Deep learning in drug discovery: a futuristic modality to materialize the large datasets for cheminformatics.

Artificial intelligence (AI) development imitates the workings of the human brain to comprehend modern problems. The traditional approaches such as high throughput screening (HTS) and combinatorial chemistry are lengthy and expensive to the pharmaceutical industry as they can only handle a smaller dataset. Deep learning (DL) is a sophisticated AI method that uses a thorough comprehension of particular systems. The pharmaceutical industry is now adopting DL techniques to enhance the research and development process. Multi-oriented algorithms play a crucial role in the processing of QSAR analysis, de novo drug design, ADME evaluation, physicochemical analysis, preclinical development, followed by clinical trial data precision. In this study, we investigated the performance of several algorithms, including deep neural networks (DNN), convolutional neural networks (CNN) and multi-task learning (MTL), with the aim of generating high-quality, interpretable big and diverse databases for drug design and development. Studies have demonstrated that CNN, recurrent neural network and deep belief network are compatible, accurate and effective for the molecular description of pharmacodynamic properties. In Covid-19, existing pharmacological compounds has also been repurposed using DL models. In the absence of the Covid-19 vaccine, remdesivir and oseltamivir have been widely employed to treat severe SARS-CoV-2 infections. In conclusion, the results indicate the potential benefits of employing the DL strategies in the drug discovery process.Communicated by Ramaswamy H. Sarma.

Therapeutic Uses of Traditional Chinese Medicines Against COVID-19.

COVID-19 is a pandemic and a serious respiratory disorder that is caused by coronavirus. It has produced an outbreak of acute infectious pneumonia in China and afterward all around the world. There is not a single anti-viral drug, vaccine or any kind of treatment available for this fatal disease. There are only a few options available for symptomatic relief. Thus, in China, 85% of SARS-CoV-2 infected individuals have been treated with traditional Chinese medicines (TCM). Thus, this article focused on the previous kinds of literature regarding COVID-19 and its treatment with TCM along with its applications. SARS-CoV-2 and SARS-CoV showed similarity in genes, pathological processes, and epidemiology, so these can be treated with TCM. The proof regarding treatment of SARS-CoV with TCM explicitly shows the advantages of using TCM therapy for COVID-19. Present literature explains the mode of action and efficacy of TCM and elaborates on the natural compounds introduced to treat COVID-19.