scholarly journals The generic unfolding of a biomimetic polymer during force spectroscopy

Soft Matter ◽  
2020 ◽  
Vol 16 (16) ◽  
pp. 3941-3951
Author(s):  
Aviel Chaimovich ◽  
Christian Leitold ◽  
Christoph Dellago

By computing free energies with molecular simulations, we find a general signature for protein unfolding in force spectroscopy, and in turn, we present a useful formula for experimentalists.

2020 ◽  
Vol 36 (20) ◽  
pp. 5014-5020
Author(s):  
Nina I Ilieva ◽  
Nicola Galvanetto ◽  
Michele Allegra ◽  
Marco Brucale ◽  
Alessandro Laio

Abstract Motivation Single-molecule force spectroscopy (SMFS) experiments pose the challenge of analysing protein unfolding data (traces) coming from preparations with heterogeneous composition (e.g. where different proteins are present in the sample). An automatic procedure able to distinguish the unfolding patterns of the proteins is needed. Here, we introduce a data analysis pipeline able to recognize in such datasets traces with recurrent patterns (clusters). Results We illustrate the performance of our method on two prototypical datasets: ∼50 000 traces from a sample containing tandem GB1 and ∼400 000 traces from a native rod membrane. Despite a daunting signal-to-noise ratio in the data, we are able to identify several unfolding clusters. This work demonstrates how an automatic pattern classification can extract relevant information from SMFS traces from heterogeneous samples without prior knowledge of the sample composition. Availability and implementation https://github.com/ninailieva/SMFS_clustering. Supplementary information Supplementary data are available at Bioinformatics online.


2017 ◽  
Vol 50 (21) ◽  
pp. 8827-8844 ◽  
Author(s):  
A. P. Sgouros ◽  
G. G. Vogiatzis ◽  
G. Kritikos ◽  
A. Boziki ◽  
A. Nikolakopoulou ◽  
...  

2018 ◽  
Author(s):  
Louis G. Smith ◽  
Zhen Tan ◽  
Aleksandar Spasic ◽  
Debapratim Dutta ◽  
Leslie A. Salas-Estrada ◽  
...  

AbstractThis study describes a comparison between melts and simulated stabilities of the same RNAs that could be used to benchmark RNA force fields, and potentially to determine future melt-ing experiments. Using umbrella sampling molecular simulations of three 12-nucleotide RNA hairpin stem loops, for which there are experimentally determined free energies of unfold-ing, we projected unfolding onto the reaction coordinate of end to end (5′ to 3′ hydroxyl oxygen) distance. We estimate the free energy change of the transition from the native con-formation to a fully extended conformation—the stretched state—with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AM-BER FF99+bsc0+χOL3 force field and each window, spaced at 1 Å intervals, was sampled for 1 μs, for a total of 552 μs of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using ther-modynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence independent. The differences between experimental and simulated ΔΔG° are on average 1.00 ± 0.66 kcal/mol, which is chemically accurate and suggests analo-gous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along the reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform such simulations.


2017 ◽  
Author(s):  
Guilherme Duarte Ramos Matos ◽  
Daisy Y. Kyu ◽  
Hannes H. Loeffler ◽  
John D. Chodera ◽  
Michael R. Shirts ◽  
...  

AbstractSolvation free energies can now be calculated precisely from molecular simulations, providing a valuable test of the energy functions underlying these simulations. Here, we briefly review “alchemical” approaches for calculating the solvation free energies of small, neutral organic molecules from molecular simulations, and illustrate by applying them to calculate aqueous solvation free energies (hydration free energies). These approaches use a non-physical pathway to compute free energy differences from a simulation or set of simulations and appear to be a particularly robust and general-purpose approach for this task. We also present an update (version 0.5) to our FreeSolv database of experimental and calculated hydration free energies of neutral compounds and provide input files in formats for several simulation packages. This revision to FreeSolv provides calculated values generated with a single protocol and software version, rather than the heterogeneous protocols used in the prior version of the database. We also further update the database to provide calculated enthalpies and entropies of hydration and some experimental enthalpies and entropies, as well as electrostatic and nonpolar components of solvation free energies.


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