Dataset Information

A New Metric Quantifying Chemical and Biological Property of Small Molecule Metabolites and Drugs.

ABSTRACT: One prominent class of drugs is chemical small molecules (CSMs), but the majority of CSMs are of very low druggable potential. Therefore, it is quite important to predict drug-related properties (druggable properties) for candidate CSMs. Currently, a number of druggable properties (e.g., logP and pKa) can be calculated by in silico methods; still the identification of druggable CSMs is a high-risk task, and new quantitative metrics for the druggable potential of CSMs are increasingly needed. Here, we present normalized bond energy (NBE), a new metric for the above purpose. By applying NBE to the DrugBank CSMs whose properties are largely known, we revealed that NBE is able to describe a number of critical druggable properties including logP, pKa, membrane permeability, blood-brain barrier penetration, and human intestinal absorption. Moreover, given that the human endogenous metabolites can serve as important resources for drug discovery, we applied NBE to the metabolites in the Human Metabolome Database. As a result, NBE showed a significant difference in metabolites from various body fluids and was correlated with some important properties, including melting point and water solubility.

SUBMITTER: Huang C

PROVIDER: S-EPMC7770129 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A New Metric Quantifying Chemical and Biological Property of Small Molecule Metabolites and Drugs.

Huang Chuanbo C Zhou Yuan Y Yang Jichun J Cui Qinghua Q Li Yanhui Y

Frontiers in molecular biosciences 20201215

One prominent class of drugs is chemical small molecules (CSMs), but the majority of CSMs are of very low druggable potential. Therefore, it is quite important to predict drug-related properties (druggable properties) for candidate CSMs. Currently, a number of druggable properties (e.g., logP and pKa) can be calculated by <i>in silico</i> methods; still the identification of druggable CSMs is a high-risk task, and new quantitative metrics for the druggable potential of CSMs are increasingly need ...[more]

PMID: 33385011

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Project description:BackgroundThe current approach to screen for drug-like molecules is to sieve for molecules with biochemical properties suitable for desirable pharmacokinetics and reduced toxicity, using predominantly biophysical properties of chemical compounds, based on empirical rules such as Lipinski's "rule of five" (Ro5). For over a decade, Ro5 has been applied to combinatorial compounds, drugs and ligands, in the search for suitable lead compounds. Unfortunately, till date, a clear distinction between drugs and non-drugs has not been achieved. The current trend is to seek out drugs which show metabolite-likeness. In identifying similar physicochemical characteristics, compounds have usually been clustered based on some characteristic, to reduce the search space presented by large molecular datasets. This paper examines the similarity of current drug molecules with human metabolites and toxins, using a range of computed molecular descriptors as well as the effect of comparison to clustered data compared to searches against complete datasets.ResultsWe have carried out statistical and substructure functional group analyses of three datasets, namely human metabolites, drugs and toxin molecules. The distributions of various molecular descriptors were investigated. Our analyses show that, although the three groups are distinct, present-day drugs are closer to toxin molecules than to metabolites. Furthermore, these distributions are quite similar for both clustered data as well as complete or unclustered datasets.ConclusionThe property space occupied by metabolites is dissimilar to that of drugs or toxin molecules, with current drugs showing greater similarity to toxins than to metabolites. Additionally, empirical rules like Ro5 can be refined to identify drugs or drug-like molecules that are clearly distinct from toxic compounds and more metabolite-like. The inclusion of human metabolites in this study provides a deeper insight into metabolite/drug/toxin-like properties and will also prove to be valuable in the prediction or optimization of small molecules as ligands for therapeutic applications.

Dataset Information

A New Metric Quantifying Chemical and Biological Property of Small Molecule Metabolites and Drugs.

Publications

A New Metric Quantifying Chemical and Biological Property of Small Molecule Metabolites and Drugs.

Similar Datasets

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