The largest database of trusted experimental protocols

Discovery studio 3

Manufactured by Dassault Systèmes
Sourced in United States, France

Discovery Studio 3.5 is a comprehensive software suite for 3D modeling, analysis, and visualization of biological macromolecules. It provides tools for protein structure prediction, ligand docking, and molecular dynamics simulations.

Automatically generated - may contain errors

151 protocols using discovery studio 3

1

Molecular Docking of PFCAs with Human Serum Albumin

Check if the same lab product or an alternative is used in the 5 most similar protocols
The crystal structure of HSA (PDB ID: 1H9Z) was downloaded from the RCSB Protein Data Bank (http://www.rcsb.org). PFBA (ZINC ID: 3861259), PFHxA (ZINC ID: 38141478), PFOA (ZINC ID: 6844606), and PFDA (ZINC ID: 6845007) were obtained from the Zinc (http://zinc.docking.org/) site as 3D mol2 text [29 (link)]. The Scripps Research Institute’s AutoDock Vina (http://vina.scripps.edu/) and MGLTools (http://mgltools.scripps.edu/) sites were used for docking calculations [30 ]. A grid of 40 Å × 40 Å × 40 Å spacing was calculated. The docking with the grid box centered at (32.033, 10.568, 4.112) in HSA indicates binding at site I for PFCAs [23 (link)]. The output of AutoDock Vina was rendered using Discovery Studio 3.5 (Discovery Studio 3.5, Accelrys, Inc., San Diego, CA, USA).
+ Open protocol
+ Expand
2

Molecular Docking of RNA Quadruplex-ThT Interaction

Check if the same lab product or an alternative is used in the 5 most similar protocols
The coordinates of the RNA quadruplex (3IBK) structures were retrieved from the RSCB Protein Data Bank. The RNA quadruplex structure was prepared for molecular docking, and the ThT structure was energy minimized (MMFF force field) using the Discovery Studio 3.5 program (Accelrys Software Inc., San Diego). The molecular docking studies were performed using the Lamarckian Genetic Algorithm as implemented in the Autodock 4.0 package. The binding site (docking grids) was prepared using 100 × 100 × 100 points with a grid spacing of 0.375 Å. For the Lamarckian Genetic Algorithm based docking, the size of the population was set to 150, and the number of energy evaluations was set to 5.0 × 107. All of the figures were rendered using the Discovery Studio 3.5 program (Accelrys Software Inc., San Diego).
+ Open protocol
+ Expand
3

Antibody-HER2 Interaction Modeling

Check if the same lab product or an alternative is used in the 5 most similar protocols
To analyze the molecular interactions between the antibody and HER2 (P04626, UniProtKB), we obtained the structural information for HER2 and hu4D5 from the PDB (code: 1N8Z; web site: http://www.rcsb.org/pdb/home/home.do). The effects of mutations in the antibody variable regions on stability, force field and charges were estimated using CHARMm module and Momany-Rone, respectively (Discovery Studio 3.5, Accelrys Inc., USA, http://accelrys.com/). Data on intraprotein interactions were obtained from the Protein Interactions Calculator (http://pic.mbu.iisc.ernet.in/), and the binding energy between the antibody and HER2 molecule was calculated by equation 1 below.
All the experiments were carried out on a 3.40 GHz Intel Core i7 Quard-Core processor. Molecular modeling was performed using the Macromolecules modules on Discovery Studio 3.5 (Accelrys Inc.), and CHARMm (ver. 36.2) was used for energy minimization.
BindingenergyofantibodyandantigenHER2ΔGHER2:VH/VLbindingenergy=ΔGHER2/VH/VLenergy(ΔGHER2energy+ΔGVH/VLenergy)
+ Open protocol
+ Expand
4

Virtual Screening of XO Inhibitors

Check if the same lab product or an alternative is used in the 5 most similar protocols
The fragments for generating the library were selected from the Spartina alterniflora-sourced natural components and the marketed XO inhibitors as well as high frequently reported ones from antioxidant agents. Then the library was built with the help of “Small molecules” module in Discovery Studio 3.5 software (BIOVIA, France) under the consideration of both FBDD and de novo concept. The virtual screening relied on the comparison of the binding patterns and interaction energy parameter from the molecular docking simulation between the generated ligands and the crystal structure of XO (PDB code: 3NVY) from the RCSB Protein Data Bank28 (link). The docking simulation was conducted with “CDOCKER” module in Discovery Studio 3.5 software (BIOVIA, France) as referenced29 (link). For each backbone, the rank depended on the rank of the fifth top hit and the manual verification of the binding pattern. In this work, three high-rank backbones were chosen for further screening of substitutes, and the top 24 hits were retained for synthesis and biological evaluation. The visual presentation of the binding patterns was conducted on Discovery Studio Visualiser 2021 software (BIOVIA, France).
+ Open protocol
+ Expand
5

Pharmacophore-Guided Discovery of ATX Inhibitors

Check if the same lab product or an alternative is used in the 5 most similar protocols
The “Receptor-Ligand Pharmacophore Generation” protocol in Discovery Studio 3.1 (Accelrys Inc., San Diego, CA, USA) was applied to set up pharmacophore models. Some relevant parameters in this protocol were set as follows: assigning 6 to the “Maximum Feature”, assigning 4 to the “Minimum Feature”, and assigning 10 to the “Maximum Pharmacophore” [23 (link)]. In this study, two diverse crystal structures of the ligand-receptor complexes (PDB ID: 5MHP, 5M7M) were used for building the pharmacophore models of ATX inhibitors, because the two complexes manifest novel binding modes between inhibitors and the receptor [22 (link)]. Finally, we built 14 pharmacophore models. Through a big compound database, which includes 6396 decoy compounds (inactives) from the DrugBank database [24 (link)] and 34 ATX inhibitors (actives), the created pharmacophore models were discreetly verified.
We applied the well-built pharmacophore models as 3D queries to retrieve potential ATX inhibitors from the original chemical database “Diversity Libraries” (129,087 compounds, Life Chemicals Inc., Burlington, VT, Canada) by utilizing the “Search 3D Database” protocol in Discovery Studio 3.1.
+ Open protocol
+ Expand
6

Homology Modeling of Human P-gp

Check if the same lab product or an alternative is used in the 5 most similar protocols
The human P-gp protein sequence (Uniprot ID: P08183) was obtained from the UniProt database [32 (link)]. The BLAST Search protocol implemented in Discovery Studio 3.1 (Accelrys Inc., San Diego, CA) was used to perform the sequence similarity search and to find the templates for homology modeling. We then selected the X-ray crystal structure of murine P-gp (4M2S.pdb [33 (link)]) with a sequence identity of 87% as the template for constructing the homology models of human P-gp. Using this template, five homology models of human P-gp were generated using the Macromolecules module in Discovery Studio 3.1. Based on the DOPE (discrete optimized protein energy) score, the homology model M002 was selected for the docking studies.
+ Open protocol
+ Expand
7

Molecular Docking and Binding Energy Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
All molecular simulations were performed using Discovery Studio 3.1 (Accelrys, San Diego, CA, USA). Accelrys Discovery Studio 3.1 is available from Accelrys Inc.-San Diego, CA 92,121, USA. Protein structures were obtained from the Protein Data Bank (PDB). All protein structures were prepared before molecular docking. Active sites were defined using “From Current Selection” tools based on active residues including catalytic triad residues and oxyanion hole residues. All chemical compounds were constructed manually using Discovery Studio Visualizer and were subjected to the “Minimization” module for full structural refinement with 5000 steps of the steepest descent algorithm, followed by 2000 steps of the conjugate gradient algorithm energy minimization, utilizing the generalized born implicit solvent model and the CHARMM forcefield. Molecular docking was then performed using the “Flexible Docking” module [21] (link) implemented in Discovery Studio 3.1 [22] (link). Finally, conformations with highest -CDocker interaction energy in each docking process were analyzed and visualized in Discovery Studio (detailed in Supporting information). For the substrate binding step, -CDocker Interaction Energy (-CDIE) and -CDocker Energy (-CDE) were used to evaluate the interaction energy and enzyme-substrate complex stability, respectively.
+ Open protocol
+ Expand
8

Receptor-Ligand Docking Simulations

Check if the same lab product or an alternative is used in the 5 most similar protocols
Docking studies were carried out using cDOCKER protocol under the receptor-ligand interaction section in Discovery Studio® 3.1 (Accelrys, Inc., San Diego, CA, USA) based on scoring option. The receptor was the homology model and was pretreated before docking by adding hydrogen atoms, and all ionizable residues were set at their default protonation of pH 7.4. Meanwhile, all the 3D structures of the ligands were built with ChemBioOffice® 2008 (PerkinElmer, Inc., Waltham, MA, USA) and minimized. The receptor was held rigid while the ligands were allowed to flex during the docking process. The heating and cooling temperature were set, respectively, to 700 K in 2000 steps and 300 K in 5000 steps, and the grid extension was set to 10 Å. Finally, 10 ligand-binding poses were ranked according to their cDOCKER energy, and the predicted binding interactions were analyzed [31 (link)].
+ Open protocol
+ Expand
9

Molecular Docking and Dynamics for Drug Development

Check if the same lab product or an alternative is used in the 5 most similar protocols
MD is a technique for studying the molecular behavior of target proteins when they bind. It is a tool widely utilized in drug development. PyRx 0.8 [https://pyrx.sourceforge.io/], a virtual screening tool was used to accomplish molecular docking Prasad et al. (2020a) (link). A genetic algorithm is an effective approach for searching the docked conformer’s space globally. It also allows for the existence of a population of solutions, which can evolve through processes like ‘breeding’ and ‘mutation’ Prasad et al. (2020b) (link). Poor solutions are extinguished, while good ones are passed down to future generations. In a few tens of generations, such algorithms may usually obtain an excellent answer Uppar et al. (2021) (link). The MD results were analyzed for their bonded and non-bonded interactions using Discovery Studio 3.1 (Accelrys, San Diego, United States) visualization software Avinash et al. (2021) . The whole process is depicted in Figure 1
+ Open protocol
+ Expand
10

Multi-Dimensional ADME and TOPKAT Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
Both ADME and TOPKAT analyses were performed using Discovery Studio® 3.1 (Accelrys, San Diego, USA). ADME analysis was performed using six descriptors such as human intestinal absorption, aqueous solubility, blood–brain barrier, cytochrome P450 2D6, plasma protein binding, and hepatotoxicity. As for the TOPKAT analysis, five descriptors were used which includes aerobic biodegradability (AB), Ames mutagenicity, ocular irritancy, skin irritancy, and skin sensitization.
+ Open protocol
+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required

Sign up now

Revolutionizing how scientists
search and build protocols!