| 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. |
