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G protein-coupled receptors (GPCRs) are the target for more than 50% of the drugs currently on the market, including about 25% of the 100 top-selling drugs. They are considered the most important molecules in the field of drug discovery and design today, mostly due to their role as receptors in many of the basic processes in the body, and because they are present in all tissues. Unfortunately, a structure-based rational design is very difficult for GPCRs; the structures available for modeling purposes are only for family A. Despite this fact, research has continued and progressed, using combined structure-based techniques. This review intends to summarize this work. [ABSTRACT FROM AUTHOR]

Over the years the identification of one gene or protein has been substituted by the determination, in a single experiment, of all the genes or proteins expressed in a given cellular state. Consequently, the amount of available data has increased considerably. In this scenario, bioinformatics has become the bridge between experimental data and computational tasks for managing, mining and retrieving information. The current paper provides an overview on the bioinformatic databases and software used to analyze the biological meaning of proteomic data, thus describing the main functions and limitations of these tools. The important challenges of data analysis are mainly related to the integration of biological information from dissimilar sources. In this field, the improvement in databases and developments in software in the future would contribute to the potential opportunities given by proteomics. [ABSTRACT FROM AUTHOR]

Absorption, distribution, metabolism, excretion and toxicity (ADME-Tox) properties should be considered to develop a new drug, because they are the main cause of failures for candidate molecules in drug design. The early evaluation of these properties during drug design could save time and money. Physicochemical properties, tridimensional (3D) structural information, and mathematical methods can be combined to develop an in silico approach to predict ADME-Tox properties. Some of these in silico methods can be used to predict these properties in a large number of compounds at an early stage in drug design, but there is no general methodology for the computer prediction of ADME-Tox properties. In this review we summarize some of the models and available programs to predict ADME-Tox properties. [ABSTRACT FROM AUTHOR]

Protein kinases have become the second most important group of drug targets after G protein coupled receptors. Deregulated kinase activity is the frequent cause of many diseases, especially cancer, where kinases regulate many aspects that control cell growth and death. Drugs inhibiting specific kinases are being developed to treat this disease, and some are already in clinical use. This article reviews the current strategies to inhibit protein kinase activity in cancer therapy and illustrates the application of bioinformatics to design novel protein kinase inhibitors. [ABSTRACT FROM AUTHOR]

This manuscript shows the current situation of two re-emerging diseases: cholera and tuberculosis, which still constitute one of the major health problems in poor countries. In this regard, difficulties, challenges and perspectives for the development of new drugs and vaccines against these diseases are discussed. The possible contributions of structural biology, bioinformatics and 'omics' to obtain an effective treatment are also considered. [ABSTRACT FROM AUTHOR]