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Calculation and visualization of atomistic mechanical stresses in nanomaterials and biomolecules.

Fenley AT, Muddana HS, Gilson MK - PLoS ONE (2014)

Bottom Line: However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context.The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms.Here, we review relevant theory and present illustrative applications.

View Article: PubMed Central - PubMed

Affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, 92093, United States of America.

ABSTRACT
Many biomolecules have machine-like functions, and accordingly are discussed in terms of mechanical properties like force and motion. However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context. We anticipate that microscopical stress analyses of biomolecules and nanomaterials will provide useful mechanistic insights and help guide molecular design. To enable such applications, we have developed Calculator of Atomistic Mechanical Stress (CAMS), an open-source software package for computing atomic resolution stresses from molecular dynamics (MD) simulations. The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms. CAMS reads GROMACS topology and trajectory files, which are easily generated from AMBER files as well; and time-varying stresses may be animated and visualized in the VMD viewer. Here, we review relevant theory and present illustrative applications.

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Related in: MedlinePlus

Mean square fluctuations of the residue-averaged stresses computed from the 1 ms BPTI trajectory.(Left) Cluster 2; values range from 1.50 to 5.08 Mbar. (Right) Difference between cluster 1 and 2 (cluster 1 minus cluster 2); values range from −90.3 to 63.6 kbar. Purple (negative) and orange (positive) indicate regions where cluster 1 has less or more stress fluctuations than cluster 2, respectively.
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pone-0113119-g003: Mean square fluctuations of the residue-averaged stresses computed from the 1 ms BPTI trajectory.(Left) Cluster 2; values range from 1.50 to 5.08 Mbar. (Right) Difference between cluster 1 and 2 (cluster 1 minus cluster 2); values range from −90.3 to 63.6 kbar. Purple (negative) and orange (positive) indicate regions where cluster 1 has less or more stress fluctuations than cluster 2, respectively.

Mentions: where is the number of snapshots, is total stress for residue at snapshot , and is the total residue-averaged stress over the whole trajectory for residue . Fig. 3 (left) shows the MSF values for all residues when BPTI is in conformational cluster 2; the corresponding result for cluster 1 looks the same, as the differences in the MSF values are small relative to the absolute values, and therefore is not shown. The distribution of stress fluctuations is quite heterogeneous, with larger fluctuations in the lower part of the protein, whose conformational fluctuations are relatively modest and which contains alpha helices, which may be expected to be relatively stiff. On the other hand, the more flexible loop region at the top of the protein shows smaller stress fluctuations. Differences in stress fluctuations between the relatively rigid cluster 1 and more flexible cluster 2 are displayed in the right-hand side of Fig. 3. Although the largest differences are roughly two orders of magnitude less than the total values (∼103 kbar2 vs. ∼10 kbar2), they clearly highlight the loop region of the protein, which is the part whose structure and dynamics differs most between the two clusters. Although cluster 1 is more rigid than cluster 2 [58], regions of both increased and decreased stress fluctuations are observed.


Calculation and visualization of atomistic mechanical stresses in nanomaterials and biomolecules.

Fenley AT, Muddana HS, Gilson MK - PLoS ONE (2014)

Mean square fluctuations of the residue-averaged stresses computed from the 1 ms BPTI trajectory.(Left) Cluster 2; values range from 1.50 to 5.08 Mbar. (Right) Difference between cluster 1 and 2 (cluster 1 minus cluster 2); values range from −90.3 to 63.6 kbar. Purple (negative) and orange (positive) indicate regions where cluster 1 has less or more stress fluctuations than cluster 2, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263534&req=5

pone-0113119-g003: Mean square fluctuations of the residue-averaged stresses computed from the 1 ms BPTI trajectory.(Left) Cluster 2; values range from 1.50 to 5.08 Mbar. (Right) Difference between cluster 1 and 2 (cluster 1 minus cluster 2); values range from −90.3 to 63.6 kbar. Purple (negative) and orange (positive) indicate regions where cluster 1 has less or more stress fluctuations than cluster 2, respectively.
Mentions: where is the number of snapshots, is total stress for residue at snapshot , and is the total residue-averaged stress over the whole trajectory for residue . Fig. 3 (left) shows the MSF values for all residues when BPTI is in conformational cluster 2; the corresponding result for cluster 1 looks the same, as the differences in the MSF values are small relative to the absolute values, and therefore is not shown. The distribution of stress fluctuations is quite heterogeneous, with larger fluctuations in the lower part of the protein, whose conformational fluctuations are relatively modest and which contains alpha helices, which may be expected to be relatively stiff. On the other hand, the more flexible loop region at the top of the protein shows smaller stress fluctuations. Differences in stress fluctuations between the relatively rigid cluster 1 and more flexible cluster 2 are displayed in the right-hand side of Fig. 3. Although the largest differences are roughly two orders of magnitude less than the total values (∼103 kbar2 vs. ∼10 kbar2), they clearly highlight the loop region of the protein, which is the part whose structure and dynamics differs most between the two clusters. Although cluster 1 is more rigid than cluster 2 [58], regions of both increased and decreased stress fluctuations are observed.

Bottom Line: However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context.The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms.Here, we review relevant theory and present illustrative applications.

View Article: PubMed Central - PubMed

Affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, 92093, United States of America.

ABSTRACT
Many biomolecules have machine-like functions, and accordingly are discussed in terms of mechanical properties like force and motion. However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context. We anticipate that microscopical stress analyses of biomolecules and nanomaterials will provide useful mechanistic insights and help guide molecular design. To enable such applications, we have developed Calculator of Atomistic Mechanical Stress (CAMS), an open-source software package for computing atomic resolution stresses from molecular dynamics (MD) simulations. The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms. CAMS reads GROMACS topology and trajectory files, which are easily generated from AMBER files as well; and time-varying stresses may be animated and visualized in the VMD viewer. Here, we review relevant theory and present illustrative applications.

Show MeSH
Related in: MedlinePlus