HDOCK update for modeling protein-RNA/DNA complex structures

A novel multitargeted self-assembling peptide-siRNA complex for simultaneous inhibition of SARS-CoV-2-host cell interaction and replication

Effective therapeutics are necessary for managing severe COVID-19 disease despite the availability of vaccines. Small interfering RNA (siRNA) can silence viral genes and restrict SARS-CoV-2 replication. Cell-penetrating peptides is a robust method for siRNA delivery, enhancing siRNA stability and targeting specific receptors. We developed a peptide HE25 that blocks SARS-CoV-2 replication by various mechanisms, including the binding of multiple receptors involved in the virus's internalization, such as ACE2, integrins and NRP1. HE25 not only acts as a vehicle to deliver the SARS-CoV-2 RNA-dependent RNA polymerase siRNA into cells but also facilitates their internalization through endocytosis. Once inside endosomes, the siRNA is released into the cytoplasm through the Histidine-proton sponge effect and the selective cleavage of HE25 by cathepsin B. These mechanisms effectively inhibited the replication of the ancestral SARS-CoV-2 and the Omicron variant BA.5 in vitro. When HE25 was administered in vivo, either by intravenous injection or inhalation, it accumulated in lungs, veins and arteries, endothelium, or bronchial structure depending on the route. Furthermore, the siRNA/HE25 complex caused gene silencing in lung cells in vitro. The SARS-CoV-2 siRNA/HE25 complex is a promising therapeutic for COVID-19, and a similar strategy can be employed to combat future emerging viral diseases.

Targeting Monkeypox Virus Methyltransferase: Virtual Screening of Natural Compounds from Middle-Eastern Medicinal Plants

Monkeypox is an infectious disease resulting from the monkeypox virus, and its fatality rate varies depending on the virus clade and the location of the outbreak. In monkeypox virus, methyltransferase (MTase) plays a crucial role in modifying the cap structure of viral mRNA. This alteration assists the virus in evading the host's immune system, enhances viral protein synthesis, and ultimately enables successful infection and replication within host cells. Given the significance of MTase in viral infection and spread within the host, our study aimed to identify a natural inhibitor for this enzyme using docking and molecular dynamic (MD) simulations. We collected a total of 12,971 natural compounds from 200 medicinal plants in the Middle East. After eliminating duplicate compounds, we had 5,749 unique ligand conformers, which we then subjected to high-throughput virtual screening against MTase. The most promising hits were further evaluated using the extra-precision (XP) tool. The affinity of these hits was also assessed by Prime-Molecular Mechanics/Generalized Born Surface Area (MMGBSA) tool. The analysis revealed that two standard controls (sinefungin and TO1119) and two Middle-Eastern compounds (folic acid and 1,2,4,6-tetragalloylglucose) exhibited the best XP docking scores. According to Prime MMGBSA calculations, the Middle-Eastern compounds showed higher affinities, with values of - 60.61 kcal/mol for 1,2,4,6-tetragalloylglucose and - 51.87 kcal/mol for folic acid, surpassing the controls (TO1119 at - 35.71 kcal/mol and sinefungin at - 31.51 kcal/mol). In the majority of Molecular dynamic (MD) simulations, folic acid exhibited demonstrated greater stability than sinefungin. Further investigation revealed that folic acid occupied a critical position in the active site of MTase, which reduced its interaction with the mRNA substrate. Based on these findings, it can be concluded that folic acid is a highly promising natural compound for potential use in the cost-effective treatment of monkeypox virus. The identification of folic acid as a potential antiviral agent highlights the importance of nature in providing new therapeutic uses that have significant implications for global health, particularly in regions where monkeypox viral outbreaks are prevalent. However, it is essential to note that further wet-lab validations are necessary to confirm its efficacy for treatment in a medical context.

The downregulation of SCGN induced by lipotoxicity promotes NLRP3-mediated β-cell pyroptosis

Lipotoxicity is a well-established phenomenon that could exacerbate damage to islet β-cells and play a significant role in the development of type 2 diabetes, the underlying mechanisms of which, however, remain unclear. In lipotoxic conditions, secretagogin (SCGN), an EF-hand calcium-binding protein abundantly expressed in islets, is found to undergo downregulation. In light of this, we aim to explore the role of SCGN in lipotoxicity-induced β-cell injury. Our findings show that exposure to ox-LDL in vitro or long-term high-fat diets (HFD) in vivo decreases SCGN expression and induces pyroptosis in β-cells. Moreover, restoring SCGN partially reverses the pyroptotic cell death under ox-LDL or HFD treatments. We have observed that the downregulation of SCGN facilitates the translocation of ChREBP from the cytosol to the nucleus, thereby promoting TXNIP transcription. The upregulation of TXNIP activates the NLRP3/Caspase-1 pathway, leading to pyroptotic cell death. In summary, our study demonstrates that lipotoxicity leads to the downregulation of SCGN expression in islet β-cells, resulting in ChREBP accumulation in the nucleus and subsequent activation of the NLRP3/Caspase-1 pyroptotic pathway. Thus, administering SCGN could be a potential therapeutic strategy to alleviate β-cell damage induced by lipotoxicity in type 2 diabetes.

From proteome to candidate vaccines: target discovery and molecular dynamics-guided multi-epitope vaccine engineering against kissing bug

Introduction

Trypanosoma cruzi is a protozoan parasite that causes the tropical ailment known as Chagas disease, which has its origins in South America. Globally, it has a major impact on health and is transported by insect vector that serves as a parasite. Given the scarcity of vaccines and the limited treatment choices, we conducted a comprehensive investigation of core proteomics to explore a potential reverse vaccine candidate with high antigenicity.

Methods

To identify the immunodominant epitopes, T. cruzi core proteomics was initially explored. Consequently, the vaccine sequence was engineered to possess characteristics of non-allergenicity, antigenicity, immunogenicity, and enhanced solubility. After modeling the tertiary structure of the human TLR4 receptor, the binding affinities were assessed employing molecular docking and molecular dynamics simulations (MDS).

Results

Docking of the final vaccine design with TLR4 receptors revealed substantial hydrogen bond interactions. A server-based methodology for immunological simulation was developed to forecast the effectiveness against antibodies (IgM + IgG) and interferons (IFN-g). The MDS analysis revealed notable levels of structural compactness and binding stability with average RMSD of 5.03 Aring;, beta-factor 1.09e+5 Å, Rg is 44.7 Aring; and RMSF of 49.50 Aring;. This is followed by binding free energies calculation. The system stability was compromised by the complexes, as evidenced by their corresponding Gibbs free energies of -54.6 kcal/mol.

Discussion

Subtractive proteomics approach was applied to determine the antigenic regions of the T cruzi. Our study utilized computational techniques to identify B- and T-cell epitopes in the T. cruzi core proteome. In current study the developed vaccine candidate exhibits immunodominant features. Our findings suggest that formulating a vaccine targeting the causative agent of Chagas disease should be the initial step in its development.

HIPPO: HIstogram-based Pseudo-POtential for scoring protein-ssRNA fragment-based docking poses

BACKGROUND

The RNA-Recognition motif (RRM) is a protein domain that binds single-stranded RNA (ssRNA) and is present in as much as 2% of the human genome. Despite this important role in biology, RRM-ssRNA interactions are very challenging to study on the structural level because of the remarkable flexibility of ssRNA. In the absence of atomic-level experimental data, the only method able to predict the 3D structure of protein-ssRNA complexes with any degree of accuracy is ssRNA'TTRACT, an ssRNA fragment-based docking approach using ATTRACT. However, since ATTRACT parameters are not ssRNA-specific and were determined in 2010, there is substantial opportunity for enhancement.

RESULTS

Here we present HIPPO, a composite RRM-ssRNA scoring potential derived analytically from contact frequencies in near-native versus non-native docking models. HIPPO consists of a consensus of four distinct potentials, each extracted from a distinct reference pool of protein-trinucleotide docking decoys. To score a docking pose with one potential, for each pair of RNA-protein coarse-grained bead types, each contact is awarded or penalised according to the relative frequencies of this contact distance range among the correct and incorrect poses of the reference pool. Validated on a fragment-based docking benchmark of 57 experimentally solved RRM-ssRNA complexes, HIPPO achieved a threefold or higher enrichment for half of the fragments, versus only a quarter with the ATTRACT scoring function. In particular, HIPPO drastically improved the chance of very high enrichment (12-fold or higher), a scenario where the incremental modelling of entire ssRNA chains from fragments becomes viable. However, for the latter result, more research is needed to make it directly practically applicable. Regardless, our approach already improves upon the state of the art in RRM-ssRNA modelling and is in principle extendable to other types of protein-nucleic acid interactions.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Thermo-reversible self-assembled novel gellan gum hydrogels containing amino acid biogelators with antibacterial activity

In recent years, hydrogels derived from natural polymers have gained considerable attention. However, lack of mechanical strength and poor stability has become major lacuna of such systems. Scientists have attempted to resolve this problem by introducing chemical cross-linkers or synthetic modifications of natural polymers. In contrast, biological cross-linkers may be more beneficial due to their cytocompatibility and non-immunogenicity. As a biogelator, amino acids (AA) may be lucrative, yet they remain untapped till date. Present study, for the first time, reports exploitation of ʟ-Lysine, ʟ-Arginine, ʟ-Aspartic acid, and ʟ-Glutamic acid as biogelator to fabricate novel gellan gum (GG) hydrogels through green chemistry. Furthermore, as a first instance, molecular docking was applied to gain insight into the interaction between GG and AA. As predicted through docking, physical cross-linking of these hydrogels accounted for their thermo-reversibility. Moreover, to assess the suitability of prepared hydrogel for its intended use, systematic characterization studies were performed via FTIR, Raman spectroscopy, XRD, FE-SEM, and TGA. Additionally, rheological behavior of hydrogels was investigated using variety of parameters. Interestingly, GG-AA hydrogels exhibited around 99 % antibacterial activity against multidrug-resistant bacteria. According to the findings of this study, these novel hydrogels may have immense potential in the food and biomedical sectors.

Novel enzyme-linked aptamer-antibody sandwich assay and hybrid lateral flow strip for SARS-CoV-2 detection

We have successfully generated oligonucleotide aptamers (Apts) and monoclonal antibodies (mAbs) targeting the recombinant nucleocapsid (N) protein of SARS-CoV-2. Apts were obtained through seven rounds of systematic evolution of ligands by exponential enrichment (SELEX), while mAbs were derived from the 6F6E11 hybridoma cell line. Leveraging these Apts and mAbs, we have successfully devised two innovative and remarkably sensitive detection techniques for the rapid identification of SARS-CoV-2 N protein in nasopharyngeal samples: the enzyme-linked aptamer-antibody sandwich assay (ELAAA) and the hybrid lateral flow strip (hybrid-LFS). ELAAA exhibited an impressive detection limit of 0.1 ng/mL, while hybrid-LFS offered a detection range of 0.1 - 0.5 ng/mL. In the evaluation using ten nasopharyngeal samples spiked with known N protein concentrations, ELAAA demonstrated an average recovery rate of 92%. Additionally, during the assessment of five nasopharyngeal samples from infected individuals and ten samples from healthy volunteers, hybrid-LFS displayed excellent sensitivity and specificity. Our study introduces a novel and efficient on-site approach for SARS-CoV-2 detection in nasopharyngeal samples. The reliable hybrid Apt-mAb strategy not only advances virus diagnostic methods but also holds promise in combating the spread of related diseases.

Structure-Function Analysis of RBP7910: An Editosome Z-Binding Protein in Trypanosomatids

RNA editing, a unique post-transcriptional modification, is observed in trypanosomatid parasites as a crucial procedure for the maturation of mitochondrial mRNAs. The editosome protein complex, involving multiple protein components, plays a key role in this process. In Trypanosoma brucei, a putative Z-DNA binding protein known as RBP7910 is associated with the editosome. However, the specific Z-DNA/Z-RNA binding activity and the interacting interface of RBP7910 have yet to be determined. In this study, we conducted a comparative analysis of the binding behavior of RBP7910 with different potential ligands using microscale thermophoresis (MST). Additionally, we generated a 3D model of the protein, revealing potential Z-α and Z-β nucleic acid-binding domains of RBP7910. RBP7910 belongs to the winged-helix-turn-helix (HTH) superfamily of proteins with an α1α2α3β1β2 topology. Finally, using docking techniques, potential interacting surface regions of RBP7910 with notable oligonucleotide ligands were identified. Our findings indicate that RBP7910 exhibits a notable affinity for (CG)n Z-DNA, both in single-stranded and double-stranded forms. Moreover, we observed a broader interacting interface across its Z-α domain when bound to Z-DNA/Z-RNA compared to when bound to non-Z-form nucleic acid ligands.

Challenges in structural modeling of RNA-protein interactions

In the past few years, the number of RNA-binding proteins (RBP) and RNA-RBP interactions has increased significantly. Here, we review recent developments in the methodology for protein-RNA and protein-protein complex structure modeling with deep learning and co-evolution, as well as discuss the challenges and opportunities for building a reliable approach for protein-RNA complex structure modelling. Protein Data bank (PDB) and Cross-linking immunoprecipitation (CLIP) data could be combined together and used to infer 2D geometry of protein-RNA interactions by deep learning.