Binding Mechanisms of fluorophores to Mango-II revealed by multiple-replica molecular dynamics simulations

2021 ◽  
Author(s):  
Junxiao Chen ◽  
Na Li ◽  
Xingyu Wang ◽  
Jianzhong Chen ◽  
John Z.H. Zhang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Molecular Mechanism ◽  
Small Molecule ◽  
Rna Aptamers ◽  
Dynamics Simulations ◽  
Binding Mechanisms

Recently, the RNA aptamers activating small-molecule fluorophores have been successfully applied to tag and track RNAs in vivo. It is of significance to investigate the molecular mechanism of the fluorophore-RNA...

Quantitative Ranking of Ligand Binding Kinetics with a Multiscale Milestoning Simulation Approach

2018 ◽  
Author(s):  
Benjamin R. Jagger ◽  
Christoper T. Lee ◽  
Rommie Amaro
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Small Molecule ◽  
Brownian Dynamics ◽  
Model Simulation ◽  
Computational Cost ◽  
Lead Selection ◽  
Delta G ◽  
Dynamics Simulations

<p>The ranking of small molecule binders by their kinetic (kon and koff) and thermodynamic (delta G) properties can be a valuable metric for lead selection and optimization in a drug discovery campaign, as these quantities are often indicators of in vivo efficacy. Efficient and accurate predictions of these quantities can aid the in drug discovery effort, acting as a screening step. We have previously described a hybrid molecular dynamics, Brownian dynamics, and milestoning model, Simulation Enabled Estimation of Kinetic Rates (SEEKR), that can predict kon’s, koff’s, and G’s. Here we demonstrate the effectiveness of this approach for ranking a series of seven small molecule compounds for the model system, -cyclodextrin, based on predicted kon’s and koff’s. We compare our results using SEEKR to experimentally determined rates as well as rates calculated using long-timescale molecular dynamics simulations and show that SEEKR can effectively rank the compounds by koff and G with reduced computational cost. We also provide a discussion of convergence properties and sensitivities of calculations with SEEKR to establish “best practices” for its future use.</p>

Machine learning and molecular dynamics simulations assisted evolutionary design and discovery pipeline to screen the efficient small molecule acceptors for PTB7-Th based organic solar cells with over 15% efficiency

2022 ◽  
Author(s):  
Jin-Liang Wang ◽  
Asif Mahmood ◽  
Ahmad Irfan
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Solar Cells ◽  
Molecular Dynamics Simulations ◽  
Small Molecule ◽  
Organic Solar Cells ◽  
Evolutionary Design ◽  
New Materials ◽  
Dynamics Simulations ◽  
Discovery Pipeline

Organic solar cells are the most promising candidates for future commercialization. This goal can be quickly achieved by designing new materials and predicting their performance without experimentation to reduce the...

scholarly journals DNA triplex structure, thermodynamics, and destabilisation: insight from molecular simulations

2018 ◽  
Vol 20 (20) ◽  
pp. 14013-14023 ◽  
Author(s):  
Belinda J. Boehm ◽  
Charles Whidborne ◽  
Alexander L. Button ◽  
Tara L. Pukala ◽  
David M. Huang
Keyword(s):  
Molecular Dynamics ◽  
Neurodegenerative Disease ◽  
Molecular Dynamics Simulations ◽  
Small Molecule ◽  
Molecular Simulations ◽  
Friedreich’S Ataxia ◽  
Dna Triplexes ◽  
Dna Triplex ◽  
Triplex Structure ◽  
Dynamics Simulations

Molecular dynamics simulations are used to elucidate the structure and thermodynamics of DNA triplexes associated with the neurodegenerative disease Friedreich's ataxia (FRDA), as well as complexes of these triplexes with the small molecule netropsin, which is known to destabilise triplexes.

scholarly journals Exploring Aurone Derivatives as Potential Human Pancreatic Lipase Inhibitors through Molecular Docking and Molecular Dynamics Simulations

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4657
Author(s):  
Phuong Thuy Viet Nguyen ◽  
Han Ai Huynh ◽  
Dat Van Truong ◽  
Thanh-Dao Tran ◽  
Cam-Van Thi Vo
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Pancreatic Lipase ◽  
Inhibitory Activity ◽  
Dynamics Simulation ◽  
Stable Complex ◽  
Catalytic Active Site ◽  
Dynamics Simulations

Inhibition of human pancreatic lipase, a crucial enzyme in dietary fat digestion and absorption, is a potent therapeutic approach for obesity treatment. In this study, human pancreatic lipase inhibitory activity of aurone derivatives was explored by molecular modeling approaches. The target protein was human pancreatic lipase (PDB ID: 1LPB). The 3D structures of 82 published bioactive aurone derivatives were docked successfully into the protein catalytic active site, using AutoDock Vina 1.5.7.rc1. Of them, 62 compounds interacted with the key residues of catalytic trial Ser152-Asp176-His263. The top hit compound (A14), with a docking score of −10.6 kcal⋅mol−1, was subsequently submitted to molecular dynamics simulations, using GROMACS 2018.01. Molecular dynamics simulation results showed that A14 formed a stable complex with 1LPB protein via hydrogen bonds with important residues in regulating enzyme activity (Ser152 and Phe77). Compound A14 showed high potency for further studies, such as the synthesis, in vitro and in vivo tests for pancreatic lipase inhibitory activity.

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