ライフサイエンスコーパス: force field

1 interactions (a term neglected in classical force fields).

2 day 1), day 2 involved adaptation to a novel force field.

3 al and the environment by means of the AMBER force field.

4 ements while only one arm was subjected to a force field.

5 after optimization in a molecular mechanics force field.

6 stic simulations with the AMOEBA polarizable force field.

7 simulation under the control of the original force field.

8 apparently reflect approximations of the DNA force field.

9 (AWSEM), a predictive coarse-grained protein force field.

10 or counterclockwise velocity-dependent curl force field.

11 r of the enzyme is represented by the CHARMM force field.

12 ecular dynamics simulations using the ReaxFF force field.

13 d on a reach task in which they adapted to a force field.

14 s were parameterized with the CHARMM General Force Field.

15 e theory of particle mobility in an external force field.

16 preceeding a second movement performed in a force field.

17 ween the anisotropic friction and the active force field.

18 r-Stokes equations for reacting species in a force field.

19 le geometric measure, inness, that maps this force field.

20 tion models produced using a modified CHARMM force field.

21 s solution exploiting a newly developed TiO2 force field.

22 ecular dynamics simulations with the Martini force-field.

23 would have some key advantages over standard force fields.

24 een limited due to the absence of applicable force fields.

25 g the functional forms of publicly available force fields.

26 tools can stimulate improvement of existing force fields.

27 represented on a simpler level by empirical force fields.

28 solvent model and different well-established force fields.

29 ee text] (exchange), in contrast to standard force fields.

30 op refolding simulations with four different force fields.

31 ions is the highly approximate nature of the force fields.

32 phatidylcholine lipids using CHARMM and OPLS force fields.

33 alculations currently relying exclusively on force fields.

34 M) approaches using simple pairwise-additive force fields.

35 e protein evolution with molecular-mechanics force fields.

36 nolin, using simulations with four different force fields.

37 tem for testing and developing computational force fields.

38 riment than those obtained with other recent force fields.

39 exception of alpha-helical residues in some force fields.

40 is compared to that obtained with empirical force fields.

41 ions using both atomistic and coarse-grained force fields.

42 We see less water order for empirical force fields.

43 of the villin headpiece using four different force fields.

44 -grained protein DNA model with transferable force fields.

45 that are often poorly described by standard force fields.

46 cles has been implemented using a variety of force fields.

47 gning protein folding simulation methods and force fields.

48 imulation with the CHARMM36 and Amber ff12SB force fields.

49 FTB) method with a molecular mechanical (MM) force field, a QM/MM model was built to describe the rea

50 ry cortex (S1) applied concurrently with the force field abolished the ability to update subsequent m

51 The hydration force field accounts for the entropic and enthalpic cont

52 The results suggest that during force field adaptation, the component of learning that p

53 matics (visuomotor adaptation) and dynamics (force-field adaptation).

54 strate that for both object manipulation and force-field adaptation, contrary to previous models, mem

55 mulations with an optimized all-atom protein force field (Amber ff03w) and an accurate water model (T

56 occurring residues with two recent additive force fields, Amber ff03w and Amber ff99SB( *).

57 was further estimated for the monopole-based force fields, AMBER, CHARMM, and OPLSAA.

58 observed in simulations using two different force fields, Amber94 and Amber99sb, for the protein.

59 molecular dynamics combined with the PRIME20 force field and a newly built inhibitor model are perfor

60 mpact on the development of advanced protein force field and folding simulation methods.

61 We introduce a force field and hydration docking method that enables th

62 cular dynamics simulations using a realistic force field and including quantum effects support this i

63 ng an all-atom approach incorporating modern force field and Monte Carlo methods to allow the unstruc

64 s of ubiquitin in solution based on CHARMM36 force field and pre-melted Ni NPs (Voter-Chen Embedded A

65 od for the validation of molecular mechanics force fields and chemical shift prediction algorithms.

66 for protein mechanisms obtained by different force fields and correct for a wide range of stationary

67 etermined using quantum mechanics (QM)-based force fields and grand canonical Monte Carlo (GCMC) simu

68 PELDOR experiments correctly rank DNA force fields and resolve subtle differences in the confo

69 gy calculations have benefited from improved force fields and sampling algorithms, as well as the adv

70 ted here can be applied to test nucleic acid force fields and to characterize dynamics in diverse RNA

71 formed with three different state-of-the-art force fields and validated by experimental NMR measureme

72 e conformational energies computed with CABS force-field and residue states is approximated using a c

73 work we have parametrized accurate classical force-fields and used these to compute the conformationa

74 ined force field of ClayFF, constant-valence force field, and SPC water model.

75 e also conducted using a supplemented CHARMM force field, and these calculations revealed low-frequen

76 s for evaluating improved molecular dynamics force fields, and also will enable further development o

77 op accurate force fields, including reactive force fields, and chemically realistic surface models, t

78 g of chemical bonding, in the development of force fields, and in the development of chemically reali

79 ul assessment and evaluation of new methods, force fields, and modeling innovations on well-character

80 quantification of high-resolution continuous force fields, and the simultaneous capability of this me

81 rmed a locomotor adaptation task (perturbing force field applied to the ankle during swing using a ro

82 sis based on a simplified harmonic potential force field applied to the reduced C(alpha) representati

83 Two distance-transform based "force" fields are used: one for "pressure", which is the

84 Last generation of force-fields are raising expectations on the quality of

85 rrections, and not some other feature of the force field, are responsible.

86 ons, carried out using multiple nucleic acid force fields, are used to demonstrate that partial base-

87 ts that the preference for beta(PR) is not a force-field artifact.

88 ntal free energies, even when using the same force field as previous computational studies that were

89 MD simulation computed using the Amber ff10 force field as well as to determine an atomic resolution

90 We interpreted the Thy1 force fields as representations of spinal motor modules.

91 , we propose a novel reactive coarse-grained force field, as well as a publicly available software pa

92 tein docking with the ATTRACT coarse-grained force field, as well as various kinds of protein flexibi

93 We used the force-field assisted refinement method, molecular dynami

94 rm would demonstrate greater adaptability to force fields associated with the opposite arm's movement

95 A predictive coarse-grained protein force field [associative memory, water-mediated, structu

96 ons of TAR based on one of the most advanced force fields available for RNA, the parmbsc0 AMBER.

97 tempering, metadynamics, and one of the best force-fields available.

98 We employ an all-atom force field based method to calculate changes in free en

99 The idea of a curvature force field based on data first introduced for rhodopsin

100 DA occasionally sampled the pathway space of force field-based DIMS MD.

101 nteractions or condensed phase properties by force field-based methods require a precise description

102 ansferases were investigated using empirical force field-based simulations.

103 d methanol-d(4) was explored using extensive force-field-based conformational searches combined with

104 ransitions in MD simulations and reduces the force-field bias.

105 ly suffer from incomplete sampling or from a force-field bias.

106 inverted-hexagonal phase, and with different force-fields (both all-atom and coarse grained represent

107 hose obtained using last generation of AMBER force-fields (BSC1 and BSC0OL15) show predictive power i

108 On day 3, patients readapted to the force field but all groups now received neutral feedback

109 20-50% of the ordered structures with three force fields, but not with a fourth.

110 WW domain Fip35 using a realistic atomistic force field by applying the Dominant Reaction Pathways a

111 lecular coordinates as based on the harmonic force field calculation revealed their origin and degree

112 Force field calculations revealed that the barrier to ro

113 were elucidated by X-ray crystallography and force field calculations, respectively.

114 On the basis of X-ray structures and force field calculations, the overall potency of this se

115 These results illustrate how the CamTube force field can be used to explore efficiently the unive

116 The coupling of these two force fields can "push" a "rolling ball" quickly along t

117 Consequently, classical force fields can be used to study the wetting of F/H-ter

118 ghting, we show that differences between the force fields can mostly be attributed to differences in

119 icted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6)

120 Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36.

121 ted using umbrella sampling with a classical force field ("classical" model).

122 on membrane and provide passive (no external force fields), continuous filtration, thus eliminating t

123 volunteers performed reaching movements in a force-field created by a robotic device.

124 t with our previous study, adaptation to the force field decreased gradually as the movement directio

125 erved in MD simulations that may result from force field deficiencies or insufficient sampling and ca

126 The force field describes accurately the chemistry of the op

127 of such approaches is the inaccuracy of the force field design, which cannot accurately describe the

128 molecular dynamics simulations to PRIME20, a force field designed to capture the chemical and physica

129 and backbone contributions differ in the two force fields, despite containing identical protein-solve

130 Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the predict

131 The reactive capability of the force field enabled a range of relevant surface chemistr

132 tion theory to consistently treat systematic force-field error and statistical errors in simulation a

133 ecules are always under the influence of the force field exerted with the wall and we have to reckon

134 h trajectories allowed us to distinguish the force fields exerted by single nanoparticles and nanopar

135 gn allows a huge enhancement of the magnetic force field experienced by paramagnetic molecular specie

136 hanism is hampered by the fact that existing force fields fail to capture the correct balance of TMAO

137 arting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and O

138 The Martini model, a coarse-grained force field for biomolecular simulations, has found a br

139 lecular simulations that utilize an accurate force field for calcium ions with scaled charges effecti

140 rge model for water and an accurate flexible force field for CO(2).

141 ther nonbonded energy functions, a dedicated force field for conformational and nonbonded protein int

142 We present parmbsc1, a force field for DNA atomistic simulation, which has been

143 y (DFM) to quantitatively map the tip-sample force field for naphthalene tetracarboxylic diimide mole

144 asis is placed on the Drude-2013 polarizable force field for proteins, DNA, lipids, and carbohydrates

145 SiCDC, and develop a novel first-principles force field for the simulation of adsorption and transpo

146 contribute to protein stability and thus in force fields for biomolecular modeling.

147 sing a composite physics and knowledge-based force fields for efficient protein structure refinement.

148 e analysis with optimization of Urey-Bradley force fields for local models of the [4Fe-4S] clusters.

149 Most previous force fields for sphingomyelins were developed before th

150 rated with the coarse-grained united-residue force field, for the B domain of staphylococcal protein

151 importance of accurate glycine parameters in force fields, for a correct description of turn structur

152 onte Carlo simulations based on an ab initio force field generated for CO(2) in Mg-MOF-74 shed some l

153 ps with respect to chain length despite both force fields generating different conformational ensembl

154 proaches based on mechanical actuation using force-field gradients have emerged as complementary tech

155 The force field has been calibrated and validated on a total

156 The C36 CHARMM lipid force field has been extended to include sphingolipids,

157 Whereas the quality of classical MD force fields has improved significantly in recent years,

158 A new generation of force-fields has been developed to better represent the

159 ons on peptides and proteins using empirical force fields have demonstrated the sensitivity of the re

160 However, the MD force fields have generally not been parameterized again

161 99chi_YIL and parm99TOR, of the AMBER parm99 force field improve the agreement between structural fea

162 ial involving a combination of the INTERFACE force field in conjunction with ReaxFF and including Cou

163 ecular dynamics (MD) simulations using AMBER force field in explicit solvent were run for over 500 ns

164 rent atom types/hybridizations, not unlike a force field in molecular mechanics, but designed for the

165 bilities of molecular dynamics and classical force fields in describing spontaneous binding events an

166 es opportunities to further develop accurate force fields, including reactive force fields, and chemi

167 lected for unfolding as the magnitude of the force field increases.

168 d by unpredictable mechanical perturbations (force field) independent of their on-line corrections.

169 olding algorithms adopt completely different force fields, indicates that the design algorithm captur

170 based on the incorporation of the 'CamTube' force field into the Gromacs molecular dynamics package.

171 The polarizable force field is based on a minimal set of fitting paramet

172 Our study demonstrates that a force field is not necessary, cryo-EM data alone is suff

173 The all-atom additive CHARMM36 protein force field is widely used in molecular modeling and sim

174 eraction potentials are added to the CamTube force field, it is possible to fold a protein into a top

175 -end elimination with the polarizable AMOEBA force field lowered Rfree by 2.8-26.7% and improved mean

176 modeling studies (conformational search --> force-field lowest energy assessment --> geometry optimi

177 o relocate solutions against the centrifugal force field, making them newly accessible for downstream

178 es compared to the traditional physics-based force field methods.

179 vious predictions from a five-site empirical force-field model.

180 A, our study highlights basic limitations of force field modeling of nucleic acids.

181 calculations, and for the parametrization of force-field models used in fields ranging from crystallo

182 Neither the force field nor the starting conformations are biased to

183 sis of the overall simulation was a combined force field of ClayFF and CVFF.

184 interactions were addressed by the combined force field of ClayFF, constant-valence force field, and

185 the problem of protein folding in a Go-like force field of empirical potentials that were designed t

186 -protein interactions suggests the curvature force field of the membrane comes into play.

187 pid bilayers with the MARTINI coarse-grained force field on length scales of tens of nanometers and t

188 the influence from water models and protein force fields on calculated profiles are insignificant up

189 We use the TIP4P/ice force field, one of the best existing molecular models o

190 licit solvent using two different simulation force fields (OPLS-AA/L and AMBER ff99SB-ILDN).

191 Fourth, two force fields, OPLS-AA and CHARMM22* have unique features

192 ional quantum chemistrycentric approaches to force field optimization, our parameters are calibrated

193 ment in the thrombin case, a next generation force field, Optimized Potentials for Liquid Simulations

194 mposite environment with the ReaxFF reactive force field over a temperature range of 300-647 K.

195 arges and radii to all atoms, and generating force field parameter/topology files for MD.

196 s purpose, model systems were conceived, and force field parameters corresponding to the dihedral ter

197 face for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the forma

198 andbook is a public database and archive for force field parameters of small and drug-like molecules.

199 this limitation that entails modification of force field parameters to reduce a few pairwise non-bond

200 g role in the development and testing of the force field parameters.

201 Here we present force-field parameters for one of the most common pairs

202 Recently, we have developed empirical force-field parameters to model lantibiotics.

203 o tackle the so-called rare events, improved force-field parameters, and the concomitant increasing a

204 dite humic acid, together with corresponding force-field parameters, available at the Vienna Soil Org

205 We describe the latest developments in Drude force field parametrization and application, primarily i

206 nce of MD simulations with the newly updated force-fields Parmbsc0epsilonzetaOLI and CHARMM36 was tes

207 a task in which mixtures of error-clamp and force-field perturbation trials were used to deconstruct

208 mouse model to study forelimb adaptation to force field perturbations.

209 to velocity-dependent and position-dependent force-field perturbations (vFFs and pFFs) at the earlies

210 ping based on the Protein-Ligand Informatics force field (PLIff).

211 r introduces the protein-ligand informatics "force field", PLIff, which begins to address these key c

212 eled by Newtonian dynamics of a conservative force field plus two asymmetrical dissipative terms.

213 First, all force fields predict that Abeta adopts unfolded structur

214 We find that the 12 force fields produce a wide range of predictions.

215 dynamics simulations carried out with modern force fields provide an accurate description of folding

216 Parallel Simulator (LAMMPS) with a reactive force-field (ReaxFF).

217 rated to be robust vis-a-vis a change in the force-field, reconciles the seemingly contradictory expe

218 have to be reconsidered and revised and that force field refinements are necessary for reliable simul

219 Evidently, the force field revisions to parm99 improve the modeling of

220 ry (DFT) with the semiempirical relativistic force field (RFF) method of Kutateladze and Mukhina (KM)

221 w that simulations using a sufficiently good force-field sample conformations that are valid but have

222 ment (EPMM) or classical molecular mechanics force field single-point partial charges with Coulomb fo

223 Despite the progress made in force fields, small molecule parameterization remains an

224 The MutaBind method uses molecular mechanics force fields, statistical potentials and fast side-chain

225 nd tested using unaltered AutoDock4 with new force field tables.

226 mbination of these potentials into a unified force field, termed ff99SBnmr1-ILDN, was used in this st

227 A thermodynamics-based coarse-grained force field, termed MARTINI, has been used together with

228 ion material, FeF(2), a dynamically adaptive force field that allows for a change in ion charge durin

229 With further improvements of the UNRES force field that are now underway, our physics-based coa

230 is significantly enhanced using an empirical force field that explicitly includes the treatment of el

231 ture of the study is the use of an atomistic force field that has been parametrised against experimen

232 ions in the current implicit solvent protein force field that must be sufficiently addressed for reli

233 ics involved compensating for a viscous curl force field that perturbed reaching movements.

234 of solutions, we have developed an optimized force field that reproduces experimental Kirkwood-Buff i

235 tions that were in the same direction as the force field that subjects expected to encounter during t

236 s inform the construction of system-specific force fields that describe each partner individually.

237 ht limitations of simulations with classical force fields that do not explicitly account for charge t

238 Molecular mechanics force fields that explicitly account for induced polariz

239 he presence of the entire nucleosome for all force fields, the secondary structure of the histone tai

240 Together with an efficient force field, these contacts allow us to determine struct

241 icit membrane potential and reoptimizing the force field to account for the differing nature of the i

242 relies on atomistic models and a polarizable force field to describe a material system and its dielec

243 y involved in the described processes with a force field to include environmental effects.

244 e, we have extended the coarse-grain Martini force field to include RNA after our recent extension to

245 These results indicate the polarizable force field to more accurately model peptide-folding coo

246 -based coarse-grained UNited RESidue (UNRES) force field to predict protein structure in the 11th Com

247 he complexity of the problem, using physical force field to predict the mutation-induced binding free

248 rget proteins with a recently improved UNRES force field to provide better reproductions of the local

249 vantage of xMDFF, which applies an optimized force field to realign molecular models during phasing b

250 e performed using the MARTINI coarse-grained force field to self-assemble lipids around the crystal s

251 ons also revealed some limitations in the CG force field to study protein assembly in solution, which

252 of the chip with respect to the centrifugal force field to time the passage of multiple components r

253 dynamics simulations, with state-of-the-art force fields to carry out a comprehensive analysis of th

254 n computational power and molecular dynamics force fields to develop and test a realistically complex

255 cal principles and state-of-the-art all-atom force fields to predict both nucleosome occupancy along

256 k, we examine the ability of 12 biomolecular force fields to reproduce the properties of a simple, 30

257 protein design methods rely on physics-based force fields to search for low free-energy states follow

258 his work we explore the ability of different force-fields to predict the structure of two new B-DNA d

259 IME20, a new intermediate-resolution protein force field, to predict which designed hexapeptide seque

260 Common force fields typically underestimate by as much as two o

261 following: (1) impaired adaptation to a new force field under TMS parietal perturbation; (2) defecti

262 reliability, improvements to the potentials/force fields underlying these tools are needed to avoid

263 free in solution and limitations in the DNA force-fields underpinning the simulations.

264 Boltzmann distribution corresponding to the force field used in the simulations.

265 kcal.mol(-1) at T = 298 K, depending on the force field used, with a 0.6 kcal.mol(-1) dispersion acr

266 ed tails but show a strong dependence on the force field used.

267 ding process and the nature of the model and force field used.

268 well-known that standard molecular-mechanics force fields used in most such calculations have a limit

269 ed proteins, but the accuracy with which the force fields used in such simulations can describe disor

270 ing free-energy landscapes correspond to the force fields used in the simulations.

271 cy of these models is limited by that of the force fields used to generate the underlying molecular d

272 s simulations performed, irrespective of the force-field used.

273 all-atom detail with a physically realistic force field using a standard computing cluster.

274 e present a systematic procedure to generate force fields using high-level quantum chemical calculati

275 ; the net simulation time using Amber ff14SB force field was 61 mus.

276 AMOEBA, a second-generation force field, was chosen as it includes both multipole el

277 formation is much improved relative to other force fields we have studied.

278 simulations in denaturant (using a range of force-fields), we derived robust rules for urea unfoldin

279 Using a predictive coarse-grained protein force field, we compute and compare the free energy land

280 Using our newly parameterized PARMBSC1 force field, we describe the conformational landscape of

281 namics simulations combined with the PRIME20 force field, we find that the Hu-, BV-, and SHaPrP(120-1

282 In this work, using a modern force field, we performed a 200 mus unrestrained MD simu

283 Using the CHARMM36 lipid and carbohydrate force fields, we have constructed a model of an Escheric

284 simulations with the coarse-grained MARTINI force field were employed to model large length (~80 nm

285 for all 4 peptides, while the three-monopole force fields were 40-50% predictive in only 2 cases and

286 of an interference experiment where opposing force fields were associated with two separate visual mo

287 We found that Thy1 force fields were more complex and diverse in structure

288 mic; additional simulations in which the two force fields were swapped suggest that these differences

289 the parameterization of molecular mechanics force fields which form the basis of molecular dynamics

290 r dynamics simulations based on the CHARMM36 force field, which could achieve only modest accord with

291 vised version of the additive CHARMM protein force field, which includes optimization of the backbone

292 ncated Abeta10-40 peptide produced with five force fields, which combine four protein parameterizatio

293 nformed by quantum-mechanically parametrized force fields, which identify the mechanisms underlying i

294 So parameterizing CG force fields, which is both tedious and time-consuming,

295 coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexp

296 on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most

297 Furthermore, when healthy subjects move in a force field with unpredictable dynamics, they have activ

298 ver, application of this approach revealed a force field within the domain generated by a springlike

299 Two of the force fields yield compact nonnative states with misplac

300 Additionally, both force fields yield very similar thermodynamic scaling re