Essential roles in biological systems depend on protein-ligand recognition, which is mostly driven by specific non-covalent interactions. Consequently, investigating these interactions contributes to understanding how molecular recognition occurs. Nowadays, a large-scale data set of protein-ligand complexes is available in the Protein Data Bank, what led several tools to be proposed as an effort to elucidate protein-ligand interactions. Nonetheless, there is not an all-in-one tool that couples large-scale statistical, visual, and interactive analysis of conserved protein-ligand interactions. Therefore, we propose nAPOLI (Analysis of PrOtein-Ligand Interactions), a web server that combines large-scale analysis of conserved interactions in protein-ligand complexes at the atomic-level, interactive visual representations, and comprehensive reports of the interacting residues/atoms to detect and explore conserved non-covalent interactions. We demonstrate the potential of nAPOLI in detecting important conserved interacting residues through four case studies: two involving a human cyclin-dependent kinase 2 (CDK2), one related to ricin, and other to the human nuclear receptor subfamily 3 (hNR3). nAPOLI proved to be suitable to identify conserved interactions according to literature, as well as highlight additional interactions. Finally, we illustrate, with a virtual screening ligand selection, how nAPOLI can be widely applied in structural biology and drug design. nAPOLI is freely available at bioinfo.dcc.ufmg.br/napoli/.

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products. In this study, we present a method, called structural signature variation (SSV), to propose mutations for improving enzymes’ activity. SSV uses the structural signature variation between target enzymes and template enzymes (obtained from the literature) to determine if randomly suggested mutations may provide some benefit for an enzyme, such as improvement of catalytic activity, half-life, and thermostability, or resistance to inhibition. To evaluate SSV, we carried out a case study that suggested mutations in β-glucosidases: Essential enzymes used in biofuel production that suffer inhibition by their product. We collected 27 mutations described in the literature, and manually classified them as beneficial or not. SSV was able to classify the mutations with values of 0.89 and 0.92 for precision and specificity, respectively. Then, we used SSV to propose mutations for Bgl1B, a low-performance β-glucosidase. We detected 15 mutations that could be beneficial. Three of these mutations (H228C, H228T, and H228V) have been related in the literature to the mechanism of glucose tolerance and stimulation in GH1 β-glucosidase. Hence, SSV was capable of detecting promising mutations, already validated by in vitro experiments, that improved the inhibition resistance of a β-glucosidase and, consequently, its catalytic activity. SSV might be useful for the engineering of enzymes used in biofuel production or other industrial applications.

The Hemiscorpius lepturus scorpion and brown spider Loxosceles intermedia represent a public health problem in Asia and America, respectively. Although distinct, these organisms contain similar toxins responsible for the principal clinical signs of envenomation. To better understand the properties of these toxins, we designed a study to compare recombinant Heminecrolysin (rHNC) and rLiD1, the major phospholipase D toxins of scorpion and spider venom, respectively. Using a competitive ELISA and a hemolytic inhibition test, we come to spot a cross reaction between scorpion and spider venoms along with an epitopic similarity between rHNC and rLiD1 associated with neutralizing antibodies. Results show that the ability of the rHNC to hydrolyze lysophosphatidylcholine (LPC) is equivalent to that of rLiD1 to hydrolyze sphingomyelin and vice-versa. rHNC exclusively catalyze transphosphatidylation of LPC producing cyclic phosphatidic acid (cPA). The in-silico analysis of hydrogen bonds between LPC and toxins provides a possible explanation for the higher transphosphatidylase activity of rHNC. Interestingly, for the first time, we reveal that lysophosphatidic acid (LPA) can be a substrate for both enzymes using cellular and enzymatic assays. The finding of the usage of LPA as a substrate as well as the formation of cPA as an end product could shed more light on the molecular basis of Hemiscorpius lepturus envenomation as well as on loxoscelism.

The NS2B-NS3 protease (NS2B-NS3pro) is regarded as an interesting molecular target for drug design, discovery, and development because of its essential role in the Zika virus (ZIKV) cycle. Although no NS2B-NS3pro inhibitors have reached clinical trials, the employment of drug-like scaffolds can facilitate the screening process for new compounds. In this study, we performed a combination of ligand-based and structure-based in silico methods targeting two known non-peptide small-molecule scaffolds with micromolar inhibitory activity against ZIKV NS2B-NS3pro by a virtual screening (VS) of promising compounds. Based on these two scaffolds, we selected 13 compounds from an initial library of 509 compounds from ZINC15’s similarity search. These compounds exhibited structural modifications that are distinct from previously known compounds yet keep pertinent features for binding. Despite promising outcomes from molecular docking and initial enzymatic assays against NS2B-NS3pro, confirmatory assays with a counter-screening enzyme revealed an artifactual inhibition of the assessed compounds. However, we report two compounds, 9 and 11, that exhibited antiviral properties at a concentration of 50 μM in cellular-based assays. Overall, this study provides valuable insights into the ongoing research on anti-ZIKV compounds to facilitate and improve the development of new inhibitors.

Mutation in the ethionamide (ETH) activating enzyme, EthA, is the main factor determining resistance to this drug, used to treat TB patients infected with MDR and XDR Mycobacterium tuberculosis isolates. Many mutations in EthA of ETH resistant (ETH-R) isolates have been described but their roles in resistance remain uncharacterized, partly because structural studies on the enzyme are lacking. Thus, we took a two-tier approach to evaluate two mutations (Y50C and T453I) found in ETH-R clinical isolates. First, we used a combination of comparative modeling, molecular docking, and molecular dynamics to build an EthA model in complex with ETH that has hallmark features of structurally characterized homologs. Second, we used free energy computational calculations for the reliable prediction of relative free energies between the wild type and mutant enzymes. The ΔΔG values for Y50C and T453I mutant enzymes in complex with FADH₂-NADP-ETH were 3.34 (+/−0.55) and 8.11 (+/−0.51) kcal/mol, respectively, compared to the wild type complex. The positive ΔΔG values indicate that the wild type complex is more stable than the mutants, with the T453I complex being the least stable. These are the first results shedding light on the molecular basis of ETH resistance, namely reduced complex stability of mutant EthA.

The spread of antibiotic-resistant bacteria represents a substantial health threat. Current antibiotics act on a few metabolic pathways, facilitating resistance. Consequently, novel regulatory inhibition mechanisms are necessary. Riboswitches represent promising targets for antibacterial drugs. Purine riboswitches are interesting, since they play essential roles in the genetic regulation of bacterial metabolism. Among these, class I (2′-dG-I) and class II (2′-dG-II) are two different 2′-deoxyguanosine (2′-dG) riboswitches involved in the control of deoxyguanosine metabolism. However, high affinity for nucleosides involves local or distal modifications around the ligand-binding pocket, depending on the class. Therefore, it is crucial to understand these riboswitches’ recognition mechanisms as antibiotic targets. In this work, we used a combination of computational biophysics approaches to investigate the structure, dynamics, and energy landscape of both 2′-dG classes bound to the nucleoside ligands, 2′-deoxyguanosine, and riboguanosine. Our results suggest that the stability and increased interactions in the three-way junction of 2′-dG riboswitches were associated with a higher nucleoside ligand affinity. Also, structural changes in the 2′-dG-II aptamers enable enhanced intramolecular communication. Overall, the 2′-dG-II riboswitch might be a promising drug design target due to its ability to recognize both cognate and noncognate ligands.