Dataset Information

Development of artificial neural network models to predict the PAMPA effective permeability of new, orally administered drugs active against the coronavirus SARS-CoV-2.

ABSTRACT: Responding to the pandemic caused by SARS-CoV-2, the scientific community intensified efforts to provide drugs effective against the virus. To strengthen these efforts, the "COVID Moonshot" project has been accepting public suggestions for computationally triaged, synthesized, and tested molecules. The project aimed to identify molecules of low molecular weight with activity against the virus, for oral treatment. The ability of a drug to cross the intestinal cell membranes and enter circulation decisively influences its bioavailability, and hence the need to optimize permeability in the early stages of drug discovery. In our present work, as a contribution to the ongoing scientific efforts, we employed artificial neural network algorithms to develop QSAR tools for modelling the PAMPA effective permeability (passive diffusion) of orally administered drugs. We identified a set of 61 features most relevant in explaining drug cell permeability and used them to develop a stacked regression ensemble model, subsequently used to predict the permeability of molecules included in datasets made available through the COVID Moonshot project. Our model was shown to be robust and may provide a promising framework for predicting the potential permeability of molecules not yet synthesized, thus guiding the process of drug design.

Supplementary information

The online version contains supplementary material available at 10.1007/s13721-023-00410-9.

SUBMITTER: Gousiadou C

PROVIDER: S-EPMC9901841 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Development of artificial neural network models to predict the PAMPA effective permeability of new, orally administered drugs active against the coronavirus SARS-CoV-2.

Gousiadou Chrysoula C Doganis Philip P Sarimveis Haralambos H

Network modeling and analysis in health informatics and bioinformatics 20230206 1

Responding to the pandemic caused by SARS-CoV-2, the scientific community intensified efforts to provide drugs effective against the virus. To strengthen these efforts, the "COVID Moonshot" project has been accepting public suggestions for computationally triaged, synthesized, and tested molecules. The project aimed to identify molecules of low molecular weight with activity against the virus, for oral treatment. The ability of a drug to cross the intestinal cell membranes and enter circulation ...[more]

PMID: 36778642

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Project description:Polymeric coatings are a promising option for the development of delivery systems for orally administered drugs. However, the gastrointestinal conditions to which they are subjected, which include low pH and solubility as well as peristaltic movements, can limit their applications. In this work, different formulations of polymeric coatings were produced using pH-sensitive materials consisting of copolymers of methyl acrylate, methyl methacrylate, and methacrylic acid. The polymers were synthesized by the emulsion polymerization technique, obtaining small average particle sizes (56-190 nm), molecular weights between 200,000 and 400,000 g/mol, and a glass transition temperature above 35 °C, which are suitable for film formation at room temperature. Thus, they were assessed as coatings for hydroxypropyl methylcellulose capsules (HPMC) using the immersion method, showing adequate capacity to protect the capsule at gastric pH (pH 1.2) and dissolve at the simulated intestinal pH (pH= 7.2). In particular, the higher the content of the acidic monomer, the higher the release time of the test molecule contained in the acrylic terpolymer-coated HPMC capsules proposed, which was a curcuminoid derivative due to their bright color and potential medical benefits. In addition, a minimum number of immersions was required for coating the HPMC capsules at high acidic concentrations, which further facilitates the delayed release needed for colonic treatment. However, too high proportions of methacrylic acid may result in cytotoxicity issues. Consequently, a biocompatible formulation containing a proportion of methyl acrylate, methyl methacrylate, and methacrylic acid of 7:3:3 is proposed as the most adequate for colonic release. Thus, by chemically modulating the molar percentages of the acrylic monomers, it was possible to obtain tailored acrylic terpolymer coatings with different characteristics and desired properties in order to modulate the release kinetics of an active substance in a colonic environment.

Dataset Information

Development of artificial neural network models to predict the PAMPA effective permeability of new, orally administered drugs active against the coronavirus SARS-CoV-2.

Supplementary information

Publications

Development of artificial neural network models to predict the PAMPA effective permeability of new, orally administered drugs active against the coronavirus SARS-CoV-2.

Similar Datasets

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