The Malaria Box molecules: a source for targeting the RBD and NTD cryptic pocket of the spike glycoprotein in SARS-CoV-2.

CONTEXT: SARS-CoV-2, responsible for COVID-19, has led to over 500 million infections and more than 6 million deaths globally. There have been limited effective treatments available. The study aims to find a drug that can prevent the virus from entering host cells by targeting specific sites on the virus's spike protein. METHOD: We examined 13,397 compounds from the Malaria Box library against two specific sites on the spike protein: the receptor-binding domain (RBD) and a predicted cryptic pocket. Using virtual screening, molecular docking, molecular dynamics, and MMPBSA techniques, they evaluated the stability of two compounds. TCMDC-124223 showed high stability and binding energy in the RBD, while TCMDC-133766 had better binding energy in the cryptic pocket. The study also identified that the interacting residues are conserved, which is crucial for addressing various virus variants. The findings provide insights into the potential of small molecules as drugs against the spike protein.

Potential use of sludge from El Ferrol Bay (Chimbote, Peru) for the production of lipids in the culture of Scenedesmus acutus (Meyen, 1829).

Despite the extensive development of microalgae biotechnology, it still requires new methodologies to lower production costs, especially in the field of biofuel production. Therefore, innovative methods that facilitate operations and enable cost-effective production are important in driving this industry. In this study, we propose a new low-cost and easy-to-use procedure, addressed to the generation of a culture medium for Scenedesmus acutus. The medium was obtained by thermal reduction of a sludge sample from El Ferrol Bay (Chimbote, Peru), whereby we obtained an aqueous medium. Our results indicated that the aqueous medium incorporates all necessary nutrients for microalgae production; allowing a maximum biomass of 0.75 ± 0.07 g/L with 60% of the medium; while high lipids production (59.42 ± 6.16%) was achieved with 20%. Besides, we quantified, in the experimental medium and at the end of the cultures, the levels of inorganic nutrients such as ammonium, nitrites, nitrates, and phosphates; in addition to COD and TOC, which were significantly reduced ( p < 0.05) after 7 days of culture, mainly in the treatment with 20%. These results suggest tremendous potential for sludge reuse, which also entails a cost reduction in microalgae biomass production, with additional positive impacts on large-scale application over highly polluted environments.

Glycosylation is key for enhancing drug recognition into spike glycoprotein of SARS-CoV-2.

The emergence of COVID-19 caused by SARS-CoV-2 and its spread since 2019 represents the major public health problem worldwide nowadays, which has generated a high number of infections and deaths. The spike protein (S protein) is the most studied protein of SARS-CoV-2, and key to host-cell entry through ACE2 receptor. This protein presents a large pattern of glycosylations with important roles in immunity and infection mechanisms. Therefore, understanding key aspects of the molecular mechanisms of these structures, during drug recognition in SARS-CoV-2, may contribute to therapeutic alternatives. In this work, we explored 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.

Comprehensive virtual screening of 4.8 k flavonoids reveals novel insights into allosteric inhibition of SARS-CoV-2 MPRO.

SARS-CoV-2 main protease is a common target for inhibition assays due to its high conservation among coronaviruses. Since flavonoids show antiviral activity, several in silico works have proposed them as potential SARS-CoV-2 main protease inhibitors. Nonetheless, there is reason to doubt certain results given the lack of consideration for flavonoid promiscuity or main protease plasticity, usage of short library sizes, absence of control molecules and/or the limitation of the methodology to a single target site. Here, we report a virtual screening study where dorsilurin E, euchrenone a11, sanggenol O and CHEMBL2171598 are proposed to inhibit main protease through different pathways. Remarkably, novel structural mechanisms were observed after sanggenol O and CHEMBL2171598 bound to experimentally proven allosteric sites. The former drastically affected the active site, while the latter triggered a hinge movement which has been previously reported for an inactive SARS-CoV main protease mutant. The use of a curated database of 4.8 k flavonoids, combining two well-known docking software (AutoDock Vina and AutoDock4.2), molecular dynamics and MMPBSA, guaranteed an adequate analysis and robust interpretation. These criteria can be considered for future screening campaigns against SARS-CoV-2 main protease.

Potential novel inhibitors against emerging zoonotic pathogen Nipah virus: a virtual screening and molecular dynamics approach.

Nipah virus is a pathogen considered highly infectious, and its lethality can cause between 40% and 70% of deaths in those infected. At present, no effective treatment is available which results in an imperative need to explore new approaches to the search for drugs. Through virtual screening techniques, docking and molecular dynamics, 183 ligands were evaluated against the Nipah virus glycoprotein (NiV-G), involved throughout the process of virus entry to the host cell, resulting in a good target for blocking the infection. Of the 183 drugs computationally screened, three of them (MMV020537, MMV688888 and MMV019838) were found to be potential inhibitors of NiV-G. Their calculated dissociation constants were 0.03 nM, 2.18 nM and 31.61 nM, respectively. Molecular dynamics studies confirm their stability binding modes in the active site of the protein. These potential inhibitors can be used later as leads for the development of new drugs that allow effective treatment of the disease.Communicated by Ramaswamy H. Sarma.

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

BACKGROUND: Pyrazinamide 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. OBJECTIVE: To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene. METHODS: We 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. RESULTS: The 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. CONCLUSIONS: This 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.

Novel multi-epitope protein containing conserved epitopes from different Leishmania species as potential vaccine candidate: Integrated immunoinformatics and molecular dynamics approach.

Leishmaniosis, caused by intracellular parasites of the genus Leishmania, has become a serious public health problem around the world, and for which there are currently extensive limitations. In this work, a theoretical model was proposed for the development of a multi-epitope vaccine. The protein GP63 of the parasite was selected for epitopes prediction, due to its important biological role for the infection process and abundance. IEDB tools were used to determine epitopes B and T in Leishmania braziliensis; besides, other conserved epitopes in three species were selected. To improve immunogenicity, 50S ribosomal protein L7 / L12 (ID: P9WHE3) was used as a domain of adjuvant in the assembly process. The folding arrangement of the vaccine was obtained through homologous modeling multi-template with MODELLER v9.21, and a Ramachandran plot analysis was done. Furthermore, physicochemical properties were described with the ProtParam tool and secondary structure prediction combining GOR-IV and SOPMA tools. Finally, a molecular dynamics simulation (50 ns) was performed to establish flexibility and conformational changes. The analysis of the results indicates high conservancy in the epitopes predicted among the four species. Moreover, Ramachandran plot, physicochemical parameters, and secondary structure prediction suggest a stable conformation of the vaccine, after a minimum conformational change that was evaluated with the free energy landscape. The conformational change does not drive any substantial change for epitope exposition on the surface. The vaccine proposed could be tested experimentally to guide new approaches in the development of pan-vaccines; vaccines with regions conserved in multiple species.