Screening for promising multi-target bioactive components from Cortex Mori Radicis for the treatment of chronic cor pulmonale based on immobilized beta1-adrenergic receptor and beta2-adrenergic receptor chromatography.

Cortex Morin Radicis (CMR) is the dried root bark of Morus alba. L. It has a variety of effects such as antibacterial, anti-tumour, treatment of cardiovascular diseases or upper respiratory tract disease and so on. The pursuit for drugs selected from Cortex Mori Radicis having improved therapeutic efficacy necessitates increasing research on new assays for screening bioactive compounds with multi-targets. In this work, we applied immobilized ß1-AR and ß2-AR as the stationary phase in chromatographic column to screen bioactive compounds from Cortex Morin Radicis. Specific ligands of the two receptors (e.g. esmolol, metoprolol, atenolol, salbutamol, methoxyphenamine, tulobuterol and clorprenaline) were utilized to characterize the specificity and bioactivity of the columns. We used high performance affinity chromatography coupled with ESI-MS to screen targeted compounds of Cortex Morin Radicis. By zonal elution, we identified morin as a bioactive compound simultaneously binding to ß1-AR and ß2-AR. The compound exhibited the association constants of 3.10 × 104 and 2.60 × 104 M-1 on the ß1-AR and ß2-AR column. On these sites, the dissociation rate constants were calculated to be 0.131 and 0.097 s-1. Molecular docking indicated that the binding of morin to the two receptors occurred on Asp200, Asp121, and Val122 of ß1-AR, Asn312, Thr110, Asp113, Tyr316, Gly90, Phe193, Ile309, and Trp109 of ß2-AR. Likewise, mulberroside C was identified as the bioactive compound binding to ß2-AR. The association constants and dissociation rate constants were calculated to be 1.08 × 104 M-1 and 0.900 s-1. Molecular docking also indicated that mulberroside C could bind to ß2-AR receptor on its agonist site. Taking together, we demonstrated that the chromatographic strategy to identify bioactive natural products based on the ß1-AR and ß2-AR immobilization, has potential for screening bioactive compounds with multi-targets from complex matrices including traditional Chinese medicines.

A chromatographic method for determining the interaction between a drug and two target proteins by fabricating a dual-heterogeneous surface.

Characterization of the drug-target interactions is pivotal throughout the whole procedure of drug development. Most of the current assays, particularly, chromatographic methods lack the capacity to reveal drug adsorption on the muti-target surface. To this end, we derived a reliable and workable mathematical equation for revealing drug bindings to dual targets on the heterogeneous surface starting from the mass balance equation. The derivatization relied on the correlation of drug injection amounts with their retention factors. Experimental validation was performed by determining the binding parameters of three canonical drugs on a heterogeneous surface, which was fabricated by fusing angiotensin receptor type I and type II receptors (AT1R and AT2R) at the terminuses of circularly permuted HaloTag (cpHaloTag) and immobilizing the whole fusion protein onto 6-bromohexanoic acid modified silica gel. We proved that immobilized AT1R-cpHalo-AT2R maintained the original ligand- and antibody-binding activities of the two receptors in three weeks. The association constants of valsartan, candesartan, and telmisartan to AT1R were (6.26±0.14) × 105, (9.66±0.71) × 105, and (3.17±0.03) × 105 L/mol. In the same column, their association constants to AT2R were (1.25±0.04) × 104, (2.30±0.08) × 104, and (8.51±0.06) × 103 L/mol. The patterns of the association constants to AT1R/AT2R (candesartan>valsartan>telmisartan) were in good line with the data by performing nonlinear chromatography on control columns containing immobilized AT1R or AT2R alone. This provided proof of the fact that the derivatization allowed the determination of drug bindings on the heterogeneous surface with the utilization of a single series of injections and linear regression. We reasoned that is simple enough to model the bindings of drug adsorption on commercially available adsorbents in fundamental or industrial fields, thus having the potential to become a universal method for analyzing the bindings of a drug to the heterogeneous surface containing multiple targets.