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Biology subjects

Sebek, M. L.

Publications and source records attributed to Sebek, M. L..

2 recordsLinked to original sources

CPIExtract: A software package to collect and harmonize small molecule and protein interactions

SummaryThe binding interactions between small molecules and proteins are the basis of cellular functions. Yet, experimental data available regarding compound-protein interactions (CPIs) are not harmonized into a single entity but rather scattered across multiple institutions, each maintaining databases with different formats. Extracting information from these multiple sources remains challenging due to data heterogeneity. Here, we present CPIExtract (Compound-Protein Interaction Extract), a Python package that automatically retrieves CPI data from nine major repositories, filters non-human and low-quality records, harmonizes chemical and protein identifiers, and computes unified pChEMBL binding values. Compared with MINER, a state-of-the-art CPI extraction algorithm, CPIExtract retrieves 85.5% more compounds, 16-fold more experimentally supported interactions, and over four times more proteins, substantially increasing the availability of strong and weak binders. The resulting harmonized dataset enables custom filtering and export in standard tabular formats for downstream applications such as network medicine, drug repurposing, and training of deep learning models. AvailabilityCPIExtract is an open-source Python package under an MIT license. CPIExtract can be downloaded from https://github.com/menicgiulia/CPIExtract and https://pypi.org/project/cpiextract. The package can run on any standard desktop computer or computing cluster.

bioinformatics↗

Estimating Nutrient Concentration in Food Using Untargeted Metabolomics

Untargeted metabolomics can detect hundreds of biochemicals in food, yet without standards, it cannot quantify them. Here we show that we can take advantage of the universal scaling of nutrient concentrations to estimate the concentration of all biochemicals detected by untargeted metabolomics. We validate our method on 20 raw foods, finding an excellent agreement between the predicted and the experimentally observed concentrations.

biochemistry↗