Candidate Formulae Research Articles

Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph

BackgroundIdentifying the molecular formula and fragmentation reactions of an unknown compound from its mass spectrum is crucial in areas such as natural product chemistry and metabolomics. We propose a method for identifying the correct candidate formula of an unidentified natural product from its mass spectrum. The method involves scoring the plausibility of parent candidate formulae based on a parent subformula graph (PSG), and two possible metrics relating to the number of edges in the PSG. This method is applicable to both electron-impact mass spectrometry (EI-MS) and tandem mass spectrometry (MS/MS) data. Additionally, this work introduces the two-dimensional fragmentation plot (2DFP) for visualizing PSGs.ResultsOur results suggest that incorporating information regarding the edges of the PSG results in enhanced performance in correctly identifying parent formulae, in comparison to the more well-accepted “MS/MS score”, on the 2016 Computational Assessment of Small Molecule Identification (CASMI 2016) data set (76.3 vs 58.9% correct formula identification) and the Research Centre for Toxic Compounds in the Environment (RECETOX) data set (66.2% vs 59.4% correct formula identification). In the extension of our method to identify the correct candidate formula from complex EI-MS data of semiochemicals, our method again performed better (correct formula appearing in the top 4 candidates in 20/23 vs 7/23 cases) than the MS/MS score, and enables the rapid identification of both the correct parent ion mass and the correct parent formula with minimal expert intervention.ConclusionOur method reliably identifies the correct parent formula even when the mass information is ambiguous. Furthermore, should parent formula identification be successful, the majority of associated fragment formulae can also be correctly identified. Our method can also identify the parent ion and its associated fragments in EI-MS spectra where the identity of the parent ion is unclear due to low quantities and overlapping compounds. Finally, our method does not inherently require empirical fitting of parameters or statistical learning, meaning it is easy to implement and extend upon.Scientific contributionDeveloped, implemented and tested new metrics for assessing plausibility of candidate molecular formulae obtained from HR-MS data.

Combining data and theory for derivable scientific discovery with AI-Descartes

Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

An available strategy for elemental composition determination of organic impurities in commercial preparations based on accurate mass and peak ratio of isotopic fine structures (IFSs) by dual mode combined-FT-ICR-MS and fraction collection technology

A strategy to determine the elemental composition of organic impurities in commercial preparations was established by combining high-performance liquid chromatography (HPLC)-Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and fraction collector with direct infusion-FT-ICR-MS (DI-FT-ICR-MS). Under HPLC-FT-ICR-MS mode, all impurities in model sample were chromatographically separated and collected by fraction collector according to their retention time. The accurate mass of each impurity and their candidate formulae under 1 ppm mass tolerance were calculated. Subsequently, theoretical isotopic fine structures (IFSs) of the candidate formulae were generated. Furthermore, the collected fractions were tested and the experimental IFSs of impurities were acquired by DI-FT-ICR-MS mode. Finally, the elemental composition of all impurities was decisively determined by comparing the experimental and theoretical IFSs. Our results demonstrate that the combined strategy is effective in separating impurities and acquiring accurate mass by HPLC-FT-ICR-MS, obtaining the appropriate samples by fraction collection technology for DI-FT-ICR-MS, and acquiring the IFSs of impurities by DI-FT-ICR-MS. It could be concluded that the strategy is an accurate and standard independent approach to determine the elemental composition of organic impurities in commercial preparations.

Novel chewable colon targeted tablets of bumadizone calcium for treatment of ulcerative colitis: Formulation and optimization

The aim of the present study was the formulation of a novel chewable tablet containing the non-steroidal anti-inflammatory bumadizone calcium (BZ) to deliver the drug to the colon for the local treatment of ulcerative colitis. Colon targeted granules were prepared following 32 full factorial design. The effect of two independent variables, namely, polymer type (Eudragit ® S100, Eudragit ® L100, and a mixture of both in the ratio of 4:1) and drug to polymer ratio (1:1, 1:3& 1:5) on the % of BZ released for 12 h was studied. In order to produce chewability, candidate formulae were then mixed with different amount of maize starch and mannitol, and compressed into tablets. F11 tablets(composed of drug: Eudragit® S100 in the ratio of 1:3, 250 mg mannitol and 50 mg maize starch with a desirability of 0.925) achieved the required release profile i.e: lowest release before target area (pH 1.2 & 6.8) reaching only 11.00% at the end of the fourth hour, and 100.27% after 12 h (pH7.4). Histopathological studies results declared clearly the ability of the chewable colon targeted tablets F11 to locally treat acetic acid induced colitis. Furthermore, the measurements of myeloperoxidase enzyme activities in colon specimens showed that F11 achieved a significantly lower levels in comparison to both untreated group and group that received the marketed tablets (p<0.05).

Bumadizone calcium dihydrate microspheres compressed tablets for colon targeting: formulation, optimization and in vivo evaluation in rabbits

The objective of this study was the development of a colon-targeted microspheres which were compressed into tablets containing the non-steroidal anti-inflammatory bumadizone calcium dihydrate. A 32 full factorial design was adopted for the evaluation of the prepared microspheres. The effect of two independent variables namely polymer type (Eudragit RS100, ethyl cellulose and cellulose acetate butyrate), and drug: polymer ratio (1:1, 9:1 and 18:1) was studied on the entrapment efficiency and in vitro drug release for 12 h. Colon targeting aims to minimize the release of the drug off target area (pH 1.2 and 6.8) and to maximize the release of the drug in target area (pH 7.4). Candidate formulae were compressed into core tablets and colon targeting was achieved using the enzyme-dependent polymer (pectin) as coat in three different concentrations 50, 75 and 90%. Candidate formula F15 (microspheres prepared using BDZ:CAB in a ratio of 18:1 and compressed into tablets using 50% pectin and 50% Avicel in the coat) was able to adequately modulate drug release avoiding drug release in the gastric ambient, and reaching the colonic targeting where 99.7% release was achieved within 12 h following zero-order model. In vivo studies showed that F15 achieved significant decrease in myeloperoxidase activity and inflammation with delayed Tmax (4 h) and lower Cmax (2700 ng/ml) when compared to marketed product.

Use of soft and hard ionization techniques for elucidation of unknown compounds by gas chromatography/time‐of‐flight mass spectrometry

Investigation of trace-level non-target compounds by gas chromatography/mass spectrometry (GC/MS) often is a challenging task that requires powerful software tools to detect the unknown components, to obtain the deconvoluted mass spectra, and to interpret the data if no acceptable library match is obtained. In this paper, the complementary use of electron ionization (EI) and chemical ionization (CI) is investigated in combination with GC/time-of-flight (TOF) MS for the elucidation of organic non-target (micro)contaminants in water samples. Based on accurate mass measurement of the molecular and fragment ions from the TOF MS, empirical formulae were calculated. Isotopic patterns, carbon number prediction filter and nitrogen rule were used to reduce the number of possible formulae. The candidate formulae were searched in databases to find possible chemical structures. Selection from possible structure candidates was achieved using information on substructures and observed neutral losses derived from the fragment ions. Four typical examples (bifenazate, boscalid, epoxiconazole, and fenhexamid) are used to illustrate the methodology applied and the various difficulties encountered in this process. Our results indicate that elucidation of unknowns cannot be achieved by following a standardized procedure, as both expertise and creativity are necessary in the process.

A new approach to aid the characterisation and identification of metabolites of a model drug; partial isotope enrichment combined with novel formula elucidation software

This work describes the identification of 'isotopically enriched' metabolites of 4-cyanoaniline using the unique features of the software package 'Spectral Simplicity'. The software is capable of creating the theoretical mass spectra for partially isotope-enriched compounds, and subsequently performing an elemental composition analysis to give the elemental formula for the 'isotopically enriched' metabolite. A novel mass spectral correlation method, called 'FuzzyFit', was employed. 'FuzzyFit' utilises the expected experimental distribution of errors in both mass accuracy and isotope pattern and enables discrimination between statistically probable and improbable candidate formulae. The software correctly determined the molecular formulae of ten previously described metabolites of 4-cyanoaniline confirming the technique of partial isotope enrichment can produce results analogous to standard methodologies. Six previously unknown species were also identified, based on the presence of the unique 'designer' isotope ratio. Three of the unknowns were tentatively identified as N-acetylglutamine, O-methyl-N acetylglucuronide and a putative fatty acid conjugate. The discovery of a significant number of unknown species of a model drug with a comprehensive history of investigation highlights the potential for enhancement to the analytical process by the use of 'designer' isotope ratio compounds. The 'FuzzyFit' methodology significantly aided the elucidation of candidate formulae, by provision of a vastly simplified candidate formula data set.

Choice of Cost-Estimation Functions Based on Statistical Quality Criteria and Technical Coherence

This paper studies the problem of choosing cost estimation functions by mixing statistical regression criteria and technical coherence. The parametric cost estimation method which looks for functional relationship between cost driver variables and the product cost is particularly well adapted to early economic evaluation during the design phase; it is simple to implement, efficient, and reactive enough to provide a powerful guideline for the designer. These cost estimation relationships (CER) are generally computed using linear or nonlinear regression algorithms. However, the problem is to identify and to choose the best CER among several candidate formulae which have been developed. In many cases, the statistical regression quality and estimation criteria are not sufficient. It is also necessary to consider the technical coherence of the CER as defined by the experts in the application domain. Therefore, an additional problem is to make these different points of view consistent. In this paper, the authors adopt a weighted multicriteria decision approach. The characteristics of the different quality criteria are described, then three practical selection methods are presented. All these methods measure the general quality of CERs, taking into account both technical and statistical points of view. The methods are based on a measure of quality using a weighted sum of normalised criteria, a weighted ranking method, and an original use of a similarity measure in the criteria space. These methods are then tested and compared using a real case.

Determination of molecular formulae from low-resolution mass spectral data by matching experimental and calculated isotope patterns of logical sets of daughter ion candidates

The determination of molecular formulae from low-resolution mass spectral data is described. The data are handled by a microcomputer program which generates not only candidate molecular formulae but also logical sets of candidate formulae of fragments corresponding to several detected ions in the same mass spectrum, and tests how well the calculated isotope patterns of these sets match the corresponding experimental isotope patterns. The sets of fragment candidates are formed so that the sum of the elemental compositions in the sets is logical and either equal or close to the elemental composition of the current candidate for the molecular formula. The generated molecular candidate which gives the best matching fragment set and the best total match represents the most probable elemental composition of the unknown compound. Some structural information is obtained simultaneously. Comparison of the results obtained with the new algorithm with those obtained with previous microcomputer programs shows that both performance and reliability are improved considerably.

Programs for molecular formula determination employing data from unit resolution MS/MS spectra

Direct determination of molecular formulae cannot be accomplished using unit resolution molecular weight data, since a given molecular weight may be consistent with many formulae. Several software tools have been developed to facilitate the determination of molecular formulae using unit resolution MS and MS/MS data. MS and MS/MS isotopic ratio data and identified substructures are used to develop constraints on the elemental composition. The composition data and molecular weight of the compound are then entered as input to a molecular formula generator program which generates all possible formulae consistent with these constraints. In this manner, the number of candidate formulae is greatly reduced.

On the quantization of quadratic momenta

AbstractUsing geometric quantization, and accepting the quantum Hamiltonian of previous authors, we propose some candidate formulae for the quantum operator of an observable which is a quadratic form in the momenta.