In the present study, the performance of the support vector machine for estimating vertical drop hydraulic parameters in the presence of dual horizontal screens has been investigated. For this purpose, 120 different laboratory data were used to estimate three parameters of the drop: the relative length, the downstream relative depth, and the residual relative energy in the support vector machine. For each parameter, 12 models were analyzed by using a support vector machine. The performance of the models was evaluated with statistical criteria (R2, DC, and RMSE) and the best model was introduced for each of the parameters. The evaluation criteria for the relative length of the vertical drop equipped with dual horizontal screens for the testing stage are R2 = 0.992, DC = 0.981 and, RMSE = 0.050. Also, the values of the downstream relative depth evaluation indicators for the testing stage are R2 = 0.9866, DC = 0.980 and, RMSE = 0.0064. For the residual relative energy parameter, the values of the residual relative energy evaluation indicators are R2 = 0.9949, DC = 0.9853 and RMSE = 0.0056. The results showed that capacity for this approach to predict the hydraulic performance of these systems with accuracy.

Structural, regulatory and enzymatic proteins interact with DNA to maintain a healthy and functional genome. Yet, our structural understanding of how proteins interact with DNA is limited. We present MELD-DNA, a novel computational approach to predict the structures of protein–DNA complexes. The method combines molecular dynamics simulations with general knowledge or experimental information through Bayesian inference. The physical model is sensitive to sequence-dependent properties and conformational changes required for binding, while information accelerates sampling of bound conformations. MELD-DNA can: (i) sample multiple binding modes; (ii) identify the preferred binding mode from the ensembles; and (iii) provide qualitative binding preferences between DNA sequences. We first assess performance on a dataset of 15 protein–DNA complexes and compare it with state-of-the-art methodologies. Furthermore, for three selected complexes, we show sequence dependence effects of binding in MELD predictions. We expect that the results presented herein, together with the freely available software, will impact structural biology (by complementing DNA structural databases) and molecular recognition (by bringing new insights into aspects governing protein–DNA interactions).

In this study, we demonstrate that anion−π interactions (an attractive noncovalent force between electron deficient π-systems and anions) are involved in the stabilization of GAAA and GGAG RNA tetraloops. Using the single recognition particle (SRP)–RNA complexes as a case of study, we combined molecular dynamics (MD) and quantum mechanics (QM) calculations to shed light on the structural influence of phosphate–G anion−π interactions and hydrogen bonds (HBs) involving K+/Mg2+ water clusters. In addition, the RNA assemblies herein were further characterized by means of the “atoms in molecules” (AIM) and noncovalent interactions plot (NCIplot) methodologies. We believe the results derived from this study might be important in the fields of chemical biology (RNA folding and engineering) and supramolecular chemistry (anion−π interactions) as well as to further expand the current knowledge regarding RNA structural motifs.

The mycobacterial enzyme pyrazinamidase (PZase) is the target of key tuberculosis drug, pyrazinamide. Mutations in PZase cause drug resistance. Herein, three point mutations, W68G, L85P, and V155G, were investigated through over 8 µs of molecular dynamics simulations coupled with essential dynamics and binding pocket analysis at neutral (pH = 7) and acidic (pH = 4) ambient conditions. The 51‐71 flap region exhibited drastic displacement leading to enlargement of binding cavity, especially at the lower pH. Accessibility of solvent to the active site of the mutant enzymes was also reduced. The protonation of key surface residues at low pH results in more contribution of these residues to structural stability and integrity of the enzyme and reduced interactions with solvent molecules, which acts as a cage, keeping the enzyme together. The observed results suggest a pattern of structural alterations due to point mutations in PZase, which is consistent with other experimental and theoretical investigations and, can be harnessed for drug design purposes.