scholarly journals Free-energy landscape of polymer-crystal polymorphism

Soft Matter ◽  
2020 ◽  
Vol 16 (42) ◽  
pp. 9683-9692
Author(s):  
Chan Liu ◽  
Jan Gerit Brandenburg ◽  
Omar Valsson ◽  
Kurt Kremer ◽  
Tristan Bereau
Keyword(s):  
Free Energy ◽  
Energy Landscape ◽  
Coarse Grained ◽  
Syndiotactic Polystyrene ◽  
Free Energy Landscape ◽  
Quantum Mechanical ◽  
Quantum Mechanical Calculations ◽  
Crystal Polymorphism ◽  
Polymer Crystal ◽  
Coarse Grained Simulations

Free-energy landscape of crystallized syndiotactic-polystyrene polymorphism from quantum-mechanical calculations and coarse-grained simulations.

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.

scholarly journals Exploring the free-energy landscape of GPCR activation

2018 ◽  
Vol 115 (41) ◽  
pp. 10327-10332 ◽  
Author(s):  
Raphael Alhadeff ◽  
Igor Vorobyov ◽  
Han Wool Yoon ◽  
Arieh Warshel
Keyword(s):  
Free Energy ◽  
Structural Information ◽  
Large Fraction ◽  
Energy Landscape ◽  
Point Of View ◽  
Coarse Grained ◽  
Free Energy Landscape ◽  
Activation Process ◽  
Gpcr Activation ◽  
Membrane Bound

G-protein–coupled receptors (GPCRs) are a large group of membrane-bound receptor proteins that are involved in a plethora of diverse processes (e.g., vision, hormone response). In mammals, and particularly in humans, GPCRs are involved in many signal transduction pathways and, as such, are heavily studied for their immense pharmaceutical potential. Indeed, a large fraction of drugs target various GPCRs, and drug-development is often aimed at GPCRs. Therefore, understanding the activation of GPCRs is a challenge of major importance both from fundamental and practical considerations. And yet, despite the remarkable progress in structural understanding, we still do not have a translation of the structural information to an energy-based picture. Here we use coarse-grained (CG) modeling to chart the free-energy landscape of the activation process of the β-2 adrenergic receptor (β2AR) as a representative GPCR. The landscape provides the needed tool for analyzing the processes that lead to activation of the receptor upon binding of the ligand (adrenaline) while limiting constitutive activation. Our results pave the way to better understand the biological mechanisms of action of the β2AR and GPCRs, from a physical chemistry point of view rather than simply by observing the receptor’s behavior physiologically.

scholarly journals Torque, chemistry and efficiency in molecular motors: a study of the rotary–chemical coupling in F1-ATPase

2015 ◽  
Vol 48 (4) ◽  
pp. 395-403 ◽  
Author(s):  
Shayantani Mukherjee ◽  
Ram Prasad Bora ◽  
Arieh Warshel
Keyword(s):  
Free Energy ◽  
Molecular Motors ◽  
Energy Landscape ◽  
Molecular Machine ◽  
Coarse Grained ◽  
Free Energy Landscape ◽  
Thermodynamic Efficiency ◽  
Rotational Angle ◽  
Torque Generation ◽  
Chemical Coupling

AbstractDetailed understanding of the action of biological molecular machines must overcome the challenge of gaining a clear knowledge of the corresponding free-energy landscape. An example for this is the elucidation of the nature of converting chemical energy to torque and work in the rotary molecular motor of F1-ATPase. A major part of the challenge involves understanding the rotary–chemical coupling from a non-phenomenological structure/energy description. Here we focused on using a coarse-grained model of F1-ATPase to generate a structure-based free-energy landscape of the rotary–chemical process of the whole system. In particular, we concentrated on exploring the possible impact of the position of the catalytic dwell on the efficiency and torque generation of the molecular machine. It was found that the experimentally observed torque can be reproduced with landscapes that have different positions for the catalytic dwell on the rotary–chemical surface. Thus, although the catalysis is undeniably required for torque generation, the experimentally observed position of the catalytic dwell at 80° might not have a clear advantage for the force generation by F1-ATPase. This further implies that the rotary–chemical couplings in these biological motors are quite robust and their efficiencies do not depend explicitly on the position of the catalytic dwells. Rather, the specific positioning of the dwells with respect to the rotational angle is a characteristic arising due to the structural construct of the molecular machine and might not bear any clear connection to the thermodynamic efficiency for the system.

scholarly journals Exploring the Mechanism of Shikimate Kinase through Quantum Mechanical and Molecular Mechanical (QM/MM) Methods

Biophysica ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 334-343
Author(s):  
Pedro Ojeda-May
Keyword(s):  
Helicobacter Pylori ◽  
Free Energy ◽  
Intermediate State ◽  
Energy Landscape ◽  
Free Energy Landscape ◽  
Phosphoryl Group ◽  
Quantum Mechanical ◽  
Shikimate Kinase ◽  
Step Process ◽  
Novel Drugs

The chemical step of Shikimate Kinase Helicobacter pylori, involving the transfer of a phosphoryl group, has been studied by using quantum mechanical and molecular mechanical (QM/MM) methods. Understanding the mechanism of this chemical step, present in bacteria and other microorganisms but absent in humans, can lead to the development of novel drugs for the treatment of common diseases caused by those pathogenic organisms. Different mechanisms including associative, dissociative, and concerted have been proposed up to now but there is not a consensus on the type of pathway that the reaction follows. Herein, we found that the mechanism has features from the associative and concerted types. An analysis of the free energy landscape of the chemical step reveals that the reaction is a two-step process without a well-defined intermediate state.

scholarly journals Free-energy landscape of ion-channel voltage-sensor–domain activation

2014 ◽  
Vol 112 (1) ◽  
pp. 124-129 ◽  
Author(s):  
Lucie Delemotte ◽  
Marina A. Kasimova ◽  
Michael L. Klein ◽  
Mounir Tarek ◽  
Vincenzo Carnevale
Keyword(s):  
Free Energy ◽  
Energy Landscape ◽  
State Theory ◽  
Voltage Sensor ◽  
Reaction Coordinate ◽  
Coarse Grained ◽  
Free Energy Landscape ◽  
Activation Process ◽  
Discrete State ◽  
Gating Charge

Voltage sensor domains (VSDs) are membrane-bound protein modules that confer voltage sensitivity to membrane proteins. VSDs sense changes in the transmembrane voltage and convert the electrical signal into a conformational change called activation. Activation involves a reorganization of the membrane protein charges that is detected experimentally as transient currents. These so-called gating currents have been investigated extensively within the theoretical framework of so-called discrete-state Markov models (DMMs), whereby activation is conceptualized as a series of transitions across a discrete set of states. Historically, the interpretation of DMM transition rates in terms of transition state theory has been instrumental in shaping our view of the activation process, whose free-energy profile is currently envisioned as composed of a few local minima separated by steep barriers. Here we use atomistic level modeling and well-tempered metadynamics to calculate the configurational free energy along a single transition from first principles. We show that this transition is intrinsically multidimensional and described by a rough free-energy landscape. Remarkably, a coarse-grained description of the system, based on the use of the gating charge as reaction coordinate, reveals a smooth profile with a single barrier, consistent with phenomenological models. Our results bridge the gap between microscopic and macroscopic descriptions of activation dynamics and show that choosing the gating charge as reaction coordinate masks the topological complexity of the network of microstates participating in the transition. Importantly, full characterization of the latter is a prerequisite to rationalize modulation of this process by lipids, toxins, drugs, and genetic mutations.

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.

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