AIMC Topic: COVID-19 Drug Treatment

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Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review.

Current topics in medicinal chemistry
BACKGROUND: SARS-CoV-2, the unique coronavirus that causes COVID-19, has wreaked damage around the globe, with victims displaying a wide range of difficulties that have encouraged medical professionals to look for innovative technical solutions and t...

[Literacy for Appropriate Use of Medical Big Data and Artificial Intelligence].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Recent developments have enabled daily accumulated medical information to be converted into medical big data, and new evidence is expected to be created using databases and various open data sources. Database research using medical big data was activ...

D3AI-CoV: a deep learning platform for predicting drug targets and for virtual screening against COVID-19.

Briefings in bioinformatics
Target prediction and virtual screening are two powerful tools of computer-aided drug design. Target identification is of great significance for hit discovery, lead optimization, drug repurposing and elucidation of the mechanism. Virtual screening ca...

Potential SARS-CoV-2 nonstructural proteins inhibitors: drugs repurposing with drug-target networks and deep learning.

Frontiers in bioscience (Landmark edition)
BACKGROUND: In the current COVID-19 pandemic, with an absence of approved drugs and widely accessible vaccines, repurposing existing drugs is vital to quickly developing a treatment for the disease.

Active disease-related compound identification based on capsule network.

Briefings in bioinformatics
Pneumonia, especially corona virus disease 2019 (COVID-19), can lead to serious acute lung injury, acute respiratory distress syndrome, multiple organ failure and even death. Thus it is an urgent task for developing high-efficiency, low-toxicity and ...

A deep learning method for repurposing antiviral drugs against new viruses via multi-view nonnegative matrix factorization and its application to SARS-CoV-2.

Briefings in bioinformatics
The outbreak of COVID-19 caused by SARS-coronavirus (CoV)-2 has made millions of deaths since 2019. Although a variety of computational methods have been proposed to repurpose drugs for treating SARS-CoV-2 infections, it is still a challenging task f...

Computational anti-COVID-19 drug design: progress and challenges.

Briefings in bioinformatics
Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the developmen...

Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions.

Briefings in bioinformatics
New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. H...

Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.

Briefings in bioinformatics
Coronavirus disease 2019 (COVID-19) has impacted public health as well as societal and economic well-being. In the last two decades, various prediction algorithms and tools have been developed for predicting antiviral peptides (AVPs). The current COV...

A Hybrid Protocol for Identifying Comorbidity-Based Potential Drugs for COVID-19 Using Biomedical Literature Mining, Network Analysis, and Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has spread on an unprecedented scale around the globe. Despite of 141,975 published papers on COVID-19 and several hundreds of new studies carri...