Hamid Eghbalnia - Academia.edu (original) (raw)

Papers by Hamid Eghbalnia

Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identifie... more Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identified in a protein in the 1980s. Subsequent surveys of high-resolution X-ray crystal structures found multiple instances, but their preponderance was determined to be infrequent. Hydrogen atoms participating in a hydrogen bond to the p-π cloud of an aromatic ring are expected to experience an upfield chemical shift arising from a shielding ring current shift. We survey the Biological Magnetic Resonance Data Bank for amide hydrogens exhibiting unusual shifts as well as corroborating nuclear Overhauser effects between the amide protons and ring protons. We find evidence that Trp residues are more likely to be involved in p-π hydrogen bonds than other aromatic amino acids, whereas His residues are more likely to be involved in hydrogen bonds with a ring nitrogen acting as the hydrogen acceptor. The p-π hydrogen bonds may be more abundant than previously believed. The inclusion in NMR structure refinement protocols of shift effects in amide protons from aromatic side chains, or explicit hydrogen bond restraints between amides and aromatic rings, could improve the local accuracy of side-chain orientations in solution NMR protein structures, but their impact on global accuracy is likely be limited.

Journal of Neuroscience Methods, Apr 1, 2022

BACKGROUND Spike trains are series of interspike intervals in a specific order that can be charac... more BACKGROUND Spike trains are series of interspike intervals in a specific order that can be characterized by their probability distributions and order in time which refer to the concepts of rate and spike timing features. Periodic structure in the spike train can be reflected in oscillatory activities. Thus, there is a direct link between oscillator activities and the spike train. The proposed methods are to investigate the dependency of emerging oscillatory activities to the rate and the spike timing features. METHOD First, the circular statistics methods were compared to Fast Fourier Transform for best estimation of spectra. Second, two statistical tests were introduced to help make decisions regarding the dependency of spectrum, or individual frequencies, onto rate and spike timing. Third, the methodology is applied to in-vivo recordings of basal ganglia neurons in mouse, primate, and human. Finally, this novel framework is shown to allow the investigation of subsets of spikes contributing to individual oscillators. RESULTS Use of circular statistical methods, in comparison to FFT, minimizes spectral leakage. Using virtual spike trains, the Rate versus Timing Dependency Spectrum Test (or RTDs-Test) permits identifying spectral spike trains solely dependent on the rate feature from those that are also dependent on the spike timing feature. Similarly, the Rate versus Timing Dependency Frequency Test (or RTDf-Test), allows to identify individual oscillators with partial dependency on spike timing. Dependency on spike timing was found for all in-vivo recordings but only in few frequencies. The mapping in frequency and time of dependencies showed a dynamical process that may be organizing the basal ganglia function. CONCLUSIONS The methodology may improve our understanding of the emergence of oscillatory activities and, possibly, the relation between oscillatory activities and circuitry functions.

Magnetic resonance, Oct 25, 2021

Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identifie... more Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identified in a protein in the 1980s. Subsequent surveys of high-resolution X-ray crystal structures found multiple instances, but their preponderance was determined to be infrequent. Hydrogen atoms participating in a hydrogen bond to the p-π cloud of an aromatic ring are expected to experience an upfield chemical shift arising from a shielding ring current shift. We surveyed the Biological Magnetic Resonance Data Bank for amide hydrogens exhibiting unusual shifts as well as corroborating nuclear Overhauser effects between the amide protons and ring protons. We found evidence that Trp residues are more likely to be involved in p-π hydrogen bonds than other aromatic amino acids, whereas His residues are more likely to be involved in in-plane hydrogen bonds, with a ring nitrogen acting as the hydrogen acceptor. The p-π hydrogen bonds may be more abundant than previously believed. The inclusion in NMR structure refinement protocols of shift effects in amide protons from aromatic sidechains, or explicit hydrogen bond restraints between amides and aromatic rings, could improve the local accuracy of sidechain orientations in solution NMR protein structures, but their impact on global accuracy is likely be limited.

Journal of Biomolecular NMR, Dec 22, 2018

The growth of the biological nuclear magnetic resonance (NMR) field and the development of new ex... more The growth of the biological nuclear magnetic resonance (NMR) field and the development of new experimental technology have mandated the revision and enlargement of the NMR-STAR ontology used to represent experiments, spectral and derived data, and supporting metadata. We present here a brief description of the NMR-STAR ontology and software tools for manipulating NMR-STAR data files, editing the files, extracting selected data, and creating data visualizations. Detailed information on these is accessible from the links provided.

Lecture notes in business information processing, 2019

We describe an approach to improving the quality and interoperability of open data related to sma... more We describe an approach to improving the quality and interoperability of open data related to small molecules, such as metabolites, drugs, natural products, food additives, and environmental contaminants. The approach involves computer implementation of an extended version of the IUPAC International Chemical Identifier (InChI) system that utilizes the three-dimensional structure of a compound to generate reproducible compound identifiers (standard InChI strings) and universally reproducible designators for all constituent atoms of each compound. These compound and atom identifiers enable reliable federation of information from a wide range of freely accessible databases. In addition, these designators provide a platform for the derivation and promulgation of information regarding the physical properties of these molecules. Examples of applications include, compound dereplication, derivation of force fields used in determination of three-dimensional structures and investigations of molecular interactions, and parameterization of NMR spin system matrices used in compound identification and quantification. We are developing a data definition language (DDL) and STAR-based data dictionary to support the storage and retrieval of these kinds of information in digital resources. The current database contains entries for more than 90 million unique compounds.

Nucleic Acids Research, Dec 7, 2022

The Biological Magnetic Resonance Data Bank (BMRB, https://bmrb.io) is the international open dat... more The Biological Magnetic Resonance Data Bank (BMRB, https://bmrb.io) is the international open data repository for biomolecular nuclear magnetic resonance (NMR) data. Comprised of both empirical and derived data, BMRB has applications in the study of biomacromolecular structure and dynamics, biomolecular interactions, drug discovery, intrinsically disordered proteins, natural products, biomarkers, and metabolomics. Advances including GHzclass NMR instruments, national and trans-national NMR cyberinfrastructure, hybrid structural biology methods and machine learning are driving increases in the amount, type, and applications of NMR data in the biosciences. BMRB is a Core Archive and member of the Worldwide Protein Data Bank (wwPDB).

Carolina Digital Repository (University of North Carolina at Chapel Hill), 2022

Metabolomics investigates global metabolic alterations associated with chemical, biological, phys... more Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Investigative Ophthalmology & Visual Science, Jul 13, 2018

Journal of Biomolecular NMR, Jan 2, 2018

Frontiers in Molecular Biosciences, Jan 17, 2022

The Biological Magnetic Resonance Data Bank (BMRB) has served the NMR structural biology communit... more The Biological Magnetic Resonance Data Bank (BMRB) has served the NMR structural biology community for 40 years, and has been instrumental in the development of many widely-used tools. It fosters the reuse of data resources in structural biology by embodying the FAIR data principles (Findable, Accessible, Inter-operable, and Re-usable). NMRbox is less than a decade old, but complements BMRB by providing NMR software and highperformance computing resources, facilitating the reuse of software resources. BMRB and NMRbox both facilitate reproducible research. NMRbox also fosters the development and deployment of complex meta-software. Combining BMRB and NMRbox helps speed and simplify workflows that utilize BMRB, and enables facile federation of BMRB with other data repositories. Utilization of BMRB and NMRbox in tandem will enable additional advances, such as machine learning, that are poised to become increasingly powerful.

Analytical Chemistry, Nov 7, 2017

The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routine... more The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routinely used to identify and characterize molecules and molecular interactions in a wide range of applications, including clinical biomarker discovery, drug discovery, environmental chemistry, and metabolomics. The set of peak positions and intensities from a reference NMR spectrum generally serves as the identifying signature for a compound. Reference spectra normally are collected under specific conditions of pH, temperature, and magnetic field strength, because changes in conditions can distort the identifying signatures of compounds. A spin system matrix that parametrizes chemical shifts and coupling constants among spins provides a much richer feature set for a compound than a spectral signature based on peak positions and intensities. Spin system matrices expand the applicability of NMR spectral libraries beyond the specific conditions under which data were collected. In addition to being able to simulate spectra at any field strength, spin parameters can be adjusted to systematically explore alterations in chemical shift patterns due to variations in other experimental conditions, such as compound concentration, pH, or temperature. We present methodology and software for efficient interactive optimization of spin parameters against experimental 1D-1 H NMR spectra of small molecules. We have used the software to generate spin system matrices for a set of key mammalian metabolites and are also using the software to parametrize spectra of small molecules used in NMR-based ligand screening. The software, along with optimized spin system matrix data for a growing number of compounds, is available from http://gissmo.nmrfam.wisc.edu/.

Journal of Animal Science, 2021

Plasma metabolomic markers were evaluated in a population of 36 Labrador Retrievers (BW 31.32 ± 0... more Plasma metabolomic markers were evaluated in a population of 36 Labrador Retrievers (BW 31.32 ± 0.85 kg) studying the effects of a dietary Saccharomyces cerevisiae fermentation product (SCFP) at baseline and before and after two distance-defined exercise regimens (DDER; 6.4 km and 16.1 km). Canine subjects were blocked by BW and randomly assigned to one of two treatments: a control group receiving no supplement (CON) or a group receiving a single, daily oral dose of 250 mg SCFP. Each treatment group was comprised of 9 males and 9 females. During each DDER subjects were guided by an all-terrain vehicle and blood samples were collected at baseline and before and after each DDER. All metabolomic studies were performed blinded to treatment and DDER regimen. Metabolic signals were identified using untargeted nuclear magnetic resonance and mass spectroscopy. A total of 31 differentially relevant metabolites reflecting host metabolism were selected from a large array of signals along with ...

NMR-Based Metabolomics, 2019

Metabolomics is the study of profiles of small molecules in biological fluids, cells, or organs. ... more Metabolomics is the study of profiles of small molecules in biological fluids, cells, or organs. These profiles can be thought of as the "fingerprints" left behind from chemical processes occurring in biological systems. Because of its potential for groundbreaking applications in disease diagnostics, biomarker discovery, and systems biology, metabolomics has emerged as a rapidly growing area of research. Metabolomics investigations often, but not always, involve the identification and quantification of endogenous and exogenous metabolites in biological samples. Software tools and databases play a crucial role in advancing the rigor, robustness, reproducibility, and validation of these studies. Specifically, the establishment of a robust library of spectral signatures with unique compound descriptors and atom identities plays a key role in profiling studies based on data from nuclear magnetic resonance (NMR) spectroscopy. Here, we discuss developments leading to a rigorous basis for unique identification of compounds, reproducible numbering of atoms, the compact representation of NMR spectra of metabolites and small molecules, tools for improved compound identification, quantification and visualization, and approaches toward the goal of rigorous analysis of metabolomics data.

Multi-nuclear, multi-dimensional Fourier transform (FT) NMR spectroscopy has ushered in a broad r... more Multi-nuclear, multi-dimensional Fourier transform (FT) NMR spectroscopy has ushered in a broad range of new applications in chemistry and biology. Multi-dimensional NMR experimental data comes at a price, however. Additional dimensions lead to exponential increases in data collection time, and the number of data points required increases at polynomial rates with the spectrometer field strength. Reducing data collection times while retaining the benefits of multi-dimensional experiments is one of the major challenges in NMR spectroscopy. This chapter focuses on the use of methods collectively referred to as reduced dimensionality experiments (RD) and their application to the recovery of spectral parameters—for example, peak positions. While standard sampling approaches can interpret the data using the standard and established computational methods rooted in the Fourier transform theory, RD methods can benefit from alternative approaches that are coupled to the ideas of RD. In this c...

We introduced a le format based on the commonly used "Structure Data Format" (.sdf) to combine th... more We introduced a le format based on the commonly used "Structure Data Format" (.sdf) to combine the chemical shifts, couplings, lists of 2D correlations and assignment (NMReDATA) with a chemical structure in the .mol format. NMR records (NMR spectra + NMReDATA) including the .sdf le will be generated by computerassisted structure elucidation software or web-based tools under development. The goal of the NMReDATA initiative is to introduce a manner to associate the data extracted from a "full" NMR analysis (the NMReDATA) to a chemical structure. A record is a folder or database entry containing: 1) All the NMR spectra of a compound (including FID's, acquisition and processing parameters). 2) The .sdf le containing the NMReDATA Mid-2016: Proposition by the members of the Associate editorial board of Magnetic resonance in Chemistry to request authors to submit NMR spectra and the extracted data in a manner allowing serious reviewing and to become a source or reliable peer-reviewed NMR data. September 2016: Decision of the Editorial board of Magnetic Resonance in Chemistry to request NMR data for structure papers. Until March 2017: Elaboration of a beta version of the format to include NMR data in .sdf les.

Scientific Data, 2020

The chemical composition of saccharide complexes underlies their biomedical activities as biomark... more The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide and non-saccharide origin becomes a challenging computational problem that hinders the aggregation of information about their bioactive moieties. We have developed an algorithm and software package called “Cheminformatics Tool for Probabilistic Identification of Carbohydrates” (CTPIC) that analyzes the covalent structure of a compound to yield a probabilistic measure for distinguishing saccharides and saccharide-derivatives from non-saccharides. CTPIC analysis of the RCSB Ligand Expo (database of small molecules found to bind proteins in the Protein Data Bank) led to a substantial increase in the number of ligands characterized as saccharides. CTPIC analysis of Protein Data Bank identifi...

Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identifie... more Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identified in a protein in the 1980s. Subsequent surveys of high-resolution X-ray crystal structures found multiple instances, but their preponderance was determined to be infrequent. Hydrogen atoms participating in a hydrogen bond to the p-π cloud of an aromatic ring are expected to experience an upfield chemical shift arising from a shielding ring current shift. We survey the Biological Magnetic Resonance Data Bank for amide hydrogens exhibiting unusual shifts as well as corroborating nuclear Overhauser effects between the amide protons and ring protons. We find evidence that Trp residues are more likely to be involved in p-π hydrogen bonds than other aromatic amino acids, whereas His residues are more likely to be involved in hydrogen bonds with a ring nitrogen acting as the hydrogen acceptor. The p-π hydrogen bonds may be more abundant than previously believed. The inclusion in NMR structure refinement protocols of shift effects in amide protons from aromatic side chains, or explicit hydrogen bond restraints between amides and aromatic rings, could improve the local accuracy of side-chain orientations in solution NMR protein structures, but their impact on global accuracy is likely be limited.

Journal of Neuroscience Methods, Apr 1, 2022

BACKGROUND Spike trains are series of interspike intervals in a specific order that can be charac... more BACKGROUND Spike trains are series of interspike intervals in a specific order that can be characterized by their probability distributions and order in time which refer to the concepts of rate and spike timing features. Periodic structure in the spike train can be reflected in oscillatory activities. Thus, there is a direct link between oscillator activities and the spike train. The proposed methods are to investigate the dependency of emerging oscillatory activities to the rate and the spike timing features. METHOD First, the circular statistics methods were compared to Fast Fourier Transform for best estimation of spectra. Second, two statistical tests were introduced to help make decisions regarding the dependency of spectrum, or individual frequencies, onto rate and spike timing. Third, the methodology is applied to in-vivo recordings of basal ganglia neurons in mouse, primate, and human. Finally, this novel framework is shown to allow the investigation of subsets of spikes contributing to individual oscillators. RESULTS Use of circular statistical methods, in comparison to FFT, minimizes spectral leakage. Using virtual spike trains, the Rate versus Timing Dependency Spectrum Test (or RTDs-Test) permits identifying spectral spike trains solely dependent on the rate feature from those that are also dependent on the spike timing feature. Similarly, the Rate versus Timing Dependency Frequency Test (or RTDf-Test), allows to identify individual oscillators with partial dependency on spike timing. Dependency on spike timing was found for all in-vivo recordings but only in few frequencies. The mapping in frequency and time of dependencies showed a dynamical process that may be organizing the basal ganglia function. CONCLUSIONS The methodology may improve our understanding of the emergence of oscillatory activities and, possibly, the relation between oscillatory activities and circuitry functions.

Magnetic resonance, Oct 25, 2021

Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identifie... more Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identified in a protein in the 1980s. Subsequent surveys of high-resolution X-ray crystal structures found multiple instances, but their preponderance was determined to be infrequent. Hydrogen atoms participating in a hydrogen bond to the p-π cloud of an aromatic ring are expected to experience an upfield chemical shift arising from a shielding ring current shift. We surveyed the Biological Magnetic Resonance Data Bank for amide hydrogens exhibiting unusual shifts as well as corroborating nuclear Overhauser effects between the amide protons and ring protons. We found evidence that Trp residues are more likely to be involved in p-π hydrogen bonds than other aromatic amino acids, whereas His residues are more likely to be involved in in-plane hydrogen bonds, with a ring nitrogen acting as the hydrogen acceptor. The p-π hydrogen bonds may be more abundant than previously believed. The inclusion in NMR structure refinement protocols of shift effects in amide protons from aromatic sidechains, or explicit hydrogen bond restraints between amides and aromatic rings, could improve the local accuracy of sidechain orientations in solution NMR protein structures, but their impact on global accuracy is likely be limited.

Journal of Biomolecular NMR, Dec 22, 2018

The growth of the biological nuclear magnetic resonance (NMR) field and the development of new ex... more The growth of the biological nuclear magnetic resonance (NMR) field and the development of new experimental technology have mandated the revision and enlargement of the NMR-STAR ontology used to represent experiments, spectral and derived data, and supporting metadata. We present here a brief description of the NMR-STAR ontology and software tools for manipulating NMR-STAR data files, editing the files, extracting selected data, and creating data visualizations. Detailed information on these is accessible from the links provided.

Lecture notes in business information processing, 2019

We describe an approach to improving the quality and interoperability of open data related to sma... more We describe an approach to improving the quality and interoperability of open data related to small molecules, such as metabolites, drugs, natural products, food additives, and environmental contaminants. The approach involves computer implementation of an extended version of the IUPAC International Chemical Identifier (InChI) system that utilizes the three-dimensional structure of a compound to generate reproducible compound identifiers (standard InChI strings) and universally reproducible designators for all constituent atoms of each compound. These compound and atom identifiers enable reliable federation of information from a wide range of freely accessible databases. In addition, these designators provide a platform for the derivation and promulgation of information regarding the physical properties of these molecules. Examples of applications include, compound dereplication, derivation of force fields used in determination of three-dimensional structures and investigations of molecular interactions, and parameterization of NMR spin system matrices used in compound identification and quantification. We are developing a data definition language (DDL) and STAR-based data dictionary to support the storage and retrieval of these kinds of information in digital resources. The current database contains entries for more than 90 million unique compounds.

Nucleic Acids Research, Dec 7, 2022

The Biological Magnetic Resonance Data Bank (BMRB, https://bmrb.io) is the international open dat... more The Biological Magnetic Resonance Data Bank (BMRB, https://bmrb.io) is the international open data repository for biomolecular nuclear magnetic resonance (NMR) data. Comprised of both empirical and derived data, BMRB has applications in the study of biomacromolecular structure and dynamics, biomolecular interactions, drug discovery, intrinsically disordered proteins, natural products, biomarkers, and metabolomics. Advances including GHzclass NMR instruments, national and trans-national NMR cyberinfrastructure, hybrid structural biology methods and machine learning are driving increases in the amount, type, and applications of NMR data in the biosciences. BMRB is a Core Archive and member of the Worldwide Protein Data Bank (wwPDB).

Carolina Digital Repository (University of North Carolina at Chapel Hill), 2022

Metabolomics investigates global metabolic alterations associated with chemical, biological, phys... more Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Investigative Ophthalmology & Visual Science, Jul 13, 2018

Journal of Biomolecular NMR, Jan 2, 2018

Frontiers in Molecular Biosciences, Jan 17, 2022

The Biological Magnetic Resonance Data Bank (BMRB) has served the NMR structural biology communit... more The Biological Magnetic Resonance Data Bank (BMRB) has served the NMR structural biology community for 40 years, and has been instrumental in the development of many widely-used tools. It fosters the reuse of data resources in structural biology by embodying the FAIR data principles (Findable, Accessible, Inter-operable, and Re-usable). NMRbox is less than a decade old, but complements BMRB by providing NMR software and highperformance computing resources, facilitating the reuse of software resources. BMRB and NMRbox both facilitate reproducible research. NMRbox also fosters the development and deployment of complex meta-software. Combining BMRB and NMRbox helps speed and simplify workflows that utilize BMRB, and enables facile federation of BMRB with other data repositories. Utilization of BMRB and NMRbox in tandem will enable additional advances, such as machine learning, that are poised to become increasingly powerful.

Analytical Chemistry, Nov 7, 2017

The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routine... more The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routinely used to identify and characterize molecules and molecular interactions in a wide range of applications, including clinical biomarker discovery, drug discovery, environmental chemistry, and metabolomics. The set of peak positions and intensities from a reference NMR spectrum generally serves as the identifying signature for a compound. Reference spectra normally are collected under specific conditions of pH, temperature, and magnetic field strength, because changes in conditions can distort the identifying signatures of compounds. A spin system matrix that parametrizes chemical shifts and coupling constants among spins provides a much richer feature set for a compound than a spectral signature based on peak positions and intensities. Spin system matrices expand the applicability of NMR spectral libraries beyond the specific conditions under which data were collected. In addition to being able to simulate spectra at any field strength, spin parameters can be adjusted to systematically explore alterations in chemical shift patterns due to variations in other experimental conditions, such as compound concentration, pH, or temperature. We present methodology and software for efficient interactive optimization of spin parameters against experimental 1D-1 H NMR spectra of small molecules. We have used the software to generate spin system matrices for a set of key mammalian metabolites and are also using the software to parametrize spectra of small molecules used in NMR-based ligand screening. The software, along with optimized spin system matrix data for a growing number of compounds, is available from http://gissmo.nmrfam.wisc.edu/.

Journal of Animal Science, 2021

Plasma metabolomic markers were evaluated in a population of 36 Labrador Retrievers (BW 31.32 ± 0... more Plasma metabolomic markers were evaluated in a population of 36 Labrador Retrievers (BW 31.32 ± 0.85 kg) studying the effects of a dietary Saccharomyces cerevisiae fermentation product (SCFP) at baseline and before and after two distance-defined exercise regimens (DDER; 6.4 km and 16.1 km). Canine subjects were blocked by BW and randomly assigned to one of two treatments: a control group receiving no supplement (CON) or a group receiving a single, daily oral dose of 250 mg SCFP. Each treatment group was comprised of 9 males and 9 females. During each DDER subjects were guided by an all-terrain vehicle and blood samples were collected at baseline and before and after each DDER. All metabolomic studies were performed blinded to treatment and DDER regimen. Metabolic signals were identified using untargeted nuclear magnetic resonance and mass spectroscopy. A total of 31 differentially relevant metabolites reflecting host metabolism were selected from a large array of signals along with ...

NMR-Based Metabolomics, 2019

Metabolomics is the study of profiles of small molecules in biological fluids, cells, or organs. ... more Metabolomics is the study of profiles of small molecules in biological fluids, cells, or organs. These profiles can be thought of as the "fingerprints" left behind from chemical processes occurring in biological systems. Because of its potential for groundbreaking applications in disease diagnostics, biomarker discovery, and systems biology, metabolomics has emerged as a rapidly growing area of research. Metabolomics investigations often, but not always, involve the identification and quantification of endogenous and exogenous metabolites in biological samples. Software tools and databases play a crucial role in advancing the rigor, robustness, reproducibility, and validation of these studies. Specifically, the establishment of a robust library of spectral signatures with unique compound descriptors and atom identities plays a key role in profiling studies based on data from nuclear magnetic resonance (NMR) spectroscopy. Here, we discuss developments leading to a rigorous basis for unique identification of compounds, reproducible numbering of atoms, the compact representation of NMR spectra of metabolites and small molecules, tools for improved compound identification, quantification and visualization, and approaches toward the goal of rigorous analysis of metabolomics data.

Multi-nuclear, multi-dimensional Fourier transform (FT) NMR spectroscopy has ushered in a broad r... more Multi-nuclear, multi-dimensional Fourier transform (FT) NMR spectroscopy has ushered in a broad range of new applications in chemistry and biology. Multi-dimensional NMR experimental data comes at a price, however. Additional dimensions lead to exponential increases in data collection time, and the number of data points required increases at polynomial rates with the spectrometer field strength. Reducing data collection times while retaining the benefits of multi-dimensional experiments is one of the major challenges in NMR spectroscopy. This chapter focuses on the use of methods collectively referred to as reduced dimensionality experiments (RD) and their application to the recovery of spectral parameters—for example, peak positions. While standard sampling approaches can interpret the data using the standard and established computational methods rooted in the Fourier transform theory, RD methods can benefit from alternative approaches that are coupled to the ideas of RD. In this c...

We introduced a le format based on the commonly used "Structure Data Format" (.sdf) to combine th... more We introduced a le format based on the commonly used "Structure Data Format" (.sdf) to combine the chemical shifts, couplings, lists of 2D correlations and assignment (NMReDATA) with a chemical structure in the .mol format. NMR records (NMR spectra + NMReDATA) including the .sdf le will be generated by computerassisted structure elucidation software or web-based tools under development. The goal of the NMReDATA initiative is to introduce a manner to associate the data extracted from a "full" NMR analysis (the NMReDATA) to a chemical structure. A record is a folder or database entry containing: 1) All the NMR spectra of a compound (including FID's, acquisition and processing parameters). 2) The .sdf le containing the NMReDATA Mid-2016: Proposition by the members of the Associate editorial board of Magnetic resonance in Chemistry to request authors to submit NMR spectra and the extracted data in a manner allowing serious reviewing and to become a source or reliable peer-reviewed NMR data. September 2016: Decision of the Editorial board of Magnetic Resonance in Chemistry to request NMR data for structure papers. Until March 2017: Elaboration of a beta version of the format to include NMR data in .sdf les.

Scientific Data, 2020

The chemical composition of saccharide complexes underlies their biomedical activities as biomark... more The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide and non-saccharide origin becomes a challenging computational problem that hinders the aggregation of information about their bioactive moieties. We have developed an algorithm and software package called “Cheminformatics Tool for Probabilistic Identification of Carbohydrates” (CTPIC) that analyzes the covalent structure of a compound to yield a probabilistic measure for distinguishing saccharides and saccharide-derivatives from non-saccharides. CTPIC analysis of the RCSB Ligand Expo (database of small molecules found to bind proteins in the Protein Data Bank) led to a substantial increase in the number of ligands characterized as saccharides. CTPIC analysis of Protein Data Bank identifi...