Current Pharmaceutical Design - Volume 16, Issue 24, 2010

Both, computer-aided Pharmaceutical Design and Drug Target Discovery using Bioinformatics are valuable tools in biomedical sciences. They may become useful in order to reduce costs in terms of material resources, personal, time and the use of animals of laboratory in the exploration of large databases. These techniques are not aimed to replace experimentation at all; we should understand these methods only as a guid Read More

In this review an overview of the application of computational approaches is given. Specifically, the uses of Quantitative Structure-Activity Relationship (QSAR) methods for in silico identification of new families of compounds as novel tyrosinase inhibitors are revised. Assembling, validation of models through prediction series, and virtual screening of external data sets are also shown, to prove the accuracy of the Read More

Development of quantitative structure-activity relationships (QSARs) and quantitative structure-property relationships (QSPRs) has been practiced for prediction of various toxicities and other relevant properties of chemicals including drug candidates to minimize animal testing, cost and time associated with risk assessment and management processes. This communication reviews published reports of QSARs/QSPRs with Exten Read More

There is a need for the study of complex diseases due to their important impact on our society. One of the solutions involves the theoretical methods which are fast and efficient tools that can lead to the discovery of new active drugs specially designed for these diseases. The Quantitative Structure - Activity Relationship models (QSAR) and the complex network theory become important solutions for screening and designin Read More

The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem computer-aided drug design has provide an extraordinary support to the different strategies in drug discovery. There are around 250 biological receptors such as enzymes that can be used in principle, for the design of antituberculosis compounds that act by Read More

GSK-3 inhibitors are interesting candidates to develop anti-Alzheimer compounds. GSK-3β are also interesting as antiparasitic compounds active against Plasmodium falciparum, Trypanosoma brucei, and Leishmania donovani; the causative agents for Malaria, African Trypanosomiasis and Leishmaniosis. The high number of possible candidates creates the necessity of Quantitative Structure-Activity Relationship models in or Read More

A topological substructural molecular design approach (TOPS-MODE) has been used to formulate structural rules for binding of substrates of P-glycoprotein (P-gp). We first review some of the models developed in the recent literature for predicting binding to Pgp. Then, we develop a model using TOPS-MODE, which is able to identify 88.4% of substrates and 84.2% of non-substrates. When the model is presented to an extern Read More

The number of protein 3D structures without function annotation in Protein Data Bank (PDB) has been steadily increased. Many of these proteins are relevant for Pharmaceutical Design because they may be enzymes of different classes that could become drug targets. This fact has led in turn to an increment of demand for theoretical models to give a quick characterization of these proteins. In this work, we present a review a Read More

The complex diseases in the field of Neurology, Cardiology and Oncology have the most important impact on our society. The theoretical methods are fast and they involve some efficient tools aimed at discovering new active drugs specially designed for these diseases. The ontology of all the items that are linked with the molecule metabolism and the treatment of these diseases gives us the possibility to correlate information Read More

Quantitative Structure-Activity Relationship (QSAR) models have been used in Pharmaceutical design and Medicinal Chemistry for the discovery of anti-parasite drugs. QSAR models predict biological activity using as input different types of structural parameters of molecules. Topological Indices (TIs) are a very interesting class of these parameters. We can derive TIs from graph representations based on only nodes (atoms) and e Read More