Computational approaches for drug discovery against COVID-19

Coronavirus disease 2019 (COVID-19) has caused widespread diseases and deaths, along with the most severe social and economic disruption worldwide. Therefore, to discover potential drug candidates against COVID-19, many researchers have found various types of molecular targets and vaccine development and also explored new bioactive compounds. Although multiple vaccines have been investigated and tested, the frequent mutation in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a matter of concern. In response to this devastating pandemic, a massive experimental and computational research effort has emerged to understand the disease and rapidly develop diagnostics, vaccines, and drugs. In this regard, more than 130,000 COVID-19-related research articles have been published in peer-reviewed journals. Much of the research has focused on the in silico identification of novel therapeutic candidates and the repurposing of existing drugs against COVID-19. In terms of time, the computational approaches offer the best chance to speed up the long and costly process of drug and vaccine development for a life-threatening condition such as COVID-19. Hence, researchers have given many novel drug candidates against COVID-19 by using computational techniques. In this chapter, we have described the essential computational methods and their applications that were used for COVID-19 drug discovery. This chapter provides an investigation of fundamentals, the process of the target identification, drug design, optimization, and production of the medicine for COVID-19 based on the in silico aspects of signature matching, genomics analysis, proteomics, pathogenesis, phylogenetic analysis, viral receptor binding analysis, protein-protein interaction, artificial intelligence and machine learning, drug repurposing, and deep learning (DL) methods. © 2023 Elsevier Inc. All rights reserved.

A bioinformatic approach to identify core genome difference between Salmonella Pullorum and Salmonella Enteritidis In silico screening of natural compounds against COVID-19 by targeting Mpro and ACE2 using molecular docking

S. Pullorum and S. Enteritidis are closely related in genetic terms, but they show very different pathogenicity and host range. S. Enteritidis infects many different hosts, usually causing acute gastroenteritis, while S. Pullorum is restricted to avian, where it causes systemic disease in young animals. The reason why they differ in host range and pathogenicity is unknown. The core-genome denotes those genes that are present in all strains within a clade, and in the present work, an automated bioinformatics workflow was developed and applied to identify core-genome differences between these two serovars with the aim to identify genome features associated with host specificity of S. Pullorum. Results showed that S. Pullorum unique coding sequences (CDS) were mainly concentrated in three regions not present in S. Enteritidis, suggesting that such CDS were taken up probably during the separation of the two types from their common ancestor. One of the unique regions encoded Pathogenicity Islands 19 (SPI-19), which encodes a type VI secretion system (T6SS). Single-nucleotide polymorphism (SNP) analysis identified 1791 conserved SNPs in coding sequences between the two serovars, including several SNPs located in a type IV secretion system (T4SS). Analyzing of 100 bp regions upstream of coding sequences identified 443 conserved SNPs between the two serovars, including SNP variations in type III secretion system effector (T3SE). In conclusion, this analysis has identified genetic features encoding putative factors controlling host-specificity in S. Pullorum. The novel bioinformatic workflow and associated scripts can directly be applied to other bacteria to uncover the genome difference between clades. OBJECTIVE: Currently, Coronavirus COVID-19 is spreading worldwide very rapidly and its control is very difficult because there is no effective vaccine or drugs available in markets. This virus can infect both animals and people and cause illnesses of the respiratory tract. WHO has declared Coronavirus as pandemic and the whole world is fighting against Coronavirus. Globally, more than 199,478 people have been diagnosed with COVID-19. As of March 18, 2020, more than 167 countries have been affected and more than 8000 deaths have been reported. The main country being affected is China followed by Italy, Iran, Spain, France, and the USA. MATERIALS AND METHODS: Since there are no effective drugs available against Coronavirus, we conducted virtual screening of phytochemicals to find novel compounds against this virus. Hence, we created a phytochemical library of 318 phytochemicals from 11 plants which have been reported as antiviral, antibacterial and antifungal activity. The phytochemical library was subjected to virtual screening against molecular targets;Main protease (Mpro) and Angiotensin-Converting Enzyme 2 (ACE2). RESULTS: Top 10 compounds were selected from each target which had better and significantly low binding energy as compared to the reference molecule. CONCLUSIONS: Based on the binding energy score, we suggest that these compounds can be tested against Coronavirus and used to develop effective antiviral drugs.

In silico screening of natural compounds against COVID-19 by targeting Mpro and ACE2 using molecular docking.

OBJECTIVE: Currently, Coronavirus COVID-19 is spreading worldwide very rapidly and its control is very difficult because there is no effective vaccine or drugs available in markets. This virus can infect both animals and people and cause illnesses of the respiratory tract. WHO has declared Coronavirus as pandemic and the whole world is fighting against Coronavirus. Globally, more than 199,478 people have been diagnosed with COVID-19. As of March 18, 2020, more than 167 countries have been affected and more than 8000 deaths have been reported. The main country being affected is China followed by Italy, Iran, Spain, France, and the USA. MATERIALS AND METHODS: Since there are no effective drugs available against Coronavirus, we conducted virtual screening of phytochemicals to find novel compounds against this virus. Hence, we created a phytochemical library of 318 phytochemicals from 11 plants which have been reported as antiviral, antibacterial and antifungal activity. The phytochemical library was subjected to virtual screening against molecular targets; Main protease (Mpro) and Angiotensin-Converting Enzyme 2 (ACE2). RESULTS: Top 10 compounds were selected from each target which had better and significantly low binding energy as compared to the reference molecule. CONCLUSIONS: Based on the binding energy score, we suggest that these compounds can be tested against Coronavirus and used to develop effective antiviral drugs.