5sfg: Difference between revisions

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== Structural highlights ==
== Structural highlights ==
<table><tr><td colspan='2'>[[5sfg]] is a 4 chain structure with sequence from [https://en.wikipedia.org/wiki/Homo_sapiens Homo sapiens]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=5SFG OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=5SFG FirstGlance]. <br>
<table><tr><td colspan='2'>[[5sfg]] is a 4 chain structure with sequence from [https://en.wikipedia.org/wiki/Homo_sapiens Homo sapiens]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=5SFG OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=5SFG FirstGlance]. <br>
</td></tr><tr id='ligand'><td class="sblockLbl"><b>[[Ligand|Ligands:]]</b></td><td class="sblockDat" id="ligandDat"><scene name='pdbligand=CME:S,S-(2-HYDROXYETHYL)THIOCYSTEINE'>CME</scene>, <scene name='pdbligand=IKK:N-[(3R)-1-(5-chloropyridin-2-yl)pyrrolidin-3-yl]-6-cyclopropyl-3-[(pyrimidin-5-yl)amino]pyridine-2-carboxamide'>IKK</scene>, <scene name='pdbligand=MG:MAGNESIUM+ION'>MG</scene>, <scene name='pdbligand=ZN:ZINC+ION'>ZN</scene></td></tr>
</td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">X-ray diffraction, [[Resolution|Resolution]] 2.31&#8491;</td></tr>
<tr id='ligand'><td class="sblockLbl"><b>[[Ligand|Ligands:]]</b></td><td class="sblockDat" id="ligandDat"><scene name='pdbligand=CME:S,S-(2-HYDROXYETHYL)THIOCYSTEINE'>CME</scene>, <scene name='pdbligand=IKK:N-[(3R)-1-(5-chloropyridin-2-yl)pyrrolidin-3-yl]-6-cyclopropyl-3-[(pyrimidin-5-yl)amino]pyridine-2-carboxamide'>IKK</scene>, <scene name='pdbligand=MG:MAGNESIUM+ION'>MG</scene>, <scene name='pdbligand=ZN:ZINC+ION'>ZN</scene></td></tr>
<tr id='resources'><td class="sblockLbl"><b>Resources:</b></td><td class="sblockDat"><span class='plainlinks'>[https://proteopedia.org/fgij/fg.htm?mol=5sfg FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=5sfg OCA], [https://pdbe.org/5sfg PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=5sfg RCSB], [https://www.ebi.ac.uk/pdbsum/5sfg PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=5sfg ProSAT]</span></td></tr>
<tr id='resources'><td class="sblockLbl"><b>Resources:</b></td><td class="sblockDat"><span class='plainlinks'>[https://proteopedia.org/fgij/fg.htm?mol=5sfg FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=5sfg OCA], [https://pdbe.org/5sfg PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=5sfg RCSB], [https://www.ebi.ac.uk/pdbsum/5sfg PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=5sfg ProSAT]</span></td></tr>
</table>
</table>
== Function ==
== Function ==
[https://www.uniprot.org/uniprot/PDE10_HUMAN PDE10_HUMAN] Plays a role in signal transduction by regulating the intracellular concentration of cyclic nucleotides. Can hydrolyze both cAMP and cGMP, but has higher affinity for cAMP and is more efficient with cAMP as substrate.<ref>PMID:17389385</ref>  
[https://www.uniprot.org/uniprot/PDE10_HUMAN PDE10_HUMAN] Plays a role in signal transduction by regulating the intracellular concentration of cyclic nucleotides. Can hydrolyze both cAMP and cGMP, but has higher affinity for cAMP and is more efficient with cAMP as substrate.<ref>PMID:17389385</ref>  
<div style="background-color:#fffaf0;">
== Publication Abstract from PubMed ==
We release a new, high quality data set of 1162 PDE10A inhibitors with experimentally determined binding affinities together with 77 PDE10A X-ray co-crystal structures from a Roche legacy project. This data set is used to compare the performance of different 2D- and 3D-machine learning (ML) as well as empirical scoring functions for predicting binding affinities with high throughput. We simulate use cases that are relevant in the lead optimization phase of early drug discovery. ML methods perform well at interpolation, but poorly in extrapolation scenarios-which are most relevant to a real-world application. Moreover, we find that investing into the docking workflow for binding pose generation using multi-template docking is rewarded with an improved scoring performance. A combination of 2D-ML and 3D scoring using a modified piecewise linear potential shows best overall performance, combining information on the protein environment with learning from existing SAR data.
A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios.,Tosstorff A, Rudolph MG, Cole JC, Reutlinger M, Kramer C, Schaffhauser H, Nilly A, Flohr A, Kuhn B J Comput Aided Mol Des. 2022 Oct;36(10):753-765. doi: 10.1007/s10822-022-00478-x., Epub 2022 Sep 25. PMID:36153472<ref>PMID:36153472</ref>
From MEDLINE&reg;/PubMed&reg;, a database of the U.S. National Library of Medicine.<br>
</div>
<div class="pdbe-citations 5sfg" style="background-color:#fffaf0;"></div>
== References ==
== References ==
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<references/>
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