Predicting pharmacokinetic properties of potential anti-cancer agents using micellar thin-layer chromatography

Janicka, Małgorzata; Śliwińska, Anna; Sztanke, Małgorzata; Sztanke, Krzysztof

doi:10.1007/s00764-022-00174-4

Cited by 1 publication

(1 citation statement)

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“…Based on this knowledge (Collander 1951;Kaliszan 1987), the relationship between partitioning log Po/w and chromatographic log k parameters can be determined as: log 𝑃 𝑜/𝑤 = 𝑎 log 𝑘 + 𝑐𝑜𝑛𝑠𝑡 (3) The retention factor log k, as presented in Equation (3), can correspond to various chromatographic techniques and systems. For example, log kw values determined by RP HPLC column technique (using water as the mobile phase) or analogous RM0 parameters in thin-layer chromatography (TLC) (Biagi et al 1994;Janicka et al 2022aJanicka et al , 2022bJanicka & Śliwińska 2022). This parameter can also be determined in chromatographic systems that mimic biological partitioning, such as immobilized artificial membranes (IAMs) or columns with immobilized cholesterol, glycoproteins, human or rat serum albumins, and others.…”

Section: Introdutionmentioning

confidence: 99%

Over-Pressured Layer Chromatography and QSARs in predicting pharmacokinetics and toxicity of new herbicide candidates

Śliwińska

Janicka

2023

Preprint

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The Quantitative Structure-Activity Relationships (QSAR) methodology was utilized to predict the biological properties, including protein binding, plasma and brain unbound fractions, blood-brain barrier permeability, intestinal permeability, and lethal dose, of a series of newly synthesized s-triazines considered as potential herbicides. The Over-Pressured Layer Chromatography (OPLC) technique, employing reversed-phase systems, was applied to determine the lipophilicities of the substances, characterized by the retention parameters RM0. In the QSAR methodology, the chromatographic lipophilicity parameters (RM0), along with polarizability (α) and molecular weight (MW), were used as independent variables. Multiple linear regression was employed to derive the Quantitative Structure-Activity Relationships, which were subsequently validated, and their statistical significance was demonstrated.

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