Structures of the σ2 receptor enable docking for bioactive ligand discovery

Structure-based discovery of CFTR potentiators and inhibitors

The cystic fibrosis transmembrane conductance regulator (CFTR) is a crucial ion channel whose loss of function leads to cystic fibrosis, whereas its hyperactivation leads to secretory diarrhea. Small molecules that improve CFTR folding (correctors) or function (potentiators) are clinically available. However, the only potentiator, ivacaftor, has suboptimal pharmacokinetics and inhibitors have yet to be clinically developed. Here, we combine molecular docking, electrophysiology, cryo-EM, and medicinal chemistry to identify CFTR modulators. We docked ∼155 million molecules into the potentiator site on CFTR, synthesized 53 test ligands, and used structure-based optimization to identify candidate modulators. This approach uncovered mid-nanomolar potentiators, as well as inhibitors, that bind to the same allosteric site. These molecules represent potential leads for the development of more effective drugs for cystic fibrosis and secretory diarrhea, demonstrating the feasibility of large-scale docking for ion channel drug discovery.

Multi-target drugs for Alzheimer's disease

Alzheimer's disease (AD), a leading cause of dementia, increasingly challenges our healthcare systems and society. Traditional therapies aimed at single targets have fallen short owing to the complex, multifactorial nature of AD that necessitates simultaneous targeting of various disease mechanisms for clinical success. Therefore, targeting multiple pathologies at the same time could provide a synergistic therapeutic effect. The identification of new disease targets beyond the classical hallmarks of AD offers a fertile ground for the design of new multi-target drugs (MTDs), and building on existing compounds have the potential to yield in successful disease modifying therapies. This review discusses the evolving landscape of MTDs, focusing on their potential as AD therapeutics. Analysis of past and current trials of compounds with multi-target activity underscores the capacity of MTDs to offer synergistic therapeutic effects, and the flourishing genetic understanding of AD will inform and inspire the development of MTD-based AD therapies.

Loss of Sigma-2 Receptor/TMEM97 Is Associated with Neuropathic Injury-Induced Depression-Like Behaviors in Female Mice

Previous studies have shown that ligands that bind to sigma-2 receptor/TMEM97 (s2R/TMEM97), a transmembrane protein, have anxiolytic/antidepressant-like properties and relieve neuropathic pain-like effects in rodents. Despite medical interest in s2R/TMEM97, little affective and pain behavioral characterization has been done using transgenic mice, which limits the development of s2R/TMEM97 as a viable therapeutic target. Using wild-type (WT) and global Tmem97 knock-out (KO) mice, we sought to identify the contribution of Tmem97 in modulating affective and pain-like behaviors using a battery of affective and pain assays, including open field, light/dark preference, elevated plus maze, forced swim test, tail suspension test, and the mechanical sensitivity tests. Our results demonstrate that female Tmem97 KO mice show less anxiety-like and depressive-like behaviors in light/dark preference and tail suspension tests but not in an open field, elevated plus maze, and forced swim tests at baseline. We next performed spared nerve injury in WT and Tmem97 KO mice to assess the role of Tmem97 in neuropathic pain-induced anxiety and depression. WT mice, but not Tmem97 KO mice, developed a prolonged neuropathic pain-induced depressive-like phenotype when tested 10 weeks after nerve injury in females. Our results show that Tmem97 plays a role in modulating anxiety-like and depressive-like behaviors in naive animals with a significant change in the presence of nerve injury in female mice. Overall, these data demonstrate that Tmem97 could be a target to alleviate affective comorbidities of pain disorders.

AlphaFold2 structures guide prospective ligand discovery

AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ2 and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules and comparing results with those obtained from docking against the experimental structures. Hit rates were high and similar for the experimental and AF2 structures, as were affinities. Success in docking against the AF2 models was achieved despite differences between orthosteric residue conformations in the AF2 models and the experimental structures. Determination of the cryo-electron microscopy structure for one of the more potent 5-HT2A ligands from the AF2 docking revealed residue accommodations that resembled the AF2 prediction. AF2 models may sample conformations that differ from experimental structures but remain low energy and relevant for ligand discovery, extending the domain of structure-based drug design.

Structure-based virtual screening of vast chemical space as a starting point for drug discovery

Structure-based virtual screening aims to find molecules forming favorable interactions with a biological macromolecule using computational models of complexes. The recent surge of commercially available chemical space provides the opportunity to search for ligands of therapeutic targets among billions of compounds. This review offers a compact overview of structure-based virtual screens of vast chemical spaces, highlighting successful applications in early drug discovery for therapeutically important targets such as G protein-coupled receptors and viral enzymes. Emphasis is placed on strategies to explore ultra-large chemical libraries and synergies with emerging machine learning techniques. The current opportunities and future challenges of virtual screening are discussed, indicating that this approach will play an important role in the next-generation drug discovery pipeline.

Design, Synthesis, and Cytotoxic Assessment of New Haloperidol Analogues as Potential Anticancer Compounds Targeting Sigma Receptors

Sigma receptors (SRs), including SR1 and SR2 subtypes, have attracted increasing interest in recent years due to their involvement in a wide range of activities, including the modulation of opioid analgesia, neuroprotection, and potential anticancer activity. In this context, haloperidol (HAL), a commonly used antipsychotic drug, also possesses SR activity and cytotoxic effects. Herein, we describe the identification of novel SR ligands, obtained by a chemical hybridization approach. There wereendowed with pan-affinity for both SR subtypes and evaluated their potential anticancer activity against SH-SY5Y and HUH-7 cancer cell lines. Through a chemical hybridization approach, we identified novel compounds (4d, 4e, 4g, and 4j) with dual affinity for SR1 and SR2 receptors. These compounds were subjected to cytotoxicity testing using a resazurin assay. The results revealed potent cytotoxic effects against both cancer cell lines, with IC50 values comparable to HAL. Interestingly, the cytotoxic potency of the novel compounds resembled that of the SR1 antagonist HAL rather than the SR2 agonist siramesine (SRM), indicating the potential role of SR1 antagonism in their mechanism of action. The further exploration of their structure-activity relationships and their evaluation in additional cancer cell lines will elucidate their therapeutic potential and may pave the way for the development of novel anticancer agents that target SRs.

Sigma Receptor Ligands Are Potent Antiprion Compounds that Act Independently of Sigma Receptor Binding

Prion diseases are invariably fatal neurodegenerative diseases of humans and other animals for which there are no effective treatment options. Previous work from our laboratory identified phenethylpiperidines as a novel class of anti-prion compounds. While working to identify the molecular target(s) of these molecules, we unexpectedly discovered ten novel antiprion compounds based on their known ability to bind to the sigma receptors, σ1R and σ2R, which are currently being tested as therapeutic or diagnostic targets for cancer and neuropsychiatric disorders. Surprisingly, however, knockout of the respective genes encoding σ1R and σ2R (Sigmar1 and Tmem97) in prion-infected N2a cells did not alter the antiprion activity of these compounds, demonstrating that these receptors are not the direct targets responsible for the antiprion effects of their ligands. Further investigation of the most potent molecules established that they are efficacious against multiple prion strains and protect against downstream prion-mediated synaptotoxicity. While the precise details of the mechanism of action of these molecules remain to be determined, the present work forms the basis for further investigation of these compounds in preclinical studies. Given the therapeutic utility of several of the tested compounds, including rimcazole and haloperidol for neuropsychiatric conditions, (+)-pentazocine for neuropathic pain, and the ongoing clinical trials of SA 4503 and ANAVEX2-73 for ischemic stroke and Alzheimer's disease, respectively, this work has immediate implications for the treatment of human prion disease.

New perspective of small-molecule antiviral drugs development for RNA viruses

High variability and adaptability of RNA viruses allows them to spread between humans and animals, causing large-scale infectious diseases which seriously threat human and animal health and social development. At present, AIDS, viral hepatitis and other viral diseases with high incidence and low cure rate are still spreading around the world. The outbreaks of Ebola, Zika, dengue and in particular of the global pandemic of COVID-19 have presented serious challenges to the global public health system. The development of highly effective and broad-spectrum antiviral drugs is a substantial and urgent research subject to deal with the current RNA virus infection and the possible new viral infections in the future. In recent years, with the rapid development of modern disciplines such as artificial intelligence technology, bioinformatics, molecular biology, and structural biology, some new strategies and targets for antivirals development have emerged. Here we review the main strategies and new targets for developing small-molecule antiviral drugs against RNA viruses through the analysis of the new drug development progress against several highly pathogenic RNA viruses, to provide clues for development of future antivirals.

The Science and Art of Structure-Based Virtual Screening

Structure-based virtual screening has gained momentum again as the high attrition rate at every stage of drug discovery drives the need to explore a greater chemical space. From the Bayesian perspective, its shortcomings as a viable strategy for sustainable hit discovery are discussed, with regard to the prior hit rates of screening libraries and the performance of computational methods. Lessons are shared in selecting virtual hits for experimental validation learned from a series of eight successful campaigns, one of which impacted the discovery of a drug candidate currently in clinical trials.

Regression-Based Active Learning for Accessible Acceleration of Ultra-Large Library Docking

Structure-based drug discovery is a process for both hit finding and optimization that relies on a validated three-dimensional model of a target biomolecule, used to rationalize the structure-function relationship for this particular target. An ultralarge virtual screening approach has emerged recently for rapid discovery of high-affinity hit compounds, but it requires substantial computational resources. This study shows that active learning with simple linear regression models can accelerate virtual screening, retrieving up to 90% of the top-1% of the docking hit list after docking just 10% of the ligands. The results demonstrate that it is unnecessary to use complex models, such as deep learning approaches, to predict the imprecise results of ligand docking with a low sampling depth. Furthermore, we explore active learning meta-parameters and find that constant batch size models with a simple ensembling method provide the best ligand retrieval rate. Finally, our approach is validated on the ultralarge size virtual screening data set, retrieving 70% of the top-0.05% of ligands after screening only 2% of the library. Altogether, this work provides a computationally accessible approach for accelerated virtual screening that can serve as a blueprint for the future design of low-compute agents for exploration of the chemical space via large-scale accelerated docking. With recent breakthroughs in protein structure prediction, this method can significantly increase accessibility for the academic community and aid in the rapid discovery of high-affinity hit compounds for various targets.

Discovery of novel and selective farnesoid X receptor antagonists through structure-based virtual screening, preliminary structure-activity relationship study, and biological evaluation

Farnesoid X receptor (FXR) is a bile acids receptor and plays a crucial role in regulating bile acids, lipids, and glucose metabolism. Previous research suggests that inhibiting FXR activation can be beneficial in reducing cholesterol and low-density lipoprotein cholesterol (LDL-C) levels, offering potential treatment options for metabolic syndrome with lipid disorders. Herein, we report p-acetylaminobenzene sulfonate derivatives as a novel scaffold of FXR antagonists by multistage screening. Among these derivatives, compound F44-A13 exhibited a half-maximal inhibitory concentration of 1.1 μM. Furthermore, compound F44-A13 demonstrated effective inhibition of FXR activation in cellular assays and exhibited high selectivity over eleven other nuclear receptors. Besides, compound F44-A13 significantly suppressed the regulation of FXR target genes Shp, Besp, and Cyp7a1, while reducing cholesterol levels in human hepatoma HepG2 cells. Pharmacological studies conducted on C57BL/6 mice further confirmed that compound F44-A13 had beneficial effects in reducing cholesterol, triglycerides, and LDL-C levels. These findings highlight that F44-A13 is a highly selective FXR antagonist that might serve as a useful molecule for further FXR studies as well as the development of FXR antagonists for the potential treatment of metabolic diseases with lipid disorders.

Transmembrane protein TMEM97 and epigenetic reader BAHCC1 constitute an axis that supports pro-inflammatory cytokine expression

Pro-inflammatory cytokine production by the retinal pigment epithelium (RPE) is a key etiology in retinal degenerative diseases, yet the underlying mechanisms are not well understood. TMEM97 is a scarcely studied transmembrane protein recently implicated in retinal degeneration. BAH domain coiled coil 1 (BAHCC1) is a newly discovered histone code reader involved in oncogenesis. A role for TMEM97 and BAHCC1 in RPE inflammation was not known. Here we found that they constitute a novel axis regulating pro-inflammatory cytokine expression in RPE cells. Transcriptomic analysis using a TMEM97-/- ARPE19 human cell line and the validation via TMEM97 loss- and gain-of-function revealed a profound role of TMEM97 in promoting the expression of pro-inflammatory cytokines, notably IL1β and CCL2, and unexpectedly BAHCC1 as well. Moreover, co-immunoprecipitation indicated an association between the TMEM97 and BAHCC1 proteins. While TMEM97 ablation decreased and its overexpression increased NFκB (p50, p52, p65), the master transcription factor for pro-inflammatory cytokines, silencing BAHCC1 down-regulated NFκB and downstream pro-inflammatory cytokines. Furthermore, in an RPE-damage retinal degeneration mouse model, immunofluorescence illustrated down-regulation of IL1β and CCL2 total proteins and suppression of glial activation in the retina of Tmem97-/- mice compared to Tmem97+/+ mice. Thus, TMEM97 is a novel determinant of pro-inflammatory cytokine expression acting via a previously unknown TMEM97- > BAHCC1- > NFκB cascade. SYNOPSIS: Retinal pigment epithelium (RPE) inflammation can lead to blindness. We identify here a previously uncharacterized cascade that underlies RPE cell production of pro-inflammatory cytokines. Specifically, transmembrane protein TMEM97 positively regulates the recently discovered histone code reader BAHCC1, which in turn enhances pro-inflammatory cytokine expression via the transcription factor NFκB.

Structure-Affinity relationships of novel σ2R/TMEM97 ligands

The sigma 2 receptor (σ2R), which was recently identified as the transmembrane protein 97 (TMEM97), is increasingly attracting interest as a possible therapeutic target for indications in neuroscience. Toward identifying novel modulators of σ2R/TMEM97, we prepared a collection of benzoxazocine, benzomorphan, and methanobenzazepine ligands related to the known bioactive norbenzomorphans DKR-1677, FEM-1689, and EES-1686 and determined their Ki values for σ2R/TMEM97 and the sigma 1 receptor (σ1R). The σ2R/TMEM97 binding affinities and selectivities relative to σ1R of these new benzoxazocine, benzomorphan, and methanobenzazepine analogs are lower, often significantly lower, than their respective norbenzomorphan counterparts, suggesting the spatial orientation of pharmacophoric substituents is critical for binding to the two proteins. The benzoxazocine, benzomorphan, and methanobenzazepine congeners of DKR-1677 and FEM-1689 tend to be weakly selective for σ2R/TMEM97 versus σ1R, whereas EES-1686 derivatives exhibit the greatest selectivity, suggesting the size and/or nature of the substituent on the nitrogen atom of the scaffold may be important for selectivity. Computational docking studies were performed for the 1S,5R-and 1R,5S-enantiomers of DKR-1677, FEM-1689, and EES-1686 and their benzoxazocine, benzomorphan, and methanobenzazepine counterparts. These computations predict that the protonated amino group of each ligand forms a highly conserved salt bridge and a H-bonding interaction with Asp29 as well as a cation-π interaction with Tyr150 of σ2R/TMEM97. These electrostatic interactions are major driving forces for binding to σ2R/TMEM97 and are similar, though not identical, for each ligand. Other interactions within the well-defined binding pocket also tend to be comparable, but there are some major differences in how the hydrophobic aryl groups of various ligands interact with the protein surface external to the binding pocket. Overall, these studies show that the orientations of aryl and N-substituents on the norbenzomorphan and related scaffolds are important determinants of binding affinity of σ2R/TMEM97 ligands, and small changes can have significant effects upon binding profiles.

Protein Structure-Based Organic Chemistry-Driven Ligand Design from Ultralarge Chemical Spaces

Ultralarge chemical spaces describing several billion compounds are revolutionizing hit identification in early drug discovery. Because of their size, such chemical spaces cannot be fully enumerated and require ad-hoc computational tools to navigate them and pick potentially interesting hits. We here propose a structure-based approach to ultralarge chemical space screening in which commercial chemical reagents are first docked to the target of interest and then directly connected according to organic chemistry and topological rules, to enumerate drug-like compounds under three-dimensional constraints of the target. When applied to bespoke chemical spaces of different sizes and chemical complexity targeting two receptors of pharmaceutical interest (estrogen β receptor, dopamine D3 receptor), the computational method was able to quickly enumerate hits that were either known ligands (or very close analogs) of targeted receptors as well as chemically novel candidates that could be experimentally confirmed by in vitro binding assays. The proposed approach is generic, can be applied to any docking algorithm, and requires few computational resources to prioritize easily synthesizable hits from billion-sized chemical spaces.

AlphaFold2 structures template ligand discovery

AlphaFold2 (AF2) and RosettaFold have greatly expanded the number of structures available for structure-based ligand discovery, even though retrospective studies have cast doubt on their direct usefulness for that goal. Here, we tested unrefined AF2 models prospectively, comparing experimental hit-rates and affinities from large library docking against AF2 models vs the same screens targeting experimental structures of the same receptors. In retrospective docking screens against the σ2 and the 5-HT2A receptors, the AF2 structures struggled to recapitulate ligands that we had previously found docking against the receptors' experimental structures, consistent with published results. Prospective large library docking against the AF2 models, however, yielded similar hit rates for both receptors versus docking against experimentally-derived structures; hundreds of molecules were prioritized and tested against each model and each structure of each receptor. The success of the AF2 models was achieved despite differences in orthosteric pocket residue conformations for both targets versus the experimental structures. Intriguingly, against the 5-HT2A receptor the most potent, subtype-selective agonists were discovered via docking against the AF2 model, not the experimental structure. To understand this from a molecular perspective, a cryoEM structure was determined for one of the more potent and selective ligands to emerge from docking against the AF2 model of the 5-HT2A receptor. Our findings suggest that AF2 models may sample conformations that are relevant for ligand discovery, much extending the domain of applicability of structure-based ligand discovery.

Structure-based discovery of CFTR potentiators and inhibitors

The cystic fibrosis transmembrane conductance regulator (CFTR) is a crucial ion channel whose loss of function leads to cystic fibrosis, while its hyperactivation leads to secretory diarrhea. Small molecules that improve CFTR folding (correctors) or function (potentiators) are clinically available. However, the only potentiator, ivacaftor, has suboptimal pharmacokinetics and inhibitors have yet to be clinically developed. Here we combine molecular docking, electrophysiology, cryo-EM, and medicinal chemistry to identify novel CFTR modulators. We docked ~155 million molecules into the potentiator site on CFTR, synthesized 53 test ligands, and used structure-based optimization to identify candidate modulators. This approach uncovered novel mid-nanomolar potentiators as well as inhibitors that bind to the same allosteric site. These molecules represent potential leads for the development of more effective drugs for cystic fibrosis and secretory diarrhea, demonstrating the feasibility of large-scale docking for ion channel drug discovery.

Small vs. Large Library Docking for Positive Allosteric Modulators of the Calcium Sensing Receptor

Drugs acting as positive allosteric modulators (PAMs) to enhance the activation of the calcium sensing receptor (CaSR) and to suppress parathyroid hormone (PTH) secretion can treat hyperparathyroidism but suffer from side effects including hypocalcemia and arrhythmias. Seeking new CaSR modulators, we docked libraries of 2.7 million and 1.2 billion molecules against transforming pockets in the active-state receptor dimer structure. Consistent with simulations suggesting that docking improves with library size, billion-molecule docking found new PAMs with a hit rate that was 2.7-fold higher than the million-molecule library and with hits up to 37-fold more potent. Structure-based optimization of ligands from both campaigns led to nanomolar leads, one of which was advanced to animal testing. This PAM displays 100-fold the potency of the standard of care, cinacalcet, in ex vivo organ assays, and reduces serum PTH levels in mice by up to 80% without the hypocalcemia typical of CaSR drugs. Cryo-EM structures with the new PAMs show that they induce residue rearrangements in the binding pockets and promote CaSR dimer conformations that are closer to the G-protein coupled state compared to established drugs. These findings highlight the promise of large library docking for therapeutic leads, especially when combined with experimental structure determination and mechanism.

Illuminating the understudied GPCR-ome

G-protein-coupled receptors (GPCRs) are the target of >30% of approved drugs. Despite their popularity, many of the >800 human GPCRs remain understudied. The Illuminating the Druggable Genome (IDG) project has generated many tools leading to important insights into the function and druggability of these so-called 'dark' receptors. These tools include assays, such as PRESTO-TANGO and TRUPATH, billions of small molecules made available via the ZINC virtual library, solved orphan GPCR structures, GPCR knock-in mice, and more. Together, these tools are illuminating the remaining 'dark' GPCRs.

Large library docking for cannabinoid-1 receptor agonists with reduced side effects

Large library docking can reveal unexpected chemotypes that complement the structures of biological targets. Seeking new agonists for the cannabinoid-1 receptor (CB1R), we docked 74 million tangible molecules, prioritizing 46 high ranking ones for de novo synthesis and testing. Nine were active by radioligand competition, a 20% hit-rate. Structure-based optimization of one of the most potent of these (Ki = 0.7 uM) led to '4042, a 1.9 nM ligand and a full CB1R agonist. A cryo-EM structure of the purified enantiomer of '4042 ('1350) in complex with CB1R-Gi1 confirmed its docked pose. The new agonist was strongly analgesic, with generally a 5-10-fold therapeutic window over sedation and catalepsy and no observable conditioned place preference. These findings suggest that new cannabinoid chemotypes may disentangle characteristic cannabinoid side-effects from their analgesia, supporting the further development of cannabinoids as pain therapeutics.

Exploring Novel Antidepressants Targeting G Protein-Coupled Receptors and Key Membrane Receptors Based on Molecular Structures

Major Depressive Disorder (MDD) is a complex mental disorder that involves alterations in signal transmission across multiple scales and structural abnormalities. The development of effective antidepressants (ADs) has been hindered by the dominance of monoamine hypothesis, resulting in slow progress. Traditional ADs have undesirable traits like delayed onset of action, limited efficacy, and severe side effects. Recently, two categories of fast-acting antidepressant compounds have surfaced, dissociative anesthetics S-ketamine and its metabolites, as well as psychedelics such as lysergic acid diethylamide (LSD). This has led to structural research and drug development of the receptors that they target. This review provides breakthroughs and achievements in the structure of depression-related receptors and novel ADs based on these. Cryo-electron microscopy (cryo-EM) has enabled researchers to identify the structures of membrane receptors, including the N-methyl-D-aspartate receptor (NMDAR) and the 5-hydroxytryptamine 2A (5-HT2A) receptor. These high-resolution structures can be used for the development of novel ADs using virtual drug screening (VDS). Moreover, the unique antidepressant effects of 5-HT1A receptors in various brain regions, and the pivotal roles of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and tyrosine kinase receptor 2 (TrkB) in regulating synaptic plasticity, emphasize their potential as therapeutic targets. Using structural information, a series of highly selective ADs were designed based on the different role of receptors in MDD. These molecules have the favorable characteristics of rapid onset and low adverse drug reactions. This review offers researchers guidance and a methodological framework for the structure-based design of ADs.

Advances in structure-based drug design: The potential for precision therapeutics in psychiatric disorders

Over the years, the field of GPCR drug design has undergone a remarkable evolution, fueled by advancements in science and technology. This evolution has given rise to a diverse range of ideas and approaches in structure-based drug design, bolstering the versatility and strength of the GPCR drug design toolbox. This review encapsulates the iterative development process, navigating challenges and opportunities in structure-based drug design within GPCRs. With a focused emphasis on its impact on psychiatric disorders, the review accentuates recent advancements and delves into the potentials unlocked by emerging technologies. The review explores the intricate interplay between scientific progress and iterative refinement, offering profound insights into the potential pathways that lie ahead for GPCR drug design.

DockOpt: A Tool for Automatic Optimization of Docking Models

Molecular docking is a widely used technique for leveraging protein structure for ligand discovery, but it remains difficult to utilize due to limitations that have not been adequately addressed. Despite some progress toward automation, docking still requires expert guidance, hindering its adoption by a broader range of investigators. To make docking more accessible, we developed a new utility called DockOpt, which automates the creation, evaluation, and optimization of docking models prior to their deployment in large-scale prospective screens. DockOpt outperforms our previous automated pipeline across all 43 targets in the DUDE-Z benchmark data set, and the generated models for 84% of targets demonstrate sufficient enrichment to warrant their use in prospective screens, with normalized LogAUC values of at least 15%. DockOpt is available as part of the Python package Pydock3 included in the UCSF DOCK 3.8 distribution, which is available for free to academic researchers at https://dock.compbio.ucsf.edu and free for everyone upon registration at https://tldr.docking.org.

Exploring the combinatorial explosion of amine-acid reaction space via graph editing

Amines and carboxylic acids are abundant chemical feedstocks that are nearly exclusively united via the amide coupling reaction. The disproportionate use of the amide coupling leaves a large section of unexplored reaction space between amines and acids: two of the most common chemical building blocks. Herein we conduct a thorough exploration of amine-acid reaction space via systematic enumeration of reactions involving a simple amine-carboxylic acid pair. This approach to chemical space exploration investigates the coarse and fine modulation of physicochemical properties and molecular shapes. With the invention of reaction methods becoming increasingly automated and bringing conceptual reactions into reality, our map provides an entirely new axis of chemical space exploration for rational property design.

DOCK 6: Incorporating hierarchical traversal through precomputed ligand conformations to enable large-scale docking

To allow DOCK 6 access to unprecedented chemical space for screening billions of small molecules, we have implemented features from DOCK 3.7 into DOCK 6, including a search routine that traverses precomputed ligand conformations stored in a hierarchical database. We tested them on the DUDE-Z and SB2012 test sets. The hierarchical database search routine is 16 times faster than anchor-and-grow. However, the ability of hierarchical database search to reproduce the experimental pose is 16% worse than that of anchor-and-grow. The enrichment performance is on average similar, but DOCK 3.7 has better enrichment than DOCK 6, and DOCK 6 is on average 1.7 times slower. However, with post-docking torsion minimization, DOCK 6 surpasses DOCK 3.7. A large-scale virtual screen is performed with DOCK 6 on 23 million fragment molecules. We use current features in DOCK 6 to complement hierarchical database calculations, including torsion minimization, which is not available in DOCK 3.7.

Design, development and bio-evaluation of a novel radio-ligand 99mTc-THQ-DTPA as a sigma 2 receptor specific breast tumor imaging agent

Over-expression of sigma-2 receptor in cancer cells provides an opportunity to develop molecular probes for diagnosis, even for non-receptor specific malignancies like triple negative breast cancers. In this work, a novel sigma-2 receptor ligand [THQ-DTPA] has been synthesized and characterized using 6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline (THQ) and diethylenetriaminepentaacetic acid (DTPA). The ligand is further chelated with 99mTc for application as metal based radiotracer [99mTc-THQ-DTPA]. Radiolabelling with 99mTc was achieved in an excellent yield of 98.0 ± 0.5% using stannous chloride as a reducing agent. The radioligand was found to be stable in human serum up-to 24 h, bio-compatible with less than 4% hemolysis, and exhibited high binding with sigma receptors isolated from rat liver membrane (Kd of 16.32 ± 4.93 nM and Bmax of 0.5232 ± 0.06 pmol/mg). Bio-distribution studies in triple-negative breast tumor bearing nude mice showed high tumor uptake after 30 min of injection with tumor/muscle (T/M) ratio of 3.58 ± 0.09. At 240 min, the T/M ratio (2.84 ± 0.20) decreased by 35% when administered in sigma blocked tumor bearing mice (1.81 ± 0.16) suggesting the selectivity of the ligand. Tumor imaging in gamma camera indicated a contrast of 3.56 at 30 min p.i. The above findings indicate that the ligand 99mTc-THQ-DTPA binds to sigma-2 receptors with high affinity and has potential for triple-negative breast tumor imaging.

Discovery of 3-oxo-1,2,3,4-tetrahydropyrido[1,2-a]pyrazin derivatives as SARS-CoV-2 main protease inhibitors through virtual screening and biological evaluation

The COVID-19 caused by SARS-CoV-2 has led to a global pandemic that continues to impact societies and economies worldwide. The main protease (Mpro) plays a crucial role in SARS-CoV-2 replication and is an attractive target for anti-SARS-CoV-2 drug discovery. Herein, we report a series of 3-oxo-1,2,3,4-tetrahydropyrido[1,2-a]pyrazin derivatives as non-peptidomimetic inhibitors targeting SARS-CoV-2 Mpro through structure-based virtual screening and biological evaluation. Further similarity search and structure-activity relationship study led to the identification of compound M56-S2 with the enzymatic IC50 value of 4.0 μM. Moreover, the molecular simulation and predicted ADMET properties, indicated that non-peptidomimetic inhibitor M56-S2 might serve as a useful starting point for the further discovery of highly potent inhibitors targeting SARS-CoV-2 Mpro.

HIt Discovery using docking ENriched by GEnerative Modeling (HIDDEN GEM): A novel computational workflow for accelerated virtual screening of ultra-large chemical libraries

Recent rapid expansion of make-on-demand, purchasable, chemical libraries comprising dozens of billions or even trillions of molecules has challenged the efficient application of traditional structure-based virtual screening methods that rely on molecular docking. We present a novel computational methodology termed HIDDEN GEM (HIt Discovery using Docking ENriched by GEnerative Modeling) that greatly accelerates virtual screening. This workflow uniquely integrates machine learning, generative chemistry, massive chemical similarity searching and molecular docking of small, selected libraries in the beginning and the end of the workflow. For each target, HIDDEN GEM nominates a small number of top-scoring virtual hits prioritized from ultra-large chemical libraries. We have benchmarked HIDDEN GEM by conducting virtual screening campaigns for 16 diverse protein targets using Enamine REAL Space library comprising 37 billion molecules. We show that HIDDEN GEM yields the highest enrichment factors as compared to state of the art accelerated virtual screening methods, while requiring the least computational resources. HIDDEN GEM can be executed with any docking software and employed by users with limited computational resources.

The molecular mechanism of the effects of the anti-neuropathic ligands on the modulation of the Sigma-2 receptor: An in-silico study

Neuropathic pain (NP) is a prevalent medical condition that lacks an effective treatment. Recently, the Sigma-2 receptor (S2R) has been proposed as a potential therapeutic target for NP. Some highly-selective S2R ligands (UKH1114, CM398, and YTD) have shown promising results in vivo, but the molecular interaction between the S2R and these ligands has been scarcely investigated. This work explores changes in the S2R upon interaction with the three mentioned ligands using in silico approaches. The results indicated that the ICL1, H1, ICL2, and ECL are the most dynamic regions of S2R in all systems. Binding interaction analysis identified amino acids with significant contribution to the binding free energy. Notably, the UKH1114-S2R simulation trajectory revealed that small alterations in the ICL1, H1, ICL2, and ECL form a new stable opening in the S2R, linking the occluded S2R binding pocket to the endoplasmic reticulum lumen, providing more evidence for the assumptions about the EBP and S2R mechanism of function. Further, the agreement between the membrane parameters in our study and experimental values confirms the validity of the MD simulations. Overall, this study provides new insights into the interaction between anti-NP ligands and the S2R.

Highly specific σ2R/TMEM97 ligand FEM-1689 alleviates neuropathic pain and inhibits the integrated stress response

The sigma 2 receptor (σ2R) was described pharmacologically more than three decades ago, but its molecular identity remained obscure until recently when it was identified as transmembrane protein 97 (TMEM97). We and others have shown that σ2R/TMEM97 ligands alleviate mechanical hypersensitivity in mouse neuropathic pain models with a time course wherein maximal antinociceptive effect is approximately 24 h following dosing. We sought to understand this unique antineuropathic pain effect by addressing two key questions: do these σ2R/TMEM97 compounds act selectively via the receptor, and what is their downstream mechanism on nociceptive neurons? Using male and female conventional knockout mice for Tmem97, we find that a σ2R/TMEM97 binding compound, FEM-1689, requires the presence of the gene to produce antinociception in the spared nerve injury model in mice. Using primary mouse dorsal root ganglion neurons, we demonstrate that FEM-1689 inhibits the integrated stress response (ISR) and promotes neurite outgrowth via a σ2R/TMEM97-specific action. We extend the clinical translational value of these findings by showing that FEM-1689 reduces ISR and p-eIF2α levels in human sensory neurons and that it alleviates the pathogenic engagement of ISR by methylglyoxal. We also demonstrate that σ2R/TMEM97 is expressed in human nociceptors and satellite glial cells. These results validate σ2R/TMEM97 as a promising target for further development for the treatment of neuropathic pain.

Docking for EP4R antagonists active against inflammatory pain

The lipid prostaglandin E2 (PGE2) mediates inflammatory pain by activating G protein-coupled receptors, including the prostaglandin E2 receptor 4 (EP4R). Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce nociception by inhibiting prostaglandin synthesis, however, the disruption of upstream prostanoid biosynthesis can lead to pleiotropic effects including gastrointestinal bleeding and cardiac complications. In contrast, by acting downstream, EP4R antagonists may act specifically as anti-inflammatory agents and, to date, no selective EP4R antagonists have been approved for human use. In this work, seeking to diversify EP4R antagonist scaffolds, we computationally dock over 400 million compounds against an EP4R crystal structure and experimentally validate 71 highly ranked, de novo synthesized molecules. Further, we show how structure-based optimization of initial docking hits identifies a potent and selective antagonist with 16 nanomolar potency. Finally, we demonstrate favorable pharmacokinetics for the discovered compound as well as anti-allodynic and anti-inflammatory activity in several preclinical pain models in mice.

Structure-based discovery of novel P-glycoprotein inhibitors targeting the nucleotide binding domains

P-glycoprotein (P-gp), a membrane transport protein overexpressed in certain drug-resistant cancer cells, has been the target of numerous drug discovery projects aimed at overcoming drug resistance in cancer. Most characterized P-gp inhibitors bind at the large hydrophobic drug binding domain (DBD), but none have yet attained regulatory approval. In this study, we explored the potential of designing inhibitors that target the nucleotide binding domains (NBDs), by computationally screening a large library of 2.6 billion synthesizable molecules, using a combination of machine learning-guided molecular docking and molecular dynamics (MD). 14 of the computationally best-scoring molecules were subsequently tested for their ability to inhibit P-gp mediated calcein-AM efflux. In total, five diverse compounds exhibited inhibitory effects in the calcein-AM assay without displaying toxicity. The activity of these compounds was confirmed by their ability to decrease the verapamil-stimulated ATPase activity of P-gp in a subsequent assay. The discovery of these five novel P-gp inhibitors demonstrates the potential of in-silico screening in drug discovery and provides a new stepping point towards future potent P-gp inhibitors.

Recent advances in drug discovery efforts targeting the sigma 1 receptor system: Implications for novel medications designed to reduce excessive drug and food seeking

Psychiatric disorders characterized by uncontrolled reward seeking, such as substance use disorders (SUDs), alcohol use disorder (AUD) and some eating disorders, impose a significant burden on individuals and society. Despite their high prevalence and substantial morbidity and mortality rates, treatment options for these disorders remain limited. Over the past two decades, there has been a gradual accumulation of evidence pointing to the sigma-1 receptor (S1R) system as a promising target for therapeutic interventions designed to treat these disorders. S1R is a chaperone protein that resides in the endoplasmic reticulum, but under certain conditions translocates to the plasma membrane. In the brain, S1Rs are expressed in several regions important for reward, and following translocation, they physically associate with several reward-related GPCRs, including dopamine receptors 1 and 2 (D1R and D2R). Psychostimulants, alcohol, as well as palatable foods, all alter expression of S1R in regions important for motivated behavior, and S1R antagonists generally decrease behavioral responses to these rewards. Recent advances in structural modeling have permitted the development of highly-selective S1R antagonists with favorable pharmacokinetic profiles, thus providing a therapeutic avenue for S1R-based medications. Here, we provide an up-to-date overview of work linking S1R with motivated behavior for drugs of abuse and food, as well as evidence supporting the clinical utility of S1R antagonists to reduce their excessive consumption. We also highlight potential challenges associated with targeting the S1R system, including the need for a more comprehensive understanding of the underlying neurobiology and careful consideration of the pharmacological properties of S1R-based drugs.

Sigma receptor ligands are potent anti-prion compounds that act independently of sigma receptor binding

Prion diseases are invariably fatal neurodegenerative diseases of humans and other animals for which there are no treatment options. Previous work from our laboratory identified phenethyl piperidines as novel class of anti-prion compounds. While working to identify the molecular target(s) of these molecules, we unexpectedly discovered ten novel anti-prion compounds based on their known ability to bind to the sigma receptors, σ 1 R and 2 R, which are currently being tested as therapeutic or diagnostic targets for cancer and neuropsychiatric disorders. Surprisingly, however, knockout of the respective genes encoding σ 1 R and σ 2 R ( Sigmar1 and Tmem97 ), in prion infected N2a cells did not alter the anti-prion activity of these compounds, demonstrating that these receptors are not the direct targets responsible the anti-prion effects of their ligands. Further investigation of the most potent molecules established that they are efficacious against multiple prion strains and protect against downstream prion-mediated synaptotoxicity. While the precise details of the mechanism of action of these molecules remains to be determined, the present work forms the basis for further investigations of these compounds in pre-clinical studies. Given the therapeutic utility of several of the tested compounds, including rimcazole and haloperidol for neuropsychiatric conditions, (+)-pentazocine for neuropathic pain, and the ongoing clinical trials of SA 4503 and ANAVEX2-73 for ischemic stroke and Alzheimer's disease, respectively, this work has immediate implications for the treatment of human prion disease.

Discovery of first novel sigma/HDACi dual-ligands with a potent in vitro antiproliferative activity

Designing and discovering compounds for dual-target inhibitors is challenging to synthesize new, safer, and more efficient drugs than single-target drugs, especially to treat multifactorial diseases such as cancer. The simultaneous regulation of multiple targets might represent an alternative synthetic approach to optimize patient compliance and tolerance, minimizing the risk of target-based drug resistance due to the modulation of a few targets. To this end, we conceived for the first time the design and synthesis of dual-ligands σR/HDACi to evaluate possible employment as innovative candidates to address this complex disease. Among all synthesized compounds screened for several tumoral cell lines, compound 6 (Kiσ1R = 38 ± 3.7; Kiσ2R = 2917 ± 769 and HDACs IC50 = 0.59 µM) is the most promising candidate as an antiproliferative agent with an IC50 of 0.9 µM on the HCT116 cell line and no significant toxicity to normal cells. Studies of molecular docking, which confirmed the affinity over σ1R and a pan-HDACs inhibitory behavior, support a possible balanced affinity and activity between both targets.

Highly specific σ2R/TMEM97 ligand alleviates neuropathic pain and inhibits the integrated stress response

The Sigma 2 receptor (σ2R) was described pharmacologically more than three decades ago, but its molecular identity remained obscure until recently when it was identified as transmembrane protein 97 (TMEM97). We and others have shown that σ2R/TMEM97 ligands alleviate mechanical hypersensitivity in mouse neuropathic pain models with a time course wherein maximal anti-nociceptive effect is approximately 24 hours following dosing. We sought to understand this unique anti-neuropathic pain effect by addressing two key questions: do these σ2R/TMEM97 compounds act selectively via the receptor, and what is their downstream mechanism on nociceptive neurons? Using male and female conventional knockout (KO) mice for Tmem97, we find that a new σ2R/TMEM97 binding compound, FEM-1689, requires the presence of the gene to produce anti-nociception in the spared nerve injury model in mice. Using primary mouse dorsal root ganglion (DRG) neurons, we demonstrate that FEM-1689 inhibits the integrated stress response (ISR) and promotes neurite outgrowth via a σ2R/TMEM97-specific action. We extend the clinical translational value of these findings by showing that FEM-1689 reduces ISR and p-eIF2α levels in human sensory neurons and that it alleviates the pathogenic engagement of ISR by methylglyoxal. We also demonstrate that σ2R/TMEM97 is expressed in human nociceptors and satellite glial cells. These results validate σ2R/TMEM97 as a promising target for further development for the treatment of neuropathic pain.

Development of a Highly Specific 18F-Labeled Radioligand for Imaging of the Sigma-2 Receptor in Brain Tumors

Novel ligands with the 6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline or 5,6-dimethoxyisoindoline pharmacophore were designed and synthesized for evaluation of their structure-activity relationship to the sigma-2 (σ2) receptor and developed as suitable PET radioligands. Compound 1 was found to possess nanomolar affinity (Ki(σ1) = 2.57 nM) for the σ2 receptor, high subtype selectivity (>2000-fold), and high selectivity over 40 other receptors and transporters. Radioligand [18F]1 was prepared with radiochemical yield of 37-54%, > 99% radiochemical purity, and molar activity of 107-189 GBq/μmol. Biodistribution and blocking studies in mice and micro-PET/CT imaging of [18F]1 in rats indicated excellent binding specificity to the σ2 receptors in vivo. Micro-PET/CT imaging of [18F]1 in the U87MG glioma xenograft model demonstrated clear tumor visualization with high tumor uptake and tumor-to-background ratio. Co-injection with CM398 (5 μmol/kg) led to a remarkable reduction of tumor uptake (80%, 60-70 min), indicating high specific binding of [18F]1 in U87MG glioma xenografts.

Sigma Receptors: Novel Regulators of Iron/Heme Homeostasis and Ferroptosis

Sigma receptors are non-opiate/non-phencyclidine receptors that bind progesterone and/or heme and also several unrelated xenobiotics/chemicals. They reside in the plasma membrane and in the membranes of the endoplasmic reticulum, mitochondria, and nucleus. Until recently, the biology/pharmacology of these proteins focused primarily on their role in neuronal functions in the brain/retina. However, there have been recent developments in the field with the discovery of unexpected roles for these proteins in iron/heme homeostasis. Sigma receptor 1 (S1R) regulates the oxidative stress-related transcription factor NRF2 and protects against ferroptosis, an iron-induced cell death process. Sigma receptor 2 (S2R), which is structurally unrelated to S1R, complexes with progesterone receptor membrane components PGRMC1 and PGRMC2. S2R, PGRMC1, and PGRMC2, either independently or as protein-protein complexes, elicit a multitude of effects with a profound influence on iron/heme homeostasis. This includes the regulation of the secretion of the iron-regulatory hormone hepcidin, the modulation of the activity of mitochondrial ferrochelatase, which catalyzes iron incorporation into protoporphyrin IX to form heme, chaperoning heme to specific hemoproteins thereby influencing their biological activity and stability, and protection against ferroptosis. Consequently, S1R, S2R, PGRMC1, and PGRMC2 potentiate disease progression in hemochromatosis and cancer. These new discoveries usher this intriguing group of non-traditional progesterone receptors into an unchartered territory in biology and medicine.

Discovery and computational studies of piperidine/piperazine-based compounds endowed with sigma receptor affinity

Herein, we describe our efforts to identify sigma receptor 1 (S1R) ligands through a screening campaign on our in-house collection of piperidine/piperazine-based compounds. Our investigations led to the discovery of the potent compound 2-[4-(benzyl)-1-piperidin-1-yl]-1-4-(4-phenylpiperazin-1-yl)ethanone (1) with high affinity toward S1R (Ki value of 3.2 nM) that was comparable to reference compound haloperidol (Ki value of 2.5 nM). Functional assay revealed that compound 1 acted as S1R agonist. To decipher the binding mode of this promising S1R ligand as a starting point for further structure-based optimization, we analysed the docking pose by using a S1R-structure derived from cocrystal structures of potent ligands in complex with target protein. The computational study was enriched with molecular dynamic simulations that revealed the crucial amino acid residues that interacted with the most interesting compound 1.

Discovery of WLB-89462, a New Drug-like and Highly Selective σ2 Receptor Ligand with Neuroprotective Properties

The synthesis and pharmacological activity of a new series of isoxazolylpyrimidines as sigma-2 receptor (σ2R) ligands are reported. Modification of a new hit retrieved in an HTS campaign allowed the identification of the compound WLB-89462 (20c) with good σ2R affinity (Ki = 13 nM) and high selectivity vs both the σ1R (Ki = 1777 nM) and a general panel of 180 targets. It represents one of the first σ2R ligands with drug-like properties, linked to a good physicochemical and ADMET profile (good solubility, no CYP inhibition, good metabolic stability, high permeability, brain penetration, and high oral exposure in rodents). Compound 20c shows neuroprotective activity in vitro and improves short-term memory impairment induced by hippocampal injection of amyloid β peptide in rats. Together with the promising effects in the chronic models where 20c is currently being evaluated, these results pave the way toward its clinical development as a neuroprotective agent.

Discovery of AD258 as a Sigma Receptor Ligand with Potent Antiallodynic Activity

The design and synthesis of a series of 2,7-diazaspiro[4.4]nonane derivatives as potent sigma receptor (SR) ligands, associated with analgesic activity, are the focus of this work. In this study, affinities at S1R and S2R were measured, and molecular modeling studies were performed to investigate the binding pose characteristics. The most promising compounds were subjected to in vitro toxicity testing and subsequently screened for in vivo analgesic properties. Compound 9d (AD258) exhibited negligible in vitro cellular toxicity and a high binding affinity to both SRs (KiS1R = 3.5 nM, KiS2R = 2.6 nM), but not for other pain-related targets, and exerted high potency in a model of capsaicin-induced allodynia, reaching the maximum antiallodynic effect at very low doses (0.6-1.25 mg/kg). Functional activity experiments showed that S1R antagonism is needed for the effects of 9d and that it did not induce motor impairment. In addition, 9d exhibited a favorable pharmacokinetic profile.

warpDOCK: Large-Scale Virtual Drug Discovery Using Cloud Infrastructure

warpDOCK is an open-source pipeline for virtual small-molecule drug discovery using cloud infrastructure. warpDOCK is designed from the ground up for the Oracle Cloud Infrastructure (OCI), enabling harmonious parallelism of docking calculations over thousands to hundreds of thousands of cores. This enables cost-effective sampling of ultra-large chemical libraries, potentially reducing the time to identify lead drug candidates by orders of magnitude. By utilizing established docking software and automating each step of the process, warpDOCK makes large-scale virtual screening accessible to a broad user group. The warpDOCK code can be found at the BruningLab GitHub repository (https://github.com/BruningLab/warpDOCK).

AI-Powered Virtual Screening of Large Compound Libraries Leads to the Discovery of Novel Inhibitors of Sirtuin-1

The discovery of new scaffolds and chemotypes via high-throughput screening is tedious and resource intensive. Yet, there are millions of small molecules commercially available, rendering comprehensive in vitro tests intractable. We show how smart algorithms reduce large screening collections to target-specific sets of just a few hundred small molecules, allowing for a much faster and more cost-effective hit discovery process. We showcase the application of this virtual screening strategy by preselecting 434 compounds for Sirtuin-1 inhibition from a library of 2.6 million compounds, corresponding to 0.02% of the original library. Multistage in vitro validation ultimately confirmed nine chemically novel inhibitors. When compared to a competitive benchmark study for Sirtuin-1, our method shows a 12-fold higher hit rate. The results demonstrate how AI-driven preselection from large screening libraries allows for a massive reduction in the number of small molecules to be tested in vitro while still retaining a large number of hits.

Recent Developments in Ultralarge and Structure-Based Virtual Screening Approaches

Drug development is a wide scientific field that faces many challenges these days. Among them are extremely high development costs, long development times, and a small number of new drugs that are approved each year. New and innovative technologies are needed to solve these problems that make the drug discovery process of small molecules more time and cost efficient, and that allow previously undruggable receptor classes to be targeted, such as protein-protein interactions. Structure-based virtual screenings (SBVSs) have become a leading contender in this context. In this review, we give an introduction to the foundations of SBVSs and survey their progress in the past few years with a focus on ultralarge virtual screenings (ULVSs). We outline key principles of SBVSs, recent success stories, new screening techniques, available deep learning-based docking methods, and promising future research directions. ULVSs have an enormous potential for the development of new small-molecule drugs and are already starting to transform early-stage drug discovery.

An equivariant generative framework for molecular graph-structure Co-design

Designing molecules with desirable physiochemical properties and functionalities is a long-standing challenge in chemistry, material science, and drug discovery. Recently, machine learning-based generative models have emerged as promising approaches for de novo molecule design. However, further refinement of methodology is highly desired as most existing methods lack unified modeling of 2D topology and 3D geometry information and fail to effectively learn the structure-property relationship for molecule design. Here we present MolCode, a roto-translation equivariant generative framework for molecular graph-structure Co-design. In MolCode, 3D geometric information empowers the molecular 2D graph generation, which in turn helps guide the prediction of molecular 3D structure. Extensive experimental results show that MolCode outperforms previous methods on a series of challenging tasks including de novo molecule design, targeted molecule discovery, and structure-based drug design. Particularly, MolCode not only consistently generates valid (99.95% validity) and diverse (98.75% uniqueness) molecular graphs/structures with desirable properties, but also generates drug-like molecules with high affinity to target proteins (61.8% high affinity ratio), which demonstrates MolCode's potential applications in material design and drug discovery. Our extensive investigation reveals that the 2D topology and 3D geometry contain intrinsically complementary information in molecule design, and provide new insights into machine learning-based molecule representation and generation.

Achieving the promise and avoiding the peril of chemical probes using genetics

Chemical probes can be valuable tools for studying protein targets, but addressing concerns about a probe's cellular target or its specificity can be challenging. A reliable strategy is to use a mutation that does not alter a target's function but confers resistance (or sensitizes) to the inhibitor in both cellular and biochemical assays. However, challenges remain in finding such mutations. Here, we discuss structure- and cell-based approaches to identify resistance- and sensitivity-conferring mutations. Further, we describe how resistance-conferring mutations can help with compound design, and the use of saturation mutagenesis to characterize a compound binding site. We highlight how genetic approaches can ensure the proper use of chemical inhibitors to pursue mechanistic studies and test therapeutic hypotheses.

Large library docking for novel SARS-CoV-2 main protease non-covalent and covalent inhibitors

Antiviral therapeutics to treat SARS-CoV-2 are needed to diminish the morbidity of the ongoing COVID-19 pandemic. A well-precedented drug target is the main viral protease (MPro ), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure-based approach, we docked 1.2 billion non-covalent lead-like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of MPro inhibitors for SARS-CoV-2, the modest success rate also reveals weaknesses in our approach for challenging targets like MPro versus other targets where it has been more successful, and versus other structure-based techniques against MPro itself.

The Sigma Receptors in Alzheimer's Disease: New Potential Targets for Diagnosis and Therapy

Sigma (σ) receptors are a class of unique proteins with two subtypes: the sigma-1 (σ1) receptor which is situated at the mitochondria-associated endoplasmic reticulum (ER) membrane (MAM), and the sigma-2 (σ2) receptor, located in the ER-resident membrane. Increasing evidence indicates the involvement of both σ1 and σ2 receptors in the pathogenesis of Alzheimer's disease (AD), and thus these receptors represent two potentially effective biomarkers for emerging AD therapies. The availability of optimal radioligands for positron emission tomography (PET) neuroimaging of the σ1 and σ2 receptors in humans will provide tools to monitor AD progression and treatment outcomes. In this review, we first summarize the significance of both receptors in the pathophysiology of AD and highlight AD therapeutic strategies related to the σ1 and σ2 receptors. We then survey the potential PET radioligands, with an emphasis on the requirements of optimal radioligands for imaging the σ1 or σ2 receptors in humans. Finally, we discuss current challenges in the development of PET radioligands for the σ1 or σ2 receptors, and the opportunities for neuroimaging to elucidate the σ1 and σ2 receptors as novel biomarkers for early AD diagnosis, and for monitoring of disease progression and AD drug efficacy.

The Emerging Role of Sigma Receptors in Pain Medicine

Sigma receptors are protein chaperones with the unexpected characteristic of being activated by ligand binding. As such, they represent intriguing new targets for potential drug development. As a protein chaperone, these "receptors" escort proteins from the endoplasmic reticulum to their destinations and act to correct misfolded proteins. The two subtypes of sigma receptors, named σ1 and σ2, are markedly distinct from each other. Agonists and antagonists at these receptors show promise as new drug targets, addressing a range of diseases including neurodegenerative disorders, cancer, and cardiac disorders, and may also be analgesic agents and rehabilitation drugs for opioid use disorder. As an analgesic, sigma receptors seem to be more effective in treating neuropathic than nociceptive pain. New bifunctional compounds are being developed with opioids, because agents targeting sigma receptors may have an opioid-sparing effect. The pipeline of agents based on the sigma receptors is long and may treat things from Fragile X syndrome to Parkinson's disease to Huntington's disease to cancer. A novel agent ADV502 acts as a high-affinity σ1 antagonist and partial agonist at the µ-opioid receptor and may be an important agent both for the treatment of neuropathic cancer pain and for rehabilitation of opioid use disorder. Since there has been little recent innovation in pain medicine regarding new compounds and drug targets, drugs that affect the sigma receptor system seem promising and encouraging.

BS148 Reduces the Aggressiveness of Metastatic Melanoma via Sigma-2 Receptor Targeting

The management of advanced-stage melanoma is clinically challenging, mainly because of its resistance to the currently available therapies. Therefore, it is important to develop alternative therapeutic strategies. The sigma-2 receptor (S2R) is overexpressed in proliferating tumor cells and represents a promising vulnerability to target. Indeed, we have recently identified a potent S2R modulator (BS148) that is effective in melanoma. To elucidate its mechanism of action, we designed and synthesized a BS148 fluorescent probe that enters SK-MEL-2 melanoma cells as assessed using confocal microscopy analysis. We show that S2R knockdown significantly reduces the anti-proliferative effect induced by BS148 administration, indicating the engagement of S2R in BS148-mediated cytotoxicity. Interestingly, BS148 treatment showed similar molecular effects to S2R RNA interference-mediated knockdown. We demonstrate that BS148 administration activates the endoplasmic reticulum stress response through the upregulation of protein kinase R-like ER kinase (PERK), activating transcription factor 4 (ATF4) genes, and C/EBP homologous protein (CHOP). Furthermore, we show that BS148 treatment downregulates genes related to the cholesterol pathway and activates the MAPK signaling pathway. Finally, we translate our results into patient-derived xenograft (PDX) cells, proving that BS148 treatment reduces melanoma cell viability and migration. These results demonstrate that BS148 is able to inhibit metastatic melanoma cell proliferation and migration through its interaction with the S2R and confirm its role as a promising target to treat cancer.

Modeling the expansion of virtual screening libraries

Recently, 'tangible' virtual libraries have made billions of molecules readily available. Prioritizing these molecules for synthesis and testing demands computational approaches, such as docking. Their success may depend on library diversity, their similarity to bio-like molecules and how receptor fit and artifacts change with library size. We compared a library of 3 million 'in-stock' molecules with billion-plus tangible libraries. The bias toward bio-like molecules in the tangible library decreases 19,000-fold versus those 'in-stock'. Similarly, thousands of high-ranking molecules, including experimental actives, from five ultra-large-library docking campaigns are also dissimilar to bio-like molecules. Meanwhile, better-fitting molecules are found as the library grows, with the score improving log-linearly with library size. Finally, as library size increases, so too do rare molecules that rank artifactually well. Although the nature of these artifacts changes from target to target, the expectation of their occurrence does not, and simple strategies can minimize their impact.