Co-authorship Network Analysis: A Powerful Tool for Strategic Planning of Research, Development and Capacity Building Programs on Neglected Diseases

The selection and prioritization of research proposals is always a challenge, particularly when addressing neglected tropical diseases, as the scientific communities are relatively small, funding is usually limited and the disparity between the science and technology capacity of different countries and regions is enormous. When the Ministry of Health and the Ministry of Science and Technology of Brazil decided to launch an R&D program on neglected diseases for which at least 30% of the Program's resources were supposed to be invested in institutions and authors from the poorest regions of Brazil, it became clear to us that new strategies and approaches would be required. Social network analysis of co-authorship networks is one of the new approaches we are exploring to develop new tools to help policy-/decision-makers and academia jointly plan, implement, monitor and evaluate investments in this area. Publications retrieved from international databases provide the starting material. After standardization of names and addresses of authors and institutions with text mining tools, networks are assembled and visualized using social network analysis software. This study enabled the development of innovative criteria and parameters, allowing better strategic planning, smooth implementation and strong support and endorsement of the Program by key stakeholders

Molecular Modeling and Receptor-Dependent (RD) 3D-QSAR Approach to a Set of Antituberculosis Derivatives

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)In this study, receptor-dependent (RD) 3D-QSAR models were built for a set of thirty-seven isoniazid derivatives bound to the enoyl-acp reductase from M. tuberculosis, called InhA (PDB entry code Izid). Ligand-receptor (L-R) molecular dynamics (MD) simulations [500000 steps; the step size was 0.001 ps (1 fs)] were carried out at 310 K (biological assay temperature). The hypothesized active conformations resulting from a previously reported receptor independent (IR) 4D-QSAR analysis were used as the molecular geometries of each ligand in this structure-based L-R binding research. The dependent variable is the reported MIC values against M. tuberculosis var. bovis. The independent variables (descriptors) are energy terms of a modified first-generation AMBER force field combined with a hydration shell aqueous solvation model. Genetic function approximation (GFA) formalism and partial least squares (PLS) regression were employed as the fitting functions to develop 3D-QSAR models. The bound ligand solvation energy, the sum of electrostatic and hydrogen bonding energies of the unbound ligand, the bending energy of the unbound ligand, the electrostatic intermolecular L-R energy, and the change in hydrogen bonding energy upon binding were found as important energy contributions to the binding process. The 3D-QSAR model at 310 K has good internal and external predictability and may be regarded as representative of the binding process of ligands to InhA.284198414551464Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Chem21 Group, IncFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)A new Receptor-Dependent LQTA-QSAR approach, RD-LQTA-QSAR, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive T. cruzi trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave-N-out cross-validation and y-randomization techniques to test for their robustness and absence of chance correlation. The final model presented Q (2) LOO of 0.87 and RA(2) of 0.92 and a suitable external prediction of = 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors.26910551065Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

The resumption of consumption: a review on tuberculosis

Among all infectious diseases that afflict humans, tuberculosis (TB) remains the deadliest. At present, epidemiologists estimate that one-third of the world population is infected with tubercle bacilli, which is responsible for 8 to 10 million new cases of TB and 3 million deaths annually throughout the world. Approximately 95% of new cases and 98% of deaths occur in developing nations, generally due to the few resources available to ensure proper treatment and where human immunodeficiency virus (HIV) infections are common. In 1882, Dr Robert Koch identified an acid-fast bacterium, Mycobacterium tuberculosis, as the causative agent of TB. Thirty-nine years later, BCG vaccine was introduced for human use, and became the most widely used prophylactic strategy to fight TB in the world. The discovery of the properties of first-line antimycobacterial drugs in the past century yielded effective chemotherapies, which considerably decreased TB mortality rates worldwide. The later introduction of some additional drugs to the arsenal used to treat TB seemed to provide an adequate number of effective antimicrobial agents. The modern, standard short-course therapy for TB recommended by the World Health Organization is based on a four-drug regimen that must be strictly followed to prevent drug resistance acquisition, and relies on direct observation of patient compliance to ensure effective treatment. Mycobacteria show a high degree of intrinsic resistance to most antibiotics and chemotherapeutic agents due to the low permeability of its cell wall. Nevertheless, the cell wall barrier alone cannot produce significant levels of drug resistance. M. tuberculosis mutants resistant to any single drug are naturally present in any large bacterial population, irrespective of exposure to drugs. The frequency of mutants resistant to rifampicin and isoniazid, the two principal antimycobacterial drugs currently in use, is relatively high and, therefore, the large extra-cellular population of actively metabolizing and rapidly growing tubercle bacilli in cavitary lesions will contain organisms which are resistant to a single drug. Consequently, monotherapy or improperly administered two-drug therapies will select for drug-resistant mutants that may lead to drug resistance in the entire bacterial population. Thereby, despite the availability of effective chemotherapy and the moderately protective vaccine, new anti-TB agents are urgently needed to decrease the global incidence of TB. The resumption of TB, mainly caused by the emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains and HIV epidemics, led to an increased need to understand the molecular mechanisms of drug action and drug resistance, which should provide significant insight into the development of newer compounds. The latter should be effective to combat both drug-susceptible and MDR/XDR-TB