Editorial [Hot Topic:Protein targets for development of drugs against Mycobacterium tuberculosis (Guest Editor: Walter Filgueira de Azevedo)]
The bacterium Mycobacterium tuberculosis remains a major challenge to public health systems worldwide, especially affecting developing countries in Asia, Africa, Latin America and Eastern Europe. Tuberculosis (TB) is one the most common bacterial diseases of humans, and World Health Organization estimates that nearly thirty percent of the world's population is infected with M. tuberculosis in a latent form and, as a result, at risk of developing active TB . Furthermore, the appearance of multidrug-resistant (MDR) and extensively drug-resistant (XDR, resistant to first- and second-line anti-TB drugs) strains of M. tuberculosis has worsened the situation. herein.
This scenario makes clear the need for development of a new generation of successful drugs against TB. The development of a new drug is result of combination of biological activity and drug-like properties. These qualities can be evaluated by computational approaches in the initial stages of drug discovery and development. Being structure-based virtual screen (SBVS) the major methodology applied for this end. SBVS is a methodology that requires structural information about protein targets, and can be applied to test libraries of small-molecule compounds against important targets for drug design, including targets identified in the Mycobacterium tuberculosis .
The use of combination of different drugs is of pivotal importance to stop the appearance of multiple drug resistant (MDR) organisms by spontaneous genetic mutations, which can lead to an ineffective treatment. Therefore new proteins should be targeted for drug development. Several enzymes of the purine and pyrimidine salvage pathways [3,4], shikimate pathway , and mycolic acid biosynthetic pathway  have been validated as anti-TB targets.
The present volume of Current Medicinal Chemistry brings reviews focused on protein targets identified in Mycobacterium tuberculosis. There are reviews about protein-drug interactions and structural basis for inhibition of protein targets identified in the Mycobacterium tuberculosis genome. Among them the enzymes of the shikimate pathway, which represent potential protein targets for developing antibacterial agents, and anti-parasite drugs, because these enzymes are of pivotal importance for bacteria and protozoans, but they are absent from humans . The shikimate pathway is a connection between the metabolism of carbohydrates and the biosynthesis of aromatic compounds through seven metabolic steps. In these pathway phosphoenolpyruvate (PEP) and erythrose 4-phosphate are converted to chorismic acid [7,8]. Due to importance of this pathway, several structural studies focused on these enzymes were carried our [9-19]. This structural information opened the possibility for structure-based virtual screens, which may be able to identity new anti-tubercular drugs . This volume presents two reviews with information about structural studies of shikimate kinase (EC 188.8.131.52) and chorismate synthase (EC 184.108.40.206)......
In addition, a review by Obiol-Pardo and collaborators describes the mechanism of action and inhibitors of the seven enzymes of the methylerythritol phosphate (MEP) pathway for isoprenoid biosynthesis, with special attention to the reported studies in M. tuberculosis. Enzymes of this pathway are also potential targets for antitubercular drugs. Three other metabolic pathways are reviewed here: purine salvage pathway (by Ducati and collaborators), pyrimidine salvage pathway (by Villela and collaborators) and mycolic acid biosynthetic pathway (by Singh and collaborators).
It is also discussed here recent development of structure-based virtual screening methodologies, including a review on modern computational approaches to molecular docking simulations. Molecular docking is a computer simulation methodology to predict the conformations of a receptor-ligand complex [21-28]. It is possible to visualize that this simulation is analogous to the key-and-lock problem, where the lock is the receptor and the key the ligand. The goal in this kind of simulation is to adjust the position of the key in the lock. In a computer simulation it is generated many possible positions for the key in the lock, which are called poses. Docking simulations employ one or more of the following methodologies: Monte Carlo (MC) , fast shape matching (SM) , incremental construction (IC) [31, 32], distance geometry (DG) , simulated annealing (SA) [34, 35] and tabu search (TS) . All these computational methodologies have been recently reviewed . Although intense research has been performed on the application of the above mentioned algorithms to the problem of molecular docking simulations, recent results strongly indicate that the most successful approaches are those based on BIAs [27, 38], such as evolutionary programming (EP) [39, 40] and genetic algorithms (GA) [41-43]. These approaches and their application to development of antiTB drugs are discussed here.
Structural aspects such as intermolecular hydrogen bonds, contact area and electrostatic interactions can be analyzed from threedimensional structures of complexes involving protein-targets and ligand . Nevertheless, the precise analysis of protein-drug interactions from these structures is inadequate since crystal structures are average structures obtained from the molecules packed in the crystal lattice. It is hard to identify directly from crystallographic structure the flexible parts of the molecule. These limitations can be overcome by application of molecular dynamics simulations. Three-dimensional structures obtained experimentally or by homology modeling can be submitted to this simulation, where dynamical features of the complexes can be analyzed. These methods are also described in the present volume.
Several recent applications of SBVS successful identified new drugs, which serve as incentives for development of new methodologies and also for extending the application to a wide range of protein targets and diseases [45-69]. In conclusion, one of the most defying challenges in the post-genomic era is the understanding of dynamics and structural features of the protein-drug interaction. Information obtained from structural studies of protein targets together with molecular docking and dynamics simulations will pave the way for discovery and development of a new generation of drugs.
Finally, I would like to express gratitude to the authors for their significant contribution to this special issue, which hopefully will be of significance to researchers working in the development of a new generation of antiTB drugs.
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