scholarly journals Mineral and Protein-Bound Water and Latching Action Control Mechanical Behavior at Protein-Mineral Interfaces in Biological Nanocomposites

2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Pijush Ghosh ◽  
Dinesh R. Katti ◽  
Kalpana S. Katti
Keyword(s):  
Mechanical Behavior ◽  
Protein Interactions ◽  
Protein Unfolding ◽  
Early Stage ◽  
Bound Water ◽  
Amino Acid Side Chain ◽  
Organic Layers ◽  
Close Proximity ◽  
Mineral Interfaces ◽  
Dynamics Simulations

The nacre structure consists of laminated interlocked mineral platelets separated by nanoscale organic layers. Here, the role of close proximity of mineral to the proteins on mechanical behavior of the protein is investigated through steered molecular dynamics simulations. Our simulations indicate that energy required for unfolding protein in the proximity of mineral aragonite is several times higher than that for isolated protein in the absence of the mineral. Here, we present details of specific mechanisms which result in higher energy for protein unfolding in the proximity of mineral. At the early stage of pulling, peaks in the load-displacement (LD) plot at mineral proximity are quantitatively correlated to the interaction energy between atoms involved in the latching phenomenon of amino acid side chain to aragonite surface. Water plays an important role during mineral and protein interaction and water molecules closer to the mineral surface are highly oriented and remain rigidly attached as the protein strand is pulled. Also, the high magnitude of load for a given displacement originates from attractive interactions between the protein, protein-bound water, and mineral. This study provides an insight into mineral-protein interactions that are predominant in biological nanocomposites and also provides guidelines towards design of biomimetic nanocomposites.

scholarly journals Mechanism of NanR gene repression and allosteric induction of bacterial sialic acid metabolism

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Christopher R. Horne ◽  
Hariprasad Venugopal ◽  
Santosh Panjikar ◽  
David M. Wood ◽  
Amy Henrickson ◽  
...  
Keyword(s):  
Sialic Acid ◽  
Dna Binding ◽  
Protein Interactions ◽  
Acid Metabolism ◽  
Environmental Changes ◽  
Dna Interaction ◽  
Protein Protein Interactions ◽  
Nutrient Source ◽  
Cryo Electron Microscopy ◽  
Close Proximity

AbstractBacteria respond to environmental changes by inducing transcription of some genes and repressing others. Sialic acids, which coat human cell surfaces, are a nutrient source for pathogenic and commensal bacteria. The Escherichia coli GntR-type transcriptional repressor, NanR, regulates sialic acid metabolism, but the mechanism is unclear. Here, we demonstrate that three NanR dimers bind a (GGTATA)3-repeat operator cooperatively and with high affinity. Single-particle cryo-electron microscopy structures reveal the DNA-binding domain is reorganized to engage DNA, while three dimers assemble in close proximity across the (GGTATA)3-repeat operator. Such an interaction allows cooperative protein-protein interactions between NanR dimers via their N-terminal extensions. The effector, N-acetylneuraminate, binds NanR and attenuates the NanR-DNA interaction. The crystal structure of NanR in complex with N-acetylneuraminate reveals a domain rearrangement upon N-acetylneuraminate binding to lock NanR in a conformation that weakens DNA binding. Our data provide a molecular basis for the regulation of bacterial sialic acid metabolism.

scholarly journals Protein unfolding by SDS: the microscopic mechanisms and the properties of the SDS-protein assembly

Nanoscale ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 5422-5434 ◽  
Author(s):  
David Winogradoff ◽  
Shalini John ◽  
Aleksei Aksimentiev
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Anionic Surfactant ◽  
Protein Unfolding ◽  
Protein Assembly ◽  
Full Length ◽  
Dynamics Simulations

Molecular dynamics simulations reveal how anionic surfactant SDS and heat unfold full-length proteins.

scholarly journals Machine learning identifies two autophagy-related genes as markers of recurrence in colorectal cancer

2020 ◽  
Vol 48 (10) ◽  
pp. 030006052095880
Author(s):  
Jianping Wu ◽  
Sulai Liu ◽  
Xiaoming Chen ◽  
Hongfei Xu ◽  
Yaoping Tang
Keyword(s):  
Colorectal Cancer ◽  
Machine Learning ◽  
Protein Interactions ◽  
Early Stage ◽  
Predictive Ability ◽  
Improve Patient Care ◽  
Active Role ◽  
Risk Groups ◽  
Recurrence Risk ◽  
Machine Learning Algorithms

Objective Colorectal cancer (CRC) is the most common cancer worldwide. Patient outcomes following recurrence of CRC are very poor. Therefore, identifying the risk of CRC recurrence at an early stage would improve patient care. Accumulating evidence shows that autophagy plays an active role in tumorigenesis, recurrence, and metastasis. Methods We used machine learning algorithms and two regression models, univariable Cox proportion and least absolute shrinkage and selection operator (LASSO), to identify 26 autophagy-related genes (ARGs) related to CRC recurrence. Results By functional annotation, these ARGs were shown to be enriched in necroptosis and apoptosis pathways. Protein–protein interactions identified SQSTM1, CASP8, HSP80AB1, FADD, and MAPK9 as core genes in CRC autophagy. Of 26 ARGs, BAX and PARP1 were regarded as having the most significant predictive ability of CRC recurrence, with prediction accuracy of 71.1%. Conclusion These results shed light on prediction of CRC recurrence by ARGs. Stratification of patients into recurrence risk groups by testing ARGs would be a valuable tool for early detection of CRC recurrence.

scholarly journals Universal Screening Methods and Applications of ThermoFluor®

2006 ◽  
Vol 11 (7) ◽  
pp. 854-863 ◽  
Author(s):  
Maxwell D. Cummings ◽  
Michael A. Farnum ◽  
Marina I. Nelen
Keyword(s):  
Protein Interactions ◽  
Protein Function ◽  
Protein Unfolding ◽  
Direct Detection ◽  
Functional Characterization ◽  
Screening Methods ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Bacterial Enzyme ◽  
Research Problems

The genomics revolution has unveiled a wealth of poorly characterized proteins. Scientists are often able to produce milligram quantities of proteins for which function is unknown or hypothetical, based only on very distant sequence homology. Broadly applicable tools for functional characterization are essential to the illumination of these orphan proteins. An additional challenge is the direct detection of inhibitors of protein-protein interactions (and allosteric effectors). Both of these research problems are relevant to, among other things, the challenge of finding and validating new protein targets for drug action. Screening collections of small molecules has long been used in the pharmaceutical industry as 1 method of discovering drug leads. Screening in this context typically involves a function-based assay. Given a sufficient quantity of a protein of interest, significant effort may still be required for functional characterization, assay development, and assay configuration for screening. Increasingly, techniques are being reported that facilitate screening for specific ligands for a protein of unknown function. Such techniques also allow for function-independent screening with better characterized proteins. ThermoFluor®, a screening instrument based on monitoring ligand effects on temperature-dependent protein unfolding, can be applied when protein function is unknown. This technology has proven useful in the decryption of an essential bacterial enzyme and in the discovery of a series of inhibitors of a cancer-related, protein-protein interaction. The authors review some of the tools relevant to these research problems in drug discovery, and describe our experiences with 2 different proteins.

scholarly journals Probing Polyoxometalate-Protein Interactions Using Molecular Dynamics Simulations

2016 ◽  
Vol 22 (43) ◽  
pp. 15280-15289 ◽  
Author(s):  
Albert Solé-Daura ◽  
Vincent Goovaerts ◽  
Karen Stroobants ◽  
Gregory Absillis ◽  
Pablo Jiménez-Lozano ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Protein Interactions ◽  
Dynamics Simulations

scholarly journals Lipid-protein interactions are unique fingerprints for membrane proteins

2017 ◽  
Author(s):  
Valentina Corradi ◽  
Eduardo Mendez-Villuendas ◽  
Helgi I. Ingólfsson ◽  
Ruo-Xu Gu ◽  
Iwona Siuda ◽  
...  
Keyword(s):  
Membrane Proteins ◽  
Protein Interactions ◽  
Cell Membranes ◽  
Spatiotemporal Resolution ◽  
Lipid Dynamics ◽  
Lipid Species ◽  
Lipid Environment ◽  
Lipid Protein Interactions ◽  
Dynamics Simulations ◽  
Asymmetrically Distributed

ABSTRACTCell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Understanding the lateral organization principles of these complex mixtures is essential for life and health. However, our current understanding of the detailed organization of cell membranes remains rather elusive, owing to the lack of experimental methods suitable for studying these fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of ten membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between leaflets. The simulations detail how each protein modulates its local lipid environment through local lipid composition, thickness, curvature and lipid dynamics. Our results provide a molecular glimpse of the complexity of lipid-protein interactions, with potentially far reaching implications for the overall organization of the cell membrane.

scholarly journals Molecular mechanisms associated with clustered lesion-induced impairment of 8-oxoG recognition by the human glycosylase OGG1

2021 ◽  
Author(s):  
Tao Jiang ◽  
Antonio MONARI ◽  
Elise Dumont ◽  
Emmanuelle Bignon
Keyword(s):  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Excision Repair ◽  
Structural Features ◽  
Repair Pathway ◽  
Dna Lesion ◽  
Damage Response ◽  
Base Excision ◽  
Structural Signature ◽  
Dynamics Simulations

The 8-oxo-7,8-dihydroguanine, referred to as 8-oxoG, is a highly mutagenic DNA lesion that can provoke the appearance of mismatches if it escapes the DNA Damage Response. The specific recognition of its structural signature by the hOGG1 glycosylase is the first step along the Base Excision Repair pathway, that ensures the integrity of the genome by preventing the emergence of mutations. 8-oxoG formation, structural features and repair have been the matter of extensive research and more recently this active field of research expended to the more complicated case of 8-oxoG within clustered lesions. Indeed, the presence of a second lesion within 1 or 2 helix turns can dramatically impact the repair yields of 8-oxoG by glycosylases. In this work, we use mu-range molecular dynamics simulations and machine learning-based post-analysis to explore the molecular mechanisms associated with the recognition of 8-oxoG by hOGG1 when embedded in a multiple lesions site with a mismatch in 5' or 3'. We delineate the stiffening of the DNA-protein interactions upon the presence of the mismatches, and rationalize the much lower repair yields reported with a 5' mismatch by describing the perturbation of 8-oxoG structural features upon addition of an adjacent lesion.

scholarly journals Molecular dynamics shows complex interplay and long-range effects of post-translational modifications in yeast protein interactions

2021 ◽  
Vol 17 (5) ◽  
pp. e1008988
Author(s):  
Nikolina ŠoŠtarić ◽  
Vera van Noort
Keyword(s):  
Molecular Dynamics ◽  
Conformational Changes ◽  
Protein Interactions ◽  
Protein Structures ◽  
Cellular Protein ◽  
Free Energy Calculations ◽  
Protein Protein Interactions ◽  
Post Translational Modifications ◽  
Protein Properties ◽  
Dynamics Simulations

Post-translational modifications (PTMs) play a vital, yet often overlooked role in the living cells through modulation of protein properties, such as localization and affinity towards their interactors, thereby enabling quick adaptation to changing environmental conditions. We have previously benchmarked a computational framework for the prediction of PTMs’ effects on the stability of protein-protein interactions, which has molecular dynamics simulations followed by free energy calculations at its core. In the present work, we apply this framework to publicly available data on Saccharomyces cerevisiae protein structures and PTM sites, identified in both normal and stress conditions. We predict proteome-wide effects of acetylations and phosphorylations on protein-protein interactions and find that acetylations more frequently have locally stabilizing roles in protein interactions, while the opposite is true for phosphorylations. However, the overall impact of PTMs on protein-protein interactions is more complex than a simple sum of local changes caused by the introduction of PTMs and adds to our understanding of PTM cross-talk. We further use the obtained data to calculate the conformational changes brought about by PTMs. Finally, conservation of the analyzed PTM residues in orthologues shows that some predictions for yeast proteins will be mirrored to other organisms, including human. This work, therefore, contributes to our overall understanding of the modulation of the cellular protein interaction networks in yeast and beyond.

scholarly journals Multi-Step Concanavalin A Phase Separation and Early-Stage Nucleation Monitored Via Dynamic and Depolarized Light Scattering

Crystals ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 620 ◽  
Author(s):  
Hévila Brognaro ◽  
Sven Falke ◽  
Celestin Nzanzu Mudogo ◽  
Christian Betzel
Keyword(s):  
Phase Separation ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Protein Interactions ◽  
Concanavalin A ◽  
Early Stage ◽  
Protein Crystallization ◽  
Cluster Formation ◽  
Macromolecular Network

Protein phase separation and protein liquid cluster formation have been observed and analysed in protein crystallization experiments and, in recent years, have been reported more frequently, especially in studies related to membraneless organelles and protein cluster formation in cells. A detailed understanding about the phase separation process preceding liquid dense cluster formation will elucidate what has, so far, been poorly understood—despite intracellular crowding and phase separation being very common processes—and will also provide more insights into the early events of in vitro protein crystallization. In this context, the phase separation and crystallization kinetics of concanavalin A were analysed in detail, which applies simultaneous dynamic light scattering and depolarized dynamic light scattering to obtain insights into metastable intermediate states between the soluble phase and the crystalline form. A multi-step mechanism was identified for ConA phase separation, according to the resultant ACF decay, acquired after an increase in the concentration of the crowding agent until a metastable ConA gel intermediate between the soluble and final crystalline phases was observed. The obtained results also revealed that ConA is trapped in a macromolecular network due to short-range intermolecular protein interactions and is unable to transform back into a non-ergodic solution.

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