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Littérature scientifique sur le sujet « Target binding »

Auteur : Grafiati

Publié le 11 mars 2023

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Target binding"

Park, Keunwan, Young-Joon Ko, Prasannavenkatesh Durai, and Cheol-Ho Pan. "Machine learning-based chemical binding similarity using evolutionary relationships of target genes." Nucleic Acids Research 47, no. 20 (2019): e128-e128. http://dx.doi.org/10.1093/nar/gkz743.

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Abstract Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional activity related to target binding often fails. To overcome this limitation, we developed a novel machine learning-based chemical binding similarity score by using various evolutionary relationships of binding targets. The chemical similarity was defined by the probability of chemical compounds binding to identical targets. Comprehensive and

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Cheung, S. H., G. E. Legge, S. T. L. Chung, and B. S. Tjan. "Target-flanker binding releases crowding." Journal of Vision 6, no. 6 (2010): 807. http://dx.doi.org/10.1167/6.6.807.

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JOHNSTON, Angus, and Eva VAN DER MAREL. "How Binding are the EU’s ‘Binding’ Renewables Targets?" Cambridge Yearbook of European Legal Studies 18 (August 9, 2016): 176–214. http://dx.doi.org/10.1017/cel.2016.7.

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AbstractThe EU’s current renewable energy legislation sets a binding EU target for renewables as a share of overall energy consumption, allied with binding national targets for renewables as well. Yet the precise implications of having imposed such ‘mandatory’ binding targets have received little attention to date. This contribution examines the history and evolution of such targets, the context within which they must be pursued and applied, and some of the problems in and prospects for their enforcement and effectiveness. Comparisons are drawn with other areas of EU law where appropriate and

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POOLSAP, UNYANEE, YUKI KATO, KENGO SATO, and TATSUYA AKUTSU. "USING BINDING PROFILES TO PREDICT BINDING SITES OF TARGET RNAs." Journal of Bioinformatics and Computational Biology 09, no. 06 (2011): 697–713. http://dx.doi.org/10.1142/s0219720011005628.

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Prediction of RNA–RNA interaction is a key to elucidating possible functions of small non-coding RNAs, and a number of computational methods have been proposed to analyze interacting RNA secondary structures. In this article, we focus on predicting binding sites of target RNAs that are expected to interact with regulatory antisense RNAs in a general form of interaction. For this purpose, we propose bistaRNA, a novel method for predicting multiple binding sites of target RNAs. bistaRNA employs binding profiles that represent scores for hybridized structures, leading to reducing the computationa

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Molina, Daniel Martinez, Rozbeh Jafari, Marina Ignatushchenko, et al. "Monitoring Drug Target Engagement in Cells and Tissues Using the Cellular Thermal Shift Assay." Science 341, no. 6141 (2013): 84–87. http://dx.doi.org/10.1126/science.1233606.

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The efficacy of therapeutics is dependent on a drug binding to its cognate target. Optimization of target engagement by drugs in cells is often challenging, because drug binding cannot be monitored inside cells. We have developed a method for evaluating drug binding to target proteins in cells and tissue samples. This cellular thermal shift assay (CETSA) is based on the biophysical principle of ligand-induced thermal stabilization of target proteins. Using this assay, we validated drug binding for a set of important clinical targets and monitored processes of drug transport and activation, off

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Briskin, Daniel, Peter Y. Wang, and David P. Bartel. "The biochemical basis for the cooperative action of microRNAs." Proceedings of the National Academy of Sciences 117, no. 30 (2020): 17764–74. http://dx.doi.org/10.1073/pnas.1920404117.

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In cells, closely spaced microRNA (miRNA) target sites within a messenger RNA (mRNA) can act cooperatively, leading to more repression of the target mRNA than expected by independent action at each site. Using purified miRNA-Argonaute (AGO2) complexes, synthetic target RNAs, and a purified domain of TNRC6B (GW182 in flies) that is able to simultaneously bind multiple AGO proteins, we examined both the occupancies and binding affinities of miRNA-AGO2 complexes and target RNAs with either one site or two cooperatively spaced sites. On their own, miRNA-AGO2 complexes displayed little if any coope

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KUMAR, YOGESH, and FEROZ KHAN. "Detection of aroma compound’s binding mode conformations on anticancer target DNA topoisomerase II." Journal of Medicinal and Aromatic Plant Sciences 40, no. 3 (2018): 40–48. http://dx.doi.org/10.62029/jmaps.v40i3.kumar.

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Cancer is one of the most common, devastating class of disease affecting millions of people causing large number of death every year. It is therefore considered to be the second leading cause of death in developing countries next to cardiovascular diseases. Recent molecular studies have focussed on the most targeted gene for cancer i.e. DNA topoisomerase II (DNA TOP2), an enzyme that controls and alters the topological states of DNA during transcription. DNA TOP2 is also a target of known anticancer drugs like etoposide, doxorubicin, daunorubicin, amsacrine, amrubicin, and many others. These d

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Jadhav, Sagar Ashok, Payal Chavan, Supriya Suresh Shete, et al. "In Silico ADMET and Docking Study of Selected Drug Used in Therapy of COVID-19." Journal of Pharmaceutical Technology, Research and Management 10, no. 1 (2022): 47–73. http://dx.doi.org/10.15415/jptrm.2022.101006.

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Docking is one of the most widely utilized technique used method in structure -based drug design because of its capability to predict the binding conformation of ligands to appropriate target. Ability of binding/ affinity towards the target i.e., bioactive peptides or specific receptor provides strong evidence of binding conformation pattern and affinity for further investigation. Aim- The present study was conducted for evaluation of current API’s potential used in COVID-19. Methods: In-silico molecular docking was performed using softwares such as SWISS ADME, MOLSOFT, MOLINSPIRATION, PYMOL,

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Tan, Zhixin Cyrillus, Brian T. Orcutt-Jahns, and Aaron S. Meyer. "A quantitative view of strategies to engineer cell-selective ligand binding." Integrative Biology 13, no. 11 (2021): 269–82. http://dx.doi.org/10.1093/intbio/zyab019.

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Abstract A critical property of many therapies is their selective binding to target populations. Exceptional specificity can arise from high-affinity binding to surface targets expressed exclusively on target cell types. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multivalent molecules, creating a combinatorial explosion of design possibilities. Guiding strategies for developing cell-specific binding are critic

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Lipovsek, D. "Adnectins: engineered target-binding protein therapeutics." Protein Engineering Design and Selection 24, no. 1-2 (2010): 3–9. http://dx.doi.org/10.1093/protein/gzq097.

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Thèses sur le sujet "Target binding"

Collins, K. M. "Target recognition by multi-domain RNA-binding proteins." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1460867/.

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Multi-functional RNA binding proteins regulate and coordinate the many steps of RNA metabolism. Accurate functioning of these processes is vital in cells and misregulation has been linked to many human diseases. RNA binding proteins contain multiple RNA binding domains. The ability to perform multiple functions depends on the recognition of a diverse range of targets and domains are used combinatorially to achieve this. In this thesis I ask how the sequence specificity of low affinity RNA-binding domains and the interplay between said domains plays a role in RNA target selectivity. Within this

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Bolotin, Eugene Leonidovich. "Investigation of transcription factor binding sequences and target genes using protein binding microarrays." Diss., [Riverside, Calif.] : University of California, Riverside, 2010. http://proquest.umi.com/pqdweb?index=0&did=2019822801&SrchMode=2&sid=3&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1274203752&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2010.<br>Includes abstract. Available via ProQuest Digital Dissertations. Title from first page of PDF file (viewed May 18, 2010). Includes bibliographical references. Also issued in print.

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Djurberg, Klara. "Applying Model Selection on Ligand-Target Binding Kinetic Analysis." Thesis, KTH, Proteinvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302137.

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The time-course of interaction formation or breaking can be studied using LigandTracer, and the data obtained from an experiment can be analyzed using a model of ligand-target binding kinetics. There are different kinetic models, and the choice of model is currently motivated by knowledge about the interaction, which is problematic when the knowledge about the interaction is unsatisfactory. In this project, a Bayesian model selection procedure was implemented to motivate the model choice using the data obtained from studying a biological system. The model selection procedure was implemented fo

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Zhao, Qian, and 赵倩. "Identification of a binding target of triptolide and related studies." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48199163.

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Triptolide, a diterpene triepoxide extracted from traditional Chinese medicinal herb Tripterygium wilfordii Hook. F has been shown to have profound inhibitory effects against tumor progression, pathological angiogenesis and inflammation. However, the mechanisms by which triptolide exerts these effects remain unclear. To understand its cellular mode of action, biotinylated/desthiobiotinylated and fluorophore-labeled triptolide derivatives were used as probes to identify cellular proteins that bind to triptolide. By using two different approaches for screening drug-protein interactions, the m

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Kasturi, Rama. "Kinetics of calmodulin binding to its smooth muscle target proteins /." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487694702782747.

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Xie, He Fang. "Understanding the interaction between xylan-binding domains and their target ligands." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324858.

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Chapman, Edwin R. "Functional domains of neuromodulin and the interaction of calmodulin with target peptides /." Thesis, Connect to this title online; UW restricted, 1992. http://hdl.handle.net/1773/6288.

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Farnie, Gillian. "MDM2-p53 binding interaction as a potential therapeutic target for cancer." Thesis, University of Newcastle Upon Tyne, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437553.

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Ma, Jun. "Mass Spectrometry Method Development to Identify Binding Ligands Against A2AR Nanodisc Complex." Thesis, Griffith University, 2017. http://hdl.handle.net/10072/380580.

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Protein is essential for human physiological processes and signalling pathways. Mass spectrometry (MS) is an important tool for ligand identification against protein target. This project aims to establish an MS-based ligand identification method towards neurodegenerative disease-related protein targets, including cytosolic LRRK2 protein, adenosine A2A receptor (A2AR), and α2-adrenergic receptor (α2AR). The LRRK2 subdomains (Roc/GTPase, COR, and MAPKKK/kinase) and GPCRs (A2AR, A2AR-GFP, and α2AR) were cloned, sequenced, expressed and purified for MS assay. The proteins were solubilised in diffe

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Zhou, Yiqing, and 周怡青. "Identification of a cellular target of triptonide and its functional study." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46923561.

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Livres sur le sujet "Target binding"

Symposium on RNA Biology (2nd 1997 North Carolina Biotechnology Center). Symposium on RNA Biology: RNA tool and target : held at North Carolina Biotechnology Center, Research Triangle Park, North Carolina, USA, October 17-19, 1997. Oxford University Press, 1997.

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Snoeck, Eric. Mechanism-based pharmacokinetic-pharmacodynamic modelling of specific target site binding to red blood cells: Application to the development of draflazine. University of Leiden, 1998.

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Podjarny, Alberto, Annick P. Dejaegere, and Bruno Kieffer, eds. Biophysical Approaches Determining Ligand Binding to Biomolecular Targets. Royal Society of Chemistry, 2011. http://dx.doi.org/10.1039/9781849732666.

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Ponte-Sucre, Alicia. ABC transporters in microorganisms: Research, innovation and value as targets against drug resistance. Caister Academic, 2009.

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Chandrudu, M. V. Rama. Bench marking of APRLP processes: Binding the programs with processes : redefining targets. WASSAN, 2006.

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Lans, Martine C. Thyroid hormone binding proteins as novel targets for hydroxylated polyhalogenated aromatic hydrocarbons (PHAHs): Possible implications for toxicity. [s.n.], 1995.

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Dufau, Maria. Hormone Binding and Target Cell Activation in the Testis. Springer, 2013.

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Dufau, Maria. Hormone Binding and Target Cell Activation in the Testis. Springer, 2012.

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Matulis, Daumantas. Carbonic Anhydrase as Drug Target: Thermodynamics and Structure of Inhibitor Binding. Springer, 2019.

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Ming, Liang. Identification of DNA-binding domains and target genes of the Hindsight zinc-finger protein. 2006.

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Chapitres de livres sur le sujet "Target binding"

Copeland, Robert A. "Drug-Target Residence Time." In Thermodynamics and Kinetics of Drug Binding. Wiley-VCH Verlag GmbH & Co. KGaA, 2015. http://dx.doi.org/10.1002/9783527673025.ch8.

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Norden, Diana M., and Benjamin J. Doranz. "Testing for Off-target Binding." In Translational Medicine. CRC Press, 2021. http://dx.doi.org/10.1201/9781003124542-13.

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Rodríguez, Santiago, Juan I. Alice, Carolina L. Bellera, and Alan Talevi. "Structure-Based Binding Pocket Detection and Druggability Assessment." In Drug Target Selection and Validation. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95895-4_5.

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Kairys, Visvaldas, Kliment Olechnovič, Vytautas Raškevičius, and Daumantas Matulis. "In Silico Modeling of Inhibitor Binding to Carbonic Anhydrases." In Carbonic Anhydrase as Drug Target. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12780-0_15.

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Paketurytė, Vaida, Asta Zubrienė, Wen-Yih Chen, et al. "Inhibitor Binding to Carbonic Anhydrases by Isothermal Titration Calorimetry." In Carbonic Anhydrase as Drug Target. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12780-0_6.

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Petrauskas, Vytautas, Asta Zubrienė, Matthew J. Todd, and Daumantas Matulis. "Inhibitor Binding to Carbonic Anhydrases by Fluorescent Thermal Shift Assay." In Carbonic Anhydrase as Drug Target. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12780-0_5.

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Zubrienė, Asta, and Daumantas Matulis. "Observed Versus Intrinsic Thermodynamics of Inhibitor Binding to Carbonic Anhydrases." In Carbonic Anhydrase as Drug Target. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12780-0_8.

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Demchenko, Alexander P. "Basic Theoretical Description of Sensor-Target Binding." In Introduction to Fluorescence Sensing. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19089-6_2.

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Smirnov, Alexey, Elena Manakova, and Daumantas Matulis. "Correlations Between Inhibitor Binding Thermodynamics and Co-crystal Structures with Carbonic Anhydrases." In Carbonic Anhydrase as Drug Target. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12780-0_17.

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Skvarnavičius, Gediminas, Daumantas Matulis, and Vytautas Petrauskas. "Change in Volume Upon Inhibitor Binding to Carbonic Anhydrases by Fluorescent Pressure Shift Assay." In Carbonic Anhydrase as Drug Target. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12780-0_7.

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Actes de conférences sur le sujet "Target binding"

Prakash, M. Sudharsan, G. Meenakashi, and Margaret Marry T. "Feature Extraction of Drug–Target Interactions Usingmodified Transformer Binding Phase." In 2024 2nd International Conference on Recent Advances in Information Technology for Sustainable Development (ICRAIS). IEEE, 2024. https://doi.org/10.1109/icrais62903.2024.10811734.

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Majumder, Subhasree, and Debnath Pal. "Prediction of Small Molecules Binding Site with RNA as a Target." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10726012.

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Wu, Yulong, Jin Xie, Jing Nie, Xiaohong Zhang, and Yuansong Zeng. "Mamba-DTA: Drug-Target Binding Affinity Prediction with State Space Model." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822594.

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Tu, Xinyi, Zhe Li, and Wenbin Lin. "SE-DTA: A Spatial Equivariant Network for Drug-Target Binding Affinity Prediction." In 2024 9th International Conference on Intelligent Computing and Signal Processing (ICSP). IEEE, 2024. http://dx.doi.org/10.1109/icsp62122.2024.10743565.

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Rose, Tyler, Charlotte Zhou, and Nicolò Monti. "AffinityLM: Binding-Site Informed Multitask Language Model for Drug-Target Affinity Prediction." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822722.

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Wu, Yulong, Jin Xie, Jing Nie, Jian Hu, and Yuansong Zeng. "Dual Interaction and Kernel-Diverse Network for Accurate Drug-Target Binding Affinity Prediction." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822466.

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Wang, Jiao, Ge Kong, and Juan Wang. "MLFF-DTA: A Multi-Level Feature Fusion Method for Predicting Drug-Target Binding Affinity." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822747.

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Song, Tao, Siyu Zhang, Xiangyu Meng, Zeyang Zhu, Xianxi Zhu, and Xun Wang. "DCUI-MGraphDTA: Enabling Efficient Inference of a Drug-Target Binding Affinity Prediction Model on DCUs." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10821809.

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Li, Huiting, Weiyu Zhang, Yong Shang, and Wenpeng Lu. "MBC-DTA: A Multi-Scale Bilinear Attention with Contrastive Learning Framework for Drug-Target Binding Affinity Prediction." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822403.

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Garg, Ayush, Shyam Sundar Das, and Narayanan Ramamurthi. "Drug Target Prioritization Based on Ligand Binding Pocket and Disease-Target Association Scores." In BCB '23: 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM, 2023. http://dx.doi.org/10.1145/3584371.3613058.

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Rapports d'organisations sur le sujet "Target binding"

Beerman, Terry A. Discovery of DNA Binding Anticancer Drugs That Target Oncogenic Transcription Factors Associated With Human Breast Cancer. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada403322.

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DeSombre, E. R. Receptor-DNA binding to target auger electrons for cancer therapy. Final report, August 1, 1993--January 31, 1997. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/477720.

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Whitham, Steven A., Amit Gal-On, and Victor Gaba. Post-transcriptional Regulation of Host Genes Involved with Symptom Expression in Potyviral Infections. United States Department of Agriculture, 2012. http://dx.doi.org/10.32747/2012.7593391.bard.

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Understanding how RNA viruses cause disease symptoms in their hosts is expected to provide information that can be exploited to enhance modern agriculture. The helper component-proteinase (HC-Pro) protein of potyviruses has been implicated in symptom development. Previously, we demonstrated that symptom expression is associated with binding of duplex small-interfering-RNA (duplex-siRNA) to a highly conserved FRNK amino acid motif in the HC-Pro of Zucchini yellow mosaic virus (ZYMV). This binding activity also alters host microRNA (miRNA) profiles. In Turnip mosaic virus (TuMV), which infects t

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Kolodny, Gerald M., and Joel Yisraeli. Riboswitch-Mediated Aptamer Binding for Imaging and Therapy (RABIT): A Novel Technique to Selectively Target an Intracellular Ligand Specific for Ovarian Cancer. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada613755.

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Thongtan, Thananya, Poonlarp Cheepsunthorn, and Kiat Ruxrungtham. An analysis and studies expression of receptor molecule on microglia cells to inhibits infection of the cells from Japanese encephalitis virus : Research report (Year 2009). Chulalongkorn University, 2009. https://doi.org/10.58837/chula.res.2009.14.

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Japanese encephalitis virus (JEV), a mosquito-borne flavivirus, is a major cause of viral encephalitis in Asia. Even though the principle target cells for JEV in the central nervous system are neurons, the microglia is activated in response to JEV infection. This research aimed to investigate the relationship between JEV and microglial cells. The percentage of JEV infectivity in mouse microglial (BV-2) cell line at 8, 15 and 24 hr post infection was determined by flow cytometry. It was found that the percentage of infected cells were approximately 53.5, 71.3 and 83.6 respectively. The JEV bind

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Rahimipour, Shai, and David Donovan. Renewable, long-term, antimicrobial surface treatments through dopamine-mediated binding of peptidoglycan hydrolases. United States Department of Agriculture, 2012. http://dx.doi.org/10.32747/2012.7597930.bard.

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There is a need for renewable antimicrobial surface treatments that are semi- permanent, can eradicate both biofilms and planktonic pathogens over long periods of time and that do not select for resistant strains. This proposal describes a dopamine binding technology that is inexpensive, bio-friendly, non-toxic, and uses straight-forward commercially available products. The antimicrobial agents are peptidoglycanhydrolase enzymes that are non-toxic and highly refractory to resistance development. The goal of this project is to create a treatment that will be applicable to a wide variety of surf

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Fromm, Hillel, and Joe Poovaiah. Calcium- and Calmodulin-Mediated Regulation of Plant Responses to Stress. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568096.bard.

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We have taken a molecular approach to clone cellular targets of calcium/calmodulin (Ca2+/CaM). A 35S-labeled recombinant CaM was used as a probe to screen various cDNA expression libraries. One of the isolated clones from petunia codes for the enzyme glutamate decarboxylase (GAD) which catalyzes the conversion of glutamate to g-aminobutyric acid (GABA). The activity of plant GAD has been shown to be dramatically enhanced in response to cold and heat shock, anoxia, drought, mechanical manipulations and by exogenous application of the stress phytohormone ABA in wheat roots. We have purified the

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Chanprateep Napathorn, Suchada, and Tanapat Palaga. Expression of novel fusion proteins IL2/FU-MK-1-scFv in microorganism-host cells and its potential anti-tumor activities as a cytotoxic immunotherapy agent for FU-MK-1 expressing tumors. Chulalongkorn University, 2012. https://doi.org/10.58837/chula.res.2012.25.

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MK-1, the target molecule of FU-MK-1, is encoded by the GA733-2 gene, which is currently being used as a target in clinical trials for gastric, intestinal, and biliary cancer treatment with monoclonal antibodies. Here, two different arrangement of heavy-chain and K light-chain variable fusion gene, IL2/FUscFv(VK-VH) or IL2/FUscFv(VWVK), were constructed. The efficiency of protein expression in prokaryotic host expression system, Escherichia coli strains BL21(DE3)pLysS and Rosetta-gami B was compared with eukaryotic host expression system, Pichia pastoris strains GS115 and KM71H, for their abil

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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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Résumé :

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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