may be promoted by both technical advances and application scopes. From the technical aspect, expanding the chemical diversity of DEL will be essential to achieve success in fragment-based drug discovery. From the application scope side, DEL-based fragment discovery holds promise for tackling a series of challenging targets.

Metabolic Rewiring in Cancer: Small Molecule Inhibitors in Colorectal Cancer Therapy.

Alterations in cellular metabolism, such as dysregulation in glycolysis, lipid metabolism, and glutaminolysis in response to hypoxic and low-nutrient conditions within the tumor microenvironment, are well-recognized hallmarks of cancer. Therefore, understanding the interplay between aerobic glycolysis, lipid metabolism, and glutaminolysis is crucial for developing effective metabolism-based therapies for cancer, particularly in the context of colorectal cancer (CRC). In this regard, the present review explores the complex field of metabolic reprogramming in tumorigenesis and progression, providing insights into the current landscape of small molecule inhibitors targeting tumorigenic metabolic pathways and their implications for CRC treatment.

Machine learning framework to predict pharmacokinetic profile of small molecule drugs based on chemical structure.

Accurate prediction of a new compound's pharmacokinetic (PK) profile is pivotal for the success of drug discovery programs. An initial assessment of PK in preclinical species and humans is typically performed through allometric scaling and mathematical modeling. These methods use parameters estimated from in vitro or in vivo experiments, which although helpful for an initial estimation, require extensive animal experiments. Furthermore, mathematical models are limited by the mechanistic underpinning of the drugs' absorption, distribution, metabolism, and elimination (ADME) which are largely unknown in the early stages of drug discovery. In this work, we propose a novel methodology in which concentration versus time profile of small molecules in rats is directly predicted by machine learning (ML) using structure-driven molecular properties as input and thus mitigating the need for animal experimentation. The proposed framework initially predicts ADME properties based on molecular structure and then uses them as input to a ML model to predict the PK profile. For the compounds tested, our results demonstrate that PK profiles can be adequately predicted using the proposed algorithm, especially for compounds with Tanimoto score greater than 0.5, the average mean absolute percentage error between predicted PK profile and observed PK profile data was found to be less than 150%. The suggested framework aims to facilitate PK predictions and thus support molecular screening and design earlier in the drug discovery process.

Research Progress on Spike-Dependent SARS-CoV-2 Fusion Inhibitors and Small Molecules Targeting the S2 Subunit of Spike.

Since the beginning of the COVID-19 pandemic, extensive drug repurposing efforts have sought to identify small-molecule antivirals with various mechanisms of action. Here, we aim to review research progress on small-molecule viral entry and fusion inhibitors that directly bind to the SARS-CoV-2 Spike protein. Early in the pandemic, numerous small molecules were identified in drug repurposing screens and reported to be effective in in vitro SARS-CoV-2 viral entry or fusion inhibitors. However, given minimal experimental information regarding the exact location of small-molecule binding sites on Spike, it was unclear what the specific mechanism of action was or where the exact binding sites were on Spike for some inhibitor candidates. The work of countless researchers has yielded great progress, with the identification of many viral entry inhibitors that target elements on the S1 receptor-binding domain (RBD) or N-terminal domain (NTD) and disrupt the S1 receptor-binding function. In this review, we will also focus on highlighting fusion inhibitors that target inhibition of the S2 fusion function, either by disrupting the formation of the postfusion S2 conformation or alternatively by stabilizing structural elements of the prefusion S2 conformation to prevent conformational changes associated with S2 function. We highlight experimentally validated binding sites on the S1/S2 interface and on the S2 subunit. While most substitutions to the Spike protein to date in variants of concern (VOCs) have been localized to the S1 subunit, the S2 subunit sequence is more conserved, with only a few observed substitutions in proximity to S2 binding sites. Several recent small molecules targeting S2 have been shown to have robust activity over recent VOC mutant strains and/or greater broad-spectrum antiviral activity for other more distantly related coronaviruses.

Development of small molecule drugs targeting immune checkpoints.

Immune checkpoint inhibitors (ICIs) are used to relieve and refuel anti-tumor immunity by blocking the interaction, transcription, and translation of co-inhibitory immune checkpoints or degrading co-inhibitory immune checkpoints. Thousands of small molecule drugs or biological materials, especially antibody-based ICIs, are actively being studied and antibodies are currently widely used. Limitations, such as anti-tumor efficacy, poor membrane permeability, and unneglected tolerance issues of antibody-based ICIs, remain evident but are thought to be overcome by small molecule drugs. Recent structural studies have broadened the scope of candidate immune checkpoint molecules, as well as innovative chemical inhibitors. By way of comparison, small molecule drug-based ICIs represent superior oral bioavailability and favorable pharmacokinetic features. Several ongoing clinical trials are exploring the synergetic effect of ICIs and other therapeutic strategies based on multiple ICI functions, including immune regulation, anti-angiogenesis, and cell cycle regulation. In this review we summarized the current progression of small molecule ICIs and the mechanism underlying immune checkpoint proteins, which will lay the foundation for further exploration.

Kinetics and molecular modeling studies on the inhibition mechanism of GH13 α-glycosidases by small molecule ligands.

Alpha-glucosidase inhibitors play an important role in Diabetes Mellitus (DM) treatment since they prevent postprandial hyperglycemia. The Glycoside Hydrolase family 13 (GH13) is the major family of enzymes acting on substrates containing α-glucoside linkages, such as maltose and amylose/amylopectin chains in starch. Previously, our group identified glycoconjugate 1H-1,2,3-triazoles (GCTs) inhibiting two GH13 α-glycosidases: yeast maltase (MAL12) and porcine pancreatic amylase (PPA). Here, we combined kinetic studies and computational methods on nine GCTs to characterize their inhibitory mechanism. They all behaved as reversible inhibitors, and kinetic models encompassed noncompetitive and various mechanisms of mixed-type inhibition for both enzymes. Most potent inhibitors displayed Ki values of 30 µM for MAL12 (GPESB16) and 37 µM for PPA (GPESB15). Molecular dynamics and docking simulations indicated that on MAL12, GPESB15 and GPESB16 bind in a cavity adjacent to the active site, while on the PPA, GPESB15 was predicted to bind at the entrance of the catalytic site. Notably, despite its putative location within the active site, the binding of GPESB15 does not obstruct the substrate's access to the cleavage site. Our study contributes to paving the way for developing novel therapeutic strategies for managing DM-2 through GH13 α-glycosidases inhibition.

Small-molecule-induced epigenetic rejuvenation promotes SREBP condensation and overcomes barriers to CNS myelin regeneration.

Remyelination failure in diseases like multiple sclerosis (MS) was thought to involve suppressed maturation of oligodendrocyte precursors; however, oligodendrocytes are present in MS lesions yet lack myelin production. We found that oligodendrocytes in the lesions are epigenetically silenced. Developing a transgenic reporter labeling differentiated oligodendrocytes for phenotypic screening, we identified a small-molecule epigenetic-silencing-inhibitor (ESI1) that enhances myelin production and ensheathment. ESI1 promotes remyelination in animal models of demyelination and enables de novo myelinogenesis on regenerated CNS axons. ESI1 treatment lengthened myelin sheaths in human iPSC-derived organoids and augmented (re)myelination in aged mice while reversing age-related cognitive decline. Multi-omics revealed that ESI1 induces an active chromatin landscape that activates myelinogenic pathways and reprograms metabolism. Notably, ESI1 triggered nuclear condensate formation of master lipid-metabolic regulators SREBP1/2, concentrating transcriptional co-activators to drive lipid/cholesterol biosynthesis. Our study highlights the potential of targeting epigenetic silencing to enable CNS myelin regeneration in demyelinating diseases and aging.

Development of Inhibitors, Probes, and PROTAC Provides a Complete Toolbox to Study PARK7 in the Living Cell.

The integration of diverse chemical tools like small-molecule inhibitors, activity-based probes (ABPs), and proteolysis targeting chimeras (PROTACs) advances clinical drug discovery and facilitates the exploration of various biological facets of targeted proteins. Here, we report the development of such a chemical toolbox for the human Parkinson disease protein 7 (PARK7/DJ-1) implicated in Parkinson's disease and cancers. By combining structure-guided design, miniaturized library synthesis, and high-throughput screening, we identified two potent compounds, JYQ-164 and JYQ-173, inhibiting PARK7 in vitro and in cells by covalently and selectively targeting its critical residue, Cys106. Leveraging JYQ-173, we further developed a cell-permeable Bodipy probe, JYQ-196, for covalent labeling of PARK7 in living cells and a first-in-class PARK7 degrader JYQ-194 that selectively induces its proteasomal degradation in human cells. Our study provides a valuable toolbox to enhance the understanding of PARK7 biology in cellular contexts and opens new opportunities for therapeutic interventions.

Identification and characterization of small molecule inhibitors of the LINE-1 retrotransposon endonuclease.

The long interspersed nuclear element-1 (LINE-1 or L1) retrotransposon is the only active autonomously replicating retrotransposon in the human genome. L1 harms the cell by inserting new copies, generating DNA damage, and triggering inflammation. Therefore, L1 inhibition could be used to treat many diseases associated with these processes. Previous research has focused on inhibition of the L1 reverse transcriptase due to the prevalence of well-characterized inhibitors of related viral enzymes. Here we present the L1 endonuclease as another target for reducing L1 activity. We characterize structurally diverse small molecule endonuclease inhibitors using computational, biochemical, and biophysical methods. We also show that these inhibitors reduce L1 retrotransposition, L1-induced DNA damage, and inflammation reinforced by L1 in senescent cells. These inhibitors could be used for further pharmacological development and as tools to better understand the life cycle of this element and its impact on disease processes.

Perspectives and challenges in developing small molecules targeting purine nucleoside phosphorylase.

As a cytosolic enzyme involved in the purine salvage pathway metabolism, purine nucleoside phosphorylase (PNP) plays an important role in a variety of cellular functions but also in immune system, including cell growth, apoptosis and cancer development and progression. Based on its T-cell targeting profile, PNP is a potential target for the treatment of some malignant T-cell proliferative cancers including lymphoma and leukemia, and some specific immunological diseases. Numerous small-molecule PNP inhibitors have been developed so far. However, only Peldesine, Forodesine and Ulodesine have entered clinical trials and exhibited some potential for the treatment of T-cell leukemia and gout. The most recent direction in PNP inhibitor development has been focused on PNP small-molecule inhibitors with better potency, selectivity, and pharmacokinetic property. In this perspective, considering the structure, biological functions, and disease relevance of PNP, we highlight the recent research progress in PNP small-molecule inhibitor development and discuss prospective strategies for designing additional PNP therapeutic agents.

Reversible male contraception by targeted inhibition of serine/threonine kinase 33.

Men or mice with homozygous serine/threonine kinase 33 (STK33) mutations are sterile owing to defective sperm morphology and motility. To chemically evaluate STK33 for male contraception with STK33-specific inhibitors, we screened our multibillion-compound collection of DNA-encoded chemical libraries, uncovered potent STK33-specific inhibitors, determined the STK33 kinase domain structure bound with a truncated hit CDD-2211, and generated an optimized hit CDD-2807 that demonstrates nanomolar cellular potency (half-maximal inhibitory concentration = 9.2 nanomolar) and favorable metabolic stability. In mice, CDD-2807 exhibited no toxicity, efficiently crossed the blood-testis barrier, did not accumulate in brain, and induced a reversible contraceptive effect that phenocopied genetic STK33 perturbations without altering testis size. Thus, STK33 is a chemically validated, nonhormonal contraceptive target, and CDD-2807 is an effective tool compound.

An emerging target for male contraception.

An inhibitor of a nonhormonal target is identified using a DNA-encoded chemical library.

Regulation of cardiac fibroblasts reprogramming into cardiomyocyte-like cells with a cocktail of small molecule compounds.

Myocardial infarction results in extensive cardiomyocyte apoptosis, leading to the formation of noncontractile scar tissue. Given the limited regenerative capacity of adult mammalian cardiomyocytes, direct reprogramming of cardiac fibroblasts (CFs) into cardiomyocytes represents a promising therapeutic strategy for myocardial repair, and small molecule drugs might offer a more attractive alternative to gene editing approaches in terms of safety and clinical feasibility. This study aimed to reprogram rat CFs into cardiomyocytes using a small molecular chemical mixture comprising CHIR99021, Valproic acid, Dorsomorphin, SB431542, and Forskolin. Immunofluorescence analysis revealed a significant increase in the expression of cardiomyocyte-specific markers, including cardiac troponin T (cTnT), Connexin 43 (Cx43), α-actinin, and Tbx5. Changes in intracellular calcium ion levels and Ca2+ signal transfer between adjacent cells were monitored using a calcium ion fluorescence probe. mRNA sequencing analysis demonstrated the upregulation of genes associated with cardiac morphogenesis, myocardial differentiation, and muscle fiber contraction during CF differentiation induced by the small-molecule compounds. Conversely, the expression of fibroblast-related genes was downregulated. These findings suggest that chemical-induced cell fate conversion of rat CFs into cardiomyocyte-like cells is feasible, offering a potential therapeutic solution for myocardial injury.

Virtual Screening of Small Molecules Targeting BCL2 with Machine Learning, Molecular Docking, and MD Simulation.

This study aimed to identify potential BCL-2 small molecule inhibitors using deep neural networks (DNN) and random forest (RF), algorithms as well as molecular docking and molecular dynamics (MD) simulations to screen a library of small molecules. The RF model classified 61% (2355/3867) of molecules as 'Active'. Further analysis through molecular docking with Vina identified CHEMBL3940231, CHEMBL3938023, and CHEMBL3947358 as top-scored small molecules with docking scores of -11, -10.9, and 10.8 kcal/mol, respectively. MD simulations validated these compounds' stability and binding affinity to the BCL2 protein.