FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3162155458> ?p ?o ?g. }

• W3162155458 endingPage "2240" @default.
• W3162155458 startingPage "2231" @default.
• W3162155458 abstract "In recent years, machine-learning-based scoring functions have significantly improved the scoring power. However, many of these methods do not perform well in distinguishing the native structure from docked decoy poses due to the lack of decoy structural information in their training data. Here, we developed a machine-learning model, named DeepBSP, that can directly predict the root mean square deviation (rmsd) of a ligand docking pose with reference to its native binding pose. Unlike the binding affinity, the rmsd between the docking poses with reference to their native structures can be straightforwardly determined. By training on a generated data set with 11,925 native complexes and more than 165,000 docked poses, our model shows excellent docking power on our test set and also on the CASF-2016 docking decoy set compared to other major scoring functions. Thus, by combining molecular dockings that generate many poses with the application of DeepBSP, one can more accurately predict the best binding pose that is closest to the native complex structure. This DeepBSP model shall be very useful in picking out poses close to their natives from many poses generated from a dock application." @default.
• W3162155458 created "2021-05-24" @default.
• W3162155458 creator A5021114829 @default.
• W3162155458 creator A5045389074 @default.
• W3162155458 creator A5082303358 @default.
• W3162155458 date "2021-05-12" @default.
• W3162155458 modified "2023-10-16" @default.
• W3162155458 title "DeepBSP—a Machine Learning Method for Accurate Prediction of Protein–Ligand Docking Structures" @default.
• W3162155458 cites W1497260480 @default.
• W3162155458 cites W1985588649 @default.
• W3162155458 cites W1988437166 @default.
• W3162155458 cites W2050456292 @default.
• W3162155458 cites W2066515324 @default.
• W3162155458 cites W2084521509 @default.
• W3162155458 cites W2102377211 @default.
• W3162155458 cites W2105668062 @default.
• W3162155458 cites W2108257090 @default.
• W3162155458 cites W2128332459 @default.
• W3162155458 cites W2134967712 @default.
• W3162155458 cites W2159006106 @default.
• W3162155458 cites W2337974904 @default.
• W3162155458 cites W2550887636 @default.
• W3162155458 cites W2578119541 @default.
• W3162155458 cites W2587598315 @default.
• W3162155458 cites W2588514765 @default.
• W3162155458 cites W2600971009 @default.
• W3162155458 cites W2617750324 @default.
• W3162155458 cites W2741292700 @default.
• W3162155458 cites W2771412909 @default.
• W3162155458 cites W2772835527 @default.
• W3162155458 cites W2774371249 @default.
• W3162155458 cites W2784213390 @default.
• W3162155458 cites W2787446985 @default.
• W3162155458 cites W2790863896 @default.
• W3162155458 cites W2792951589 @default.
• W3162155458 cites W2802974816 @default.
• W3162155458 cites W2804136686 @default.
• W3162155458 cites W2898364362 @default.
• W3162155458 cites W2902435351 @default.
• W3162155458 cites W2902812092 @default.
• W3162155458 cites W2905303571 @default.
• W3162155458 cites W2907348324 @default.
• W3162155458 cites W2912171584 @default.
• W3162155458 cites W2914431119 @default.
• W3162155458 cites W2951676304 @default.
• W3162155458 cites W2954297401 @default.
• W3162155458 cites W2963833291 @default.
• W3162155458 cites W2972485984 @default.
• W3162155458 cites W2982145277 @default.
• W3162155458 cites W2985346127 @default.
• W3162155458 cites W3002058234 @default.
• W3162155458 cites W3008142620 @default.
• W3162155458 cites W3008726875 @default.
• W3162155458 cites W3015608194 @default.
• W3162155458 cites W3027871337 @default.
• W3162155458 cites W3092720182 @default.
• W3162155458 cites W3098189759 @default.
• W3162155458 cites W3098846260 @default.
• W3162155458 cites W3137067752 @default.
• W3162155458 cites W4242360498 @default.
• W3162155458 cites W4242580188 @default.
• W3162155458 doi "https://doi.org/10.1021/acs.jcim.1c00334" @default.
• W3162155458 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33979150" @default.
• W3162155458 hasPublicationYear "2021" @default.
• W3162155458 type Work @default.
• W3162155458 sameAs 3162155458 @default.
• W3162155458 citedByCount "31" @default.
• W3162155458 countsByYear W31621554582021 @default.
• W3162155458 countsByYear W31621554582022 @default.
• W3162155458 countsByYear W31621554582023 @default.
• W3162155458 crossrefType "journal-article" @default.
• W3162155458 hasAuthorship W3162155458A5021114829 @default.
• W3162155458 hasAuthorship W3162155458A5045389074 @default.
• W3162155458 hasAuthorship W3162155458A5082303358 @default.
• W3162155458 hasConcept C103697762 @default.
• W3162155458 hasConcept C119857082 @default.
• W3162155458 hasConcept C154945302 @default.
• W3162155458 hasConcept C159110408 @default.
• W3162155458 hasConcept C169903167 @default.
• W3162155458 hasConcept C170493617 @default.
• W3162155458 hasConcept C185592680 @default.
• W3162155458 hasConcept C2779179475 @default.
• W3162155458 hasConcept C41008148 @default.
• W3162155458 hasConcept C41685203 @default.
• W3162155458 hasConcept C51632099 @default.
• W3162155458 hasConcept C55493867 @default.
• W3162155458 hasConcept C60644358 @default.
• W3162155458 hasConcept C71924100 @default.
• W3162155458 hasConcept C74187038 @default.
• W3162155458 hasConcept C86803240 @default.
• W3162155458 hasConcept C93073132 @default.
• W3162155458 hasConceptScore W3162155458C103697762 @default.
• W3162155458 hasConceptScore W3162155458C119857082 @default.
• W3162155458 hasConceptScore W3162155458C154945302 @default.
• W3162155458 hasConceptScore W3162155458C159110408 @default.
• W3162155458 hasConceptScore W3162155458C169903167 @default.
• W3162155458 hasConceptScore W3162155458C170493617 @default.
• W3162155458 hasConceptScore W3162155458C185592680 @default.

• next