FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3139043826> ?p ?o ?g. }

• W3139043826 endingPage "2033" @default.
• W3139043826 startingPage "2022" @default.
• W3139043826 abstract "A variety of enhanced statistical and numerical methods are now routinely used to extract important thermodynamic and kinetic information from the vast amount of complex, high-dimensional data obtained from molecular simulations. For the characterization of kinetic properties, Markov state models, in which the long-time statistical dynamics of a system is approximated by a Markov chain on a discrete partition of configuration space, have seen widespread use in recent years. However, obtaining kinetic properties for molecular systems with high energy barriers remains challenging as often enhanced sampling techniques are required with biased simulations to observe the relevant rare events. Particularly, the calculation of diffusion coefficients remains elusive from biased molecular simulation data. Here, we propose a novel method that can calculate multidimensional position-dependent diffusion coefficients equally from either biased or unbiased simulations using the same formalism. Our method builds on Markov state model analysis and the Kramers–Moyal expansion. We demonstrate the validity of our formalism using one- and two-dimensional analytic potentials and also apply it to data from explicit solvent molecular dynamics simulations, including the water-mediated conformations of alanine dipeptide and umbrella sampling simulations of drug transport across a lipid bilayer. Importantly, the developed algorithm presents significant improvement compared to standard methods when the transport of solute across three-dimensional heterogeneous porous media is studied, for example, the prediction of membrane permeation of drug molecules." @default.
• W3139043826 created "2021-03-29" @default.
• W3139043826 creator A5002880748 @default.
• W3139043826 creator A5029465880 @default.
• W3139043826 creator A5071032850 @default.
• W3139043826 creator A5079404524 @default.
• W3139043826 date "2021-03-17" @default.
• W3139043826 modified "2023-10-04" @default.
• W3139043826 title "Position-Dependent Diffusion from Biased Simulations and Markov State Model Analysis" @default.
• W3139043826 cites W1616975058 @default.
• W3139043826 cites W1878196545 @default.
• W3139043826 cites W1963861287 @default.
• W3139043826 cites W1969798710 @default.
• W3139043826 cites W1974072532 @default.
• W3139043826 cites W1976499671 @default.
• W3139043826 cites W1977838033 @default.
• W3139043826 cites W1979018519 @default.
• W3139043826 cites W1994103685 @default.
• W3139043826 cites W1996257841 @default.
• W3139043826 cites W2001230333 @default.
• W3139043826 cites W2001294077 @default.
• W3139043826 cites W2005154531 @default.
• W3139043826 cites W2011189520 @default.
• W3139043826 cites W2013141616 @default.
• W3139043826 cites W2015669922 @default.
• W3139043826 cites W2017686863 @default.
• W3139043826 cites W2018532993 @default.
• W3139043826 cites W2025912890 @default.
• W3139043826 cites W2036441926 @default.
• W3139043826 cites W2041894087 @default.
• W3139043826 cites W2054338713 @default.
• W3139043826 cites W2056928595 @default.
• W3139043826 cites W2057189552 @default.
• W3139043826 cites W2057477511 @default.
• W3139043826 cites W2063945425 @default.
• W3139043826 cites W2064817890 @default.
• W3139043826 cites W2067174909 @default.
• W3139043826 cites W2070799401 @default.
• W3139043826 cites W2075629744 @default.
• W3139043826 cites W2076353448 @default.
• W3139043826 cites W2076602648 @default.
• W3139043826 cites W2085125074 @default.
• W3139043826 cites W2085213650 @default.
• W3139043826 cites W2085266415 @default.
• W3139043826 cites W2092144432 @default.
• W3139043826 cites W2094902533 @default.
• W3139043826 cites W2104395386 @default.
• W3139043826 cites W2111674120 @default.
• W3139043826 cites W2118233996 @default.
• W3139043826 cites W2120010582 @default.
• W3139043826 cites W2123768693 @default.
• W3139043826 cites W2128572087 @default.
• W3139043826 cites W2142506069 @default.
• W3139043826 cites W2142528678 @default.
• W3139043826 cites W2143351549 @default.
• W3139043826 cites W2158870666 @default.
• W3139043826 cites W2160341881 @default.
• W3139043826 cites W2296154651 @default.
• W3139043826 cites W2320711955 @default.
• W3139043826 cites W2339460745 @default.
• W3139043826 cites W2340673398 @default.
• W3139043826 cites W2397367200 @default.
• W3139043826 cites W2432414111 @default.
• W3139043826 cites W2462377291 @default.
• W3139043826 cites W2500781682 @default.
• W3139043826 cites W2516733692 @default.
• W3139043826 cites W2564974142 @default.
• W3139043826 cites W2588292212 @default.
• W3139043826 cites W2613660158 @default.
• W3139043826 cites W2736124076 @default.
• W3139043826 cites W2767197262 @default.
• W3139043826 cites W2783073729 @default.
• W3139043826 cites W2783269842 @default.
• W3139043826 cites W2793086365 @default.
• W3139043826 cites W2798017727 @default.
• W3139043826 cites W2803727203 @default.
• W3139043826 cites W2809446691 @default.
• W3139043826 cites W2891656222 @default.
• W3139043826 cites W2892865232 @default.
• W3139043826 cites W2932485468 @default.
• W3139043826 cites W2963287317 @default.
• W3139043826 cites W2964750812 @default.
• W3139043826 cites W2999605457 @default.
• W3139043826 cites W2999815934 @default.
• W3139043826 cites W3041493850 @default.
• W3139043826 cites W3100665980 @default.
• W3139043826 cites W3104359495 @default.
• W3139043826 cites W3106208511 @default.
• W3139043826 cites W83927685 @default.
• W3139043826 doi "https://doi.org/10.1021/acs.jctc.0c01151" @default.
• W3139043826 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33728916" @default.
• W3139043826 hasPublicationYear "2021" @default.
• W3139043826 type Work @default.
• W3139043826 sameAs 3139043826 @default.
• W3139043826 citedByCount "16" @default.
• W3139043826 countsByYear W31390438262021 @default.
• W3139043826 countsByYear W31390438262022 @default.
• W3139043826 countsByYear W31390438262023 @default.

• next