Convenient access to 5-arylisoindolo[2,1- α]quinolin-11(6a )-ones.

Substituted isoindoloquinolinones were obtained from N-aryl-3-hydroxyisoindolinones and aryl alkynes under Lewis acid-catalyzed conditions in 30-99% yields.

A Short Review of the Generation of Molecular Descriptors and Their Applications in Quantitative Structure Property/Activity Relationships.

Background: Synthesis of organic compounds with specific biological activity or physicochemical characteristics needs a thorough analysis of the enumerable data set obtained from literature. Quantitative structure property/activity relationships have made it simple by predicting the structure of the compound with any optimized activity. For that there is a paramount data set of molecular descriptors (MD).

Novel computational models for predicting dopamine interactions.

Dopamine is a crucial neurotransmitter responsible for functioning and maintenance of the nervous system. Dopamine has also been implicated in a number of diseases including schizophrenia, Parkinson's disease and drug addiction. Dopamine agonists are used in early Parkinson's disease treatment.

The classification of solvents by combining classical QSPR methodology with principal component analysis.

The results of a quantitative structure-property relationship (QSPR) analysis of 127 different solvent scales and 774 solvents using the CODESSA PRO program are presented. QSPR models for each scale were constructed using only theoretical descriptors. The high quality of the models is reflected by the squared multiple correlation coefficients that range from 0.

Correlation of blood-brain penetration using structural descriptors.

Experimental blood-brain partition coefficients (logBB) for a diverse set of 113 drug molecules are correlated with computed structural descriptors using CODESSA-PRO and ISIDA programs to give statistically significant QSAR models based respectively, on molecular and on fragment descriptors. The linear correlation CODESSA-PRO five-descriptor model has correlation coefficient R2=0.781 and standard deviation s2=0.

Antimalarial activity: a QSAR modeling using CODESSA PRO software.

A quantitative structure-activity relationship (QSAR) modeling of the antimalarial activity of two diverse sets of compounds for each of two strains D6 and NF54 of Plasmodium falciparum is presented. The molecular structural features of compounds are presented by molecular descriptors (geometrical, topological, quantum mechanical, and electronic) calculated using the CODESSA PRO software. Satisfactory multilinear regression models were obtained for data sets of the D6 and NF54 strains, with R2 = 0.

QSAR modeling of blood:air and tissue:air partition coefficients using theoretical descriptors.

Human blood:air, human and rat tissue (fat, brain, liver, muscle, and kidney):air partition coefficients of a diverse set of organic compounds were correlated and predicted using structural descriptors by employing CODESSA-PRO and ISIDA programs. Four and five descriptor regression models developed using CODESSA-PRO were validated on three different test sets. Overall, these models have reasonable values of correlation coefficients (R(2)) and leave-one-out correlation coefficients (R(cv)(2)): R(2) = 0.

QSPR treatment of rat blood:air, saline:air and olive oil:air partition coefficients using theoretical molecular descriptors.

A QSPR treatment has been applied to a data set that consists of 100 diverse organic compounds to relate the logarithmic function of rat blood:air, saline:air and olive oil:air partition coefficients (denoted by log K(b:a), log K(s:a), and log K(o:a), respectively), with theoretical molecular and fragment descriptors. Three QSPR models with squared correlation coefficients of 0.881, 0.

Aqueous biphasic systems. Partitioning of organic molecules: a QSPR treatment.

The partitioning of 29 small organic probes in a PEG-2000/(NH4)2SO4 biphasic system was investigated using a quantitative structure-property relationship (QSPR) approach. A three-descriptor equation with the squared correlation coefficient (R2) of 0.97 for the partition coefficient (log D) was obtained.