Quantitative Structure – Pharmacokinetics Relationships Analysis of Basic Drugs: Volume of Distribution

Abstract

-Purpose. The early prediction of pharmacokinetic behavior is of paramount importance for saving time and resources and for increasing the success of new drug candidates. The steady-state volume of distribution (VD ss ) is one of the key pharmacokinetic parameters required for the design of a suitable dosage regimen. The aim of the study is to propose a quantitative structure -pharmacokinetics relationships (QSPkR) for VD ss of basic drugs. Methods: The data set consists of 216 basic drugs, divided to a modeling (n = 180) and external validation set (n = 36). 179 structural and physicochemical descriptors are calculated using validated commercial software. Genetic algorithm, stepwise regression and multiple linear regression are applied for variable selection and model development. The models are validated by internal and external test sets. Results: A number of significant QSPkRs are developed. The most frequently emerged descriptors are used to derive the final consensus model for VD ss with good explanatory (r 2 0.663) and predictive ability (q 2 LOO-CV 0.606 and r 2 pred 0.593). The model reveals clear structural features determining VD ss of basic drugs which are summarized in a short list of criteria for rapid discrimination between drugs with a large and small VD ss . Conclusions: Descriptors like lipophilicity, fraction ionized as a base at pH 7.4, number of cycles and fused aromatic rings, presence of Cl and F atoms contribute positively to VD ss , while polarity and presence of strong electrophiles have a negative effect.

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

“…QSPkRs allow prediction of PK properties at early stages of drug discovery, even on virtual compounds, thus reducing time and expense and preventing costly late-stage failures. We have previously reported QSPkR models for V d (11), pf u (12), CL (13) and t 1/2 (14) of acidic drugs, as well as for V d of basic drugs (15).…”

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

“…The key PK parameters were predicted by quantitative structure–activity relationships (QSPkRs) models, derived previously 43–46 . Briefly, the PK parameters of 145 neutral and/or 262 basic drugs 47 were used to derive QSPkR models by multiple linear regression (MLR) with MDL QSAR v. 2.2 (MDL Information Systems Inc., San Leandro, CA).…”

Partial Least Square Model (PLS) as a Tool to Predict the Diffusion of Steroids Across Artificial Membranes

“…Certain criteria have been defined to discriminate between drugs with high and low VD ss . LogP has been shown to be a significant determinant of VD ss , which along with the presence of Cl atoms and molecule compactness, have a positive contribution on this descriptor, while polarity and strong electrophiles have a negative contribution on VD ss [48]. High VD ss values (> 42 L), representative of more lipophilic drugs, indicate a high likeliness of drug distribution throughout body tissues, whereas low VD ss values (< 3 L) associate with a predominant location in the systemic circulation [49].…”