Exploring Protocols to Build Reservoirs to Accelerate Temperature Replica Exchange MD Simulations

Kasavajhala, Koushik; Lam, Kenneth; Simmerling, Carlos

doi:10.1021/acs.jctc.0c00513

Cited by 11 publications

(54 citation statements)

References 57 publications

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Section: Resultssupporting

confidence: 76%

“…6c), which indicates that insufficient sampling to obtain an equilibrium ensemble in the 419K reservoir results in convergence to a non-equilibrium (incorrect) ensemble at 300K. Similar effects have been observed in Kasavajhala et al 86 To further investigate the composition of the reservoir when accumulating states to generate an equilibrium ensemble in the reservoir, the conformational states of conventional MD at 419K and 475K were evenly sampled and projected on 2 dimensional phase space by t-SNE analysis 97 (see Section 2.8.1) (Fig. 7b).…”

Section: Reservoir Temperature Should Be High Enough To Prevent Insuf...supporting

confidence: 76%

“…All Res-REMD simulations in this study are Boltzmann-weighted Res-REMD, in that reservoir is Boltzmann sampled. The number of states in the reservoir for each simulation are all well above the recommended range of 1000-5000 conformations 86 for a Boltzmann-weighted reservoir.…”

Section: Methodsmentioning

confidence: 82%

“…This is far from the 100 folding/unfolding transitions suggested for sufficient reservoir convergence. 86 To generate a correct reservoir, a PMF-weighted method was thus used (See Section 2.7).…”

Section: Resultsmentioning

confidence: 99%

“…This method is similar to finding the cluster population correlation from combined clustering. 86 The difference here is that our clusters were pre-defined to be the torsional states, instead of being assigned from structural clustering.…”

Section: Ensemble Similarity Analysis For Cyclic Peptides 261 Torsion...mentioning

confidence: 99%

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Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS

Hsueh

Aina

Plotkin

2022

Preprint

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Cyclic peptides naturally occur as antibiotics, fungicides, and immunosuppressants, and have been adapted for use as potential therapeutics. Scaffolded cyclic peptide antigens have many protein characteristics such as reduced toxicity, increased stability over linear peptides, and conformational selectivity, but with fewer amino acids than whole proteins. The profile of shapes presented by a cyclic peptide modulates its therapeutic efficacy, and is represented by the ensemble of its sampled conformations. Although some algorithms excel in creating a diverse ensemble of cyclic peptide conformations, they seldom address the entropic contribution of flexible conformations, and they often have significant practical difficulty producing an ensemble with converged and reliable thermodynamic properties. In this study, an accelerated molecular dynamics (MD) method, reservoir replica exchange MD (R-REMD or Res-REMD), was implemented in GROMACS-4.6.7, and benchmarked on three small cyclic peptide model systems: a cyclized segment of Aβ (cyclo-(CGHHQKLVG)), a cyclized furin cleavage site of SARS-CoV-2 spike (cyclo-(CGPRRARSG)), and oxytocin (disulfide bonded CYIQNCPLG). Additionally, we also benchmarked Res-REMD on Alanine dipeptide and Trpzip2 to demonstrate its validity and efficiency over REMD. Compared to REMD, Res-REMD significantly accelerated the ensemble generation of cyclo-(CGHHQKLVG), but not cyclo-(CGPRRARSG) or oxytocin. This difference is due to the longer auto-correlation time of torsional angles in cyclo-(CGHHQKLVG) vs. the latter two cyclic peptide systems; The randomly seeded reservoir in Res-REMD thus accelerates sampling and convergence. The auto-correlation time of the torsional angles can thus be used to determine whether Res-REMD is preferable to REMD for cyclic peptides. We provide a github page with modified GROMACS source code for running Res-REMD at https://github.com/PlotkinLab/Reservoir-REMD

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Section: Resultssupporting

confidence: 76%

Section: Reservoir Temperature Should Be High Enough To Prevent Insuf...supporting

confidence: 76%

Section: Methodsmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

Section: Ensemble Similarity Analysis For Cyclic Peptides 261 Torsion...mentioning

confidence: 99%

See 3 more Smart Citations

Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS

Hsueh

Aina

Plotkin

2022

Preprint

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Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models

Coppa,

Bazzoli,

Barkhordari

et al. 2023

J. Chem. Inf. Model.

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Accelerated molecular dynamics (aMD) protocols were assessed on predicting the secondary structure of eight peptides, of which two are helical, three are β-hairpins, and three are disordered. Protocols consisted of combinations of three force fields (ff99SB, ff14SB, ff19SB) and two explicit solvation models (TIP3P and OPC), and were evaluated in two independent aMD simulations, one starting from an extended conformation, the other starting from a misfolded conformation. The results of these analyses indicate that all three combinations performed well on helical peptides. As for β-hairpins, ff19SB performed well with both solvation methods, with a slight preference for the TIP3P solvation model, even though performance was dependent on both peptide sequence and initial conformation. The ff19SB/OPC combination had the best performance on intrinsically disordered peptides. In general, ff14SB/TIP3P suffered the strongest helical bias.

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Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

Mostofian,

Martin,

Razavi

et al. 2023

J. Chem. Inf. Model.

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The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein−degrader−ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein−protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

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Exploring Protocols to Build Reservoirs to Accelerate Temperature Replica Exchange MD Simulations

Cited by 11 publications

References 57 publications

Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS

Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS

Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

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