Transition path theory from biased simulations

Bartolucci, Giacomo; Orioli, Simone; Faccioli, Pietro

doi:10.1063/1.5027253

Cited by 19 publications

(19 citation statements)

References 54 publications

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“…rMD-based methods have been successfully applied to simulate protein folding and other conformational transitions (17,18). However, this scheme provides a sampling of the transition path ensemble only if the biasing force is applied along a reliable reaction coordinate (19). Therefore, the first step towards developing our rMD simulation was to build a statistical model to identify the reaction coordinate of the process.…”

Section: Resultsmentioning

confidence: 99%

Full Atomistic Model of Prion Structure and Conversion

Spagnolli

Rigoli

Orioli

et al. 2018

Preprint

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Prions are unusual protein assemblies that propagate their conformationally-encoded information in absence of nucleic acids. The first prion identified, the scrapie isoform (PrP Sc ) of the cellular prion protein (PrP C ), is the only one known to cause epidemic and epizootic episodes(1). Most aggregates of other misfolding-prone proteins are amyloids, often arranged in a Parallel-In-Register-β-Sheet (PIRIBS)(2) or βsolenoid conformations(3). Similar folding models have also been proposed for PrP Sc , although none of these have been confirmed experimentally. Recent cryo-electron microscopy (cryo-EM) and X-ray fiberdiffraction studies provided evidence that PrP Sc is structured as a 4-rung β-solenoid (4RβS)(4, 5). Here, we combined different experimental data and computational techniques to build the first physically-plausible, atomic resolution model of mouse PrP Sc , based on the 4RβS architecture. The stability of this new PrP Sc model, as assessed by Molecular Dynamics (MD) simulations, was found to be comparable to that of the prion forming domain of Het-s, a naturally-occurring β-solenoid. Importantly, the 4RβS arrangement allowed the first simulation of the sequence of events underlying PrP C conversion into PrP Sc . Our results provide the most updated, experimentally-driven and physically-coherent model of PrP Sc , together with an unprecedented reconstruction of the mechanism underlying the self-catalytic propagation of prions. SignificanceSince the original hypothesis by Stanley Prusiner, prions have represented enigmatic agents diverging from the classical concept of genetic inheritance. However, the structure of PrP Sc , the infectious isoform of the cellular prion protein (PrP C ), has so far remained elusive, mostly due to technical challenges posed by its aggregation propensity. Here, we present a new high resolution model of PrP Sc derived from the integration of a wide array of recent experimental constraints. By coupling the information of such model with a newly developed computational method, we reconstructed for the first time the conformational transition of PrP C to PrP Sc . This study offers a unique workbench for designing therapeutics against prion diseases, and a physically-plausible mechanism explaining how protein conformation could self-propagate.

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Section: Resultsmentioning

confidence: 99%

Full Atomistic Model of Prion Structure and Conversion

Spagnolli

Rigoli

Orioli

et al. 2018

Preprint

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“…The BF variational principle allows the subsequent identification of the rMD transition pathways with the highest probability to occur in the absence of biasing force. It has been rigorously shown that rMD yields realistic transition path ensembles when the CV used in the biasing force is an ideal reaction coordinate (RC), namely the committor function [16]. However, whenever a reasonable proxy of the RC is available, then the BF variational scheme enables to keep the systematic errors of rMD to a minimum.…”

Section: Introductionmentioning

confidence: 99%

“…It has been shown that SCPS provides a rigorous mean-field approximation of the unbiased Langevin dynamics, even when the initial guess of reaction coordinate is suboptimal [16,22]. Thus, SCPS provides a much better tool than BF to investigate structural reactions in which the reaction coordinate is poorly known, thus including prion propagation.…”

Section: Introductionmentioning

confidence: 99%

All-Atom Simulation of the HET-s Prion Replication

Spagnolli²,

Boldrini

et al. 2020

Preprint

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Prions are self-replicative protein particles lacking nucleic acids. Originally discovered for causing infectious neurodegenerative disorders, they have also been found to play several physiological roles in a variety of species. Functional and pathogenic prions share a common mechanism of replication, characterized by the ability of an amyloid conformer to propagate by inducing the conversion of its physiological, soluble counterpart. In this work, we focus on the propagation of the prion forming domain of HET-s, a physiological fungal prion for which high-resolution structural data are available. Since time-resolved biophysical experiments cannot yield a full reconstruction of prion replication, we resort to computational methods. To overcome the computational limitations of plain Molecular Dynamics (MD) simulations, we adopt a special type of biased dynamics called ratchet-and-pawl MD (rMD). The accuracy of this enhanced path sampling protocol strongly depends on the choice of the collective variable (CV) used to define the biasing force. Since for prion propagation a reliable reaction coordinate (RC) is not yet available, we resort to the recently developed Self-Consistent Path Sampling (SCPS). Indeed, in such an approach the CV where the biasing force is applied is not heuristically postulated but is calculated through an iterative refinement procedure. Our atomistic reconstruction of the HET-s replication shows remarkable similarities with a previously reported mechanism of mammalian PrP Sc propagation obtained with a different computational protocol. Together, these results indicate that the propagation of prions generated by evolutionary distant proteins shares common features. In particular, in both these cases, prions propagate their conformation through a very similar templating mechanism.

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“…Recently, more elaborate statistical methods have been proposed for recovering equilibrium distributions from SCPS and BF nonequilibrium simulations. For example, a recently proposed scheme makes it possible to sample the Boltzmann distribution in the transition region by means of specific ratchetand-pawl simulations (77). To date, however, these techniques have only been validated against MD simulations for simple systems, and further validation is required to assess their accuracy for realistic and biologically relevant systems.…”

Section: All-atom-enhanced Sampling Based On a Native-centric Biasingmentioning

confidence: 99%

Successes and challenges in simulating the folding of large proteins

Gershenson

Gosavi

Faccioli

et al. 2020

Journal of Biological Chemistry

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Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structurebased models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.

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Transition path theory from biased simulations

Cited by 19 publications

References 54 publications

Full Atomistic Model of Prion Structure and Conversion

Full Atomistic Model of Prion Structure and Conversion

All-Atom Simulation of the HET-s Prion Replication

Successes and challenges in simulating the folding of large proteins

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