How do you study protein ligand interaction through molecular docking?
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Our comparison of these complexes highlights differences in the protein-ligand interactions between the two docking methods. |
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Docking study in dft chemistry4 answersDocking studies in density functional theory (DFT) chemistry have been conducted in several papers. In one study, the efficiency of obtained products against selected drug targets in anti-Alzheimer ligand-receptor interactions was investigated using molecular docking analysis. Another study evaluated the bioactivity of phytochemicals as inhibitors against SARS-CoV-2 using computational models and molecular docking. In a different study, molecular docking was performed to investigate the mode of binding of novel sulfonamide derivatives to paraoxonase 1 enzyme. Additionally, molecular docking was used to determine the interactions between AChE and BChE enzymes and a chemical compound. Furthermore, a docking study was conducted to identify protein-ligand interactions and determine the best binding score. These papers demonstrate the use of molecular docking in DFT chemistry for various applications.
How to do ligand docking in protein?5 answersLigand docking in proteins involves several steps. First, a suitable search strategy and scoring function are needed for efficient and effective docking. One approach is to use AutoDock Vina, which employs an exhaustiveness parameter and a grid box to define the ligand binding site. Another method, FitDock, utilizes a hierarchical multi-feature alignment approach to fit the initial conformation to a given template, resulting in improved docking success rates and faster performance. Additionally, flexible protein-ligand docking can be achieved using a deep learning model based on the prediction of an intermolecular Euclidean distance matrix, which outperforms traditional docking methods. Finally, computational molecular docking can be used to generate a density of binding states, which can be used to calculate binding strengths, conformations, and atomic interactions between the ligand and protein.
How moleculer docking used for diabetes type 2?5 answersMolecular docking is used for diabetes type 2 by predicting the interaction and binding affinity of compounds with target enzymes involved in the disease. Several studies have utilized molecular docking to identify potential drug candidates for diabetes type 2 treatment. For example, Kwatra et al. conducted docking-based screening using a library of approved drugs and compounds to identify potential antiviral activity against diabetes type 2. Nursanti et al. used molecular docking to study the interaction between compounds from various plants and the Peroxisome Proliferator-Actived Receptor-Gamma (PPAR-y), a receptor involved in diabetes treatment. Cen et al. employed network pharmacological analysis and molecular docking to explore the mechanism of a traditional Chinese medicine formula on diabetes type 2. Hartanti et al. investigated the inhibition mechanism of compounds from Garcinia cowa on the protein tyrosine phosphatase 1B (PTP1B) enzyme using molecular docking. Farahin et al. used molecular docking to predict the interaction between polyphenol compounds from Anacardium occidentale and alpha-glucosidase (AG) and dipeptidyl-peptidase IV (DPP-4) enzymes involved in diabetes type 2.
What are the main tools use in molecular docking?4 answersThe main tools used in molecular docking include molecular docking software and web services. These tools are employed to study complex biological and chemical systems, and to identify, characterize, and develop novel drugs and compounds. Some commonly used tools include AutoDock Vina in UCSF Chimera, the VEGA Online web service, and the VEGA Web Edition (WE) and Score tools. These tools provide features such as file format conversion, 2D/3D conversion, surface mapping, editing and preparing input files, and rescoring docking poses. Additionally, consensus methods, fragment-based approaches, and machine learning algorithms are also utilized in molecular docking. These tools and approaches contribute to an increase in accuracy and are expected to eventually accomplish the full potential of molecular docking.
What is the best method for molecular docking study?5 answersMolecular docking is a powerful computational method for studying the interactions between biomolecules. It is widely used in drug design, as well as predicting protein-protein and protein-nucleic acid interactions. High-throughput molecular docking has proven to be extremely useful in identifying novel bioactive compounds within large chemical libraries. Quantum mechanical-based molecular docking has gained attention for its ability to provide better accuracy compared to classical molecular mechanics methods. The AlteQ method, which calculates electron density using Slater's type atomic contributions, has been used to evaluate the quality of interactions in docking complexes. LeDock, DSX, and X-score have shown good performance in molecular docking, with the combination of LeDock and DSX or X-score improving prediction accuracy. A meta-docking approach that combines the results of multiple docking programs, such as AutoDock4.2, LeDock, and rDOCK, has shown superior performance in scoring, posing, and screening protein-ligand complexes.
How do you choose ligands for docking?6 answers