A Comparative Analysis of SARS-CoV-2 Variants of Concern (VOC) Spike Proteins Interacting with hACE2 Enzyme.

In late 2019, the emergence of a novel coronavirus led to its identification as SARS-CoV-2, precipitating the onset of the COVID-19 pandemic. Many experimental and computational studies were performed on SARS-CoV-2 to understand its behavior and patterns. In this research, Molecular Dynamic (MD) simulation is utilized to compare the behaviors of SARS-CoV-2 and its Variants of Concern (VOC)-Alpha, Beta, Gamma, Delta, and Omicron-with the hACE2 protein. Protein structures from the Protein Data Bank (PDB) were aligned and trimmed for consistency using Chimera, focusing on the receptor-binding domain (RBD) responsible for ACE2 interaction. MD simulations were performed using Visual Molecular Dynamics (VMD) and Nanoscale Molecular Dynamics (NAMD2), and salt bridges and hydrogen bond data were extracted from the results of these simulations. The data extracted from the last 5 ns of the 10 ns simulations were visualized, providing insights into the comparative stability of each variant's interaction with ACE2. Moreover, electrostatics and hydrophobic protein surfaces were calculated, visualized, and analyzed. Our comprehensive computational results are helpful for drug discovery and future vaccine designs as they provide information regarding the vital amino acids in protein-protein interactions (PPIs). Our analysis reveals that the Original and Omicron variants are the two most structurally similar proteins. The Gamma variant forms the strongest interaction with hACE2 through hydrogen bonds, while Alpha and Delta form the most stable salt bridges; the Omicron is dominated by positive potential in the binding site, which makes it easy to attract the hACE2 receptor; meanwhile, the Original, Beta, Delta, and Omicron variants show varying levels of interaction stability through both hydrogen bonds and salt bridges, indicating that targeted therapeutic agents can disrupt these critical interactions to prevent SARS-CoV-2 infection.

AI-Driven Deep Learning Techniques in Protein Structure Prediction.

Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the computational models used in predicting protein structure. It covers the progression from established protein modeling to state-of-the-art artificial intelligence (AI) frameworks. The paper will start with a brief introduction to protein structures, protein modeling, and AI. The section on established protein modeling will discuss homology modeling, ab initio modeling, and threading. The next section is deep learning-based models. It introduces some state-of-the-art AI models, such as AlphaFold (AlphaFold, AlphaFold2, AlphaFold3), RoseTTAFold, ProteinBERT, etc. This section also discusses how AI techniques have been integrated into established frameworks like Swiss-Model, Rosetta, and I-TASSER. The model performance is compared using the rankings of CASP14 (Critical Assessment of Structure Prediction) and CASP15. CASP16 is ongoing, and its results are not included in this review. Continuous Automated Model EvaluatiOn (CAMEO) complements the biennial CASP experiment. Template modeling score (TM-score), global distance test total score (GDT_TS), and Local Distance Difference Test (lDDT) score are discussed too. This paper then acknowledges the ongoing difficulties in predicting protein structure and emphasizes the necessity of additional searches like dynamic protein behavior, conformational changes, and protein-protein interactions. In the application section, this paper introduces some applications in various fields like drug design, industry, education, and novel protein development. In summary, this paper provides a comprehensive overview of the latest advancements in established protein modeling and deep learning-based models for protein structure predictions. It emphasizes the significant advancements achieved by AI and identifies potential areas for further investigation.

Multi-omic analysis shows REVEILLE clock genes are involved in carbohydrate metabolism and proteasome function.

Plants are able to sense changes in their light environments, such as the onset of day and night, as well as anticipate these changes in order to adapt and survive. Central to this ability is the plant circadian clock, a molecular circuit that precisely orchestrates plant cell processes over the course of a day. REVEILLE (RVE) proteins are recently discovered members of the plant circadian circuitry that activate the evening complex and PSEUDO-RESPONSE REGULATOR genes to maintain regular circadian oscillation. The RVE8 protein and its two homologs, RVE 4 and 6 in Arabidopsis (Arabidopsis thaliana), have been shown to limit the length of the circadian period, with rve 4 6 8 triple-knockout plants possessing an elongated period along with increased leaf surface area, biomass, cell size, and delayed flowering relative to wild-type Col-0 plants. Here, using a multi-omics approach consisting of phenomics, transcriptomics, proteomics, and metabolomics we draw new connections between RVE8-like proteins and a number of core plant cell processes. In particular, we reveal that loss of RVE8-like proteins results in altered carbohydrate, organic acid, and lipid metabolism, including a starch excess phenotype at dawn. We further demonstrate that rve 4 6 8 plants have lower levels of 20S proteasome subunits and possess significantly reduced proteasome activity, potentially explaining the increase in cell-size observed in RVE8-like mutants. Overall, this robust, multi-omic dataset provides substantial insight into the far-reaching impact RVE8-like proteins have on the diel plant cell environment.

Arabidopsis RING-type E3 ubiquitin ligase XBAT35.2 promotes proteasome-dependent degradation of ACD11 to attenuate abiotic stress tolerance.

Plants employ multiple mechanisms to cope with a constantly changing and challenging environment, including using the ubiquitin proteasome system (UPS) to alter their proteome to assist in initiating, modulating and terminating responses to stress. We previously reported that the ubiquitin ligase XBAT35.2 mediates the proteasome-dependent degradation of Accelerated Cell Death 11 (ACD11) to promote pathogen defense. Here, we demonstrate roles for XBAT35.2 and ACD11 in abiotic stress tolerance. As seen in response to pathogen infection, abiotic stress stabilizes XBAT35.2 and the abundance of ACD11 rose consistently with increasing concentrations of abscisic acid (ABA) and salt. Surprisingly, exposure to ABA and salt increased the stability of ACD11, and the overexpression of ACD11 improves plant survival of salt and drought stress, suggesting a role for ACD11 in promoting tolerance. Prolonged exposure to high concentrations of ABA or salt resulted in ubiquitination and the proteasome-dependent degradation of ACD11, however. The stress-induced turnover of ACD11 requires XBAT35.2, as degradation is slowed in the absence of the E3 ubiquitin ligase. Consistent with XBAT35.2 mediating the proteasome-dependent degradation of ACD11, the loss of E3 ubiquitin ligase function enhances the tolerance of salt and drought stress, whereas overexpression increases sensitivity. A model is presented where, upon the perception of abiotic stress, ACD11 abundance increases to promote tolerance. Meanwhile, XBAT35.2 accumulates and in turn promotes the degradation of ACD11 to attenuate the stress response. The results characterize XBAT35.2 as an E3 ubiquitin ligase with opposing roles in abiotic and biotic stress.

Cloning and characterization of ovine immunoglobulin G Fc receptor II (FcgammaRII).

Immunoglobulin G (IgG) Fc receptors (FcgammaRs) bind to immune complexes through interactions with the Fc region of IgG to initiate or inhibit the defense mechanism of the leukocytes on which they are expressed. In this study, we describe the cloning, sequencing and characterization of ovine FcgammaRII. By screening a translated expression sequence tag (EST) database with the protein sequence of bovine IgG Fc receptor II, we identified a putative ovine homologue. Using rapid amplification of cDNA ends (RACE), we isolated the cDNA encoding ovine FcgammaRII from peripheral blood leucocyte RNA. The ovine FcgammaRII cDNA contains an 894bp open-reading frame, encoding a 297 amino acid transmembrane glycoprotein composed of two immunoglobulin-like extracellular domains, a transmembrane region and a cytoplasmic tail with an immunoreceptor tyrosine-based inhibitory motif (ITIM). The glycoprotein encoded by the cloned cDNA was then expressed on the surface of COS-7 cells and immunoglobulin-binding assays show that it binds ovine IgG1, but not IgG2. Identification of the ovine FcgammaRII will aid in the understanding of the molecular basis of IgG-FcgammaR interaction.

A hybrid promoter-containing vector for direct cloning and enhanced expression of PCR-amplified ORFs in mammalian cells.

An efficient vector, designated as pCAGX, was designed for direct cloning and enhanced expression of PCR-amplified ORFs in mammalian cells. It relied on the well-known TA-cloning principle, and utilized the CMV enhancer/chicken beta-actin/rabbit beta-globin (CAG) hybrid promoter instead of the classical CMV promoter to drive more efficient transgene expression in wider host cells. The specially designed cassette under CAG hybrid promoter contained two tandemly arrayed XcmI sites which were spaced by an additional EcoRV site. For direct cloning and expressing PCR-amplified ORFs, the T-vector was prepared by further digesting the EcoRV-linearized pCAGX with XcmI to produce T tails on both 3'-ends, which could efficiently minimize the non-recombinant background of T-vector and eliminate the necessity of selective marker genes such as LacZ that allowed blue/white screening. Various PCR fragments in length were prepared to verify the cloning efficiency by ligation with this vector, and GFP gene expression under control of the CAG hybrid promoter in different host cells was assayed by flow cytometry. The results indicated that this vector was higher efficient, especially suitable for cloning and expressing a number of interesting ORFs in parallel, and higher-level transgene expression in different mammalian cells was obtained than the reported vectors using the CMV promoter.