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Journal articles on the topic 'Pocketome'

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1

Cabaye, Alexandre, Kong T. Nguyen, Lihua Liu, Vineet Pande, and Matthieu Schapira. "Structural diversity of the epigenetics pocketome." Proteins: Structure, Function, and Bioinformatics 83, no. 7 (May 29, 2015): 1316–26. http://dx.doi.org/10.1002/prot.24830.

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2

Kingwell, Katie. "Picking the pocketome for orphan receptor ligands." Nature Reviews Drug Discovery 16, no. 2 (February 2017): 86. http://dx.doi.org/10.1038/nrd.2017.6.

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3

Nicola, George, Irina Kufareva, Andrey V. Ilatovskiy, and Ruben Abagyan. "Druggable exosites of the human kino-pocketome." Journal of Computer-Aided Molecular Design 34, no. 3 (January 10, 2020): 219–30. http://dx.doi.org/10.1007/s10822-019-00276-y.

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4

Yazdani, Setayesh, Nicola De Maio, Yining Ding, Vijay Shahani, Nick Goldman, and Matthieu Schapira. "Genetic Variability of the SARS-CoV-2 Pocketome." Journal of Proteome Research 20, no. 8 (June 28, 2021): 4212–15. http://dx.doi.org/10.1021/acs.jproteome.1c00206.

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5

Ansar, Samdani, Anupriya Sadhasivam, and Umashankar Vetrivel. "PocketPipe: A computational pipeline for integrated Pocketome prediction and comparison." Bioinformation 15, no. 4 (April 15, 2019): 295–98. http://dx.doi.org/10.6026/97320630015295.

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6

An, Jianghong, Maxim Totrov, and Ruben Abagyan. "Pocketome via Comprehensive Identification and Classification of Ligand Binding Envelopes." Molecular & Cellular Proteomics 4, no. 6 (March 9, 2005): 752–61. http://dx.doi.org/10.1074/mcp.m400159-mcp200.

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7

Kufareva, Irina, Andrey V. Ilatovskiy, and Ruben Abagyan. "Pocketome: an encyclopedia of small-molecule binding sites in 4D." Nucleic Acids Research 40, no. D1 (November 12, 2011): D535—D540. http://dx.doi.org/10.1093/nar/gkr825.

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8

Volkamer, Andrea, Sameh Eid, Samo Turk, Sabrina Jaeger, Friedrich Rippmann, and Simone Fulle. "Pocketome of Human Kinases: Prioritizing the ATP Binding Sites of (Yet) Untapped Protein Kinases for Drug Discovery." Journal of Chemical Information and Modeling 55, no. 3 (January 20, 2015): 538–49. http://dx.doi.org/10.1021/ci500624s.

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9

Bhagavat, Raghu, Santhosh Sankar, Narayanaswamy Srinivasan, and Nagasuma Chandra. "An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure." Structure 26, no. 3 (March 2018): 499–512. http://dx.doi.org/10.1016/j.str.2018.02.001.

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10

Palomba, Tommaso, Giusy Tassone, Carmine Vacca, Matteo Bartalucci, Aurora Valeri, Cecilia Pozzi, Simon Cross, Lydia Siragusa, and Jenny Desantis. "Exploiting ELIOT for Scaffold-Repurposing Opportunities: TRIM33 a Possible Novel E3 Ligase to Expand the Toolbox for PROTAC Design." International Journal of Molecular Sciences 23, no. 22 (November 17, 2022): 14218. http://dx.doi.org/10.3390/ijms232214218.

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The field of targeted protein degradation, through the control of the ubiquitin–proteasome system (UPS), is progressing considerably; to exploit this new therapeutic modality, the proteolysis targeting chimera (PROTAC) technology was born. The opportunity to use PROTACs engaging of new E3 ligases that can hijack and control the UPS system could greatly extend the applicability of degrading molecules. To this end, here we show a potential application of the ELIOT (E3 LIgase pocketOme navigaTor) platform, previously published by this group, for a scaffold-repurposing strategy to identify new ligands for a novel E3 ligase, such as TRIM33. Starting from ELIOT, a case study of the cross-relationship using GRID Molecular Interaction Field (MIF) similarities between TRIM24 and TRIM33 binding sites was selected. Based on the assumption that similar pockets could bind similar ligands and considering that TRIM24 has 12 known co-crystalised ligands, we applied a scaffold-repurposing strategy for the identification of TRIM33 ligands exploiting the scaffold of TRIM24 ligands. We performed a deeper computational analysis to identify pocket similarities and differences, followed by docking and water analysis; selected ligands were synthesised and subsequently tested against TRIM33 via HTRF binding assay, and we obtained the first-ever X-ray crystallographic complexes of TRIM33α with three of the selected compounds.
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11

Naz, Sadia, Tony Ngo, Umar Farooq, and Ruben Abagyan. "Analysis of drug binding pockets and repurposing opportunities for twelve essential enzymes of ESKAPE pathogens." PeerJ 5 (September 19, 2017): e3765. http://dx.doi.org/10.7717/peerj.3765.

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BackgroundThe rapid increase in antibiotic resistance by various bacterial pathogens underlies the significance of developing new therapies and exploring different drug targets. A fraction of bacterial pathogens abbreviated as ESKAPE by the European Center for Disease Prevention and Control have been considered a major threat due to the rise in nosocomial infections. Here, we compared putative drug binding pockets of twelve essential and mostly conserved metabolic enzymes in numerous bacterial pathogens including those of the ESKAPE group andMycobacterium tuberculosis. The comparative analysis will provide guidelines for the likelihood of transferability of the inhibitors from one species to another.MethodsNine bacterial species including six ESKAPE pathogens,Mycobacterium tuberculosisalong withMycobacterium smegmatisandEschershia coli, two non-pathogenic bacteria, have been selected for drug binding pocket analysis of twelve essential enzymes. The amino acid sequences were obtained from Uniprot, aligned using ICM v3.8-4a and matched against the Pocketome encyclopedia. We used known co-crystal structures of selected target enzyme orthologs to evaluate the location of their active sites and binding pockets and to calculate a matrix of pairwise sequence identities across each target enzyme across the different species. This was used to generate sequence maps.ResultsHigh sequence identity of enzyme binding pockets, derived from experimentally determined co-crystallized structures, was observed among various species. Comparison at both full sequence level and for drug binding pockets of key metabolic enzymes showed that binding pockets are highly conserved (sequence similarity up to 100%) among various ESKAPE pathogens as well asMycobacterium tuberculosis. Enzymes orthologs having conserved binding sites may have potential to interact with inhibitors in similar way and might be helpful for design of similar class of inhibitors for a particular species. The derived pocket alignments and distance-based maps provide guidelines for drug discovery and repurposing. In addition they also provide recommendations for the relevant model bacteria that may be used for initial drug testing.DiscussionComparing ligand binding sites through sequence identity calculation could be an effective approach to identify conserved orthologs as drug binding pockets have shown higher level of conservation among various species. By using this approach we could avoid the problems associated with full sequence comparison. We identified essential metabolic enzymes among ESKAPE pathogens that share high sequence identity in their putative drug binding pockets (up to 100%), of which known inhibitors can potentially antagonize these identical pockets in the various species in a similar manner.
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12

Sigurdardottir, A. G., A. Winter, A. Sobkowicz, M. Fragai, D. Chirgadze, D. B. Ascher, T. L. Blundell, and E. Gherardi. "Exploring the chemical space of the lysine-binding pocket of the first kringle domain of hepatocyte growth factor/scatter factor (HGF/SF) yields a new class of inhibitors of HGF/SF-MET binding." Chemical Science 6, no. 11 (2015): 6147–57. http://dx.doi.org/10.1039/c5sc02155c.

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13

Luggen, Martin. "A concept for technology and innovation management in start-ups and new technology based firms (NTBF): PockeTM." Innovation 6, no. 3 (December 2004): 458–67. http://dx.doi.org/10.5172/impp.2004.6.3.458.

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14

Al-Azzawi, Bev. "Perioperative practice in your pocketThe Association for Perioperative Practice/ Synergy Health Perioperative practice in your pocket 70pp £11.95 978 1 9042 9017 9 9781904290179." Nursing Standard 26, no. 52 (August 29, 2012): 31. http://dx.doi.org/10.7748/ns.26.52.31.s35.

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15

Hedderich, Janik B., Margherita Persechino, Katharina Becker, Franziska M. Heydenreich, Torben Gutermuth, Michel Bouvier, Moritz Bünemann, and Peter Kolb. "The pocketome of G-protein-coupled receptors reveals previously untargeted allosteric sites." Nature Communications 13, no. 1 (May 10, 2022). http://dx.doi.org/10.1038/s41467-022-29609-6.

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AbstractG-protein-coupled receptors do not only feature the orthosteric pockets, where most endogenous agonists bind, but also a multitude of other allosteric pockets that have come into the focus as potential binding sites for synthetic modulators. Here, to better characterise such pockets, we investigate 557 GPCR structures by exhaustively docking small molecular probes in silico and converting the ensemble of binding locations to pocket-defining volumes. Our analysis confirms all previously identified pockets and reveals nine previously untargeted sites. In order to test for the feasibility of functional modulation of receptors through binding of a ligand to such sites, we mutate residues in two sites, in two model receptors, the muscarinic acetylcholine receptor M3 and β2-adrenergic receptor. Moreover, we analyse the correlation of inter-residue contacts with the activation states of receptors and show that contact patterns closely correlating with activation indeed coincide with these sites.
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16

Anand, Praveen, and Nagasuma Chandra. "Characterizing the pocketome of Mycobacterium tuberculosis and application in rationalizing polypharmacological target selection." Scientific Reports 4, no. 1 (September 15, 2014). http://dx.doi.org/10.1038/srep06356.

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17

Hassan, Syed S., Syed B. Jamal, Leandro G. Radusky, Sandeep Tiwari, Asad Ullah, Javed Ali, Behramand, et al. "The Druggable Pocketome of Corynebacterium diphtheriae: A New Approach for in silico Putative Druggable Targets." Frontiers in Genetics 9 (February 13, 2018). http://dx.doi.org/10.3389/fgene.2018.00044.

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18

Palomba, Tommaso, Massimo Baroni, Simon Cross, Gabriele Cruciani, and Lydia Siragusa. "ELIOT : a platform to navigate the E3 pocketome and aid the design of new PROTACs." Chemical Biology & Drug Design, July 20, 2022. http://dx.doi.org/10.1111/cbdd.14123.

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19

Bhagavat, Raghu, Heung-Bok Kim, Chang-Yub Kim, Thomas C. Terwilliger, Dolly Mehta, Narayanaswamy Srinivasan, and Nagasuma Chandra. "A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis." Scientific Reports 7, no. 1 (October 2, 2017). http://dx.doi.org/10.1038/s41598-017-12471-8.

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AbstractNucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived from a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. As the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.
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20

Rohr, Claudia M., Daniel J. Sprague, Sang-Kyu Park, Nicholas J. Malcolm, and Jonathan S. Marchant. "Natural variation in the binding pocket of a parasitic flatworm TRPM channel resolves the basis for praziquantel sensitivity." Proceedings of the National Academy of Sciences 120, no. 1 (December 27, 2022). http://dx.doi.org/10.1073/pnas.2217732120.

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The drug praziquantel (PZQ) is the key clinical therapy for treating schistosomiasis and other infections caused by parasitic flatworms. A schistosome target for PZQ was recently identified— a transient receptor potential ion channel in the melastatin subfamily (TRPM PZQ )—however, little is known about the properties of TRPM PZQ in other parasitic flatworms. Here, TRPM PZQ orthologs were scrutinized from all currently available parasitic flatworm genomes. TRPM PZQ is present in all parasitic flatworms, and the consensus PZQ binding site was well conserved. Functional profiling of trematode, cestode, and a free-living flatworm TRPM PZQ ortholog revealed differing sensitives (~300-fold) of these TRPM PZQ channels toward PZQ, which matched the varied sensitivities of these different flatworms to PZQ. Three loci of variation were defined across the parasitic flatworm TRPM PZQ pocketome with the identity of an acidic residue in the TRP domain acting as a gatekeeper residue impacting PZQ residency within the TRPM PZQ ligand binding pocket. In trematodes and cyclophyllidean cestodes, which display high sensitivity to PZQ, this TRP domain residue is an aspartic acid which is permissive for potent activation by PZQ. However, the presence of a glutamic acid residue found in other parasitic and free-living flatworm TRPM PZQ was associated with lower sensitivity to PZQ. The definition of these different binding pocket architectures explains why PZQ shows high therapeutic effectiveness against specific fluke and tapeworm infections and will help the development of better tailored therapies toward other parasitic infections of humans, livestock, and fish.
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