scholarly journals Exploring the conformational space and dynamics of biomolecular systems using pressure perturbation

2017 ◽  
Vol 950 ◽  
pp. 022002
Author(s):  
Roland Winter
Keyword(s):  
Conformational Space ◽  
Pressure Perturbation ◽  
Biomolecular Systems

REVO: Resampling of Ensembles by Variation Optimization

2019 ◽  
Author(s):  
Nazanin Donyapour ◽  
Nicole Roussey ◽  
Alex Dickson
Keyword(s):  
Protein Interactions ◽  
Conformational Space ◽  
Energy Landscapes ◽  
Enhanced Sampling ◽  
Biomolecular Systems ◽  
Space Networks ◽  
Diverse Ensemble ◽  
Efficient Exploration ◽  
Dynamics Simulations ◽  
Rough Energy Landscapes

Conventional molecular dynamics simulations are incapable of sampling many important interactions in biomolecular systems due to their high dimensionality and rough energy landscapes. To observe rare events and calculate transition rates in these systems, enhanced sampling is a necessity. In particular, the study of ligand-protein interactions necessitates a diverse ensemble of protein conformations and transition states, and for many systems this occurs on prohibitively long timescales. Previous strategies such as WExplore that can be used to determine these types of ensembles are hindered by problems related to the regioning of conformational space. Here we propose a novel, regionless, enhanced sampling method that is based on the weighted ensemble framework. In this method, a value referred to as “trajectory variation” is optimized after each cycle through cloning and merging operations. This method allows for a more consistent measurement of observables and broader sampling resulting in the efficient exploration of previously unexplored conformations. We demonstrate the performance of this algorithm with the N-dimensional random walk and the unbinding of the trypsin-benzamidine system. The system is analyzed using conformation space networks, the residence time of benzamidine is confirmed, and a new unbinding pathway for the trypsin-benzamidine system is found. We expect that REVO will be a useful general tool to broadly explore free energy landscapes.

REVO: Resampling of Ensembles by Variation Optimization

2019 ◽  
Author(s):  
Nazanin Donyapour ◽  
Nicole Roussey ◽  
Alex Dickson
Keyword(s):  
Protein Interactions ◽  
Conformational Space ◽  
Energy Landscapes ◽  
Enhanced Sampling ◽  
Biomolecular Systems ◽  
Space Networks ◽  
Diverse Ensemble ◽  
Efficient Exploration ◽  
Dynamics Simulations ◽  
Rough Energy Landscapes

Conventional molecular dynamics simulations are incapable of sampling many important interactions in biomolecular systems due to their high dimensionality and rough energy landscapes. To observe rare events and calculate transition rates in these systems, enhanced sampling is a necessity. In particular, the study of ligand-protein interactions necessitates a diverse ensemble of protein conformations and transition states, and for many systems this occurs on prohibitively long timescales. Previous strategies such as WExplore that can be used to determine these types of ensembles are hindered by problems related to the regioning of conformational space. Here we propose a novel, regionless, enhanced sampling method that is based on the weighted ensemble framework. In this method, a value referred to as “trajectory variation” is optimized after each cycle through cloning and merging operations. This method allows for a more consistent measurement of observables and broader sampling resulting in the efficient exploration of previously unexplored conformations. We demonstrate the performance of this algorithm with the N-dimensional random walk and the unbinding of the trypsin-benzamidine system. The system is analyzed using conformation space networks, the residence time of benzamidine is confirmed, and a new unbinding pathway for the trypsin-benzamidine system is found. We expect that REVO will be a useful general tool to broadly explore free energy landscapes.

REVO: Resampling of Ensembles by Variation Optimization

2019 ◽  
Author(s):  
Nazanin Donyapour ◽  
Nicole Roussey ◽  
Alex Dickson
Keyword(s):  
Protein Interactions ◽  
Conformational Space ◽  
Energy Landscapes ◽  
Enhanced Sampling ◽  
Biomolecular Systems ◽  
Space Networks ◽  
Diverse Ensemble ◽  
Efficient Exploration ◽  
Dynamics Simulations ◽  
Rough Energy Landscapes

Conventional molecular dynamics simulations are incapable of sampling many important interactions in biomolecular systems due to their high dimensionality and rough energy landscapes. To observe rare events and calculate transition rates in these systems, enhanced sampling is a necessity. In particular, the study of ligand-protein interactions necessitates a diverse ensemble of protein conformations and transition states, and for many systems this occurs on prohibitively long timescales. Previous strategies such as WExplore that can be used to determine these types of ensembles are hindered by problems related to the regioning of conformational space. Here we propose a novel, regionless, enhanced sampling method that is based on the weighted ensemble framework. In this method, a value referred to as “trajectory variation” is optimized after each cycle through cloning and merging operations. This method allows for a more consistent measurement of observables and broader sampling resulting in the efficient exploration of previously unexplored conformations. We demonstrate the performance of this algorithm with the N-dimensional random walk and the unbinding of the trypsin-benzamidine system. The system is analyzed using conformation space networks, the residence time of benzamidine is confirmed, and a new unbinding pathway for the trypsin-benzamidine system is found. We expect that REVO will be a useful general tool to broadly explore free energy landscapes.

REVO: Resampling of Ensembles by Variation Optimization

2019 ◽  
Author(s):  
Nazanin Donyapour ◽  
Nicole Roussey ◽  
Alex Dickson
Keyword(s):  
Protein Interactions ◽  
Conformational Space ◽  
Energy Landscapes ◽  
Enhanced Sampling ◽  
Biomolecular Systems ◽  
Space Networks ◽  
Diverse Ensemble ◽  
Efficient Exploration ◽  
Dynamics Simulations ◽  
Rough Energy Landscapes

Conventional molecular dynamics simulations are incapable of sampling many important interactions in biomolecular systems due to their high dimensionality and rough energy landscapes. To observe rare events and calculate transition rates in these systems, enhanced sampling is a necessity. In particular, the study of ligand-protein interactions necessitates a diverse ensemble of protein conformations and transition states, and for many systems this occurs on prohibitively long timescales. Previous strategies such as WExplore that can be used to determine these types of ensembles are hindered by problems related to the regioning of conformational space. Here we propose a novel, regionless, enhanced sampling method that is based on the weighted ensemble framework. In this method, a value referred to as “trajectory variation” is optimized after each cycle through cloning and merging operations. This method allows for a more consistent measurement of observables and broader sampling resulting in the efficient exploration of previously unexplored conformations. We demonstrate the performance of this algorithm with the N-dimensional random walk and the unbinding of the trypsin-benzamidine system. The system is analyzed using conformation space networks, the residence time of benzamidine is confirmed, and a new unbinding pathway for the trypsin-benzamidine system is found. We expect that REVO will be a useful general tool to broadly explore free energy landscapes.

Hierarchy of π-Stacking Determines the Conformational Preference of Bis-Squaraines

2020 ◽  
Author(s):  
Abhishek Singh ◽  
Reman K. Singh ◽  
G Naresh Patwari
Keyword(s):  
Hydrogen Bonding ◽  
Rational Design ◽  
Biological Molecules ◽  
Conformational Space ◽  
X Ray Crystallography ◽  
Simple Strategy ◽  
Induced Folding ◽  
Π Stacking ◽  
Varying Length ◽  
Dynamics Simulations

The rational design of conformationally controlled foldable modules can lead to a deeper insight into the conformational space of complex biological molecules where non-covalent interactions such as hydrogen bonding and π-stacking are known to play a pivotal role. Squaramides are known to have excellent hydrogen bonding capabilities and hence, are ideal molecules for designing foldable modules that can mimic the secondary structures of bio-molecules. The π-stacking induced folding of bis-squaraines tethered using aliphatic primary and secondary-diamine linkers of varying length is explored with a simple strategy of invoking small perturbations involving the length linkers and degree of substitution. Solution phase NMR investigations in combination with molecular dynamics simulations suggest that bis-squaraines predominantly exist as extended conformations. Structures elucidated by X-ray crystallography confirmed a variety of folded and extended secondary conformations including hairpin turns and 𝛽-sheets which are determined by the hierarchy of π-stacking relative to N–H···O hydrogen bonds.

Hierarchy of π-Stacking Determines the Conformational Preference of Bis-Squaraines

2020 ◽  
Author(s):  
Abhishek Singh ◽  
Reman K. Singh ◽  
G Naresh Patwari
Keyword(s):  
Hydrogen Bonding ◽  
Rational Design ◽  
Biological Molecules ◽  
Conformational Space ◽  
X Ray Crystallography ◽  
Simple Strategy ◽  
Induced Folding ◽  
Π Stacking ◽  
Varying Length ◽  
Dynamics Simulations

The rational design of conformationally controlled foldable modules can lead to a deeper insight into the conformational space of complex biological molecules where non-covalent interactions such as hydrogen bonding and π-stacking are known to play a pivotal role. Squaramides are known to have excellent hydrogen bonding capabilities and hence, are ideal molecules for designing foldable modules that can mimic the secondary structures of bio-molecules. The π-stacking induced folding of bis-squaraines tethered using aliphatic primary and secondary-diamine linkers of varying length is explored with a simple strategy of invoking small perturbations involving the length linkers and degree of substitution. Solution phase NMR investigations in combination with molecular dynamics simulations suggest that bis-squaraines predominantly exist as extended conformations. Structures elucidated by X-ray crystallography confirmed a variety of folded and extended secondary conformations including hairpin turns and 𝛽-sheets which are determined by the hierarchy of π-stacking relative to N–H···O hydrogen bonds.

Improved Sampling Strategies for Protein Model Refinement based on Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Lim Heo ◽  
Collin Arbour ◽  
Michael Feig
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Structure Prediction ◽  
Protein Structures ◽  
Conformational Space ◽  
Dynamics Simulation ◽  
Model Refinement ◽  
Protein Model ◽  
Lower Accuracy ◽  
Simulation Based

Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. Those methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on an optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore conformational space more broadly. Based on the insight of this analysis we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here. <br>

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