Biomedical subjects

Antony J Williams

Publications and source records attributed to Antony J Williams.

10 recordsLinked to original sources

PubMed2006

The application of 1H high-resolution magic-angle spinning NMR for the study of clay-organic associations in natural and synthetic complexes.

The preferential sorption of model compounds to calcium-exchanged montmorillonite surfaces was investigated using 1H high-resolution magic-angle spinning (HR-MAS) and liquid-state NMR. Synthetic mixtures, representing the major structural categories abundant in natural organic matter (NOM), and two soil extracts were sorbed to montmorillonite. The NMR spectra indicate that, of the organic components observable by 1H HR-MAS NMR, aliphatic components preferentially sorb to the clay surface, while carbohydrates and amino acids mainly remain in the supernatant. These results may help explain the highly aliphatic nature of organic matter associated with clay fractions in natural soils and sediments. Investigations using the synthetic mixtures demonstrate a specific interaction between the clay surface and the polar region in 1-palmitoyl-3-stearoyl-rac-glycerol. Similar observations were obtained with natural soil extracts. The results presented have important implications for understanding the role of organoclay complexes in natural processes, and provides preliminary evidence that HR-MAS NMR is a powerful analytical technique for the investigation of organoclay complex structure and conformation.

Aluminum Silicates↗

PubMed2006

Long-range carbon-carbon connectivity via unsymmetrical indirect covariance processing of HSQC and HMBC NMR data.

It was recently demonstrated that an IDR- (Inverted Direct Response) HSQC-TOCSY data set could be decomposed into a negatively phased direct response spectrum and a positively phased relayed response spectrum that could then be subjected to unsymmetrical indirect covariance processing for the removal of artifacts due to response overlap in the proton NMR spectrum of the molecule. Using experimentally discrete HSQC and HMBC data sets, it is shown that unsymmetrical indirect covariance processing of the pair of NMR spectra affords a presentation containing long-range carbon-carbon connectivity information. The method is demonstrated using strychnine as a model compound. The resulting data are largely free of artifacts although artifacts can arise due to proton response overlap, as previously reported.

Journal Article↗

PubMed2006

Automated structure verification based on 1H NMR prediction.

A unique opportunity exists when an experimental NMR spectrum is obtained for which a specific chemical structure is anticipated. A process of Verification--the confirmation of a postulated structure--is now possible, as opposed to Elucidation-the de novo determination of a structure. A method for automated structure verification is suggested, which compares the chemical shifts, intensities and multiplicities of signals in an experimental 1H NMR spectrum with those from a predicted spectrum for the proposed structure. A match factor (MF) is produced and used to classify the spectrum-structure match into one of three categories, correct, ambiguous, or incorrect. The verification result is also augmented by the spectrum assignment obtained as part of the verification process. This method was tested on a set of synthetic spectra and several sets of experimental spectra, all of which were automatically prepared from raw data. Taking into account even the most problematic structures, with many labile protons present and poor prediction accuracy, 50% of all spectra can still be automatically verified without any false positives or negatives. In a blind test on a typical set of data, it is shown that fewer than 31% of the structures would need manual evaluation. This means that a system is possible whereby 69% of the spectra are prepared and evaluated automatically, and never need to be seen or evaluated by a human.

Algorithms↗

PubMed2006

Computational approaches to the prediction of blood-brain barrier permeability: A comparative analysis of central nervous system drugs versus secretase inhibitors for Alzheimer's disease.

This review summarizes progress made in the development of fully computational approaches to the prediction of blood-brain barrier (BBB) permeability of small molecules, with a focus on rapid computational methods suitable for the analysis of large compound sets and virtual screening. A comparative analysis using the recently developed Advanced Chemistry Development (ACD/Labs) Inc BBB permeability algorithm for the calculation of logBB values for known Alzheimer's disease medicines, selected central nervous system drugs and new secretase inhibitors for Alzheimer's disease, is presented. The trends in logBB values and the associated physiochemical properties of these agents as they relate to the potential for BBB permeability are also discussed.

Alzheimer Disease↗

PubMed2005

Assessing the organic composition of urban surface films using nuclear magnetic resonance spectroscopy.

Recently it has been shown that urban surfaces are covered with a thin film which mediates the fate, distribution and accumulation of semi-volatile organic compounds in the environment. In this study we apply a combination of solution, semi-solids, and solid state nuclear magnetic resonance (NMR) methods to provide a general overview of the organic constituents. In surface film collected from 30 m2 of outside windows over an area of 12 km2 in downtown Toronto, we roughly estimate that the organic carbon is approximately 35% carbohydrate, approximately 35% aliphatics, approximately 20% aromatics, and approximately 10% carbonyl groups. Various aliphatic groups can be identified including a number of acids, alcohols, alkanes, and alkenes. Also, numerous intact aliphatic esters are apparent that have not been observed before, as well as carbohydrates. The aromatic species include a small portion that appears to be derived from a polymer of styrene, in addition a larger fraction is consistent with polyhydroxylated PAH derived material, although this assignment is tentative and based solely on 1-D NMR data only. In addition, signals from polybutadiene are present and while accurate quantification is not possible, it appears that this polymer may be up to a few percents by weight of the total organic material.

Air Pollutants↗

PubMed2005

Analysis and elimination of artifacts in indirect covariance NMR spectra via unsymmetrical processing.

Indirect covariance NMR offers an alternative method of extracting spin-spin connectivity information via the conversion of an indirect-detection heteronuclear shift-correlation data matrix to a homonuclear data matrix. Using an IDR (inverted direct response)-HSQC-TOCSY spectrum as a starting point for the indirect covariance processing, a spectrum that can be described as a carbon-carbon COSY experiment is obtained. These data are analogous to the autocorrelated 13C-13C double quantum INADEQUATE experiment except that the indirect covariance NMR spectrum establishes carbon-carbon connectivities only between contiguous protonated carbons. Cyclopentafuranone and the complex polynuclear heteroaromatic naphtho[2',1':5,6]-naphtho[2',1':4,5]thieno[2,3-c]quinoline are used as model compounds. The former is a straightforward example because of its well-resolved proton spectrum, while the latter, which has considerable resonance overlap in its congested proton spectrum, gives rise to two types of artifact responses that must be considered when using the indirect covariance NMR method.

Journal Article↗

PubMed2002

Application of a new expert system for the structure elucidation of natural products from their 1D and 2D NMR data.

Described herein are applications of the latest version of the StrucEluc expert software system, enhanced to use 2D NMR data, to the structure elucidation of 60 recently isolated natural products. In this study, selected molecules containing between 15 and 65 skeletal atoms and having molecular masses ranging from 200 to 900 amu have been investigated. The correct structure was determined unambiguously for 58 of these molecules. The structures for 75% of the data sets were determined in less than one minute, while 90% of the analyses required no more than 30 minutes. The strategy of structure elucidation by this expert system is described, and several examples are discussed. These illustrate that StrucEluc is a powerful and versatile analytical tool for the structure elucidation of natural products.

Biological Products↗

PubMedDate not supplied

Structure Elucidator: a versatile expert system for molecular structure elucidation from 1D and 2D NMR data and molecular fragments.

StrucEluc is an expert system that allows the computer-assisted elucidation of chemical structures based on the inputs of a series of spectral data including 1D and 2D NMR and mass spectra. The system has been enabled to allow a chemist to utilize fragments stored in a fragment database as well as user-defined fragments submitted by the chemist in the structure elucidation process. The association of fragments in this way has been shown to dramatically speed up the process of structure generation from 2D NMR data and has helped to minimize or eliminate the need for user intervention thereby further enabling the vision of automated elucidation. The use of fragments has frequently transformed very difficult 2D NMR elucidation challenges into easily solvable tasks. A strategy to utilize molecular fragments has been developed and optimized based on specific challenging examples. This strategy will be described here using real world examples. Experience gained by solving more than 150 structure elucidation problems from a variety of literature sources is also reviewed in this work.

Journal Article↗

PubMedDate not supplied

Structure elucidation from 2D NMR spectra using the StrucEluc expert system: detection and removal of contradictions in the data.

The elucidation of chemical structures from 2D NMR data commonly utilizes a combination of COSY, HMQC/HSQC, and HMBC data. Generally COSY connectivities are assumed to mostly describe the separation of protons that are separated by 1 skeletal bond (3JHH), while HMBC connectivities represent protons separated from carbon atoms by 1 to 2 skeletal bonds (2JCH and 3JCH). Obviously COSY and HMBC connectivities of lengths greater than those described have been detected. Though experimental techniques have recently been described to aid in the identification of the nature of the couplings the detection of whether a coupling is 2-bond or greater still remains a challenge in most laboratories. In the StrucEluc software system the common lengths of the connectivities, 1-bond for COSY and 1- or 2-bond for HMBC, derived from 2D NMR data are set as the default. Therefore, in the presence of any extended connectivities contradictions can appear in the 2D NMR data. In this article, algorithmic methods for the detection and removal of contradictions in 2D NMR data that have been developed in support of StrucEluc are described. The methods are based on the analysis of molecular connectivity diagrams, MCDs. These methods have been implemented in the StrucEluc system and tested by solving 50 structural problems with 2D NMR spectral data containing contradictions. The presence of contradictions was detected by the algorithm in 90% of the cases, and the contradictions were automatically removed in approximately 50% of the problems. A method of "fuzzy" structure generation in the presence of contradictions has been suggested and successfully tested in this work. This work will demonstrate examples of the application of developed methods to a number of structural problems.

Journal Article↗

PubMedDate not supplied

Are deterministic expert systems for computer-assisted structure elucidation obsolete?

Expert systems for spectroscopic molecular structure elucidation have been developed since the mid-1960s. Algorithms associated with the structure generation process within these systems are deterministic; that is, they are based on graph theory and combinatorial analysis. A series of expert systems utilizing 2D NMR spectra have been described in the literature and are capable of determining the molecular structures of large organic molecules including complex natural products. Recently, an opinion was expressed in the literature that these systems would fail when elucidating structures containing more than 30 heavy atoms. A suggestion was put forward that stochastic algorithms for structure generation would be necessary to overcome this shortcoming. In this article, we describe a comprehensive investigation of the capabilities of the deterministic expert system Structure Elucidator. The results of performing the structure elucidation of 250 complex natural products with this program were studied and generalized. The conclusion is that 2D NMR deterministic expert systems are certainly capable of elucidating large structures (up to about 100 heavy atoms) and can deal with the complexities associated with both poor and contradictory spectral data.

Expert Systems↗