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Role of Computational Tools in Designing Enzymatic Biosensors for the Detection of Pesticides in Environment
Published in Chaudhery Mustansar Hussain, Ajay Kumar Mishra, Nanocomposites for Pollution Control, 2018
Mohd. Shahbaaz, Suvardhan Kanchi, Myalowenkosi Sabela, Krishna Bisetty
The structure of acetylcholinesterase (ACE, PDB ID - 5HF9), cytochrome P450 (CYP, PDB ID - 4D7D), glutathione S-transferase (GST, PDB ID - 4MPF), and protein kinase C (PKC, PDB ID - 5F9E) were remodelled to remove the discontinuities in the structural coordinates deposited in the biological database. The protein structures were predicted by satisfying the spatial restraints using MODELLER module of the Discovery Studio 2016 (DS, http://accelrys.com/products/collaborative-science/biovia- discovery-studio/). The generated 3-D models were minimized using the optimization and side chain refinement modules of DS.
Computer-Aided Drug Design for the Identification of Multi-Target Directed Ligands (MTDLs) in Complex Diseases: An Overview
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
Structure-based pharmacophore (SBP) model development is only possible when the 3D structural information of target macromolecule is available. Here, the methodology involves an analysis of the complementary chemical features of the active/binding site along with their spatial arrangement. Subsequently from this analysis, a pharmacophore model with selected features is built. Further, the (SBP) modeling technique can be further divided into two sub-categories, namely, target–ligand complex-based and target (only)-based. The target–ligand complex-based approach is more suitable as it helps in finding the ligand-binding site of the macromolecular target and for understanding the key interaction points between ligands and target. LigandScout (Wolber and Langer, 2005), Pocket v.2 (Chen and Lai, 2006) and GRID-based pharmacophore model (GBPM) (Ortuso et al., 2006) are some tools to perform target–ligand complex-based pharmacophore modeling. However, in cases when no compounds are known that are targeting the binding site of interest, then one can perform pharmacophore modeling using the target (only)-based approach. The SBP method implemented in Discovery Studio software (Discovery Studio, 2009) can be used to perform target (only)-based approach (Yang, 2010). Further, to identify the MTDLs, the parallel screening is performed on a set of chemicals obtained from several available databases through the multiple pharmacophore models representing different targets. Another faster way to perform pharmacophore-based virtual screening is to use the available online platform such as PharmMapper (http://lilab.ecust.edu.cn/pharmmapper/) (Liu et al., 2010), which is an integrated pharmacophore matching platform with statistical method for potential target identification and it includes a database (i.e., PharmTargetDB) of over 7000 target-based pharmacophore models. Another database “PharmaDB” (Meslamani and Rognan, 2015), which is included in Discovery Studio software (Discovery Studio, 2009), comprises about 140,000 receptor-ligand pharmacophore models, which are built from and validated using the scPDB (an annotated database of druggable binding sites from the Protein Data Bank) (Kellenberger et al., 2006). Finally, pharmacophore-based techniques are not computationally expensive when compared to molecular docking (or inverse docking) or molecular dynamics studies. However, identifying a good-quality pharmacophore hypothesis is a big task (Lavecchia and Cerchia, 2016).
A EuIII-based coordination polymer: crystal structure and anti-colon cancer activity
Published in Inorganic and Nano-Metal Chemistry, 2021
Wen-Long Xu, Qi Sun, Chun-Dong Gao, Neng-Wei Zhang
Discovery studio 3.0 is a common utilized software, which was used as a platform for the simulation of molecular docking. It can be used for the study of molecular docking of proteins along with small molecules. The advantage of this software is that it is customized at the aim of better supporting the development of high-precision scoring function. The structure of ligand was derived from the structure of crystal acquired by measuring X-ray and downloaded from the protein date bank (PDB), using ligand preparation tools before the docking program was performed. The receptor protein, TRIB3 (PDB ID), has been widely utilized for the simulation of molecular docking along with the screening of drug since it has protein residues and double helix structure at the same time. The Libdock and CDOCKER tools have been utilized to generate the structures of receptor along with ligand for the simulation of molecular docking, grid box length is set at 40, and it is enough large to cover all the docking bag and involve double helix chains as well as protein moieties.