Co-Occurring Infections in Cancer Patients Treated with Checkpoint Inhibitors Significantly Increase the Risk of Immune-Related Adverse Events.

Therapeutic antibodies designed to target three immune checkpoint proteins have been applied in the treatment of various malignancies, including small and non-small cell lung cancers, melanoma, renal cell carcinoma, and others. These treatments combat cancers by reactivating cytotoxic T cells. Nevertheless, this mode of action was found to be associated with a broad range of immune-related adverse events (irAEs), including pneumonitis, sarcoidosis, myocarditis, nephritis, colitis, and hepatitis. Depending on their severity, these irAEs often necessitate the suspension or discontinuation of treatment and, in rare instances, may lead to fatalities. We analyzed over nineteen million reports and identified over eighty thousand adverse event reports from patients treated with immune checkpoint inhibitors submitted to the Food and Drug Administration's Adverse Event Reporting System MedWatch. Reports concerning pembrolizumab, nivolumab, cemiplimab, avelumab, durvalumab, atezolizumab, and ipilimumab revealed a statistically significant association between the irAEs and concurrent infectious diseases for five out of seven treatments. Furthermore, the association trend was preserved across all three types of checkpoint inhibitors and each of the five individual therapeutic agent cohorts, while the remaining two showed the same trend, but an increased confidence interval, due to an insufficient number of records.

Software and Databases for Protein-Protein Docking.

Protein-protein interactions (PPIs) provide valuable insights for understanding the principles of biological systems and for elucidating causes of incurable diseases. One of the techniques used for computational prediction of PPIs is protein-protein docking calculations, and a variety of software has been developed. This chapter is a summary of software and databases used for protein-protein docking.

Hepatic injury and hepatic failure adverse events in 3,4-methylenedioxymethamphetamine users reported to the FDA Adverse Event Reporting System.

3,4-Methylenedioxymethamphetamine (MDMA) is being investigated in controlled clinical trials for use as an adjunct medication treatment for post-traumatic stress disorder. MDMA is metabolized by N-demethylation, primarily by CYP2D6, to its main inactive metabolite, 4-hydroxy-3-methoxymethamphetamine. It is also metabolized to a lesser extent by CYP1A2, CYP2B6, and CYP3A4 to its active metabolite, 3,4-methylenedioxyamphetamine. Considering the extensive hepatic metabolism and excretion, MDMA use in psychiatry raises concerns over drug-induced liver injury (DILI), a rare but dangerous event. Majority of the drugs withdrawn from the market for liver injury caused death or transplantation at frequencies under 0.01%. Unfortunately, markers for liver injury were not measured in most published clinical trials. At the same time, no visible DILI-related symptoms and adverse events were observed. Idiosyncratic DILI cases are rarely registered during clinical trials due to their rare nature. In this study, we surveyed a larger, over 1,500, and a more diverse set of reports from the FDA Adverse Event Reporting System and found 23 cases of hepatic injury and hepatic failure, in which MDMA was reported to be taken in addition to one or more substances. Interestingly, 22 out of 23 cases had one or more listed drugs with a known DILI concern based on the FDA's DILIrank dataset. Furthermore, only one report had MDMA listed as the primary suspect. Considering the nearly 20 million doses of MDMA used annually, this single report is insufficient for establishing a significant association with DILI.

De novo generation of multi-target compounds using deep generative chemistry.

Polypharmacology drugs-compounds that inhibit multiple proteins-have many applications but are difficult to design. To address this challenge we have developed POLYGON, an approach to polypharmacology based on generative reinforcement learning. POLYGON embeds chemical space and iteratively samples it to generate new molecular structures; these are rewarded by the predicted ability to inhibit each of two protein targets and by drug-likeness and ease-of-synthesis. In binding data for >100,000 compounds, POLYGON correctly recognizes polypharmacology interactions with 82.5% accuracy. We subsequently generate de-novo compounds targeting ten pairs of proteins with documented co-dependency. Docking analysis indicates that top structures bind their two targets with low free energies and similar 3D orientations to canonical single-protein inhibitors. We synthesize 32 compounds targeting MEK1 and mTOR, with most yielding >50% reduction in each protein activity and in cell viability when dosed at 1-10 µM. These results support the potential of generative modeling for polypharmacology.

Thyroid Hyperplasia and Neoplasm Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists in the Food and Drug Administration Adverse Event Reporting System: Retrospective Analysis.

Background: Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are one of the most commonly used drugs for type 2 diabetes mellitus. Clinical guidelines recommend GLP-1 RAs as an adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, and obesity. The weight loss observed in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment. Objective: Although the adverse event profile is relatively safe, most GLP-1 RAs come with a labeled boxed warning for the risk of thyroid cancers, based on animal models and some postmarketing case reports in humans. Considering the increasing popularity of this drug class and its expansion into a new popular indication, a further review of the most recent postmarketing safety data was warranted to quantify thyroid hyperplasia and neoplasm instances. Methods: GLP-1 RA patient reports from the US Food and Drug Administration (FDA) Adverse Event Reporting System database were analyzed using reporting odds ratios and 95% CIs. Results: In this study, we analyzed over 18 million reports from the US FDA Adverse Event Reporting System and provided evidence of significantly increased propensity for thyroid hyperplasias and neoplasms in patients taking GLP-1 RA monotherapy when compared to patients taking sodium-glucose cotransporter-2 (SGLT-2) inhibitor monotherapy. Conclusions: GLP-1 RAs, regardless of indication, are associated with an over 10-fold increase in thyroid neoplasm and hyperplasia adverse event reporting when compared to SGLT-2 inhibitors.

Efficient Generation of Conformer Ensembles Using Internal Coordinates and a Generative Directional Graph Convolution Neural Network.

We present a neural-network-based high-throughput molecular conformer-generation algorithm. A chemical graph-convolutional network is trained to predict low-energy conformers in internal coordinate representation (bond lengths, bond, and torsion angles), starting from two-dimensional (2D) chemical topology. Generative neural network (NN) architecture performs denoising from torsion space, producing conformer ensembles with populations that are well correlated with torsion energy profiles. Short force-field-based energy minimization is applied to refine final conformers. All computation-intensive stages of the algorithm are GPU-optimized. The procedure (termed GINGER) is benchmarked on a commonly used test set of bioactive three-dimensional (3D) conformers from the PDB. We demonstrate highly competitive results in conformer recovery and throughput rates suitable for giga-scale compound library processing. A web server that allows interactive conformer ensemble generation by GINGER and their viewing is made freely available at https://www.molsoft.com/gingerdemo.html.

Co-occurring infections in cancer patients treated with checkpoint inhibitors significantly increase the risk of immune related adverse events.

Therapeutic antibodies designed to target immune checkpoint proteins such as PD-1, PD-L1, and CTLA-4 have been applied in the treatment of various tumor types, including small and non-small cell lung cancers, melanoma, renal cell carcinoma, and others. These treatments combat cancers by reactivating CD8 cytotoxic T-cells. Nevertheless, this unique targeted mode of action was found to be associated with a broader range of immune-related adverse events, irAEs, affecting multiple physiological systems. Depending on their severity, these irAEs often necessitate the suspension or discontinuation of treatment and, in rare instances, may lead to fatal consequences. In this study we investigated over eighty thousand adverse event reports of irAEs in patients treated with PD-1, PD-L1, and CTLA-4 inhibitors. FDA Adverse Event Reporting System MedWatch submissions were used as the data source. These therapeutics included pembrolizumab, nivolumab, cemiplimab, avelumab, durvalumab, atezolizumab, and ipilimumab. The data analysis of these reports revealed a statistically significant association of immune related adverse events, including serious and life-threatening events in patients who experienced infectious disease during treatment. Additionally, the association trend was preserved across all the three classes of checkpoint inhibitors and each of the seven individual therapeutic agent cohorts.

Thyroid hyperplasia and neoplasm adverse events associated with GLP-1 receptor agonists in FDA Adverse Event Reporting System.

Glucagon receptor-like peptide receptor agonists, GLP-1 RAs, are one of the most commonly used drugs for type-2 diabetes mellitus. The clinical guidelines recommend GLP-1 RAs as adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, obesity, and other cardiometabolic conditions. The weight loss seen in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment. Although the adverse event profile is relatively safe, most GLP-1 RAs come with a labeled black boxed warning of the risk of thyroid cancers, based on animal models and some postmarketing case reports in humans. Considering the increasing popularity of this drug class and its expansion into a new popular indication, a further review of most recent postmarketing safety data is warranted to quantify thyroid hyperplasia and neoplasms instances. In this study we analyzed over eighteen million reports from United States Food and Drug Administration Adverse Event Reporting System and identified 17,653 relevant GLP-1 RA monotherapy reports to provide the evidence of significantly increased propensity for thyroid hyperplasias and neoplasms in patients taking GLP-1 RA as monotherapy when compared to patients taking sodium-glucose cotransporter-2 inhibitor monotherapy.

Human gain-of-function variants in HNF1A confer protection from diabetes but independently increase hepatic secretion of atherogenic lipoproteins.

Loss-of-function mutations in hepatocyte nuclear factor 1A (HNF1A) are known to cause rare forms of diabetes and alter hepatic physiology through unclear mechanisms. In the general population, 1:100 individuals carry a rare, protein-coding HNF1A variant, most of unknown functional consequence. To characterize the full allelic series, we performed deep mutational scanning of 11,970 protein-coding HNF1A variants in human hepatocytes and clinical correlation with 553,246 exome-sequenced individuals. Surprisingly, we found that ∼1:5 rare protein-coding HNF1A variants in the general population cause molecular gain of function (GOF), increasing the transcriptional activity of HNF1A by up to 50% and conferring protection from type 2 diabetes (odds ratio [OR] = 0.77, p = 0.007). Increased hepatic expression of HNF1A promoted a pro-atherogenic serum profile mediated in part by enhanced transcription of risk genes including ANGPTL3 and PCSK9. In summary, ∼1:300 individuals carry a GOF variant in HNF1A that protects carriers from diabetes but enhances hepatic secretion of atherogenic lipoproteins.

Anti-TNF-α therapy induced psoriasis in rheumatoid arthritis patients according to FDA postmarketing surveillance data.

Rheumatoid arthritis, RA, is a chronic autoimmune disease characterized by joint pain, tenderness, swelling, and stiffness. This disease affects nearly 1% of the world population. RA predominates in females and typically develops between the ages of 30 and 50 years. Common therapeutics for the treatment of RA include immune system suppressants such as tumor necrosis factor, or TNF, inhibitors. There is growing concern related to multiple clinical cases reporting an unexpected onset of psoriasis following the use of TNF inhibitors. This adverse event is counterintuitive since some tumor necrosis factor inhibitors are indicated for the treatment of plaque psoriasis. In this study, we analyzed over 880 thousand postmarketing safety reports from patients being treated for RA with a single therapeutic and provided evidence for a statistically significant association of psoriasis adverse events with TNF inhibitor use as compared to methotrexate. Additionally, we quantified the reported odds ratios and their 95% confidence intervals between four individual TNF inhibitors and found that the degree of association with psoriasis was variable among the drugs studied, with certolizumab pegol exhibiting the highest reported risk.

Concomitant medications associated with ischemic, hypertensive, and arrhythmic events in MDMA users in FDA adverse event reporting system.

3,4-Methylenedioxymethamphetamine (MDMA) is currently being investigated as an adjunctive treatment to therapy for posttraumatic stress and other anxiety related disorders in clinical trials. Within the next few years MDMA-assisted therapy is projected for approval by regulatory authorities. MDMA's primary mechanism of action includes modulation of monoamine signaling by increasing release and inhibiting reuptake of serotonin, norepinephrine, and, to a lesser extent, dopamine. This pharmacology affects sympathomimetic physiology. In controlled trials, special attention has been given to cardiovascular adverse events (AEs), because transient increases in heart rate and blood pressure have been observed during the MDMA-assisted therapy sessions. Finding and quantifying the potential drivers of cardiac AEs in clinical trials is difficult since only a relatively small number of participants have been included in these studies, and a limited set of allowed concomitant drugs has been studied. In this study a more diverse set of reports from the FDA Adverse Event Reporting System was surveyed. We found 17 cases of cardiovascular AEs, in which the individuals had taken one or more substances in addition to MDMA. Interestingly, all of those concomitant medications and illicit substances, including opioids, stimulants, anticholinergics, and amphetamines, had been previously associated with cardiovascular AEs. Furthermore, in none of the reports MDMA was marked as the primary suspect.

High-throughput phenotypic screen identifies a new family of potent anti-amoebic compounds.

Entamoeba histolytica is a disease-causing parasitic amoeba which affects an estimated 50 million people worldwide, particularly in socioeconomically vulnerable populations experiencing water sanitation issues. Infection with E. histolytica is referred to as amoebiasis, and can cause symptoms such as colitis, dysentery, and even death in extreme cases. Drugs exist that are capable of killing this parasite, but they are hampered by downsides such as significant adverse effects at therapeutic concentrations, issues with patient compliance, the need for additional drugs to kill the transmissible cyst stage, and potential development of resistance. Past screens of small and medium sized chemical libraries have yielded anti-amoebic candidates, thus rendering high-throughput screening a promising direction for new drug discovery in this area. In this study, we screened a curated 81,664 compound library from Janssen pharmaceuticals against E. histolytica trophozoites in vitro, and from it identified a highly potent new inhibitor compound. The best compound in this series, JNJ001, showed excellent inhibition activity against E. histolytica trophozoites with EC50 values at 0.29 µM, which is better than the current approved treatment, metronidazole. Further experimentation confirmed the activity of this compound, as well as that of several structurally related compounds, originating from both the Janssen Jump-stARter library, and from chemical vendors, thus highlighting a new structure-activity relationship (SAR). In addition, we confirmed that the compound inhibited E. histolytica survival as rapidly as the current standard of care and inhibited transmissible cysts of the related model organism Entamoeba invadens. Together these results constitute the discovery of a novel class of chemicals with favorable in vitro pharmacological properties. The discovery may lead to an improved therapy against this parasite and in all of its life stages.

Allosteric Inhibitors of Zika Virus NS2B-NS3 Protease Targeting Protease in "Super-Open" Conformation.

The Zika virus (ZIKV), a member of the Flaviviridae family, is considered a major health threat causing multiple cases of microcephaly in newborns and Guillain-Barré syndrome in adults. In this study, we targeted a transient, deep, and hydrophobic pocket of the "super-open" conformation of ZIKV NS2B-NS3 protease to overcome the limitations of the active site pocket. After virtual docking screening of approximately seven million compounds against the novel allosteric site, we selected the top six candidates and assessed them in enzymatic assays. Six candidates inhibited ZIKV NS2B-NS3 protease proteolytic activity at low micromolar concentrations. These six compounds, targeting the selected protease pocket conserved in ZIKV, serve as unique drug candidates and open new opportunities for possible treatment against several flavivirus infections.

Graph-Convolutional Neural Net Model of the Statistical Torsion Profiles for Small Organic Molecules.

We present a graph-convolutional neural network (GCNN)-based method for learning and prediction of statistical torsional profiles (STP) in small organic molecules based on the experimental X-ray structure data. A specialized GCNN torsion profile model is trained using the structures in the Crystallography Open Database (COD). The GCNN-STP model captures torsional preferences over a wide range of torsion rotor chemotypes and correctly predicts a variety of effects from the vicinal atoms and moieties. GCNN-STP statistical profiles also show good agreement with quantum chemically (DFT) calculated torsion energy profiles. Furthermore, we demonstrate the application of the GCNN-STP statistical profiles for conformer generation. A web server that allows interactive profile prediction and viewing is made freely available at https://www.molsoft.com/tortool.html.

Discovery of Triple Inhibitors of Both SARS-CoV-2 Proteases and Human Cathepsin L.

One inhibitor of the main SARS-CoV-2 protease has been approved recently by the FDA, yet it targets only SARS-CoV-2 main protease (Mpro). Here, we discovered inhibitors containing thiuram disulfide or dithiobis-(thioformate) tested against three key proteases involved in SARS-CoV-2 replication, including Mpro, SARS-CoV-2 papain-like protease (PLpro), and human cathepsin L. The use of thiuram disulfide and dithiobis-(thioformate) covalent inhibitor warheads was inspired by an idea to find a better alternative than disulfiram, an approved treatment for chronic alcoholism that is currently in phase 2 clinical trials against SARS-CoV-2. Our goal was to find more potent inhibitors that target both viral proteases and one essential human protease to reduce the dosage, improve the efficacy, and minimize the adverse effects associated with these agents. We found that compounds coded as RI175, RI173, and RI172 were the most potent inhibitors in an enzymatic assay against SARS-CoV-2 Mpro, SARS-CoV-2 PLpro, and human cathepsin L, with IC50s of 300, 200, and 200 nM, which is about 5-, 19-, and 11-fold more potent than disulfiram, respectively. In addition, RI173 was tested against SARS-CoV-2 in a cell-based and toxicity assay and was shown to have a greater antiviral effect than disulfiram. The identified compounds demonstrated the promising potential of thiuram disulfide or dithiobis-(thioformate) as a reactive functional group in small molecules that could be further developed for treatment of the COVID-19 virus or related variants.

Control of Unsaturation in De Novo Fatty Acid Biosynthesis by FabA.

Carrier protein-dependent biosynthesis provides a thiotemplated format for the production of natural products. Within these pathways, many reactions display exquisite substrate selectivity, a regulatory framework proposed to be controlled by protein-protein interactions (PPIs). In Escherichia coli, unsaturated fatty acids are generated within the de novo fatty acid synthase by a chain length-specific interaction between the acyl carrier protein AcpP and the isomerizing dehydratase FabA. To evaluate PPI-based control of reactivity, interactions of FabA with AcpP bearing multiple sequestered substrates were analyzed through NMR titration and guided high-resolution docking. Through a combination of quantitative binding constants, residue-specific perturbation analysis, and high-resolution docking, a model for substrate control via PPIs has been developed. The in silico results illuminate the mechanism of FabA substrate selectivity and provide a structural rationale with atomic detail. Helix III positioning in AcpP communicates sequestered chain length identity recognized by FabA, demonstrating a powerful strategy to regulate activity by allosteric control. These studies broadly illuminate carrier protein-dependent pathways and offer an important consideration for future inhibitor design and pathway engineering.

Retrospective analysis of clinical trial safety data for pembrolizumab reveals the effect of co-occurring infections on immune-related adverse events.

Biologics targeting PD-1, PD-L1, and CTLA-4 immune checkpoint proteins have been used in a variety of tumor types including small and non-small cell lung cancers, melanoma, and renal cell carcinoma. Their anti-tumor activity is achieved through amplifying components of the patient's own immune system to target immune response evading cancer cells. However, this unique mechanism of action causes a range of immune related adverse events, irAEs, that affect multiple physiological systems in the body. These irAEs, depending on severity, often cause suspension or discontinuation of therapy and, in rare cases, may lead to fatal outcomes. In this study we focused on pembrolizumab, a PD-1 inhibitor currently approved for multiple types of cancer. We analyzed over ten thousand adverse event reports from Keynote clinical trials of pembrolizumab for various cancer indications with or without co-occurring infections, and observed a statistically significant 80% increase in the risk of developing an irAE in subjects with infections.

Mapping the gene network landscape of Alzheimer's disease through integrating genomics and transcriptomics.

Integration of multi-omics data with molecular interaction networks enables elucidation of the pathophysiology of Alzheimer's disease (AD). Using the latest genome-wide association studies (GWAS) including proxy cases and the STRING interactome, we identified an AD network of 142 risk genes and 646 network-proximal genes, many of which were linked to synaptic functions annotated by mouse knockout data. The proximal genes were confirmed to be enriched in a replication GWAS of autopsy-documented cases. By integrating the AD gene network with transcriptomic data of AD and healthy temporal cortices, we identified 17 gene clusters of pathways, such as up-regulated complement activation and lipid metabolism, down-regulated cholinergic activity, and dysregulated RNA metabolism and proteostasis. The relationships among these pathways were further organized by a hierarchy of the AD network pinpointing major parent nodes in graph structure including endocytosis and immune reaction. Control analyses were performed using transcriptomics from cerebellum and a brain-specific interactome. Further integration with cell-specific RNA sequencing data demonstrated genes in our clusters of immunoregulation and complement activation were highly expressed in microglia.