Subjects: Biology >> Virology Subjects: Computer Science >> Other Disciplines of Computer Science submitted time 2020-02-21
Abstract： During the outbreak of new infectious diseases, there is an urgent need to put forward scientific hypotheses for the efficacy, mechanism and side effects of candidate drugs. The research and development of vaccines or new drugs need a certain period of time, so the strategy of drug repositioning has its place. However, the clinical data of pathogen and host response of new diseases are not ready, restricts the hypothesis of candidate drugs. At this stage, we often try to use broad-spectrum antiviral drugs according to the clinical characteristics of patients. In this paper, we propose a new method aCODE (agile discovery method of drugs or natural products for emerging epidemic) which based on the heuristic search strategy widely used in the field of artificial intelligence. Based on the broad-spectrum antiviral drugs with some early efficacy tips, the host target protein collection is obtained, and the associated gene modules is searched on the whole genome scale. We then carry out pattern matching and statistics for candidate compounds (such as approved drugs and natural products ingredients). This method can update the input drugs according to the progress of clinical practice, and output more accurate results iteratively. The output components from natural products, traditional Chinese medicine or food can be used for quick trial to form a closed loop of agile R & D test. In addition, for the second update of this method and its comparison with literature evidence, please refer to: http://chinaxiv.org/abs/202002.00024.
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Awaiting Review
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