Computer-Aided Design and Pharmacophore-Based Screening of a Diverse Combinatorial Library of Phytoselective Aryloxyacetic Acid Derivatives as HPPD Inhibitors.

We investigated the inhibitory potency of aryloxyacetic acid derivatives (AADs) on 4-hydroxyphenylpyruvate dioxygenase (HPPD), a crucial enzyme target for HPPD herbicide development. Developing a wide-ranging approach combining reported structure-activity relationships (SARs with the observed inhibitory potencies of the enzyme Kiexp), our simulations for molecular mechanics Poisson-Boltzmann (MM-PB) complexation quantitative SAR (QSAR) (computed relative Gibbs free energies of the HPPD-AADx complex formation ΔΔGcom), and three-dimensional (3D)-QSAR pharmacophore (PH4) models for screening the chemical subspace of aryloxyacetic acid derivatives (a virtual library of AADs, VL), we come out with a handful of novel AADs with promising predictive HPPD inhibitory potency and confirmed molecular dynamics (MD) conformational stability. The 3D-QSAR model revealed a correlation (pKiexp = a × ΔΔGcom + b) between computed data and observed inhibition ones: pKiexp = -0.0544 × ΔΔGcom + 6.93, R2 = 0.87 for a training set (TS) of 30 AAD (AAD1-30). The subsequent 3D-QSAR pharmacophore (PH4) of HPPD inhibition by AADs confirmed the correlation (pKiexp = 0.863 × pKipre + 7.92, R2 = 0.86) between PH4-predicted pKipre and the observed ones pKiexp. The structural information derived from these models suggested suitable substituents for building a virtual library (VL) of AAD analogues representing a chemical subspace of 79,500 compounds to be PH4-screened in search of more potent inhibitors; the best predicted Kipre of them reached 40 pM. Finally, the good stability of the AtHPPD-AADx complex and the flexibility of the active conformation of the inhibitor for selected top-ranked AAD analogues were checked with the help of molecular dynamics (MD, 200 ns runs). This computational study proposed a set of new predicted potent inhibitors with herbicidal effects.