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PMC:7755033 / 22589-25087 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
439 118-122 Gene denotes ACE2 Gene:59272
440 112-117 Species denotes human Tax:9606
441 133-141 Species denotes SARS-CoV Tax:694009
442 146-156 Species denotes SARS-CoV-2 Tax:2697049
443 101-103 Species denotes WS Tax:126910
450 819-823 Gene denotes ACE2 Gene:59272
451 813-818 Species denotes human Tax:9606
452 846-854 Species denotes SARS-CoV Tax:694009
453 859-869 Species denotes SARS-CoV-2 Tax:2697049
454 790-801 Chemical denotes withanolide MESH:D054358
455 1093-1095 Chemical denotes BE
457 2390-2398 Chemical denotes hydrogen MESH:D006859

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T197 0-4 Sentence denotes 2.5.
T198 6-31 Sentence denotes Molecular docking studies
T199 33-39 Sentence denotes 2.5.1.
T200 41-49 Sentence denotes AutoDock
T201 50-311 Sentence denotes Molecular docking of selected phytoconstituents of WS against human ACE2 receptor, SARS-CoV and SARS-CoV-2 target proteins was performed using AutoDock 4.0/ADT version 4.2.6 program (Morris et al., 1998) and further validated using two additional softwares viz.
T202 312-434 Sentence denotes AutoDock vina and iGEMDOCK version 2.1 in order to investigate binding kinetics and binding modes to the refined proteins.
T203 435-535 Sentence denotes Grid spacing was set at 0.375 Å and the grid points in the X, Y and Z axes were set to 60 × 60 × 60.
T204 536-714 Sentence denotes The quest was based on the Lamarckian genetic algorithm (Miyamoto & Kollman, 1992; Oprea et al., 2001) and the binding energies of the results were subjected to further analysis.
T205 715-950 Sentence denotes Molecular docking computation and visualization of binding interactions of withanolide analogs to human ACE2 receptor and selected SARS-CoV and SARS-CoV-2 protein targets was done using Accelrys Biovia Discovery Studio version 2017 R2.
T206 951-1128 Sentence denotes The best possible orientation of the ligand(s) in the protein binding pocket was selected for analysis on the basis of lowest binding energy (BE) and dissociation constant (Kd).
T207 1130-1136 Sentence denotes 2.5.2.
T208 1138-1151 Sentence denotes AutoDock Vina
T209 1152-1307 Sentence denotes AutoDock Vina is a free platform designed to be significantly faster than AutoDock 4, yet at the same time more accurate in predictions of binding pockets.
T210 1308-1493 Sentence denotes It calculates grid maps and clusters automatically, in contrast to AutoDock 4 and as a result of multithreading on multicore machines, faster results are obtained (Trott & Olson, 2010).
T211 1495-1511 Sentence denotes 2.5.3. iGEMDOCK
T212 1512-1737 Sentence denotes Institute of Bioinformatics in Taiwan's National Chiao Tung University developed iGEMDOCK version 2.1, a graphical, user-friendly and automated software for integrated docking, screening and post-analysis (Yang & Chen, 2004).
T213 1738-1982 Sentence denotes Binding sites for a particular ligand were established with the help of the software. iGEMDOCK employs a generic evolutionary method (GA) in order to calculate ligand conformation and orientation with respect to the target protein binding site.
T214 1983-2134 Sentence denotes The parameters selected for GA were as follows: population size = 200, generations = 70, solution number = 2 and docking feature as 'standard docking'.
T215 2135-2296 Sentence denotes Once a set of poses is generated, the software recalculates the energy of each pose and the interaction data represents the individual as well as overall energy.
T216 2297-2498 Sentence denotes Best fit is selected, representing the total energy viz. vdW (van der Waals energy), H-bond (hydrogen bonding energy) and Elect (electrostatic energy) of the predicted pose at the protein binding site.