Uko Maran

Learn More
The potential utility of data reduction methods (e.g. principal component analysis) for the analysis of matrices assembled from the related properties of large sets of compounds is discussed by reference to results obtained from solvent polarity scales, ongoing work on solubilities and sweetness properties, and proposed general treatments of toxicities and(More)
Quantitative structure-property relationships on a large set of descriptors are developed for the melting points of a large set of mono-and disubstituted benzenes (443 compounds). A correlation equation including nine descriptors (R 2) 0.8373) is reported for the whole set of compounds, and six descriptor equations are given for the subsets of ortho-,(More)
Two four-parameter quantitative structure-property relations, with R2 = 0.95 and R2 = 0.97, respectively, gave good correlations for the solubilities of 87 gases and vapors in methanol and 61 in ethanol. All the descriptors used are derived solely from the structures of the molecules, making it possible to predict solubilities for unavailable or unknown(More)
Mutations in the gene autoimmune regulator (AIRE) cause autoimmune polyendocrinopathy candidiasis ectodermal dystrophy. AIRE is expressed in thymic medullary epithelial cells, where it promotes the expression of tissue-restricted antigens. By the combined use of biochemical and biophysical methods, we show that AIRE selectively interacts with histone H3(More)
As part of our general QSPR treatment of solubility (started in the preceding paper), we now present quantitative relationships between solvent structures and the solvation free energies of individual solutes. Solvation free energies of 80 diverse organic solutes are each modeled in a range from 15 to 82 solvents using our CODESSA PRO software. Significant(More)
We present an extended QSPR modeling of solubilities of about 500 substances in series of up to 69 diverse solvents. The models are obtained with our new software package, CODESSA PRO, which is furnished with an advanced variable selection procedure and a large pool of theoretically derived molecular descriptors. The squared correlation coefficients and(More)
An overview on the development of QSPR/QSAR equations using various descriptor mining techniques and multilinear regression analysis in the framework of program CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) is given. The description of the methodologies applied in CODESSA is followed by the presentation of the QSAR and QSPR(More)
Quantitative structure-toxicity relationships were developed for the prediction of aqueous toxicities for Poecilia reticulata (guppy) using the CODESSA treatment. A two-parameter correlation was found for class 1 toxins with R(2) = 0.96, and a five-parameter correlation was found for class 2 toxins with R(2) = 0.92. A five-parameter correlation for class 3(More)
A dataset of protein-drug complexes with experimental binding energy and crystal structure were analyzed and the performance of different docking engines and scoring functions (as well as components of these) for predicting the free energy of binding and several ligand efficiency indices were compared. The aim was not to evaluate the best docking method,(More)