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An Analysis of Protein Interaction and Its Methods, Metabolite Pathway and Drug Discovery
Published in Ayodeji Olalekan Salau, Shruti Jain, Meenakshi Sood, Computational Intelligence and Data Sciences, 2022
Docking use to conform ligand binding to the receptor; usually, the receptor is bigger than the molecules. This information includes the coordination of the ligand atoms, to find the lowest energy binding site of the docking configuration. FLEX and AutoDock example programs will be shown in a later chapter of this chapter. The aim is to confirm the binding affinity and the bind. The overall minimum energy of complex formation can be found with the exact position and direction of the binding ligand that belongs to the interacting molecule activation within that. Various bioinformatics tools are helpful in disease management, diagnosis and drug discovery. Sequencing enables identifying the disease and drug discovery by scientists. Mutation and drug and all identified and experimented by utilizing different computational tools. Drug targets decide the suitable drug entry into the pipeline of drug development with the help of bioinformatics tools. The process of designing a medication with the target molecule is known as drug designing. The smallest molecule is ligand that switches on the biological target molecule output in the therapeutic effect [50]. However, the approach of single regulatory is a difficult task in marketing authorization application in all countries. Figure 13.5 represents the levels of drug discovery with regulations. Figure 13.6 shows the drug designing methods and their types.
Preliminary Phytochemical Screening and Identification of Bioactive Compounds from Banana Inflorescence and to Find the Interactions on Molecular Docking for PCOS
Published in Parimelazhagan Thangaraj, Phytomedicine, 2020
M. C. Kamaraj, Suman Thamburaj, R. Akshaya, V. Bhanu Deepthi
In addition, in silico molecular docking studies revealed that the bioactive compounds from the banana inflorescence exhibit good interactions with the PCOS protein (CYP17A) namely, vitamin E, epicatechin, gallocatechin, β-tocopherol, estragole, and phytol. During drug discovery, the effective screening procedures should be applied to reduce the cost and time. In this study, we have utilized molecular docking by the AutoDock server to analyze the binding ability between six compounds with CYP17A. The compounds such as β-tocopherol, phytol, epicatechin, and gallocatechin were found to have good binding affinity with the protein by analyzing its AutoDock. Among these, beta tocopherol was found to be the lead compound with maximum binding affinity. This study shows the presence of active compounds from using the Musa florets’ extract as a docking platform. Further, in vitro and in vivo studies are to be carried out in order to establish the effect of Yuvati on polycystic ovarian syndrome.
Structure and function of Human CYP2D6
Published in Shufeng Zhou, Cytochrome P450 2D6, 2018
De Graaf et al. (2006) have described an improved automated docking approach to predict the catalytic site of 65 substrates in a CYP2D6 homology model. This approach incorporates the water molecules at predicted positions in the active site and the rescoring of pooled docking poses from four different docking programs (AutoDock, FlexX, GOLD-Goldscore, and GOLD-Chemscore). The SCORE scoring function successful predicts experimentally reported sites of catalysis of more than 80% of the substrates (de Graaf et al. 2006). Three docking algorithms (FlexX, GOLD-Goldscore, and GOLD-Chemscore) are then employed in combination with six scoring functions (Chemscore, DOCK, FlexX, GOLD, PMF, and SCORE) to evaluate the ability of docking-based virtual screening methods to prioritize known CYP2D6 substrates seeded into a drug-like chemical database in the absence and presence of active-site water molecules. The optimized docking strategy is successfully used to identify high-affinity CYP2D6 ligands among a larger proprietary database.
Integration of network pharmacology and intestinal flora to investigate the mechanism of action of Chinese herbal Cichorium intybus formula in attenuating adenine and ethambutol hydrochloride-induced hyperuricemic nephropathy in rats
Published in Pharmaceutical Biology, 2022
Na Li, Mukaram Amatjan, Pengke He, Boheng Zhang, Xianyan Mai, Qianle Jiang, Haochen Xie, Xiaoni Shao
The PDB ID of the core target proteins obtained above was searched in UniProt. The three-dimensional structure files of core target proteins were retrieved and downloaded in PBD format via the RSCB PBD database (https://www.rcsb.org/), and the MOL2 structure of the core components was downloaded from the TCMSP database. The downloaded target proteins were preprocessed using AutoDockTools-1.5.6 and PyMOL software for removing water molecules, separating proteins, adding non-polar hydrogens, calculating the Gasteiger charges for the structure, and saving them as PDBQT files (Morris et al. 2009). AutoDock is a prevalent receptor-ligand docking simulation programme. In this study, the target protein was the receptor and the active ingredient was the ligand. AutoDock was also used to evaluate the binding affinity of the protein to the ligand and to choose the lowest energy conformation in the docking simulation (Bitencourt-Ferreira et al. 2019). Ultimately, Autodock Vina was adopted for molecular docking, and it is commonly believed that the lower the binding energy of the receptor to the ligand, the higher the affinity and the greater the likelihood of binding occurring. The conformation with the lowest affinity was opted as the superior docking conformation and visualized in Pymol.
Design, synthesis, and evaluation of novel O-alkyl ferulamide derivatives as multifunctional ligands for treating Alzheimer’s disease
Published in Journal of Enzyme Inhibition and Medicinal Chemistry, 2022
Gaofeng Zhu, Ping Bai, Keren Wang, Jing Mi, Jing Yang, Jiaqi Hu, Yujuan Ban, Ran Xu, Rui Chen, Changning Wang, Lei Tang, Zhipei Sang
The crystal structure of human MAO-B in complex with the selective inhibitor 7–(3-chlorobenzyloxy)-4-carboxaldehyde-coumarin (PDB code: 2V60) was obtained from the Protein Data Bank after eliminating the original inhibitors and water molecules. The 3 D Structure of 5a was built and performed geometry optimisation by molecular mechanics. After the addition of Gasteiger charges, removal of hydrogen atoms, the addition of the atomic charges to skeleton atoms, and the assignment of proper atomic types, the further preparation of the inhibitor was accomplished. Docking studies were performed using the AUTODOCK 4.2.6 program. By using Autodock Tools (ADT: version 1.5.6), polar hydrogen atoms were added to amino acid residues, and Gasteiger charges were assigned to all atoms of the enzyme. The resulting enzyme structure was used as an input for the AUTOGRID program. AUTOGRID performed pre-calculated atomic affinity grid maps for each atom type in the ligand. The centre of the grid box was placed with coordinated x = 14.846, y = 128.673, z = 24.971. The dimensions of the active site box were set at 50 × 50 × 50 Å. Flexible ligand docking was performed for the compound. Each docked system was performed by 100 runs of the AUTODOCK search by the Lamarchian genetic algorithm (LGA). A cluster analysis was performed on the docking results using a root mean square (RMS) tolerance of 1.0 and the lowest energy conformation of the highest populated cluster was selected for analysis. Graphic manipulations and visualisations were done by Autodock Tools or Discovery Studio 2.1 software.
Target-based in-silico screening of basil polysaccharides against different epigenetic targets responsible for breast cancer
Published in Journal of Receptors and Signal Transduction, 2022
Nancy Bhura, Pawan Gupta, Jeena Gupta
For target-based in-silico screening, molecular docking studies were performed against the active site of epigenetic targets (Table 2). For this purpose, AutoDock Vina (version 1.5.6) was used. This tool was developed by Molecular Graphics Lab at The Scripps Research Institute, USA. AutoDock tools 1.5.6 (ADT) were used to prepare the proteins (Table 2) and grid was generated around bound co-crystalized ligand of the protein. In AutoDock Vina, the first bound molecule in protein was docked into the active site of protein to check the docking program if it is generating the same binding modes in PDB or not. Using the same docking parameters, docking studies of the BPSs were then performed against individual proteins. For each ligand, nine poses were generated with energy and H-bonding in the Vina program.