Quantitative Structure – Pharmacokinetics Relationships for Plasma Protein Binding of Basic Drugs

Abstract

Purpose. Binding of drugs to plasma proteins is a common physiological occurrence which may have a profound effect on both pharmacokinetics and pharmacodynamics. The early prediction of plasma protein binding (PPB) of new drug candidates is an important step in drug development process. The present study is focused on the development of quantitative structure -pharmacokinetics relationship (QSPkR) for the negative logarithm of the free fraction of the drug in plasma (pf u ) of basic drugs. Methods. A dataset includes 220 basic drugs, which chemical structures are encoded by 176 descriptors. Genetic algorithm, stepwise regression and multiple linear regression are used for variable selection and model development. Predictive ability of the model is assessed by internal and external validation. Results. A simple, significant, interpretable and predictive QSPkR model is constructed for pf u of basic drugs. It is able to predict 59% of the drugs from an external validation set within the 2-fold error of the experimental values with squared correlation coefficient of prediction 0.532, geometric mean fold error (GMFE) 1.94 and mean absolute error (MAE) 0.17. Conclusions. PPB of basic drugs is favored by the lipophilicity, the presence of aromatic C-atoms (either non-substituted, or involved in bridged aromatic systems) and molecular volume. The fraction ionized as a base f B and the presence of quaternary Catoms contribute negatively to PPB. A short checklist of criteria for high PPB is defined, and an empirical rule for distinguishing between low, high and very high plasma protein binders is proposed based. This rule allows correct classification of 69% of the very high binders, 71% of the high binders and 91% of the low binders in plasma.

Novel hits for acetylcholinesterase inhibition derived by docking-based screening on ZINC database

“…The VD ss s in the training set range between 0.073 and 140 L/kg, with mean 5.90 L/kg and median 2.45 L/kg. The lower VD ss s of the neutral molecules also is in accordance with the VD ss s of the training set of neutral molecules, which vary between 0.16 and 25 L/kg, with mean 1.94 L/kg and median 1 L/kg 44 . As log P is one of the descriptors with high positive effect on VD ss 43 , the hydrophilic compounds 6 and 8 have reasonably the lowest VD ss s.…”

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

“…The most important, and the most difficult to pass, is the blood-brain barrier (BBB), which separates crucial organs from the environment. Binding with HSA and AAG macromolecules affects the pharmacokinetic properties of pharmacologically-active compounds by decreasing their bioavailability and slowing their passage across biological membranes and barriers [32][33][34]; proteins themselves hardly penetrate through the cell membranes [35][36][37]. On the contrary new approaches in target therapy also reveal that drug binding to the protein carrier improves the effectiveness of several pharmacotherapies [38], e.g.…”

Quantitative Structure–pharmacokinetics Relationship for Plasma Protein Binding of Neutral Drugs

“…The negative contribution of the presence of aromatic N-atoms (descriptor SaaN) could be attributed to decrease of lipophilicity and reduced tendency for hydrophobic and Van der Waals interactions in the binding site. Some of the descriptors were suggested to affect positively PPB of acids (logP and SaasC_acnt) and bases (logP and SaaaC_acnt) as well [47,48].…”

“…QSPkR models for PPB of acidic and basic drugs have been published recently [47,48]. Lipophilicity was identified as a major factor with a positive contribution for both types, while the presence of quaternary C-atom contributed negatively to PPB.…”