Molecular modeling databases: A new way in the search of protein targets for drug development

DBMODELING is a relational database of annotated comparative protein structure models and their metabolic, pathway characterization. It is focused on enzymes identified in the genomes of Mycobacterium tuberculosis and Xylella fastidiosa. The main goal of the present database is to provide structural models to be used in docking simulations and drug design. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models which show high structural quality should be used in such efforts. Molecular modeling of these genomes generated a database, in which all structural models were built using alignments presenting more than 30% of sequence identity, generating models with medium and high accuracy. All models in the database are publicly accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools. DBMODELING user interface provides users friendly menus, so that all information can be printed in one stop from any web browser. Furthermore, DBMODELING also provides a docking interface, which allows the user to carry out geometric docking simulation, against the molecular models available in the database. There are three other important homology model databases: MODBASE, SWISSMODEL, and GTOP. The main applications of these databases are described in the present article. © 2007 Bentham Science Publishers Ltd.

Evidence for dark matter in the inner Milky Way

The ubiquitous presence of dark matter in the Universe is today a central tenet in modern cosmology and astrophysics(1). Throughout the Universe, the evidence for dark matter is compelling in dwarfs, spiral galaxies, galaxy clusters as well as at cosmological scales. However, it has been historically difficult to pin down the dark matter contribution to the total mass density in the Milky Way, particularly in the innermost regions of the Galaxy and in the solar neighbourhood(2). Here we present an up-to-date compilation of Milky Way rotation curve measurements(3-13), and compare it with state-of-the-art baryonic mass distribution models(14-26). We show that current data strongly disfavour baryons as the sole contribution to the Galactic mass budget, even inside the solar circle. Our findings demonstrate the existence of dark matter in the inner Galaxy without making any assumptions about its distribution. We anticipate that this result will compel new model-independent constraints on the dark matter local density and profile, thus reducing uncertainties on direct and indirect dark matter searches, and will help reveal the structure and evolution of the Galaxy.

The dark matter profile of the Milky Way: a non-parametric reconstruction

We present the results of a new, non-parametric method to reconstruct the Galactic dark matter profile directly from observations. Using the latest kinematic data to track the total gravitational potential and the observed distribution of stars and gas to set the baryonic component, we infer the dark matter contribution to the circular velocity across the Galaxy. The radial derivative of this dynamical contribution is then estimated to extract the dark matter profile. The innovative feature of our approach is that it makes no assumption on the functional form or shape of the profile, thus allowing for a clean determination with no theoretical bias. We illustrate the power of the method by constraining the spherical dark matter profile between 2.5 and 25 kpc away from the Galactic center. The results show that the proposed method, free of widely used assumptions, can already be applied to pinpoint the dark matter distribution in the Milky Way with competitive accuracy, and paves the way for future developments.