Studying The Interaction Patterns Between Cancer-related Proteins And Inhibitors Based On Molecular Dynamics Simulation And Network Pharmacology

So far,cancer-related proteins have been widely involved in cell differentiation,signaling,apoptosis.In addition,they are closely related to the occurrence and development of cancer.The abnormal expression of these proteins and the changes of activity caused by the changes of spatial conformation could promote the proliferation of tumor cells,the loss of signal transduction and the inhibition of apoptosis.Therefore,in-depth study of protein structure and functional mechanism and exploration of novel cancer-related target proteins are crucial for understanding the pathogenesis of cancer and formulating effective treatment strategies.The design and development of many anti-cancer drugs are also based on it.At present,the combination of experimental technology and computer-aided drug designs,as well as the application of bioinformation technology,have a positive impact on the safety and accuracy of new drug development,as well as the improvement of research and development efficiency and success rate.Driven by the rapid development of high-performance computers,molecular dynamics simulation technology has become a powerful scientific tool for processing and analyzing complex biological macromolecular systems and biological processes.Moreover,it has unique advantages in the study of protein structure-function.Network pharmacology uses existing databases to screen disease-related drug molecules,predict drug targets,and study their biological functions and molecular pathways.The computer-aided drug biological computing method has broadened the field of drug research and development,and deeply explored the active ingredients of drugs and the relevant mechanisms of their intervention in diseases,which can provide new directions and more possibilities for the development of new drugs and the diversification of disease treatment means.In this paper,we used the enhanced sampling method of molecular dynamics simulation,combined with network pharmacology technology,to deeply study the interaction mechanism of cancer-related proteins and inhibitors.Specifically as follows:1.Through Gaussian accelerated molecular dynamics simulations to investigate machine learning cluster analysis,other structurally similar components in licorice were searched for and quantified to collect the structural commonalities of these components related to liver cancer,and to identify the key residues of interaction between small molecules and key target proteins.The results showed that licorice flavone A(LCA),licorice flavone B(LCB),licorice flavone C(LCC),licorice flavone D(LCD),licorice flavone E(LCE),licorice flavone F(LCF)and licorice flavone G(LCG)interfered with liver cancer through MicroRNAs,NF-κB signaling pathway,MAPK signaling pathway,PD-L1 expression and PD-1 checkpoint pathway.Glypallichalcone,Echinatin and 3,4,3’,4’-Tetrahydroxy-2-methoxychalcone in licorice had the similar structures and possibly similar effects to LCA-LCG.The key residues involved in hydrogen bond interaction between 10 glycyrrhiza flavonoids and key target protein nitric oxide synthase 2(NOS2),namely Asn364,Gly365,Trp366 and Tyr485,were also identified.In conclusion,this study provided valuable insights into the molecular mechanism of glycyrrhiza flavonoid intervention in HCC,and also provided a new idea for the design of small molecule drugs related to the treatment of HCC.3.Through Gaussian accelerated molecular dynamics combined with Markov state models to explore the action mechanism of the new inhibitor HP661 on complex IOxidative phosphorylation(OXPHOS)is one of the main pathways of intracellular energy production,and it had been found that it played the key role in the dry maintenance of some specific subtypes of tumor cells.In this study,the inhibitory mechanism of HP661,a new selective OXPHOS inhibitor.1H-1,2,3-triazole derivatives,on complex I was investigated.ND1,NDUFS2 and NDUFS7 subunits of complex I were selected as receptor proteins,and three systems of protein-IACS010759,protein-10 and protein-HP661 were set up to construct the Markov state model by Gaussian accelerated molecular dynamics simulation of 500 ns.The conformational changes,the role of key residues and the binding ability of proteins during the simulation were studied.The results showed that compared with IACS-010759 and compound 10,HP661 had the stronger binding ability with receptor proteins,resulting in increased protein extensibility and hydrophilicity,and also affected the stability of a-helix structure in the region of the residues 726-730,and partial unspinning occurred.Amino acid residues Met37,Phe53 and Pro212 were the key residues that played an important role in inhibitor binding to receptor proteins.In conclusion,this study provided important information for further understanding of the mechanism of action of highly effective and novel OXPHOS inhibitors,and provided useful theoretical support for future research and development of such drugs and disease treatment design.