Study On Virtual Screening For Targeted TRPV1 Channel Modulators

TRPV1 channel is a ligand-gated non-selective cation channel that can be activated by a variety of physical and chemical stimuli,and mediates the entry of cations into the cell,forming action potential,causing pain and changes in downstream signal transduction pathways.TRPV1 channel existing in sensory neurons and some non-neuronal cells and tissues is relevant to the pathogenesis of many diseases,such as pain,inflammation,cardiovascular disease,cough,mental disease and diabetes.TRPV1agonists such as capsaicin,can not only be used as analgesics,but also as marine antifouling coatings,anti-ant and anti-rat repellents,and riot control agents for military and police.TRPV1 modulators are studied widely in analgesic drugs,and both agonists and antagonists can produce potent analgesic effects without the addictive problem of traditional analgesics.However,due to their clinical side effects,the development of new drugs for TRPV1 channels is slow.Currently,the only TRPV1 drugs on the market are topical preparations of capsaicin.Therefore,exploring TRPV1 channel modulators with high efficiency and low side effects has been a hot topic of research.In this paper,computer-aided drug design（CADD）and artificial intelligence-assisted drug design（AIDD）methods were comprehensively applied to established CADD and AIDD virtual screening protocols.Various virtual screening models based on ligand,structure and machine learning were constructed to conduct high-throughput virtual screening on large compound databases.Finally,three hits were obtained after in vitro activity evaluation.The main research content and results are as follows:（1）Virtual screening of TRPV1 modulators based on CADD:In order to combine the advantages of two types of methods:structure based virtual screening（SBVS）and ligand based virtual screening（LBVS）,this thesis adopts the strategy of parallel screening,that is,screening compounds independently through SBVS and LBVS,so as to effectively enrich potential compounds with activity.In the SBVS route,human TRPV1 channel protein was first constructed by homology modeling,and then molecular docking was conducted based on this structure.This work employed three different precision molecular docking methods to gradually enrich active compounds.In the LBVS route,based on the assumption that similar ligands have similar activity,a three-dimensional shape similarity and electrostatic similarity search queries was constructed using existing highly active TRPV1 modulators as templates,and 3.57 million compounds were screened successively.The compounds obtained through SBVS and LBVS were further screened by cluster analysis,ADME/T property filtering,and manual inspection.Finally,11（SBVS）and 26（LBVS）compounds were selected for testing.（2）Virtual screening of TRPV1 modulators based on AIDD:In this part of work,a quantitative structure-activity relationship（QSAR）model based on random forest（RF）algorithm was first constructed for the prediction of antagonistic activity of TRPV1channel.This model is of good prediction performance(²₍(8(8(8（8）=0.729±0.01,₀²0)0)0)0)0))=0.813),and the Y-randomization test proved that there is an intrinsic relationship between the model and the TRPV1 modulators.The result of application domain evaluation indicates that the model has good generalization ability.Subsequently,this work constructed a molecular docking rescoring model based on extreme gradient boosting（XGBoost）.This model exhibits superior early enrichment ability compared to Glide XP and can be used for post-molecular docking screening.This thesis designed a virtual screening protocol consisting of molecular docking,molecular docking rescoring,MM/GBSA binding free energy calculation,QSAR model prediction,and ADME/T property filtering.This protocol was applied to screen 6.2 million compounds,and 40compounds were ultimately retained for activity evaluation.（3）In vitro activity test and mechanism simulation:In this study,FLIPR calcium flow detection was used to evaluate the activity of 77 compounds selected by CADD and AIDD virtual screening.The results showed that 8 compounds had inhibitory or agonistic activity around or over 50%,in which 6 compounds have antagonistic activity,1compounds has agonistic activity,and compound Z1118828305 exhibits both strong antagonistic and agonistic activity.Through further activity testing,three hits were found,with IC₅₀ vlaues of around 2μM close to the classic TRPV1 antagonist capsazepine(IC₅₀=1.57μM).Wherein the EC₅₀value of Z1118828305 is 1.32μM,which indicates that this compound is a partial agonist and is expected to be used to develop non-pungent TRPV1 agonists.At the same time,in order to understand the mechanism of the interaction between the active compounds and h TRPV1,molecular docking and molecular dynamics simulation were applied to study the binding modes of the active compounds and the TRPV1 channel and analyze their agonism or antagonism mechanism.In conclusion,this thesis combines the advantages of CADD and AIDD virtual screening to establish a variety of TRPV1 channel virtual screening models,methods and protocols.Through high-throughput virtual screening and in vitro activity tests,three highly active hits with antagonistic activities at around 2μM,which provide a technical foundation and hits for the development of new TRPV1 modulators.