Transcription factors (TFs) are the main carcinogenic factors of many cancers, and are therefore regarded as therapeutic targets with high research value. The function of TFs is achieved by the direct interaction between protein and DNA. In order to find a strategy for targeted therapy, it is necessary to start with the interaction between protein and DNA. However, it is recognized that small molecule drugs are difficult to target such interactions. With the advancement of computer-aided drug design (CADD) technology, this problem is expected to be solved.
Through CADD, we discovered drug candidates that can directly interfere with the interaction between TFs and DNA in several cancers. The targets mainly include androgen receptor (AR), ETS-related gene (ERG), MYC, thymocyte selection-associated high mobility group box protein TOX, topoisomerase II (Top2), as well as signal transducer and activator of transcription 3 (STAT3). More importantly, the discovery of these drug candidates has also opened up a new path for the development of targeted treatment strategies for more than 1,600 TFs involving cancer and other types of diseases in the human body.
Figure 1 Protein-DNA interaction
Protein-DNA interaction is very important for the functions of TFs, high-mobility group (HMG) and other DNA binding proteins (such as histones, DNA methyltransferases, polymerases, topoisomerases, etc.). The protein-DNA interaction surface is different from the ligand binding pocket, that is directly exposed to the solvent. So those amino acid residues that are rich in positive charges (such as Lysine) , Arginine) can directly interact with the DNA backbone. Moreover, inhibitors of protein-DNA binding are very scarce, especially since the DNA binding interface may usually have a convex shape or be enriched in positive charges. DNA binding domain (DBD) is often highly conserved among homologous proteins in the protein family. Therefore, it is very difficult to design specific small molecule inhibitors. Despite these difficult obstacles, with the advancement of computing power and experimental technology, and the increase in available structure data for transcription factors, structure-based drug design methods, such as molecular docking, have become more and more important in research. The continuous progress in the development of new computing tools (such as Deep Docking), will further advance the development of drug target identification, protein structure prediction, and new drug design.
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Raw data and calculation result analysis.
In drug design, the molecular docking method is mainly used to search for small molecules with good affinity with the biomacromolecule receptor. And then conduct pharmacological tests to discover new lead compounds. With the advancement of small molecule databases, large-scale virtual screening, and other computational tools, the successful discovery of PCC targeting protein-DNA interaction sites becomes feasible. If you have service needs for protein-DNA docking, please feel free to contact us.