Basic primitives for molecular diagram sketching

Clark, Alex M.

doi:10.1186/1758-2946-2-8

Cited by 20 publications

(16 citation statements)

References 24 publications

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“…These molecules were sketched using the mobile application Mobile Molecular DataSheet (Molecular Materials Informatics, Montreal, CA) (41, 42) to create sdf files which were used in Discovery Studio for prediction with the Bayesian models.…”

Section: Methodsmentioning

confidence: 99%

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium Tuberculosis Drug Discovery

et al. 2013

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Purpose Tuberculosis treatments need to be shorter and overcome drug resistance. Our previous large scale phenotypic high-throughput screening against Mycobacterium tuberculosis (Mtb) has identified 737 active compounds and thousands that are inactive. We have used this data for building computational models as an approach to minimize the number of compounds tested. Methods A cheminformatics clustering approach followed by Bayesian machine learning models (based on publicly available Mtb screening data) was used to illustrate that application of these models for screening set selections can enrich the hit rate. Results In order to explore chemical diversity around active cluster scaffolds of the dose-response hits obtained from our previous Mtb screens a set of 1924 commercially available molecules have been selected and evaluated for antitubercular activity and cytotoxicity using Vero, THP-1 and HepG2 cell lines with 4.3%, 4.2% and 2.7% hit rates, respectively. We demonstrate that models incorporating antitubercular and cytotoxicity data in Vero cells can significantly enrich the selection of non-toxic actives compared to random selection. Across all cell lines, the Molecular Libraries Small Molecule Repository (MLSMR) and cytotoxicity model identified ~10% of the hits in the top 1% screened (>10 fold enrichment). We also showed that seven out of nine Mtb active compounds from different academic published studies and eight out of eleven Mtb active compounds from a pharmaceutical screen (GSK) would have been identified by these Bayesian models. Conclusion Combining clustering and Bayesian models represents a useful strategy for compound prioritization and hit-to lead optimization of antitubercular agents.

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Section: Methodsmentioning

confidence: 99%

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium Tuberculosis Drug Discovery

et al. 2013

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“…Next steps include enhancement of the user interface, specifically moving towards compliance with web-based molecular drawing standards [44,45] for building tools and molecule images, and a comprehensive update and extension of the parameter database. The extension will make parameters available for the newest TraPPE -UA models, TraPPE -EH, TraPPE -pol and TraPPE-CG models.…”

Section: Next Stepsmentioning

confidence: 99%

An online parameter and property database for the TraPPE force field

Eggimann

Sunnarborg

Stern

et al. 2013

Molecular Simulation

135

121

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The transferable potentials for phase equilibria (TraPPE) force field aims to be accurate, computationally efficient and applicable to a wide range of chemical compounds, state points and thermophysical properties. When new users wish to implement TraPPE models into their chosen simulation program, they face several obstacles: the TraPPE models are dispersed over many separate publications and misinterpretations of the primary literature are possible; the TraPPE force field makes specific choices for standard conventions that may require non-trivial code modifications for some simulation software. Therefore, the TraPPE developers report here a resource website and online searchable parameter and property database designed to provide new and experienced users with tools for successful implementation and validation

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“…Database users obviously require knowledge of molecular structure, which should be drawn using small, reproducible fragments known as basic primitives [71]. Chemistry students require basic training in molecular editors, in particular if chemistry textbooks in primary and secondary schools do not represent molecular structures built from basic primitives [15].…”

Section: Database Search Based On Molecular Structurementioning

confidence: 99%

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

Minkiewicz

Darewicz

Iwaniak

et al. 2016

IJMS

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Internet databases of small molecules, their enzymatic reactions, and metabolism have emerged as useful tools in food science. Database searching is also introduced as part of chemistry or enzymology courses for food technology students. Such resources support the search for information about single compounds and facilitate the introduction of secondary analyses of large datasets. Information can be retrieved from databases by searching for the compound name or structure, annotating with the help of chemical codes or drawn using molecule editing software. Data mining options may be enhanced by navigating through a network of links and cross-links between databases. Exemplary databases reviewed in this article belong to two classes: tools concerning small molecules (including general and specialized databases annotating food components) and tools annotating enzymes and metabolism. Some problems associated with database application are also discussed. Data summarized in computer databases may be used for calculation of daily intake of bioactive compounds, prediction of metabolism of food components, and their biological activity as well as for prediction of interactions between food component and drugs.

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Basic primitives for molecular diagram sketching

Cited by 20 publications

References 24 publications

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium Tuberculosis Drug Discovery

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium Tuberculosis Drug Discovery

An online parameter and property database for the TraPPE force field

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

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