In silico environmental chemical science: properties and processes from statistical and computational modelling Paul G. Tratnyek, * a Eric J. Bylaska b and Eric J. Weber c Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials. Environmental impact Computational models are used in all aspects of environmental science, including assessment of the environmental fate and effects of chemical substances. In these applications, the prediction of missing property data is the main motivation, but prediction of pathways (e.g., products from contaminant degradation) is becoming feasible and should soon be available for use in research and regulation. The degree to which substance impact assessment can be done in silico will continue to increase, but incorporation of environmental factors (i.e., conditions) is a continuing challenge. Introduction Progress in environmental chemical science is limited by the availability of data even more than most domains of science. The complexity of environmental conditions, combined with the diversity of substances (chemical, biological, and material) that are of environmental concern, mean that direct measure- ments will never be sufficient to meet the data needs of envi- ronmental scientists or regulators. Therefore, predicting chemical properties is a long-standing challenge that has received extensive study for many applications (chemical engineering, green chemistry, environmental chemistry, toxi- cology, pharmacology, etc.). Fortunately, advances in computer- based methods are making it increasingly feasible to estimate substance properties, evaluate their fate-determining processes, and predict their effects. These methods and their applications comprise the domain we refer to herein as “in silico environ- mental chemical science”. The scope of this domain includes theoretical and statistical methods for calculating substance properties, fate, and effects. The theoretical and statistical methods used to calculate substance properties are rooted in very different disciplines, so the recent trend toward combining these approaches poses some novel challenges for developers and users of these models. One goal of this perspective is to show how these challenges become opportunities when methods are combined in a complementary way. To encourage this, we provide an overview of some core concepts, key devel- opments, and opportunities, with emphasis on the properties that are the most fundamental determinants of chemical fate a Institute of Environmental Health, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA. E-mail: tratnyek@ohsu.edu b William R. Wiley Environmental Molecular Sciences Laboratory, Pacic Northwest National Laboratory, P.O. Box 999, Richland, WA 99352, USA c National Exposure Assessment Laboratory, U.S. Environmental Protection Agency, 960 College Station Road, Athens, GA 30605, USA Cite this: Environ. Sci.: Processes Impacts, 2017, 19, 188 Received 2nd February 2017 Accepted 21st February 2017 DOI: 10.1039/c7em00053g rsc.li/process-impacts 188 | Environ. Sci.: Processes Impacts, 2017, 19, 188–202 This journal is © The Royal Society of Chemistry 2017 Environmental Science Processes & Impacts PERSPECTIVE Open Access Article. Published on 24 February 2017. Downloaded on 5/23/2020 7:21:00 PM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online View Journal | View Issue