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A Shifting Paradigm of a Chemistry Methods Approach: Cheminformatics
Published in Alexander V. Vakhrushev, Omari V. Mukbaniani, Heru Susanto, Chemical Technology and Informatics in Chemistry with Applications, 2019
Heru Susanto, Ching Kang Chen, Teuku Beuna Bardant, Arief Amier Rahman Setiawan
Consequently, cheminformatics is related to the application of computational methods to solve chemical problems, with special emphasis on manipulation chemical structural information. As mentioned previously, the term was introduced by Frank K. Brown in 1998 but there has been no universal agreement about the correct term for this field. Cheminformatics is also known as chemoinformatics, chemioinformatics, and chemical informatics. Many of the techniques used in cheminformatics are actually rather well established, be the result of years if not decades of research in academic, government, and industrial laboratories. The main reason for its inception can be traced to the need for dealing with large amounts of data generated by the new approach to drug discovery, such as high-throughput screening and combinatorial chemistry. An increase in computer power, especially for desktop engine, has provided the resources to handle this flood. Many other aspects of drug discovery make use of the techniques of cheminformatics, from design of new synthetic route by searching a database of reactions known through development of computational models such as quantitative structure–activity relationship (QSAR), which associates something that is observed through the biological activity of chemical structures through the use of molecular docking program to predict the three-dimensional (3-D) structure protein–ligand complexes and then choose from a set of compounds for screening. One common characteristic is that this method of cheminformatics must be applicable to a large number of molecules.
Cheminformatics—The promising future: Managing change of approach through ICT emerging technology
Published in A. K. Haghi, Lionello Pogliani, Devrim Balköse, Omari V. Mukbaniani, Andrew G. Mercader, Applied Chemistry and Chemical Engineering, 2017
Moreover, ICT applications in the field of molecular science have spawned the field of Biotechnology. Biotechnology is a branch of science that studies the use of living organisms (bacteria, fungi, viruses, etc.) as well as products from living organisms (enzyme, alcohol) in the production process to produce goods and services. This study is increasingly important, because the development has been encouraging and impactful on the field of medicine, pharmacy, environment, and others. These fields include the application of methods of mathematics, statistics, and informatics to answer biological problems, especially with the use of DNA and amino acid sequences as well as the information related to it. Insistence of the need to collect, store, and analyze biological data from a database of DNA, RNA, or protein acts as a spur to the development of bioinformatics. There are nine branches of biotechnology, and one of them is cheminformatics. Cheminformatics is one of biotechnology’s disciplines that is a combination of chemical synthesis, biological filtering, and data mining, and is used for drug discovery and development.
On Error Measures for Validation and Uncertainty Estimation of Predictive QSAR Models
Published in Agnieszka Gajewicz, Tomasz Puzyn, Computational Nanotoxicology, 2019
Supratik Kar, Kunal Roy, Jerzy Leszczynski
The term “cheminformatics” is an applied field of chemistry involving informatics and defines the implication of computational resources for answering unexplained problems arising in chemical, pharmaceutical, food, agrochemicals, and allied industries. Cheminformatics has transformed pharmaceutical, chemical, and material research faster economically and efficiently in the last two decades. Software tools under cheminformatics provide diverse functionalities, like molecular modeling through QSAR and machine learning techniques, virtual screening, read-across techniques, pharmacophore, docking, and molecular dynamics packages, which are most often user-friendly tools involving the graphical user interface (GUI) [53]. Software is classified under two distinct groups: commercial and open access or open-source ones. Commercial ones are powerful and well developed under a strong industrial background but expensive, which restricts their usage to industry and research laboratories. On the other hand, open-source ones are freely available, that is, open access, which makes them easy to use, learn, and apply by beginners and connoisseurs alike. To support the scientific community in resolving the diverse problems arising in miscellaneous areas of science, it is critical that cheminformatics resources be openly accessible. A good number of resources are available in the present times from different research laboratories, universities, and industries, as well as from government funding organizations. To limit the discussion, we have reported open-source software that are directly or indirectly required for QSAR model development only in Table 10.5.
A perspective on the development of gas-phase chemical mechanisms for Eulerian air quality models
Published in Journal of the Air & Waste Management Association, 2020
William R. Stockwell, Emily Saunders, Wendy S. Goliff, Rosa M. Fitzgerald
We suggest that some attention to the possibility that there may be alternatives to current protocols to create chemical modules for air quality modeling. Here we are asking the unorthodox question: Does a mechanism, in the traditional sense consisting of reactions with their reactants, products (with yields) and rate coefficients, need to be created to have a credible chemical module to simulate O3, PM and other atmospheric constituents of regulatory interest? We suggest that an answer might be found in cheminformatics and machine learning (e.g. Leach and Gillet 2007; Wang, Men, and Lu 2008). Cheminformatics (also known as Chemoinformatics) is a field that applies information science, data mining and similar fields to chemistry. Perhaps the first problem should be to investigate the possibility of creating a chemical module that makes calculations for higher molecular weight compounds that are based on SAR data directly rather than by estimating explicitly the reactants, products, product yields and rate coefficients of unmeasured reactions.