As Simple As Possible, but Not Simpler: Exploring the Fidelity of Coarse-Grained Protein Models for Simulated Force Spectroscopy

Habibi, Mehdi; Rottler, Jörg; Plotkin, Steven S.

doi:10.1371/journal.pcbi.1005211

Cited by 29 publications

(32 citation statements)

References 92 publications

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“…al. 23 recently demonstrated that three different CG models provide disparate descriptions of the forced unfolding process of a 110 residue peptide, despite the capability of all models to fold the peptide to the proper native structure. Furthermore, the fidelity of the folding process, with respect to an AA reference simulation, did not correlate with the complexity of the model.…”

Section: Introductionmentioning

confidence: 99%

Structural-Kinetic-Thermodynamic Relationships Identified from Physics-based Molecular Simulation Models

Rudzinski

Bereau

2017

Preprint

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Coarse-grained molecular simulation models have provided immense, often general, insight into the complex behavior of condensed-phase systems, but suffer from a lost connection to the true dynamical properties of the underlying system. In general, the physics that is built into a model shapes the free-energy landscape, restricting the attainable static and kinetic properties. In this work, we perform a detailed investigation into the property interrelationships resulting from these restrictions, for a representative system of the helix-coil transition. Inspired by high-throughput studies, we systematically vary force-field parameters and monitor their structural, kinetic, and thermodynamic properties. The focus of our investigation is a simple coarse-grained model, which accurately represents the underlying structural ensemble, i.e., effectively avoids sterically-forbidden configurations. As a result of this built-in physics, we observe a rather large restriction in the topology of the networks characterizing the simulation kinetics. When screening across force-field parameters, we find that structurally-accurate models also best reproduce the kinetics, suggesting structural-kinetic relationships for these models. Additionally, an investigation into thermodynamic properties reveals a link between the cooperativity of the transition and the network topology at a single reference temperature.

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Section: Introductionmentioning

confidence: 99%

Structural-Kinetic-Thermodynamic Relationships Identified from Physics-based Molecular Simulation Models

Rudzinski

Bereau

2017

Preprint

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“…Other studies have analyzed the force--induced mechanical unfolding of a de novo designed SOD1 construct . (39) , obtained by truncating the metal---binding loops (40). In silico methods have also been successfully used to design mutants of β2---microglobulin by changing surface residues to modulate its intrinsic solubility (41).…”

Section: Discussionmentioning

confidence: 99%

In Silico Determined Properties of Designed Superoxide Dismutase-1 Mutants Predict ALS-like Phenotypes In Vitro and In Vivo

DuVal

McAlary

Habibi

et al. 2018

Preprint

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The underlying physical causes of SOD1---related ALS are still not well---understood. We address this problem here by computationally designing two de novo mutants, A89R and K128N, which were predicted theoretically to be either significantly destabilizing or stabilizing respectively. We subjected these in silico designed mutants to a series of experimental tests, including in vitro measures of thermodynamic stability, cell---based aggregation and toxicity assays, and an in vivo developmental model of zebrafish motor neuron axonopathy. The experimental tests validated the theoretical predictions: A89R is an unstable, highly---deleterious mutant, and K128N is a stable, non--toxic mutant. Moreover, K128N is predicted computationally to form an unusually stable heterodimer with the familial ALS mutant A4V. Consistent with this prediction, co---injection of K128N and A4V into zebrafish shows profound rescue of motor neuron pathology. The demonstrated success of these first principles calculations to predict the physical properties of SOD1 mutants holds promise for rationally designed therapies to counter the progression of ALS. SignificanceMutations in the protein superoxide dismutase cause ALS, and many of these mutants have decreased folding stability. We sought to pursue this thread using a synthetic biology approach, where we designed two de novo mutations, one stabilizing and one destabilizing, as predicted using computational molecular dynamics simulations. We then tested these mutants using in vitro, cell--based, and in vivo zebrafish models. We found that the unstable mutant was toxic, and induced a severe ALS phenotype in zebrafish; the predicted stable mutant, on the other hand, behaved even better than WT. In fact, it was able to rescue the ALS phenotype caused by mutant SOD1. We propose a mechanism for this rescue, which may provide an avenue for therapeutic intervention.\bodyMain Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive loss of motor neurons in the motor cortex, brainstem and spinal cord, with a lifetime risk of about 1:400(1). Most cases of ALS cases are sporadic with no consistently identified genetic mutation, however, a significant fraction of familial ALS (fALS) cases are due mutations in Cu,Zn superoxide dismutase (SOD1)(2---4). The ubiquity of disease---associated mutations (currently over 160 (5)) throughout the primary sequence of SOD1 suggests a physico---chemical origin for SOD1--related fALS.When natively folded, SOD1 is a 32 kDa homodimer that catalyzes the dismutation of oxygen radicals to less harmful molecular oxygen and hydrogen peroxide(4). A properly folded monomer binds one zinc and one copper atom, and contains an intramolecular disulfide bond, all of which are important for the stability of the protein(4). Loss of any of these factors increases the likelihood of SOD1 misfolding into a toxic disease state due to a decrease in stability and invariable formation of toxic aggregates(6). Indeed, SOD1---related fALS mutations ar...

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“…[24][25][26] Although these models have been useful for investigating the environment-dependent folding processes of IDPs 27,28 (i.e., coupled folding and binding processes), their reliance on a well-defined native structure limits their ability to describe unfolded or disordered conformations. This limitation can even propagate into the characterization of the folding process of globular proteins, resulting in a qualitatively incorrect representation of folding pathways 29 .…”

Section: Introductionmentioning

confidence: 99%

Investigating the Conformational Ensembles of Intrinsically-Disordered Proteins with a Simple Physics-Based Model

Zhao

Cortes-Huerto

Kremer

et al. 2020

Preprint

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Intrinsically disordered proteins (IDPs) play an important role in an array of biological processes but present a number of fundamental challenges for computational modeling. Recently, simple polymer models have regained popularity for interpreting the experimental characterization of IDPs. Homopolymer theory provides a strong foundation for understanding generic features of phenomena ranging from single-chain conformational dynamics to the properties of entangled polymer melts, but is difficult to extend to the copolymer context. This challenge is magnified for proteins due to the variety of competing interactions and large deviations in side-chain properties. In this work, we apply a simple physics-based coarse-grained model for describing largely disordered conformational ensembles of peptides, based on the premise that sampling sterically-forbidden conformations can compromise the faithful description of both static and dynamical properties. The Hamiltonian of the employed model can be easily adjusted to investigate the impact of distinct interactions and sequence specificity on the randomness of the resulting conformational ensemble. In particular, starting with a bead-spring-like model and then adding more detailed interactions one by one, we construct a hierarchical set of models and perform a detailed comparison of their properties. Our analysis clarifies the role of generic attractions, electrostatics and side-chain sterics, while providing a foundation for developing efficient models for IDPs that retain an accurate description of the hierarchy of conformational dynamics, which is nontrivially influenced by interactions with surrounding proteins and solvent molecules.

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As Simple As Possible, but Not Simpler: Exploring the Fidelity of Coarse-Grained Protein Models for Simulated Force Spectroscopy

Cited by 29 publications

References 92 publications

Structural-Kinetic-Thermodynamic Relationships Identified from Physics-based Molecular Simulation Models

Structural-Kinetic-Thermodynamic Relationships Identified from Physics-based Molecular Simulation Models

In Silico Determined Properties of Designed Superoxide Dismutase-1 Mutants Predict ALS-like Phenotypes In Vitro and In Vivo

Investigating the Conformational Ensembles of Intrinsically-Disordered Proteins with a Simple Physics-Based Model

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