scholarly journals Free Energy Landscapes of Vesicle Fusion by Umbrella Sampling MD Simulations

2013 ◽  
Vol 104 (2) ◽  
pp. 92a ◽  
Author(s):  
Gregory Bubnis ◽  
H.J. Risselada ◽  
Helmut Grubmueller
Keyword(s):  
Free Energy ◽  
Md Simulations ◽  
Vesicle Fusion ◽  
Umbrella Sampling ◽  
Energy Landscapes ◽  
Free Energy Landscapes

scholarly journals High resolution ensemble description of metamorphic and intrinsically disordered proteins using an efficient hybrid parallel tempering scheme

2020 ◽  
Author(s):  
Rajeswari Appadurai ◽  
Jayashree Nagesh ◽  
Anand Srivastava
Keyword(s):  
Free Energy ◽  
Sampling Method ◽  
Intrinsically Disordered Proteins ◽  
Md Simulations ◽  
Disordered Proteins ◽  
Parallel Tempering ◽  
Energy Landscapes ◽  
Intrinsically Disordered ◽  
Advanced Sampling ◽  
Free Energy Landscapes

AbstractDetermining the conformational ensemble for proteins with multi-funneled complex free-energy landscapes is often not possible with classical structure-biology methods that produce time and ensemble averaged data. With vastly improved force fields and advances in rare-event sampling methods, molecular dynamics (MD) simulations offer a complementary approach towards determining the collection of 3-dimensional structures that proteins can adopt. However, in general, MD simulations need to either impose restraints or reweigh the generated data to match experiments. The limitations extend beyond systems with high free-energy barriers as is the case with metamorphic proteins such as RFA-H. The predicted structures in even weakly-funneled intrinsically disordered proteins (IDPs) such as Histatin-5 (His-5) are too compact relative to experiments. Here, we employ a new computationally-efficient parallel-tempering based advanced-sampling method applicable across proteins with extremely diverse free-energy landscapes. And we show that the calculated ensemble averages match reasonably well with the NMR, SAXS and other biophysical experiments without the need to reweigh. We benchmark our method against standard model systems such as alanine di-peptide, TRP-cage and β-hairpin and demonstrate significant enhancement in the sampling efficiency. The method successfully scales to large metamorphic proteins such as RFA-H and to highly disordered IDPs such as His-5 and produces experimentally-consistent ensemble. By allowing accurate sampling across diverse landscapes, the method enables for ensemble conformational sampling of deep multi-funneled metamorphic proteins as well as highly flexible IDPs with shallow multi-funneled free-energy landscape.Significance/Authors’ SummaryGenerating high-resolution ensemble of intrinsically disordered proteins, particularly the highly flexible ones with high-charge and low-hydrophobicity and with shallow multi-funneled free-energy landscape, is a daunting task and often not possible since information from biophysical experiments provide time and ensemble average data at low resolutions. At the other end of the spectrum are the metamorphic proteins with multiple deep funnels and elucidating the structures of the transition intermediates between the fold topologies is a non-trivial exercise. In this work, we propose a new parallel-tempering based advanced-sampling method where the Hamiltonian is designed to allow faster decay of water orientation dynamics, which in turn facilitates accurate and efficient sampling across a wide variety of free-energy landscapes.

scholarly journals Passive Internalization of Bioactive β-Casein Peptides into Phospholipid (POPC) Bilayers. Free Energy Landscapes from Unbiased Equilibrium MD Simulations at μs-Time Scale

2020 ◽  
Author(s):  
Eduardo Jardón-Valadez ◽  
Charles H. Chen ◽  
Mariano García-Garibay ◽  
Judith Jiménez-Guzmán ◽  
Martin B. Ulmschneider
Keyword(s):  
Free Energy ◽  
Time Scale ◽  
Md Simulations ◽  
Energy Landscapes ◽  
Free Energy Landscapes

scholarly journals Identification of ligand-specific G-protein coupled receptor states and prediction of downstream efficacy via data-driven modeling

2020 ◽  
Author(s):  
Oliver Fleetwood ◽  
Jens Carlsson ◽  
Lucie Delemotte
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Site ◽  
G Protein ◽  
Md Simulations ◽  
Conformational Ensemble ◽  
Energy Landscapes ◽  
Reduction Techniques ◽  
Free Energy Landscapes ◽  
G Protein Coupled

AbstractG protein-coupled receptors (GPCRs) shift between inactive states and active signaling states, to which intracellular binding partners can bind. Extracellular binding of ligands stabilizes different receptor states and modulates the intracellular response via a complex allosteric process, which is not completely understood. Despite the recent advances in structure determination and spectroscopy techniques, a comprehensive view of the ligand-protein interplay remains a challenge. We derived free energy landscapes describing activation of the β2 adrenergic receptor (β2AR) bound to ligands with different efficacy profiles using enhanced sampling molecular dynamics (MD) simulations. The resulting free energy landscapes reveal clear shifts towards active-like states at the G protein binding site for receptors bound to partial and full agonists compared to antagonists and inverse agonists. Not only do the ligands control the population of states, they also modulate the conformational ensemble of the receptor by tuning allosteric protein microswitches. We find an excellent correlation between the conformation of the microswitches close to the ligand binding site and in the transmembrane region and experimentally reported cAMP signaling responses, highlighting the predictive power of our approach. Using dimensionality reduction techniques, we could further assess the similarity between the unique conformational states induced by different ligands. Two distant hotspots governing agonism on transmembrane helices 5 and 7, including the conserved NPxxY motif, formed the endpoints of an allosteric pathway between the binding sites. Our results demonstrate how molecular dynamics simulations can further provide insights into the mechanism of GPCR regulation by ligands, which may contribute to the design of drugs with specific efficacy profiles.

scholarly journals Distributions of experimental protein structures on coarse-grained free energy landscapes

2015 ◽  
Vol 143 (24) ◽  
pp. 243153 ◽  
Author(s):  
Kannan Sankar ◽  
Jie Liu ◽  
Yuan Wang ◽  
Robert L. Jernigan
Keyword(s):  
Free Energy ◽  
Protein Structures ◽  
Coarse Grained ◽  
Energy Landscapes ◽  
Free Energy Landscapes
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