Models for the Prediction of Receptor Tyrosine Kinase Inhibitory Activity of Substituted 3-Aminoindazole Analogues

The inhibition of tumor angiogenesis has become a compelling approach in the development of anticancer drugs. In the present study, topological models were developed through decision tree and moving average analysis using a data set comprising 42 analogues of 3-aminoindazoles. A total of 22 descriptors (distance based, adjacency based, pendenticity and distance-cum-adjacency based) were used. The values of all 22 topological indices for each analogue in the dataset were computed using an in-house computer program. A decision tree was constructed for the receptor tyrosine kinase KDR (kinase insert domain receptor) inhibitory activity to determine the importance of topological indices. The decision tree learned the information from the input data with an accuracy of 88%. Three independent topological models were also developed for prediction of receptor tyrosine kinase inhibitory (KDR) activity using moving average analysis. The models developed were also found to be sensitive towards the prediction of other receptor tyrosine kinases i.e. FLT3 (fms-like tyrosine kinase-3) and cKIT inhibitory activity. The accuracy of classification of single index based models using moving average analysis was found to be 88%. The performance of models was assessed by calculating precision, sensitivity, overall accuracy and Mathew’s correlation coefficient (MCC). The significance of the models was also assessed by intercorrelation analysis

Wiener Index Extension by Counting Even/Odd Graph Distances

Chemical structures of organic compounds are characterized numerically by a variety of structural descriptors, one of the earliest and most widely used being the Wiener index W, derived from the interatomic distances in a molecular graph. Extensive use of such structural descriptors or topological indices has been made in drug design, screening of chemical databases, and similarity and diversity assessment. A new set of topological indices is introduced representing a partitioning of the Wiener index based on counts of even and odd molecular graph distances. These new indices are further generalized by weighting exponents which can be optimized during the quantitative structure-activity/-property relationship (QSAR/QSPR) modeling process. These novel topological indices are tested in QSPR models for the boiling temperature, molar heat capacity, standard Gibbs energy of formation, vaporization enthalpy, refractive index, and density of alkanes. In many cases, the even/odd distance indices proposed here give notably improved correlations

MULTISCALE DYNAMIC MONTE CARLO / CONTINUUM MODELING OF DRYING AND CURING IN SOL-GEL SILICA FILMS

Modeling the competition between drying and curing processes in polymerizing films is of great importance to many existing and developing materials synthesis processes. These processes involve multiple length and time scales ranging from molecular to macroscopic, and are challenging to fully model in situations where the polymerization is non-ideal, such as sol-gel silica thin film formation. A comprehensive model of sol-gel silica film formation should link macroscopic flow and drying (controlled by process parameters) to film microstructure (which dictates the properties of the films). This dissertation describes a multiscale model in which dynamic Monte Carlo (DMC) polymerization simulations are coupled to a continuum model of drying. Unlike statistical methods, DMC simulations track the entire molecular structure distribution to allow the calculation not only of molecular weight but also of cycle ranks and topological indices related to molecular size and shape. The entire DMC simulation (containing 106 monomers) is treated as a particle of sol whose position and composition are tracked in the continuum mass transport model of drying. The validity of the multiscale model is verified by the good agreement of the conversion evolution of DMC and continuum simulations for ideal polycondensation and first shell substitution effect (FSSE) cases. Because our model allows cyclic and cage-like siloxanes to form, it is better able to predict the silica gelation conversion than other reported kinetic models. By studying the competition between molecular growth and cyclization, and the competition between mass transfer (drying) and reaction (gelation) on the drying process of the sol-gel silica film, we observe that cyclization delays gelation, shrinks the molecular size, increases the likelihood of skin formation, and leads to a molecular structure gradient inside the film. We also find that compared with a model with only 3-membered rings, the molecular structure is more complicated and the structure gradients in the films are larger with 4- membered rings. We expect that our simulation will allow better prediction of the formation of structure gradients in sol-gel derived ceramics and other nonideal multifunctional polycondensation products, and that this will help in developing procedures to reduce coating defects