Systematic coarse-graining of molecular models by the Newton inversion method

Lyubartsev, Alexander P.; Mirzoev, Alexander; Chen, Li Jun; Laaksonen, Aatto

doi:10.1039/b901511f

Cited by 142 publications

(145 citation statements)

References 44 publications

Supporting

Mentioning

143

Contrasting

Order By: Relevance

“…The counterions were also included into CG trajectory. The CG trajectory generated from the atomistic simulations was used to extract effective coarse-grained potentials by the inverse Monte Carlo method [19,62]. For that, radial distribution functions between the sites of the CG model, as well as internal bond and angle distributions between the CG sites were determined from the CG trajectory and were used as input to the inverse Monte Carlo procedure.…”

Section: Coarse-grained Dna and Computations Of Effective Potentialsmentioning

confidence: 99%

“…There are two basic approaches for constructing effective coarse-grained potentials from the results of atomistic simulations. One is based on fitting of structural properties, for which the radial distribution functions (RDFs) are typically used (the inverse Monte Carlo, also called the Newton inversion method) [18,19]. Another approach is based on reproduction of forces for specific snapshots of the system (the force matching approach) [20,21].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Coarse-Grained DNA Model Parameterized from Atomistic Simulations by Inverse Monte Carlo

et al. 2014

Self Cite

View full text Add to dashboard Cite

Abstract:Computer modeling of very large biomolecular systems, such as long DNA polyelectrolytes or protein-DNA complex-like chromatin cannot reach all-atom resolution in a foreseeable future and this necessitates the development of coarse-grained (CG) approximations. DNA is both highly charged and mechanically rigid semi-flexible polymer and adequate DNA modeling requires a correct description of both its structural stiffness and salt-dependent electrostatic forces. Here, we present a novel CG model of DNA that approximates the DNA polymer as a chain of 5-bead units. Each unit represents two DNA base pairs with one central bead for bases and pentose moieties and four others for phosphate groups. Charges, intra-and inter-molecular force field potentials for the CG DNA model were calculated using the inverse Monte Carlo method from all atom molecular dynamic (MD) simulations of 22 bp DNA oligonucleotides. The CG model was tested by performing dielectric continuum Langevin MD simulations of a 200 bp double helix DNA in solutions of monovalent salt with explicit ions. Excellent agreement with experimental data was obtained for the dependence of the DNA persistent length on salt concentration in the range 0.1-100 mM. The new CG DNA model is suitable for modeling various biomolecular systems with adequate description of electrostatic and mechanical properties.

show abstract

Section: Coarse-grained Dna and Computations Of Effective Potentialsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Coarse-Grained DNA Model Parameterized from Atomistic Simulations by Inverse Monte Carlo

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…In contrast to the Force Matching or Multi-scale coarse graining scheme, other structure-based methods provide CG interactions that reproduce pre-defined target structure properties-often a set of radial distribution functions [77][78][79][80][81][82][83][84][85][86][87][88][89]. This means that the many-body PMF (Equations (6) and (7)) is replaced as a target by a set of simpler structural correlation functions.…”

Section: Boltzmann-inversion Based Methodsmentioning

confidence: 99%

“…Another numerical scheme is the so called inverse Monte Carlo (or more recently renamed Newton inversion) method [78,79,83,84] which, according to Henderson's theorem, should lead to the same numerical solution for the pair potential corresponding to a given pair correlation function. While in IBI the potential update ∆V i is ad hoc, in IMC it is computed using rigorous statistical mechanical arguments (for details see Reference [78]).…”

Section: Boltzmann-inversion Based Methodsmentioning

confidence: 99%

“…In another group of approaches, one numerically generates CG interaction functions with the aim of reproducing the configurational phase space sampled in an atomistic reference simulation. These approaches may rely on different types of reference properties such as structure functions [77][78][79][80][81][82][83][84][85][86][87][88][89], mean forces [90][91][92][93][94][95] or relative entropies [96][97][98]. In the following subsection, a few basic notions of coarse-graining theory will be introduced, together with examples of the strategies that can be employed to perform the coarse-graining in practice.…”

Section: Coarse-grainingmentioning

confidence: 99%

See 1 more Smart Citation

Computer Simulations of Soft Matter: Linking the Scales

Potestio

Peter

Kremer

2014

Entropy

102

View full text Add to dashboard Cite

Abstract:In the last few decades, computer simulations have become a fundamental tool in the field of soft matter science, allowing researchers to investigate the properties of a large variety of systems. Nonetheless, even the most powerful computational resources presently available are, in general, sufficient to simulate complex biomolecules only for a few nanoseconds. This limitation is often circumvented by using coarse-grained models, in which only a subset of the system's degrees of freedom is retained; for an effective and insightful use of these simplified models; however, an appropriate parametrization of the interactions is of fundamental importance. Additionally, in many cases the removal of fine-grained details in a specific, small region of the system would destroy relevant features; such cases can be treated using dual-resolution simulation methods, where a subregion of the system is described with high resolution, and a coarse-grained representation is employed in the rest of the simulation domain. In this review we discuss the basic notions of coarse-graining theory, presenting the most common methodologies employed to build low-resolution descriptions of a system and putting particular emphasis on their similarities and differences. The AdResS and H-AdResS adaptive resolution simulation schemes are reported as examples of dual-resolution approaches, especially focusing in particular on their theoretical background.

show abstract

Multiscale simulation of small peptides: Consistent conformational sampling in atomistic and coarse‐grained models

et al. 2012

View full text Add to dashboard Cite

A bottom-up coarse-graining procedure for peptides in aqueous solution is presented, where the interactions in the coarse-grained (CG) model are determined such that the CG peptide samples conformations according to a high-resolution (atomistic) model. It is shown that important aspects of conformational sampling, such as correlated degrees of freedom (DOF) which play an important role in secondary structure formation, can be reproduced in the CG description. In some cases, microscopic structural/conformational details are lost in the coarse-graining process. We show that these "lost" properties can be recovered in a backmapping procedure which reintroduces atomistic DOF into CG structures - as long as the overall conformational sampling of the molecule is correctly represented in the CG level of resolution. Thus, it is possible to link an existing all-atom model of a biomolecular system with a CG description such that after inverse mapping one can recover structures at high resolution with the correctly sampled (according to the atomistic model) conformational properties.

show abstract

Systematic coarse-graining of molecular models by the Newton inversion method

Cited by 142 publications

References 44 publications

A Coarse-Grained DNA Model Parameterized from Atomistic Simulations by Inverse Monte Carlo

A Coarse-Grained DNA Model Parameterized from Atomistic Simulations by Inverse Monte Carlo

Computer Simulations of Soft Matter: Linking the Scales

Multiscale simulation of small peptides: Consistent conformational sampling in atomistic and coarse‐grained models

Contact Info

Product

Resources

About