High-throughput retrieval method for drug targets

Abstract

The invention relates to a high-throughput retrieval method for drug targets, and belongs to the field of bioinformatics. The high-throughput retrieval method includes the steps that a drug and target complex serves as reference, a drug combining bag is defined, all fragments in the combining bag are represented with protein structural fingerprints, and the protein structural fingerprints include amino acid sequences, protein folding shape codes, physicochemical properties and vector coupling; the digital drug combining bag is input, a global known protein structure database is retrieved to perform fingerprint comparison and quantitative evaluation, and protein structures are arrayed in the sequence of fingerprint similarity from high to low; structural protein is selected as possible target spot regions, wherein similarity scores of the protein folding codes and similarity scores of the amino acid physicochemical properties reach top two thousand at the same time, and possible target protein of drugs is analyzed and predicted. The high-throughput retrieval method can be applied to secondary development and research of the drugs, and new effects of the approved clinic drugs are developed by finding the new targets.

Description

technical field [0001] The invention relates to a high-throughput retrieval method for drug targets, belonging to the field of bioinformatics. Background technique [0002] Although most drugs have high selectivity, any drug entering the human or animal body has the potential to bind to multiple proteins. The traditional method is to detect and predict the protein target of the drug through in vitro and in vivo biological experiments. From the design to the implementation of these experiments, it takes a lot of time and resources 1,2,3 . Biomedical research has recognized that methods using computers and big data can improve lead information for these biological experiments. This can avoid research detours and save a lot of time and research costs. So far, the global shared protein database (PDB) has accumulated more than 110,000 protein three-dimensional structure data, and many proteins and ligand molecules combine with each other to form complexes. Thus protein datab...

AI Technical Summary

Problems solved by technology

These methods do describe drug-binding pockets, but they are poorly applicable to structural screening of large protein databases

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