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

Ton, Anh-Tien; Gentile, Francesco; Hsing, Michael; Ban, Fuqiang; Cherkasov, Artem

doi:10.26434/chemrxiv.11860077.v1

Cited by 11 publications

(1 citation statement)

References 21 publications

(26 reference statements)

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“…To fight against COVID-19 and promote the prevention and control of the epidemic, researchers have recently made efforts in various aspects; their research involves epidemiological research 5,6,7 , diagnostic methods of the novel coronavirus 8,9,10,11 , clinical characteristics of the disease 12,13,14,15,16 , characteristics of disease transmission 17,18,19 , development of candidate therapies 20,21,22 , the identification of animal hosts 23,24,25,26 , etc. However, there has been no research conducted on the public's attention to COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Chinese Public Attention to COVID-19 Epidemic: Based on Social Media

Zhao

2020

Preprint

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Background:Since the new coronavirus epidemic in China in December 2019, information and discussions about COVID-19 have spread rapidly on the Internet and have quickly become the focus of worldwide attention, especially on social media. and described the trend of public attention on COVID-19 epidemic-related topics. ROST CM6.0 (ROST Content Mining System Version 6.0) was used to analyze the collected text for word segmentation, word frequency, and sentiment analysis. We further described the hot topic keywords and sentiment trends of public attention. We used VOSviewer to implement a visual cluster analysis of hot keywords and build a social network of public opinion content. Results:The study has four main findings. First, we analyzed the changing trend of the public's attention to the COVID-19 epidemic, which can be divided into three stages. Second, the hot topic keywords of public attention at each stage are : medRxiv preprint slightly different. In addition, the emotional tendency of the public toward the COVID-19 epidemic-related hot topics has changed from negative to neutral, with negative emotions weakening and positive emotions increasing as a whole. Finally, we divided the COVID-19 topics with the most public concern into five categories:(1) new COVID-19 epidemics and their impact; (2) frontline reporting of the epidemic and prevention and control measures; (3) expert interpretation and discussion on the source of infection; (4) medical services on the frontline of the epidemic; and (5) focus on the global epidemic and the search for suspected cases.Conclusions: This is the first study of public attention on the COVID-19 epidemic using a Chinese social media platform (i.e., Sina Microblog). Our study found that social media (e.g., Sina Microblog) can be used to measure public attention to public health emergencies. During the epidemic of the novel coronavirus, a large amount of information about the COVID-19 epidemic was disseminated on Sina Microblog and received widespread public attention. We have learned about the hotspots of public concern regarding the COVID-19 epidemic. These findings can help the government and health departments better communicate with the public on health and translate public health needs into practice to create targeted measures to prevent and control the spread of COVID-19.

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Section: Introductionmentioning

confidence: 99%

Chinese Public Attention to COVID-19 Epidemic: Based on Social Media

Zhao

2020

Preprint

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Computational Modeling in Virus Infections and Virtual Screening, Docking, and Molecular Dynamics in Drug Design

Simões

Ferreira

Paula

et al. 2020

Networks in Systems Biology

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Computer modeling is an area of broad multidisciplinary knowledge that includes the study of various biological systems. This chapter will describe the molecular aspects of viral infections and molecular modeling techniques applied to drug discovery with examples of applications in protein activity inhibition in several pathologies. The first part will cover topics of computational chemistry methods, DNA technologies, structural modeling of virus proteins, molecular biology, viral vectors, virus-like particles, and pharmaceutical bioprocess with application in some specific viruses such as papillomavirus, hepatitis B virus, hepatitis C virus, Coronavirus, and Zika Virus. The second part will deal with methods in Virtual Screening for the drug design based on ligands and on the structure of target macromolecules. Molecular docking in drug design, its search algorithms, and scoring functions will be covered in the third part. Finally, a protocol of the Molecular Dynamics technique for studies of protein-ligand complexes and analysis of free energy of binding will be exposed in the last part.

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