Current Bioinformatics - Volume 10, Issue 5, 2015

QSAR models supervised by Multiple linear regressions (MLR) and Gaussian kernel support vector machines were developed to predict β2 potency for Sibenadet (Viozan™) and its derivatives along with established LABAs (Formeterol, Salmetrol) and ultra LABA Indacaterol. MLR aided linear QSAR models identified four molecular descriptors MATS6e, GATS5e, Mor17p, R7m+ related to β2 potency while descriptors like R5p+, L Read More

Chagas' disease, which occurs particularly in South America is a human tropical parasitic disease, caused by Trypanosoma cruzi. A virtual screening in an in-house databank (SISTEMATX), of 469 Apocynaceae indole alkaloids, using models developed with fragment descriptors using Support Vector Machines (SVM) and Decision Trees (DT) were performed. A dataset 545 agrochemicals selected from ChEMBL database was use Read More

Classifier ensembles appeared to be powerful alternative for handling a difficult problem. It is rapidly growing and enjoying many attentions from pattern recognition and machine learning communities. In the present report, the potential of multi-criteria decision making via multiclassifier approaches is assessed by applying them in the modeling of chemicals against hyper-pigmentation. TOMOCOMD-CARDD atom-based qu Read More

The present manuscript describes a novel 3D-QSAR alignment free method (QuBiLS-MIDAS Duplex) based on algebraic bilinear, quadratic and linear forms on the kth two-tuple spatial-(dis)similarity matrix. Generalization schemes for the inter-atomic spatial distance using diverse (dis)-similarity measures are discussed. On the other hand, normalization approaches for the two-tuple spatial-(dis)similarity matrix by using Read More

Fullerenes are carbon allotropes, and they have called the attention of scientists in the last 15 years. In nanotechnology, fullerenes have had several promising applications in medicinal chemistry, pharmaceutical sciences, biomedicine, and related disciplines. Particularly, the design and biological evaluation of fullerene-C60 derivatives as antimicrobial agents constitute essential components of several active areas of rese Read More

Several antiretroviral drugs have been approved for use in HIV infected people. Despite efforts made by the scientific community, an effective drug that kills the virus has not been developed yet. A lot of computational algorithms have been used for finding mutations associated with drug resistance as well as for prediction of HIV resistance. This article provides an overview of machine learning techniques used to predict th Read More

In the recent years, so-called cell-penetrating peptides (CPPs) have been in constant study due to its ability to penetrate cell membranes. CCPs are characterized by a length of less than 60 amino acids, its highly cationic nature and by a positive net charge at neutral pH. For the CPPs either an endocytic or non-endocytic uptake mechanism has been identified. This work presents the computational polarity index method that is a Read More

Azo dyes form substantial industrial pollutants owing to their poor biodegradation capacity. Present study identifies azo dye detoxifying strain of bacteria from waste water near textile industries. In order to identify the azo dye degrading strain, 16S rRNA gene was sequenced from the pure bacterial culture obtained from the samples collected from textile industry area at Erode in Tamil Nadu state of India. Two novel azo dye Read More

The complex information encoded into the element connectivity of a system gives rise to the possibility of graphical processing of divisible systems by using the Graph theory. An application in this sense is the quantitative characterization of molecule topologies of drugs, proteins and nucleic acids, in order to build mathematical models as Quantitative Structure - Activity Relationships between the molecules and a specific biol Read More

We present a computational-mathematical algorithm that can identify peptides that are experimentally associated with their action against cancer cells and classified in the APD2 database. The algorithm, named polarity index method, showed an accuracy of 95% in a double-blind test applied to peptides from eight different databases. The method only requires the primary peptide structure, i.e. the amino acid sequence, to deter Read More

In this work, we reviewed different aspects about the epidemiology, drugs, targets, chem-bioinformatics, and systems biology methods, related to AIDS/HIV. Next, we developed a new model to predict complex networks of the prevalence of AIDS in U.S. counties taking into consideration the values of Gini coefficients of social income inequality. We also used activity/structure data of anti-HIV drugs in preclinical assays. First, we Read More

We can use Artificial Neural Networks (ANNs) and graph Topological Indices (TIs) to seek structure-property relationship. Balabans’ J index is one of the classic TIs for chemo-informatics studies. We used here Markov chains to generalize the J index and apply it to bioinformatics, systems biology, and social sciences. We seek new ANN models to show the discrimination power of the new indices at node level in three proof-of-conce Read More

Data mining and data classification over biomedical data are two of the most important research fields in computer science. Among the great diversity of technique that computer science can use for this purpose, Artificial Neural Networks (ANNs) are one of the most suited. One of the main problems in the development of this technique, ANNs, is the slow performance of the full process. Traditionally, in this developmen Read More

Complex systems and networks appear in almost all areas of reality. We find then from proteins residue networks to Protein Interaction Networks (PINs). Chemical reactions form Metabolic Reactions Networks (MRNs) in living beings or Atmospheric reaction networks in planets and moons. Network of neurons appear in the worm C. elegans, in Human brain connectome, or in Artificial Neural Networks (ANNs). Infection sprea Read More