Data · collection · 2016
A coupling of homology modeling with multiple molecular dynamics simulation for identifying representative conformation of GPCR structures: a case study on human bombesin receptor subtype-3
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In this study, a computational pipeline was therefore devised to overcome homology modeling (HM) bottlenecks.
Description
The coupling of HM with molecular dynamics (MD) simulation is useful in that it tackles the sampling deficiency of dynamics simulations by providing good-quality initial guesses for the native structure. Indeed, HM also relaxes the severe requirement of force fields to explore the huge conformational space of protein structures.
In this study, the interaction between the human bombesin receptor subtype-3 and MK-5046 was investigated integrating HM, molecular docking, and MD simulations. To improve conformational sampling in typical MD simulations of GPCRs, as in other biomolecules, multiple trajectories with different initial conditions can be employed rather than a single long trajectory. Multiple MD simulations of human bombesin receptor subtype-3 with different initial atomic velocities are applied to sample conformations in the vicinity of the structure generated by HM.
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The backbone atom conformational space distribution of replicates is analyzed employing principal components analysis. As a result, the averages of structural and dynamic properties over the twenty-one trajectories differ significantly from those obtained from individual trajectories.
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Where it is published
- Repository landing page figshare.com/collections/A_coupling_of_homology_modeling_with_multiple_mole… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.3248764.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
- CC-BY creativecommons.org/licenses/by/3.0/us ↗
license · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.3248764.v1 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.3248764.v1 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Biological sciences · Chemical sciences · Physical sciences
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.c.3248764.v1 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| concepts[field].fos:biological-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:chemical-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:physical-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · DataCite | connector:datacite@1.0.0 | |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
| license | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| updated_date | source · DataCite | connector:datacite@1.0.0 |