From Zn to Mn: the study of novel manganese-binding groups in the search for new drugs against tuberculosis.

In most eubacteria, apicomplexans, and most plants, including the causal agents for diseases such as malaria, leprosy, and tuberculosis, the methylerythritol phosphate pathway is the route for the biosynthesis of the C(5) precursors to the essential isoprenoid class of compounds. Owing to their absence in humans, the enzymes of the methylerythritol phosphate pathway have become attractive targets for drug discovery. This work investigates a new class of inhibitors against the second enzyme of the pathway, 1-deoxy-D-xylulose 5-phosphate reductoisomerase. Inhibition of this enzyme may involve the chelation of a crucial active site Mn ion, and the metal-chelating moieties studied here have previously been shown to be successful in application to the zinc-dependent metalloproteinases. Quantum mechanics and docking calculations presented in this work suggest the transferability of these metal-chelating compounds to Mn-containing 1-deoxy-D-xylulose 5-phosphate reductoisomerase enzyme, as a promising starting point to the development of potent inhibitors

Coupling Accelerated Molecular Dynamics Methods with Thermodynamic Integration Simulations

In this work we propose a straightforward and efficient approach to improve accuracy and convergence of free energy simulations in condensed-phase systems. We also introduce a new accelerated Molecular Dynamics (MD) approach in which molecular conformational transitions are accelerated by lowering the energy barriers while the potential surfaces near the minima are left unchanged. All free energy calculations were performed on the propane-to-propane model system. The accuracy of free energy simulations was significantly improved when sampling of internal degrees of freedom of solute was enhanced. However, accurate and converged results were only achieved when the solvent interactions were taken into account in the accelerated MD approaches. The analysis of the distribution of boost potential along the free energy simulations showed that the new accelerated MD approach samples efficiently both low- and high-energy regions of the potential surface. Since this approach also maintains substantial populations in regions near the minima, the statistics are not compromised in the thermodynamic integration calculations, and, as a result, the ensemble average can be recovered

On the Role of Dewetting Transitions in Host-Guest Binding Free Energy Calculations.

We use thermodynamic integration (TI) and explicit solvent molecular dynamics (MD) simulation to estimate the absolute free energy of host-guest binding. In the unbound state, water molecules visit all of the internally accessible volume of the host, which is fully hydrated on all sides. Upon binding of an apolar guest, the toroidal host cavity is fully dehydrated; thus, during the intermediate λ stages along the integration, the hydration of the host fluctuates between hydrated and dehydrated states. Estimating free energies by TI can be especially challenging when there is a considerable difference in hydration between the two states of interest. We investigate these aspects using the popular TIP3P and TIP4P water models. TI free energy estimates through MD largely depend on water-related interactions, and water dynamics significantly affect the convergence of binding free energy calculations. Our results indicate that wetting/dewetting transitions play a major role in slowing the convergence of free energy estimation. We employ two alternative approaches-one analytical and the other empirically based on actual MD sampling-to correct for the standard state free energy. This correction is sizable (up to 4 kcal/mol), and the two approaches provide corrections that differ by about 1 kcal/mol. For the system considered here, the TIP4P water model combined with an analytical correction for the standard state free energy provides higher overall accuracy. This observation might be transferable to other systems in which water-related contributions dominate the binding process

Large-Scale Conformational Changes of Trypanosoma cruzi Proline Racemase Predicted by Accelerated Molecular Dynamics Simulation

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life-threatening illness affecting 11–18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR) as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations

Comparative assessment of mortality risk factors between admission and follow-up models among patients hospitalized with COVID-19

Objectives: This study aimed to compare differences in mortality risk factors between admission andfollow-up incorporated models.Methods: A retrospective cohort study of 524 patients with confirmed COVID-19 infection admitted to atertiary medical center in São Paulo, Brazil from 13 March to 30 April 2020. Data were collected onadmission, and the third, eighth and fourteenth days of hospitalization. The hazard ratio (HR) wascalculated and 28-day in-hospital mortality risk factors were compared between admission and follow-up models using a time-dependent Cox regression model.Results: Of 524 patients, 50.4% needed mechanical ventilation. The 28-day mortality rate was 32.8%.Compared with follow-up, admission models under-estimated the mortality HR for peripheral oxygensaturation 100 bpm (1.19 versus 2.04), respiratory rate >24/min (1.01versus 1.82) and mechanical ventilation (1.92 versus 12.93). Low oxygen saturation, higher oxygensupport and more biomarkers–including lactate dehydrogenase, C-reactive protein, neutrophil-lymphocyte ratio, and urea remained associated with mortality after adjustment for clinical factorsat follow-up compared with only urea and oxygen support at admission.Conclusions: The inclusion of follow-up measurements changed mortality hazards of clinical signs andbiomarkers. Low oxygen saturation, higher oxygen support, lactate dehydrogenase, C-reactive protein,neutrophil-lymphocyte ratio, and urea could help with prognosis of patients during follow-up