1,2,4-Oxadiazole Derivatives: Physicochemical Properties, Antileishmanial Potential, Docking and Molecular Dynamic Simulations of Leishmania infantum Target Proteins.

Visceral leishmaniasis (VL), caused by protozoa of the genus Leishmania, remains a significant public health concern due to its potentially lethal nature if untreated. Current chemotherapy options are limited by severe toxicity and drug resistance. Derivatives of 1,2,4-oxadiazole have emerged as promising drug candidates due to their broad biological activity. This study investigated the effects of novel 1,2,4-oxadiazole derivatives (Ox1-Ox7) on Leishmania infantum, the etiological agent of VL. In silico predictions using SwissADME suggest that these compounds have high oral absorption and good bioavailability. Among them, Ox1 showed the most promise, with higher selectivity against promastigotes and lower cytotoxicity towards L929 fibroblasts and J774.G8 macrophages. Ox1 exhibited selectivity indices of 18.7 and 61.7 against L. infantum promastigotes and amastigotes, respectively, compared to peritoneal macrophages. Ultrastructural analyses revealed severe morphological damage in both parasite forms, leading to cell death. Additionally, Ox1 decreased the mitochondrial membrane potential in promastigotes, as shown by flow cytometry. Molecular docking and dynamic simulations indicated a strong affinity of Ox1 for the L. infantum CYP51 enzyme. Overall, Ox1 is a promising and effective compound against L. infantum.

Structure-based computational design of antibody mimetics: challenges and perspectives.

The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure-based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen-binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein-protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high-throughput computer design of antibody mimetics and experimental realization, offering a forward-looking perspective into the field and the promises it holds to biotechnology.

Identification and characterization of a nonbiological small-molecular mimic of a Zika virus conformational neutralizing epitope.

Antigenic similarities between Zika virus (ZIKV) and other flaviviruses pose challenges to the development of virus-specific diagnostic tools and effective vaccines. Starting with a DNA-encoded one-bead-one-compound combinatorial library of 508,032 synthetic, non-natural oligomers, we selected and characterized small molecules that mimic ZIKV epitopes. High-throughput fluorescence-activated cell sorter-based bead screening was used to select molecules that bound IgG from ZIKV-immune but not from dengue-immune sera. Deep sequencing of the DNA from the "Zika-only" beads identified 40 candidate molecular structures. A lead candidate small molecule "CZV1-1" was selected that correctly identifies serum specimens from Zika-experienced patients with good sensitivity and specificity (85.3% and 98.4%, respectively). Binding competition studies of purified anti-CZV1-1 IgG against known ZIKV-specific monoclonal antibodies (mAbs) showed that CZV1-1 mimics a nonlinear, neutralizing conformational epitope in the domain III of the ZIKV envelope. Purified anti-CZV1-1 IgG neutralized infection of ZIKV in cell cultures with potencies comparable to highly specific ZIKV-neutralizing mAbs. This study demonstrates an innovative approach for identification of synthetic non-natural molecular mimics of conformational virus epitopes. Such molecular mimics may have value in the development of accurate diagnostic assays for Zika, as well as for other viruses.

A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers.

The main-protease (Mpro) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (MCoV2pro) with 12 mutations compared to SARS-CoV (MCoV1pro). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications. We use metadynamics simulations and a sort of computational analysis to probe the dynamic, pharmacophoric and catalytic environment differences between the monomers of both enzymes. So, we verify how much intrinsic distinctions are preserved in the functional dimer of MCoV2pro, as well as its implications for ligand accessibility and optimized drug screening. We find a significantly higher accessibility to open binding conformers in the MCoV2pro monomer compared to MCoV1pro. A higher hydration propensity for the MCoV2pro S2 loop with the A46S substitution seems to exercise a key role. Quantum calculations suggest that the wider conformations for MCoV2pro are less catalytically active in the monomer. However, the statistics for contacts involving the N-finger suggest higher maintenance of this activity at the dimer. Docking analyses suggest that the ability to vary the active site width can be important to improve the access of the ligand to the active site in different ways. So, we carry out a multiconformational virtual screening with different ligand bases. The results point to the importance of taking into account the protein conformational multiplicity for new promissors anti MCoV2pro ligands. We hope these results will be useful in prospecting, repurposing and/or designing new anti SARS-CoV-2 drugs.Communicated by Ramaswamy H. Sarma.

Determining the Relative Binding Affinity of Ricin Toxin A Inhibitors by Using Molecular Docking and Nonequilibrium Work.

Ricin is a ribosome-inactivating protein (RIP type 2) consisting of two subunits, ricin toxin A (RTA) and ricin toxin B (RTB). Because of its cytotoxicity, ricin has worried world authorities for its potential use as a chemical weapon; therefore, its inhibition is of great biotechnological interest. RTA is the target for inhibitor synthesis, and pterin derivatives are promising candidates to inhibit it. In this study, we used a combination of the molecular docking approach and fast steered molecular dynamics (SMD) to assess the correlation between nonequilibrium work, ⟨ W⟩, and the IC50 for six RTA inhibitors. The results showed that molecular docking is a powerful tool to predict good bioactive poses of RTA inhibitors, and ⟨ W⟩ presented a strong correlation with IC50 ( R2 = 0.961). Such a profile ranked the RTA inhibitors better than the molecular docking approach. Therefore, the combination of docking and fast SMD simulation was shown to be a promising tool to distinguish RTA-active inhibitors from inactive ones and could be used as postdocking filtering approach.