Organic pollutants environmental fate: modeling and prediction of global persistence by molecular descriptors P.Gramatica, F.Consolaro and M.Pavan QSAR Research Unit, Dept. of Structural and Functional Biology, University of Insubria, Varese, Italy Web: INTRODUCTION The persistence of organic compounds in various environmental compartments is mainly governed by the rates at which they are removed by chemical and/or physical processes. Half-life in various compartments is the most commonly used criteria for studying persistence, but such data, available for only a few organic compounds, vary greatly for the various compartments and depend on laboratory tests. As most literature data are reported as ranges of values, we used the average values as the input data in QSPR studies. Validated OLS regression models have been developed using different theoretical molecular descriptors to predict half-life mean values in the atmosphere, soil, surface water and groundwater for more than 90 supposed POPs of different chemical classes (pesticides, PAH, PCB,etc). All the regression models have been strongly validated and the predicted data checked for their reliability by the leverage procedure. These predicted values are obviously not the real half-life, but a reasonable estimate that have been simultaneously used in Principal Component Analysis to produce useful indexes for POP persistence: PC1 as a global persistence index and PC2 as a compartment related persistence index. These two indexes have been also modeled allowing a fast screening and ranking of organic compounds for their persistence. DATA SET Our data set is constituted by 33 organic pollutants, mainly supposed POPs, for which half-life values in air, surface-water, groundwater and soil have been collected from Howard 2 and Rodan 3. It must be emphasized that these values are subject to considerable variation, thus presenting single value is over-simplistic, which is why we considered the mean value of the half life range. The data of the mean value reported range were always transformed in logarithmic units to linearize the experimental range of variation. [2] Howard,P.H. et all. Handbook of Environmental Degradation Rates, (1991). [3] Rodan,B.D. et all. Screening for Persistent Organic Pollutants: Techniques To Provide a scientific basis for POPs Criteria in International Negotiations. Environ. Sci. Technol.,33(20), (1999). MOLECULAR DESCRIPTORS The molecular structure has been represented by a wide set of molecular descriptors (about 170) calculated by the software DRAGON 1.0 of R.Todeschini ( mono-dimensional: counts and fragments descriptors two-dimensional: topological descriptors three-dimensional:3D-WHIM (Weighted Holistic Invariant Molecular) 1 [1]R.Todeschini and P.Gramatica, 3D-modelling and prediction by WHIM descriptors. Part 5. Theory development and chemical meaning of the WHIM descriptors, Quant.Struct.-Act.Relat., 16 (1997) Are half life ranges usefully QSPR - modeled and predicted by theoretical molecular descriptors? Are half life ranges usefully QSPR - modeled and predicted by theoretical molecular descriptors? Log h.l. air = nR BAL UI E1e NR07 : number of rings with 7 atoms BAL : Balaban index UI : unsaturation index E1e : directional WHIM Log h.l. groundwater = nC E2m E1e nC : number of Carbon atoms E2m - E1e : directional WHIM Log h.l. surf.water = nR ROUV IDMT E1p Vu nR09 : number of rings with 9 atoms ROUV : Rouvray index IDMT: total inf. index on the distance magnitude E1p : atomic distribution directional WHIM Vu : global shape and dimensional WHIM Log h.l. soil = IDM E2m G2e IDM : mean inf. index on distance magnitude E2m- G2e : directional WHIMs The PC scores have been used as indexes for POP persistence: PC1 (EV%= 51.2) as a global persistence index and PC2 (EV%= 28.3) as a compartment related persistence index. These two indexes have been also modeled by molecular descriptors selected by Genetic Algorithm with satisfactory predictive power; this allows a fast screening and ranking of organic compounds for their persistence. The data predicted by this QSPR approach, based on few descriptors of the molecular structure, could be usefully applied in organic pollutants environmental fate modelling, for not yet synthesised chemicals too. PC1 and PC2 scores as persistence indexes PC1 (overall persistence index)= AAC E2s – E1e – 0.16 Tm n = 91 R 2 = 85.1 Q 2 LOO = 82.6 Q 2 LMO = 82.2 s = F 86 = SDEC= SDEP= PC2 (media persistence index)=10.31– 8.29IDE– 0.48G2p+9.93 E1p+5.46 Ks+0.09Ve n = 91 R 2 = 78.9 Q 2 LOO = 75.1 Q 2 LMO = 74.5 s = F 6, 85 = SDEC= SDEP= PERSISTENCE SOLUBLES and VOLATILES SORBED Principal Component Analysis on experimental plus QSPR-predicted half life data Cum E.V.% = 79.5 PERSISTENCE SOLUBLES and VOLATILES SORBED Principal Component Analysis on QSPR-predicted half life data Cum E.V.% = 78.6 SOLUBLES and VOLATILES SORBED PERSISTENCE