Predicting gas phase entropy of select hydrocarbon classes through specific information-theoretical molecular descriptors

The usefulness of five specific information-theoretical molecular descriptors was investigated for predicting the gas phase entropy of selected classes of acyclic and cyclic compounds. Among them, total information on atomic number (TI^Z), graph vertex complexity (H^V) and total information on bonds (TIB^AT), considered together showed the best correlation along with a low standard deviation (r² = 0.97, s = 21.14) with gas phase entropy values of 130 compounds. The multiple regression equation treating these three indices as independent variables was statistically highly significant which was evident from the F-statistics. In particular, very small difference between r² and r²-pred values indicates that the regression model is not overfitted and is, therefore, suitable for prediction purposes. When truly used as a training set to predict (from regression equation) 40 additional compounds we get a very high correlation (r² = 0.975), which remains almost identical (r² = 0.97) for the combined data set of 170 compounds. The three indices appear to be useful descriptors producing correlation that remains stable with the change in the size of the data set. Also, the information-theoretical measures appear to capture an additive-cum-constitutive nature of gas phase entropy yielding an acceptable statistical fit.

Indexing scheme and similarity measures for macromolecular sequences

Nucleotide composition and distribution along a DNA sequence is known to play a vital role in the determination of gene functions. Protein coding regions, regulatory sequences, and other functional regions are determined generally by homology studies with comparable genes from other species or specific experimental verification. With the rapid and explosive increase in sequence information, new computational techniques for rapid determination of such information and comparative studies of different genes are becoming necessary which ideally should encompass not only DNA sequences but other macromolecular sequences as well.

Topological shape and size of peptides: identification of potential allele specific helper T cell antigenic sites

A database of primary sequences of 28 immunogenic peptides, known to elicit T cell response, derived from five different haplotypes was compiled to identify allele specific helper T cell antigenic sites using a rule based graph-theoretical method. The prediction was based on the identification of allele specific patterns in the form of "topological shape and size" present in the peptides. Indices computed from weighted connected graph models of amino acid side chains and peptides were used in this purpose. The system was trained by 10 Ad and 10 non-Ad restricted peptide sequences, assigned actives and inactives, respectively, chosen randomly from the database, and four Ad and four non-Ad restricted sequences were kept as test peptides. This allowed the system to learn about "topological shape and size" specific for Ad restricted peptides from the differences, if any, they had with the inactive peptides in that respect. The system made 100% correct prediction for the training set peptides and misclassified only one inactive peptide of the test set. The system also identified crucial residues for lambda repressor 12-24 and insulin A-chains. This identification also shows that activity related/crucial residues could be located at varying distances from the peptide terminals. To our knowledge, the method is unique of its kind in the literature and may find application in the rational design of synthetic vaccines and other peptides of immunological importance.

Use of a rule based graph-theoretical system in evaluating the activity of a class of nucleoside analogues against human immunodeficiency virus

A rule based graph-theoretical system has been used to evaluate qualitatively the activity of a class of nucleoside analogues against human immunodeficiency virus (HIV). The system identifies biologically relevant vertices (atoms) in the molecular graphs of the compounds which have the biological activity of interest. The idea is to relate biological activity with the structural or substructural characteristics of the compounds from the point of view of molecular topology (connectivity). The system brings vertices of similar or close topological environment in the respective compounds together and this is reflected in the ranges of values formed by a distance based index of the vertices, the 'distance exponent index (Dx)', where x is any real number. It is found that the system makes correct prediction of the activity of all the compounds (active as well as inactives) of both training set and the test set against HIV. It is also apparent from this study that the index D-4, which has been used here, can make a useful classification of the vertices according to their molecular environment and the system can produce significant result in a small as well as diverse data base.

An approach for immunodiagnosis of clinical cases of filariasis

In this communication an immunodiagnostic approach has been adopted for detection of antigen and antibody in amicrofilaeamic Mf(-) patients by countercurrent immuno electrophoresis (CCIE) and immunodiffusion (ID). Using Setaria cervi and Immune Complex (IC) antigens, out of fifteen clinical cases the number of positive patients in CCIE were twelve and ten respectively. Sixty percent of the Mf(-) cases were positive in antigen detection against both the homologous and heterologous antibody. In ID nine Mf(-) cases gave precipitin bands against S. cervi antigen while with IC antigens ten patients were positive. In similar experiments, it was found that out of fifteen Mf(-) cases nine and eleven patients were positive in antigen detection against microfilaraemic Mf(+) sera and S. cervi antibody respectively. All the Mf(+) cases were positive in both antibody and antigen detection. From the standpoint of immunodiagnosis the data were analysed by two-way analysis of variance study and a newly developed system using Binomial distribution. The sera from the control group were negative in all the immunodiagnostic tests.