VaPOrS v1.0.1: an automated model for functional group detection and property prediction of organic compounds via SMILES notation

Abstract

Volatile organic compounds play a significant role in atmospheric chemistry, influencing air quality and climate change. Accurate prediction of their physical properties is essential for understanding their behavior. This paper introduces VaPOrS (Vapor Pressure in Organics via SMILES) as a comprehensive tool designed to process SMILES notation of organic compounds, identify key functional groups, and apply group-contribution methods for property estimation. The core innovation of VaPOrS lies in its self-contained functional group recognition algorithm, which eliminates dependence on external cheminformatics libraries. The current approach enables fully auditable, easily modifiable, and computationally efficient detection of 30 functional groups required by the SIMPOL method. Compared to existing tools, VaPOrS avoids heavy SMILES-to-graph conversions and can obviate interface overhead, providing orders-of-magnitude speedups for large-scale atmospheric modeling scenarios. While this first implementation focuses on the SIMPOL method for estimating saturation vapor pressure and enthalpy of vaporization, the framework is readily extendable to other group-contribution schemes and thermodynamic properties (e.g., partition coefficients, volatility basis set models, solubility, Henry’s law constants). The tool has been validated against manually counted functional groups and experimental saturation vapor pressure data for a diverse set of compounds. Results demonstrate excellent agreement with both the original SIMPOL model and experimental observations, while comparisons with existing tools highlight the robustness and accuracy of the new parsing functions. VaPOrS thus provides a generalizable and computationally efficient platform for property prediction of large molecular datasets, facilitating integration into chemical transport and climate models and streamlining the analysis of thousands of organic compounds in atmospheric science applications.