Validating ADME QSAR Models Using Marketed Drugs

Siramshetty, Vishal B.; Williams, Jeffery A.; Nguyễn, Ðắc-Trung; Neyra, Jorge; Southall, Noel; Mathé, Ewy A.; Xu, Xin; Shah, Pranav

doi:10.1177/24725552211017520

Cited by 25 publications

(14 citation statements)

References 46 publications

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“… 47 d Parallel artificial membrane permeation assay (PAMPA) is reported as a metric of the passive permeability of the compounds (1 × 10 –6 cm/s). 48 , 49 e Solubility—pION μSOL assay for kinetic aqueous solubility determination, pH 7.4. 50 …”

Section: Resultsmentioning

confidence: 99%

“… d Parallel artificial membrane permeation assay (PAMPA) is reported as a metric of the passive permeability of the compounds (1 × 10 –6 cm/s). , …”

Section: Resultsmentioning

confidence: 99%

“… a IC 50 : half-maximal inhibitory concentration values obtained from the CPE assay in eight-point dose response, measured in duplicate. b Values represent data obtained from five-point dose response, measured in duplicate. c Efficacy: maximum inhibitory effect observed in CPE assay. d T 1/2 : metabolic half-life measured in rat liver microsome fractions reported in minutes, the minimum detectable half-life of 1 min e Parallel artificial membrane permeation assay (PAMPA) is reported as a metric of the passive permeability of the compounds. , f SolubilitypION μSOL assay for kinetic aqueous solubility determination, pH 7.4 …”

Section: Resultsmentioning

confidence: 99%

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Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants

Jain

Talley

Baljinnyam

et al. 2021

ACS Pharmacol. Transl. Sci.

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The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal ( ). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytopathic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (∼16% of predicted hits) active compounds (efficacy > 30%, IC 50 ≤ 15 μM). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further investigation resulted in the identification of allosteric binders to host receptor angiotensin-converting enzyme 2; these compounds were then shown to inhibit the entry of pseudoparticles bearing spike protein of wild-type SARS-CoV-2, as well as South African B.1.351 and UK B.1.1.7 variants.

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Section: Resultsmentioning

confidence: 99%

“… d Parallel artificial membrane permeation assay (PAMPA) is reported as a metric of the passive permeability of the compounds (1 × 10 –6 cm/s). , …”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants

Jain

Talley

Baljinnyam

et al. 2021

ACS Pharmacol. Transl. Sci.

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“…In this regard, Food and Drug Administration (FDA) guidelines include in vivo, in situ, and in vitro (tissues and cells such as Caco-2 cell) methods to assess drug permeability [2]. In this context, the parallel artificial membrane permeability assay (PAMPA) [3] has proven to be particularly advantageous in identifying promising candidates in the early stages of drug development, to the extent that it has been included in the Tier I ADME assay at the National Center for Advancing Translational Sciences (NCATS), together with rat liver microsomal (RLM) stability, and kinetic aqueous solubility [4]. Indeed, PAMPA is an inexpensive and easily reproducible non-cell permeability assay able to model passive transcellular permeation mechanisms, which are predominant in the gastrointestinal tract.…”

Section: Introductionmentioning

confidence: 99%

“…Focusing attention on systems designed to simulate gastrointestinal tract absorption, most studies in this field apply regression methods (mainly multiple linear regression or partial least squares) on datasets derived from different PAMPA systems and specific to a certain class of bioactive compounds [6][7][8]. Otherwise, a very recent study concerning PAMPA-QSAR models, used to classify many pharmaceuticals into highly or poorly permeable classes, using random forest and graph convolutional neural networks as classification methods, has been proposed [4].…”

Section: Introductionmentioning

confidence: 99%

Advanced Analytical Tools for the Estimation of Gut Permeability of Compounds of Pharmaceutical Interest

et al. 2022

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The present study aims at developing a quantitative structure–activity relationship (QSAR) model for the determination of gut permeability of 228 pharmacological drugs at different pH conditions (3, 5, 7.4, 9, intrinsic). As a consequence, five different datasets (according to the diverse permeability shown by the compounds at the different pH values) were handled, with the aim of discriminating compounds as low-permeable or high-permeable. In order to achieve this goal, molecular descriptors for all the investigated compounds were computed and then classification models calculated by means of partial least squares discriminant analysis (PLS-DA). A high predictive capability was achieved for all models, providing correct classification rates in external validation between 80% and 96%. In order to test whether a reduction in the molecular descriptors would improve predictions and provide information about the most relevant variables, a feature selection approach, covariance selection, was used to select the most relevant subsets of predictors. This led to a slight improvement in the predictive accuracies, and it has indicated that the most relevant descriptors for the discrimination of the investigated compounds into low- and high-permeable were associated with the 2D and 3D structures.

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Open Access Databases and Datasets for Computer‐Aided Drug Design. A Short List Used in the Molecular Modelling Group of the SIB

Daina,

Ojeda‐Montes,

Bragina

et al. 2023

Methods and Principles in Medicinal Chemistry

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Validating ADME QSAR Models Using Marketed Drugs

Cited by 25 publications

References 46 publications

Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants

Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants

Advanced Analytical Tools for the Estimation of Gut Permeability of Compounds of Pharmaceutical Interest

Open Access Databases and Datasets for Computer‐Aided Drug Design. A Short List Used in the Molecular Modelling Group of the SIB

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