A kinetic ensemble of the Alzheimer’s Aβ peptide

Löhr, Thomas; Kohlhoff, Kai; Heller, Gabriella T.; Camilloni, Carlo; Vendruscolo, Michele

doi:10.1038/s43588-020-00003-w

Cited by 53 publications

(112 citation statements)

References 76 publications

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“…(7,8) for thorough reviews. MSMs have successfully been built to obtain compact and yet accurate representations of the kinetics of full proteins (9)(10)(11)(12)(13)(14)(15)(16), protein-ligand (17)(18)(19)(20)(21)(22) and even protein-protein systems (23).…”

confidence: 99%

“…In practice, we will apply the trace and Frobenius norms that correspond to the VAMP-1 and VAMP-2 scores of the Koopman operator. The VAMP-2 score has successfully been used in many practical applications (16,45,47,48). If our molecu-lar system consists of N independent subdomains such that its global MSM is a Kronecker product of N subspace MSMs as described above, its VAMP score is the simple product of VAMP scores (SI Appendix, VAMP score decomposition):…”

Section: Markov State Modelsmentioning

confidence: 99%

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Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes

Hempel

Razo

Lee

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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To advance the mission of in silico cell biology, modeling the interactions of large and complex biological systems becomes increasingly relevant. The combination of molecular dynamics (MD) simulations and Markov state models (MSMs) has enabled the construction of simplified models of molecular kinetics on long timescales. Despite its success, this approach is inherently limited by the size of the molecular system. With increasing size of macromolecular complexes, the number of independent or weakly coupled subsystems increases, and the number of global system states increases exponentially, making the sampling of all distinct global states unfeasible. In this work, we present a technique called independent Markov decomposition (IMD) that leverages weak coupling between subsystems to compute a global kinetic model without requiring the sampling of all combinatorial states of subsystems. We give a theoretical basis for IMD and propose an approach for finding and validating such a decomposition. Using empirical few-state MSMs of ion channel models that are well established in electrophysiology, we demonstrate that IMD models can reproduce experimental conductance measurements with a major reduction in sampling compared with a standard MSM approach. We further show how to find the optimal partition of all-atom protein simulations into weakly coupled subunits.

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confidence: 99%

Section: Markov State Modelsmentioning

confidence: 99%

Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes

Hempel

Razo

Lee

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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show abstract

“…All simulations were performed on the Google Compute Engine with n1-highcpu-8 preemptible virtual machine instances, equipped with eight Intel Haswell CPU cores and 7.2 GB of RAM. Molecular dynamics simulations were performed with GROMACS 2018.1 [47], with 1,024 starting structures sampled from the previously performed apo simulation [6] using the Koopman model weights. Each conformation was placed in the center of a rhombic dodecahedron box with a volume of 358 nm 3 , and the corresponding small molecule was placed in the corner of the box.…”

Section: Details Of the Simulationsmentioning

confidence: 99%

“…State decomposition and kinetic model construction was performed using the constrained VAMPNet approach [24,25], using the same method described previously [6]. We again chose flattened inter-residue nearest-neighbour heavyatom distance matrices as inputs, resulting in 780 input dimensions.…”

Section: Details Of the Neural Networkmentioning

confidence: 99%

“…transition rates, relaxation constants, autocorrelations, and state lifetimes can be challenging. This is because in contrast to folded systems, the definition of states for disordered proteins is not always clear: due to the generally shallow free energy landscape state transitions may be fast, but not always distinct [6]. New developments in the theory of dynamical systems now allow an optimal state decomposition and transition operator to be learned using deep neural networks, for example using the VAMPNet framework [24,25].…”

Section: Introductionmentioning

confidence: 99%

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A small molecule stabilises the disordered native state of the Alzheimer’s Aβ peptide

Löhr

Kohlhoff

Heller

et al. 2021

Preprint

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The stabilisation of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here we report a small molecule that stabilises the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer’s disease. We show that this stabilisation takes place by a dynamic binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favourable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilise disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

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Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules

Brotzakis

2024

Methods in Molecular Biology

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A kinetic ensemble of the Alzheimer’s Aβ peptide

Cited by 53 publications

References 76 publications

Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes

Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes

A small molecule stabilises the disordered native state of the Alzheimer’s Aβ peptide

Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules

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