Pathogenic/likely pathogenic mutations identified in Vietnamese children diagnosed with autism spectrum disorder using high-resolution SNP genotyping platform.

Among the most prevalent neurodevelopmental disorders, Autism Spectrum Disorder (ASD) is highly diverse showing a broad phenotypic spectrum. ASD also couples with a broad range of mutations, both de novo and inherited. In this study, we used a proprietary SNP genotyping chip to analyze the genomic DNA of 250 Vietnamese children diagnosed with ASD. Our Single Nucleotide Polymorphism (SNP) genotyping chip directly targets more than 800 thousand SNPs in the genome. Our primary focus was to identify pathogenic/likely pathogenic mutations that are potentially linked to more severe symptoms of autism. We identified and validated 23 pathogenic/likely pathogenic mutations in this initial study. The data shows that these mutations were detected in several cases spanning multiple biological pathways. Among the confirmed SNPs, mutations were identified in genes previously known to be strongly associated with ASD such as SLCO1B1, ACADSB, TCF4, HCP5, MOCOS, SRD5A2, MCCC2, DCC, and PRKN while several other mutations are known to associate with autistic traits or other neurodevelopmental disorders. Some mutations were found in multiple patients and some patients carried multiple pathogenic/likely pathogenic mutations. These findings contribute to the identification of potential targets for therapeutic solutions in what is considered a genetically heterogeneous neurodevelopmental disorder.

Activation of cyclin-dependent kinase 5 broadens action potentials in human sensory neurons.

Chronic pain is one of the most devastating and unpleasant conditions, associated with many pathological states. Tissue or nerve injuries induce extensive neurobiological plasticity in nociceptive neurons, which leads to chronic pain. Recent studies suggest that cyclin-dependent kinase 5 (CDK5) in primary afferents is a key neuronal kinase that modulates nociception through phosphorylation under pathological conditions. However, the impact of the CDK5 on nociceptor activity especially in human sensory neurons is not known. To determine the CDK5-mediated regulation of human dorsal root ganglia (hDRG) neuronal properties, we have performed the whole-cell patch clamp recordings in neurons dissociated from hDRG. CDK5 activation induced by overexpression of p35 depolarized the resting membrane potential (RMP) and reduced the rheobase currents as compared to the control neurons. CDK5 activation changed the shape of the action potential (AP) by increasing AP -rise time, -fall time, and -half width. The application of a prostaglandin E2 (PG) and bradykinin (BK) cocktail in control hDRG neurons induced the depolarization of RMP and the reduction of rheobase currents along with increased AP rise time. However, PG and BK applications failed to induce any significant changes in the p35-overexpressing group. We conclude that, in dissociated hDRGs neurons, CDK5 activation through the overexpression of p35 broadens the AP and that CDK5 may play important roles in the modulation of AP properties in human primary afferents under the condition in which CDK5 is upregulated, contributing to chronic pain.

A novel class of broad-spectrum active-site-directed 3C-like protease inhibitors with nanomolar antiviral activity against highly immune-evasive SARS-CoV-2 Omicron subvariants.

Antivirals with broad coronavirus activity are important for treating high-risk individuals exposed to the constantly evolving SARS-CoV-2 variants of concern (VOCs) as well as emerging drug-resistant variants. We developed and characterized a novel class of active-site-directed 3-chymotrypsin-like protease (3CLpro) inhibitors (C2-C5a). Our lead direct-acting antiviral (DAA), C5a, is a non-covalent, non-peptide with a dissociation constant of 170 nM against recombinant SARS-CoV-2 3CLpro. The compounds C2-C5a exhibit broad-spectrum activity against Omicron subvariants (BA.5, BQ.1.1, and XBB.1.5) and seasonal human coronavirus-229E infection in human cells. Notably, C5a has median effective concentrations of 30-50 nM against BQ.1.1 and XBB.1.5 in two different human cell lines. X-ray crystallography has confirmed the unique binding modes of C2-C5a to the 3CLpro, which can limit virus cross-resistance to emerging Paxlovid-resistant variants. We tested the effect of C5a with two of our newly discovered host-directed antivirals (HDAs): N-0385, a TMPRSS2 inhibitor, and bafilomycin D (BafD), a human vacuolar H+-ATPase [V-ATPase] inhibitor. We demonstrated a synergistic action of C5a in combination with N-0385 and BafD against Omicron BA.5 infection in human Calu-3 lung cells. Our findings underscore that a SARS-CoV-2 multi-targeted treatment for circulating Omicron subvariants based on DAAs (C5a) and HDAs (N-0385 or BafD) can lead to therapeutic benefits by enhancing treatment efficacy. Furthermore, the high-resolution structures of SARS-CoV-2 3CLpro in complex with C2-C5a will facilitate future rational optimization of our novel broad-spectrum active-site-directed 3C-like protease inhibitors.

Anti-miR-93-5p therapy prolongs sepsis survival by restoring the peripheral immune response.

Sepsis remains a leading cause of death for humans and currently has no pathogenesis-specific therapy. Hampered progress is partly due to a lack of insight into deep mechanistic processes. In the past decade, deciphering the functions of small noncoding miRNAs in sepsis pathogenesis became a dynamic research topic. To screen for new miRNA targets for sepsis therapeutics, we used samples for miRNA array analysis of PBMCs from patients with sepsis and control individuals, blood samples from 2 cohorts of patients with sepsis, and multiple animal models: mouse cecum ligation puncture-induced (CLP-induced) sepsis, mouse viral miRNA challenge, and baboon Gram+ and Gram- sepsis models. miR-93-5p met the criteria for a therapeutic target, as it was overexpressed in baboons that died early after induction of sepsis, was downregulated in patients who survived after sepsis, and correlated with negative clinical prognosticators for sepsis. Therapeutically, inhibition of miR-93-5p prolonged the overall survival of mice with CLP-induced sepsis, with a stronger effect in older mice. Mechanistically, anti-miR-93-5p therapy reduced inflammatory monocytes and increased circulating effector memory T cells, especially the CD4+ subset. AGO2 IP in miR-93-KO T cells identified important regulatory receptors, such as CD28, as direct miR-93-5p target genes. In conclusion, miR-93-5p is a potential therapeutic target in sepsis through the regulation of both innate and adaptive immunity, with possibly a greater benefit for elderly patients than for young patients.

Large-Scale Virtual Screening for the Discovery of SARS-CoV-2 Papain-like Protease (PLpro) Non-covalent Inhibitors.

The rapid global spread of the SARS-CoV-2 virus facilitated the development of novel direct-acting antiviral agents (DAAs). The papain-like protease (PLpro) has been proposed as one of the major SARS-CoV-2 targets for DAAs due to its dual role in processing viral proteins and facilitating the host's immune suppression. This dual role makes identifying small molecules that can effectively neutralize SARS-CoV-2 PLpro activity a high-priority task. However, PLpro drug discovery faces a significant challenge due to the high mobility and induced-fit effects in the protease's active site. Herein, we virtually screened the ZINC20 database with Deep Docking (DD) to identify prospective noncovalent PLpro binders and combined ultra-large consensus docking with two pharmacophore (ph4)-filtering strategies. The analysis of active compounds revealed their somewhat-limited diversity, likely attributed to the induced-fit nature of PLpro's active site in the crystal structures, and therefore, the use of rigid docking protocols poses inherited limitations. The top hits were assessed against recombinant viral proteins and live viruses, demonstrating desirable inhibitory activities. The best compound VPC-300195 (IC50: 15 µM) ranks among the top noncovalent PLpro inhibitors discovered through in silico methodologies. In the search for novel SARS-CoV-2 PLpro-specific chemotypes, the identified inhibitors could serve as diverse templates for the development of effective noncovalent PLpro inhibitors.

The Role of Non-Coding RNAs in Chromosomal Instability in Cancer.

Chromosomal instability (CIN) is characterized by an increased frequency of changes in chromosome structure or number and is regarded as a hallmark of cancer. CIN plays a prevalent role in tumorigenesis and cancer progression by assisting the cancer cells' phenotypic adaptation to stress, which have been tightly linked to therapy resistance and metastasis. Both CIN-inducing and CIN-repressing agents are being clinically tested for the treatment of cancer to increase CIN levels to unsustainable levels leading to cell death or to decrease CIN levels to limit the development of drug resistance, respectively. Non-coding RNAs (ncRNAs) including microRNAs and long ncRNAs (lncRNAs) have been fundamentally implicated in CIN. The miR-22, miR-26a, miR-28, and miR-186 target important checkpoint proteins involved in mediating chromosomal stability and their expression modulation has been directly related to CIN occurrence. lncRNAs derived from telomeric, centrosomal, and enhancer regions play an important role in mediating genome stability, while specific lncRNA transcripts including genomic instability inducing RNA called Ginir, P53-responsive lncRNA termed as GUARDIN, colon cancer-associated transcript 2, PCAT2, and ncRNA activated by DNA damage called NORAD have been shown to act within CIN-associated pathways. In this review, we discuss how these ncRNAs either maintain or disrupt the stability of chromosomes and how these mechanisms could be exploited for novel therapeutic approaches targeting CIN in cancer patients. SIGNIFICANCE STATEMENT: Chromosomal instability increases tumor heterogeneity and thereby assists the phenotypic adaptation of cancer cells, causing therapy resistance and metastasis. Several microRNAs and long non-coding RNAs that have been causally linked to chromosomal instability could represent novel therapeutic targets. Understanding the role of non-coding RNAs in regulating different genes involved in driving chromosomal instability will give insights into how non-coding RNAs can be utilized toward modifying chemotherapeutic regimens in different cancers.

Computational design of peptides to target NaV1.7 channel with high potency and selectivity for the treatment of pain.

The voltage-gated sodium NaV1.7 channel plays a key role as a mediator of action potential propagation in C-fiber nociceptors and is an established molecular target for pain therapy. ProTx-II is a potent and moderately selective peptide toxin from tarantula venom that inhibits human NaV1.7 activation. Here we used available structural and experimental data to guide Rosetta design of potent and selective ProTx-II-based peptide inhibitors of human NaV1.7 channels. Functional testing of designed peptides using electrophysiology identified the PTx2-3127 and PTx2-3258 peptides with IC50s of 7 nM and 4 nM for hNaV1.7 and more than 1000-fold selectivity over human NaV1.1, NaV1.3, NaV1.4, NaV1.5, NaV1.8, and NaV1.9 channels. PTx2-3127 inhibits NaV1.7 currents in mouse and human sensory neurons and shows efficacy in rat models of chronic and thermal pain when administered intrathecally. Rationally designed peptide inhibitors of human NaV1.7 channels have transformative potential to define a new class of biologics to treat pain.

X-ray crystallographic characterization of the SARS-CoV-2 main protease polyprotein cleavage sites essential for viral processing and maturation.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the pathogen that causes COVID-19, produces polyproteins 1a and 1ab that contain, respectively, 11 or 16 non-structural proteins (nsp). Nsp5 is the main protease (Mpro) responsible for cleavage at eleven positions along these polyproteins, including at its own N- and C-terminal boundaries, representing essential processing events for viral assembly and maturation. Using C-terminally substituted Mpro chimeras, we have determined X-ray crystallographic structures of Mpro in complex with 10 of its 11 viral cleavage sites, bound at full occupancy intermolecularly in trans, within the active site of either the native enzyme and/or a catalytic mutant (C145A). Capture of both acyl-enzyme intermediate and product-like complex forms of a P2(Leu) substrate in the native active site provides direct comparative characterization of these mechanistic steps as well as further informs the basis for enhanced product release of Mpro's own unique C-terminal P2(Phe) cleavage site to prevent autoinhibition. We characterize the underlying noncovalent interactions governing binding and specificity for this diverse set of substrates, showing remarkable plasticity for subsites beyond the anchoring P1(Gln)-P2(Leu/Val/Phe), representing together a near complete analysis of a multiprocessing viral protease. Collectively, these crystallographic snapshots provide valuable mechanistic and structural insights for antiviral therapeutic development.

Targeting SARS-CoV-2 papain-like protease in the postvaccine era.

While vaccines remain at the forefront of global healthcare responses, pioneering therapeutics against SARS-CoV-2 are expected to fill the gaps for waning immunity. Rapid development and approval of orally available direct-acting antivirals targeting crucial SARS-CoV-2 proteins marked the beginning of the era of small-molecule drugs for COVID-19. In that regard, the papain-like protease (PLpro) can be considered a major SARS-CoV-2 therapeutic target due to its dual biological role in suppressing host innate immune responses and in ensuring viral replication. Here, we summarize the challenges of targeting PLpro and innovative early-stage PLpro-specific small molecules. We propose that state-of-the-art computer-aided drug design (CADD) methodologies will play a critical role in the discovery of PLpro compounds as a novel class of COVID-19 drugs.

Connexin Lateralization Contributes to Male Susceptibility to Atrial Fibrillation.

Men have a higher risk of developing atrial fibrillation (AF) than women, though the reason for this is unknown. Here, we compared atrial electrical and structural properties in male and female mice and explored the contribution of sex hormones. Cellular electrophysiological studies revealed that action potential configuration, Na+ and K+ currents were similar in atrial myocytes from male and female mice (4-5 months). Immunofluorescence showed that male atrial myocytes had more lateralization of connexins 40 (63 ± 4%) and 43 (66 ± 4%) than females (Cx40: 45 ± 4%, p = 0.006; Cx43: 44 ± 4%, p = 0.002), with no difference in mRNA expression. Atrial mass was significantly higher in males. Atrial myocyte dimensions were also larger in males. Atrial fibrosis was low and similar between sexes. Orchiectomy (ORC) abolished sex differences in AF susceptibility (M: 65%; ORC: 38%, p = 0.050) by reducing connexin lateralization and myocyte dimensions. Ovariectomy (OVX) did not influence AF susceptibility (F: 42%; OVX: 33%). This study shows that prior to the development of age-related remodeling, male mice have more connexin lateralization and larger atria and atrial myocyte than females. Orchiectomy reduced AF susceptibility in males by decreasing connexin lateralization and atrial myocyte size, supporting a role for androgens. These sex differences in AF substrates may contribute to male predisposition to AF.

Atrial Electrical Remodeling in Mice With Cardiac-Specific Overexpression of Angiotensin II Type 1 Receptor.

Background Elevated angiotensin II levels are thought to play an important role in atrial electrical and structural remodeling associated with atrial fibrillation. However, the mechanisms by which this remodeling occurs are still unclear. Accordingly, we explored the effects of angiotensin II on atrial remodeling using transgenic mice overexpressing angiotensin II type 1 receptor (AT1R) specifically in cardiomyocytes. Methods and Results Voltage-clamp techniques, surface ECG, programmed electrical stimulations along with quantitative polymerase chain reaction, Western blot, and Picrosirius red staining were used to compare the atrial phenotype of AT1R mice and their controls at 50 days and 6 months. Atrial cell capacitance and fibrosis were increased only in AT1R mice at 6 months, indicating the presence of structural remodeling. Ca2+ (ICaL) and K+ currents were not altered by AT1R overexpression (AT1R at 50 days). However, ICaL density and CaV1.2 messenger RNA expression were reduced by structural remodeling (AT1R at 6 months). Conversely, Na+ current (INa) was reduced (-65%) by AT1R overexpression (AT1R at 50 days) and the presence of structural remodeling (AT1R at 6 months) yields no further effect. The reduced INa density was not explained by lower NaV1.5 expression but was rather associated with an increase in sarcolemmal protein kinase C alpha expression in the atria, suggesting that chronic AT1R activation reduced INa through protein kinase C alpha activation. Furthermore, connexin 40 expression was reduced in AT1R mice at 50 days and 6 months. These changes were associated with delayed atrial conduction time, as evidenced by prolonged P-wave duration. Conclusions Chronic AT1R activation leads to slower atrial conduction caused by reduced INa density and connexin 40 expression.

Development of VPC-70619, a Small-Molecule N-Myc Inhibitor as a Potential Therapy for Neuroendocrine Prostate Cancer.

The Myc family of transcription factors are involved in the development and progression of numerous cancers, including prostate cancer (PCa). Under the pressure of androgen receptor (AR)-directed therapies resistance can occur, leading to the lethal form of PCa known as neuroendocrine prostate cancer (NEPC), characterized among other features by N-Myc overexpression. There are no clinically approved treatments for NEPC, translating into poor patient prognosis and survival. Therefore, there is a pressing need to develop novel therapeutic avenues to treat NEPC patients. In this study, we investigate the N-Myc-Max DNA binding domain (DBD) as a potential target for small molecule inhibitors and utilize computer-aided drug design (CADD) approaches to discover prospective hits. Through further exploration and optimization, a compound, VPC-70619, was identified with notable anti-N-Myc potency and strong antiproliferative activity against numerous N-Myc expressing cell lines, including those representing NEPC.

Artificial intelligence-enabled virtual screening of ultra-large chemical libraries with deep docking.

With the recent explosion of chemical libraries beyond a billion molecules, more efficient virtual screening approaches are needed. The Deep Docking (DD) platform enables up to 100-fold acceleration of structure-based virtual screening by docking only a subset of a chemical library, iteratively synchronized with a ligand-based prediction of the remaining docking scores. This method results in hundreds- to thousands-fold virtual hit enrichment (without significant loss of potential drug candidates) and hence enables the screening of billion molecule-sized chemical libraries without using extraordinary computational resources. Herein, we present and discuss the generalized DD protocol that has been proven successful in various computer-aided drug discovery (CADD) campaigns and can be applied in conjunction with any conventional docking program. The protocol encompasses eight consecutive stages: molecular library preparation, receptor preparation, random sampling of a library, ligand preparation, molecular docking, model training, model inference and the residual docking. The standard DD workflow enables iterative application of stages 3-7 with continuous augmentation of the training set, and the number of such iterations can be adjusted by the user. A predefined recall value allows for control of the percentage of top-scoring molecules that are retained by DD and can be adjusted to control the library size reduction. The procedure takes 1-2 weeks (depending on the available resources) and can be completely automated on computing clusters managed by job schedulers. This open-source protocol, at https://github.com/jamesgleave/DD_protocol , can be readily deployed by CADD researchers and can significantly accelerate the effective exploration of ultra-large portions of a chemical space.

Drugging the 'undruggable'. Therapeutic targeting of protein-DNA interactions with the use of computer-aided drug discovery methods.

Transcription factors (TFs) act as major oncodrivers in many cancers and are frequently regarded as high-value therapeutic targets. The functionality of TFs relies on direct protein-DNA interactions, which are notoriously difficult to target with small molecules. However, this prior view of the 'undruggability' of protein-DNA interfaces has shifted substantially in recent years, in part because of significant advances in computer-aided drug discovery (CADD). In this review, we highlight recent examples of successful CADD campaigns resulting in drug candidates that directly interfere with protein-DNA interactions of several key cancer TFs, including androgen receptor (AR), ETS-related gene (ERG), MYC, thymocyte selection-associated high mobility group box protein (TOX), topoisomerase II (TOP2), and signal transducer and activator of transcription 3 (STAT3). Importantly, these findings open novel and compelling avenues for therapeutic targeting of over 1600 human TFs implicated in many conditions including and beyond cancer.

Arrhythmogenic and antiarrhythmic actions of late sustained sodium current in the adult human heart.

Late sodium current (late INa) inhibition has been proposed to suppress the incidence of arrhythmias generated by pathological states or induced by drugs. However, the role of late INa in the human heart is still poorly understood. We therefore investigated the role of this conductance in arrhythmias using adult primary cardiomyocytes and tissues from donor hearts. Potentiation of late INa with ATX-II (anemonia sulcata toxin II) and E-4031 (selective blocker of the hERG channel) slowed the kinetics of action potential repolarization, impaired Ca2+ homeostasis, increased contractility, and increased the manifestation of arrhythmia markers. These effects could be reversed by late INa inhibitors, ranolazine and GS-967. We also report that atrial tissues from donor hearts affected by atrial fibrillation exhibit arrhythmia markers in the absence of drug treatment and inhibition of late INa with GS-967 leads to a significant reduction in arrhythmic behaviour. These findings reveal a critical role for the late INa in cardiac arrhythmias and suggest that inhibition of this conductance could provide an effective therapeutic strategy. Finally, this study highlights the utility of human ex-vivo heart models for advancing cardiac translational sciences.

Automated discovery of noncovalent inhibitors of SARS-CoV-2 main protease by consensus Deep Docking of 40 billion small molecules.

Recent explosive growth of 'make-on-demand' chemical libraries brought unprecedented opportunities but also significant challenges to the field of computer-aided drug discovery. To address this expansion of the accessible chemical universe, molecular docking needs to accurately rank billions of chemical structures, calling for the development of automated hit-selecting protocols to minimize human intervention and error. Herein, we report the development of an artificial intelligence-driven virtual screening pipeline that utilizes Deep Docking with Autodock GPU, Glide SP, FRED, ICM and QuickVina2 programs to screen 40 billion molecules against SARS-CoV-2 main protease (Mpro). This campaign returned a significant number of experimentally confirmed inhibitors of Mpro enzyme, and also enabled to benchmark the performance of twenty-eight hit-selecting strategies of various degrees of stringency and automation. These findings provide new starting scaffolds for hit-to-lead optimization campaigns against Mpro and encourage the development of fully automated end-to-end drug discovery protocols integrating machine learning and human expertise.

Crystallographic structure of wild-type SARS-CoV-2 main protease acyl-enzyme intermediate with physiological C-terminal autoprocessing site.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the pathogen that causes the disease COVID-19, produces replicase polyproteins 1a and 1ab that contain, respectively, 11 or 16 nonstructural proteins (nsp). Nsp5 is the main protease (Mpro) responsible for cleavage at eleven positions along these polyproteins, including at its own N- and C-terminal boundaries, representing essential processing events for subsequent viral assembly and maturation. We have determined X-ray crystallographic structures of this cysteine protease in its wild-type free active site state at 1.8 Å resolution, in its acyl-enzyme intermediate state with the native C-terminal autocleavage sequence at 1.95 Å resolution and in its product bound state at 2.0 Å resolution by employing an active site mutation (C145A). We characterize the stereochemical features of the acyl-enzyme intermediate including critical hydrogen bonding distances underlying catalysis in the Cys/His dyad and oxyanion hole. We also identify a highly ordered water molecule in a position compatible for a role as the deacylating nucleophile in the catalytic mechanism and characterize the binding groove conformational changes and dimerization interface that occur upon formation of the acyl-enzyme. Collectively, these crystallographic snapshots provide valuable mechanistic and structural insights for future antiviral therapeutic development including revised molecular docking strategies based on Mpro inhibition.

Dual-Inhibitors of N-Myc and AURKA as Potential Therapy for Neuroendocrine Prostate Cancer.

Resistance to androgen-receptor (AR) directed therapies is, among other factors, associated with Myc transcription factors that are involved in development and progression of many cancers. Overexpression of N-Myc protein in prostate cancer (PCa) leads to its transformation to advanced neuroendocrine prostate cancer (NEPC) that currently has no approved treatments. N-Myc has a short half-life but acts as an NEPC stimulator when it is stabilized by forming a protective complex with Aurora A kinase (AURKA). Therefore, dual-inhibition of N-Myc and AURKA would be an attractive therapeutic avenue for NEPC. Following our computer-aided drug discovery approach, compounds exhibiting potent N-Myc specific inhibition and strong anti-proliferative activity against several N-Myc driven cell lines, were identified. Thereafter, we have developed dual inhibitors of N-Myc and AURKA through structure-based drug design approach by merging our novel N-Myc specific chemical scaffolds with fragments of known AURKA inhibitors. Favorable binding modes of the designed compounds to both N-Myc and AURKA target sites have been predicted by docking. A promising lead compound, 70812, demonstrated low-micromolar potency against both N-Myc and AURKA in vitro assays and effectively suppressed NEPC cell growth.

Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery.

Drug discovery is a rigorous process that requires billion dollars of investments and decades of research to bring a molecule "from bench to a bedside". While virtual docking can significantly accelerate the process of drug discovery, it ultimately lags the current rate of expansion of chemical databases that already exceed billions of molecular records. This recent surge of small molecules availability presents great drug discovery opportunities, but also demands much faster screening protocols. In order to address this challenge, we herein introduce Deep Docking (DD), a novel deep learning platform that is suitable for docking billions of molecular structures in a rapid, yet accurate fashion. The DD approach utilizes quantitative structure-activity relationship (QSAR) deep models trained on docking scores of subsets of a chemical library to approximate the docking outcome for yet unprocessed entries and, therefore, to remove unfavorable molecules in an iterative manner. The use of DD methodology in conjunction with the FRED docking program allowed rapid and accurate calculation of docking scores for 1.36 billion molecules from the ZINC15 library against 12 prominent target proteins and demonstrated up to 100-fold data reduction and 6000-fold enrichment of high scoring molecules (without notable loss of favorably docked entities). The DD protocol can readily be used in conjunction with any docking program and was made publicly available.

Rapid Identification of Potential Inhibitors of SARS-CoV-2 Main Protease by Deep Docking of 1.3†Billion Compounds.

The recently emerged 2019 Novel Coronavirus (SARS-CoV-2) and associated COVID-19 disease cause serious or even fatal respiratory tract infection and yet no approved therapeutics or effective treatment is currently available to effectively combat the outbreak. This urgent situation is pressing the world to respond with the development of novel vaccine or a small molecule therapeutics for SARS-CoV-2. Along these efforts, the structure of SARS-CoV-2 main protease (Mpro) has been rapidly resolved and made publicly available to facilitate global efforts to develop novel drug candidates. Recently, our group has developed a novel deep learning platform - Deep Docking (DD) which provides fast prediction of docking scores of Glide (or any other docking program) and, hence, enables structure-based virtual screening of billions of purchasable molecules in a short time. In the current study we applied DD to all 1.3 billion compounds from ZINC15 library to identify top 1,000 potential ligands for SARS-CoV-2 Mpro protein. The compounds are made publicly available for further characterization and development by scientific community.