OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation.

OpenMM is a software toolkit for performing molecular simulations on a range of high performance computing architectures. It is based on a layered architecture: the lower layers function as a reusable library that can be invoked by any application, while the upper layers form a complete environment for running molecular simulations. The library API hides all hardware-specific dependencies and optimizations from the users and developers of simulation programs: they can be run without modification on any hardware on which the API has been implemented.

Molecular dynamics simulations of the full triple helical region of collagen type I provide an atomic scale view of the protein's regional heterogeneity.

Collagen is a ubiquitous extracellular matrix protein. Its biological functions, including maintenance of the structural integrity of tissues, depend on its multiscale, hierarchical structure. Three elongated, twisted peptide chains of > 1000 amino acids each assemble into trimeric proteins characterized by the defining triple helical domain.

Knowledge-based instantiation of full atomic detail into coarse-grain RNA 3D structural models.

Motivation: The recent development of methods for modeling RNA 3D structures using coarse-grain approaches creates a need to bridge low- and high-resolution modeling methods. Although they contain topological information, coarse-grain models lack atomic detail, which limits their utility for some applications.

Results: We have developed a method for adding full atomic detail to coarse-grain models of RNA 3D structures.

Improving structure-based function prediction using molecular dynamics.

The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive.

Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters.

Understanding the function of complex RNA molecules depends critically on understanding their structure. However, creating three-dimensional (3D) structural models of RNA remains a significant challenge. We present a protocol (the nucleic acid simulation tool [NAST]) for RNA modeling that uses an RNA-specific knowledge-based potential in a coarse-grained molecular dynamics engine to generate plausible 3D structures.

Combining molecular dynamics and machine learning to improve protein function recognition.

As structural genomics efforts succeed in solving protein structures with novel folds, the number of proteins with known structures but unknown functions increases. Although experimental assays can determine the functions of some of these molecules, they can be expensive and time consuming. Computational approaches can assist in identifying potential functions of these molecules.

Triple helical structure and stabilization of collagen-like molecules with 4(R)-hydroxyproline in the Xaa position.

In this study, we examine the relationships between the structure and stability of five related collagen-like molecules that have hydroxyproline residues occupying positions not observed in vertebrate collagen. Two of the molecules contain valine or threonine and form stable triple helices in water. Three of the molecules contain allo-threonine (an enantiomer of threonine), serine, or alanine, and are not stable.

A new set of molecular mechanics parameters for hydroxyproline and its use in molecular dynamics simulations of collagen-like peptides.

Recently, the importance of proline ring pucker conformations in collagen has been suggested in the context of hydroxylation of prolines. The previous molecular mechanics parameters for hydroxyproline, however, do not reproduce the correct pucker preference. We have developed a new set of parameters that reproduces the correct pucker preference.

Severity of osteogenesis imperfecta and structure of a collagen-like peptide modeling a lethal mutation site.

We show that there are correlations between the severities of osteogenesis imperfecta (OI) phenotypes and changes in the residues near the mutation site. Our results show the correlations between the severity of various forms of the inherited disease OI and alteration of residues near the site of OI causing mutations. Among our many observed correlations are particularly striking ones between the presence of nearby proline residues and lethal mutations, and the presence of nearby alanines residues and nonlethal mutations.

Theoretical and experimental studies of biotin analogues that bind almost as tightly to streptavidin as biotin.

We have used a newly developed qualitative computational approach, PROFEC (Pictorial Representation of Free Energy Changes), to visualize the areas of the ligand biotin where modifications of its structure might lead to tighter binding to the protein streptavidin. The PROFEC analysis, which includes protein flexibility and ligand solvation/desolvation, led to the suggestion that the pro-9R hydrogen atom of biotin, which is in alpha-position to the CO(2)(-) group, might be changed to a larger group and lead to better binding with streptavidin and avidin. Free energy calculations supported this suggestion and predicted that the methyl analogue should bind approximately 3 kcal/mol more tightly to streptavidin, with this difference coming exclusively from the relative desolvation free energy of the ligand.