Chemical Computing Group Excellence Award
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Category Archives: Publication
Education: Initiatives to bridge faith and science
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Statistically identifying tumor suppressors and oncogenes from pan-cancer genome-sequencing data.
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Modeling Epoxidation of Drug-like Molecules with a Deep Machine Learning Network
Citation:
Modeling Epoxidation of Drug-like Molecules with a Deep Machine Learning Network. Tyler B. Hughes, Grover P. Miller, and S. Joshua Swamidass. ACS Central Science. DOI: 10.1021/acscentsci.5b00131
Abstract:
Drug toxicity is frequently caused by electrophilic reactive metabolites that covalently bind to proteins. Epoxides comprise … Continue Reading ››
Drug toxicity is frequently caused by electrophilic reactive metabolites that covalently bind to proteins. Epoxides comprise … Continue Reading ›› 
Site of Reactivity Models Predict Molecular Reactivity of Diverse Chemicals with Glutathione
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XenoSite Regions
Published online in Bioinformatics in February 2015
Extending P450 Site-of-Metabolism Models with Region-Resolution Data
Jed Zaretzki, Michael Browning, Tyler B. Hughes, S. Joshua Swamidass
Motivation: Cytochrome P450s are a family of enzymes responsible for the metabolism of approximately 90% of FDA approved drugs. Medicinal chemists often want to know which atoms of a … Continue Reading ›› 
Combined Analysis of Phenotypic and Target-Based Screening in Assay Networks
Citation:
Swamidass, S. J., Schillebeeckx, C. N., Matlock, M., Hurle, M. R., & Agarwal, P. (2014). Combined Analysis of Phenotypic and Target-Based Screening in Assay Networks. Journal of biomolecular screening, 1087057114523068.
Abstract:
Small-molecule screens are an integral part of drug discovery. Public domain data in PubChem alone represent more than
158 million measurements, 1.2 million molecules, and 4300 assays. … Continue Reading ››
Sharing Chemical Relationships Does Not Reveal Structures
Citation:
Matlock, M., & Swamidass, S. J. (2013). Sharing Chemical Relationships Does Not Reveal Structures. Journal of chemical information and modeling, 54(1), 37-48.
Abstract: In this study, we propose a new, secure method of sharing useful chemical information from small-molecule libraries, without revealing the structures of the libraries’ molecules. Our method shares the relationship between molecules rather … Continue Reading ››
XenoSite: Accurately Predicting CYP-mediated Sites of Metabolism with Neural Networks
Web Server:
https://swami.wustl.edu/xenosite
Citation:
Zaretzki, J., Matlock, M., & Swamidass, S. J. (2013). XenoSite: Accurately predicting CYP-mediated sites of metabolism with neural networks. Journal of chemical information and modeling, 53(12), 3373-3383..
Abstract:
Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these … Continue Reading ››
Round up of Recently Published Papers
Over the last several months we have published several papers. In the coming weeks, I will be posting abstracts and additional information for each of these papers. In the meantime, here are the citations of those that have hit print.
Managing missing measurements in small-molecule screens. Browning MR, Calhoun BT, Swamidass SJ. J Comput Aided Mol Des. 2013 … Continue Reading ››