@article{mansouri_kleinstreuer_abdelaziz_alberga_alves_andersson_andrade_bai_balabin_ballabio_et al._2020, title={CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity}, volume={128}, ISSN={["1552-9924"]}, DOI={10.1289/EHP5580}, abstractNote={Background: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. Objectives: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). Methods: The CoMPARA list of screened chemicals built on CERAPP’s list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays. Results: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. Discussion: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program’s Integrated Chemical Environment. https://doi.org/10.1289/EHP5580}, number={2}, journal={ENVIRONMENTAL HEALTH PERSPECTIVES}, author={Mansouri, Kamel and Kleinstreuer, Nicole and Abdelaziz, Ahmed M. and Alberga, Domenico and Alves, Vinicius M. and Andersson, Patrik L. and Andrade, Carolina H. and Bai, Fang and Balabin, Ilya and Ballabio, Davide and et al.}, year={2020}, month={Feb} }
 @article{wen_wang_van den driessche_chen_zhang_chen_li_soto_liu_ohashi_et al._2019, title={Adipocytes as Anticancer Drug Delivery Depot}, volume={1}, ISSN={["2590-2385"]}, DOI={10.1016/j.matt.2019.08.007}, abstractNote={Tumor-associated adipocytes promote tumor growth by providing energy and causing chronic inflammation. Here, we have exploited the lipid metabolism to engineer adipocytes that serve as a depot to deliver cancer therapeutics at the tumor site. Rumenic acid (RA), as an anticancer fatty acid, and a doxorubicin prodrug (pDox) with a reactive oxygen species (ROS)-cleavable linker, are encapsulated in adipocytes to deliver therapeutics in a tumor-specific bioresponsive manner. After intratumoral or postsurgical administration, lipolysis releases the RA and pDox that is activated by intracellular ROS-responsive conversion, subsequently promoting antitumor efficacy. Furthermore, downregulation of PD-L1 expression is observed in tumor cells, favoring the emergence of CD4+ and CD8+ T cell-mediated immune responses.}, number={5}, journal={MATTER}, author={Wen, Di and Wang, Jinqiang and Van Den Driessche, George and Chen, Qian and Zhang, Yuqi and Chen, Guojun and Li, Hongjun and Soto, Jennifer and Liu, Ming and Ohashi, Masao and et al.}, year={2019}, month={Nov}, pages={1203–1214} }
 @article{van den driessche_fourches_2018, title={Adverse drug reactions triggered by the common HLA-B*57:01 variant: Virtual screening of DrugBank using 3D molecular docking}, volume={10}, journal={Journal of Cheminformatics}, author={Van Den Driessche, G. and Fourches, D.}, year={2018} }
 @article{williams_kuenemann_driessche_williams_fourches_freeman_2018, title={Toward the Rational Design of Sustainable Hair Dyes Using Cheminformatics Approaches: Step 1. Database Development and Analysis}, volume={6}, ISSN={["2168-0485"]}, url={https://doi.org/10.1021/acssuschemeng.7b03795}, DOI={10.1021/acssuschemeng.7b03795}, abstractNote={Herein, we report on the initial step of the design process of new hair dyes with the desired properties. The first step is dedicated to the development of the largest, publicly available database of hair dye substances (containing temporary and semipermanent hair dyes as well as permanent hair dye precursors) used in commercial hair dye formulations. The database was utilized to perform a cheminformatics study assessing the computed physicochemical properties of the different hair dye substances, especially within each cluster of structurally similar dyes. The various substances could be differentiated based on their average molecular weight, hydrophobicity, topological polar surface area, and number of hydrogen bond acceptors, with some overlap also observed. In particular, we found that dyes such as C.I. Basic Orange 1 and 2 were clustered among the precursors, suggesting that their diffusion behavior is similar to that of permanent hair dye precursors. We anticipate taking advantage of this interestin...}, number={2}, journal={ACS SUSTAINABLE CHEMISTRY & ENGINEERING}, publisher={American Chemical Society (ACS)}, author={Williams, Tova N. and Kuenemann, Melaine A. and Driessche, George A. and Williams, Antony J. and Fourches, Denis and Freeman, Harold S.}, year={2018}, month={Feb}, pages={2344–2352} }