Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors.

BackgroundPyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function.ObjectiveTo develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene.MethodsWe measured the catalytic constant (kcat), KM, enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike's information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models.ResultsThe stability, physicochemical, and geometrical descriptors explained most of the variability (R2) of the kinetic parameters. Our models are best suited to predict kcat, efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation.ConclusionsThis study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance

Glycosylation as a key for enhancing drug recognition into spike glycoprotein of SARS-CoV-2

The emergence of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and its spread since 2019 represents the major public health problem worldwide nowadays, generating a high number of infections and deaths. That’s why, in addition to vaccination campaigns, the design of a drug to help in the treatment of severe cases of COVID-19 is being investigated. In relation to SARS-CoV-2, one of its most studied proteins is the spike protein (S protein), which mediates host-cell entry and is heavily glycosylated. Regarding the latter, several investigations have been carried out, since it plays an important role in the evasion of the host\u27s immune system and contributes to protein folding and the thermostability of the viral particle. For that reason, our objective was to evaluate the impact of glycosylations on the drug recognition on two domains of the S protein, the receptor-binding domain (RBD) and the N-terminal domain (NTD) through molecular dynamics simulations and computational biophysics analysis. Our results show that glycosylations in the S protein induce structural stability and changes in rigidity/flexibility related to the number of glycosylations in the structure. These structural changes are important for its biological activity as well as the correct interaction of ligands in the RBD and NTD regions. Additionally, we evidenced a roto-translation phenomenon in the interaction of the ligand with RBD in the absence of glycosylation, which disappears due to the influence of glycosylation and the convergence of metastable states in RBM. Similarly, glycosylations in NTD promote an induced-fit phenomenon, which is not observed in the absence of glycosylations; this process is decisive for the activity of the ligand at the cryptic site. Altogether, these results provide an explanation of glycosylation relevance in biophysical properties and drug recognition to S protein of SARS-CoV-2 which must be considered in the rational drug development and virtual screening targeting S protein