Combined deep learning and molecular docking simulations approach identifies potentially effective FDA approved drugs for repurposing against SARS-CoV-2.

The ongoing pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health. Drug repurposing is a time-efficient approach to finding effective drugs against SARS-CoV-2 in this emergency. Here, we present a robust experimental design combining deep learning with molecular docking experiments to identify the most promising candidates from the list of FDA-approved drugs that can be repurposed to treat COVID-19. We have employed a deep learning-based Drug Target Interaction (DTI) model, called DeepDTA, with few improvements to predict drug-protein binding affinities, represented as KIBA scores, for 2440 FDA-approved and 8168 investigational drugs against 24 SARS-CoV-2 viral proteins. FDA-approved drugs with the highest KIBA scores were selected for molecular docking simulations. We ran around 50,000 docking simulations for 168 selected drugs against 285 total predicted and/or experimentally proven active sites of all 24 SARS-CoV-2 viral proteins. A list of 49 most promising FDA-approved drugs with the best consensus KIBA scores and binding affinity values against selected SARS-CoV-2 viral proteins was generated. Most importantly, 16 drugs including anidulafungin, velpatasvir, glecaprevir, rifapentine, flavin adenine dinucleotide (FAD), terlipressin, and selinexor demonstrated the highest predicted inhibitory potential against key SARS-CoV-2 viral proteins. We further measured the inhibitory activity of 5 compounds (rifapentine, velpatasvir, glecaprevir, anidulafungin, and FAD disodium) on SARS-CoV-2 PLpro using Ubiquitin-Rhodamine 110 Gly fluorescent intensity assay. The highest inhibition of PLpro activity was seen with rifapentine (IC50: 15.18 µM) and FAD disodium (IC50: 12.39 µM), the drugs with high predicted KIBA scores and binding affinities.

Public awareness and preparedness towards Covid-19 pandemic in Pakistan

Objective: To examine the level of public awareness towards the coronavirus pandemic and knowledge about its preparedness. Methodology: In this cross-sectional study, a self-administrated online questionnaire was circulated through emails and social media. The questionnaire comprised of close ended questions regarding assessing awareness about the causes and symptoms of COVID-19 and knowledge about preventative measures required to be taken at individual and state level. A total of 350 participants responded to the survey in the given time period of six days from 13th to 19th March 2020. The participants belonged to all provinces of Pakistan including Azad Jammu Kashmir and Islamabad. Results: Public was aware of the COVID-19 epidemiological breakout, its causes, symptoms, modes of transmission and preparedness mechanism. The correlation matrix also depicted that public awareness about the danger of COVID-19 were significantly correlated with the preparedness at the individual and state levels. Conclusion: The general public was well aware of the COVID-19 epidemiological breakout, its causes, symptoms, modes of transmission and preparedness mechanism.