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Relevant bibliographies by topics / Ligand-protein binding, molecular dynamics, molecular docking, structure-based

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Journal articles

Academic literature on the topic 'Ligand-protein binding, molecular dynamics, molecular docking, structure-based'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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Journal articles on the topic "Ligand-protein binding, molecular dynamics, molecular docking, structure-based"

1

Naqvi, Ahmad Abu Turab, Taj Mohammad, Gulam Mustafa Hasan, and Md Imtaiyaz Hassan. "Advancements in Docking and Molecular Dynamics Simulations Towards Ligand-receptor Interactions and Structure-function Relationships." Current Topics in Medicinal Chemistry 18, no. 20 (2018): 1755–68. http://dx.doi.org/10.2174/1568026618666181025114157.

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Protein-ligand interaction is an imperative subject in structure-based drug design and protein function prediction process. Molecular docking is a computational method which predicts the binding of a ligand molecule to the particular receptor. It predicts the binding pose, strength and binding affinity of the molecules using various scoring functions. Molecular docking and molecular dynamics simulations are widely used in combination to predict the binding modes, binding affinities and stability of different protein-ligand systems. With advancements in algorithms and computational power, molec

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2

Rayevsky, O. V., O. M. Demchyk, P. A. Karpov та ін. "Structure-based virtual screening for new lead compounds targeted Plasmodium α-tubulin". Faktori eksperimental'noi evolucii organizmiv 28 (31 серпня 2021): 135–39. http://dx.doi.org/10.7124/feeo.v28.1389.

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Aim. Search for new dinitroaniline and phosphorothioamide compounds, capable of selective binding with Plasmodium α-tubulin, affecting its mitotic apparatus. Methods. Structural biology methods of computational prediction of protein-ligand interaction: molecular docking, molecular dynamics and pharmacophore analysis. Selection of compounds based on pharmacophore characteristics and virtual screening results. Results. The protocol and required structural conditions for target (α-tubulin of P. falciparum) preparation and correct modeling of the ligand-protein interaction (docking and virtual scr

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3

Karpov, P. A., S. I. Spivak, O. V. Rayevsky, O. Yu Nyporko, S. P. Ozheredov та Ya B. Blume. "Assessment of structural peculiarities of glaziovianin A interaction with human α-, β and γ-tubulins". Faktori eksperimental'noi evolucii organizmiv 22 (9 вересня 2018): 340–44. http://dx.doi.org/10.7124/feeo.v22.972.

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Aim. To determine the features of the ligand-protein interaction of glaziovianin A and human α-, β- and γ-tubulin. Methods. Protein and ligand spatial structure modelling (I-Tasser, Grid), molecular docking (CCDC Gold), molecular dynamics simulation (GROMACS). Results. Using the method of molecular docking in CCDC Gold ligand-protein complexes of glaziovianin A and human α-, β- and γ-tubulin were reconstructed. Studied ligand interactions in GTP/GDP-exchange and colchicine binding sites of different tubulin isotypes. The built ligand-protein complexes were studied using molecular dynamics simu

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4

Ozheredov, S. P., O. M. Demchuk, P. A. Karpov, S. I. Spivak та Ya B. Blume. "Identification of plant α-tubulin amino acids playing a key role in specific binding of nitroaniline compounds". Faktori eksperimental'noi evolucii organizmiv 24 (30 серпня 2019): 333–37. http://dx.doi.org/10.7124/feeo.v24.1125.

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Aim. Computational prediction of amino acid residues critical for specific binding of nitro- and dinitroaniline compounds in plant α-tubulin. Methods. Protein structure modeling (I-Tasser, Grid-computing) and ligand library preparation, molecular docking (CCDC Gold), molecular dynamics (MD, Gromacs computing in Grid). Evaluation of the amino acid ensemble associated with ligand binding based on results of MD energy perturbations of protein-ligand complex. Results. The structural model of plant α-tubulin from Avena sativa was build. Also, the virtual library of 25 nitroaniline compounds was pre

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Panchangam, Sameera Sastry. "BabyBoom: 3-Dimensional Structure-Based Ligand and Protein Interaction Prediction by Molecular Docking." Biomolecules 12, no. 11 (2022): 1633. http://dx.doi.org/10.3390/biom12111633.

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Baby Boom (BBM) is a key transcription factor that triggers embryogenesis, enhances transformation and regeneration efficiencies, and regulates developmental pathways in plants. Triggering or activating BBM in non-model crops could overcome the bottlenecks in plant breeding. Understanding BBM’s structure is critical for functional characterization and determination of interacting partners and/or ligands. The current in silico study aimed to study BBM’s sequence and conservation across all plant proteomes, predict protein-protein and protein-ligand interactions, and perform molecular docking an

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6

Menin, Silvia, Matteo Pavan, Veronica Salmaso, Mattia Sturlese, and Stefano Moro. "Thermal Titration Molecular Dynamics (TTMD): Not Your Usual Post-Docking Refinement." International Journal of Molecular Sciences 24, no. 4 (2023): 3596. http://dx.doi.org/10.3390/ijms24043596.

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Molecular docking is one of the most widely used computational approaches in the field of rational drug design, thanks to its favorable balance between the rapidity of execution and the accuracy of provided results. Although very efficient in exploring the conformational degrees of freedom available to the ligand, docking programs can sometimes suffer from inaccurate scoring and ranking of generated poses. To address this issue, several post-docking filters and refinement protocols have been proposed throughout the years, including pharmacophore models and molecular dynamics simulations. In th

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7

Bera, Indrani, and Pavan V. Payghan. "Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery." Current Pharmaceutical Design 25, no. 31 (2019): 3339–49. http://dx.doi.org/10.2174/1381612825666190903153043.

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Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). M

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8

Hidayatullah, Arief, Wira Eka Putra, Sustiprijatno Sustiprijatno, Diana Widiastuti, Wa Ode Salma, and Muhammad Fikri Heikal. "Molecular Docking and Molecular Dynamics Simulation-Based Identification of Natural Inhibitors against Druggable Human Papilloma Virus Type 16 Target." Trends in Sciences 20, no. 4 (2023): 4891. http://dx.doi.org/10.48048/tis.2023.4891.

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The E5 protein is the smallest known oncoprotein linked to HPV 16 cancer development. In this study, we determined the potential of asarinin and thiazolo as an inhibitor of the E5 protein through molecular dynamics. The results showed that the binding site is unstable because of its hydrophobic nature and small size, causing considerable changes in the binding site for each of the 3 drugs examined. Except for asarinin, which still interacts with the first hydrophobic domain, they preserved their capacity to prevent endosomal acidification, hyper amplification of the EGFR pathway and contact wi

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Mishra and Dey. "Molecular Docking Studies of a Cyclic Octapeptide-Cyclosaplin from Sandalwood." Biomolecules 9, no. 11 (2019): 740. http://dx.doi.org/10.3390/biom9110740.

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Natural products from plants, such as chemopreventive agents, attract huge attention because of their low toxicity and high specificity. The rational drug design in combination with structure-based modeling and rapid screening methods offer significant potential for identifying and developing lead anticancer molecules. Thus, the molecular docking method plays an important role in screening a large set of molecules based on their free binding energies and proposes structural hypotheses of how the molecules can inhibit the target. Several peptide-based therapeutics have been developed to combat

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10

Nagamalla, Lavanya, J. V. Shanmukha Kumar, Mohammed Rafi Shaik, et al. "Identification of Novel AXL Kinase Inhibitors Using Ligand-Based Pharmacophore Screening and Molecular Dynamics Simulations." Crystals 12, no. 8 (2022): 1158. http://dx.doi.org/10.3390/cryst12081158.

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AXL kinase is a promising target in novel drug discovery for cancer. A ligand-based pharmacophore model was generated with the Pharmit web server. Its inbuilt PubChem molecule database was screened and led to 408 candidate molecules. Docking of the AXL kinase active sites with the identified list of candidate molecules was carried out with Autodock Vina docking software. This resulted in four compounds selected for further investigation. Molecular dynamics simulation of two ligands (PubChem-122421875 and PubChem-78160848) showed considerable binding with AXL kinase. From the MM-PBSA binding fr

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