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P-glycoprotein (P-gp) is an ATP (adenosine triphosphate)-binding cassette transporter that causes multidrug resistance of various chemotherapeutic substances by active efflux from mammalian cells. P-gp plays a pivotal role in limiting drug absorption and distribution in different organs, including the intestines and brain. Thus, the prediction of P-gp–drug interactions is of vital importance in assessing drug pharmacokinetic and pharmacodynamic properties. To find the strongest P-gp blockers, we performed an in silico structure-based screening of P-gp inhibitor library (1,300 molecules) by the gradient optimization method, using polynomial empirical scoring (POLSCORE) functions. We report a strong correlation (r2=0.80, F=16.27, n=6, P<0.0157) of inhibition constants (Kiexp or pKiexp; experimental Ki or negative decimal logarithm of Kiexp) converted from experimental IC50 (half maximal inhibitory concentration) values with POLSCORE-predicted constants (KiPOLSCORE or pKiPOLSCORE), using a linear regression fitting technique. The hydrophobic interactions between P-gp and selected drug substances were detected as the main forces responsible for the inhibition effect. The results showed that this scoring technique might be useful in the virtual screening and filtering of databases of drug-like compounds at the early stage of drug development processes.
The blood–brain barrier choline transporter (BBB-ChT) may have utility as a drug delivery vector to the central nervous system (CNS). We therefore initiated molecular docking studies with the AutoDock and AutoDock Vina (ADVina) algorithms to develop predictive models for compound screening and to identify structural features important for binding to this transporter. The binding energy predictions were highly correlated with r2=0.88, F=692.4, standard error of estimate =0.775, and P-value<0.0001 for selected BBB-ChT-active/inactive compounds (n=93). Both programs were able to cluster active (Gibbs free energy of binding <−6.0 kcal*mol-1) and inactive (Gibbs free energy of binding >−6.0 kcal*mol-1) molecules and dock them significantly better than at random with an area under the curve value of 0.86 and 0.84, respectively. In ranking smaller molecules with few torsional bonds, a size-related bias in scoring producing false-negative outcomes was detected. Finally, important blood–brain barrier parameters, such as the logBBpassive and logBBactive values, were assessed to predict compound transport to the CNS accurately. Knowledge gained from this study is useful to better understand the binding requirements in BBB-ChT, and until such time as its crystal structure becomes available, it may have significant utility in developing a highly predictive model for the rational design of drug-like compounds targeted to the brain.
We investigated the ionization profiles for open-ring (OR) and closed-ring (CR) forms of midazolam and drug-binding modes with heptakis-(2,3,6-tri-O-methyl)-β-cyclodextrin (trimethyl-β-cyclodextrin; TRIMEB) using molecular modeling techniques and quantum mechanics methods. The results indicated that the total net charges for different molecular forms of midazolam tend to be cationic for OR and neutral for CR at physiological pH levels. The thermodynamic calculations demonstrated that CR is less water-soluble than OR, mainly due to the maximal solvation energy (ΔG(CR)(solv = -9.98 kcal·mol ⁻¹), which has a minimal ΔG(OR)(solv) of -67.01 kcal·mol⁻¹. A cell viability assay did not detect any signs of TRIMEB and OR/CR-TRIMEB complex toxicity on the cEND cells after 24 h of incubation in either Dulbecco's Modified Eagles Medium or in heat-inactivated human serum. The molecular docking studies identified the more flexible OR form of midazolam as being a better binder to TRIMEB with the fluorophenyl ring introduced inside the amphiphilic cavity of the host molecule. The OR binding affinity was confirmed by a minimal Gibbs free energy of binding (ΔG(bind)) value of -5.57 ± 0.02 kcal·mol⁻¹, an equilibrium binding constant (K(b)) of 79.89 ± 2.706 μM, and a ligand efficiency index (LE(lig)) of -0.21 ± 0.001. Our current data suggest that in order to improve the clinical applications of midazolam via its complexation with trimethyl-β-cyclodextrin to increase drug's overall aqueous solubility, it is important to concern the different forms and ionization states of this anesthetic. All mean values are indicated with their standard deviations.