The bioactive constituents found in natural products(NPs)are crucial in protein-ligand interactions and drug discovery.However,it is difficult to identify ligand molecules from complex NPs that specifically bind to ta...The bioactive constituents found in natural products(NPs)are crucial in protein-ligand interactions and drug discovery.However,it is difficult to identify ligand molecules from complex NPs that specifically bind to target protein,which often requires time-consuming and labor-intensive processes such as isolation and enrichment.To address this issue,in this study we developed a method that combines ultra-high performance liquid chromatography-electrospray ionization-mass spectrometry(UHPLCESI-MS)with molecular dynamics(MD)simulation to identify and observe,rapidly and efficiently,the bioactive components in NPs that bind to specific protein target.In this method,a specific protein target was introduced online using a three-way valve to form a protein-ligand complex.The complex was then detected in real time using high-resolution MS to identify potential ligands.Based on our method,only 10 molecules from green tea(a representative natural product),including the commonly reported epigallocatechin gallate(EGCG)and epicatechin gallate(ECG),as well as the previously unreported eepicatechin(4β→8)-epigallocatechin 3-O-gallate(EC-EGCG)and eepiafzelechin 3-O-gallate-(4β→8)-epigallocatechin 3-O-gallate(EFG-EGCG),were screened out,which could form complexes with Aβ_(1-42)(a representative protein target),and could be potential ligands of Aβ_(1-42).Among of them,EC-EGCG demonstrated the highest binding free energy with Aβ_(1-42)(−68.54±3.82 kcal/mol).On the other side,even though the caffeine had the highest signal among green tea extracts,it was not observed to form a complex with Aβ_(1-42).Compared to other methods such as affinity selection mass spectrometry(ASMS)and native MS,our method is easy to operate and interpret the data.Undoubtedly,it provides a new methodology for potential drug discovery in NPs,and will accelerate the research on screening ligands for specific proteins from complex NPs.展开更多
基金supported by the National Key R&D Program of China(No.2018YFA0800900).
文摘The bioactive constituents found in natural products(NPs)are crucial in protein-ligand interactions and drug discovery.However,it is difficult to identify ligand molecules from complex NPs that specifically bind to target protein,which often requires time-consuming and labor-intensive processes such as isolation and enrichment.To address this issue,in this study we developed a method that combines ultra-high performance liquid chromatography-electrospray ionization-mass spectrometry(UHPLCESI-MS)with molecular dynamics(MD)simulation to identify and observe,rapidly and efficiently,the bioactive components in NPs that bind to specific protein target.In this method,a specific protein target was introduced online using a three-way valve to form a protein-ligand complex.The complex was then detected in real time using high-resolution MS to identify potential ligands.Based on our method,only 10 molecules from green tea(a representative natural product),including the commonly reported epigallocatechin gallate(EGCG)and epicatechin gallate(ECG),as well as the previously unreported eepicatechin(4β→8)-epigallocatechin 3-O-gallate(EC-EGCG)and eepiafzelechin 3-O-gallate-(4β→8)-epigallocatechin 3-O-gallate(EFG-EGCG),were screened out,which could form complexes with Aβ_(1-42)(a representative protein target),and could be potential ligands of Aβ_(1-42).Among of them,EC-EGCG demonstrated the highest binding free energy with Aβ_(1-42)(−68.54±3.82 kcal/mol).On the other side,even though the caffeine had the highest signal among green tea extracts,it was not observed to form a complex with Aβ_(1-42).Compared to other methods such as affinity selection mass spectrometry(ASMS)and native MS,our method is easy to operate and interpret the data.Undoubtedly,it provides a new methodology for potential drug discovery in NPs,and will accelerate the research on screening ligands for specific proteins from complex NPs.
