Chromatographic Data in Statistical Analysis of BBB Permeability Indices.

Blood-brain barrier (BBB) permeability is an essential phenomena when considering the treatment of neurological disorders as well as in the case of central nervous system (CNS) adverse effects caused by peripherally acting drugs. The presented work contains statistical analyses and the correlation assessment of the analyzed group of active pharmaceutical ingredients (APIs) with their BBB-permeability data collected from the literature (such as computational log BB; Kp,uu,brain, and CNS+/- groups). A number of regression models were constructed in order to observe the connections between the APIs' physicochemical properties in combination with their retention data from the chromatographic experiments (TLC and HPLC) and the indices of bioavailability in the CNS. Conducted analyses confirm that descriptors significant in BBB permeability modeling are hydrogen bond acceptors and donors, physiological charge, or energy of the lowest unoccupied molecular orbital. These molecular descriptors were the basis, along with the chromatographic data from the TLC in log BB regression analyses. Normal-phase TLC data showed a significant contribution to the creation of the log BB regression model using the multiple linear regression method. The model using them showed a good predictive value at the level of R2 = 0.87. Models for Kp,uu,brain resulted in lower statistics: R2 = 0.56 for the group of 23 APIs with the participation of k IAM.

Statistical Methods in the Study of Protein Binding and Its Relationship to Drug Bioavailability in Breast Milk.

Protein binding (PB) is indicated as the factor most severely limiting distribution in the organism, reducing the bioavailability of the drug, but also minimizing the penetration of xenobiotics into the fetus or the body of a breastfed child. Therefore, PB is an important aspect to be analyzed and monitored in the design of new drug substances. In this paper, several statistical analyses have been introduced to find the relationship between protein binding and the amount of drug in breast milk and to select molecular descriptors responsible for both pharmacokinetic phenomena. Along with descriptors related to the physicochemical properties of drugs, chromatographic descriptors from TLC and HPLC experiments were also used. Both methods used modification of the stationary phase, using bovine serum albumin (BSA) in TLC and human serum albumin (HSA) in HPLC. The use of the chromatographic data in the protein binding study was found to be positive -the most effective application of normal-phase TLC and HPLCHSA data was found. Statistical analyses also confirmed the prognostic value of affinity chromatography data and protein binding itself as the most important parameters in predicting drug excretion into breast milk.

In silico Plasma Protein Binding Studies of Selected Group of Drugs Using TLC and HPLC Retention Data.

Plasma protein binding is an important determinant of the pharmacokinetic properties of chemical compounds in living organisms. The aim of the present study was to determine the index of protein binding affinity based on chromatographic experiments. The question is which chromatographic environment will best mimic the drug-protein binding conditions. Retention data from normal phase thin-layer liquid chromatography (NP TLC), reversed phase (RP) TLC and HPLC chromatography experiments with 129 active pharmaceutical ingredients (APIs) were collected. The stationary phase of the TLC plates was modified with protein and the HPLC column was filled with immobilized human serum albumin. In both chromatographic methods, the mobile phase was based on a buffer with a pH of 7.4 to mimic physiological conditions. Chemometric analyses were performed to compare multiple linear regression models (MLRs) with retention data, using protein binding values as the dependent variable. In the course of the analysis, APIs were divided into acidic, basic and neutral groups, and separate models were created for each group. The MLR models had a coefficient of determination between 0.73 and 0.91, with the highest values from NP TLC data.

Biological barriers, and the influence of protein binding on the passage of drugs across them.

Drug-protein binding plays a key role in determining the pharmacokinetics of a drug. The distribution and protein binding ability of a drug changes over a lifetime, and are important considerations during pregnancy and lactation. Although proteins are a significant fraction in plasma composition, they also exist beyond the bloodstream and bind with drugs in the skin, tissues or organs. Protein binding influences the bioavailability and distribution of active compounds, and is a limiting factor in the passage of drugs across biological membranes and barriers: drugs are often unable to cross membranes mainly due to the high molecular mass of the drug-protein complex, thus resulting in the accumulation of the active compounds and a significant reduction of their pharmacological activity. This review describes the consequences of drug-protein binding on drug transport across physiological barriers, whose role is to allow the passage of essential substances-such as nutrients or oxygen, but not of xenobiotics. The placental barrier regulates passage of xenobiotics into a fetus and protects the unborn organism. The blood-brain barrier is the most important barrier in the entire organism and the skin separates the human body from the environment.

Aspects of Drug-Protein Binding and Methods of Analyzing the Phenomenon.

In recent decades, drug-protein interactions have been widely studied and several methods of analysis of these phenomena have been developed and improved. These can be classified into separation, physical, chromatographic and electrophoretic methods. This review depicts the assumptions and mechanisms of methods from each group, details their strengths and weaknesses, and presents examples of their usage from the literature. Equilibrium dialysis, ultrafiltration, Hummel-Dreyer method or high performance affinity chromatography are given as representative examples, but this issue is far more expanded. Nowadays, increasing attention is paid to the computational methods and molecular modeling which are convenient tools to estimate protein binding affinity based on the physicochemical properties of compounds. To gain a broader overview, the study also examines the protein binding ability and pharmacotherapy of drugs against a range of substrates such as plasma, skin, tissue and human milk.