2026-10-12T22:21:56Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33960754 2026-09-22T03:09:29Z category_1 category_4 category_915 category_7 category_21 category_873 category_39 category_69 category_133 category_135 portal_63 item_type_3 month_year_09_2026

Unraveling the PFAS Helix: A Statistical Approach Pranoy Ray (25086292) Haden Cavalli (15458836) Gashaw Bizana (25086295) Andrew R. Castillo (25086298) Shubham Vyas (672918) Ronald L. Siefert (2717578) Surya R. Kalidindi (5292808) Manoj Kolel-Veetil (25086301) Biophysics Biochemistry Physical Sciences not elsewhere classified Medicine Biotechnology Chemical Sciences not elsewhere classified Ecology Inorganic Chemistry Plant Biology Computational Biology varying fluorine content structurally distinct subfamilies perfluoroalkyl chains due incorporating backbone conformation helical twist adopted fluorine substitution pattern dimensional molecular conformation f </ sup pfas environmental fate geometric dihedral benchmarks including pfoa analogues 2 </ sub chain pfoa pfos analogues hydrogenated analogues spectroscopic definitions spatial autocorrelations remained absent predictive models polyfluoroalkyl substances pfas helix persistent homology perfluorosulfonic acids hyperconjugation involving homologous series fluorotelomer alcohols extreme persistence continuous metric binary occupancy agnostic toolset The extreme persistence of per- and polyfluoroalkyl substances (PFAS) in the environment is rooted in their three-dimensional molecular conformation. The helical twist adopted by perfluoroalkyl chains due to hyperconjugation involving their recalcitrant C–F bonds governs their resistance to degradation, yet a quantitative, continuous metric for helicity has remained absent. Here we introduce a data-driven framework that quantifies backbone helicity using three statistical descriptors: void-state (binary occupancy) spatial autocorrelations, local backbone principal component analysis, and persistent homology. We further validate each statistical descriptor against geometric dihedral benchmarks and DFT-calculated Vibrational Circular Dichroism (VCD) spectra. The framework is initially established on a homologous series of perfluorocarboxylic acids (^FC₂ through ^FC₁₆) and their hydrogenated analogues, then extended across perfluorosulfonic acids, fluorotelomer alcohols, polyfluoroalkyl hexanoic acid analogues, and longer-chain PFOA and PFOS analogues. Agreement between statistical, geometric, and spectroscopic definitions of helicity is established for PFCAs and extended to structurally distinct subfamilies, including PFOA analogues of varying fluorine content and perfluorosulfonic acids, demonstrating that the descriptors are robust to changes in headgroup chemistry and fluorine substitution pattern. The framework provides a chemistry-agnostic toolset for incorporating backbone conformation into predictive models of PFAS environmental fate and degradation reactivity. 2026-09-21T00:00:00Z Dataset Dataset 10.1021/acs.jcim.6c01874.s002 https://figshare.com/articles/dataset/Unraveling_the_PFAS_Helix_A_Statistical_Approach/33960754 CC BY-NC 4.0