Learning how to use IAM chromatography for predicting permeability

Ermondi, Giuseppe; Vallaro, Maura; Caron, Giulia

doi:10.1016/j.ejps.2018.01.001

Cited by 37 publications

(36 citation statements)

References 28 publications

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“…Comparative block relevance analysis of PLS models based on Volsurf descriptors further supports the similar information content of log k w(IAM) and log P for neutral compounds. As for bases and acids the analysis of log k w(IAM) (and also of log P) generates a positive sign for the block of H-bond donor (HBD) properties in accordance with the enhanced affinity to the IAM stationary phase , favoured for cations over anions , while the opposite sign (negative) is observed in the log D model [45].…”

Section: Relationship Of Iam Retention With Lipophilicity and Other Mmentioning

confidence: 84%

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Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

Tsopelas

Stergiopoulos²,

Tsantili‐Kakoulidou³

2018

ADMET DMPK

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Immobilized Artificial Membrane (IAM) chromatography constitutes a valuable tool for medicinal chemists to prioritize drug candidates in early drug development. The retention on IAM stationary phases encodes lipophilicity, electrostatic and other secondary interactions contrary to traditional octanol-water partitioning. An increasing number of publications in recent years have suggested that IAM indices, including isocratic log k(IAM) or extrapolated log kw(IAM) retention factors, chromatographic hydrophobicity index CHI(IAM) or the polarity parameter Δlog kw(IAM) can successfully model the passage of xeniobiotics through biological membranes and barriers and predict pharmacokinetic properties, often in combination with additional descriptors. Examples referring to the modeling of human oral absorption, blood-brain penetration and skin partition are described. More recently, IAM chromatography has been applied to estimate toxicological endpoints in regard to drug safety, such as phospholipidosis potential, or in regard to chemical risk hazards including the bioconcentration factor and aquatic organisms’ toxicity. The promising results in both medicinal chemistry and in environmental science in combination with the speed, reproducibility and low analyte consumption suggest that a broader application of IAM chromatography in the early drug discovery process and in ecotoxicity may save time and money in initial drug candidate selection and will contribute to a reduced risk hazard of chemicals.

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Section: Relationship Of Iam Retention With Lipophilicity and Other Mmentioning

confidence: 84%

“…As confirmed also by block relevance analysis at least for neutral compounds, Δlog k w(IAM) is considered as a polarity index, which can be used in QSPR studies replacing other polarity parameters such as polar surface area (PSA) or Δlog P oct-alk [45].…”

Section: Relationship Of Iam Retention With Lipophilicity and Other Mmentioning

confidence: 99%

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

Tsopelas

Stergiopoulos²,

Tsantili‐Kakoulidou³

2018

ADMET DMPK

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“…Overall our study reveals that log K w SDS is a complex descriptor since it is due to the contribution of more intermolecular forces of comparable relevance. Notably, it exhibits a very different blocks profile than log K W IAM and Dlog K W IAM , two chromatographic indexes determined in an Immobilised Artificial Membranes (IAM) system [26] and claimed to be relevant in the prediction of intestinal absorption. These findings suggest that the retention mechanisms involved in IAM and SDS-MLC are different and their potential contribution to predict HIA and BBB permeability as well.…”

Section: Molecular Factors Governing Log K W Sdsmentioning

confidence: 99%

MLR, PLSR‐BR Analysis and MBPLSR to Interpret Multivariate QSPR Models. The Case of a Micellar Liquid Chromatography Descriptor (log K_W^SDS)

Ermondi

Caron

2019

Molecular Informatics

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This paper is dedicated to Prof. Paola Gramatica on the occasion of her retirement.Abstract: Improving the interpretability of multivariate QSPR models is a major issue in modern drug discovery. In this study we applied three strategies to model and deconvolute the balance of intermolecular forces governing log K W SDS , a chromatographic descriptor of potential relevance in the prediction of ADME phenomena. A dataset of 77 compounds was set-up and an ad hoc pool of VS + descriptors calculated. The data matrix was firstly submitted to a PCA run for a preliminary analysis and outliers detection. To model and interpret log K W SDS three chemoinformatic approaches implementing either variable selection or grouping tools were used: a) MLR and GA, b) PLSR combined with BR analysis and c) MBPLSR. Results provided by the three methods were largely superposable both in terms of prediction performances and mechanistic interpretation. Overall, they showed that log K W SDS is a complex descriptor mainly governed by the dimension, polarity and HBD solutes' properties. Chemoinformatic strategies as those reported in this paper might be applied to any chromatographic system and thus represent a potent tool to exploit the full potential of chromatographic descriptors in pharmaceutical, toxicological and related sciences.

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“…Finally, VIPs and coefficients values are exported to Excel, elaborated and submitted to BR analysis which produces an easy-to-interpret graphical output. Our recent modelling study of Immobilized Artificial Membrane (IAM) chromatography [2] will be used to illustrate details of the BR approach. In this case, BR analysis was applied to extract the relative contribution of the intermolecular forces governing the IAM.PC.DD2 log K w IAM parameter from PLS models.…”

Section: Theorymentioning

confidence: 99%

“…log D tol ). log D oct and log D tol encode diverse information [2] and thus are not interchangeable. Therefore, it could be relevant for a medicinal chemist to know how a structural change impacts both log D oct and log D tol .…”

mentioning

confidence: 99%

Block relevance (BR) analysis and polarity descriptors in property-based drug design

Ermondi

2018

ADMET DMPK

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Learning how to use IAM chromatography for predicting permeability

Cited by 37 publications

References 28 publications

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

MLR, PLSR‐BR Analysis and MBPLSR to Interpret Multivariate QSPR Models. The Case of a Micellar Liquid Chromatography Descriptor (log K_W^SDS)

Block relevance (BR) analysis and polarity descriptors in property-based drug design

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Learning how to use IAM chromatography for predicting permeability

Cited by 37 publications

References 28 publications

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

MLR, PLSR‐BR Analysis and MBPLSR to Interpret Multivariate QSPR Models. The Case of a Micellar Liquid Chromatography Descriptor (log KWSDS)

Block relevance (BR) analysis and polarity descriptors in property-based drug design

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Product

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MLR, PLSR‐BR Analysis and MBPLSR to Interpret Multivariate QSPR Models. The Case of a Micellar Liquid Chromatography Descriptor (log K_W^SDS)