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High-Performance Analysis of Biomolecular Containers to Measure Small-Molecule Transport, Transbilayer Lipid Diffusion, and Protein Cavities.
Bryer, Alexander J; Hadden-Perilla, Jodi A; Stone, John E; Perilla, Juan R.
Afiliación
  • Bryer AJ; Department of Chemistry and Biochemistry , University of Delaware , Newark , Delaware 19716 , United States.
  • Hadden-Perilla JA; Department of Chemistry and Biochemistry , University of Delaware , Newark , Delaware 19716 , United States.
  • Stone JE; Beckman Institute for Advanced Science and Technology , University of Illinois at Urbana-Champaign , Urbana , Illinois 61801 , United States.
  • Perilla JR; Department of Chemistry and Biochemistry , University of Delaware , Newark , Delaware 19716 , United States.
J Chem Inf Model ; 59(10): 4328-4338, 2019 10 28.
Article en En | MEDLINE | ID: mdl-31525965
ABSTRACT
Compartmentalization is a central theme in biology. Cells are composed of numerous membrane-enclosed structures, evolved to facilitate specific biochemical processes; viruses act as containers of genetic material, optimized to drive infection. Molecular dynamics simulations provide a mechanism to study biomolecular containers and the influence they exert on their environments; however, trajectory analysis software generally lacks knowledge of container interior versus exterior. Further, many relevant container analyses involve large-scale particle tracking endeavors, which may become computationally prohibitive with increasing system size. Here, a novel method based on 3-D ray casting is presented, which rapidly classifies the space surrounding biomolecular containers of arbitrary shape, enabling fast determination of the identities and counts of particles (e.g., solvent molecules) found inside and outside. The method is broadly applicable to the study of containers and enables high-performance characterization of properties such as solvent density, small-molecule transport, transbilayer lipid diffusion, and topology of protein cavities. The method is implemented in VMD, a widely used simulation analysis tool that supports personal computers, clouds, and parallel supercomputers, including ORNL's Summit and Titan and NCSA's Blue Waters, where the method can be employed to efficiently analyze trajectories encompassing millions of particles. The ability to rapidly characterize the spatial relationships of particles relative to a biomolecular container over many trajectory frames, irrespective of large particle counts, enables analysis of containers on a scale that was previously unfeasible, at a level of accuracy that was previously unattainable.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Proteínas / Lípidos Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Proteínas / Lípidos Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2019 Tipo del documento: Article