Selecting the right compounds for screening: does Lipinski's Rule of 5 for pharmaceuticals apply to agrochemicals?

Large numbers of compounds are now available through combinatorial chemistry and from compound vendors to screen for lead-level agrochemical activity. The likelihood that compounds with whole-organism activity will be discovered can be increased if compounds with physicochemical parameters consistent with transport to the target site are selected for screening. Certain ranges of simple parameters (molecular mass, log P, hydrogen-bond donors and acceptors, rotatable bonds) have been correlated with oral bioavailability of drugs. The distribution of these parameters for commercial insecticides and post-emergence herbicides was examined and ranges consistent with whole-organism activity are proposed for the two classes of agrochemical. The most significant difference identified between drugs and these two classes of agrochemicals was the lower numbers of hydrogen-bond donors allowed in the latter cases. The frequency with which certain functional groups occur in drugs and agrochemicals was also compared.

[1]  Michael H. Abraham,et al.  Hydrogen bonding part 46: a review of the correlation and prediction of transport properties by an lfer method: physicochemical properties, brain penetration and skin permeability , 1999 .

[2]  Ajay,et al.  Recognizing molecules with drug-like properties. , 1999, Current opinion in chemical biology.

[3]  H Lennernäs,et al.  Correlation of human jejunal permeability (in vivo) of drugs with experimentally and theoretically derived parameters. A multivariate data analysis approach. , 1998, Journal of medicinal chemistry.

[4]  S. Hirono,et al.  Simple Method of Calculating Octanol/Water Partition Coefficient. , 1992 .

[5]  The search for orally active medications through combinatorial chemistry , 1998, Medicinal research reviews.

[6]  J R Chretien,et al.  Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors. , 1998, Journal of drug targeting.

[7]  D. E. Clark Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 1. Prediction of intestinal absorption. , 1999, Journal of pharmaceutical sciences.

[8]  Barry A. Bunin The Combinatorial Index , 1998 .

[9]  E. Gordon,et al.  Combinatorial chemistry and molecular diversity in drug discovery , 1998 .

[10]  R. Kirkwood Recent developments in our understanding of the plant cuticle as a barrier to the foliar uptake of pesticides , 1999 .

[11]  N. Balke,et al.  Effects of Calcium, Magnesium, and Phosphate on Glyphosate Absorption by Cultured Plant Cells , 1991, Weed Science.

[12]  H. Kubinyi,et al.  A scoring scheme for discriminating between drugs and nondrugs. , 1998, Journal of medicinal chemistry.

[13]  A. Ghose,et al.  Atomic physicochemical parameters for three dimensional structure directed quantitative structure‐activity relationships III: Modeling hydrophobic interactions , 1988 .

[14]  F. Hsu,et al.  Phloem Mobility of Xenobiotics. VII. The Design of Phloem Systemic Pesticides , 1996, Weed Science.

[15]  Arup K. Ghose,et al.  Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics , 1989, J. Chem. Inf. Comput. Sci..

[16]  Ajay,et al.  Can we learn to distinguish between "drug-like" and "nondrug-like" molecules? , 1998, Journal of medicinal chemistry.

[17]  W. Steurbaut Adjuvants for use with foliar fungicides , 1993 .

[18]  R. Bromilow,et al.  Phloem translocation of weak acids in ricinus communis , 1987 .

[19]  C. T. Lewis The Penetration of Cuticle by Insecticides , 1980 .

[20]  H. Matter,et al.  Selecting optimally diverse compounds from structure databases: a validation study of two-dimensional and three-dimensional molecular descriptors. , 1997, Journal of medicinal chemistry.

[21]  F. Hsu,et al.  Phloem mobility of xenobiotics VIII. A short review. , 1996, Journal of experimental botany.

[22]  A. Leo CALCULATING LOG POCT FROM STRUCTURES , 1993 .

[23]  D. E. Clark,et al.  Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood-brain barrier penetration. , 1999, Journal of pharmaceutical sciences.

[24]  N. Casabé,et al.  The relation between viscosity and penetration of some diethyl p-substituted phenyl phosophorothionates and oil carriers into the cuticle of Triatoma infestans , 1983 .

[25]  K. Luthman,et al.  Evaluation of dynamic polar molecular surface area as predictor of drug absorption: comparison with other computational and experimental predictors. , 1998, Journal of medicinal chemistry.

[26]  P A Carrupt,et al.  Evaluation and Prediction of Drug Permeation , 1999, The Journal of pharmacy and pharmacology.

[27]  D. Kleier Phloem mobility of xenobiotics. V. Structural requirements for phloem‐systemic pesticides , 1994 .

[28]  A. Ghose,et al.  A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. , 1999, Journal of combinatorial chemistry.

[29]  A. Ghose,et al.  Atomic Physicochemical Parameters for Three‐Dimensional Structure‐Directed Quantitative Structure‐Activity Relationships I. Partition Coefficients as a Measure of Hydrophobicity , 1986 .

[30]  Robert D Clark,et al.  Bioisosterism as a molecular diversity descriptor: steric fields of single "topomeric" conformers. , 1996, Journal of medicinal chemistry.

[31]  Robert D Clark,et al.  Neighborhood behavior: a useful concept for validation of "molecular diversity" descriptors. , 1996, Journal of medicinal chemistry.

[32]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings , 1997 .

[33]  G P Moss,et al.  Investigation of the mechanism of flux across human skin in vitro by quantitative structure-permeability relationships. , 1999, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[34]  John H. Van Drie,et al.  Approaches to virtual library design , 1998 .

[35]  R. Metcalf,et al.  Structure‐Activity for uptake and toxicity of DDT‐type insecticides utilizing an NMR method for estimating σ* , 1989 .

[36]  U Norinder,et al.  Theoretical calculation and prediction of intestinal absorption of drugs in humans using MolSurf parametrization and PLS statistics. , 1999, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[37]  S. Krämer,et al.  Absorption prediction from physicochemical parameters. , 1999, Pharmaceutical science & technology today.

[38]  R. Bromilow,et al.  Relationships between lipophilicity and root uptake and translocation of non-ionised chemicals by barley† , 1982 .

[39]  P Buchwald,et al.  Octanol-water partition: searching for predictive models. , 1998, Current medicinal chemistry.

[40]  M. Trevisan,et al.  Root Uptake and Xylem Translocation of Pesticides from Different Chemical Classes , 1997 .