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Relevant bibliographies by topics / Virtual screening

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Academic literature on the topic 'Virtual screening'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Virtual screening"

1

Musumeci, Daniele, Christopher A. Hunter, Rafel Prohens, Serena Scuderi, and James F. McCabe. "Virtual cocrystal screening." Chemical Science 2, no. 5 (2011): 883. http://dx.doi.org/10.1039/c0sc00555j.

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Sun, Hongmao. "Pharmacophore-Based Virtual Screening." Current Medicinal Chemistry 15, no. 10 (2008): 1018–24. http://dx.doi.org/10.2174/092986708784049630.

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Talevi, Alan, Luciana Gavernet, and Luis Bruno-Blanch. "Combined Virtual Screening Strategies." Current Computer Aided-Drug Design 5, no. 1 (2009): 23–37. http://dx.doi.org/10.2174/157340909787580854.

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Markt, P., S. Herdlinger, and D. Schuster. "Virtual Screening Against Obesity." Current Medicinal Chemistry 18, no. 14 (2011): 2158–73. http://dx.doi.org/10.2174/092986711795656162.

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Hirata, Shuzo, and Katsuyuki Shizu. "High-throughput virtual screening." Nature Materials 15, no. 10 (2016): 1056–57. http://dx.doi.org/10.1038/nmat4750.

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Walters, W. Patrick, Matthew T. Stahl, and Mark A. Murcko. "Virtual screening—an overview." Drug Discovery Today 3, no. 4 (1998): 160–78. http://dx.doi.org/10.1016/s1359-6446(97)01163-x.

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Crunkhorn, Sarah. "Novel virtual screening approach." Nature Reviews Drug Discovery 16, no. 1 (2017): 18. http://dx.doi.org/10.1038/nrd.2016.272.

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Muegge, Ingo, and Scott Oloff. "Advances in virtual screening." Drug Discovery Today: Technologies 3, no. 4 (2006): 405–11. http://dx.doi.org/10.1016/j.ddtec.2006.12.002.

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Glen, Robert C, and Gisbert Schneider. "Challenges in Virtual Screening." QSAR & Combinatorial Science 25, no. 12 (2006): 1131. http://dx.doi.org/10.1002/qsar.200690032.

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Mestres, J. "Virtual screening: a real screening complement to high-throughput screening." Biochemical Society Transactions 30, no. 4 (2002): 797–99. http://dx.doi.org/10.1042/bst0300797.

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Virtual screening is being routinely used as an integral part of today's hit-identification strategies for, on one hand, prioritizing large corporate screening collections and, on the other hand, to extend the scope of screening to external databases. A brief description of the essential elements required for virtual screening and an application example to the identification of agonist hits for the oestrogen receptor subtype ERα are presented.

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Dissertations / Theses on the topic "Virtual screening"

1

Grecu, T. "Virtual cocrystal screening." Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/5929/.

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Capuccini, Marco. "Structure-Based Virtual Screening in Spark." Thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-257028.

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Corbeil, Christopher. "New virtual screening tools for molecular discovery." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=40786.

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In the field of molecular discovery, virtually screening large libraries of compounds proved to be often more cost-efficient than the traditional experimental approaches. In fact, it has now become common practice thanks to the virtual screening tools available to chemists in the pharmaceutical industry, specifically docking. Most docking programs do not account for the dynamics associated with protein-ligand binding whether it is protein flexibility or the inclusion of displaceable water molecules. FITTED1.0 was developed to include these specific two features and has been validated on a test

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Müller, Christoph H. P. "Similarity-based virtual screening using inference networks." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531182.

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Koutsoukas, Alexios. "Virtual screening and bioactivities of small molecules." Thesis, University of Cambridge, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708215.

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Shave, Steven R. "Development of high performance structure and ligand based virtual screening techniques." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4333.

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Virtual Sreening (VS) is an in silico technique for drug discovery. An overview of VS methods is given and is seen to be approachable from two sides: structure based and ligand based. Structure based virtual screening uses explicit knowledge of the target receptor to suggest candidate receptor-ligand complexes. Ligand based virtual screening can infer required characteristics of binders from known ligands. A consideration for all virtual screening techniques is the amount of computing time required to arrive at a solution. For this reason, techniques of high performance computing have been app

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Schellhammer, Ingo. "Structure based molecule indexing for sublinear virtual screening." Berlin Logos-Verl, 2005. http://deposit.ddb.de/cgi-bin/dokserv?id=2820891&prov=M&dok_var=1&dok_ext=htm.

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Arif, Shereena M. "Fragment weighting schemes for similarity-based virtual screening." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540932.

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Martin, Richard Luis. "Wavelet approximation of GRID fields for virtual screening." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531509.

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Hert, JeÌroÌ‚me. "Two-dimensional, similarity-based methods for virtual screening." Thesis, University of Sheffield, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425602.

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Books on the topic "Virtual screening"

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Sotriffer, Christoph, ed. Virtual Screening. Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527633326.

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Taha, Mutasem Omar. Virtual screening. Intech, 2012.

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Saha, Ishika, Patrick G. Harran, Dr. Jonathan Bohmann, Department of Pharmaceuticals and Bioe, and Ryan Gumpper, Postdoctoral Researcher, University of North C. Virtual Screening for Chemists. American Chemical Society, 2021. http://dx.doi.org/10.1021/acsinfocus.7e5001.

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Varnek, Alexandre, and Alex Tropsha, eds. Chemoinformatics Approaches to Virtual Screening. Royal Society of Chemistry, 2008. http://dx.doi.org/10.1039/9781847558879.

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Alexandre, Varnek, Tropsha Alex, and Royal Society of Chemistry (Great Britain)., eds. Chemoinformatics approaches to virtual screening. RSC Pub., 2008.

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Hans-Joachim, Böhm, and Schneider Gisbert 1965-, eds. Virtual screening for bioactive molecules. Wiley-VCH, 2000.

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1965-, Alvarez Juan, and Shoichet Brian 1963-, eds. Virtual screening in drug discovery. Taylor & Francis, 2005.

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Klebe, Gerhard, ed. Virtual Screening: An Alternative or Complement to High Throughput Screening? Kluwer Academic Publishers, 2002. http://dx.doi.org/10.1007/0-306-46883-2.

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Gerhard, Klebe, ed. Virtual screening: An alternative or complement to high throughput screening : proceedings of the Workshop 'New Approaches in Drug Design and Discovery', special topic 'Virtual Screening', SchloB Rauischholzhausen, Germany, March 15-18, 1999. Kluwer Academic Publishers, 2000.

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Taha, Mutasem, ed. Virtual Screening. InTech, 2012. http://dx.doi.org/10.5772/2049.

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Book chapters on the topic "Virtual screening"

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Baringhaus, Karl-Heinz, and Gerhard Hessler. "Virtual Screening." In Small Molecule Medicinal Chemistry. John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781118771723.ch9.

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Yellasubbaiah, N., B. Sivakumar, and B. Nagasudha. "Virtual Screening." In Computational and Experimental Studies in Alzheimer's Disease. CRC Press, 2024. http://dx.doi.org/10.1201/9781003412069-10.

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Kumar, T. Durai Ananda. "Virtual Screening." In Drug Design: A Conceptual Overview. CRC Press, 2022. http://dx.doi.org/10.1201/9781003298755-7.

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Bajorath, Jürgen. "Virtual Screening Methods." In Diversity-Oriented Synthesis. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118618110.ch15.

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Sykora, Vladimir Joseph. "Automated Virtual Screening." In Methods in Molecular Biology. Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3449-3_6.

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Sison, Antonio D. "Films from a Virtual Geography of Third Cinema." In Screening Schillebeeckx. Palgrave Macmillan US, 2006. http://dx.doi.org/10.1057/9780230602106_4.

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Koeppen, Herbert, Jan Kriegl, Uta Lessel, Christofer S. Tautermann, and Bernd Wellenzohn. "Ligand-Based Virtual Screening." In Methods and Principles in Medicinal Chemistry. Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527633326.ch3.

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Horvath, Dragos. "Pharmacophore-Based Virtual Screening." In Methods in Molecular Biology. Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-839-3_11.

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Kolodzik, Adrian, Nadine Schneider, and Matthias Rarey. "Structure-Based Virtual Screening." In Applied Chemoinformatics. Wiley-VCH Verlag GmbH & Co. KGaA, 2018. http://dx.doi.org/10.1002/9783527806539.ch6h.

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Li, Qingliang, and Salim Shah. "Structure-Based Virtual Screening." In Protein Bioinformatics. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6783-4_5.

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Conference papers on the topic "Virtual screening"

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Tang, Haoyang, Yanhong Li, Xinyue Yao, and Chenyang Fan. "Virtual Screening of Natural Anti-Senescent Compounds Based on Sq-TabPFN." In 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE). IEEE, 2024. https://doi.org/10.1109/icaice63571.2024.10864333.

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Halls, Mathew D., David J. Giesen, Thomas F. Hughes, et al. "Virtual screening for OLED materials." In SPIE Organic Photonics + Electronics, edited by Franky So and Chihaya Adachi. SPIE, 2014. http://dx.doi.org/10.1117/12.2066565.

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Seus, Vinicius Rosa, Lande Silva, Jorge Gomes, Pedro E. A. da Silva, Adriano V. Werhli, and Karina S. Machado. "A framework for virtual screening." In SAC 2016: Symposium on Applied Computing. ACM, 2016. http://dx.doi.org/10.1145/2851613.2851618.

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Piechowski, Kara, and Brijesh Patel. "Coronary Artery Calcification In Lung Cancer Screening." In Radiopaedia 2024 Virtual Conference. Radiopaedia.org, 2024. http://dx.doi.org/10.53347/rposter-2474.

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Rafati-Afshar, Amir Ali, and Abdelhamid Bouchachia. "An Empirical Investigation of Virtual Screening." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.451.

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Hagan, Daniel M., and Martin T. Hagan. "Virtual drug screening using neural networks." In 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, 2016. http://dx.doi.org/10.1109/ijcnn.2016.7727252.

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Kumar, Dhananjay, Anshul Sarvate, Sakshi Singh, and Puja Priya. "Virtual screening using machine learning approach." In 2013 IEEE Conference on Information & Communication Technologies (ICT). IEEE, 2013. http://dx.doi.org/10.1109/cict.2013.6558164.

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Jaghoori, Mohammad Mahdi, Allard J. Van Altena, Boris Bleijlevens, and Silvia D. Olabarriaga. "A Grid-Enabled Virtual Screening Gateway." In 2014 6th International Workshop on Science Gateways (IWSG). IEEE, 2014. http://dx.doi.org/10.1109/iwsg.2014.11.

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Bickmore, Timothy, Amy Rubin, and Steven Simon. "Substance Use Screening using Virtual Agents." In IVA '20: ACM International Conference on Intelligent Virtual Agents. ACM, 2020. http://dx.doi.org/10.1145/3383652.3423869.

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Ge, Yaorong, David J. Vining, David K. Ahn, and David R. Stelts. "Colorectal cancer screening with virtual colonoscopy." In Medical Imaging '99, edited by Chin-Tu Chen and Anne V. Clough. SPIE, 1999. http://dx.doi.org/10.1117/12.349577.

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Reports on the topic "Virtual screening"

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Wale, Nikil, George Karypis, and Ian A. Watson. Methods for Effective Virtual Screening and Scaffold-Hopping in Chemical Compounds. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada467533.

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Chappelle, Wayne, Lillian Prince, Tanya Goodman, William Thompson, Sara Cowper, and Bobbie Ray-Sannerud. Occupational Health Screenings of the Virtual Warrior: Distributed Common Ground System Intelligence Operators Compared with Non-Combatant Support Personnel. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada604765.

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Yedidia, I., H. Senderowitz, and A. O. Charkowski. Small molecule cocktails designed to impair virulence targets in soft rot Erwinias. United States-Israel Binational Agricultural Research and Development Fund, 2020. http://dx.doi.org/10.32747/2020.8134165.bard.

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Chemical signaling between beneficial or pathogenic bacteria and plants is a central factor in determining the outcome of plant-microbe interactions. Pectobacterium and Dickeya (soft rot Erwinias) are the major cause of soft rot, stem rot, and blackleg formed on potato and ornamentals, currently with no effective control. Our major aim was to establish and study specific bacterial genes/proteins as targets for anti-virulence compounds, by combining drug design tools and bioinformatics with experimental work. The approach allowed us to identify and test compounds (small molecules) that specific

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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and p

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Yusrina, Asri, Emilie Berkhout, Daniel Suryadarma, and Luhur Bima. Can the Teacher Professional Education Admission Criteria in Indonesia Predict Teacher Performance? Research on Improving Systems of Education (RISE), 2023. http://dx.doi.org/10.35489/bsg-rise-ri_2023/055.

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Studies find that effective teachers raise student test achievement and lead to higher future earnings for the students (Chetty et.al, 2014; Hanushek, 2011). Teacher selection and the criteria used in making the selection are important because they aim to identify such effective teachers. Identifying teachers with such potential is relatively more cost-effective than other policies applied after the teachers have teaching jobs (Klassen and Kim, 2019; Hobson et al., 2010). Many studies focus on selecting teachers based on the information collected at the time of hire to predict student outcomes

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Elizur, Abigail, Amir Sagi, Gideon Hulata, Clive Jones, and Wayne Knibb. Improving Crustacean Aquaculture Production Efficiencies through Development of Monosex Populations Using Endocrine and Molecular Manipulations. United States Department of Agriculture, 2010. http://dx.doi.org/10.32747/2010.7613890.bard.

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Background Most of Australian prawn aquaculture production is based on P. monodon. However, the Australian industry is under intense competition from lower priced overseas imports. The availability of all-female monosex populations, by virtue of their large size and associated premium prize, will offer competitive advantage to the industry which desperately needs to counteract competitors within this market. As for the redclaw production in Israel, although it is at its infancy, the growers realized that the production of males is extremely advantageous and that such management strategy will c

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