Cross-species molecular docking method to support predictions of species susceptibility to chemical effects
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The advancement of protein structural prediction tools, exemplified by AlphaFold and Iterative Threading ASSEmbly Refinement, has enabled the prediction of protein structures across species based on available protein sequence and structural data. In this study, we introduce an innovative molecular docking method that capitalizes on this wealth of structural data to enhance predictions of chemical susceptibility across species. We demonstrated this method using the androgen receptor as a pertinent modulator of endocrine function. By using protein structures, this method contextualizes species susceptibility within a functional framework and helps to integrate molecular docking into the repertoire of New Approach Methodologies (NAMs) that support the Next-Generation Risk Assessment (NGRA) paradigm through the novel integration of various open-source tools. This dataset is associated with the following publication: Schumann, P., D. Chang, S. Mayasich, S. Vliet, T. Brown, and C. LaLone. Cross-species molecular docking method to support predictions of species susceptibility to chemical effects. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 30(4): 100319, (2024).
Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
공공데이터포털
Data file for "Vliet SMF, Hazemi M, Blatz D, Jensen M, Mayasich S, Transue TR, Simmons C, Wilkinson A, LaLone CA. Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation. J Vis Exp. 2023 Feb 10;(192). doi: 10.3791/63970. PMID: 36847398.". This dataset is associated with the following publication: Vliet, S., M. Hazemi, D. Blatz, M. Jensen, S. Mayasich, T. Transue, C. Simmons, A. Wilkinson, and C. Lalone. Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation. Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 192, (2023).
Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
공공데이터포털
Data file for "Vliet SMF, Hazemi M, Blatz D, Jensen M, Mayasich S, Transue TR, Simmons C, Wilkinson A, LaLone CA. Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation. J Vis Exp. 2023 Feb 10;(192). doi: 10.3791/63970. PMID: 36847398.". This dataset is associated with the following publication: Vliet, S., M. Hazemi, D. Blatz, M. Jensen, S. Mayasich, T. Transue, C. Simmons, A. Wilkinson, and C. Lalone. Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation. Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 192, (2023).
The Protein database is a collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB. Protein sequences are the fundamental determinants of biological structure and function.