| Drug biomembrane permeability screening is of great significance in new drug research and development,which could reduce the enormous waste of resources during clinicll stage caused by unfavorable effectiveness and security issues.of the drug candidates.Biopartitioning micellar chromatography（BMC） introduces biomembrane-mimetic structures（micelle） into chromatographic system and thereby emulates drug-biomembrane interactions difficult to study in the liquid state but by well reproducible,rapid,sensitive and adequately designed chromatographic technique.In recent years,it has been paid more attention,because of its superior behavior in describing the biological processes of different kinds of drugs.The purpose of this study was to establish quantitative structure-retention relationship with BMC and optimize the BMC system,elucidating the retention mechanism and predicting the retention behavior, benefiting for the design of new chemical entities;meanwhile,to establish quantitative retention-permeability relationship with BMC,predicting the drug biomembrane permeability,facilitating the high-throughput analysis of large compounds’ bank and providing a new technical platform to evaluate the activities of drug candidates and to enhance the success rate of new drug research and development.Quantitative structure-retention relationship,utilizing the linear solvation energy relationship（LSER）,was established to elucidating the retention mechanism and predicting the retention behavior of drugs in BMC for the first time.The solute volume V and HB basicity B had the maximum influence on the retention of the solutes,an increase in the V contributes the retention of the compounds and an increase in the B will reduce the retention.When the mean net charge per molecule（δ） was introduced into LSER as the sixth variable,the LSER regression coefficients and predictive capability were significantly improved.The comparison of calculated and experimental retention indices suggested that the amended LSER could reproduce adequately the retention of the structurally diverse solutes investigated in BMC.The optimization of anionic surfactant SDS to the BMC system could simulate the electro-negativity of biomembrane.The quantitative structure-retention relationship with LSER showed that the BMCBrij35:SDS system could be better for predicting the retention behavior of the structurally diverse solutes.Chemometrics methods,stepwise regression and partial least squares regression, were utilized to establish quantitative structure-retention relationship for structure diverse drugs based on basic physicochemical molecular descriptors（Clog P,rings,rotation bonds,etc） which affecting the drug absorption processes.The models obtained exhibited good predictability（R2＞0.82）.The hydrophobicity（Clog P）,the mean net charge per molecule（δ）,the molecular weight（MW） and the total surface area（TSA） were the main factors influenced the retention behavior of the drugs in BMC.The hydrophobicity（Clog P） has the most significant positive effect but the mean net charge per molecule（δ） has significant negative effect.The power of prediction of the above model was evaluated and validated using an external test set and the model presented satisfying predictive ability. The dissociated basic compounds could permeate the biomembrane and BMCBrij35:SDS system could simulate this behavior better which optimized the BMC system.The monolithic column was introduced into BMC system and the retention mechanism of BMC using monolithic column was characterized by LSER in order to achieve a high-throughput screening for the first time.With the aid of the high flow rate, the monolithic column significantly facilitated the high-throughput analysis of large compounds’ bank without changing the mechanism of the retention in BMC.Principal component analysis of LSER coefficients showed that the system had certain similarity to drug biomembrane transport processes,such as blood-brain barrier penetration.The quantitative retention-permeability relationship of drug penetration across blood-brain barrier was established and the good predictive capability was achieved.The introduction of the molecular descriptor HD improved the predictability.The increasing of the number of HD inhibited the drug permeability of blood-brain barrier.The BMC using monolithic column will be a promising high-throughput screening method to model drug penetration across the blood-brain barrier and other biological membranes.The correlation between the lipophilicity parameter of BMC,n-octanol/water system, liiposome/water system,immobilized artificial membrane（IAM） chromatography and Caco-2 cell permeability showed that BMCBrij35 system could simulate the new antiasthmatic compounds’ Caco-2 cell permeability well.The introduction of molecular volumn MV could improve the model’s predictability.BMC system could be a potential high-throughput biomembrane permeability screening method.In combination Caco-2 cells model,BMC could enhance the success rate of new drug research and development to a large extent. |
