ATRANET – Automated generation of transition networks for the structural characterization of intrinsically disordered proteins

Schäffler, Moritz; Khaled, Mohammed; Strodel, Birgit

doi:10.1016/j.ymeth.2022.07.013

Cited by 8 publications

(11 citation statements)

References 54 publications

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“…To examine the possibility of an allosteric effect, we calculated transition networks (TNs) using our software ATRANET [40][41][42][43] to reveal conformational transition pathways within mGBP2. Since HREMD data does not allow the construction of TNs due to the exchanges between replicas causing the loss of the information about time correlation between states, we run standard MD simulations of 1 µs length for both mGBP2 apo and mGBP2 holo .…”

Section: /27mentioning

confidence: 99%

Domain motions, dimerization, and membrane interactions of the murine guanylate binding protein 2

Loschwitz

Wang

Strodel

2022

Preprint

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Guanylate-binding proteins (GBPs) are a group of interferon-inducible GTPases that are essential components of cell-autonomous immunity against intracellular pathogens. They restrict the replication of intracellular pathogens by targeting and lysing the membrane of the pathogen-containing vacuole. The aim of our work is to provide a molecular-level understanding of how the GBPs destroy the parasitophorous vacuole membrane. To this end, we use molecular dynamics (MD) simulations to elucidate the domain motions of GBPs and the effects on these motions following GTP binding, GBP multimerization, and membrane binding, assuming that each of these steps plays important roles in the defense mechanism. Here, we present our results for the murine GBP2, one of the eleven GBPs present in mice, obtained from standard and replica exchange MD simulations with an accumulated simulation time of 30 µs. The main findings are that mGBP2 features a large-scale hinge motion in its M/E domain which is not hugely affected by either GTP binding, geranylgeranylation, homodimer formation, or lipid-membrane binding. Our prognosis is that this hinge motion has the potential to destroy the membrane following the formation of supramolecular mGBP2 complexes on the membrane surface.

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Section: /27mentioning

confidence: 99%

Domain motions, dimerization, and membrane interactions of the murine guanylate binding protein 2

Loschwitz

Wang

Strodel

2022

Preprint

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“…To examine polymorphism in htt, trajectories were filtered based on the value of N int . Compactness was calculated as the ratio of the smallest and largest eigenvalues of the moment of inertia tensors, inspired by the implementation in ATRANET [36].…”

Section: Analysis Methodsmentioning

confidence: 99%

Unraveling the Molecular Complexity of N-Terminus Huntingtin Oligomers: Insights into Polymorphic Structures

Nanajkar,

Sahoo,

Matysiak

2024

Preprint

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Huntington’s disease is a fatal neurodegenerative disease caused by an aberrant polyQ expansion in the Huntingtin protein (htt). In cases with polyQ≥35, the expanded polyQ tract misfolds and forms large intra-cellular aggregates. Despite significant attention, no clear consensus has been reached on the aggregate structures of the Huntingtin exon 1 protein fragments. Here, we apply coarse grained molecular dynamics to examine the mechanisms driving the aggregation process and resulting aggregate structures of 5 different N17 + polyQ systems, with polyQ lengths of 7, 15, 35, 40 and 45, using the ProMPT forcefield. Elongation of the polyQ domain results in an increase inβ-sheet rich structures. At longer polyQ lengths, intra-molecularβ-sheets are preferred over inter-molecular sheets, due to the collapse of the elongated polyQ domain into hairpin rich conformations. Crucially, we have discovered that changes in the polyQ length affect the resulting aggregated structure. With short polyQ domains, the N17 domains of htt bundle together, forming a hydrophobic core. As the polyQ length increases, competition between the hydrophobic interactions of N17 and the polar interactions of polyQ arises, leading to a tightly packed polyQ core, with an external distribution of the N17 domains. These findings can help explain the toxic gain-of function that mutant htt acquires.Author summaryIn this work, we consider 5 huntingtin peptide systems-N17 with polyQ lengths of 7, 15 35, 40 and 45, and examine structural characteristics of both the monomeric and aggregated peptide systems. We observe the presence of helices andβ-sheet in the polyQ domain. Most importantly, we discovered that the polyQ length affects the resultant aggregate structure. With short polyQ lengths, there is a competition between the hydrophobic interactions of N17 and the polar interactions of the polyQ domain, leading to a bundling of the N17 domains. At longer lengths of polyQ, the polar interactions dominate leading to a loss of N17 bundling and external distribution of the N17 domains. We suspect these variations in the aggregate morphology could explain possible downstream effects in Huntington’s disease pathology.

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“…In parallel, work on transition networks continued 214 and resulted in the ATRANET software package, an open‐source Python script for automated calculation of transition networks for both monomeric proteins, including IDPs, and amyloid aggregation (https://github.com/strodel-group/ATRANET). 188,215 The similarities and differences of MSMs and conventional conformational transition networks for characterizing amyloid aggregation pathways were analyzed for the dimerization of

{\mathrm{A}\upbeta}_{16-22}

188 . In general, both methods show excellent results in identifying the major aggregation pathways.…”

Section: Review Of Simulation Studies On Amyloid Aggregationmentioning

confidence: 99%

A brief history of amyloid aggregation simulations

Fatafta,

Khaled,

Kav

et al. 2024

WIREs Comput Mol Sci

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Amyloid proteins are characterized by their tendency to aggregate into amyloid fibrils, which are often associated with devastating diseases. Aggregation pathways typically involve unfolding or misfolding of monomeric proteins and formation of transient oligomers and protofibrils before the final aggregation product is formed. The conformational dynamics and polymorphic and volatile nature of these aggregation intermediates make their characterization by experimental techniques alone insufficient and also require computational approaches. Over the past 25 years, the size of simulated amyloid aggregation systems and the length of these simulations have increased significantly. These advances are discussed here. The review includes simulation approaches that model the aggregating peptides or proteins at both the all‐atom and coarse‐grained levels, use molecular dynamics simulations or Monte Carlo sampling to simulate the conformational changes, and present results for various amyloid peptides and proteins ranging from Lys‐Phe‐Phe‐Glu (KFFE) as the smallest system to as an intermediate‐sized peptide to α‐synuclein. The presentation of the history of amyloid aggregation simulations concludes with a discussion of where the future of these simulations may lie.This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods

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ATRANET – Automated generation of transition networks for the structural characterization of intrinsically disordered proteins

Cited by 8 publications

References 54 publications

Domain motions, dimerization, and membrane interactions of the murine guanylate binding protein 2

Domain motions, dimerization, and membrane interactions of the murine guanylate binding protein 2

Unraveling the Molecular Complexity of N-Terminus Huntingtin Oligomers: Insights into Polymorphic Structures

A brief history of amyloid aggregation simulations

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