Relevant bibliographies by topics / DNA Encoded Library

Academic literature on the topic 'DNA Encoded Library'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "DNA Encoded Library"

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Hackler, Amber L., Forrest G. FitzGerald, Vuong Q. Dang, Alexander L. Satz, and Brian M. Paegel. "Off-DNA DNA-Encoded Library Affinity Screening." ACS Combinatorial Science 22, no. 1 (December 12, 2019): 25–34. http://dx.doi.org/10.1021/acscombsci.9b00153.

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Brunschweiger, Andreas. "A DNA-encoded library special issue." Bioorganic & Medicinal Chemistry 56 (February 2022): 116582. http://dx.doi.org/10.1016/j.bmc.2021.116582.

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Cochrane, Wesley G., Marie L. Malone, Vuong Q. Dang, Valerie Cavett, Alexander L. Satz, and Brian M. Paegel. "Activity-Based DNA-Encoded Library Screening." ACS Combinatorial Science 21, no. 5 (March 18, 2019): 425–35. http://dx.doi.org/10.1021/acscombsci.9b00037.

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Zhang, Y., and M. A. Clark. "Design concepts for DNA-encoded library synthesis." Bioorganic & Medicinal Chemistry 41 (July 2021): 116189. http://dx.doi.org/10.1016/j.bmc.2021.116189.

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Shin, Min Hyeon, Kang Ju Lee, and Hyun-Suk Lim. "DNA-Encoded Combinatorial Library of Macrocyclic Peptoids." Bioconjugate Chemistry 30, no. 11 (October 30, 2019): 2931–38. http://dx.doi.org/10.1021/acs.bioconjchem.9b00628.

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Cochrane, Wesley G., Patrick R. Fitzgerald, and Brian M. Paegel. "Antibacterial Discovery via Phenotypic DNA-Encoded Library Screening." ACS Chemical Biology 16, no. 12 (November 20, 2021): 2752–56. http://dx.doi.org/10.1021/acschembio.1c00714.

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Shen, Yurong, Guanyu Yang, Wei Huang, Alex Shaginian, Qian Lin, Jinqiao Wan, Jin Li, Yun Deng, and Guansai Liu. "Photoredox Deaminative Alkylation in DNA-Encoded Library Synthesis." Organic Letters 24, no. 14 (April 1, 2022): 2650–54. http://dx.doi.org/10.1021/acs.orglett.2c00697.

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Kómár, Péter, and Marko Kalinić. "Denoising DNA Encoded Library Screens with Sparse Learning." ACS Combinatorial Science 22, no. 8 (June 12, 2020): 410–21. http://dx.doi.org/10.1021/acscombsci.0c00007.

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Ding, Yun, Jing Chai, Paolo A. Centrella, Chenaimwoyo Gondo, Jennifer L. DeLorey, and Matthew A. Clark. "Development and Synthesis of DNA-Encoded Benzimidazole Library." ACS Combinatorial Science 20, no. 5 (April 12, 2018): 251–55. http://dx.doi.org/10.1021/acscombsci.8b00009.

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Onda, Yuichi, Gabriele Bassi, Abdullah Elsayed, Franziska Ulrich, Sebastian Oehler, Louise Plais, Jörg Scheuermann, and Dario Neri. "A DNA‐Encoded Chemical Library Based on Peptide Macrocycles." Chemistry – A European Journal 27, no. 24 (March 18, 2021): 7160–67. http://dx.doi.org/10.1002/chem.202005423.

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Dissertations / Theses on the topic "DNA Encoded Library"

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Geylan, Gökçe. "Training Machine Learning-based QSAR models with Conformal Prediction on Experimental Data from DNA-Encoded Chemical Libraries." Thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447354.

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DNA-encoded chemical libraries (DEL) allows an exhaustive chemical space sampling with a large-scale data consisting of compounds produced through combinatorial synthesis. This novel technology was utilized in the early drug discovery stages for robust hit identification and lead optimization. In this project, the aim was to build a Machine Learning- based QSAR model with conformal prediction for hit identification on two different target proteins, the DEL was assayed on. An initial investigation was conducted on a pilot project with 1000 compounds and the analyses and the conclusions drawn from this part were later applied to a larger dataset with 1.2 million compounds. With this classification model, the prediction of the compound activity in the DEL as well as in an external dataset was aimed to be analyzed with identification of the top hits to evaluate model’s performance and applicability. Support Vector Machine (SVM) and Random Forest (RF) models were built on both the pilot and the main datasets with different descriptor sets of Signature Fingerprints, RDKIT and CDK. In addition, an Autoencoder was used to supply data-driven descriptors on the pilot data as well. The Libsvm and the Liblinear implementations were explored and compared based on the models’ performances. The comparisons were made by considering the key concepts of conformal prediction such as the trade-off between validity and efficiency, observed fuzziness and the calibration against a range of significance levels. The top hits were determined by two sorting methods, credibility and p-value differences between the binary classes. The assignment of correct single-labels to the true actives over a wide range of significance levels regardless of the similarity of the test compounds to the training set was confirmed for the models. Furthermore, an accumulation of these true actives in the models’ top hit selections was observed according to the latter sorting method and additional investigations on the similarity and the building block enrichments in the top 50 and 100 compounds were conducted. The Tanimoto similarity demonstrated the model’s predictive power in selecting structurally dissimilar compounds while the building block enrichment analysis showed the selectivity of the binding pocket where the target protein B was determined to be more selective. All of these comparison methods enabled an extensive study on the model evaluation and performance. In conclusion, the Liblinear model with the Signature Fingerprints was concluded to give the best model performance for both the pilot and the main datasets with the considerations of the model performances and the computational power requirements. However, an external set prediction was not successful due to the low structural diversity in the DEL which the model was trained on.
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Parameswaran, Aishwarya. "DNA Encoded Libraries (DEGL) of Glycan Antigens to Detect Antibodies: An Approach Towards Next Generation Functional Glycomics." 2017. http://scholarworks.gsu.edu/chemistry_theses/101.

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Structure and functional study of glycans are highly challenging due to the difficulties in analyzing glycans and limited availability of samples for study. These limitations could be resolved by attaching DNA barcode to the glycan, which virtually represent glycan in further application, by increasing the sensitivity of detection by polymerase chain reaction (PCR), requiring minimal samples for analysis. Assuming bigger arena of DNA Encoded Glycan Libraries (DEGL) in future, we propose here a method for uniquely coding all glycans using computer program that can convert the structural information of glycans to DNA barcode. A unique and universal coding for glycans will benefit both synthesis and analysis of DEGLs. As a proof of principle study, a small DNA Encoded Glycan Library (DEGL) of blood and globo series glycan antigen and its application was demonstrated in detecting blood group and breast cancer from plasma.
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Books on the topic "DNA Encoded Library"

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Jr, Robert A. Goodnow. A Handbook for DNA-Encoded Chemistry: Theory and Applications for Exploring Chemical Space and Drug Discovery. Wiley, 2014.

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Book chapters on the topic "DNA Encoded Library"

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Zhu, Zhengrong, Alex Shaginian, La Shadric C. Grady, Christopher P. Davie, Kenneth Lind, Sandeep Pal, Praew Thansandote, and Graham L. Simpson. "DNA-Encoded Macrocyclic Peptide Library." In Methods in Molecular Biology, 273–84. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9504-2_12.

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Ottl, Johannes. "Reported Applications of DNA-Encoded Library Chemistry." In A Handbook for DNA-Encoded Chemistry, 319–47. Hoboken, NJ: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118832738.ch14.

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Satz, Alexander Lee. "Foundations of a DNA-Encoded Library (DEL)." In A Handbook for DNA-Encoded Chemistry, 99–121. Hoboken, NJ: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118832738.ch5.

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Perkins, George L., and G. John Langley. "Analytical Challenges for DNA-Encoded Library Systems." In A Handbook for DNA-Encoded Chemistry, 171–99. Hoboken, NJ: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118832738.ch8.

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Yao, Gang, Xiaojie Lu, Chris Phelps, and Ghotas Evindar. "Chapter 7. DNA-encoded Library Technology (ELT)." In Chemical and Biological Synthesis, 153–83. Cambridge: Royal Society of Chemistry, 2018. http://dx.doi.org/10.1039/9781788012805-00153.

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Melkko, Samu, and Johannes Ottl. "Keeping the Promise? An Outlook on DNA Chemical Library Technology." In A Handbook for DNA-Encoded Chemistry, 427–34. Hoboken, NJ: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118832738.ch19.

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Škopić, Mateja Klika, Denise dos Santos Smith, Anne Gohla, Verena B. K. Kunig, and Andreas Brunschweiger. "Initiating DNA-Encoded Library Synthesis with a Hexathymidine DNA Oligonucleotide." In Methods in Molecular Biology, 89–104. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2545-3_14.

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Zhu, Zhengrong. "Selection Method of DNA-Encoded Chemical Library for Irreversible Covalent Binders." In Methods in Molecular Biology, 165–72. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2545-3_20.

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Satz, Alexander L., and Weiren Cui. "Analysis of DNA-Encoded Library Screening Data: Selection of Molecules for Synthesis." In Methods in Molecular Biology, 195–205. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2545-3_23.

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Csakai, Adam, Yun Ding, Melissa C. Grenier-Davies, Lisa A. Marcaurelle, and Ann M. Rowley. "Reaction Development for DNA-Encoded Library Technology: Expanding the Toolkit on DNA Chemistry." In 2021 Medicinal Chemistry Reviews, 413–41. Medicinal Chemistry Division of the American Chemical Society, 2021. http://dx.doi.org/10.29200/acsmedchemrev-v56.ch17.

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Conference papers on the topic "DNA Encoded Library"

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Arora, Shilpi, Chris Hupp, Sarah Talcott, Usha Narayanan, Diana Gikunju, Mortiz Von Rechenberg, Michael I. Monteiro, et al. "Abstract C049: Identification of novel K-Ras G12C inhibitors using a DNA encoded library platform." In Abstracts: AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; October 26-30, 2019; Boston, MA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1535-7163.targ-19-c049.

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McCort, Gary, Rosalia Arrebola, Loreley Calvet, Baptiste Ronan, Fabrice Vergne, Francis Duffieux, Alexey Rak, et al. "Abstract 3070: Discovery of novel potent allele-selective KRAS-G12C covalent inhibitors stemming from DNA-encoded library." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-3070.

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McCort, Gary, Rosalia Arrebola, Loreley Calvet, Baptiste Ronan, Fabrice Vergne, Francis Duffieux, Alexey Rak, et al. "Abstract 3070: Discovery of novel potent allele-selective KRAS-G12C covalent inhibitors stemming from DNA-encoded library." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-3070.

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Andersen, Jannik N., Andrew J. McRiner, Lynette A. Fouser, Junyi Zhang, Shilpi Arora, Michael Cordeau, Ying Zhang, et al. "Abstract 981: Degradation of immuno-oncology targets via proprietary PROTAC platform integrating DNA-encoded library technology and rational drug design." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-981.

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Andersen, Jannik N., Andrew J. McRiner, Lynette A. Fouser, Junyi Zhang, Shilpi Arora, Michael Cordeau, Ying Zhang, et al. "Abstract 981: Degradation of immuno-oncology targets via proprietary PROTAC platform integrating DNA-encoded library technology and rational drug design." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-981.

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McRiner, Andrew J., Jannik N. Andersen, Lynette A. Fouser, Junyi Zhang, Kaan Certel, John Cuozzo, Betty Chan, et al. "Abstract 4453: Novel, potent, and selective small-molecule inhibitors modulating immuno-oncology targets CD73, A2A/A2Badenosine receptors and CSF1R discovered via DNA-encoded library screening." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-4453.

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McRiner, Andrew J., Jannik N. Andersen, Lynette A. Fouser, Junyi Zhang, Kaan Certel, John Cuozzo, Betty Chan, et al. "Abstract 4453: Novel, potent, and selective small-molecule inhibitors modulating immuno-oncology targets CD73, A2A/A2Badenosine receptors and CSF1R discovered via DNA-encoded library screening." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-4453.

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Reports on the topic "DNA Encoded Library"

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Lichter, Amnon, Gopi K. Podila, and Maria R. Davis. Identification of Genetic Determinants that Facilitate Development of B. cinerea at Low Temperature and its Postharvest Pathogenicity. United States Department of Agriculture, March 2011. http://dx.doi.org/10.32747/2011.7592641.bard.

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Botrytis cinerea is the postharvest pathogen of many agricultural produce with table grapes, strawberries and tomatoes as major targets. The high efficiency with which B. cinerea causes disease on these produce during storage is attributed in part due to its exceptional ability to develop at very low temperature. Our major goal was to understand the genetic determinants which enable it to develop at low temperature. The specific research objectives were: 1. Identify expression pattern of genes in a coldenriched cDNA library. 2. Identify B. cinerea orthologs of cold-induced genes 3. Profile protein expression and secretion at low temperature on strawberry and grape supplemented media. 4. Test novel methods for the functional analysis of coldresponsive genes. Objective 1 was modified during the research because a microarray platform became available and it allowed us to probe the whole set of candidate genes according to the sequence of 2 strains of the fungus, BO5.10 and T4. The results of this experiment allowed us to validate some of our earlier observations which referred to genes which were the product of a SSH suppression-subtraction library. Before the microarray became available during 2008 we also analyzed the expression of 15 orthologs of cold-induced genes and some of these results were also validated by the microarray experiment. One of our goals was also to perform functional analysis of cold-induced genes. This goal was hampered for 3 years because current methodology for transformation with ‘protoplasts’ failed to deliver knockouts of bacteriordopsin-like (bR) gene which was our primary target for functional analysis. Consequently, we developed 2 alternative transformation platforms, one which involves an air-gun based technique and another which involves DNA injection into sclerotia. Both techniques show great promise and have been validated using different constructs. This contribution is likely to serve the scientific community in the near future. Using these technologies we generated gene knockout constructs of 2 genes and have tested there effect on survival of the fungus at low temperature. With reference to the bR genes our results show that it has a significant effect on mycelial growth of the B. cinerea and the mutants have retarded development at extreme conditions of ionic stress, osmotic stress and low temperature. Another gene of unknown function, HP1 is still under analysis. An ortholog of the yeast cold-induced gene, CCH1 which encodes a calcium tunnel and was shown to be cold-induced in B. cinerea was recently cloned and used to complement yeast mutants and rescue them from cold-sensitivity. One of the significant findings of the microarray study involves a T2 ribonuclease which was validated to be cold-induced by qPCR analysis. This and other genes will serve for future studies. In the frame of the study we also screened a population of 631 natural B. cinerea isolates for development at low temperature and have identified several strains with much higher and lower capacity to develop at low temperature. These strains are likely to be used in the future as candidates for further functional analysis. The major conclusions from the above research point to specific targets of cold-induced genes which are likely to play a role in cold tolerance. One of the most significant observations from the microarray study is that low temperature does not induce ‘general stress response in B. cinerea, which is in agreement to its exceptional capacity to develop at low temperature. Due to the tragic murder of the Co-PI Maria R. Davis and GopiPodila on Feb. 2010 it is impossible to deliver their contribution to the research. The information of the PI is that they failed to deliver objective 4 and none of the information which relates to objective 3 has been delivered to the PI before the murder or in a visit to U. Alabama during June, 2010. Therefore, this report is based solely on the IS data.
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