Matches in SemOpenAlex for { <https://semopenalex.org/work/W2991001243> ?p ?o ?g. }
- W2991001243 endingPage "321" @default.
- W2991001243 startingPage "310" @default.
- W2991001243 abstract "The dual-basin Gō-model is a structural-based coarse-grained model for simulating a conformational transition between two known structures of a protein. Two parameters are required to produce a dual-basin potential mixed using two single-basin potentials, although the determination of mixing parameters is usually not straightforward. Here, we have developed an efficient scheme to determine the mixing parameters using the Multistate Bennett Acceptance Ratio (MBAR) method after short simulations with a set of parameters. In the scheme, MBAR allows us to predict observables at various unsimulated conditions, which are useful to improve the mixing parameters in the next round of iterative simulations. The number of iterations that are necessary for obtaining the converged mixing parameters are significantly reduced in the scheme. We applied the scheme to two proteins, the glutamine binding protein and the ribose binding protein, for showing the effectiveness in the parameter determination. After obtaining the converged parameters, both proteins show frequent conformational transitions between open and closed states, providing the theoretical basis to investigate structure-dynamics-function relationships of the proteins." @default.
- W2991001243 created "2019-12-05" @default.
- W2991001243 creator A5032436398 @default.
- W2991001243 creator A5048007044 @default.
- W2991001243 creator A5074728289 @default.
- W2991001243 creator A5090328150 @default.
- W2991001243 date "2019-01-01" @default.
- W2991001243 modified "2023-10-18" @default.
- W2991001243 title "Building a macro-mixing dual‑basin Gō model using the Multistate Bennett Acceptance Ratio" @default.
- W2991001243 cites W1508256447 @default.
- W2991001243 cites W1550166367 @default.
- W2991001243 cites W1598141219 @default.
- W2991001243 cites W1806547840 @default.
- W2991001243 cites W1969231606 @default.
- W2991001243 cites W1973481676 @default.
- W2991001243 cites W1976164436 @default.
- W2991001243 cites W1978012161 @default.
- W2991001243 cites W1978159078 @default.
- W2991001243 cites W1983728565 @default.
- W2991001243 cites W1986059044 @default.
- W2991001243 cites W1989017034 @default.
- W2991001243 cites W1992945955 @default.
- W2991001243 cites W1993085892 @default.
- W2991001243 cites W1993560924 @default.
- W2991001243 cites W1995406360 @default.
- W2991001243 cites W1998367993 @default.
- W2991001243 cites W2001199221 @default.
- W2991001243 cites W2014425795 @default.
- W2991001243 cites W2022196464 @default.
- W2991001243 cites W2024263199 @default.
- W2991001243 cites W2024762727 @default.
- W2991001243 cites W2026737855 @default.
- W2991001243 cites W2027408247 @default.
- W2991001243 cites W2031089381 @default.
- W2991001243 cites W2035041418 @default.
- W2991001243 cites W2036239645 @default.
- W2991001243 cites W2038494121 @default.
- W2991001243 cites W2044626483 @default.
- W2991001243 cites W2048538166 @default.
- W2991001243 cites W2049598343 @default.
- W2991001243 cites W2065864578 @default.
- W2991001243 cites W2066962978 @default.
- W2991001243 cites W2067204014 @default.
- W2991001243 cites W2072667360 @default.
- W2991001243 cites W2082028745 @default.
- W2991001243 cites W2086018137 @default.
- W2991001243 cites W2090432482 @default.
- W2991001243 cites W2097412382 @default.
- W2991001243 cites W2098787719 @default.
- W2991001243 cites W2107076671 @default.
- W2991001243 cites W2107257584 @default.
- W2991001243 cites W2115005877 @default.
- W2991001243 cites W2120451413 @default.
- W2991001243 cites W2128978059 @default.
- W2991001243 cites W2130661537 @default.
- W2991001243 cites W2136686218 @default.
- W2991001243 cites W2150981663 @default.
- W2991001243 cites W2158314430 @default.
- W2991001243 cites W2158476854 @default.
- W2991001243 cites W2159010139 @default.
- W2991001243 cites W2159875359 @default.
- W2991001243 cites W2171546617 @default.
- W2991001243 cites W2171755502 @default.
- W2991001243 cites W2178631187 @default.
- W2991001243 cites W2179425537 @default.
- W2991001243 cites W2192231700 @default.
- W2991001243 cites W2234216373 @default.
- W2991001243 cites W2346816855 @default.
- W2991001243 cites W2413334978 @default.
- W2991001243 cites W2542660070 @default.
- W2991001243 cites W2547615955 @default.
- W2991001243 cites W2737764894 @default.
- W2991001243 cites W2769177858 @default.
- W2991001243 cites W2800010716 @default.
- W2991001243 cites W2902461580 @default.
- W2991001243 doi "https://doi.org/10.2142/biophysico.16.0_310" @default.
- W2991001243 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6975896" @default.
- W2991001243 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31984186" @default.
- W2991001243 hasPublicationYear "2019" @default.
- W2991001243 type Work @default.
- W2991001243 sameAs 2991001243 @default.
- W2991001243 citedByCount "4" @default.
- W2991001243 countsByYear W29910012432020 @default.
- W2991001243 countsByYear W29910012432021 @default.
- W2991001243 countsByYear W29910012432022 @default.
- W2991001243 crossrefType "journal-article" @default.
- W2991001243 hasAuthorship W2991001243A5032436398 @default.
- W2991001243 hasAuthorship W2991001243A5048007044 @default.
- W2991001243 hasAuthorship W2991001243A5074728289 @default.
- W2991001243 hasAuthorship W2991001243A5090328150 @default.
- W2991001243 hasBestOaLocation W29910012431 @default.
- W2991001243 hasConcept C109007969 @default.
- W2991001243 hasConcept C121332964 @default.
- W2991001243 hasConcept C121864883 @default.
- W2991001243 hasConcept C124952713 @default.
- W2991001243 hasConcept C127313418 @default.
- W2991001243 hasConcept C134306372 @default.
- W2991001243 hasConcept C138777275 @default.