Pesticide Indirect Photodegradation Database: A Data-Sharing Platform for Screening Existing and Discovering New Agrochemicals

The ability to control and tune physicochemical properties
that
underscore chemical behavior in living systems and the environment
is at the “heart” of green chemistry. This is especially
true for chemical classes designed a priori to be biologically active,
such as pesticides, where the chance of unintended adverse outcomes
is high. We recently proposed a design-vectoring framework, leveraging
validated computational models of ecotoxicity and indirect photodegradation
as a useful, quasisystems-based tool for screening existing and designing
new agrochemicals. Here, we describe the development of a database
that integrates our models, which link structural and substructural
features to process metrics, and corresponding predicated data for
all agrochemicals with photodegradable cores on the U.S. Environmental
Protection Agency’s registry (785 compounds and over 18,000
pairwise interactions with chromophoric dissolved organic matter,
CDOM). The database is searchable by structural and nonstructural
identifiers (e.g., chemical class, oxidizable core, physicochemical
and electronic properties, etc.) to aid in chemical selection, hazard,
and alternative assessment. Crucially, it can be easily updated and
augmented to aid in interactive data-sharing across industry, government,
and academia. The overarching goal of this project is to spur grander
efforts in systems-based design of pesticides that would see this
platform paired with target-based computational methods and incorporated
into the discovery phase of new product development across industry
sectors.