A Simple Computational Approach to Identify Potential Drugs for Multiple Sclerosis and Cognitive Disorders from Expert Curated Resources.

Multiple sclerosis, a disease of central nervous system leads to potential disability. In the USA, one million cases are diagnosed with multiple sclerosis in 2019. Multiple sclerosis is identified as one of the diseases causing global burden. Cognitive disorder is highly prevalent among 43-70% of multiple sclerosis patients. However, treating cognitive disorder in multiple sclerosis patients is mostly ignored and this leads to several complications. We utilized various expert curated resources to identify potential drugs for multiple sclerosis and cognitive disorder, with specific focus on identifying drugs that are capable of treating both the conditions. We used simple text mining techniques to compile two databases, disease-drug association database and gene-drug interaction database from various existing standard resources. Our study suggests four drugs, Baclofen, Levodopa, Minocycline, and Vitamin B12, for treating both multiple sclerosis and cognitive disorder. In addition, our approach suggests six drugs for multiple sclerosis and 10 drugs for cognitive disorder. We obtained pharmacologist opinion on the drugs suggested for each condition and provided literature evidence for our claim. Here, we present our computational approach as a protocol such that it can be applied to other comorbid diseases that did not gain much attention so far.