scholarly journals Exploring the aggregation free energy landscape of the amyloid-β protein (1–40)

2016 ◽  
Vol 113 (42) ◽  
pp. 11835-11840 ◽  
Author(s):  
Weihua Zheng ◽  
Min-Yeh Tsai ◽  
Mingchen Chen ◽  
Peter G. Wolynes
Keyword(s):  
Free Energy ◽  
Energy Landscape ◽  
Amyloid Β ◽  
Umbrella Sampling ◽  
Coarse Grained ◽  
Free Energy Landscape ◽  
Amyloid Β Protein ◽  
Hydrophobic Core ◽  
Β Protein ◽  
Β Sheets

A predictive coarse-grained protein force field [associative memory, water-mediated, structure, and energy model for molecular dynamics (AWSEM)-MD] is used to study the energy landscapes and relative stabilities of amyloid-β protein (1–40) in the monomer and all of its oligomeric forms up to an octamer. We find that an isolated monomer is mainly disordered with a short α-helix formed at the central hydrophobic core region (L17-D23). A less stable hairpin structure, however, becomes increasingly more stable in oligomers, where hydrogen bonds can form between neighboring monomers. We explore the structure and stability of both prefibrillar oligomers that consist of mainly antiparallel β-sheets and fibrillar oligomers with only parallel β-sheets. Prefibrillar oligomers are polymorphic but typically take on a cylindrin-like shape composed of mostly antiparallel β-strands. At the concentration of the simulation, the aggregation free energy landscape is nearly downhill. We use umbrella sampling along a structural progress coordinate for interconversion between prefibrillar and fibrillar forms to identify a conversion pathway between these forms. The fibrillar oligomer only becomes favored over its prefibrillar counterpart in the pentamer where an interconversion bottleneck appears. The structural characterization of the pathway along with statistical mechanical perturbation theory allow us to evaluate the effects of concentration on the free energy landscape of aggregation as well as the effects of the Dutch and Arctic mutations associated with early onset of Alzheimer’s disease.

Determination of Base Flipping Free Energy Landscapes from Nonequilibrium Stratification

2019 ◽  
Author(s):  
Xiaohui Wang ◽  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Energy Landscape ◽  
Sampling Technique ◽  
Umbrella Sampling ◽  
Energy Simulation ◽  
Nonlinear Dependence ◽  
Free Energy Landscape ◽  
Convergence Criterion ◽  
Base Flipping ◽  
Convergence Behavior

<p>Correct calculation of the variation of free energy upon base flipping is crucial in understanding the dynamics of DNA systems. The free energy landscape along the flipping pathway gives the thermodynamic stability and the flexibility of base-paired states. Although numerous free energy simulations are performed in the base flipping cases, no theoretically rigorous nonequilibrium techniques are devised and employed to investigate the thermodynamics of base flipping. In the current work, we report a general nonequilibrium stratification scheme for efficient calculation of the free energy landscape of base flipping in DNA duplex. We carefully monitor the convergence behavior of the equilibrium sampling based free energy simulation and the nonequilibrium stratification and determine the empirical length of time blocks required for converged sampling. Comparison between the performances of equilibrium umbrella sampling and nonequilibrium stratification is given. The results show that nonequilibrium free energy simulation is able to give similar accuracy and efficiency compared with the equilibrium enhanced sampling technique in the base flipping cases. We further test a convergence criterion we previously proposed and it comes out that the convergence behavior determined by this criterion agrees with those given by the time-invariant behavior of PMF and the nonlinear dependence of standard deviation on the sample size. </p>

scholarly journals Free energy landscape for the entire transport cycle of triose-phosphate/phosphate translocator

2017 ◽  
Author(s):  
Mizuki Takemoto ◽  
Yongchan Lee ◽  
Ryuichiro Ishitani ◽  
Osamu Nureki
Keyword(s):  
Free Energy ◽  
Conformational Changes ◽  
Conformational Transition ◽  
Substrate Binding ◽  
Energy Landscape ◽  
Umbrella Sampling ◽  
Free Energy Landscape ◽  
Coupling Mechanism ◽  
Triose Phosphate ◽  
Phosphate Translocator

AbstractSecondary active transporters translocate their substrates using the electrochemical potentials of other chemicals, undergoing large-scale conformational changes. Despite extensive structural studies, the atomic details of the transport mechanism still remain elusive. Here we performed a series of all-atom molecular dynamics simulations of the triose-phosphate/phosphate translocator (TPT), which exports organic phosphates in the chloroplast stroma in strict counter exchange with inorganic phosphate (Pi). Biased sampling methods, including string method and umbrella sampling, successfully reproduced the conformational changes between the inward– and outward-facing states, along with the substrate binding. The free energy landscape of this entire TPT transition pathway demonstrated the alternating access and substrate translocation mechanisms, which revealed Pi is relayed by positively charged residues along the transition pathway. Furthermore, the conserved Glu207 functions as a “molecular switch”, linking the local substrate binding and the global conformational transition. Our results provide atomic-detailed insights into the energy coupling mechanism of antiporter.

Virtual-system-coupled adaptive umbrella sampling to compute free-energy landscape for flexible molecular docking

2015 ◽  
Vol 36 (20) ◽  
pp. 1489-1501 ◽  
Author(s):  
Junichi Higo ◽  
Bhaskar Dasgupta ◽  
Tadaaki Mashimo ◽  
Kota Kasahara ◽  
Yoshifumi Fukunishi ◽  
...  
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Energy Landscape ◽  
Umbrella Sampling ◽  
Free Energy Landscape ◽  
Virtual System

scholarly journals Determination of Base Flipping Free Energy Landscapes from Nonequilibrium Stratification

2018 ◽  
Author(s):  
Xiaohui Wang ◽  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Energy Landscape ◽  
Sampling Technique ◽  
Umbrella Sampling ◽  
Energy Simulation ◽  
Nonlinear Dependence ◽  
Free Energy Landscape ◽  
Convergence Criterion ◽  
Base Flipping ◽  
Convergence Behavior

<p>Correct calculation of the variation of free energy upon base flipping is crucial in understanding the dynamics of DNA systems. The free energy landscape along the flipping pathway gives the thermodynamic stability and the flexibility of base-paired states. Although numerous free energy simulations are performed in the base flipping cases, no theoretically rigorous nonequilibrium techniques are devised and employed to investigate the thermodynamics of base flipping. In the current work, we report a general nonequilibrium stratification scheme for efficient calculation of the free energy landscape of base flipping in DNA duplex. We carefully monitor the convergence behavior of the equilibrium sampling based free energy simulation and the nonequilibrium stratification and determine the empirical length of time blocks required for converged sampling. Comparison between the performances of equilibrium umbrella sampling and nonequilibrium stratification is given. The results show that nonequilibrium free energy simulation is able to give similar accuracy and efficiency compared with the equilibrium enhanced sampling technique in the base flipping cases. We further test a convergence criterion we previously proposed and it comes out that the convergence behavior determined by this criterion agrees with those given by the time-invariant behavior of PMF and the nonlinear dependence of standard deviation on the sample size. </p>

scholarly journals Determination of Base Flipping Free Energy Landscapes from Nonequilibrium Stratification

2019 ◽  
Author(s):  
Xiaohui Wang ◽  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Energy Landscape ◽  
Sampling Technique ◽  
Umbrella Sampling ◽  
Energy Simulation ◽  
Nonlinear Dependence ◽  
Free Energy Landscape ◽  
Convergence Criterion ◽  
Base Flipping ◽  
Convergence Behavior

<p>Correct calculation of the variation of free energy upon base flipping is crucial in understanding the dynamics of DNA systems. The free energy landscape along the flipping pathway gives the thermodynamic stability and the flexibility of base-paired states. Although numerous free energy simulations are performed in the base flipping cases, no theoretically rigorous nonequilibrium techniques are devised and employed to investigate the thermodynamics of base flipping. In the current work, we report a general nonequilibrium stratification scheme for efficient calculation of the free energy landscape of base flipping in DNA duplex. We carefully monitor the convergence behavior of the equilibrium sampling based free energy simulation and the nonequilibrium stratification and determine the empirical length of time blocks required for converged sampling. Comparison between the performances of equilibrium umbrella sampling and nonequilibrium stratification is given. The results show that nonequilibrium free energy simulation is able to give similar accuracy and efficiency compared with the equilibrium enhanced sampling technique in the base flipping cases. We further test a convergence criterion we previously proposed and it comes out that the convergence behavior determined by this criterion agrees with those given by the time-invariant behavior of PMF and the nonlinear dependence of standard deviation on the sample size. </p>

Properties of cytotoxic peptide-formed ion channels

2000 ◽  
Vol 278 (6) ◽  
pp. C1063-C1087 ◽  
Author(s):  
J. I. Kourie ◽  
A. A. Shorthouse
Keyword(s):  
Ion Channels ◽  
Amyloid Β ◽  
Wolf Spider ◽  
Amyloid Β Protein ◽  
Scorpion Toxins ◽  
Naturally Occurring ◽  
Β Protein ◽  
Skin Secretions ◽  
Β Sheets ◽  
Cytotoxic Peptide

Cytotoxic peptides are relatively small cationic molecules such as those found 1) in venoms, e.g., melittin in bee, scorpion toxins in scorpion, pilosulin 1 in jumper ant, and lycotoxin I and II in wolf spider; 2) in skin secretions (e.g., magainin I and II from Xenopus laevis, dermaseptin from frog, antimicrobials from carp) and cells of the immune system (e.g., insect, scorpion, and mammalian defensins and cryptdins); 3) as autocytotoxicity peptides, e.g., amylin cytotoxic to pancreatic β-cells, prion peptide fragment 106–126 [PrP-(106–126)], and amyloid β-protein (AβP) cytotoxic to neurons; and 4) as designed synthetic peptides based on the sequences and properties of naturally occurring cytotoxic peptides. The small cytotoxic peptides are composed of β-sheets, e.g., mammalian defensins, AβP, amylin, and PrP-(106–126), whereas the larger cytotoxic peptides have several domains composed of both α-helices and β-sheets stabilized by cysteine bonds, e.g., scorpion toxins, scorpion, and insect defensins. Electrophysiological and molecular biology techniques indicate that these structures modify cell membranes via 1) interaction with intrinsic ion transport proteins and/or 2) formation of ion channels. These two nonexclusive mechanisms of action lead to changes in second messenger systems that further augment the abnormal electrical activity and distortion of the signal transduction causing cell death.

scholarly journals Accurate protein-folding transition-path statistics from a simple free-energy landscape

2018 ◽  
Author(s):  
William M. Jacobs ◽  
Eugene I. Shakhnovich
Keyword(s):  
Free Energy ◽  
Protein Folding ◽  
Energy Landscape ◽  
Coarse Grained ◽  
Free Energy Landscape ◽  
Configuration Model ◽  
Trajectory Data ◽  
Transition Path ◽  
One Dimensional ◽  
Transition Paths

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths — the rare trajectories that transit between the folded and unfolded ensembles — using only thermodynamic information, such as a low-dimensional equilibrium free-energy landscape. However, commonly used one-dimensional landscapes typically fall short of this aim, because an empirical coordinate-dependent diffusion coefficient has to be fit to transition-path trajectory data in order to reproduce the transition-path dynamics. We show that an alternative, first-principles free-energy landscape predicts transition-path statistics that agree well with simulations and single-molecule experiments without requiring dynamical data as an input. This ‘topological configuration’ model assumes that distinct, native-like substructures assemble on a timescale that is slower than native-contact formation but faster than the folding of the entire protein. Using only equilibrium simulation data to determine the free energies of these coarse-grained intermediate states, we predict a broad distribution of transition-path transit times that agrees well with the transition-path durations observed in simulations. We further show that both the distribution of finite-time displacements on a one-dimensional order parameter and the ensemble of transition-path trajectories generated by the model are consistent with the simulated transition paths. These results indicate that a landscape based on transient folding intermediates, which are often hidden by one-dimensional projections, can form the basis of a predictive model of protein-folding transition-path dynamics.

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