Antony Williams

Publications

• 6.63

  Impact points

  Towards a gold standard: regarding quality in public domain chemistry databases and approaches to improving the situation.

  Antony J Williams, Sean Ekins, Valery Tkachenko

  Drug discovery today. 03/2012;

  In recent years there has been a dramatic increase in the number of freely accessible online databases serving the chemistry community. The internet provides chemistry data that can be used for data-mining, for computer models, and integration into systems to aid drug discovery. There is however a r... [more] In recent years there has been a dramatic increase in the number of freely accessible online databases serving the chemistry community. The internet provides chemistry data that can be used for data-mining, for computer models, and integration into systems to aid drug discovery. There is however a responsibility to ensure that the data are high quality to ensure that time is not wasted in erroneous searches, that models are underpinned by accurate data and that improved discoverability of online resources is not marred by incorrect data. In this article we provide an overview of some of the experiences of the authors using online chemical compound databases, critique the approaches taken to assemble data and we suggest approaches to deliver definitive reference data sources.

• Blind trials of Computer-Assisted Structure Elucidation software.

  Arvin Moser, Mikhail E Elyashberg, Antony J Williams, Kirill A Blinov, Joseph C Dimartino

  Journal of cheminformatics. 02/2012; 4(1):5.

  ABSTRACT: BACKGROUND: One of the largest challenges in chemistry today remains that of efficiently mining through vast amounts of data in order to elucidate the chemical structure for an unknown compound. The elucidated candidate compound must be fully consistent with the data and any other competin... [more] ABSTRACT: BACKGROUND: One of the largest challenges in chemistry today remains that of efficiently mining through vast amounts of data in order to elucidate the chemical structure for an unknown compound. The elucidated candidate compound must be fully consistent with the data and any other competing candidates efficiently eliminated without doubt by using additional data if necessary. It has become increasingly necessary to incorporate an in silico structure generation and verification tool to facilitate this elucidation process. An effective structure elucidation software technology aims to mimic the skills of a human in interpreting the complex nature of spectral data while producing a solution within a reasonable amount of time. This type of software is known as computer-assisted structure elucidation or CASE software. A systematic trial of the ACD/Structure Elucidator CASE software was conducted over an extended period of time by analysing a set of single and double-blind trials submitted by a global audience of scientists. The purpose of the blind trials was to reduce subjective bias. Double-blind trials comprised of data where the candidate compound was unknown to both the submitting scientist and the analyst. The level of expertise of the submitting scientist ranged from novice to expert structure elucidation specialists with experience in pharmaceutical, industrial, government and academic environments. RESULTS: Beginning in 2003, and for the following nine years, the algorithms and software technology contained within ACD/Structure Elucidator have been tested against 112 data sets; many of these were unique challenges. Of these challenges 9% were double-blind trials. The results of eighteen of the single-blind trials were investigated in detail and included problems of a diverse nature with many of the specific challenges associated with algorithmic structure elucidation such as deficiency in protons, structure symmetry, a large number of heteroatoms and poor quality spectral data. CONCLUSION: When applied to a complex set of blind trials, ACD/Structure Elucidator was shown to be a very useful tool in advancing the computer's contribution to elucidating a candidate structure from a set of spectral data (NMR and MS) for an unknown. The synergistic interaction between humans and computers can be highly beneficial in terms of less biased approaches to elucidation as well as dramatic improvements in speed and throughput. In those cases where multiple candidate structures exist, ACD/Structure Elucidator is equipped to validate the correct structure and eliminate inconsistent candidates. Full elucidation can generally be performed in less than two hours; this includes the average spectral data processing time and data input.
• 1.61

  Impact points

  Elucidating 'undecipherable' chemical structures using computer-assisted structure elucidation approaches.

  Mikhail Elyashberg, Kirill Blinov, Sergey Molodtsov, Antony Williams

  Magnetic resonance in chemistry : MRC. 01/2012; 50(1):22-7.

  Structure elucidation using 2D NMR data and application of traditional methods of structure elucidation are known to fail for certain problems. In this work, it is shown that computer-assisted structure elucidation methods are capable of solving such problems. We conclude that it is now impossible t... [more] Structure elucidation using 2D NMR data and application of traditional methods of structure elucidation are known to fail for certain problems. In this work, it is shown that computer-assisted structure elucidation methods are capable of solving such problems. We conclude that it is now impossible to evaluate the capabilities of novel NMR experimental techniques in isolation from expert systems developed for processing fuzzy, incomplete and contradictory information obtained from 2D NMR spectra. Copyright © 2012 John Wiley & Sons, Ltd.
• 3.39

  Impact points

  Identification of "known unknowns" utilizing accurate mass data and ChemSpider.

  James L Little, Antony J Williams, Alexey Pshenichnov, Valery Tkachenko

  Journal of the American Society for Mass Spectrometry. 11/2011; 23(1):179-85.

  In many cases, an unknown to an investigator is actually known in the chemical literature, a reference database, or an internet resource. We refer to these types of compounds as "known unknowns." ChemSpider is a very valuable internet database of known compounds useful in the identificatio... [more] In many cases, an unknown to an investigator is actually known in the chemical literature, a reference database, or an internet resource. We refer to these types of compounds as "known unknowns." ChemSpider is a very valuable internet database of known compounds useful in the identification of these types of compounds in commercial, environmental, forensic, and natural product samples. The database contains over 26 million entries from hundreds of data sources and is provided as a free resource to the community. Accurate mass mass spectrometry data is used to query the database by either elemental composition or a monoisotopic mass. Searching by elemental composition is the preferred approach. However, it is often difficult to determine a unique elemental composition for compounds with molecular weights greater than 600 Da. In these cases, searching by the monoisotopic mass is advantageous. In either case, the search results are refined by sorting the number of references associated with each compound in descending order. This raises the most useful candidates to the top of the list for further evaluation. These approaches were shown to be successful in identifying "known unknowns" noted in our laboratory and for compounds of interest to others.

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• 6.63

  Impact points

  Mobile apps for chemistry in the world of drug discovery.

  Antony J Williams, Sean Ekins, Alex M Clark, J James Jack, Richard L Apodaca

  Drug discovery today. 09/2011; 16(21-22):928-39.

  Mobile hardware and software technology continues to evolve very rapidly and presents drug discovery scientists with new platforms for accessing data and performing data analysis. Smartphones and tablet computers can now be used to perform many of the operations previously addressed by laptops or de... [more] Mobile hardware and software technology continues to evolve very rapidly and presents drug discovery scientists with new platforms for accessing data and performing data analysis. Smartphones and tablet computers can now be used to perform many of the operations previously addressed by laptops or desktop computers. Although the smaller screen sizes and requirements for touch-screen manipulation can present user-interface design challenges, especially with chemistry-related applications, these limitations are driving innovative solutions. In this early review of the topic, we collectively present our diverse experiences as software developer, chemistry database expert and naïve user, in terms of what mobile platforms could provide to the drug discovery chemist in the way of applications in the future as this disruptive technology takes off.

• ONS Open Melting Point Collection

  Jean-Claude Bradley, Andrew Lang, Antony Williams, Evan Curtin

  Nature Precedings. 08/2011;
• 6.63

  Impact points

  A quality alert and call for improved curation of public chemistry databases.

  Antony J Williams, Sean Ekins

  Drug discovery today. 07/2011; 16(17-18):747-50.

  In the last ten years, public online databases have rapidly become trusted valuable resources upon which researchers rely for their chemical structures and data for use in cheminformatics, bioinformatics, systems biology, translational medicine and now drug repositioning or repurposing efforts. Thei... [more] In the last ten years, public online databases have rapidly become trusted valuable resources upon which researchers rely for their chemical structures and data for use in cheminformatics, bioinformatics, systems biology, translational medicine and now drug repositioning or repurposing efforts. Their utility depends on the quality of the underlying molecular structures used. Unfortunately, the quality of much of the chemical structure-based data introduced to the public domain is poor. As an example we describe some of the errors found in the recently released NIH Chemical Genomics Center 'NPC browser' database as an example. There is an urgent need for government funded data curation to improve the quality of internet chemistry and to limit the proliferation of errors and wasted efforts.
• 3.84

  Impact points

  Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.

  Iurii Sushko, Sergii Novotarskyi, Robert Körner, Anil Kumar Pandey, Matthias Rupp, Wolfram Teetz, Stefan Brandmaier, Ahmed Abdelaziz, Volodymyr V Prokopenko, Vsevolod Y Tanchuk, [......], Dmitriy Chekmarev, Artem Cherkasov, Joao Aires-de-Sousa, Qing-You Zhang, Andreas Bender, Florian Nigsch, Luc Patiny, Antony Williams, Valery Tkachenko, Igor V Tetko

  Journal of computer-aided molecular design. 06/2011; 25(6):533-54.

  The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains ... [more] The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.

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• 3.28

  Impact points

  Finding promiscuous old drugs for new uses.

  Sean Ekins, Antony J Williams

  Pharmaceutical research. 05/2011; 28(8):1785-91.

  From research published in the last six years we have identified 34 studies that have screened libraries of FDA-approved drugs against various whole cell or target assays. These studies have each identified one or more compounds with a suggested new bioactivity that had not been described previously... [more] From research published in the last six years we have identified 34 studies that have screened libraries of FDA-approved drugs against various whole cell or target assays. These studies have each identified one or more compounds with a suggested new bioactivity that had not been described previously. We now show that 13 of these drugs were active against more than one additional disease, thereby suggesting a degree of promiscuity. We also show that following compilation of all the studies, 109 molecules were identified by screening in vitro. These molecules appear to be statistically more hydrophobic with a higher molecular weight and AlogP than orphan-designated products with at least one marketing approval for a common disease indication or one marketing approval for a rare disease from the FDA's rare disease research database. Capturing these in vitro data on old drugs for new uses will be important for potential reuse and analysis by others to repurpose or reposition these or other existing drugs. We have created databases which can be searched by the public and envisage that these can be updated as more studies are published.

• Smart Phones, a Powerful Tool in the Chemistry Classroom

  Antony J. Williams, Harry E. Pence

  Journal of Chemical Education. 04/2011; 88(6):110414085023061.

  Cell phones, especially “smart phones”, seem to have become ubiquitous. Actually, it is misleading to call many of these devices phones, as they are actually a portable and powerful computer that can be very valuable in the chemistry classroom. Currently, there are three major ways in which smart ph... [more] Cell phones, especially “smart phones”, seem to have become ubiquitous. Actually, it is misleading to call many of these devices phones, as they are actually a portable and powerful computer that can be very valuable in the chemistry classroom. Currently, there are three major ways in which smart phones can be used for education. Smart phones include a Web browser, which gives access to the wealth of material on the World Wide Web (WWW); inexpensive applications (commonly called apps) expand this usefulness even further; and two-dimensional barcode labels can be used to create “smart objects”. Taken together, these capabilities are creating a world of mobile computing that may have an impact on society, including chemical education, that may be even greater than the changes brought about by the personal computer.
• 6.63

  Impact points

  In silico repositioning of approved drugs for rare and neglected diseases.

  Sean Ekins, Antony J Williams, Matthew D Krasowski, Joel S Freundlich

  Drug discovery today. 03/2011; 16(7-8):298-310.

  One approach to speed up drug discovery is to examine new uses for existing approved drugs, so-called 'drug repositioning' or 'drug repurposing', which has become increasingly popular in recent years. Analysis of the literature reveals many examples of US Food and Drug Administration... [more] One approach to speed up drug discovery is to examine new uses for existing approved drugs, so-called 'drug repositioning' or 'drug repurposing', which has become increasingly popular in recent years. Analysis of the literature reveals many examples of US Food and Drug Administration-approved drugs that are active against multiple targets (also termed promiscuity) that can also be used to therapeutic advantage for repositioning for other neglected and rare diseases. Using proof-of-principle examples, we suggest here that with current in silico technologies and databases of the structures and biological activities of chemical compounds (drugs) and related data, as well as close integration with in vitro screening data, improved opportunities for drug repurposing will emerge for neglected or rare/orphan diseases.
• 3.74

  Impact points

  A predictive ligand-based Bayesian model for human drug-induced liver injury.

  Sean Ekins, Antony J Williams, Jinghai J Xu

  Drug metabolism and disposition: the biological fate of chemicals. 12/2010; 38(12):2302-8.

  Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both preapproval and postapproval stages. There has been increased interest in developing predictive in vivo, in vitro, and in silico models to identify compounds that cause idiosyncratic hepatotoxi... [more] Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both preapproval and postapproval stages. There has been increased interest in developing predictive in vivo, in vitro, and in silico models to identify compounds that cause idiosyncratic hepatotoxicity. In the current study, we applied machine learning, a Bayesian modeling method with extended connectivity fingerprints and other interpretable descriptors. The model that was developed and internally validated (using a training set of 295 compounds) was then applied to a large test set relative to the training set (237 compounds) for external validation. The resulting concordance of 60%, sensitivity of 56%, and specificity of 67% were comparable to results for internal validation. The Bayesian model with extended connectivity functional class fingerprints of maximum diameter 6 (ECFC_6) and interpretable descriptors suggested several substructures that are chemically reactive and may also be important for DILI-causing compounds, e.g., ketones, diols, and α-methyl styrene type structures. Using Smiles Arbitrary Target Specification (SMARTS) filters published by several pharmaceutical companies, we evaluated whether such reactive substructures could be readily detected by any of the published filters. It was apparent that the most stringent filters used in this study, such as the Abbott alerts, which captures thiol traps and other compounds, may be of use in identifying DILI-causing compounds (sensitivity 67%). A significant outcome of the present study is that we provide predictions for many compounds that cause DILI by using the knowledge we have available from previous studies. These computational models may represent cost-effective selection criteria before in vitro or in vivo experimental studies.
• 6.63

  Impact points

  When pharmaceutical companies publish large datasets: an abundance of riches or fool's gold?

  Sean Ekins, Antony J Williams

  Drug discovery today. 10/2010; 15(19-20):812-5.

  The recent announcement that GlaxoSmithKline have released a huge tranche of whole-cell malaria screening data to the public domain, accompanied by a corresponding publication, raises some issues for consideration before this exemplar instance becomes a trend. We have examined the data from a high l... [more] The recent announcement that GlaxoSmithKline have released a huge tranche of whole-cell malaria screening data to the public domain, accompanied by a corresponding publication, raises some issues for consideration before this exemplar instance becomes a trend. We have examined the data from a high level, by studying the molecular properties, and consider the various alerts presently in use by major pharma companies. We not only acknowledge the potential value of such data but also raise the issue of the actual value of such datasets released into the public domain. We also suggest approaches that could enhance the value of such datasets to the community and theoretically offer an immediate benefit to the search for leads for other neglected diseases.
• 9.20

  Impact points

  Structural revisions of natural products by Computer-Assisted Structure Elucidation (CASE) systems.

  Mikhail Elyashberg, Antony J Williams, Kirill Blinov

  Natural product reports. 09/2010; 27(9):1296-328.

• Meta-analysis of molecular property patterns and filtering of public datasets of antimalarial “hits” and drugs

  Sean Ekins, Antony J. Williams

  MedChemComm. 09/2010; 1(5):325.

• ChemSpider: An Online Chemical Information Resource

  Harry E. Pence, Antony Williams

  Journal of Chemical Education. 08/2010;

  ChemSpider is a free, online chemical database offering access to physical and chemical properties, molecular structure, spectral data, synthetic methods, safety information, and nomenclature for almost 25 million unique chemical compounds sourced and linked to almost 400 separate data sources on th... [more] ChemSpider is a free, online chemical database offering access to physical and chemical properties, molecular structure, spectral data, synthetic methods, safety information, and nomenclature for almost 25 million unique chemical compounds sourced and linked to almost 400 separate data sources on the Web. ChemSpider is quickly becoming the primary chemistry Internet portal and it can be very useful for both chemical teaching and research.
• 3.28

  Impact points

  Reaching out to collaborators: crowdsourcing for pharmaceutical research.

  Sean Ekins, Antony J Williams

  Pharmaceutical research. 03/2010; 27(3):393-5.
• 1.61

  Impact points

  Empirical and DFT GIAO quantum-mechanical methods of (13)C chemical shifts prediction: competitors or collaborators?

  Mikhail Elyashberg, Kirill Blinov, Yegor Smurnyy, Tatiana Churanova, Antony Williams

  Magnetic resonance in chemistry : MRC. 03/2010; 48(3):219-29.

  The accuracy of (13)C chemical shift prediction by both DFT GIAO quantum-mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM-calculated chemical shifts were published in the literature. For these structures, (13)C chemical shifts were calculated usin... [more] The accuracy of (13)C chemical shift prediction by both DFT GIAO quantum-mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM-calculated chemical shifts were published in the literature. For these structures, (13)C chemical shifts were calculated using HOSE code and neural network (NN) algorithms developed within our laboratory. In total, 2531 chemical shifts were analyzed and statistically processed. It has been shown that, in general, QM methods are capable of providing similar but inferior accuracy to the empirical approaches, but quite frequently they give larger mean average error values. For the structural set examined in this work, the following mean absolute errors (MAEs) were found: MAE(HOSE) = 1.58 ppm, MAE(NN) = 1.91 ppm and MAE(QM) = 3.29 ppm. A strategy of combined application of both the empirical and DFT GIAO approaches is suggested. The strategy could provide a synergistic effect if the advantages intrinsic to each method are exploited.
• 6.34

  Impact points

  [In Process Citation]

  Sean Ekins, Antony J Williams

  Lab on a chip. 01/2010; 10(1):13-22.

  Web-based technologies coupled with a drive for improved communication between scientists have resulted in the proliferation of scientific opinion, data and knowledge at an ever-increasing rate. The increasing array of chemistry-related computer-based resources now available provides chemists with a... [more] Web-based technologies coupled with a drive for improved communication between scientists have resulted in the proliferation of scientific opinion, data and knowledge at an ever-increasing rate. The increasing array of chemistry-related computer-based resources now available provides chemists with a direct path to the discovery of information, once previously accessed via library services and limited to commercial and costly resources. We propose that preclinical absorption, distribution, metabolism, excretion and toxicity data as well as pharmacokinetic properties from studies published in the literature (which use animal or human tissues in vitro or from in vivo studies) are precompetitive in nature and should be freely available on the web. This could be made possible by curating the literature and patents, data donations from pharmaceutical companies and by expanding the currently freely available ChemSpider database of over 21 million molecules with physicochemical properties. This will require linkage to PubMed, PubChem and Wikipedia as well as other frequently used public databases that are currently used, mining the full text publications to extract the pertinent experimental data. These data will need to be extracted using automated and manual methods, cleaned and then published to the ChemSpider or other database such that it will be freely available to the biomedical research and clinical communities. The value of the data being accessible will improve development of drug molecules with good ADME/Tox properties, facilitate computational model building for these properties and enable researchers to not repeat the failures of past drug discovery studies.

• Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining.

  Kristina M Hettne, Antony J Williams, Erik M van Mulligen, Jos Kleinjans, Valery Tkachenko, Jan A Kors

  Journal of cheminformatics. 01/2010; 2(1):4.

  :