Uncovering Large-Scale Conformational Change in Molecular Dynamics without Prior Knowledge

Melvin, Ryan L.; Godwin, Ryan C.; Xiao, Jiajie; Thompson, W. G.; Berenhaut, Kenneth S.; Salsbury, Freddie R.

doi:10.1021/acs.jctc.6b00757

Cited by 45 publications

(59 citation statements)

References 146 publications

(268 reference statements)

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“…Therefore, clustering analysis was performed on these regulatory regions to identify structural ensembles corresponding to Na + -bound/unbound and K + -bound/unbound states. Using a non-parametric clustering tool we have recently developed based on HDSCAN algorithm, 75,76,82 the conformations of the thrombin in Na + -bound/unbound and K + -bound/unbound states are classified into different groups due to their structural similarity.…”

Section: Resultsmentioning

confidence: 99%

“…The clustering algorithm we utilized here was the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), 75 which has been adapted and employed as a non-parametric approach to group high dimensional MD data by our research group. 76,77 This clustering algorithm has been shown the effectiveness of identifying global conformational changes 76 and thereby was employed here as well to evaluate ion-binding’s influence on the structural ensembles.…”

Section: Methodsmentioning

confidence: 99%

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Mechanistic insights into thrombin's switch between “slow” and “fast” forms

Xiao

Melvin

Salsbury

2017

Phys. Chem. Chem. Phys.

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Thrombin is a multifunctional enzyme that plays an important role in blood coagulation, cell growth, and metastasis. Depending upon the binding of sodium ions, thrombin presents significantly different enzymatic activities. In the environment with sodium ions, thrombin is highly active in cleaving the coagulated substrates and this is referred to as the “fast” form; in the environment without sodium ions, thrombin turns catalytically less active and is in the “slow” form. Although many experimental studies over the last two decades have attempted to reveal the structural and kinetic differences between these two forms, it remains vague and disputed how the functional switch between the “fast” and “slow” forms is mediated by Na+ cations. In this work, we employ microsecond-scale all-atom molecular dynamics simulations to investigate the differences in the structural ensembles in sodium-bound/unbound and potassium-bound/unbound thrombin. Our calculations indicate that the regulatory regions, including the 60s, γ loops, and exosite I and II, are primarily affected by both the bound and unbound cations. Conformational free energy surfaces, estimated from principal component analysis, further reveal the existence of multiple conformational states. The binding of a cation introduces changes in the distribution of these states. Through comparisons with potassium-binding, the binding of sodium ions appears to shift the population toward conformational states that might be catalytically favorable. Our study of thrombin in the presence of sodium/potassium ions suggests Na+-mediated generalized allostery is the mechanism of thrombin’s functional switch between the “fast” and “slow” forms.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Mechanistic insights into thrombin's switch between “slow” and “fast” forms

Xiao

Melvin

Salsbury

2017

Phys. Chem. Chem. Phys.

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“…53 This is a density-based method that results in a hierarchical clustering. However, HDBSCAN differs from other hierarchical techniques in that it does not cut the final dendrogram at one point but rather selects clusters from multiple levels of the tree.…”

Section: Methodsmentioning

confidence: 99%

All-atom MD indicates ion-dependent behavior of therapeutic DNA polymer

Melvin

Gmeiner

Salsbury

2017

Phys. Chem. Chem. Phys.

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Understanding the efficacy of and creating delivery mechanisms for therapeutic nucleic acids requires understanding structural and kinetic properties which allow these polymers to promote the death of cancerous cells. One molecule of interest is a 10mer of FdUMP (5-fluoro-2′-deoxyuridine-5′-O-monophosphate) – also called F10. Here we investigate the structural and kinetic behavior of F10 in intracellular and extracellular solvent conditions along with non-biological conditions that may be efficacious in in vitro preparations of F10 delivery systems. From our all-atom Molecular Dynamics simulations totaling 80 microseconds, we predict that F10’s phosphate groups form close-range interactions with calcium and zinc ions, with calcium having the highest affinity of the five ions investigated. We also predict that F10’s interactions with magnesium, potassium and sodium are almost exclusively long-range interactions. In terms of intramolecular interactions, we find that F10 is least structured (in terms of hydrogen bonds among bases) in the 150mM NaCl (extracellular-like solvent conditions) and most structured in 150mM ZnCl2. Kinetically, we see that F10 is unstable in the presence of magnesium, sodium or potassium, finding stable kinetic traps in the presence of calcium or zinc.

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“…We have chosen to use imwk-means in particular because of our previous success with it, and positive results in comparisons [12,6,16].…”

Section: Clustering and Feature Weightingmentioning

confidence: 99%

Feature weighting as a tool for unsupervised feature selection

Panday

Amorim

Lane

2018

Information Processing Letters

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights• We generate cluster-dependent feature weights reflecting the relevance of features.• Features with a relatively low weight are removed from a data set.• Our methods outperform other popular alternatives in synthetic and real-world data. AbstractFeature selection is a popular data pre-processing step. The aim is to remove some of the features in a data set with minimum information loss, leading to a number of benefits including faster running time and easier data visualisation. In this paper we introduce two unsupervised feature selection algorithms. These make use of a cluster-dependent feature-weighting mechanism reflecting the within-cluster degree of relevance of a given feature. Those features with a relatively low weight are removed from the data set. We compare our algorithms to two other popular alternatives using a number of experiments on both synthetic and real-world data sets, with and without added noisy features. These experiments demonstrate our algorithms clearly outperform the alternatives.

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Uncovering Large-Scale Conformational Change in Molecular Dynamics without Prior Knowledge

Cited by 45 publications

References 146 publications

Mechanistic insights into thrombin's switch between “slow” and “fast” forms

Mechanistic insights into thrombin's switch between “slow” and “fast” forms

All-atom MD indicates ion-dependent behavior of therapeutic DNA polymer

Feature weighting as a tool for unsupervised feature selection

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