Application of computational methods in genetic study of inflammatory bowel disease

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.

Association of Variant Interactions in RANK, RANKL, OPG, TRAF6, and NFATC1 Genes with the Development of Osteonecrosis of the Femoral Head

Multiple gene polymorphisms have been demonstrated to correlate with the susceptibility to osteonecrosis of the femoral head (ONFH). However, as a complex disease induced by multiple genes, the development of ONFH has rarely been reported to involve in gene interaction. In this study, we first explored the association of 10 variants interactions in receptor activator of nuclear factor-kappa B (RANK), RANK ligand (RANKL), osteoprotegerin (OPG), tumor necrosis factor receptor-associated factor 6 (TRAF6), and nuclear factor of activated T cells cytoplasmic 1 (NFATC1) genes with the development and clinical phenotypes of ONFH in a 377 ONFH case-control study with using Mass ARRAY^® platform. Our results showed that not only a total of 6 interactional variants in the paired 10 variants interactions were significantly associated with the development of ONFH (OPG rs2073617 and NFATC1 rs754093, p < 0.019; OPG rs2073618 and NFATC1 rs754093, p < 0.008; OPG rs2073617 and RANKL rs1054016, p < 0.039, respectively) but also a total of 4 paired interactional variants were found to involve significantly in the increased risk of bilateral hip lesions in ONFH (OPG rs2073617 and TRAF6 rs5030411, p = 0.044; RANK rs884205 and TRAF6 rs5030411, p = 0.045, respectively). Moreover, the results from generalized multifactor dimensionality reduction also showed that the five best models were identified and associated significantly with ONFH risk, p = 0.001, 0.01, 0.01, 0.01, and 0.01, respectively. Our results first suggest that the variants in RANK/RANKL/OPG pathway genes affected the development of ONFH in gene interaction manner through the interaction of the paired variants and multiple variants.