Apremilast Add-On Benefits Over Conventional Drugs (ABCD) in Unstable Non-segmental Vitiligo: A 12-Week Single-Center Randomized Controlled Trial.

Background Apremilast is an oral phosphodiesterase-4 enzyme inhibitor that modulates the immune system by increasing intracellular cyclic adenosine monophosphate levels and inhibiting inflammatory cytokines synthesis. We aimed to compare the efficacy and safety of add-on apremilast in combination therapy with standard treatment in patients with unstable, non-segmental vitiligo. Methods The study was a 12-week randomized, controlled, parallel-group, open-labeled trial. The control group received standard treatment (n=15), and the intervention group received 30 mg apremilast twice daily in addition to standard treatment (n= 16). Time to the first sign of re-pigmentation, halt in progression, and change in vitiligo area scoring index (VASI) score is the primary outcomes. Normality was assessed, and appropriate parametric and nonparametric tests were undertaken. Results Thirty-seven participants were randomized into two groups, and analysis was done on thirty-one participants. Over the treatment duration of 12 weeks, the median time to observe the first sign of re-pigmentation was four weeks in the add-on apremilast group compared to seven weeks in the control group (p=0.018). The halt in progression was observed more in the add-on Apremilast group (93.75%) compared to the control group (66.66%) (p=0.08). The VASI score decreased by 1.24 in the add-on apremilast group and 0.05 in the control group (p= 0.754). Parameters including body surface area, dermatology life quality index, and body mass index reduced significantly, while the visual analog scale increased significantly in the add-on apremilast group. However, results were comparable between groups. Conclusions Treatment with add-on apremilast accelerated clinical improvement. It also reduced disease progression and improved the disease index among participants. However, add-on apremilast had a lower tolerability profile than the control group.

Computational study of novel inhibitory molecule, 1-(4-((2S,3S)-3-amino-2-hydroxy-4-phenylbutyl)piperazin-1-yl)-3-phenylurea, with high potential to competitively block ATP binding to the RNA dependent RNA polymerase of SARS-CoV-2 virus.

For coronaviruses, RNA-dependent RNA polymerase (RdRp) is an essential enzyme that catalyses the replication from RNA template and therefore remains an attractive therapeutic target for anti-COVID drug discovery. In the present study, we performed a comprehensive in silico screening for 16,776 potential molecules from recently established drug libraries based on two important pharmacophores (3-amino-4-phenylbutan-2-ol and piperazine). Based on initial assessment, 4042 molecules were obtained suitable as drug candidates, which were following Lipinski's rule. Molecular docking implemented for the analysis of molecular interactions narrowed this number of compounds down to 19. Subsequent to screening filtering criteria and considering the critical parameters viz. docking score and MM-GBSA binding free energy, 1-(4-((2S,3S)-3-amino-2-hydroxy-4-phenylbutyl)piperazin-1-yl)-3-phenylurea (compound 1) was accomplished to score highest in comparison to the remaining 18 shortlisted drug candidates. Notably, compound 1 displayed higher docking score (-8.069 kcal/mol) and MM-GBSA binding free energy (-49.56 kcal/mol) than the control drug, remdesivir triphosphate, the active form of remdesivir as well as adenosine triphosphate. Furthermore, a molecular dynamics simulation was carried out (100 ns), which substantiated the candidacy of compound 1 as better inhibitor. Overall, our systematic in silico study predicts the potential of compound 1 to exhibit a more favourable specific activity than remdesivir triphosphate. Hence, we suggest compound 1 as a novel potential drug candidate, which should be considered for further exploration and validation of its potential against SARS-CoV-2 in wet lab experimental studies.Communicated by Ramasawamy H. Sarma.

Computational methods directed towards drug repurposing for COVID-19: advantages and limitations.

Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent for COVID-19, it continues to transmit and newer variants of concern have been consistently emerging world-wide. Computational strategies involving drug repurposing offer a viable opportunity to choose a medication from a rundown of affirmed drugs against distinct diseases including COVID-19. While pandemics impede the healthcare systems, drug repurposing or repositioning represents a hopeful approach in which existing drugs can be remodeled and employed to treat newer diseases. In this review, we summarize the diverse computational approaches attempted for developing drugs through drug repurposing or repositioning against COVID-19 and discuss their advantages and limitations. To this end, we have outlined studies that utilized computational techniques such as molecular docking, molecular dynamic simulation, disease-disease association, drug-drug interaction, integrated biological network, artificial intelligence, machine learning and network medicine to accelerate creation of smart and safe drugs against COVID-19.

Multi-targeting approach for nsp3, nsp9, nsp12 and nsp15 proteins of SARS-CoV-2 by Diosmin as illustrated by molecular docking and molecular dynamics simulation methodologies.

Novel coronavirus SARS-CoV-2continues tospread rapidly worldwide and causing serious health and economic loss. In the absence of any effective treatment, various in-silico approaches are being explored towards the therapeutic discovery against COVID-19. Targeting multiple key enzymes of SARS-CoV-2 with a single potential drug could be an important in-silico strategy to tackle the therapeutic emergency. A number of Food and Drug Administration (FDA) approved drugs entered into clinical stages were originated from multi-target approaches with an increased rate, 16-21% between 2015 and 2017. In this study, we selected an FDA-approved library (Prestwick Chemical Library of 1520 compounds) and implemented in-silico virtual screening against multiple protein targets of SARS-CoV-2 on the Glide module of Schrödinger software (release 2020-1). Compounds were analyzed for their docking scores and the top-ranked against each targeted protein were further subjected to Molecular Dynamics (MD) simulations to assess the binding stability of ligand-protein complexes. A multi-targeting approach was optimized that enabled the analysis of several compounds' binding efficiency with more than one protein targets. It was demonstrated that Diosmin (6) showed the highest binding affinity towards multiple targets with binding free energy (kcal/mol) values of -63.39 (nsp3); -62.89 (nsp9); -31.23 (nsp12); and -65.58 (nsp15). Therefore, our results suggests that Diosmin (6) possesses multi-targeting capability, a potent inhibitor of various non-structural proteins of SARS-CoV-2, and thus it deserves further validation experiments before using as a therapeutic against COVID-19 disease.

Viral Ribonucleic Acid Shedding and Transmission Potential of Asymptomatic and Paucisymptomatic Coronavirus Disease 2019 Patients.

We studied the pattern and duration of viral ribonucleic acid (RNA) shedding in 32 asymptomatic and 11 paucisymptomatic coronavirus disease 2019 cases. Viral RNA shedding in exhaled breath progressively diminished and became negative after 6 days of a positive reverse-transcription polymerase chain reaction test. Therefore, the duration of isolation can be minimized to 6 days.

Tobacco, alcohol use and other risk factors for developing symptomatic COVID-19 vs asymptomatic SARS-CoV-2 infection: a case-control study from western Rajasthan, India.

BACKGROUND: Understanding risk factors of symptomatic coronavirus disease 2019 (COVID-19) vis-à-vis asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, severe disease and death is important. METHODS: An unmatched case-control study was conducted through telephonic interviews among individuals who tested positive for SARS-CoV-2 in Jodhpur, India from 23 March to 20 July 2020. Contact history, comorbidities and tobacco and alcohol use were elicited using standard tools. RESULTS: Among 911 SARS-CoV-2-infected individuals, 47.5% were symptomatic, 14.1% had severe COVID-19 and 41 (4.5%) died. Older age, working outside the home, cardiac and respiratory comorbidity and alcohol use were found to increase the risk of symptomatic disease as compared with asymptomatic infection. Current tobacco smoking (odds ratio [OR] 0.46 [95% confidence interval {CI} 0.26 to 0.78]) but not smokeless tobacco use (OR 0.81 [95% CI 0.55 to 1.19]) appeared to reduce the risk of symptomatic disease. Age ≥60 y and renal comorbidity were significantly associated with severe COVID-19. Age ≥60 y and respiratory and cardiac comorbidity were found to predispose to mortality. CONCLUSIONS: The apparent reduced risk of symptomatic COVID-19 among tobacco smokers could be due to residual confounding owing to unknown factors, while acknowledging the limitation of recall bias. Cross-protection afforded by frequent upper respiratory tract infection among tobacco smokers could explain why a similar association was not found for smokeless tobacco use, thereby being more plausible than the 'nicotinic hypothesis'. Those with comorbidities and age ≥60 y should be prioritized for hospital admission.

Structure-based drug repurposing for targeting Nsp9 replicase and spike proteins of severe acute respiratory syndrome coronavirus 2.

Drug re-purposing might be a fast and efficient way of drug development against the novel coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We applied a bioinformatics approach using molecular dynamics and docking to identify FDA-approved drugs that can be re-purposed to potentially inhibit the non-structural protein 9 (Nsp9) replicase and spike proteins in SARS-CoV-2. We performed virtual screening of FDA-approved compounds, including antiviral, anti-malarial, anti-parasitic, anti-fungal, anti-tuberculosis, and active phytochemicals against the Nsp9 replicase and spike proteins. Selected hit compounds were identified based on their highest binding energy and favorable absorption, distribution, metabolism and excretion (ADME) profile. Conivaptan, an arginine vasopressin antagonist drug exhibited the highest binding energy (-8.4 Kcal/mol) and maximum stability with the amino acid residues present at the active site of the Nsp9 replicase. Tegobuvir, a non-nucleoside inhibitor of the hepatitis C virus, also exhibited maximum stability along with the highest binding energy (-8.1 Kcal/mol) at the active site of the spike proteins. Molecular docking scores were further validated by molecular dynamics using Schrodinger, which supported the strong stability of ligands with the proteins at their active sites through water bridges, hydrophobic interactions, and H-bonding. Our findings suggest Conivaptan and Tegobuvir as potential therapeutic agents against SARS-CoV-2. Further in vitro and in vivo validation and evaluation are warranted to establish how these drug compounds target the Nsp9 replicase and spike proteins.

Discovery of New Hydroxyethylamine Analogs against 3CLpro Protein Target of SARS-CoV-2: Molecular Docking, Molecular Dynamics Simulation, and Structure-Activity Relationship Studies.

The novel coronavirus, SARS-CoV-2, has caused a recent pandemic called COVID-19 and a severe health threat around the world. In the current situation, the virus is rapidly spreading worldwide, and the discovery of a vaccine and potential therapeutics are critically essential. The crystal structure for the main protease (Mpro) of SARS-CoV-2, 3-chymotrypsin-like cysteine protease (3CLpro), was recently made available and is considerably similar to the previously reported SARS-CoV. Due to its essentiality in viral replication, it represents a potential drug target. Herein, a computer-aided drug design (CADD) approach was implemented for the initial screening of 13 approved antiviral drugs. Molecular docking of 13 antivirals against the 3-chymotrypsin-like cysteine protease (3CLpro) enzyme was accomplished, and indinavir was described as a lead drug with a docking score of -8.824 and a XP Gscore of -9.466 kcal/mol. Indinavir possesses an important pharmacophore, hydroxyethylamine (HEA), and thus, a new library of HEA compounds (>2500) was subjected to virtual screening that led to 25 hits with a docking score more than indinavir. Exclusively, compound 16 with a docking score of -8.955 adhered to drug-like parameters, and the structure-activity relationship (SAR) analysis was demonstrated to highlight the importance of chemical scaffolds therein. Molecular dynamics (MD) simulation analysis performed at 100 ns supported the stability of 16 within the binding pocket. Largely, our results supported that this novel compound 16 binds with domains I and II, and the domain II-III linker of the 3CLpro protein, suggesting its suitability as a strong candidate for therapeutic discovery against COVID-19.