Putative Drug Research Articles

Prevention of Drug Hypersensitivity Reactions: Prescreening and Premedication

Drug hypersensitivity reactions (DHR) are heterogeneous in their pathomechanisms, clinical presentation, severity, and outcomes. Novel DHR mechanisms, phenotypes, and endotypes have been described. The key to prevention from further exposure to the culprit drugs involves correct identification of the putative drug through a combination of invitro and/or invivo tests, accurate drug allergy labeling and reporting, and electronic decision support systems within electronic medical records to prevent future accidental prescribing. Prescreening and premedication, the focus of this review, may be a useful adjunct to preventive measures in certain situations. After an index immediate drug hypersensitivity reaction, prescreening may be useful in perioperative anaphylaxis, and iodinated (ICM) and gadolinium-based contrast media (GCM) where the culprit and potential alternative agents are skin tested. In certain nonimmediate DHR, pharmacogenomic prescreening may be used before prescribing high-risk drugs (eg, carbamazepine and allopurinol) where specific human-leukocyte antigen genotypes are associated with severe cutaneous adverse reactions. Premedication with antihistamine and systemic corticosteroids is another therapeutic strategy to prevent infusion reactions for certain biologicals and chemotherapeutic agents, in cases of perioperative anaphylaxis, ICM and GCM DHR, and clonal mast cell disorders. Rapid drug desensitization may also be used to induce temporary tolerance in situations where there are limited alternative drugs.

Homology Modelling and Virtual Screening of 3-deoxy-D-mannooctulosonic Acid Transferase of Aeromonas hydrophila as a Potential Target for Novel Natural Inhibitory Compounds

Background: The fish pathogen Aeromonas hydrophila is fast acquiring resistance to commonly employed antibiotics in aquaculture. This development has compelled the aquaculture sector to identify and develop new therapeutics to manage the pathogen. Methods: In this study, the protein 3-deoxy-d-manno-2-octulosonic acid (Kdo) transferase of A. hydrophila involved in the biosynthesis of the cell wall was studied in-silico as a potential drug target to control this pathogen. The three-dimensional structure of Kdo transferase was predicted by homology modelling using the Modellar 9.15. A total of 7682 natural compounds and 55 known Gram-negative bacterial inhibitors were virtually screened. Laboratory evaluation of inhibitory effects of identified inhibitors against A. hydrophila was performed using extracts from tea leaves and Astragalus by standard disc diffusion method. Results: A molecular model of putative virulence factor Kdo was derived by homology modelling. Eleven compounds were found to be potential inhibitors of Kdo. Among natural compounds, LArabinose and Flavan-3,4-diol were identified as the putative therapeutic agents. In the disc diffusion test, the zones of inhibition were observed at 2 mg/ml concentrations for tea leaves extracts and 8 mg/ml for Astragalus, suggesting the inhibitory effects of these extracts. Conclusion: The study shows the utility of essential enzymes such as the protein Kdo transferase as a putative drug target and the potential application of natural compounds in the control of pathogens in aquaculture without the need to use synthetic antimicrobial compounds.

Solid Lipid Nanoparticles (SLNs): An Advanced Drug Delivery System Targeting Brain through BBB.

The blood–brain barrier (BBB) plays a vital role in the protection and maintenance of homeostasis in the brain. In this way, it is an interesting target as an interface for various types of drug delivery, specifically in the context of the treatment of several neuropathological conditions where the therapeutic agents cannot cross the BBB. Drug toxicity and on-target specificity are among some of the limitations associated with current neurotherapeutics. In recent years, advances in nanodrug delivery have enabled the carrier system containing the active therapeutic drug to target the signaling pathways and pathophysiology that are closely linked to central nervous system (CNS) disorders such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), multiple sclerosis (MS), brain tumor, epilepsy, ischemic stroke, and neurodegeneration. At present, among the nano formulations, solid lipid nanoparticles (SLNs) have emerged as a putative drug carrier system that can deliver the active therapeutics (drug-loaded SLNs) across the BBB at the target site of the brain, offering a novel approach with controlled drug delivery, longer circulation time, target specificity, and higher efficacy, and more importantly, reducing toxicity in a biomimetic way. This paper highlights the synthesis and application of SLNs as a novel nontoxic formulation strategy to carry CNS drugs across the BBB to improve the use of therapeutics agents in treating major neurological disorders in future clinics.

Identification of long non-coding RNA biomarkers and signature scoring, with competing endogenous RNA networks- targeted drug candidates for recurrent implantation failure

Recurrent implantation failure (RIF) remains a source of frustration and presents challenges to clinicians in the practice of assisted reproductive technology (ART). Long non-coding RNAs (lncRNAs) are increasingly recognised as potential biomarkers in various diseases. In this study, eight differentially expressed lncRNAs (LINC00645, LINC00844, LINC02349, AC010975.1, AC022034.1, AC096719.1, AC104072.1 and DLGAP1-AS3) to distinguish RIF from fertile women were identified by RobustRankAggreg (RRA). A two-lncRNA signature for predicting RIF was established by least absolute shrinkage and selection operator (LASSO) regression, with accuracy confirmed by receiver operating characteristic (ROC) curves. After lncRNA-microRNA-mRNA regulatory networks were established by Cytoscape 3.7.2, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed, suggesting that the lncRNA-miRNA-mRNA regulatory networks were associated with biological processes involved in endometrial receptivity. Finally, three putative drugs (miconazole, terfenadine and STOCK1N-35215) for RIF were predicted by a Connectivity Map. In conclusion, we identified eight lncRNA biomarkers and a two-lncRNA signature for predicting RIF, as well as proposing three candidate drugs against RIF by targeting the ceRNA networks.

Subtractive Genomics Approach for Identification of Novel Therapeutic Drug Targets in Mycoplasma genitalium

Mycoplasma genitalium infection is a sexually transmitted infection that causes urethritis, cervicitis, and pelvic inflammatory disease (PID) in men and women. The global rise in antimicrobial resistance against recommended antibiotics for the treatment of M. genitalium infection has triggered the need to explore novel drug targets against this pathogen. The application of a bioinformatics approach through subtractive genomics has proven highly instrumental in predicting novel therapeutic targets against a pathogen. This study aimed to identify essential and non-homologous proteins with unique metabolic pathways in the pathogen that could serve as novel drug targets. Based on this, a manual comparison of the metabolic pathways of M. genitalium and the human host was done, generating nine pathogen-specific metabolic pathways. Additionally, the analysis of the whole proteome of M. genitalium using different bioinformatics databases generated 21 essential, non-homologous, and cytoplasmic proteins involved in nine pathogen-specific metabolic pathways. The further screening of these 21 cytoplasmic proteins in the DrugBank database generated 13 druggable proteins, which showed similarity with FDA-approved and experimental small-molecule drugs. A total of seven proteins that are involved in seven different pathogen-specific metabolic pathways were finally selected as novel putative drug targets after further analysis. Therefore, these proposed drug targets could aid in the design of potent drugs that may inhibit the functionality of these pathogen-specific metabolic pathways and, as such, lead to the eradication of this pathogen.

Emerging Modulators of TMEM16A and Their Therapeutic Potential.

Calcium-activated chloride channels (CaCCs) are widespread chloride channels which rely on calcium activation to perform their functions. In 2008, TMEM16A (also known as anoctamin1, ANO1) was identified as the molecular basis of the CaCCs, which provided the possibility to study the physiological function of CaCCs. TMEM16A is widely expressed in various cells and controls basic physiological functions, including neuronal and cardiac excitability, nerve transduction, smooth muscle contraction, epithelial Cl- secretion and fertilization. However, the abnormal function of TMEM16A may cause a variety of diseases, including asthma, gastrointestinal motility disorder and various cancers. Therefore, TMEM16A is a putative drug target for many diseases, and it is important to determine specific and efficient modulators of TMEM16A channel. In recent years, we and others have screened several natural modulators of TMEM16A against cancers and gastrointestinal motility dysfunction. This article reviews the screening methods, efficacy of TMEM16A modulators and pharmacological effects of TMEM16A modulators on different diseases. GRAPHIC ABSTACT.

Synthetic corticosteroids as tryptophan hydroxylase stabilizers.

Background: Clinically, corticosteroids are used mainly for their immune-modulatory properties but are also known to influence mood. Despite evidence of a role in regulating tryptophan hydroxylases (TPH), key enzymes in serotonin biosynthesis, a direct action of corticosteroids on these enzymes has not been systematically investigated. Methodology & results: Corticosteroid effects on TPHs were tested using an in vitro assay. The compound with the strongest modulatory effect, beclomethasone dipropionate, activated TPH1 and TPH2 with low micromolar potency. Thermostability assays suggested a stabilizing mechanism, and computational docking indicated that beclomethasone dipropionate interacts with the TPH active site. Conclusion: Beclomethasone dipropionate is a stabilizer of TPHs, acting as a pharmacological chaperone. Our findings may inspire further development of steroid scaffolds as putative antidepressant drugs.

Intestinal MYC modulates obesity-related metabolic dysfunction.

MYC is a transcription factor with broad biological functions, notably in the control of cell proliferation. Here, we show that intestinal MYC regulates systemic metabolism. We find that MYC expression is increased in ileum biopsies from individuals with obesity and positively correlates with body mass index. Intestine-specific reduction of MYC in mice improves high-fat-diet-induced obesity, insulin resistance, hepatic steatosis and steatohepatitis. Mechanistically, reduced expression of MYC in the intestine promotes glucagon-like peptide-1 (GLP-1) production and secretion. Moreover, we identify Cers4, encoding ceramide synthase 4, catalysing de novo ceramide synthesis, as a MYC target gene. Finally, we show that administration of the MYC inhibitor 10058-F4 has beneficial effects on high-fat-diet-induced metabolic disorders, and is accompanied by increased GLP-1 and reduced ceramide levels in serum. This study positions intestinal MYC as a putative drug target against metabolic diseases, including non-alcoholic fatty liver disease and non-alcoholic steatohepatitis.

SCD Inhibition Protects from α-Synuclein-Induced Neurotoxicity But Is Toxic to Early Neuron Cultures.

Here, we report the independent discovery and validation of stearoyl-CoA desaturase (SCD) as a modulator of α-synuclein (αSyn)-induced pathology and toxicity in cell-based Parkinson’s disease (PD) models. We identified SCD as top altered gene from transcriptional profiling in primary neurons exogenously expressing αSyn with the amplified familial PD mutation 3K. Thus, we sought to further explore SCD as a therapeutic target in neurodegeneration. We report that SCD inhibitors are toxic to early human and rat neuron cultures while displaying minimal toxicity to late cultures. The fatty acid product of SCD, oleic acid (OLA), fully rescues this toxicity in early cultures, suggesting on-target toxicity. Furthermore, SCD inhibition rescues αSyn 3K-induced toxicity in late primary neurons. We also confirm that SCD inhibitors reduce formation of αSyn accumulations, while OLA increases these accumulations in an αSyn 3K neuroblastoma model. However, we identify a caveat with this model where αSyn 3K levels can be suppressed by high SCD inhibitor concentrations, obscuring true effect size. Further, we show that both SCD1 or SCD5 knock-down reduce αSyn 3K accumulations and toxicity, making both a putative drug target. Overall, we confirm key findings of published data on SCD inhibition and its benefits in αSyn accumulation and stress models. The differential neurotoxicity induced by SCD inhibition based on neuron culture age must be accounted for when researching SCD in neuron models and has potential clinical implications. Lastly, our gene profiling studies also revealed novel putative genes connected to αSyn neurotoxicity that are worth further study.

Balanced impacts of fitness and drug pressure on the evolution of PfMDR1 polymorphisms in Plasmodium falciparum

BackgroundAnti-malarial drug resistance may be limited by decreased fitness in resistant parasites. Important contributors to resistance are mutations in the Plasmodium falciparum putative drug transporter PfMDR1.MethodsImpacts on in vitro fitness of two common PfMDR1 polymorphisms, N86Y, which is associated with sensitivity to multiple drugs, and Y184F, which has no clear impact on drug sensitivity, were evaluated to study associations between resistance mediators and parasite fitness, measured as relative growth in competitive culture experiments. NF10 P. falciparum lines engineered to represent all PfMDR1 N86Y and Y184F haplotypes were co-cultured for 40 days, and the genetic make-up of the cultures was characterized every 4 days by pyrosequencing. The impacts of culture with anti-malarials on the growth of different haplotypes were also assessed. Lastly, the engineering of P. falciparum containing another common polymorphism, PfMDR1 D1246Y, was attempted.ResultsCo-culture results were as follows. With wild type (WT) Y184 fixed (N86/Y184 vs. 86Y/Y184), parasites WT and mutant at 86 were at equilibrium. With mutant 184 F fixed (N86/184F vs. 86Y/184F), mutants at 86 overgrew WT. With WT N86 fixed (N86/Y184 vs. N86/184F), WT at 184 overgrew mutants. With mutant 86Y fixed (86Y/Y184 vs. 86Y/184F), WT and mutant at 86 were at equilibrium. Parasites with the double WT were in equilibrium with the double mutant, but 86Y/Y184 overgrew N86/184F. Overall, WT N86/mutant 184F parasites were less fit than parasites with all other haplotypes. Parasites engineered for another mutation, PfMDR1 1246Y, were unstable in culture, with reversion to WT over time. Thus, the N86 WT is stable when accompanied by the Y184 WT, but incurs a fitness cost when accompanied by mutant 184F. Culturing in the presence of chloroquine favored 86Y mutant parasites and in the presence of lumefantrine favored N86 WT parasites; piperaquine had minimal impact.ConclusionsThese results are consistent with those for Ugandan field isolates, suggest reasons for varied haplotypes, and highlight the interplay between drug pressure and fitness that is guiding the evolution of resistance-mediating haplotypes in P. falciparum.

A diagnostic miRNA signature for pulmonary arterial hypertension using a consensus machine learning approach.

BackgroundPulmonary arterial hypertension (PAH) is a rare but life shortening disease, the diagnosis of which is often delayed, and requires an invasive right heart catheterisation. Identifying diagnostic biomarkers may improve screening to identify patients at risk of PAH earlier and provide new insights into disease pathogenesis. MicroRNAs are small, non-coding molecules of RNA, previously shown to be dysregulated in PAH, and contribute to the disease process in animal models.MethodsPlasma from 64 treatment naïve patients with PAH and 43 disease and healthy controls were profiled for microRNA expression by Agilent Microarray. Following quality control and normalisation, the cohort was split into training and validation sets. Four separate machine learning feature selection methods were applied to the training set, along with a univariate analysis.Findings20 microRNAs were identified as putative biomarkers by consensus feature selection from all four methods. Two microRNAs (miR-636 and miR-187-5p) were selected by all methods and used to predict PAH diagnosis with high accuracy. Integrating microRNA expression profiles with their associated target mRNA revealed 61 differentially expressed genes verified in two independent, publicly available PAH lung tissue data sets. Two of seven potentially novel gene targets were validated as differentially expressed in vitro in human pulmonary artery smooth muscle cells.InterpretationThis consensus of multiple machine learning approaches identified two miRNAs that were able to distinguish PAH from both disease and healthy controls. These circulating miRNA, and their target genes may provide insight into PAH pathogenesis and reveal novel regulators of disease and putative drug targets.

Identification and Validation of an 11-Ferroptosis Related Gene Signature and Its Correlation With Immune Checkpoint Molecules in Glioma.

BackgroundGlioma is the most common primary malignant brain tumor with significant mortality and morbidity. Ferroptosis, a novel form of programmed cell death (PCD), is critically involved in tumorigenesis, progression and metastatic processes.MethodsWe revealed the relationship between ferroptosis-related genes and glioma by analyzing the mRNA expression profiles from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), GSE16011, and the Repository of Molecular Brain Neoplasia Data (REMBRANDT) datasets. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct a ferroptosis-associated gene signature in the TCGA cohort. Glioma patients from the CGGA, GSE16011, and REMBRANDT cohorts were used to validate the efficacy of the signature. Receiver operating characteristic (ROC) curve analysis was applied to measure the predictive performance of the risk score for overall survival (OS). Univariate and multivariate Cox regression analyses of the 11-gene signature were performed to determine whether the ability of the prognostic signature in predicting OS was independent. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to identify the potential biological functions and pathways of the signature. Subsequently, we performed single sample gene set enrichment analysis (ssGSEA) to explore the correlation between risk scores and immune status. Finally, seven putative small molecule drugs were predicted by Connectivity Map.ResultsThe 11-gene signature was identified to divide patients into two risk groups. ROC curve analysis indicated the 11-gene signature as a potential diagnostic factor in glioma patients. Multivariate Cox regression analyses showed that the risk score was an independent predictive factor for overall survival. Functional analysis revealed that genes were enriched in iron-related molecular functions and immune-related biological processes. The results of ssGSEA indicated that the 11-gene signature was correlated with the initiation and progression of glioma. The small molecule drugs we selected showed significant potential to be used as putative drugs.Conclusionwe identified a novel ferroptosis-related gene signature for prognostic prediction in glioma patients and revealed the relationship between ferroptosis-related genes and immune checkpoint molecules.

Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium

Mycoplasma genitalium is an obligate intracellular bacterium that is responsible for several sexually transmitted infections, including non-gonococcal urethritis in men and several inflammatory reproductive tract syndromes in women. Here, we applied subtractive genomics and reverse vaccinology approaches for in silico prediction of potential vaccine and drug targets against five strains of M. genitalium. We identified 403 genes shared by all five strains, from which 104 non-host homologous proteins were selected, comprising of 44 exposed/secreted/membrane proteins and 60 cytoplasmic proteins. Based on the essentiality, functionality, and structure-based binding affinity, we finally predicted 19 (14 novel) putative vaccine and 7 (2 novel) candidate drug targets. The docking analysis showed six molecules from the ZINC database as promising drug candidates against the identified targets. Altogether, both vaccine candidates and drug targets identified here may contribute to the future development of therapeutic strategies to control the spread of M. genitalium worldwide.

Pulmonary Edema in COVID-19 Patients: Mechanisms and Treatment Potential.

COVID-19 mortality is primarily driven by abnormal alveolar fluid metabolism of the lung, leading to fluid accumulation in the alveolar airspace. This condition is generally referred to as pulmonary edema and is a direct consequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. There are multiple potential mechanisms leading to pulmonary edema in severe Coronavirus Disease (COVID-19) patients and understanding of those mechanisms may enable proper management of this condition. Here, we provide a perspective on abnormal lung humoral metabolism of pulmonary edema in COVID-19 patients, review the mechanisms by which pulmonary edema may be induced in COVID-19 patients, and propose putative drug targets that may be of use in treating COVID-19. Among the currently pursued therapeutic strategies against COVID-19, little attention has been paid to abnormal lung humoral metabolism. Perplexingly, successful balance of lung humoral metabolism may lead to the reduction of the number of COVID-19 death limiting the possibility of healthcare services with insufficient capacity to provide ventilator-assisted respiration.

MicroRNAs expression analysis shows key affirmation of Synaptopodin-2 as a novel prognostic and therapeutic biomarker for colorectal and cervical cancers

MicroRNAs play a crucial role in tumorigenesis, tumor progression, and metastasis, and thus they contribute in development of different malignancies including cervical cancer (CC) and colorectal cancer (CRC). Through integrated strategies of computational biology, this study aims to identify prognostic biomarkers responsible for CRC and CC prognosis, and potential therapeutic agents to halt the progression of these cancers. Expression analysis of miRNA datasets of CRC and CC identified 17 differentially expressed miRNAs (DEMs). SYNPO2, NEGR1, FGF7, LIFR, RUNX1T1, CFL2, BNC2, EPHB2, PMAIP1, and CDC25A differentially expressed genes (DEGs) regulated by these DEMs were classified as candidate genes responsible for CRC and CC. Down-regulation of Synaptopodin-2 (SYNPO2) is involved in emergence and progression of these cancers by activating ER, PI3K/AKT, and EMT pathways as well as by suppressing DNA damage response, and cell cycle pathways. Higher methylation rate in promoter region of SYNPO2 could be a possible reason for lowering the expression of SYNPO2 in tumor stages. Hence, the lower expression of SYNPO2 is associated with poor prognosis of CRC and CC and could function as prognostic biomarker and therapeutic target. Fourteen transcription factors were recognized which can activate/inhibit the transcription of SYNPO2 and may be a potential target to regulate expression of SYNPO2 in CRC and CC. Retinoic acid and Estradiol were identified as putative therapeutic drugs for CRC and CC patients. This study will thus help in understanding the underlying molecular events in CRC and CC that may improve the detection of malignant lesions in primary screening and will broaden the clinical applications.

Discovery of MK-8153, a Potent and Selective ROMK Inhibitor and Novel Diuretic/Natriuretic.

A renal outer medullary potassium channel (ROMK, Kir1.1) is a putative drug target for a novel class of diuretics with potential for treating hypertension and heart failure. Our first disclosed clinical ROMK compound, 2 (MK-7145), demonstrated robust diuresis, natriuresis, and blood pressure lowering in preclinical models, with reduced urinary potassium excretion compared to the standard of care diuretics. However, 2 projected to a short human half-life (∼5 h) that could necessitate more frequent than once a day dosing. In addition, a short half-life would confer a high peak-to-trough ratio which could evoke an excessive peak diuretic effect, a common liability associated with loop diuretics such as furosemide. This report describes the discovery of a new ROMK inhibitor 22e (MK-8153), with a longer projected human half-life (∼14 h), which should lead to a reduced peak-to-trough ratio, potentially extrapolating to more extended and better tolerated diuretic effects.

Screening of Mycobacterium tuberculosis genes as putative drug targets for treatment of HIV-TB and lung cancer-TB comorbidities: An in silico analysis

This study focuses on insilico analysis to understand the mechanism between tuberculosis (TB) associated comorbidities such as Human Immunodeficiency Virus (HIV) and lung cancer. Initially, gene expression studies of samples associated with HIV-TB and lung cancer-TB were analyzed and differentially expressed genes were identified. Further, gene networks for the up-regulated genes were constructed and the functionally associated genes were identified. Functional enrichment analysis was also performed for the genes associated. Differentially- regulated genes could be possible drug targets for treatment of TB associated comorbidities. In this regards, Rv2949c which was found to be highly expressed in HIV patients with TB and it could be a candidate drug target for treatment of patients with HIV comorbidity. Similarly, pgsA1 is highly expressed in lung cancer patients with TB, is a candidate drug target for treatment of patients with lung cancer comorbidity. Suitable inhibitors for Rv2949c and pgsA1 have been found through molecular docking studies. Thus the insights gained through this study will be helpful in designing suitable drug candidates for treatment of TB related comorbidities.

Pharmacovigilance-based drug repurposing: The search for inverse signals via OpenVigil identifies putative drugs against viral respiratory infections.

AimsPharmacovigilance data are primarily used to identify adverse drug reactions by screening for disproportionate reporting, i.e. more reports of certain combinations of adverse events and drugs than expected. However, scanning for associations of drugs and adverse events that occur less frequently than expected provides hypotheses for drug repurposing, i.e. a known drug could be therapeutically beneficial for a new indication such as the coronavirus disease (COVID‐19). As coronavirus‐related adverse events are scarce in pharmacovigilance data prior to 2020, we searched for drugs suitable against similar viral diseases.MethodsIn this observational, retrospective, pharmacovigilance study, drugs associated with viral respiratory tract infections and/or diseases caused by RNA‐viruses, which are phylogenetically similar to SARS‐CoV‐2, were extracted from the US FAERS pharmacovigilance data 2004Q1 to 2020Q2 using OpenVigil 2.1‐MedDRA17, filtered for significant inverse associations (reporting odds ratio <1 and adjusted P < .05), checked for implausibility (e.g. only topically) or clinical infeasibility (e.g. strong cytotoxic effects), and categorised by their World Health Organization Anatomical Therapeutic Chemical classification code.ResultsA total of 126 drugs were identified. Anatomical Therapeutic Chemical clustering of the manually curated list of 112 candidate drugs revealed female sex hormones, antidiabetics, neuropharmacological sigma‐receptor modulators, peptidase inhibitors, antiviral drugs, nicotinic acetylcholine receptor agonists and tyrosine kinase inhibitors as putatively antiviral.ConclusionScanning for inverse signals in pharmacovigilance data provides new hypotheses for drug repurposing, theoretically for all indications. Concerning the treatment of viral respiratory infections, there are affirmative data for some candidate drugs; the remaining proposed candidate drugs without already known antiviral mechanism of action should stimulate further exploration.

Computational Approaches to Discover Novel Natural Compounds for SARS-CoV-2 Therapeutics.

Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID‐19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug‐like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS‐CoV‐2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug‐like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N‐71493 and STOCK1N‐45683 as SARS‐CoV‐2 treatment regime.

A molecular single-cell lung atlas of lethal COVID-19.

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection1,2, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1β and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1+ pathological fibroblasts3 contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand-receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development.