ライフサイエンスコーパス: energy landscape

1 rtainty regarding the order parameter's free-energy landscape.

2 g have converged to paint a rich and complex energy landscape.

3 provides a quantitative picture of the free-energy landscape.

4 ing the position of the final product in the energy landscape.

5 tanding of the role of local ordering on the energy landscape.

6 g an ever-increasingly important role in our energy landscape.

7 nal states defined by energetic minima on an energy landscape.

8 ne how these mutations alter the aggregation energy landscape.

9 of attractor-like structure in the inferred energy landscape.

10 ltidimensional and described by a rough free-energy landscape.

11 ial to elucidate the underlying folding free energy landscape.

12 , largely ignoring the impact of a protein's energy landscape.

13 l fold, i.e., the global minimum in the free energy landscape.

14 the hierarchical structure of the potential energy landscape.

15 inimum-energy state in a conformational free-energy landscape.

16 is dominant is determined by details of the energy landscape.

17 reveal the complexities of a protein's free-energy landscape.

18 onformational pools over the low-dimensional energy landscape.

19 adjacent CBD within a nearly degenerate free energy landscape.

20 odifies a protein's function by altering its energy landscape.

21 tive-like contacts on a minimally frustrated energy landscape.

22 handful of key residues dominate the binding energy landscape.

23 sily deteriorated by traps in the disordered energy landscape.

24 iate receptor conformations along the OFF-ON energy landscape.

25 de detachment was defined solely by the free-energy landscape.

26 3(T2AG3)3]), computing also the binding free-energy landscape.

27 ng trajectories that are shown upon the free energy landscape.

28 nanomagnet array, resulting in an asymmetric energy landscape.

29 units to exhaustively sample the interaction energy landscape.

30 otein folding can be described by a funneled energy landscape.

31 resulting descriptions of the conformational energy landscape.

32 nsitions between structural states within an energy landscape.

33 or the construction of a coarse-grained free energy landscape.

34 d the protein as a random walker in the free energy landscape.

35 ncerted atomic motions on a multidimensional energy landscape.

36 arises from strain-induced smoothing of the energy landscape.

37 teract and travel through a static potential energy landscape.

38 isordered proteins (IDPs) by affecting their energy landscapes.

39 l structures or equilibrium unperturbed free-energy landscapes.

40 rstanding of functional protein dynamics and energy landscapes.

41 energy model (AWSEM) to construct their free energy landscapes.

42 he degree of frustration of their respective energy landscapes.

43 n-helix transcription factors with different energy landscapes.

44 , has emerged as a powerful tool for probing energy landscapes.

45 proteins, and hence to determine their free energy landscapes.

46 variations are highlighted on projected free energy landscapes.

47 nequilibrium conditions and to map out their energy landscapes.

48 rds, what interactions govern the molecule's energy landscape?

49 arising from the combination of a flat free-energy landscape, a fragmented local structure, and the

50 roteins reveal information on the underlying energy landscape along the pulling coordinate.

51 Structural free-energy landscape analysis shows that although the presen

52 Using a variety of energy landscape analysis tools, here we uncover the fea

53 aracterize brain dynamics in autism using an energy-landscape analysis applied to resting-state fMRI

54 t kinetic traps in their conformational free energy landscape and fold efficiently to the native stat

55 provides an effective representation of the energy landscape and folding kinetics that does justice

56 f scaling parameters that are related to the energy landscape and geometric nature of the competitors

57 This allows complete enumeration of the energy landscape and gives bounds on how large a colloid

58 locally creates vacancies, shifts the Fermi energy landscape and increases the Young's modulus of el

59 count the effects of mutations on the entire energy landscape and not just the native state.

60 ion measurements, we are able to map out the energy landscape and structural dynamics for both ligand

61 d representations of the conformational free energy landscape and the complex folding mechanism inher

62 cal approach capable of determining the free-energy landscape and the continuous trajectories of mole

63 also necessary to understand the electronic energy landscape and the dynamics that govern electron t

64 We report the characterization of the energy landscape and the folding/unfolding thermodynamic

65 sical SNARE properties such as the zippering energy landscape and the surface charge distribution.

66 e the progression of NCS-1 folding along its energy landscapes and provided a solid platform for unde

67 e pathways result from the interplay of free-energy landscapes and reaction dynamics.

68 ar dynamics (AWSEM)-MD] is used to study the energy landscapes and relative stabilities of amyloid-be

69 force field, we compute and compare the free energy landscapes and relative stabilities of amyloid-be

70 s unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily descri

71 s ascribed to their hierarchical and fractal energy landscape, and is also different from [Formula: s

72 ld) encodes information about the underlying energy landscape, and it is often used to judge the qual

73 ver, most biophysical studies of a protein's energy landscape are carried out in isolation under idea

74 show that, even for small ligands, the free energy landscapes are complex.

75 Protein energy landscapes are highly complex, yet the vast major

76 at, in supramolecular systems, functions and energy landscapes are linked, superseding the more tradi

77 s folding process, which is described by its energy landscape, are encoded in the amino acid sequence

78 ughness measured by the variance of the free energy landscape around its mean.

79 ations under drug pressure remodels the free-energy landscape as a primary mechanism.

80 e point mutants at the interface altered the energy landscape as predicted, but were not enough to co

81 of apoSOD1(2SH) and characterize their free energy landscapes as a first step in understanding the i

82 sen-Shannon distance between sample-specific energy landscapes as a measure of epigenetic dissimilari

83 me arises from an equivalent sampling of the energy landscape at the respective melting temperatures.

84 Energy landscapes based on F-actin-tropomyosin models sh

85 embles (TSE) and providing a less frustrated energy landscape between the unfolded and TS ensembles.

86 ity rather than possible differences in free-energy landscapes between the solvent models.

87 ates is determined not only by the potential-energy landscape, but also by selective energy dissipati

88 enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of

89 one sampling followed by sequence design and energy landscape calculations.

90 Free energy landscapes can be generated for both cPCA and dpP

91 Once reconstructed, energy landscapes can be used to study critical folding

92 To study how a protein's energy landscape changed over time, we characterized the

93 The effects of these energy landscape changes on the conformational ensemble

94 be combined to give consistent estimates of energy landscape characteristics of natural proteins.

95 rst time to our knowledge that a rugged free energy landscape coincides with incomplete occupation of

96 or the modulation of the conformational free energy landscape connecting these states resulting from

97 otein folding model derived from theoretical energy landscape considerations and the defined-pathway

98 phase and mitotic chromosomes from effective energy landscapes constructed using Hi-C data.

99 irpin substrates with an optimized flat free energy landscape containing all binding motifs allows de

100 s sluggishness is often ascribed to the free energy landscape containing multiple minima (basins) sep

101 framework enables the estimation of the free energy landscape corresponding to the identified states.

102 From the energy landscape, critical information about an interact

103 The computed rugged free-energy landscape demonstrates that hysteresis emerges as

104 Our free energy landscape depicts a low barrier for the permeatio

105 e acoustic radiation force is governed by an energy landscape, determined by an applied high-amplitud

106 A complex conformational energy landscape determines G-protein-coupled receptor (

107 nt for specific RNA folding is that the free-energy landscape discriminate against non-native folds.

108 sis in Escherichia coli, traverses a complex energy landscape during Fe-S cluster synthesis and trans

109 oaches, such as the base-pairing entropy and energy landscapes dynamics.

110 specificity while offering insights into how energy landscapes evolve.

111 r, is possible with the breakthrough protein energy landscape exploration technique.

112 the microscope, have elucidated how protein energy landscapes facilitate folding and how they are su

113 Modeling of the conformational free energy landscape (FEL) of a thioglycoside strongly favor

114 olecule force spectroscopy to probe the free energy landscape for an unconventional intercalator that

115 Using simulations, we predict the energy landscape for cadherin adhesion, the transition p

116 on donor structure strongly impacts the free energy landscape for CPET to extended solid surfaces and

117 Information about the energy landscape for H2 production can be obtained by ch

118 n energy analysis to generate a quantitative energy landscape for hbeta2AR activation.

119 The energy landscape for hSSTR5 activation is consistent wit

120 rregular prismatic loops are used to map the energy landscape for self climb in iron and tungsten, fi

121 An energy landscape for symport and uniport is presented.

122 approach to derive a least-biased effective energy landscape for the chromosome.

123 amics simulations of the conformational free energy landscape for the cyclopropyl inhibitors show a s

124 brane protein we have characterized the free energy landscape for the dimerization of a bacterial out

125 form, reflecting how S672R remodels the free energy landscape for the modulation of HCN4 by cAMP, i.e

126 The data allow us to construct an energy landscape for the ssDNA-SSB complex, revealing th

127 We quantified the statistical energy landscapes for binding, from which we can charact

128 of gyration suggest that the less frustrated energy landscapes for optimized variants are a result of

129 rgy model, we construct the aggregation free energy landscapes for polyQ peptides of different repeat

130 rse-grained model enables estimation of free-energy landscapes for the interactions of 12 different P

131 tic denaturation phase diagram together with energy landscapes for the two very different proteins, w

132 Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic var

133 hape to bind and recognize DNA, shifting the energy landscape from a weak binding, rapid search mode

134 show how p(fold) can be used to reconstruct energy landscapes from single-molecule folding trajector

135 and information theory, we derive epigenetic energy landscapes from whole-genome bisulfite sequencing

136 s as it corresponds to downhill motion on an energy landscape function spanning a high-dimensional co

137 ion energies, we fully quantify the reaction energy landscape, gaining important predictive power for

138 Free-energy landscapes govern the behavior of all interaction

139 nto minimal aggregates, we reconstructed the energy landscape governing nonnative structure formation

140 olding dynamics such as the roughness of the energy landscape governing the folding and the level of

141 a novel approach in reconstructing the free energy landscape governing the IF<-->OF transition along

142 re sampled via simulations with a predictive energy landscape Hamiltonian.

143 ny Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now.

144 ent friction alone, with ruggedness of their energy landscapes having no consequences for their dynam

145 y sophisticated analysis of the folding free energy landscape, however, can provide the relevant info

146 ith suboptimal cargo and thereby adjusts the energy landscape in favor of MHC I complexes with immuno

147 nd thereby map the precise topography of the energy landscape in full breadth and remarkable detail.

148 Modulation of its energy level on the energy landscape in photosynthetic vs. respiratory enzym

149 We use (1)H NMR to probe the energy landscape in the protein folding and unfolding pr

150 ditions and may not accurately report on the energy landscape in vivo.

151 ther emphasizes the need to use well-defined energy landscapes in studying molecular motors in genera

152 are required to reduce the intractably vast energy landscapes into condensed representations such as

153 servation provides evidence that the protein energy landscape is distorted by high pressure, which is

154 The high-energy landscape is dominated by an energy ladder of par

155 How exactly a protein's energy landscape is maintained or altered throughout evo

156 tion of the simulation, the aggregation free energy landscape is nearly downhill.

157 ain) an identical sequence on all states the energy landscape is simplified, which accelerates the se

158 This funneled energy landscape is the result of foldable protein seque

159 erization of structure spaces and underlying energy landscapes is desirable but continues to challeng

160 scale deformation and general stacking fault energy landscapes, it is unequivocally demonstrated that

161 ffects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pro

162 airpins found from measurements of rates and energy landscapes made using optical tweezers with estim

163 Such funnel-shaped potential energy landscapes may be typical of broad classes of mol

164 20 to 42 degrees C fit well globally with an energy landscape model characterized by a single activat

165 is neural network are used as an input to an energy landscape model for chromatin organization [Minim

166 A basic tenet of the energy landscape model is that proteins fold through man

167 Using a coarse-grained energy landscape model, we predict the structures of the

168 We call the model ELM for "energy landscape model." In ELM, the interaction of the

169 f solid-state NMR spectroscopy and potential energy landscape modelling of synthetic triple-helical c

170 ics simulations of coarse-grained predictive energy landscape models for the constituent proteins by

171 optimization, making the funnel-like binding energy landscape more biased toward the native state.

172 xhibits upward curvature then the underlying energy landscape must be strongly multidimensional.

173 The computed crystal energy landscape of 3-chloromandelic acid, which has at

174 comprehensive description of the folded free-energy landscape of a hyperstable RNA tetraloop and high

175 The energy landscape of a supramolecular material can includ

176 ate the effects of concentration on the free energy landscape of aggregation as well as the effects o

177 Here, we investigate the free energy landscape of alphabeta-tubulin using molecular dy

178 The folding energy landscape of an RNA is highly dependent on its nu

179 toward the formation of kinetic traps in the energy landscape of aS fibril disassembly and the presen

180 a modifications of protein dynamics and free energy landscape of catalytic reaction.

181 onpolar solvents plays a minimal role in the energy landscape of charge transfer in quantum dot devic

182 etics and reconstruct the thermodynamic free-energy landscape of crystal formation.

183 ws us to qualitatively predict the potential energy landscape of each protein.

184 In this study, we explore the underlying energy landscape of enzyme-substrate interactions and in

185 Here, we unveil the free-energy landscape of Htt17, Htt17Q17, and Htt17Q17P11 usi

186 ynamic force spectroscopy can probe the free energy landscape of interacting bonds, but interpretatio

187 To characterize the complex structure-energy landscape of IscU, we employed NMR spectroscopy,

188 d membrane composition modulate the complete energy landscape of membrane-bound proteins.

189 ded coils, where Psi0 serves to modulate the energy landscape of nucleosomal states.

190 ractions and their effects on modulating the energy landscape of protein folding and (ii) qualitative

191 be conveniently used to derive a simplified energy landscape of protein folding.

192 s of such local frustration in dictating the energy landscape of proteins, here we compare the foldin

193 Thus, the energy landscape of ribosome nascent chains and the effe

194 Finally, the free energy landscape of rim-pore expansion/HD dilation may v

195 es taking the effective disordered potential energy landscape of strongly excited crystals and dopant

196 Here we map out the energy landscape of Tau-mediated, GTP-dependent 'active'

197 s application to the calculation of the free energy landscape of the alanine dipeptide.

198 secondary structure shapes the tertiary free-energy landscape of the Azoarcus ribozyme.

199 Here we explore the free energy landscape of the bacterial response regulator Ntr

200 an be inferred from NMR measurements, a free energy landscape of the complete pseudorotation cycle of

201 By determining the free energy landscape of the complex using NMR residual dipol

202 helices in membrane, thus leading to a free energy landscape of the dimerization process.

203 r dynamics simulations to determine the free energy landscape of the L99A cavity mutant of T4 lysozym

204 Our exploration of the energy landscape of the Li-CO2 binary phase diagram usin

205 It is shown that the conformational energy landscape of the Michaelis complex analogue is sh

206 The energy landscape of the model was derived by using the m

207 By comparing the conformational free energy landscape of the mutants with those of the wild-t

208 ce data, we describe the conformational free-energy landscape of the NADPH-cytochrome P450 reductase

209 Because the exchange involves the free-energy landscape of the protein, the QENS not only provi

210 We used our OP technique to map the energy landscape of the protein-induced looping dynamics

211 ynamics, but it may also illuminate the free-energy landscape of the protein-solvent system.

212 ound to occur mainly via changes to the free energy landscape of the proton transfer step, favoring t

213 pKa, which provides information on the free-energy landscape of the protonation reaction, showing th

214 F1-ATPase to generate a structure-based free energy landscape of the rotary-chemical process.

215 f SAM and magnesium ions on the folding free energy landscape of the SAM-I riboswitch.

216 s are employed to calculate the folding free energy landscape of the SAM-II riboswitch.

217 fects from protein to protein and across the energy landscape of the same protein.

218 We show that DnaK binding modifies the energy landscape of the substrate by removing long-range

219 he transition field [Formula: see text], the energy landscape of the system becomes completely flat,

220 nalyzed by generating and analyzing the Free Energy Landscape of the system.

221 ine the thermodynamic stability and the free-energy landscape of the tetraloop.

222 e and single-point mutations affect the free-energy landscape of the unfolded protein.

223 l minima in the computed conformational free energy landscape of the unliganded proteins.

224 We characterize the free-energy landscape of these three fragments in terms of a

225 prefusion trimer and rationalizing the free-energy landscape of this conformational machine.

226 cise structural characterization of the free energy landscape of this peptide.

227 modynamic data, we have established the free energy landscape of this two-state folding system.

228 Our current system with an energy landscape of two competing nucleated aggregation

229 minimum of the equilibrium unperturbed free-energy landscape of two K+ ions that can be 'locked' in

230 ar local minimum in the two-dimensional free-energy landscape of two Na+ ions for a block state.

231 techniques for measuring the effective free energy landscapes of biomolecules.

232 ork we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the pr

233 the applicability of GaMD for exploring free energy landscapes of large biomolecules and the simulati

234 sequence of emergent fractal geometry in the energy landscapes of many complex fluids.

235 ics simulations to explore the eversion free energy landscapes of oxoG and G by Fpg, focusing on stru

236 vide quantitative information about the free energy landscapes of proteins and yield detailed insight

237 The energy landscapes of proteins are highly complex and can

238 metadynamics simulations to obtain the free-energy landscapes of single-strand unfolding and unzippi

239 tal overlaps--we show that the minima in the energy landscapes of supramolecular systems are defined

240 Analysis of the energy landscapes of the designed versus wild-type prote

241 path sampling (DPS) approach to explore the energy landscapes of two RNA tetraloop hairpins, and pro

242 g experimental evidence for roughness in the energy landscape, or internal friction, in these peptide

243 This view does not match the funneled energy landscape paradigm of a very large number of fold

244 ms, most experiments do not directly measure energy landscapes, particularly for interactions with st

245 ses can be neatly expressed by the potential energy landscape (PEL).

246 at is characterised by complicated potential energy landscapes (PEL) consisting of sets of barriers a

247 n (the proofreading step) through the use of energy landscape principles, molecular dynamics simulati

248 nd high pH self-assembly occurs via a rugged energy landscape, reminiscent of RNA folding.

249 Quantum mechanical calculations of the free energy landscapes reveal how the neutral inhibitors prov

250 Molecular modeling of the energy landscape reveals a lower barrier for the kinetic

251 Quantitative characterization of the free-energy landscapes reveals the mechanism of nucleosome un

252 ENP-A nucleosome occupies a more rugged free energy landscape than the canonical H3 nucleosome.

253 lts show that apoSOD1(2SH) has a rugged free energy landscape that codes for distinct kinetic pathway

254 ng so allows for the study of the underlying energy landscape that governs the mechanism of Rsn-2 int

255 ion and therefore occupy local minima on the energy landscape that have relatively narrow basins.

256 t of near-barrierless diffusion on a protein energy landscape that is radically reshaped by membrane

257 Spatial energy landscape that provides new insights into domain

258 rrier creates a transition state in the free energy landscape that slows fibril formation and creates

259 edge, route for understanding the changes in energy landscape that underlie protein function and adap

260 the hierarchy in the protein conformational energy landscape that underlies these motions, based on

261 ures that can be exploited to reconstruct an energy landscape that would be computationally impractic

262 orce microscopy (AFM) approach for measuring energy landscapes that increases sampling of strongly ad

263 find that both systems exhibit shallow free-energy landscapes that link functional states through mu

264 Within the same energy landscape, the peptide-amphiphile system forms a

265 The free energy landscape theory has been very successful in rati

266 The funneled energy landscape theory implies that protein structures

267 Energy landscape theory, developed in the context of pro

268 The protein frustratometer is an energy landscape theory-inspired algorithm that aims at

269 are briefly discussed in the context of the energy-landscape theory.

270 Cellular molecules sometimes alter the energy landscape, thereby changing the ensemble of likel

271 s for activating GPCRs and the corresponding energy landscapes, thereby providing detailed structural

272 Energy landscape thinking raises new questions about the

273 s using HP-NMR as MpNep2 moved uphill in the energy landscape; this process contrasts with the overal

274 lization can involve funnel-shaped potential energy landscapes through a detailed analysis of mixed g

275 between such states enabled the folding free-energy landscape to be deduced.

276 fusion coefficient is combined with the free energy landscape to calculate the effective permeability

277 the result expected from diffusion over a 1D energy landscape to obtain the implied landscape profile

278 tion of enzymatic conformational changes and energy landscape to regulate and manipulate the enzymati

279 n increased sensitivity of the excited state energy landscape to the disorder induced by the protein

280 Despite the importance of energy landscapes to understanding reaction mechanisms,

281 ysics-based concept and method show that the energy landscape topography is valuable for understandin

282 through constant-force measurements and the energy landscapes underlying the observed transitions we

283 main-wall devices through the engineering of energy landscape using defect-induced internal fields su

284 g the possibility of examining the full free energy landscape using many coordinates.

285 In this work, we study paths in the energy landscape via which the transition between the sk

286 exchange with solute tempering, and the free energy landscape was explored by metadynamics.

287 From this peculiar structure of the free energy landscape we predict that this peptide should bec

288 Based on the energy landscape, we quantify missing information, emerg

289 Two-dimensional free-energy landscapes were calculated along the opening of t

290 caspases is described globally by a complex energy landscape where the binding of substrate selects

291 Macromolecular function is rooted in energy landscapes, where sequence determines not a singl

292 ailable energy states of polarization in the energy landscape which is determined by defect-induced i

293 nal freedom along its reaction path over the energy landscape, which in turn allows the phosphoryl tr

294 e effects of temperature on speedup and free-energy landscapes, which may differ substantially betwee

295 The renewable energy landscape will be reshaped if the current trend i

296 details and features of the protein folding energy landscape, will fuel this old field to move forwa

297 Comparing the measured energy landscape with adhesive force measurements reveal

298 ed us to describe PAR1's ligand-binding free-energy landscape with high accuracy.

299 he three wetting modes by analyzing the free energy landscape with many local minima originated from

300 ential to accurately reconstruct interfacial energy landscapes with steep gradients.