Efficient Sampling of High-Dimensional Free Energy Landscapes: A Review of Parallel Bias Metadynamics

Alamdari, Sarah; Sampath, Janani; Prakash, Arushi; Gibson, Luke D.; Pfaendtner, Jim

doi:10.1007/978-981-33-6639-8_6

Cited by 6 publications

(6 citation statements)

References 86 publications

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“…In contrast to typical MetaD which uses a high-dimensional bias potential to reconstruct the free energy landscape, in the PBMetaD sampling scheme, multiple 1D bias potentials are constructed on the fly to reconstruct the free energy surface (FES) of a highly dimensional CV space. This approach has previously been applied to converge the FES for many high-dimensional systems. − Mastery of these energy landscapes provides insight into the sidechain interactions that give rise to unique secondary structures in peptoids and the development of predictive models for the rational design of engineered peptoid structures.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains

et al. 2023

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Peptoids are a class of highly customizable biomimetic foldamers that retain properties from both proteins and polymers. It has been shown that peptoids can adopt peptide-like secondary structures through the careful selection of sidechain chemistries, but the underlying conformational landscapes that drive these assemblies at the molecular level remain poorly understood. Given the high flexibility of the peptoid backbone, it is essential that methods applied to study peptoid secondary structure formation possess the requisite sensitivity to discriminate between structurally similar yet energetically distinct microstates. In this work, a generalizable simulation scheme is used to robustly sample the complex folding landscape of various 12mer polypeptoids, resulting in a predictive model that links sidechain chemistry with preferential assembly into one of 12 accessible backbone motifs. Using a variant of the metadynamics sampling method, four peptoid dodecamers are simulated in water: sarcosine, N-(1-phenylmethyl)glycine (Npm), (S)-N-(1-phenylethyl)glycine (Nspe), and (R)-N-(1-phenylethyl)glycine (Nrpe)to determine the underlying entropic and energetic impacts of hydrophobic and chiral peptoid sidechains on secondary structure formation. Our results indicate that the driving forces to assemble Nrpe and Nspe sequences into polyproline type-I helices in water are found to be enthalpically driven, with small benefits from an entropic gain for isomerization and steric strain due to the presence of the chiral center. The minor entropic gains from bulky chiral sidechains in Nrpe- and Nspe-containing peptoids can be explained through increased configurational entropy in the cis state. However, overall assembly into a helix is found to be overall entropically unfavorable. These results highlight the importance of considering the many various competing interactions in the rational design of peptoid secondary structure building blocks.

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Section: Introductionmentioning

confidence: 99%

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains

et al. 2023

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“…In the PBMetaD sampling scheme, multiple 1D bias potentials are deposited on the fly and later reconstructed to fully sample and characterize a highly dimensional CV space. This approach has previously been shown to converge exactly and been applied to a number of other high-dimensional systems. − In the parallel bias metadynamics scheme, the following CVs were biased using 1D well-tempered metadynamics potentials: ring coordination number for each aromatic pair (sigma = 0.5), overall coordination number (sigma = 0.5), radius of gyration (sigma = 0.5 nm), backbone ω dihedrals (sigma = 0.35 rad), backbone ϕ dihedrals (sigma = 0.35 rad), backbone ψ dihedrals (sigma = 0.35 rad), and sidechain χ 1 dihedrals (sigma = 0.35 rad). A Gaussian potential with an initial hill height of 2.5 kJ/mol, a bias factor of 50, and a hill deposition pace of 1 hill/1 ps (500 steps) was used.…”

Section: Methodsmentioning

confidence: 99%

Origins of Conformational Heterogeneity in Peptoid Helices Formed by Chiral N-1-Phenylethyl Sidechains

Alamdari

Pfaendtner

2023

J. Phys. Chem. B

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N-substituted glycines (polypeptoids) containing chiral hydrophobic sidechains are known to fold into biomimetic alpha helices. These helix formers often produce conformationally heterogeneous structures and are difficult to characterize at a sub-nanometer resolution. Previously, peptoid N-1-phenylethyl (S)-enantiomer sidechains (Nspe) were inferred from various experiments to form right-handed helices and (R)-enantiomers (Nrpe), left-handed helices. Prior computational work for N(s/r)pe oligomers has struggled to reproduce this trend. Herein, quantum mechanics calculations and molecular dynamics simulations are used to understand the origins of this discrepancy. Results from DFT and molecular mechanics calculations on a variety of Nspe and Nrpe oligomers as a function of chain length are in agreement, showing that Nspe and Nrpe prefer left- and right-handed helices, respectively. Additional metadynamics simulations are used to study Nrpe and Nspe oligomers folding in water. These results show that the free-energy driving forces for assembly into a helical backbone configuration are very small (within ∼k B T). Lastly, we compare DFT calculations for other experimentally characterized peptoid sidechains, N(r/s)sb, N(r/s)tbe, and N(r/s)npe. In this analysis, we show that peptoid sidechains determined to be more robust experimentally (tbe and npe) have helical preferences opposite the trend seen in less robust assemblies formed by N(r/s)pe and N(r/s)sb chemistries. The more robust tbe and nnpe favor the (S)-enantiomer to right-handed and the (R)-enantiomers to left-handed helices.

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Section: Methodsmentioning

confidence: 99%

“…This method was found to be very efficient for revealing the free energy estimates associated with various biological and chemical systems that have high energy barriers. 49,[63][64][65][66] By contrast, umbrella sampling provides control over a given CV to model the conformational transitions aided by a series of independent windows. 48,67,68 The method of combining umbrella sampling and metadynamics biases for the sampling of high-dimensional free energy surfaces was proposed by Filizola and co-workers 69 and by Nair and co-workers.…”

Section: Equilibration and Simulationmentioning

confidence: 99%

Molecular insights into the stereospecificity of arginine in RNA tetraloop folding

Vijay

Mukherjee

2023

Phys. Chem. Chem. Phys.

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Efficient Sampling of High-Dimensional Free Energy Landscapes: A Review of Parallel Bias Metadynamics

Cited by 6 publications

References 86 publications

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains

Origins of Conformational Heterogeneity in Peptoid Helices Formed by Chiral N-1-Phenylethyl Sidechains

Molecular insights into the stereospecificity of arginine in RNA tetraloop folding

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