المؤلفون: Rifai, Eko Aditya, van Dijk, Marc, Vermeulen, Nico P. E., Geerke, Daan P.

المصدر: Journal of Computer-Aided Molecular Design: Incorporating Perspectives in Drug Discovery and Design. :1-11

المؤلفون: Salmaso, Veronica, Sturlese, Mattia, Cuzzolin, Alberto, Moro, Stefano

المصدر: Journal of Computer-Aided Molecular Design: Incorporating Perspectives in Drug Discovery and Design. :1-14

المؤلفون: Kumar, Ashutosh, Zhang, Kam Y. J.

المصدر: Journal of Computer-Aided Molecular Design: Incorporating Perspectives in Drug Discovery and Design. :1-11

المؤلفون: Veronica Salmaso, Stefano Moro, Alberto Cuzzolin, Mattia Sturlese

المصدر: Journal of Computer-Aided Molecular Design. 32:251-264

مصطلحات موضوعية: DockBench, 0301 basic medicine, Protein Conformation, Computer science, Receptors, Cytoplasmic and Nuclear, Ligands, Machine learning, computer.software_genre, 01 natural sciences, Self-docking, Small Molecule Libraries, Docking benchmark, 03 medical and health sciences, Software, D3R Grand Challenge 2, Drug Discovery, Humans, Physical and Theoretical Chemistry, Databases, Protein, Simulation, Lead Finder, Binding Sites, Cross-docking, Molecular docking, Drug Discovery3003 Pharmaceutical Science, business.industry, 0104 chemical sciences, Computer Science Applications, Molecular Docking Simulation, Benchmarking, 010404 medicinal & biomolecular chemistry, 030104 developmental biology, Protein–ligand docking, Docking (molecular), Drug Design, Computer-Aided Design, Thermodynamics, Pose prediction, Artificial intelligence, business, computer, Target binding, Protein Binding

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9441dff1d2f79a68506d6832151b3402
https://doi.org/10.1007/s10822-017-0051-4

المؤلفون: Daan P. Geerke, Nico P. E. Vermeulen, Marc van Dijk, Eko Aditya Rifai

المساهمون: Molecular and Computational Toxicology, AIMMS

المصدر: Journal of Computer-aided Molecular Design
Journal of Computer-Aided Molecular Design
Journal of Computer-aided Molecular Design, 32(1), 239-249. Springer Netherlands
Rifai, E A, van Dijk, M, Vermeulen, N P E & Geerke, D P 2017, ' Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation : application to the D3R Grand Challenge 2 ', Journal of Computer-aided Molecular Design, vol. 32, no. 1, pp. 239-249 . https://doi.org/10.1007/s10822-017-0055-0

مصطلحات موضوعية: 0301 basic medicine, Binding free energy prediction, Computer science, Protein Conformation, Receptors, Cytoplasmic and Nuclear, Context (language use), Molecular Dynamics Simulation, computer.software_genre, Ligands, Molecular Docking Simulation, Article, 03 medical and health sciences, Molecular dynamics, D3R Grand Challenge 2, Drug Discovery, Applicability domain, Humans, Drug Design Data Resource, Spiro Compounds, SDG 7 - Affordable and Clean Energy, Physical and Theoretical Chemistry, Profiling (computer programming), Sulfonamides, Binding Sites, Drug discovery, Reliability estimation, Interaction energy, Isoxazoles, Computer Science Applications, Linear interaction energy, Human Health and Life Sciences, 030104 developmental biology, Drug Design, Computer-Aided Design, Thermodynamics, Farnesoid X receptor, Benzimidazoles, Data mining, Science for Sustainability, computer, Algorithm, Protein Binding

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::580c9a18f6878d4971290234f09a515f
https://doi.org/10.1007/s10822-017-0055-0

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.

لا يتم عرض هذه النتيجة على الضيوف.
تسجيل الدخول للوصول الكامل.