FGO: a novel ontology for identification of ligand functional group

Small molecules play crucial role in the modulation of biological functions by interacting with specific macromolecules. Hence small molecule interactions are captured by a variety of experimental methods to estimate and propose correlations between molecular structures to their biological activities. The tremendous expanse in publicly available small molecules is also driving new efforts to better understand interactions involving small molecules particularly in area of drug docking and pharmacogenomics. We have studied and designed a functional group identification system with the associated ontology for it. The functional group identification system can detect the functional group components from given ligand structure with specific coordinate information. Functional group ontology (FGO) proposed by us is a structured classification of chemical functional group which acts as an important source of prior knowledge that may be automatically integrated to support identification, categorization and predictive data analysis tasks. We have used a new annotation method which can be used to construct the original structure from given ontological expression using exact coordinate information. Here, we also discuss about ontology-driven similarity measure of functional groups and uses of such novel ontology for pharmacophore searching and de-novo ligand designing.     

Cause-effect modeling as a general method for describing and studying phenomena in complex hierarchical systems

A strict definition of a cause-effect model of a complex phenomenon is given, and the rules for presenting such models in the form of cause-effect diagrams are formulated. The relationship between the cause-effect modeling and conventional methods of mathematical modeling is analyzed. Examples of the cause-effect models (diagrams) of phenomena of various physical nature are presented, and the application of these models to some specific problems is shown. In particular, the mechanism of renormalizing the rate constants of chemical reactions is considered in terms of dissipative resonance. An example of renormalizing the parameters of climate sensitivity and the relaxation time of the Earth’s climatic system in terms of a two-component (CO₂ + H₂O) greenhouse effect is considered.