Modern drug discovery for inflammatory bowel disease: The role of computational methods.

Inflammatory bowel diseases (IBDs) comprising ulcerative colitis, Crohn's disease and microscopic colitis are characterized by chronic inflammation of the gastrointestinal tract. IBD has spread around the world and is becoming more prevalent at an alarming rate in developing countries whose societies have become more westernized. Cell therapy, intestinal microecology, apheresis therapy, exosome therapy and small molecules are emerging therapeutic options for IBD. Currently, it is thought that low-molecular-mass substances with good oral bio-availability and the ability to permeate the cell membrane to regulate the action of elements of the inflammatory signaling pathway are effective therapeutic options for the treatment of IBD. Several small molecule inhibitors are being developed as a promising alternative for IBD therapy. The use of highly efficient and time-saving techniques, such as computational methods, is still a viable option for the development of these small molecule drugs. The computer-aided (in silico) discovery approach is one drug development technique that has mostly proven efficacy. Computational approaches when combined with traditional drug development methodology dramatically boost the likelihood of drug discovery in a sustainable and cost-effective manner. This review focuses on the modern drug discovery approaches for the design of novel IBD drugs with an emphasis on the role of computational methods. Some computational approaches to IBD genomic studies, target identification, and virtual screening for the discovery of new drugs and in the repurposing of existing drugs are discussed.

A Computational Approach to Elucidate the Interactions of Chemicals From Artemisia annua Targeted Toward SARS-CoV-2 Main Protease Inhibition for COVID-19 Treatment.

The inhibitory potential of Artemisia annua, a well-known antimalarial herb, against several viruses, including the coronavirus, is increasingly gaining recognition. The plant extract has shown significant activity against both the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and the novel SARS-CoV-2 that is currently ravaging the world. It is therefore necessary to evaluate individual chemicals of the plant for inhibitory potential against SARS-CoV-2 for the purpose of designing drugs for the treatment of COVID-19. In this study, we employed computational techniques comprising molecular docking, binding free energy calculations, pharmacophore modeling, induced-fit docking, molecular dynamics simulation, and ADMET predictions to identify potential inhibitors of the SARS-CoV-2 main protease (Mpro) from 168 bioactive compounds of Artemisia annua. Rhamnocitrin, isokaempferide, kaempferol, quercimeritrin, apigenin, penduletin, isoquercitrin, astragalin, luteolin-7-glucoside, and isorhamnetin were ranked the highest, with docking scores ranging from -7.84 to -7.15 kcal/mol compared with the -6.59 kcal/mol demonstrated by the standard ligand. Rhamnocitrin, Isokaempferide, and kaempferol, like the standard ligand, interacted with important active site amino acid residues like HIS 41, CYS 145, ASN 142, and GLU 166, among others. Rhamnocitrin demonstrated good stability in the active site of the protein as there were no significant conformational changes during the simulation process. These compounds also possess acceptable druglike properties and a good safety profile. Hence, they could be considered for experimental studies and further development of drugs against COVID-19.