Relevant bibliographies by topics / Ligand based virtual screening

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Ligand based virtual screening'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 January 2023

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Journal articles on the topic "Ligand based virtual screening"

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Kato, Koya, and George Chikenji. "1P266 Development of Ligand Based Virtual Screening considering protein-ligand interaction(22A. Bioinformatics: Structural genomics,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S150. http://dx.doi.org/10.2142/biophys.53.s150_1.

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Douguet, Dominique. "Ligand-Based Approaches in Virtual Screening." Current Computer Aided-Drug Design 4, no. 3 (September 1, 2008): 180–90. http://dx.doi.org/10.2174/157340908785747456.

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Stahura, Florence, and Jürgen Bajorath. "New Methodologies for Ligand-Based Virtual Screening." Current Pharmaceutical Design 11, no. 9 (April 1, 2005): 1189–202. http://dx.doi.org/10.2174/1381612053507549.

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Ahmed, Ali, Naomie Salim, and Ammar Abdo. "Fragment Reweighting in Ligand-Based Virtual Screening." Advanced Science Letters 19, no. 9 (September 1, 2013): 2782–86. http://dx.doi.org/10.1166/asl.2013.5012.

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HIRAYAMA, Noriaki. "Virtual Screening Based on Protein-Ligand Interactions." YAKUGAKU ZASSHI 127, no. 1 (January 1, 2007): 101–2. http://dx.doi.org/10.1248/yakushi.127.101.

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Jain, Ajay N. "Ligand-Based Structural Hypotheses for Virtual Screening." Journal of Medicinal Chemistry 47, no. 4 (February 2004): 947–61. http://dx.doi.org/10.1021/jm030520f.

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Abdo, Ammar, Beining Chen, Christoph Mueller, Naomie Salim, and Peter Willett. "Ligand-Based Virtual Screening Using Bayesian Networks." Journal of Chemical Information and Modeling 50, no. 6 (May 26, 2010): 1012–20. http://dx.doi.org/10.1021/ci100090p.

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Dai, Weixing, and Dianjing Guo. "A Ligand-Based Virtual Screening Method Using Direct Quantification of Generalization Ability." Molecules 24, no. 13 (June 30, 2019): 2414. http://dx.doi.org/10.3390/molecules24132414.

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Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient when dealing with such problems where the data are imbalanced and features describing the chemical characteristic of ligands are high-dimensional. We here describe a machine learning algorithm LBS (local beta screening) for ligand-based virtual screening. The unique characteristic of LBS is that it quantifies the generalization ability of screening directly by a refined loss function, and thus can assess the risk of over-fitting accurately and efficiently for imbalanced and high-dimensional data in ligand-based virtual screening without the help of resampling methods such as cross validation. The robustness of LBS was demonstrated by a simulation study and tests on real datasets, in which LBS outperformed conventional algorithms in terms of screening accuracy and model interpretation. LBS was then used for screening potential activators of HIV-1 integrase multimerization in an independent compound library, and the virtual screening result was experimentally validated. Of the 25 compounds tested, six were proved to be active. The most potent compound in experimental validation showed an EC50 value of 0.71 µM.
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Kato, Koya, and George Chikenji. "2P272 A Ligand Based Virtual Screening method that takes into account of protein-ligand interactions(22A. Bioinformatics:Structural genomics,Poster)." Seibutsu Butsuri 54, supplement1-2 (2014): S240. http://dx.doi.org/10.2142/biophys.54.s240_2.

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Rayevsky, O. V., O. M. Demchyk, P. A. Karpov, S. P. Ozheredov, S. I. Spivak, A. I. Yemets, and Ya B. Blume. "Structure-based virtual screening for new lead compounds targeted Plasmodium α-tubulin." Faktori eksperimental'noi evolucii organizmiv 28 (August 31, 2021): 135–39. http://dx.doi.org/10.7124/feeo.v28.1389.

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Aim. Search for new dinitroaniline and phosphorothioamide compounds, capable of selective binding with Plasmodium α-tubulin, affecting its mitotic apparatus. Methods. Structural biology methods of computational prediction of protein-ligand interaction: molecular docking, molecular dynamics and pharmacophore analysis. Selection of compounds based on pharmacophore characteristics and virtual screening results. Results. The protocol and required structural conditions for target (α-tubulin of P. falciparum) preparation and correct modeling of the ligand-protein interaction (docking and virtual screening) were developed. The generalized pharmacophore model of ligand-protein interaction and key functional groups of ligands responsible for specific binding were identified. Conclusions. Based on results of virtual screening, 22 commercial compounds were selected. Identified compounds proposed as potential inhibitors of Plasmodium mitotic machinery and the base of new antimalarial drugs. Keywords: malaria, Plasmodium, intermolecular interaction, dinitroaniline derived, phosphorothioamidate derived.
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Dissertations / Theses on the topic "Ligand based virtual screening"

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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 applied to both the structural and ligand based approaches. A proven structure based virtual screening code LIDAEUS (Ligand Discovery At Edinburgh University) has been ported and parallelised to a massively parallel computing platform, the University of Edinburgh’s IBM Bluegene/l, consisting of 2,048 processor cores. A challenge in achieving scaling to such a large number of processors required implementation of a minimal communication parallel sort algorithm. Parallel efficiencies achieved within this parallelisation exceeded 99%, confirming that a near optimum strategy has been followed and capacity for running the code on a greater number of processors exists. This implementation of the program has been successfully used with a number of protein targets. The development of a new ligand based virtual screening code has been completed. The program UFSRAT (Ultra Fast Shape Recognition with Atom Types) takes the features of known binders and suggests molecules which will be able to make similar interactions. This similarity method is both fast (1 million molecules per hour per processor) and independent of input orientation. Along with UFSRAT, some other methods (VolRAT and UFSRGraph) based on UFSRAT have been developed, addressing different approaches to ligand based virtual screening. UFSRAT as an approach to discovering novel protein-ligand complexes has been validated with the discovery of a number of inhibitors for 11β-Hydroxysteroid Dehydrogenase type 1 and FK binding protein 12.
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Mazalan, Lucyantie. "Evaluation of similarity measures for ligand-based virtual screening." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/21422/.

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Alaasam, Mohammed. "Identification of novel monoamine oxidase B inhibitors from ligand based virtual screening." Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1405439915.

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Heikamp, Kathrin [Verfasser]. "Application and Development of Computational Methods for Ligand-Based Virtual Screening / Kathrin Heikamp." Bonn : Universitäts- und Landesbibliothek Bonn, 2014. http://d-nb.info/1052061036/34.

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Gregori, Puigjané Elisabet. "A new Ligand-Based approach to virtual screening, and prolifing or large chemical libraries." Doctoral thesis, Universitat Pompeu Fabra, 2008. http://hdl.handle.net/10803/7166.

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La representació de les molècules per mitjà de descriptors moleculars és la base de moltes de les eines computacionals pel disseny de fàrmacs. Aquests mètodes computacionals es basen en l'abstracció de l'estructura química per resumir aquelles característiques rellevants sent al mateix temps eficients en la comparació de grans llibreries de molècules. Una característica molt important d'aquests descriptors és la seva habilitat de capturar la informació rellevant per la interacció amb qualsevol proteïna independentment de l'esquelet del compost. Això permet detectar com a similars qualsevol parella de compostos amb les mateixes característiques ordenades de la mateixa manera al voltant d'esquelets essencialment diferents, una propietat a la qual hom es refereix com a "scaffold hopping". Tenint en compte això, un nou conjunt de descriptors basat en la distribució de parelles de característiques farmacofòriques centrades en els àtoms per mitjà del concepte de teoria de la informació de l'entropia de Shannon [1], anomenats SHED, s'han desenvolupat.
Aquests descriptors han sigut usats amb èxit en nombroses aplicacions importants en el procés de descoberta de fàrmacs. Després de la implementació de noves tecnologies in vitro com ara el "high-throughput screening" i la química combinatòria, la capacitat de sintetitzar i assajar compostos va augmentar exponencialment però alhora la necessitat d'una selecció racional dels compostos va fer-se patent. La priorització dels compostos en termes de la predicció de la seva probabilitat de mostrar la activitat desitjada és per tant una de les primeres aplicacions del perfilat virtual basat en lligands usant els descriptors SHED.
En realitat, aquesta metodologia es pot estendre al punt de vista quimiogenòmic del procés de descoberta de fàrmacs, usant els descriptors per generar models basats en ligands de totes les proteïnes amb informació de lligands. Aquesta aproximació més ampla, el perfilat virtual de proteïnes, és un pas més per completar la matriu d'activitat entre tots els possibles compostos químics i totes les proteïnes rellevants. A més, una anàlisi més aprofundida d'aquesta matriu completa generada per mitjà del perfilat virtual de proteïnes pot dur-nos a una perspectiva de farmacologia en xarxa del procés de descoberta de fàrmacs. Aquesta direcció pot ser seguida afegint a aquesta informació de lligands i proteïnes la informació relativa a rutes de reaccions i anàlisi de sistemes, donant lloc a l'anomenada biologia química de sistemes que pot ajudar a entendre els processos biològics com un conjunt i a identificar de manera més racional noves i prometedores dianes terapèutiques.
The representation of molecules by means of molecular descriptors is the basis of most of the computational tools for drug design. These computational methods are based on the abstraction from the chemical structure to summarize its relevant features while being efficient in the comparison of large molecule libraries. A very important feature of these descriptors is their ability to capture the information relevant for the interaction with any target independently from the scaffold of the compound. This will allow detecting as similar any two compounds with the same features arranged in the same way around essentially different scaffolds, a property referred to as scaffold hopping. With this in mind, a new set of descriptors based on the distribution of atom-centred pharmacophoric feature pairs by means of the information theory concept of Shannon entropy [1], called SHED, have been developed.
These descriptors have been successfully used in a number of applications important in the drug discovery process. After the implementation of novel in vitro technologies like high-throughput screening and combinatorial chemistry, the capacity of synthesizing and testing compounds increased exponentially but the need for a rational selection of the compounds arose as well. The prioritisation of compounds in terms of their predicted chances of displaying the targeted activity is thus one of the first applications of the ligand-based virtual ligand screening based on SHED descriptors. This application has shown very good results, both in terms of enrichment of actives in the hit list and in terms of scaffold hopping ability, i.e. the novelty of the scaffolds of the found actives in the top ranked compounds.
Actually, this methodology can be extended to a chemogenomics view of the drug discovery process, using the descriptors to build ligand-based models of all the proteins with any ligand information. This broader approach, the virtual target profiling, is a step towards completing the activity matrix between all possible chemical compounds and all relevant targets. Moreover, a deeper analysis of this complete matrix generated by virtual target profiling can lead us to a network pharmacology perspective of the drug discovery process. This direction can be further followed by adding to ligand-target information the information about pathways and systems approaches, leading to a systems chemical biology approach that could help understanding biological processes as a whole and identifying more rationally novel and promising drug targets.
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Tai, Hio Kuan. "Protein-ligand docking and virtual screening based on chaos-embedded particle swarm optimization algorithm." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3948431.

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Behren, Mathias Michael von Verfasser], and Matthias [Akademischer Betreuer] [Rarey. "Ligand-based Virtual Screening Utilizing Partial Shape Constraints / Mathias Michael von Behren ; Betreuer: Matthias Rarey." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2017. http://nbn-resolving.de/urn:nbn:de:gbv:18-86060.

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Behren, Mathias Michael von [Verfasser], and Matthias [Akademischer Betreuer] Rarey. "Ligand-based Virtual Screening Utilizing Partial Shape Constraints / Mathias Michael von Behren ; Betreuer: Matthias Rarey." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2017. http://d-nb.info/113732371X/34.

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Santos, Alan Diego dos. "Ranking ligands in structure-based virtual screening using siamese neural networks." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2017. http://tede2.pucrs.br/tede2/handle/tede/7763.

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Triagem virtual de bancos de dados de ligantes ? amplamente utilizada nos est?gios iniciais do processo de descoberta de f?rmacos. Abordagens computacionais ?docam? uma pequena mol?cula dentro do s?tio ativo de um estrutura biol?gica alvo e avaliam a afinidade das intera??es entre a mol?cula e a estrutura. Todavia, os custos envolvidos ao aplicar algoritmos de docagem molecular em grandes bancos de ligantes s?o proibitivos, dado a quantidade de recursos computacionais necess?rios para essa execu??o. Nesse contexto, estrat?gias de aprendizagem de m?quina podem ser aplicadas para ranquear ligantes baseadas na afinidade com determinada estrutura biol?gica e, dessa forma, reduzir o n?mero de compostos qu?micos a serem testados. Nesse trabalho, propomos um modelo para ranquear ligantes baseados na arquitetura de redes neurais siamesas. Esse modelo calcula a compatibilidade entre receptor e ligante usando grades de propriedades bioqu?micas. N?s tamb?m mostramos que esse modelo pode aprender a identificar intera??es moleculares importantes entre ligante e receptor. A compatibilidade ? calculada baseada em rela??o ? conforma??o do ligante, independente de sua posi??o e orienta??o em rela??o ao receptor. O modelo proposto foi treinado usando ligantes ativos previamente conhecidos e mol?culas chamarizes (decoys) em um modelo de receptor totalmente flex?vel (Fully Flexible Receptor - FFR) do complexo InhA-NADH da Mycobacterium tuberculosis, encontrando ?timos resultados.
Structure-based virtual screening (SBVS) on compounds databases has been widely applied in early stage of the drug discovery on drug target with known 3D structure. In SBVS, computational approaches usually ?dock? small molecules into binding site of drug target and ?score? their binding affinity. However, the costs involved in applying docking algorithms into huge compounds databases are prohibitive, due to the computational resources required by this operation. In this context,different types of machine learning strategies can be applied to rank ligands, based on binding affinity,and to reduce the number of compounds to be tested. In this work, we propose a deep learning energy-based model using siamese neural networks to rank ligands. This model takes as inputs grids of biochemical properties of ligands and receptors and calculates their compatibility. We show that the model can learn to identify important biochemical interactions between ligands and receptors. Besides, we demonstrate that the compatibility score is computed based only on conformation of small molecule, independent of its position and orientation in relation to the receptor. The proposed model was trained using known ligands and decoys in a Fully Flexible Receptor model of InhA-NADH complex (PDB ID: 1ENY), having achieved outstanding results.
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Nawsheen, Sabia. "Evaluation of Fragment-Based Virtual Screening by Applying Docking on Fragments obtained from Optimized Ligands." Thesis, Uppsala universitet, Institutionen för läkemedelskemi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-446388.

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Fragment-based virtual screening is an in-silico method that potentially identifies new startingpoints for drug molecules and provides an inexpensive and fast exploration of the relevantchemical space compared to its experimental counterpart. It focuses on docking small potentialbinding fragments to a binding pocket and is used to design improved binders by growing thefragments or joining fragments using suitable linkers. In this project, a fragment-based virtualscreening was evaluated by docking 21 fragments that are obtained from 4 different drugs. Here,the fragments were evaluated using SP score in place and SP and XP flexible docking methodsand were compared to the results of the two decoy fragment datasets. Three of the investigatedfragments are positioned at the top and docked with the correct poses and pockets when comparedto the corresponding substructure in the crystal structure and thus could be considered a successfulfragment starting points. Out of the two flexible docking methods used, the SP method providedadditional correct poses and pockets than XP in this limited dataset.
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Books on the topic "Ligand based virtual screening"

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Klebe, Gerhard. Virtual Screening: An Alternative or Complement to High Throughput Screening? Springer, 2010.

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

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(Editor), Juan Alvarez, and Brian Shoichet (Editor), eds. Virtual Screening in Drug Discovery. CRC, 2005.

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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. Dordrecht [Netherlands]: Kluwer Academic Publishers, 2000.

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Book chapters on the topic "Ligand based virtual screening"

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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, 61–85. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527633326.ch3.

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Pitt, William R., Mark D. Calmiano, Boris Kroeplien, Richard D. Taylor, James P. Turner, and Michael A. King. "Structure-Based Virtual Screening for Novel Ligands." In Protein-Ligand Interactions, 501–19. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-398-5_19.

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Abdo, Ammar, and Naomie Salim. "Ligand-Based Virtual Screening Using Bayesian Inference Network." In Library Design, Search Methods, and Applications of Fragment-Based Drug Design, 57–69. Washington, DC: American Chemical Society, 2011. http://dx.doi.org/10.1021/bk-2011-1076.ch004.

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Bhunia, Shome S., Mridula Saxena, and Anil K. Saxena. "Ligand- and Structure-Based Virtual Screening in Drug Discovery." In Biophysical and Computational Tools in Drug Discovery, 281–339. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/7355_2021_130.

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Howe, Trevor, Daniele Bemporad, and Gary Tresadern. "Scenarios and Case Studies: Examples for Ligand-Based Virtual Screening." In Methods and Principles in Medicinal Chemistry, 359–79. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527633326.ch13.

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Matsuyama, Yusuke, and Takashi Ishida. "Stacking Multiple Molecular Fingerprints for Improving Ligand-Based Virtual Screening." In Intelligent Computing Theories and Application, 279–88. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95933-7_35.

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Shin, Woong-Hee, and Daisuke Kihara. "Virtual Ligand Screening Using PL-PatchSurfer2, a Molecular Surface-Based Protein–Ligand Docking Method." In Methods in Molecular Biology, 105–21. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7756-7_7.

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Al-Dabbagh, Mohammed Mumtaz, Naomie Salim, and Faisal Saeed. "Methods to Improve Ranking Chemical Structures in Ligand-Based Virtual Screening." In Advances in Intelligent Systems and Computing, 259–69. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33582-3_25.

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Nasser, Maged, Naomie Salim, Hentabli Hamza, and Faisal Saeed. "Deep Belief Network for Molecular Feature Selection in Ligand-Based Virtual Screening." In Advances in Intelligent Systems and Computing, 3–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99007-1_1.

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Puertas-Martín, Savíns, Juana L. Redondo, Antonio J. Banegas-Luna, Ester M. Garzón, Horacio Pérez-Sánchez, Valerie J. Gillet, and Pilar M. Ortigosa. "Virtual Screening Based on Electrostatic Similarity and Flexible Ligands." In Computational Science and Its Applications – ICCSA 2022 Workshops, 127–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10562-3_10.

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Conference papers on the topic "Ligand based virtual screening"

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Skoda, Petr, and David Hoksza. "Benchmarking platform for ligand-based virtual screening." In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2016. http://dx.doi.org/10.1109/bibm.2016.7822693.

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Skoda, Petr, David Hoksza, and Jan Jelinek. "Platform for ligand-based virtual screening integration." In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2017. http://dx.doi.org/10.1109/bibm.2017.8218015.

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Babaria, Khushboo, Sanya Ambegaokar, Shubhankar Das, and Hemant Palivela. "Algorithms for ligand based virtual screening in drug discovery." In 2015 International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT). IEEE, 2015. http://dx.doi.org/10.1109/icatcct.2015.7457004.

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Palivela, Hemant, Divesh Kubal, and C. R. Nirmala. "Multiple kernel learning techniques for ligand based virtual screening." In 2017 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2017. http://dx.doi.org/10.1109/iccci.2017.8117724.

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Ullrich, Katrin, Michael Kamp, Thomas Gartner, Martin Vogt, and Stefan Wrobel. "Ligand-Based Virtual Screening with Co-regularised Support Vector Regression." In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). IEEE, 2016. http://dx.doi.org/10.1109/icdmw.2016.0044.

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Bahi, Meriem, and Mohamed Batouche. "Deep Learning for Ligand-Based Virtual Screening in Drug Discovery." In 2018 3rd International Conference on Pattern Analysis and Intelligent Systems (PAIS). IEEE, 2018. http://dx.doi.org/10.1109/pais.2018.8598488.

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Cavasotto, Claudio N. "Ligand Docking and Virtual Screening in Structure-based Drug Discovery." In FROM PHYSICS TO BIOLOGY: The Interface between Experiment and Computation - BIFI 2006 II International Congress. AIP, 2006. http://dx.doi.org/10.1063/1.2345621.

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"Deep Belief Networks for Ligand-Based Virtual Screening of Drug Design." In 2016 the 6th International Workshop on Computer Science and Engineering. WCSE, 2016. http://dx.doi.org/10.18178/wcse.2016.06.115.

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Park, Jung Woo, and Sung-Wha Hong. "Ligand- and Structure-based Virtual Screening Studies for the Discovery of Selective Inhibitors." In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2019. http://dx.doi.org/10.1109/bibm47256.2019.8983013.

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Ahmed, Ali, Ammar Abdo, and Naomie Salim. "An enhancement of Bayesian inference network for ligand-based virtual screening using minifingerprints." In Fourth International Conference on Machine Vision (ICMV 11), edited by Zhu Zeng and Yuting Li. SPIE, 2011. http://dx.doi.org/10.1117/12.920338.

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Reports on the topic "Ligand based virtual screening"

1

Altstein, Miriam, and Ronald J. Nachman. Rational Design of Insect Control Agent Prototypes Based on Pyrokinin/PBAN Neuropeptide Antagonists. United States Department of Agriculture, August 2013. http://dx.doi.org/10.32747/2013.7593398.bard.

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The general objective of this study was to develop rationally designed mimetic antagonists (and agonists) of the PK/PBAN Np class with enhanced bio-stability and bioavailability as prototypes for effective and environmentally friendly pest insect management agents. The PK/PBAN family is a multifunctional group of Nps that mediates key functions in insects (sex pheromone biosynthesis, cuticular melanization, myotropic activity, diapause and pupal development) and is, therefore, of high scientific and applied interest. The objectives of the current study were: (i) to identify an antagonist biophores (ii) to develop an arsenal of amphiphilic topically active PK/PBAN antagonists with an array of different time-release profiles based on the previously developed prototype analog; (iii) to develop rationally designed non-peptide SMLs based on the antagonist biophore determined in (i) and evaluate them in cloned receptor microplate binding assays and by pheromonotropic, melanotropic and pupariation in vivo assays. (iv) to clone PK/PBAN receptors (PK/PBAN-Rs) for further understanding of receptor-ligand interactions; (v) to develop microplate binding assays for screening the above SMLs. In the course of the granting period A series of amphiphilic PK/PBAN analogs based on a linear lead antagonist from the previous BARD grant was synthesized that incorporated a diverse array of hydrophobic groups (HR-Suc-A[dF]PRLa). Others were synthesized via the attachment of polyethylene glycol (PEG) polymers. A hydrophobic, biostablePK/PBAN/DH analog DH-2Abf-K prevented the onset of the protective state of diapause in H. zea pupae [EC50=7 pmol/larva] following injection into the preceding larval stage. It effectively induces the crop pest to commit a form of ‘ecological suicide’. Evaluation of a set of amphiphilic PK analogs with a diverse array of hydrophobic groups of the formula HR-Suc-FTPRLa led to the identification of analog T-63 (HR=Decyl) that increased the extent of diapause termination by a factor of 70% when applied topically to newly emerged pupae. Another biostablePK analog PK-Oic-1 featured anti-feedant and aphicidal properties that matched the potency of some commercial aphicides. Native PK showed no significant activity. The aphicidal effects were blocked by a new PEGylated PK antagonist analog PK-dF-PEG4, suggesting that the activity is mediated by a PK/PBAN receptor and therefore indicative of a novel and selective mode-of-action. Using a novel transPro mimetic motif (dihydroimidazole; ‘Jones’) developed in previous BARD-sponsored work, the first antagonist for the diapause hormone (DH), DH-Jo, was developed and shown to block over 50% of H. zea pupal diapause termination activity of native DH. This novel antagonist development strategy may be applicable to other invertebrate and vertebrate hormones that feature a transPro in the active core. The research identifies a critical component of the antagonist biophore for this PK/PBAN receptor subtype, i.e. a trans-oriented Pro. Additional work led to the molecular cloning and functional characterization of the DH receptor from H. zea, allowing for the discovery of three other DH antagonist analogs: Drosophila ETH, a β-AA analog, and a dF analog. The receptor experiments identified an agonist (DH-2Abf-dA) with a maximal response greater than native DH. ‘Deconvolution’ of a rationally-designed nonpeptide heterocyclic combinatorial library with a cyclic bis-guanidino (BG) scaffold led to discovery of several members that elicited activity in a pupariation acceleration assay, and one that also showed activity in an H. zea diapause termination assay, eliciting a maximal response of 90%. Molecular cloning and functional characterization of a CAP2b antidiuretic receptor from the kissing bug (R. prolixus) as well as the first CAP2b and PK receptors from a tick was also achieved. Notably, the PK/PBAN-like receptor from the cattle fever tick is unique among known PK/PBAN and CAP2b receptors in that it can interact with both ligand types, providing further evidence for an evolutionary relationship between these two NP families. In the course of the granting period we also managed to clone the PK/PBAN-R of H. peltigera, to express it and the S. littoralis-R Sf-9 cells and to evaluate their interaction with a variety of PK/PBAN ligands. In addition, three functional microplate assays in a HTS format have been developed: a cell-membrane competitive ligand binding assay; a Ca flux assay and a whole cell cAMP ELISA. The Ca flux assay has been used for receptor characterization due to its extremely high sensitivity. Computer homology studies were carried out to predict both receptor’s SAR and based on this analysis 8 mutants have been generated. The bioavailability of small linear antagonistic peptides has been evaluated and was found to be highly effective as sex pheromone biosynthesis inhibitors. The activity of 11 new amphiphilic analogs has also been evaluated. Unfortunately, due to a problem with the Heliothis moth colony we were unable to select those with pheromonotropic antagonistic activity and further check their bioavailability. Six peptides exhibited some melanotropic antagonistic activity but due to the low inhibitory effect the peptides were not further tested for bioavailability in S. littoralis larvae. Despite the fact that no new antagonistic peptides were discovered in the course of this granting period the results contribute to a better understanding of the interaction of the PK/PBAN family of Nps with their receptors, provided several HT assays for screening of libraries of various origin for presence of PK/PBAN-Ragonists and antagonists and provided important practical information for the further design of new, peptide-based insecticide prototypes aimed at the disruption of key neuroendocrine physiological functions in pest insects.
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2

Rafaeli, Ada, and Russell Jurenka. Molecular Characterization of PBAN G-protein Coupled Receptors in Moth Pest Species: Design of Antagonists. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7593390.bard.

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The proposed research was directed at determining the activation/binding domains and gene regulation of the PBAN-R’s thereby providing information for the design and screening of potential PBAN-R-blockers and to indicate possible ways of preventing the process from proceeding to its completion. Our specific aims included: (1) The identification of the PBAN-R binding domain by a combination of: (a) in silico modeling studies for identifying specific amino-acid side chains that are likely to be involved in binding PBAN with the receptor and; (b) bioassays to verify the modeling studies using mutant receptors, cell lines and pheromone glands (at tissue and organism levels) against selected, designed compounds to confirm if compounds are agonists or antagonists. (2) The elucidation ofthemolecular regulationmechanisms of PBAN-R by:(a) age-dependence of gene expression; (b) the effect of hormones and; (c) PBAN-R characterization in male hair-pencil complexes. Background to the topic Insects have several closely related G protein-coupled receptors (GPCRs) belonging to the pyrokinin/PBAN family, one with the ligand pheromone biosynthesis activating neuropeptide or pyrokinin-2 and another with diapause hormone or pyrokinin-1 as a ligand. We were unable to identify the diapause hormone receptor from Helicoverpa zea despite considerable effort. A third, related receptor is activated by a product of the capa gene, periviscerokinins. The pyrokinin/PBAN family of GPCRs and their ligands has been identified in various insects, such as Drosophila, several moth species, mosquitoes, Triboliumcastaneum, Apis mellifera, Nasoniavitripennis, and Acyrthosiphon pisum. Physiological functions of pyrokinin peptides include muscle contraction, whereas PBAN regulates pheromone production in moths plus other functions indicating the pleiotropic nature of these ligands. Based on the alignment of annotated genomic sequences, the primary and secondary structures of the pyrokinin/PBAN family of receptors have similarity with the corresponding structures of the capa or periviscerokinin receptors of insects and the neuromedin U receptors found in vertebrates. Major conclusions, solutions, achievements Evolutionary trace analysisof receptor extracellular domains exhibited several class-specific amino acid residues, which could indicate putative domains for activation of these receptors by ligand recognition and binding. Through site-directed point mutations, the 3rd extracellular domain of PBAN-R was shown to be critical for ligand selection. We identified three receptors that belong to the PBAN family of GPCRs and a partial sequence for the periviscerokinin receptor from the European corn borer, Ostrinianubilalis. Functional expression studies confirmed that only the C-variant of the PBAN-R is active. We identified a non-peptide agonist that will activate the PBAN-receptor from H. zea. We determined that there is transcriptional control of the PBAN-R in two moth species during the development of the pupa to adult, and we demonstrated that this transcriptional regulation is independent of juvenile hormone biosynthesis. This transcriptional control also occurs in male hair-pencil gland complexes of both moth species indicating a regulatory role for PBAN in males. Ultimate confirmation for PBAN's function in the male tissue was revealed through knockdown of the PBAN-R using RNAi-mediated gene-silencing. Implications, both scientific and agricultural The identification of a non-peptide agonist can be exploited in the future for the design of additional compounds that will activate the receptor and to elucidate the binding properties of this receptor. The increase in expression levels of the PBAN-R transcript was delineated to occur at a critical period of 5 hours post-eclosion and its regulation can now be studied. The mysterious role of PBAN in the males was elucidated by using a combination of physiological, biochemical and molecular genetics techniques.
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3

Eyal, Yoram, and Sheila McCormick. Molecular Mechanisms of Pollen-Pistil Interactions in Interspecific Crossing Barriers in the Tomato Family. United States Department of Agriculture, May 2000. http://dx.doi.org/10.32747/2000.7573076.bard.

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During the evolutionary process of speciation in plants, naturally occurring barriers to reproduction have developed that affect the transfer of genes within and between related species. These barriers can occur at several different levels beginning with pollination-barriers and ending with hybrid-breakdown. The interaction between pollen and pistils presents one of the major barriers to intra- and inter-specific crosses and is the focus of this research project. Our long-term goal in this research proposal was defined to resolve questions on recognition and communication during pollen-pistil interactions in the extended tomato family. In this context, this work was initiated and planned to study the potential involvement of tomato pollen-specific receptor-like kinases (RLK's) in the interaction between pollen and pistils. By special permission from BARD the objectives of this research were extended to include studies on pollen-pistil interactions and pollination barriers in horticultural crops with an emphasis on citrus. Functional characterization of 2 pollen-specific RLK's from tomato was carried out. The data shows that both encode functional kinases that were active as recombinant proteins. One of the kinases was shown to accumulate mainly after pollen germination and to be phosphorylated in-vitro in pollen membranes as well as in-vivo. The presence of style extract resulted in dephosphorylation of the RLK, although no species specificity was observed. This data implies a role for at least one RLK in pollination events following pollen germination. However, a transgenic plant analysis of the RLK's comprising overexpression, dominant-negative and anti-sense constructs failed to provide answers on their role in pollination. While genetic effects on some of the plants were observed in both the Israeli and American labs, no clear functional answers were obtained. An alternative approach to addressing function was pursued by screening for an artificial ligand for the receptor domain using a peptide phage display library. An enriched peptide sequence was obtained and will be used to design a peptide-ligand to be tested for its effect o pollen germination and tube growth. Self-incompatibility (SI) in citrus was studied on 3 varieties of pummelo. SI was observed using fluorescence microscopy in each of the 3 varieties and compatibility relations between varieties was determined. An initial screen for an S-RNase SI mechanism yielded only a cDNA homologous to the group of S-like RNases, suggesting that SI results from an as yet unknown mechanism. 2D gel electrophoresis was applied to compare pollen and style profiles of different compatibility groups. A "polymorphic" protein band from style extracts was observed, isolated and micro-sequenced. Degenerate primers designed based on the peptide sequence date will be used to isolate the relevant genes i order to study their potential involvement in SI. A study on SI in the apple cultivar Top red was initiated. SI was found, as previously shown, to be complete thus requiring a compatible pollinator variety. A new S-RNase allele was discovered fro Top red styles and was found to be highly homologous to pear S-RNases, suggesting that evolution of these genes pre-dated speciation into apples and pears but not to other Rosaceae species. The new allele provides molecular-genetic tools to determine potential pollinators for the variety Top red as well as a tool to break-down SI in this important variety.
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4

Altstein, Miriam, and Ronald Nachman. Rationally designed insect neuropeptide agonists and antagonists: application for the characterization of the pyrokinin/Pban mechanisms of action in insects. United States Department of Agriculture, October 2006. http://dx.doi.org/10.32747/2006.7587235.bard.

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The general objective of this BARD project focused on rationally designed insect neuropeptide (NP) agonists and antagonists, their application for the characterization of the mechanisms of action of the pyrokinin/PBAN (PK-PBAN) family and the development of biostable, bioavailable versions that can provide the basis for development of novel, environmentally-friendly pest insect control agents. The specific objectives of the study, as originally proposed, were to: (i) Test stimulatory potencies of rationally designed backbone cyclic (BBC) peptides on pheromonotropic, melanotropic, myotropic and pupariation activities; (ii) Test the inhibitory potencies of the BBC compounds on the above activities evoked either by synthetic peptides (PBAN, LPK, myotropin and pheromonotropin) or by the natural endogenous mechanism; (iii) Determine the bioavailability of the most potent BBC compounds that will be found in (ii); (iv) Design, synthesize and examine novel PK/PBAN analogs with enhanced bioavailability and receptor binding; (v) Design and synthesize ‘magic bullet’ analogs and examine their ability to selectively kill cells expressing the PK/PBAN receptor. To achieve these goals the agonistic and antagonistic activities/properties of rationally designed linear and BBC neuropeptide (NP) were thoroughly studied and the information obtained was further used for the design and synthesis of improved compounds toward the design of an insecticide prototype. The study revealed important information on the structure activity relationship (SAR) of agonistic/antagonistic peptides, including definitive identification of the orientation of the Pro residue as trans for agonist activity in 4 PK/PBANbioassays (pheromonotropic, pupariation, melanotropic, & hindgut contractile) and a PK-related CAP₂b bioassay (diuretic); indications that led to the identification of a novel scaffold to develop biostbiostable, bioavailable peptidomimetic PK/PBANagonists/antagonists. The work led to the development of an arsenal of PK/PBAN antagonists with a variety of selectivity profiles; whether between different PKbioassays, or within the same bioassay between different natural elicitors. Examples include selective and non-selective BBC and novel amphiphilic PK pheromonotropic and melanotropic antagonists some of which are capable of penetrating the moth cuticle in efficacious quantities. One of the latter analog group demonstrated unprecedented versatility in its ability to antagonize a broad spectrum of pheromonotropic elicitors. A novel, transPro mimetic motif was proposed & used to develop a strong, selective PK agonist of the melanotropic bioassay in moths. The first antagonist (pure) of PK-related CAP₂b diuresis in flies was developed using a cisPro mimetic motif; an indication that while a transPro orientation is associated with receptor agonism, a cisPro orientation is linked with an antagonist interaction. A novel, biostablePK analog, incorporating β-amino acids at key peptidase-susceptible sites, exhibited in vivo pheromonotropic activity that by far exceeded that of PBAN when applied topically. Direct analysis of neural tissue by state-of-the-art MALDI-TOF/TOF mass spectrometry was used to identify specific PK/PK-related peptides native to eight arthropod pest species [house (M. domestica), stable (S. calcitrans), horn (H. irritans) & flesh (N. bullata) flies; Southern cattle fever tick (B. microplus), European tick (I. ricinus), yellow fever mosquito (A. aegypti), & Southern Green Stink Bug (N. viridula)]; including the unprecedented identification of mass-identical Leu/Ile residues and the first identification of NPs from a tick or the CNS of Hemiptera. Evidence was obtained for the selection of Neb-PK-2 as the primary pupariation factor of the flesh fly (N. bullata) among native PK/PK-related candidates. The peptidomic techniques were also used to map the location of PK/PK-related NP in the nervous system of the model fly D. melanogaster. Knowledge of specific PK sequences can aid in the future design of species specific (or non-specific) NP agonists/antagonists. In addition, the study led to the first cloning of a PK/PBAN receptor from insect larvae (S. littoralis), providing the basis for SAR analysis for the future design of 2ⁿᵈgeneration selective and/or nonselective agonists/antagonists. Development of a microplate ligand binding assay using the PK/PBAN pheromone gland receptor was also carried out. The assay will enable screening, including high throughput, of various libraries (chemical, molecular & natural product) for the discovery of receptor specific agonists/antagonists. In summary, the body of work achieves several key milestones and brings us significantly closer to the development of novel, environmentally friendly pest insect management agents based on insect PK/PBANNPs capable of disrupting critical NP-regulated functions.
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