Dataset Information

Simultaneous Visualization of Covalent and Noncovalent Interactions Using Regions of Density Overlap.

ABSTRACT: We introduce a density-dependent bonding descriptor that enables simultaneous visualization of both covalent and noncovalent interactions. The proposed quantity is tailored to reveal the regions of space, where the total electron density results from a strong overlap of shell, atomic, or molecular densities. We show that this approach is successful in describing a variety of bonding patterns as well as nonbonding contacts. The Density Overlap Regions Indicator (DORI) analysis is also exploited to visualize and quantify the concept of electronic compactness in supramolecular chemistry. In particular, the scalar field is used to compare the compactness in molecular crystals, with a special emphasis on quaterthiophene derivatives with enhanced charge mobilities.

SUBMITTER: de Silva P

PROVIDER: S-EPMC4158806 | biostudies-other | 2014 Sep

REPOSITORIES: biostudies-other

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Publications

Simultaneous Visualization of Covalent and Noncovalent Interactions Using Regions of Density Overlap.

de Silva Piotr P Corminboeuf Clémence C

Journal of chemical theory and computation 20140630 9

We introduce a density-dependent bonding descriptor that enables simultaneous visualization of both covalent and noncovalent interactions. The proposed quantity is tailored to reveal the regions of space, where the total electron density results from a strong overlap of shell, atomic, or molecular densities. We show that this approach is successful in describing a variety of bonding patterns as well as nonbonding contacts. The Density Overlap Regions Indicator (DORI) analysis is also exploited t ...[more]

PMID: 25221443

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Project description:Over the past decade, we have developed a spectroscopic approach to measure electric fields inside matter with high spatial (<1 Å) and field (<1 MV/cm) resolution. The approach hinges on exploiting a physical phenomenon known as the vibrational Stark effect (VSE), which ultimately provides a direct mapping between observed vibrational frequencies and electric fields. Therefore, the frequency of a vibrational probe encodes information about the local electric field in the vicinity around the probe. The VSE method has enabled us to understand in great detail the underlying physical nature of several important biomolecular phenomena, such as drug-receptor selectivity in tyrosine kinases, catalysis by the enzyme ketosteroid isomerase, and unidirectional electron transfer in the photosynthetic reaction center. Beyond these specific examples, the VSE has provided a conceptual foundation for how to model intermolecular (noncovalent) interactions in a quantitative, consistent, and general manner. The starting point for research in this area is to choose (or design) a vibrational probe to interrogate the particular system of interest. Vibrational probes are sometimes intrinsic to the system in question, but we have also devised ways to build them into the system (extrinsic probes), often with minimal perturbation. With modern instruments, vibrational frequencies can increasingly be recorded with very high spatial, temporal, and frequency resolution, affording electric field maps correspondingly resolved in space, time, and field magnitude. In this Account, we set out to explain the VSE in broad strokes to make its relevance accessible to chemists of all specialties. Our intention is not to provide an encyclopedic review of published work but rather to motivate the underlying framework of the methodology and to describe how we make and interpret the measurements. Using certain vibrational probes, benchmarked against computer models, it is possible to use the VSE to measure absolute electric fields in arbitrary environments. The VSE approach provides an organizing framework for thinking generally about intermolecular interactions in a quantitative way and may serve as a useful conceptual tool for molecular design.

Project description:BackgroundA fundamental goal of single nucleotide polymorphism (SNP) genotyping is to determine the sharing of alleles between individuals across genomic loci. Such analyses have diverse applications in defining the relatedness of individuals (including unexpected relationships in nominally unrelated individuals, or consanguinity within pedigrees), analyzing meiotic crossovers, and identifying a broad range of chromosomal anomalies such as hemizygous deletions and uniparental disomy, and analyzing population structure.Principal findingsWe present SNPduo, a command-line and web accessible tool for analyzing and visualizing the relatedness of any two individuals using identity by state. Using identity by state does not require prior knowledge of allele frequencies or pedigree information, and is more computationally tractable and is less affected by population stratification than calculating identity by descent probabilities. The web implementation visualizes shared genomic regions, and generates UCSC viewable tracks. The command-line version requires pedigree information for compatibility with existing software and determining specified relationships even though pedigrees are not required for IBS calculation, generates no visual output, is written in portable C++, and is well-suited to analyzing large datasets. We demonstrate how the SNPduo web tool identifies meiotic crossover positions in siblings, and confirm our findings by visualizing meiotic recombination in synthetic three-generation pedigrees. We applied SNPduo to 210 nominally unrelated Phase I / II HapMap samples and, consistent with previous findings, identified six undeclared pairs of related individuals. We further analyzed identity by state in 2,883 individuals from multiplex families with autism and identified a series of anomalies including related parents, an individual with mosaic loss of chromosome 18, an individual with maternal heterodisomy of chromosome 16, and unexplained replicate samples.ConclusionsSNPduo provides the ability to explore and visualize SNP data to characterize the relatedness between individuals. It is compatible with, but distinct from, other established analysis software such as PLINK, and performs favorably in benchmarking studies for the analyses of genetic relatedness.

Dataset Information

Simultaneous Visualization of Covalent and Noncovalent Interactions Using Regions of Density Overlap.

Publications

Simultaneous Visualization of Covalent and Noncovalent Interactions Using Regions of Density Overlap.

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