Matches in SemOpenAlex for { <https://semopenalex.org/work/W4315928045> ?p ?o ?g. }
- W4315928045 endingPage "697" @default.
- W4315928045 startingPage "685" @default.
- W4315928045 abstract "Network Hamiltonian models (NHMs) are a framework for topological coarse-graining of protein–protein interactions, in which each node corresponds to a protein, and edges are drawn between nodes representing proteins that are noncovalently bound. Here, this framework is applied to aggregates of γD-crystallin, a structural protein of the eye lens implicated in cataract disease. The NHMs in this study are generated from atomistic simulations of equilibrium distributions of wild-type and the cataract-causing variant W42R in solution, performed by Wong, E. K.; Prytkova, V.; Freites, J. A.; Butts, C. T.; Tobias, D. J. Molecular Mechanism of Aggregation of the Cataract-Related γD-Crystallin W42R Variant from Multiscale Atomistic Simulations. Biochemistry2019, 58 (35), 3691–3699. Network models are shown to successfully reproduce the aggregate size and structure observed in the atomistic simulation, and provide information about the transient protein–protein interactions therein. The system size is scaled from the original 375 monomers to a system of 10000 monomers, revealing a lowering of the upper tail of the aggregate size distribution of the W42R variant. Extrapolation to higher and lower concentrations is also performed. These results provide an example of the utility of NHMs for coarse-grained simulation of protein systems, as well as their ability to scale to large system sizes and high concentrations, reducing computational costs while retaining topological information about the system." @default.
- W4315928045 created "2023-01-14" @default.
- W4315928045 creator A5039651585 @default.
- W4315928045 creator A5041126111 @default.
- W4315928045 creator A5054892499 @default.
- W4315928045 creator A5070881468 @default.
- W4315928045 date "2023-01-13" @default.
- W4315928045 modified "2023-09-25" @default.
- W4315928045 title "Network Hamiltonian Models for Unstructured Protein Aggregates, with Application to γD-Crystallin" @default.
- W4315928045 cites W1486765142 @default.
- W4315928045 cites W1836168718 @default.
- W4315928045 cites W1850772731 @default.
- W4315928045 cites W1865307680 @default.
- W4315928045 cites W1874853784 @default.
- W4315928045 cites W1964845458 @default.
- W4315928045 cites W1973617853 @default.
- W4315928045 cites W1974470274 @default.
- W4315928045 cites W1976499671 @default.
- W4315928045 cites W1980031953 @default.
- W4315928045 cites W1994569931 @default.
- W4315928045 cites W1998017337 @default.
- W4315928045 cites W2001987122 @default.
- W4315928045 cites W2010775881 @default.
- W4315928045 cites W2026737855 @default.
- W4315928045 cites W2029695041 @default.
- W4315928045 cites W2031908838 @default.
- W4315928045 cites W2040743789 @default.
- W4315928045 cites W2056978902 @default.
- W4315928045 cites W2057583855 @default.
- W4315928045 cites W2058047116 @default.
- W4315928045 cites W2060872117 @default.
- W4315928045 cites W2070760920 @default.
- W4315928045 cites W2075220720 @default.
- W4315928045 cites W2078168940 @default.
- W4315928045 cites W2078578908 @default.
- W4315928045 cites W2086963517 @default.
- W4315928045 cites W2088084026 @default.
- W4315928045 cites W2089980139 @default.
- W4315928045 cites W2093522132 @default.
- W4315928045 cites W2094912385 @default.
- W4315928045 cites W2101414808 @default.
- W4315928045 cites W2114220616 @default.
- W4315928045 cites W2117492258 @default.
- W4315928045 cites W2122854841 @default.
- W4315928045 cites W2125652394 @default.
- W4315928045 cites W2136676173 @default.
- W4315928045 cites W2145067884 @default.
- W4315928045 cites W2145402497 @default.
- W4315928045 cites W2151739788 @default.
- W4315928045 cites W2154319440 @default.
- W4315928045 cites W2155910443 @default.
- W4315928045 cites W2168322240 @default.
- W4315928045 cites W2312616445 @default.
- W4315928045 cites W2441602768 @default.
- W4315928045 cites W2465646024 @default.
- W4315928045 cites W2562798927 @default.
- W4315928045 cites W2610933635 @default.
- W4315928045 cites W2614053601 @default.
- W4315928045 cites W2748354746 @default.
- W4315928045 cites W2787800177 @default.
- W4315928045 cites W2898777114 @default.
- W4315928045 cites W2909859862 @default.
- W4315928045 cites W2944818307 @default.
- W4315928045 cites W2949585241 @default.
- W4315928045 cites W2952474824 @default.
- W4315928045 cites W2968670330 @default.
- W4315928045 cites W2976067555 @default.
- W4315928045 cites W3015724787 @default.
- W4315928045 cites W3034975640 @default.
- W4315928045 cites W3080557125 @default.
- W4315928045 cites W3084458619 @default.
- W4315928045 cites W3089305478 @default.
- W4315928045 cites W3098679232 @default.
- W4315928045 cites W3098739554 @default.
- W4315928045 cites W3121893592 @default.
- W4315928045 cites W3178131779 @default.
- W4315928045 cites W3208325286 @default.
- W4315928045 cites W3217451626 @default.
- W4315928045 cites W4234057457 @default.
- W4315928045 cites W4242095649 @default.
- W4315928045 cites W4247477375 @default.
- W4315928045 cites W4248681815 @default.
- W4315928045 doi "https://doi.org/10.1021/acs.jpcb.2c07672" @default.
- W4315928045 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36637342" @default.
- W4315928045 hasPublicationYear "2023" @default.
- W4315928045 type Work @default.
- W4315928045 citedByCount "1" @default.
- W4315928045 countsByYear W43159280452023 @default.
- W4315928045 crossrefType "journal-article" @default.
- W4315928045 hasAuthorship W4315928045A5039651585 @default.
- W4315928045 hasAuthorship W4315928045A5041126111 @default.
- W4315928045 hasAuthorship W4315928045A5054892499 @default.
- W4315928045 hasAuthorship W4315928045A5070881468 @default.
- W4315928045 hasBestOaLocation W43159280452 @default.
- W4315928045 hasConcept C105795698 @default.
- W4315928045 hasConcept C121332964 @default.
- W4315928045 hasConcept C121864883 @default.
- W4315928045 hasConcept C132459708 @default.