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Fifteen physicochemical descriptors of side chains of the 20 natural and of 26 non-coded amino acids are compiled and simple methods for their evaluation described. The relevance of these parameters to account for hydrophobic, steric, and electric properties of the side chains is assessed and their intercorrelation analyzed. It is shown that three principal(More)
Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR(More)
The derivation of a new 3D QSAR field based on the electrotopological state (E-state) formalism is described. A complementary index and its associated field, the HE-state, describing the polarity of hydrogens is also defined. These new fields are constructed from a nonempirical index that incorporates electronegativity, the inductive influence of(More)
The connectivity index, easily computed by arithmetic and based upon the degree of connectedness at each vertex in the molecular skeleton, is shown to give highly significant correlations with water solubility of branched, cyclic, and straight-chain alcohols and hydrocarbons as well as with boiling points of alcohols. These correlations are superior to(More)
The role of a scientist is to study nature and to attempt to unlock her secrets. In order to pursue this goal, a certain process is usually followed, normally starting with observations. The scientist observes some part of the natural world and attempts to find patterns in the behaviors observed. These patterns, when they are found in what may be a quite(More)
Three QSAR methods, artificial neural net (ANN), k-nearest neighbors (kNN), and Decision Forest (DF), were applied to 3363 diverse compounds tested for their Ames genotoxicity. The ratio of mutagens to non-mutagens was 60/40 for this dataset. This group of compounds includes >300 therapeutic drugs. All models were developed using the same initial set of 148(More)
Several QSPR models were developed for predicting intrinsic aqueous solubility, S(o). A data set of 5,964 neutral compounds was sub-divided into two classes, aromatic and non-aromatic compounds. Three models were created with different methods on both data sets: two regression models (multiple linear regression and partial least squares) and an artificial(More)