The derivation of molecular models from spatial density data generated by X-ray crystallography or electron microscopy is an active field of research. Here, we introduce and evaluate an approach relying on the equilibrium sampling of energy landscapes describing restraints to experimental input data. Our procedure combines density restraints with replica exchange methodologies in the parameter space of the restraints, and we demonstrate its applicability to both flexible polymers and the assembly of protein complexes from rigid components. For the most difficult system studied, we highlight the importance of advanced data analysis techniques in mining poorly converged data further. Successful and unbiased interpretation of input density map...
AbstractNested sampling is a Bayesian sampling technique developed to explore probability distributi...
ABSTRACT: Molecular dynamics simulation using enhanced sampling methods is one of the powerful compu...
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring c...
SummaryThe derivation of molecular models from spatial density data generated by X-ray crystallograp...
The derivation of molecular models from spatial density data generated by X-ray crystallography or e...
We propose an approach for summarizing the output of long simulations of complex systems, affording ...
Polymers is a class of molecules which can have many different structures due to a large number of d...
51 pages, 5 figuresInternational audienceEnhanced sampling algorithms have emerged as powerful metho...
Conformational properties of polymers, like average dihedral angles or molecular #alpha#-helicity, d...
The paper expands on the growing body of literature which makes use of constraint programming techni...
Statistical methods for analyzing large data sets of molecular configurations within the chemical co...
SummaryStructural studies of large proteins and protein assemblies are a difficult and pressing chal...
Ensemble refinement, the application of molecular dynamics to crystallographic refinement, explicitl...
The gap between the time scale of interesting behavior in macromolecular systems and that which our ...
In this article, we present an enhanced sampling method based on a hybrid Hamiltonian which combines...
AbstractNested sampling is a Bayesian sampling technique developed to explore probability distributi...
ABSTRACT: Molecular dynamics simulation using enhanced sampling methods is one of the powerful compu...
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring c...
SummaryThe derivation of molecular models from spatial density data generated by X-ray crystallograp...
The derivation of molecular models from spatial density data generated by X-ray crystallography or e...
We propose an approach for summarizing the output of long simulations of complex systems, affording ...
Polymers is a class of molecules which can have many different structures due to a large number of d...
51 pages, 5 figuresInternational audienceEnhanced sampling algorithms have emerged as powerful metho...
Conformational properties of polymers, like average dihedral angles or molecular #alpha#-helicity, d...
The paper expands on the growing body of literature which makes use of constraint programming techni...
Statistical methods for analyzing large data sets of molecular configurations within the chemical co...
SummaryStructural studies of large proteins and protein assemblies are a difficult and pressing chal...
Ensemble refinement, the application of molecular dynamics to crystallographic refinement, explicitl...
The gap between the time scale of interesting behavior in macromolecular systems and that which our ...
In this article, we present an enhanced sampling method based on a hybrid Hamiltonian which combines...
AbstractNested sampling is a Bayesian sampling technique developed to explore probability distributi...
ABSTRACT: Molecular dynamics simulation using enhanced sampling methods is one of the powerful compu...
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring c...