How good is automated protein docking?

Dengue Virus dependence on glucokinase activity and glycolysis Confers Sensitivity to NAD(H) biosynthesis inhibitors

Viruses have developed sophisticated strategies to control metabolic activity of infected cells in order to supply replication machinery with energy and metabolites. Dengue virus (DENV), a mosquito-borne flavivirus responsible for dengue fever, is no exception. Previous reports have documented DENV interactions with metabolic pathways and shown in particular that glycolysis is increased in DENV-infected cells. However, underlying molecular mechanisms are still poorly characterized and dependence of DENV on this pathway has not been investigated in details yet. Here, we identified an interaction between the non-structural protein 3 (NS3) of DENV and glucokinase regulator protein (GCKR), a host protein that inhibits the liver-specific hexokinase GCK. NS3 expression was found to increase glucose consumption and lactate secretion in hepatic cell line expressing GCK. Interestingly, we observed that GCKR interaction with GCK decreases DENV replication, indicating the dependence of DENV to GCK activity and supporting the role of NS3 as an inhibitor of GCKR function. Accordingly, in the same cells, DENV replication both induces and depends on glycolysis. By targeting NAD(H) biosynthesis with the antimetabolite 6-Amino-Nicotinamide (6-AN), we decreased cellular glycolytic activity and inhibited DENV replication in hepatic cells. Infection of primary organotypic liver cultures (OLiC) from hamsters was also inhibited by 6-AN. Altogether, our results show that DENV has evolved strategies to control glycolysis in the liver, which could account for hepatic dysfunctions associated to infection. Besides, our findings suggest that lowering intracellular availability of NAD(H) could be a valuable therapeutic strategy to control glycolysis and inhibit DENV replication in the liver.

Prediction of the 3D conformation of a small peptide vaccine targeting Aβ42 oligomers

The original etiology of Alzheimer's disease (AD) is the deposition of amyloid-beta (Aβ) proteins, which starts from the aggregation of the Aβ oligomers. The optimal therapeutic strategy targeting Aβ oligomer aggregation is the development of AD vaccines. Despite the fact that positive progress has been made for experimental attempts at AD vaccines, the physicochemical and even structural properties of these AD vaccines remain unclear. In this study, through immunoinformatic and molecular dynamics (MD) simulations, we first designed and simulated an alternative of vaccine TAPAS and found that the structure of the alternative can reproduce the 3D conformation of TAPAS determined experimentally. Meanwhile, immunoinformatic methods were used to analyze the physicochemical properties of TAPAS, including immunogenicity, antigenicity, thermal stability, and solubility, which confirm well the efficacy and safety of the vaccine, and validate the scheme reliability of immunoinformatic and MD simulations in designing and simulating the TAPAS vaccine. Using the same scheme, we predicted the 3D conformation of the optimized ACI-24 peptide vaccine, an Aβ peptide with the first 15 residues of Aβ42 (Aβ1-15). The vaccine was verified once to be effective against both full-length Aβ1-42 and truncated Aβ4-42 aggregates, but an experimental 3D structure was absent. We have also explored the immune mechanism of the vaccine at the molecular level and found that the optimized ACI-24 and its analogues can block the growth of either full-length Aβ1-42 or truncated Aβ4-42 pentamer by contacting the hydrophobic residues within the N-terminus and β1 region on the contact surface of either pentamer. Additionally, residues (D1, D7, S8, H13, and Q15) were identified as the key residues of the vaccine to contact either of the two Aβ oligomers. This work provides a feasible implementation scheme of immunoinformatic and MD simulations for the development of AD small peptide vaccines, validating the power of the scheme as a parallel tool to the experimental approaches and injecting molecular-level information into the understanding and design of anti-AD vaccines.

Lassa virus Z protein hijacks the autophagy machinery for efficient transportation by interrupting CCT2-mediated cytoskeleton network formation

The Lassa virus (LASV) is a widely recognized virulent pathogen that frequently results in lethal viral hemorrhagic fever (VHF). Earlier research has indicated that macroautophagy/autophagy plays a role in LASV replication, but, the precise mechanism is unknown. In this present study, we show that LASV matrix protein (LASV-Z) is essential for blocking intracellular autophagic flux. LASV-Z hinders actin and tubulin folding by interacting with CCT2, a component of the chaperonin-containing T-complexes (TRiC). When the cytoskeleton is disrupted, lysosomal enzyme transit is hampered. In addition, cytoskeleton disruption inhibits the merge of autophagosomes with lysosomes, resulting in autophagosome accumulation that promotes the budding of LASV virus-like particles (VLPs). Inhibition of LASV-Z-induced autophagosome accumulation blocks the LASV VLP budding process. Furthermore, it is found that glutamine at position 29 and tyrosine at position 48 on LASV-Z are important in interacting with CCT2. When these two sites are mutated, LASV-mut interacts with CCT2 less efficiently and can no longer inhibit the autophagic flux. These findings demonstrate a novel strategy for LASV-Z to hijack the host autophagy machinery to accomplish effective transportation.Abbreviation: 3-MA: 3-methyladenine; ATG5: autophagy related 5; ATG7: autophagy related 7; Baf-A1: bafilomycin A1; CCT2: chaperonin containing TCP1 subunit 2; co-IP: co-immunoprecipitation; CTSD: cathepsin D; DAPI: 4',6-diamidino-2'-phenylindole; DMSO: dimethyl sulfoxide; EGFR: epidermal growth factor receptor; GFP: green fluorescent protein; hpi: hours post-infection; hpt: hours post-transfection; LAMP1: lysosomal-associated membrane protein 1; LASV: lassa virus; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; mCherry: red fluorescent protein; PM: plasma membrane; SQSTM1/p62: sequestosome 1; STX6: syntaxin 6; VLP: virus-like particle; TEM: transmission electron microscopy; TRiC: chaperonin-containing T-complex; WB: western blotting; μm: micrometer; μM: micromole.

Erlotinib Treatment in Colorectal Cancer Suppresses Autophagy Based on KRAS Mutation

The KRAS gene is mutated in approximately 45% of colorectal cancer patients. There are currently very few targeted treatments or therapies equipped to directly inhibit KRAS due to its unusual structural intricacies. Erlotinib, an EGFR inhibitor, has previously been demonstrated to reduce cell viability by inducing autophagy in lung cancer cell lines with varying EGFR mutations. In contrast to lung cancer cells, evidence is provided herein for the first time that erlotinib treatment in colorectal cancer (CRC) cell lines reduces autophagy and still results in decreased cell viability. However, the effects of erlotinib in CRC cell lines containing a wildtype KRAS gene were different than in cells carrying a mutant KRAS gene. We show that there is significantly more downregulation of autophagy in KRAS mutant CRC cells compared to KRAS wildtype cells, both at transcriptional and translational levels, suggesting that the KRAS mutation is advantageous for cancer growth, even in the presence of erlotinib. Cell viability results determined that KRAS wildtype CRC cells had significantly more cell death compared to KRAS mutant cells. Using patient mRNA datasets, we showed that there was a significant correlation between the presence of the KRAS mutation and the expression of autophagy proteins. Additionally, through molecular dynamics simulations, we develop a blueprint for KRAS and autophagy protein interaction and the impact of the KRAS mutation on autophagy protein regulation. Overall, this is the first report of erlotinib treatment in CRC cells that assesses autophagy, and we demonstrate that autophagy activity is downregulated in these cells. This effect is not only greater in cells carrying a KRAS mutation compared to wildtype cells, but the KRAS mutant cells also have increased cell viability compared to wildtype cells. We hypothesize that the difference in cell viability and autophagy expression between KRAS mutant and KRAS wildtype cells after treatment with erlotinib can be of therapeutic value to treat CRC patients carrying KRAS mutations.

Super epitope dengue vaccine instigated serotype independent immune protection in-silico

Dengue becomes the most common life-threatening infectious arbovirus disease globally, with prevalence in the tropical and subtropical areas. The major clinical features include dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS), a condition of hypovolemic shock. Four different serotypes of the dengue virus, known as dengue virus serotype (DENV)- 1, 2, 3 and 4 can infect humans. Only one vaccine is available in the market, named Dengvaxia by Sanofi Pasteur, but there is no desired outcome of this treatment due the antibody dependent enhancement (ADE) of the multiple dengue serotypes. As of now, there is no cure against dengue disease. Our goal in this work was to create a subunit vaccine based on several epitopes that would be effective against every serotype of the dengue virus. Here, computational methods like- immunoinformatics and bioinformatics were implemented to find out possible dominant epitopes. A total of 21 epitopes were chosen using various in-silico techniques from the expected 133 major histocompatibility complex (MHC)- I and major histocompatibility complex (MHC)- II epitopes, along with 95 B-cell epitopes which were greatly conserved. Immune stimulant, non-allergenic and non-toxic immunodominant epitopes (super epitopes) with a suitable adjuvant (Heparin-Binding Hemagglutinin Adhesin, HBHA) were used to construct the vaccine. Following the physicochemical analysis, vaccine construct was docked with Toll-like receptors (TLRs) to predict the immune stimulation. Consequently, the optimal docked complex that demonstrated the least amount of ligand-receptor complex deformability was used to conduct the molecular dynamics analysis. By following the codon optimization, the final vaccine molecule was administered into an expressing vector to perform in-silico cloning. The robust immune responses were generated in the in-silico immune simulation analysis. Hence, this study provides a hope to control the dengue infections. For validation of the immune outcomes, in-vitro as well as in-vivo investigations are essential.

Glutamate is a key nutrient for Porphyromonas gingivalis growth and survival during intracellular autophagic life under nutritionally limited conditions

Porphyromonas gingivalis survives in special autophagic vacuoles that serve as major replicative habitats in human primary gingival epithelial cells (GECs). As an asaccharolytic strict anaerobe, P. gingivalis is dependent on amino acids and peptides for nutrient sources. However, it is largely unknown as to P. gingivalis' metabolic processing under the nutritionally limited intracellular environments such the vacuoles, especially the preferred amino acids and associated-metabolic machineries. Here we elucidate that a Glutamate (Glu) catabolic enzyme, glutamate dehydrogenase (GdhA) is highly enriched in the isolated P. gingivalis -containing vacuoles. Interestingly, we found that P. gingivalis induces conversion of intracellular glutamine pool to Glu determined by analyses of the P. gingivalis- containing vacuoles and the whole infected-GECs. Critically, exogenous Glu-Glu dipeptide, a simple precursor of Glu, significantly increases the size of isolated intact P. gingivalis containing-vacuoles and live wild-type P. gingivalis numbers in GECs. In contrast, the isogenic GdhA-deficient-strain, Δ gdhA displayed a significant growth defect with collapsed-vacuoles in GECs. Next, we confirmed that P. gingivalis uptakes 14 C-Glu and it preferentially utilizes Glu-Glu-dipeptide using a nutritionally reduced Tryptic-Soy-Broth (TSB) media supplemented with Glu-Glu. Contrary, Δ gdhA -strain showed no detectable growth especially in nutritionally reduced TSB media with Glu-Glu. Using Atomic-Force-Microscopy, we observed that, wild-type P. gingivalis but not Δ gdhA strain notably increased the cell volume upon Glu-Glu supplementation, an indicator of higher metabolism and growth. Utilization of a human gingiva-mimicking organoid-system further validated the importance of Glu as an essential nutrient for the intramucosal colonization of P. gingivalis via the protected replicative vacuoles in GECs.

Importance

This study reveals that P. gingivalis heavily depends on preferential utilization of Glutamate (Glu) for autophagic vacuolar growth and survival in human GECs. Several novel observations are made to support this: (i) GdhA of P. gingivalis is highly enriched in these vacuoles, (ii) P. gingivalis induces a large conversion of intracellular glutamine to Glu, (iii) size of vacuoles are significantly increased in the presence of Glu-Glu in P. gingivalis wild-type strain infection which is opposite in a Δ gdhA strain, (iv) P. gingivalis uptakes 14 C-Glu and preferentially utilizes Glu-Glu dipeptide, (v) similarly, wild-type strain shows growth increase in a nutritionally reduced bacterial culture media, and (vi) finally, Glu-Glu supplementation increases bacterial cell-volume of P. gingivalis wild-type but not Δ gdhA strain, an indicator of higher metabolism and growth. Taken together, this study highlights the pathophysiological importance of Glu for P. gingivalis growth-rate, biomass induction and survival in nutritionally limited host subcellular environments.

An mRNA vaccine for pancreatic cancer designed by applying in silico immunoinformatics and reverse vaccinology approaches

Pancreatic ductal adenocarcinoma is the most prevalent pancreatic cancer, which is considered a significant global health concern. Chemotherapy and surgery are the mainstays of current pancreatic cancer treatments; however, a few cases are suitable for surgery, and most of the cases will experience recurrent episodes. Compared to DNA or peptide vaccines, mRNA vaccines for pancreatic cancer have more promise because of their delivery, enhanced immune responses, and lower proneness to mutation. We constructed an mRNA vaccine by analyzing S100 family proteins, which are all major activators of receptors for advanced glycation end products. We applied immunoinformatic approaches, including physicochemical properties analysis, structural prediction and validation, molecular docking study, in silico cloning, and immune simulations. The designed mRNA vaccine was estimated to have a molecular weight of 165023.50 Da and was highly soluble (grand average of hydropathicity of -0.440). In the structural assessment, the vaccine seemed to be a well-stable and functioning protein (Z score of -8.94). Also, the docking analysis suggested that the vaccine had a high affinity for TLR-2 and TLR-4 receptors. Additionally, the molecular mechanics with generalized Born and surface area solvation analysis of the "Vaccine-TLR-2" (-141.07 kcal/mol) and "Vaccine-TLR-4" (-271.72 kcal/mol) complexes also suggests a strong binding affinity for the receptors. Codon optimization also provided a high expression level with a GC content of 47.04% and a codon adaptation index score 1.0. The appearance of memory B-cells and T-cells was also observed over a while, with an increased level of helper T-cells and immunoglobulins (IgM and IgG). Moreover, the minimum free energy of the mRNA vaccine was predicted at -1760.00 kcal/mol, indicating the stability of the vaccine following its entry, transcription, and expression. This hypothetical vaccine offers a groundbreaking tool for future research and therapeutic development of pancreatic cancer.

Kinin B1 receptor and TLR4 interaction in inflammatory response

OBJECTIVE

We aimed to broaden our understanding of a potential interaction between B1R and TLR4, considering earlier studies suggesting that lipopolysaccharide (LPS) may trigger B1R stimulation.

METHODS

We assessed the impact of DBK and LPS on the membrane potential of thoracic aortas from C57BL/6, B1R, or TLR4 knockout mice. Additionally, we examined the staining patterns of these receptors in the thoracic aortas of C57BL/6 and in endothelial cells (HBMEC).

RESULTS

DBK does not affect the resting membrane potential of aortic rings in C57BL/6 mice, but it hyperpolarizes preparations in B1KO and TLR4KO mice. The hyperpolarization mechanism in B1KO mice involves B2R, and the TLR4KO response is independent of cytoplasmic calcium influx but relies on potassium channels. Conversely, LPS hyperpolarizes thoracic aorta rings in both C57BL/6 and B1KO mice, with the response unaffected by a B1R antagonist. Interestingly, the absence of B1R alters the LPS response to potassium channels. These activities are independent of nitric oxide synthase (NOS). While exposure to DBK and LPS does not alter B1R and TLR4 mRNA expression, treatment with these agonists increases B1R staining in endothelial cells of thoracic aortic rings and modifies the staining pattern of B1R and TLR4 in endothelial cells. Proximity ligation assay suggests a interaction between the receptors.

CONCLUSION

Our findings provide additional support for a putative connection between B1R and TLR4 signaling. Given the involvement of these receptors and their agonists in inflammation, it suggests that drugs and therapies targeting their effects could be promising therapeutic avenues worth exploring.

O-GlcNAcylated RALY Contributes to Hepatocellular Carcinoma Cells Proliferation by Regulating USP22 mRNA Nuclear Export

Hepatocellular carcinoma (HCC) is one of the most prevalent and deadly tumors; however, its pathogenic mechanism remains largely elusive. In-depth researches are needed to reveal the expression regulatory mechanisms and functions of the RNA-binding protein RALY in HCC. Here, we identify RALY as a highly expressed oncogenic factor that affects HCC cells proliferation both in vitro and in vivo. O-GlcNAcylation of RALY at Ser176 enhances its stability by protecting RALY from TRIM27-mediated ubiquitination, thus maintaining hyper-expression of the RALY protein. Mechanistically, RALY interacts with USP22 messenger RNA, as revealed by RNA immunoprecipitation, to increase their cytoplasmic localization and protein expression, thereby promoting the proliferation of HCC cells. Furthermore, we develop a novel RALY protein degrader based on peptide proteolysis-targeting chimeras, named RALY-PROTAC, which we chemically synthesize by linking a RALY-targeting peptide with the E3 ubiquitin ligase recruitment ligand pomalidomide. In conclusion, our findings demonstrate a novel mechanism by which O-GlcNAcylation/RALY/USP22 mRNA axis aggravates HCC cells proliferation. RALY-PROTACs as degraders of the RALY protein exhibit potential as therapeutic drugs for RALY-overexpressing HCC.

A Comparison of Antibody-Antigen Complex Sequence-to-Structure Prediction Methods and their Systematic Biases

The ability to accurately predict antibody-antigen complex structures from their sequences could greatly advance our understanding of the immune system and would aid in the development of novel antibody therapeutics. There have been considerable recent advancements in predicting protein-protein interactions (PPIs) fueled by progress in machine learning (ML). To understand the current state of the field, we compare six representative methods for predicting antibody-antigen complexes from sequence, including two deep learning approaches trained to predict PPIs in general (AlphaFold-Multimer, RoseTTAFold), two composite methods that initially predict antibody and antigen structures separately and dock them (using antibody-mode ClusPro), local refinement in Rosetta (SnugDock) of globally docked poses from ClusPro, and a pipeline combining homology modeling with rigid-body docking informed by ML-based epitope and paratope prediction (AbAdapt). We find that AlphaFold-Multimer outperformed other methods, although the absolute performance leaves considerable room for improvement. AlphaFold-Multimer models of lower-quality display significant structural biases at the level of tertiary motifs (TERMs) towards having fewer structural matches in non-antibody containing structures from the Protein Data Bank (PDB). Specifically, better models exhibit more common PDB-like TERMs at the antibody-antigen interface than worse ones. Importantly, the clear relationship between performance and the commonness of interfacial TERMs suggests that scarcity of interfacial geometry data in the structural database may currently limit application of machine learning to the prediction of antibody-antigen interactions.

Molecular Insight into the Effect of HIV-TAT Protein on Amyloid-β Peptides

Increased deposition of amyloid-β (Aβ) plaques in the brain is a frequent pathological feature observed in human immunodeficiency virus (HIV)-positive patients. Emerging evidence indicates that HIV regulatory proteins, particularly the transactivator of transcription (TAT) protein, could interact with Aβ peptide, accelerating the formation of Aβ plaques in the brain and potentially contributing to the onset of Alzheimer's disease in individuals with HIV infection. Nevertheless, the molecular mechanisms underlying these processes remain unclear. In the present study, we have used long all-atom molecular dynamics simulations to probe the direct interactions between the TAT protein and Aβ peptide at the molecular level. Sampling over 28.0 μs, our simulations show that TAT protein induces a shift in the Aβ monomer ensemble toward elongated conformations, exposing aggregation-prone regions on the surface and thereby inducing subsequent aggregation. TAT protein also appears to enhance the stability of preformed Aβ fibrils, while increasing the β-sheet content within these fibrils. Our atomistically detailed simulations qualitatively agree with previous in vitro and in vivo studies. Importantly, our simulations identify key interactions between Aβ and the TAT protein that drive the Aβ aggregation process and stabilize the preformed Aβ aggregates, which are particularly challenging to obtain through current experimental techniques.

Identification of heparin-binding amino acid residues in antibody HS4C3 with the potential to design antibodies against heparan sulfate domains

Heparan sulfate (HS) is a linear polysaccharide with high structural and functional diversity. Detection and localization of HS in tissues can be performed using single chain variable fragment (scFv) antibodies. Although several anti-HS antibodies recognizing different sulfation motifs have been identified, little is known about their interaction with HS. In this study the interaction between the scFv antibody HS4C3 and heparin was investigated. Heparin-binding lysine and arginine residues were identified using a protect and label methodology. Site-directed mutagenesis was applied to further identify critical heparin-binding lysine/arginine residues using immunohistochemical and biochemical assays. In addition, computational docking of a heparin tetrasaccharide towards a 3-D homology model of HS4C3 was applied to identify potential heparin-binding sites. Of the 12 lysine and 15 arginine residues within the HS4C3 antibody, 6 and 9, respectively, were identified as heparin-binding. Most of these residues are located within one of the complementarity determining regions (CDR) or in their proximity. All basic amino acid residues in the CDR3 region of the heavy chain were involved in binding. Computational docking showed a heparin tetrasaccharide close to these regions. Mutagenesis of heparin-binding residues reduced or altered reactivity towards HS and heparin. Identification of heparin-binding arginine and lysine residues in HS4C3 allows for better understanding of the interaction with HS and creates a framework to rationally design antibodies targeting specific HS motifs.

Structural, Biophysical, and Computational Studies of a Murine Light Chain Dimer

Antibodies are widely used in medicinal and scientific research due to their ability to bind to a specific antigen. Most often, antibodies are composed of heavy and light chain domains. Under physiological conditions, light chains are produced in excess, as compared to the heavy chain. It is now known that light chains are not silent partners of the heavy chain and can modulate the immune response independently. In this work, the first crystal structure of a light chain dimer originating from mice is described. It represents the light chain dimer of 6A8, a monoclonal antibody specific to the allergen Der f 1. Building on the unexpected occurrence of this kind of dimer, we have demonstrated that this light chain is stable in solution alone. Moreover, enzyme-linked immunosorbent assays (ELISA) have revealed that, when the light chain is not partnered to its corresponding heavy chain, it interacts non-specifically with a wide range of proteins. Computational studies were used to provide insight on the role of the 6A8 heavy chain domain in the specific binding to Der f 1. Overall, this work demonstrates and supports the ongoing notion that light chains can function by themselves and are not silent partners of heavy chains.

De novo structure prediction of meteorin and meteorin-like protein for identification of domains, functional receptor binding regions, and their high-risk missense variants

Meteorin (Metrn) and Meteorin-like (Metrnl) are homologous secreted proteins involved in neural development and metabolic regulation. In this study, we have performed de novo structure prediction and analysis of both Metrn and Metrnl using Alphafold2 (AF2) and RoseTTAfold (RF). Based on the domain and structural homology analysis of the predicted structures, we have identified that these proteins are composed of two functional domains, a CUB domain and an NTR domain, connected by a hinge/loop region. We have identified the receptor binding regions of Metrn and Metrnl using the machine-learning tools ScanNet and Masif. These were further validated by docking Metrnl with its reported KIT receptor, thus establishing the role of each domain in the receptor interaction. Also, we have studied the effect of non-synonymous SNPs on the structure and function of these proteins using an array of bioinformatics tools and selected 16 missense variants in Metrn and 10 in Metrnl that can affect the protein stability. This is the first study to comprehensively characterize the functional domains of Metrn and Metrnl at their structural level and identify the functional domains, and protein binding regions. This study also highlights the interaction mechanism of the KIT receptor and Metrnl. The predicted deleterious SNPs will allow further understanding of the role of these variants in modulating the plasma levels of these proteins in disease conditions such as diabetes.Communicated by Ramaswamy H. Sarma.

A comprehensive examination of ACE2 receptor and prediction of spike glycoprotein and ACE2 interaction based on in silico analysis of ACE2 receptor

The ACE2 receptor plays a vital role not only in the SARS-CoV-induced epidemic but also in various other diseases, including cardiovascular diseases and ARDS. While studies have explored the interactions between ACE2 and SARS-CoV proteins, comprehensive research utilizing bioinformatic tools on the ACE2 protein has been lacking. The one aim of present study was to extensively analyze the regions of the ACE2 protein. After utilizing all bioinformatics tools especially G104 and L108 regions on ACE2 were come forward. The results of our analysis revealed that possible mutations or deletions in the G104 and L108 regions play a critical role in both the biological functioning and the determination of the chemical-physical properties of ACE2. Additionally, these regions were found to be more susceptible to mutations or deletions compared to other regions of the ACE2 protein. Notably, the randomly selected peptide, LQQNGSSVLS (100-109), which includes G104 and L108, exhibited a crucial role in binding the RBD of the spike protein, as supported by docking scores. Furthermore, both MDs and iMODs results provided evidence that G104 and L108 influence the dynamics of ACE2-spike complexes. This study is expected to offer a new perspective on the ACE2-SARS-CoV interaction and other research areas where ACE2 plays a significant role, such as biotechnology (protein engineering, enzyme optimization), medicine (RAS, pulmonary and cardiac diseases), and basic research (structural motifs, stabilizing protein folds, or facilitating important inter molecular contacts, protein's proper structure and function).Communicated by Ramaswamy H. Sarma.

An immunoinformatic approach for developing a multi-epitope subunit vaccine against Monkeypox virus

An in-silico approach was implemented to develop a multi-epitope subunit vaccine construct against the recent outbreak of the Monkeypox virus. The contribution of 10 different antigenic proteins based on their antigenicity led to the selection of 10 HTL, 9 CTL, and 6 BCL epitopes. The construct was further investigated for its allergenicity, antigenicity, and physio-chemical properties using servers such as AllerTOP and Allergen FP, VaxiJen and ANTIGENPro, and ProtParam respectively. The secondary structure of the vaccine was predicted using the SOPMA server followed by I-TASSER for the 3D structure. After refinement and validation of structural stability of the modelled vaccine, a molecular docking assay was implemented to study the interaction of the known TLR4 receptor with that of the constructed vaccine using the ClusPro server. The docked vaccine and TLR4 receptor were studied using the molecular dynamics (MD) simulation to validate the stability of the complex. After codon optimization the cDNA was constructed and in-silico cloning of the vaccine construct was carried out. The vaccine was also subjected to computational immune assay which predicted a powerful immune response against the Monkeypox virus validating that the developed multi-epitope vaccine construct can be a potent vaccine candidate.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00220-5.

Small protein blockers of human IL-6 receptor alpha inhibit proliferation and migration of cancer cells

BACKGROUND

Interleukin-6 (IL-6) is a multifunctional cytokine that controls the immune response, and its role has been described in the development of autoimmune diseases. Signaling via its cognate IL-6 receptor (IL-6R) complex is critical in tumor progression and, therefore, IL-6R represents an important therapeutic target.

METHODS

An albumin-binding domain-derived highly complex combinatorial library was used to select IL-6R alpha (IL-6Rα)-targeted small protein binders using ribosome display. Large-scale screening of bacterial lysates of individual clones was performed using ELISA, and their IL-6Rα blocking potential was verified by competition ELISA. The binding of proteins to cells was monitored by flow cytometry and confocal microscopy on HEK293T-transfected cells, and inhibition of signaling function was examined using HEK-Blue IL-6 reporter cells. Protein binding kinetics to living cells was measured by LigandTracer, cell proliferation and toxicity by iCELLigence and Incucyte, cell migration by the scratch wound healing assay, and prediction of binding poses using molecular modeling by docking.

RESULTS

We demonstrated a collection of protein variants called NEF ligands, selected from an albumin-binding domain scaffold-derived combinatorial library, and showed their binding specificity to human IL-6Rα and antagonistic effect in HEK-Blue IL-6 reporter cells. The three most promising NEF108, NEF163, and NEF172 variants inhibited cell proliferation of malignant melanoma (G361 and A2058) and pancreatic (PaTu and MiaPaCa) cancer cells, and suppressed migration of malignant melanoma (A2058), pancreatic carcinoma (PaTu), and glioblastoma (GAMG) cells in vitro. The NEF binders also recognized maturation-induced IL-6Rα expression and interfered with IL-6-induced differentiation in primary human B cells.

CONCLUSION

We report on the generation of small protein blockers of human IL-6Rα using directed evolution. NEF proteins represent a promising class of non-toxic anti-tumor agents with migrastatic potential.

Engineering PD-1-targeted small protein variants for in vitro diagnostics and in vivo PET imaging

BACKGROUND

Programmed cell death 1 (PD-1) belongs to immune checkpoint proteins ensuring negative regulation of the immune response. In non-small cell lung cancer (NSCLC), the sensitivity to treatment with anti-PD-1 therapeutics, and its efficacy, mostly correlated with the increase of tumor infiltrating PD-1+ lymphocytes. Due to solid tumor heterogeneity of PD-1+ populations, novel low molecular weight anti-PD-1 high-affinity diagnostic probes can increase the reliability of expression profiling of PD-1+ tumor infiltrating lymphocytes (TILs) in tumor tissue biopsies and in vivo mapping efficiency using immune-PET imaging.

METHODS

We designed a 13 kDa β-sheet Myomedin scaffold combinatorial library by randomization of 12 mutable residues, and in combination with ribosome display, we identified anti-PD-1 Myomedin variants (MBA ligands) that specifically bound to human and murine PD-1-transfected HEK293T cells and human SUP-T1 cells spontaneously overexpressing cell surface PD-1.

RESULTS

Binding affinity to cell-surface expressed human and murine PD-1 on transfected HEK293T cells was measured by fluorescence with LigandTracer and resulted in the selection of most promising variants MBA066 (hPD-1 KD = 6.9 nM; mPD-1 KD = 40.5 nM), MBA197 (hPD-1 KD = 29.7 nM; mPD-1 KD = 21.4 nM) and MBA414 (hPD-1 KD = 8.6 nM; mPD-1 KD = 2.4 nM). The potential of MBA proteins for imaging of PD-1+ populations in vivo was demonstrated using deferoxamine-conjugated MBA labeled with 68Galium isotope. Radiochemical purity of 68Ga-MBA proteins reached values 94.7-99.3% and in vitro stability in human serum after 120 min was in the range 94.6-98.2%. The distribution of 68Ga-MBA proteins in mice was monitored using whole-body positron emission tomography combined with computerized tomography (PET/CT) imaging up to 90 min post-injection and post mortem examined in 12 mouse organs. The specificity of MBA proteins was proven by co-staining frozen sections of human tonsils and NSCLC tissue biopsies with anti-PD-1 antibody, and demonstrated their potential for mapping PD-1+ populations in solid tumors.

CONCLUSIONS

Using directed evolution, we developed a unique set of small binding proteins that can improve PD-1 diagnostics in vitro as well as in vivo using PET/CT imaging.

Simulation and Computational Study of RING Domain Mutants of BRCA1 and Ube2k in AD/PD Pathophysiology

Lysine-based post-translational modification (PTM) such as acylation, acetylation, deamination, methylation, SUMOylation, and ubiquitination has proven to be a major regulator of gene expression, chromatin structure, protein stability, protein-protein interaction, protein degradation, and cellular localization. However, besides all the PTMs, ubiquitination stands as the second most common PTM after phosphorylation that is involved in the etiology of neurodegenerative diseases (NDDs) namely, Alzheimer's disease (AD) and Parkinson's disease (PD). NDDs are characterized by the accumulation of misfolded protein aggregates in the brain that lead to disease-related gene mutation and irregular protein homeostasis. The ubiquitin-proteasome system (UPS) is in charge of degrading these misfolded proteins, which involve an interplay of E1, E2, E3, and deubiquitinase enzymes. Impaired UPS has been commonly observed in NDDs and E3 ligases are the key members of the UPS, thus, dysfunction of the same can accelerate the neurodegeneration process. Therefore, the aim of this study is firstly, to find E3 ligases that are common in both AD and PD through data mining. Secondly, to study the impact of mutation on its structure and function. The study deciphered 74 E3 ligases that were common in both AD and PD. Later, 10 hub genes were calculated of which protein-protein interaction, pathway enrichment, lysine site prediction, domain, and motif analysis were performed. The results predicted BRCA1, PML, and TRIM33 as the top three putative lysine-modified E3 ligases involved in AD and PD pathogenesis. However, based on structural characterization, BRCA1 was taken further to study RING domain mutation that inferred K32Y, K32L, K32C, K45V, K45Y, and K45G as potential mutants that alter the structural and functional ability of BRCA1 to interact with Ube2k, E2-conjugating enzyme. The most probable mutant observed after molecular dynamics simulation of 50 ns is K32L. Therefore, our study concludes BRCA1, a potential E3 ligase common in AD and PD, and RING domain mutation at sites K32 and K45 possibly disturbs its interaction with its E2, Ube2k.

Lactobacilli-derived adjuvants combined with immunoinformatics-driven multi-epitope antigens based approach protects against Clostridium perfringens in a mouse model

Clostridium perfringens is ubiquitously distributed and capable of secreting toxins, posing a significant threat to animal health. Infections caused by Clostridium perfringens, such as Necrotic Enteritis (NE), result in substantial economic losses to the livestock industry annually. However, there is no effective commercial vaccine available. Hence, we set out to propose an effective approach for multi-epitope subunit vaccine construction utilizing biomolecules. We utilized immunoinformatics to design a novel multi-epitope antigen against C. perfringens (CPMEA). Furthermore, we innovated novel bacterium-like particles (BLPs) through thermal acid treatment of various Lactobacillus strains and selected BLP23017 among them. Then, we detailed the structure of CPMEA and BLPs and utilized them to prepare a multi-epitope vaccine. Here, we showed that our vaccine provided full protection against C. perfringens infection after a single dose in a mouse model. Additionally, BLP23017 notably augmented the secretion of secretory immunoglobulin A (sIgA) and enhanced antibody production. We conclude that our vaccine possess safety and high efficacy, making it an excellent candidate for preventing C. perfringens infection. Moreover, we demonstrate our approach to vaccine construction and the preparation of BLP23017 with distinct advantages may contribute to the prevention of a wider array of diseases and the novel vaccine development.

Identifying citrus limonoids as a potential fusion inhibitor of DENV-2 virus through its in silico study and FTIR analysis

Dengue virus type 2 (DENV-2) is an arthropod-borne deadly RNA human pathogen transmitted through the mosquito Aedes. The DENV-2 roots viral infection by facilitating entry with its envelope glycoprotein to the receptor protein Dendritic-cell-specific ICAM3-grabbing non-integrin (DC-SIGN) through membrane fusion. Here, an organizational path is reported for inhibiting the transition due to fusion activation and by blocking the residues of the DC-SIGN-E-Glyco protein complex through citrus limonoids with its antiviral effect. Based on lower binding affinity obtained with E-glycoprotein, and based on ADMET and drug-likeness study, limonin was selected as having effective interaction with DC-SIGN-E-glycoprotein complex in comparison to other citrus limonoids. The FTIR spectra performed with the limonin-E-glycoprotein sample provide evidence of hydrogen bond formation that indicates the formation of a strong limonin-E-glycoprotein conjugate. Further, the strong physical interaction between DC-SIGN and small limonin molecules in comparison to that of E-glyco with DC-SIGN assures the development of immunity against DENV-2.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00207-2.

Quantitative proteomics analysis identified new interacting proteins of JAL30 in Arabidopsis

Jacalin-related lectins (JALs) are a unique group of plant lectins derived from the jacalin protein family, which play important roles in plant defense responses. JAL30/PBP1 (PYK10 binding protein 1) interacts with inactive PYK10, exerting negative regulatory control over the size of the PYK10 complex, which is formed and activated upon insect or pathogen invasion. However, the precise interplay between JAL30 and other components remains elusive. In this study, we found JAL30 as a nucleocytoplasmic protein, but no obvious phenotype was observed in jal30-1 single mutant. Through immunoprecipitation (IP) enrichment combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS), dozens of new JAL30 interacting proteins were found in addition to several reported ones. Gene Ontology (GO) analysis revealed that these interacting proteins were highly related to the wounding and bacterial stimuli, suggesting their potential involvement in the jasmonate (JA) response. Importantly, the expression of JAL30 was induced by MeJA treatment, further highlighting its relevance in plant defense mechanisms. A novel JAL30 interacting protein, ESM1, was identified and its interaction with JAL30 was confirmed by Co-immunoprecipitation. Moreover, ESM1 was found as an O-GlcNAcylated protein, suggesting that JAL30 may possess glycosylated protein binding ability, particularly in O-GlcNAcylated protein and peptide recognition. Overall, our study provides valuable insights into the interacting protein network and biological function of JAL30, demonstrates the interaction between JAL30 and ESM1, and uncovers the potential significance of JAL30 in plant defense system, potentially through its association with PYK10 complex or JA response. SIGNIFICANCE: The biological functions of lectin proteins, including defense responses, immunity responses, signal transduction, have been well studied. Lectin proteins were also utilized to enrich glycosylated proteins for their specific carbohydrates binding capability. Jacalin-related lectins (JALs) were found to involve in plant defense mechanism. However, it is not yet clear whether JALs could use for enrichment of glycosylated proteins. In this study, we used label-free quantification method to identify interacting proteins of JAL30. A novel interacting protein, ESM1, as an O-GlcNAcylated protein was found. ESM1 has been reported to take part in defense against insect herbivory. Therefore, our findings provided experimental evidence to confirm that JALs have potential to be developed as the bio-tools to enrich glycosylated proteins. Finally, our data not only illustrated the vital biological role of JALs in plants, but also verified unique function of JAL30 in recognizing O-GlcNAcylated proteins.

PRMT4 interacts with NCOA4 to inhibit ferritinophagy in cisplatin-induced acute kidney injury

Cisplatin-induced acute kidney injury (AKI) is commonly seen in the clinical practice, and ferroptosis, a type of non-apoptotic cell death, plays a pivotal role in it. Previous studies suggested that protein arginine methyltransferase 4 (PRMT4) was incorporated in various bioprocesses, but its role in renal injuries has not been investigated. Our present study showed that PRMT4 was highly expressed in renal proximal tubular cells, and it was downregulated in cisplatin-induced AKI. Besides, genetic disruption of PRMT4 exacerbated, while its overexpression attenuated, cisplatin-induced redox injuries in renal proximal epithelia. Mechanistically, our work showed that PRMT4 interacted with NCOA4 to inhibit ferritinophagy, a type of selective autophagy favoring lipid peroxidation to accelerate ferroptosis. Taken together, our study demonstrated that PRMT4 interacted with NCOA4 to attenuate ferroptosis in cisplatin-induced AKI, suggesting that PRMT4 might present as a new therapeutic target for cisplatin-related nephropathy.

Designing a Novel Multiepitope Vaccine from the Human Papilloma Virus E1 and E2 Proteins for Indonesia with Immunoinformatics and Molecular Dynamics Approaches

One of the deadliest malignant cancer in women globally is cervical cancer. Specifically, cervical cancer is the second most common type of cancer in Indonesia. The main infectious agent of cervical cancer is the human papilloma virus (HPV). Although licensed prophylactic vaccines are available, cervical cancer cases are on the rise. Therapy using multiepitope-based vaccines is a very promising therapy for cervical cancer. This study aimed to develop a multiepitope vaccine based on the E1 and E2 proteins of HPV 16, 18, 45, and 52 using in silico. In this study, we develop a novel multiepitope vaccine candidate using an immunoinformatic approach. We predicted the epitopes of the cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) and evaluated their immunogenic properties. Population coverage analysis of qualified epitopes was conducted to determine the successful use of the vaccine worldwide. The epitopes were constructed into a multiepitope vaccine by using AAY linkers between the CTL epitopes and GPGPG linkers between the HTL epitopes. The tertiary structure of the multiepitope vaccine was modeled with AlphaFold and was evaluated by Prosa-web. The results of vaccine construction were analyzed for B-cell epitope prediction, molecular docking with Toll like receptor-4 (TLR4), and molecular dynamics simulation. The results of epitope prediction obtained 4 CTL epitopes and 7 HTL epitopes that are eligible for construction of multiepitope vaccines. Prediction of the physicochemical properties of multiepitope vaccines obtained good results for recombinant protein production. The interaction showed that the interaction of the multiepitope vaccine-TLR4 complex is stable based on the binding free energy value -106.5 kcal/mol. The results of the immune response simulation show that multiepitope vaccine candidates could activate the adaptive and humoral immune systems and generate long-term B-cell memory. According to these results, the development of a multiepitope vaccine with a reverse vaccinology approach is a breakthrough to develop potential cervical cancer therapeutic vaccines.

A Conserved Intramolecular Ion-Pair Plays a Critical but Divergent Role in Regulation of Dimerization and Transport Function among the Monoamine Transporters

The monoamine transporters, including the serotonin transporter (SERT), dopamine transporter (DAT), and norepinephrine transporter (NET), are the therapeutic targets for the treatment of many neuropsychiatric disorders. Despite significant progress in characterizing the structures and transport mechanisms of these transporters, the regulation of their transport functions through dimerization or oligomerization remains to be understood. In the present study, we identified a conserved intramolecular ion-pair at the third extracellular loop (EL3) connecting TM5 and TM6 that plays a critical but divergent role in the modulation of dimerization and transport functions among the monoamine transporters. The disruption of the ion-pair interactions by mutations induced a significant spontaneous cross-linking of a cysteine mutant of SERT and an increase in cell surface expression but with an impaired specific transport activity. On the other hand, similar mutations of the corresponding ion-pair residues in both DAT and NET resulted in an opposite effect on their oxidation-induced dimerization, cell surface expression, and transport function. Reversible biotinylation experiments indicated that the ion-pair mutations slowed down the internalization of SERT but stimulated the internalization of DAT. In addition, cysteine accessibility measurements for monitoring SERT conformational changes indicated that substitution of the ion-pair residues resulted in profound effects on the rate constants for cysteine modification in both the extracellular and cytoplasmatic substrate permeation pathways. Furthermore, molecular dynamics simulations showed that the ion-pair mutations increased the interfacial interactions in a SERT dimer but decreased it in a DAT dimer. Taken together, we propose that the transport function is modulated by the equilibrium between monomers and dimers on the cell surface, which is regulated by a potential compensatory mechanism but with different molecular solutions among the monoamine transporters. The present study provided new insights into the structural elements regulating the transport function of the monoamine transporters through their dimerization.

Defining Requirements for Heme Binding in PGRMC1 and Identifying Key Elements that Influence Protein Dimerization

Progesterone receptor membrane component 1 (PGRMC1) binds heme via a surface-exposed site and displays some structural resemblance to cytochrome b5 despite their different functions. In the case of PGRMC1, it is the protein interaction with drug-metabolizing cytochrome P450s and the epidermal growth factor receptor that has garnered the most attention. These interactions are thought to result in a compromised ability to metabolize common chemotherapy agents and to enhance cancer cell proliferation. X-ray crystallography and immunoprecipitation data have suggested that heme-mediated PGRMC1 dimers are important for facilitating these interactions. However, more recent studies have called into question the requirement of heme binding for PGRMC1 dimerization. Our study employs spectroscopic and computational methods to probe and define heme binding and its impact on PGRMC1 dimerization. Fluorescence, electron paramagnetic resonance and circular dichroism spectroscopies confirm heme binding to apo-PGRMC1 and were used to demonstrate the stabilizing effect of heme on the wild-type protein. We also utilized variants (C129S and Y113F) to precisely define the contributions of disulfide bonds and direct heme coordination to PGRMC1 dimerization. Understanding the key factors involved in these processes has important implications for downstream protein-protein interactions that may influence the metabolism of chemotherapeutic agents. This work opens avenues for deeper exploration into the physiological significance of the truncated-PGRMC1 model and developing design principles for potential therapeutics to target PGRMC1 dimerization and downstream interactions.

Impact of carbamazepine on SMARCA4 (BRG1) expression in colorectal cancer: modulation by KRAS mutation status

SMARCA4 is a gene traditionally considered a tumor suppressor. Recent research has however found that SMARCA4 likely promotes cancer growth and is a good target for cancer treatment. The drug carbamazepine, an autophagy inducer, was used on colorectal cancer cell lines, HCT1116 and Hke3 (KRAS mutant and wildtype). Our study finds that Carbamazepine affects SMARCA4 levels and that this effect is different depending on the KRAS mutation status. This study analyzes the effect of carbamazepine on early-stage autophagy via ULK1 as well as simulates the docking of carbamazepine on KRAS, depending on the mutation status. Our study highlights the therapeutic uses of carbamazepine on cancer, and we propose that carbamazepine in conjunction with other chemotherapies may prove useful in targeting KRAS-mutated colorectal cancer.

Immunoinformatic based designing of potential immunogenic novel mRNA and peptide-based prophylactic vaccines against H5N1 and H7N9 avian influenza viruses

Influenza viruses are the most common cause of serious respiratory illnesses worldwide and are responsible for a significant number of annual fatalities. Therefore, it is crucial to look for new immunogenic sites that might trigger an effective immune response. In the present study, bioinformatics tools were used to design mRNA and multiepitope-based vaccines against H5N1 and H7N9 subtypes of avian influenza viruses. Several Immunoinformatic tools were employed to extrapolate T and B lymphocyte epitopes of HA and NA proteins of both subtypes. The molecular docking approach was used to dock the selected HTL and CTL epitopes with the corresponding MHC molecules. Eight (8) CTL, four (4) HTL, and Six (6) linear B cell epitopes were chosen for the structural arrangement of mRNA and of peptide-based prophylactic vaccine designs. Different physicochemical characteristics of the selected epitopes fitted with suitable linkers were analyzed. High antigenic, non-toxic, and non-allergenic features of the designed vaccines were noted at a neutral physiological pH. Codon optimization tool was used to check the GC content and CAI value of constructed MEVC-Flu vaccine, which were recorded to be 50.42% and 0.97 respectively. the GC content and CAI value verify the stable expression of vaccine in pET28a + vector. In-silico immunological simulation the MEVC-Flu vaccine construct revealed a high level of immune responses. The molecular dynamics simulation and docking results confirmed the stable interaction of TLR-8 and MEVC-Flu vaccine. Based on these parameters, vaccine constructs can be regarded as an optimistic choice against H5N1 and H7N9 strains of the influenza virus. Further experimental testing of these prophylactic vaccine designs against pathogenic avian influenza strains may clarify their safety and efficacy.Communicated by Ramaswamy H. Sarma.

Sensitive detection of SARS-CoV-2 main protease 3CLpro with an engineered ribonuclease zymogen

Alongside vaccines and antiviral therapeutics, diagnostic tools are a crucial aid in combating the COVID-19 pandemic caused by the etiological agent SARS-CoV-2. All common assays for infection rely on the detection of viral sub-components, including structural proteins of the virion or fragments of the viral genome. Selective pressure imposed by human intervention of COVID-19 can, however, induce viral mutations that decrease the sensitivity of diagnostic assays based on biomolecular structure, leading to an increase in false-negative results. In comparison, mutations are unlikely to alter the function of viral proteins, and viral machinery is under less selective pressure from vaccines and therapeutics. Accordingly, diagnostic assays that rely on biomolecular function can be more robust than ones that rely on biopolymer structure. Toward this end, we used a split intein to create a circular ribonuclease zymogen that is activated by the SARS-CoV-2 main protease, 3CLpro . Zymogen activation by 3CLpro leads to a >300-fold increase in ribonucleolytic activity, which can be detected with a highly sensitive fluorogenic substrate. This coupled assay can detect low nanomolar concentrations of 3CLpro within a timeframe comparable to that of common antigen-detection protocols. More generally, the concept of detecting a protease by activating a ribonuclease could be the basis of diagnostic tools for other indications.

Phase transition of GvpU regulates gas vesicle clustering in bacteria

Gas vesicles (GVs) are microbial protein organelles that support cellular buoyancy. GV engineering has multiple applications, including reporter gene imaging, acoustic control and payload delivery. GVs often cluster into a honeycomb pattern to minimize occupancy of the cytosol. The underlying molecular mechanism and the influence on cellular physiology remain unknown. Using genetic, biochemical and imaging approaches, here we identify GvpU from Priestia megaterium as a protein that regulates GV clustering in vitro and upon expression in Escherichia coli. GvpU binds to the C-terminal tail of the core GV shell protein and undergoes a phase transition to form clusters in subsaturated solution. These properties of GvpU tune GV clustering and directly modulate bacterial fitness. GV variants can be designed with controllable sensitivity to GvpU-mediated clustering, enabling design of genetically tunable biosensors. Our findings elucidate the molecular mechanisms and functional roles of GV clustering, enabling its programmability for biomedical applications.

Functional and structural characterisation of RimL from Bacillus cereus, a new Nα-acetyltransferase of ribosomal proteins that was wrongly assigned as an aminoglycosyltransferase

Enzymes of the GNAT (GCN5-relate N-acetyltransferases) superfamily are important regulators of cell growth and development. They are functionally diverse and share low amino acid sequence identity, making functional annotation difficult. In this study, we report the function and structure of a new ribosomal enzyme, Nα-acetyl transferase from Bacillus cereus (RimLBC), a protein that was previously wrongly annotated as an aminoglycosyltransferase. Firstly, extensive comparative amino acid sequence analyses suggested RimLBC belongs to a cluster of proteins mediating acetylation of the ribosomal protein L7/L12. To assess if this was the case, several well established substrates of aminoglycosyltransferases were screened. The results of these studies did not support an aminoglycoside acetylating function for RimLBC. To gain further insight into RimLBC biological role, a series of studies that included MALDI-TOF, isothermal titration calorimetry, NMR, X-ray protein crystallography, and site-directed mutagenesis confirmed RimLBC affinity for Acetyl-CoA and that the ribosomal protein L7/L12 is a substrate of RimLBC. Last, we advance a mechanistic model of RimLBC mode of recognition of its protein substrates. Taken together, our studies confirmed RimLBC as a new ribosomal Nα-acetyltransferase and provide structural and functional insights into substrate recognition by Nα-acetyltransferases and protein acetylation in bacteria.

Integrating Reinforcement Learning and Monte Carlo Tree Search for enhanced neoantigen vaccine design

Recent advances in cancer immunotherapy have highlighted the potential of neoantigen-based vaccines. However, the design of such vaccines is hindered by the possibility of weak binding affinity between the peptides and the patient's specific human leukocyte antigen (HLA) alleles, which may not elicit a robust adaptive immune response. Triggering cross-immunity by utilizing peptide mutations that have enhanced binding affinity to target HLA molecules, while preserving their homology with the original one, can be a promising avenue for neoantigen vaccine design. In this study, we introduced UltraMutate, a novel algorithm that combines Reinforcement Learning and Monte Carlo Tree Search, which identifies peptide mutations that not only exhibit enhanced binding affinities to target HLA molecules but also retains a high degree of homology with the original neoantigen. UltraMutate outperformed existing state-of-the-art methods in identifying affinity-enhancing mutations in an independent test set consisting of 3660 peptide-HLA pairs. UltraMutate further showed its applicability in the design of peptide vaccines for Human Papillomavirus and Human Cytomegalovirus, demonstrating its potential as a promising tool in the advancement of personalized immunotherapy.

Iterative In Silico Screening for Optimizing Stable Conformation of Anti-SARS-CoV-2 Nanobodies

Nanobodies (Nbs or VHHs) are single-domain antibodies (sdAbs) derived from camelid heavy-chain antibodies. Nbs have special and unique characteristics, such as small size, good tissue penetration, and cost-effective production, making Nbs a good candidate for the diagnosis and treatment of viruses and other pathologies. Identifying effective Nbs against COVID-19 would help us control this dangerous virus or other unknown variants in the future. Herein, we introduce an in silico screening strategy for optimizing stable conformation of anti-SARS-CoV-2 Nbs. Firstly, various complexes containing nanobodies were downloaded from the RCSB database, which were identified from immunized llamas. The primary docking between Nbs and the SARS-CoV-2 spike protein receptor-binding domain was performed through the ClusPro program, with the manual screening leaving the reasonable conformation to the next step. Then, the binding distances of atoms between the antigen-antibody interfaces were measured through the NeighborSearch algorithm. Finally, filtered nanobodies were acquired according to HADDOCK scores through HADDOCK docking the COVID-19 spike protein with nanobodies under restrictions of calculated molecular distance between active residues and antigenic epitopes less than 4.5 Å. In this way, those nanobodies with more reasonable conformation and stronger neutralizing efficacy were acquired. To validate the efficacy ranking of the nanobodies we obtained, we calculated the binding affinities (∆G) and dissociation constants (Kd) of all screened nanobodies using the PRODIGY web tool and predicted the stability changes induced by all possible point mutations in nanobodies using the MAESTROWeb server. Furthermore, we examined the performance of the relationship between nanobodies' ranking and their number of mutation-sensitive sites (Spearman correlation > 0.68); the results revealed a robust correlation, indicating that the superior nanobodies identified through our screening process exhibited fewer mutation hotspots and higher stability. This correlation analysis demonstrates the validity of our screening criteria, underscoring the suitability of these nanobodies for future development and practical implementation. In conclusion, this three-step screening strategy iteratively in silico greatly improved the accuracy of screening desired nanobodies compared to using only ClusPro docking or default HADDOCK docking settings. It provides new ideas for the screening of novel antibodies and computer-aided screening methods.

Affinity fine-tuning anti-CAIX CAR-T cells mitigate on-target off-tumor side effects

One of the major hurdles that has hindered the success of chimeric antigen receptor (CAR) T cell therapies against solid tumors is on-target off-tumor (OTOT) toxicity due to sharing of the same epitopes on normal tissues. To elevate the safety profile of CAR-T cells, an affinity/avidity fine-tuned CAR was designed enabling CAR-T cell activation only in the presence of a highly expressed tumor associated antigen (TAA) but not when recognizing the same antigen at a physiological level on healthy cells. Using direct stochastic optical reconstruction microscopy (dSTORM) which provides single-molecule resolution, and flow cytometry, we identified high carbonic anhydrase IX (CAIX) density on clear cell renal cell carcinoma (ccRCC) patient samples and low-density expression on healthy bile duct tissues. A Tet-On doxycycline-inducible CAIX expressing cell line was established to mimic various CAIX densities, providing coverage from CAIX-high skrc-59 tumor cells to CAIX-low MMNK-1 cholangiocytes. Assessing the killing of CAR-T cells, we demonstrated that low-affinity/high-avidity fine-tuned G9 CAR-T has a wider therapeutic window compared to high-affinity/high-avidity G250 that was used in the first anti-CAIX CAR-T clinical trial but displayed serious OTOT effects. To assess the therapeutic effect of G9 on patient samples, we generated ccRCC patient derived organotypic tumor spheroid (PDOTS) ex vivo cultures and demonstrated that G9 CAR-T cells exhibited superior efficacy, migration and cytokine release in these miniature tumors. Moreover, in an RCC orthotopic mouse model, G9 CAR-T cells showed enhanced tumor control compared to G250. In summary, G9 has successfully mitigated OTOT side effects and in doing so has made CAIX a druggable immunotherapeutic target.

Molecular Insights into the Inhibitory Role of α-Crystallin against γD-Crystallin Aggregation

Cataracts, a major cause of global blindness, contribute significantly to the overall prevalence of blindness. The opacification of the lens, resulting in cataract formation, primarily occurs due to the aggregation of crystallin proteins within the eye lens. Despite the high concentration of these crystallins, they remarkably maintain the lens transparency and refractive index. α-Crystallins (α-crys), acting as chaperones, play a crucial role in preventing crystallin aggregation, although the exact molecular mechanism remains uncertain. In this study, we employed a combination of molecular docking, all-atom molecular dynamics simulations, and advanced free energy calculations to investigate the interaction between γD-crystallin (γD-crys), a major structural protein of the eye lens, and α-crystallin proteins. Our findings demonstrate that α-crys exhibits an enhanced affinity for the NTD2 and CTD4 regions of γD-crys. The NTD2 and CTD4 regions form the interface between the N-terminal domain (NTD) and the C-terminal domain (CTD) of the γD-crys protein. By binding to the interface region between the NTD and CTD of the protein, α-crys effectively inhibits the formation of domain-swapped aggregates and mitigates protein aggregation. Analysis of the Markov state models using molecular dynamics trajectories confirms that minimum free energy conformations correspond to the binding of the α-crystallin domain (ACD) of α-crys to NTD2 and CTD4 that form the interdomain interface.

Computational Analysis of the Tripartite Interaction of Phasins (PhaP4 and 5)-Sigma Factor (σ24)-DNA of Azospirillum brasilense Sp7

Azospirillum brasilense Sp7 produces PHB, which is covered by granule-associated proteins (GAPs). Phasins are the main GAPs. Previous studies have shown phasins can regulate PHB synthesis. When A. brasilense grows under stress conditions, it uses sigma factors to transcribe genes for survival. One of these factors is the σ24 factor. This study determined the possible interaction between phasins and the σ24 factor or phasin-σ24 factor complex and DNA. Three-dimensional structures of phasins and σ24 factor structures were predicted using the I-TASSER and SWISS-Model servers, respectively. Subsequently, a molecular docking between phasins and the σ24 factor was performed using the ClusPro 2.0 server, followed by molecular docking between protein complexes and DNA using the HDOCK server. Evaluation of the types of ligand-receptor interactions was performed using the BIOVIA Discovery Visualizer for three-dimensional diagrams, as well as the LigPlot server to obtain bi-dimensional diagrams. The results showed the phasins (Pha4Abs7 or Pha5Abs7)-σ24 factor complex was bound near the -35 box of the promoter region of the phaC gene. However, in the individual interaction of PhaP5Abs7 and the σ24 factor, with DNA, both proteins were bound to the -35 box. This did not occur with PhaP4Abs7, which was bound to the -10 box. This change could affect the transcription level of the phaC gene and possibly affect PHB synthesis.

Fusing Peptide Epitopes for Advanced Multiplex Serological Testing for SARS-CoV-2 Antibody Detection

The tragic COVID-19 pandemic, which has seen a total of 655 million cases worldwide and a death toll of over 6.6 million seems finally tailing off. Even so, new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to arise, the severity of which cannot be predicted in advance. This is concerning for the maintenance and stability of public health, since immune evasion and increased transmissibility may arise. Therefore, it is crucial to continue monitoring antibody responses to SARS-CoV-2 in the general population. As a complement to polymerase chain reaction tests, multiplex immunoassays are elegant tools that use individual protein or peptide antigens simultaneously to provide a high level of sensitivity and specificity. To further improve these aspects of SARS-CoV-2 antibody detection, as well as accuracy, we have developed an advanced serological peptide-based multiplex assay using antigen-fused peptide epitopes derived from both the spike and the nucleocapsid proteins. The significance of the epitopes selected for antibody detection has been verified by in silico molecular docking simulations between the peptide epitopes and reported SARS-CoV-2 antibodies. Peptides can be more easily and quickly modified and synthesized than full length proteins and can, therefore, be used in a more cost-effective manner. Three different fusion-epitope peptides (FEPs) were synthesized and tested by enzyme-linked immunosorbent assay (ELISA). A total of 145 blood serum samples were used, compromising 110 COVID-19 serum samples from COVID-19 patients and 35 negative control serum samples taken from COVID-19-free individuals before the outbreak. Interestingly, our data demonstrate that the sensitivity, specificity, and accuracy of the results for the FEP antigens are higher than for single peptide epitopes or mixtures of single peptide epitopes. Our FEP concept can be applied to different multiplex immunoassays testing not only for SARS-CoV-2 but also for various other pathogens. A significantly improved peptide-based serological assay may support the development of commercial point-of-care tests, such as lateral-flow-assays.

SARS-CoV-2 ORF7a Mutation Found in BF.5 and BF.7 Sublineages Impacts Its Functions

A feature of the SARS-CoV-2 Omicron subvariants BF.5 and BF.7 that recently circulated mainly in China and Japan was the high prevalence of the ORF7a: H47Y mutation, in which the 47th residue of ORF7a has been mutated from a histidine (H) to a tyrosine (Y). Here, we evaluated the effect of this mutation on the three main functions ascribed to the SARS-CoV-2 ORF7a protein. Our findings show that H47Y mutation impairs the ability of SARS-CoV-2 ORF7a to antagonize the type I interferon (IFN-I) response and to downregulate major histocompatibility complex I (MHC-I) cell surface levels, but had no effect in its anti-SERINC5 function. Overall, our results suggest that the H47Y mutation of ORF7a affects important functions of this protein, resulting in changes in virus pathogenesis.

Computational Procedure for Predicting Excipient Effects on Protein-Protein Affinities

Protein-protein interactions lie at the center of many biological processes and are a challenge in formulating biological drugs, such as antibodies. A key to mitigating protein association is to use small-molecule additives, i.e., excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials, and a thermodynamic perturbation theory. In a proof of principle, this method successfully ranks the order of four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting the effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost intensive. Computational methods have potential to accelerate epitope predictions, however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologs. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2 Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis alone each proved ineffectual in differentiating between two putative binding models referred to as parallel and perpendicular. However, our integrated approach based on dynamic network analysis showed that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols including cross linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Our research highlights the potential of deploying dynamic network analysis to refine AI-based structure predictions for precise predictions of protein-protein interaction interfaces.

Glyceraldehyde-3-Phosphate Dehydrogenase Binds with Spike Protein and Inhibits the Entry of SARS-CoV-2 into Host Cells

INTRODUCTION

Coronavirus disease 2019 caused by coronavirus-2 (SARS-CoV-2) has emerged as an aggressive viral pandemic. Health care providers confront a challenging task for rapid development of effective strategies to combat this and its long-term after effects. Virus entry into host cells involves interaction between receptor-binding domain (RBD) of spike (S) protein S1 subunit with angiotensin converting enzyme present on host cells. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a moonlighting enzyme involved in cellular glycolytic energy metabolism and micronutrient homeostasis. It is deployed in various cellular compartments and the extra cellular milieu. Though it is known to moonlight as a component of mammalian innate immune defense machinery, till date its role in viral restriction remains unknown.

METHOD

Recombinant S protein, the RBD, and human GAPDH protein were used for solid phase binding assays and biolayer interferometry. Pseudovirus particles expressing four different strain variants of S protein all harboring ZsGreen gene as marker of infection were used for flow cytometry-based infectivity assays.

RESULTS

Pseudovirus entry into target cells in culture was significantly inhibited by addition of human GAPDH into the extracellular medium. Binding assays demonstrated that human GAPDH binds to S protein and RBD of SARS-CoV-2 with nanomolar affinity.

CONCLUSIONS

Our investigations suggest that this interaction of GAPDH interferes in the viral docking with hACE2 receptors, thereby affecting viral ingress into mammalian cells.

Determining Structural Changes for Ligand Recognition between Human and Rat Phosphorylated BACE1 in Silico and Its Phosphorylation by GSK3β at Thr252 by in Vitro Studies

Alzheimer's disease (AD) is a neurodegenerative disease affecting older adults. AD pathogenesis involves the production of the highly neurotoxic amyloid-β peptide 1-42 (Aβ1-42) from β-site amyloid precursor protein cleaving enzyme 1 (BACE1). The phosphorylation of BACE1 at Thr252 increases its enzymatic activity. This study examined the phosphorylation of BACE1 from human and rat BACE1 in silico through phosphorylation predictors. Besides, we explored how phosphorylation at various sites affected the BACE1 structure and its affinity with amyloid precursor protein (APP) and six BACE1 inhibitors. Additionally, we evaluated the phosphorylation of Thr252-BACE1 by glycogen synthase kinase 3 β (GSK3β) in vitro. The phosphorylation predictors showed that Thr252, Ser59, Tyr76, Ser71, and Ser83 could be phosphorylated. Also, Ser127 in rat BACE1 can be phosphorylated, but human BACE1 has a Gly at this position. Molecular dynamics simulations showed that Ser127 plays an important role in the open and closed BACE1 conformational structures. Docking studies and the molecular mechanics generalized Born surface area (MMGBSA) approach showed that human BACE1 phosphorylated at Thr252 and rat BACE1 phosphorylated at Ser71 have the best binding and free energy with APP, forming hydrogen bonds with Asp672. Importantly, inhibitors have a higher affinity for the phosphorylated rat BACE1 than for its human counterpart, which could explain their failure during clinical trials. Finally, in vitro experiments showed that GSK3β could phosphorylate BACE1. In conclusion, BACE1 phosphorylation influences the BACE1 conformation and its recognition of ligands and substrates. Thus, these features should be carefully considered in the design of BACE1 inhibitors.

A significance score for protein-protein interaction models through random docking

Comparing accuracies of structural protein-protein interaction (PPI) models for different complexes on an absolute scale is a challenge, requiring normalization of scores across structures of different sizes and shapes. To help address this challenge, we have developed a statistical significance metric for docking models, called random-docking (RD) p-value. This score evaluates a PPI model based on how likely a random docking process is to produce a model of better or equal accuracy. The binding partners are randomly docked against each other a large number of times, and the probability of sampling a model of equal or greater accuracy from this reference distribution is the RD p-value. Using a subset of top predicted models from CAPRI (Critical Assessment of PRediction of Interactions) rounds over 2017-2020, we find that the ease of achieving a given root mean squared deviation or DOCKQ score varies considerably by target; achieving the same relative metric can be thousands of times easier for one complex compared to another. In contrast, RD p-values inherently normalize scores for models of different complexes, making them globally comparable. Furthermore, one can calculate RD p-values after generating a reference distribution that accounts for prior information about the interface geometry, such as residues involved in binding, by giving the random-docking process access the same information. Thus, one can decouple improvements in prediction accuracy that arise solely from basic modeling constraints from those due to the rest of the method. We provide efficient code for computing RD p-values at https://github.com/Grigoryanlab/RDP.

Novel role of peptidoglycan recognition protein 2 in activating NOD2-NFκB inflammatory axis in coronary artery disease

BACKGROUNDS AND AIMS

The role of inflammation in driving atherosclerosis is well-established. It exerts systemic effects beyond the local site of plaque formation. In the context of coronary artery disease (CAD), the proteins that show altered levels in the plasma, are potentially important for understanding the key regulatory mechanism in the pathogenesis of atherosclerosis. A case-control study revealed that plasma soluble Peptidoglycan Recognition Protein 2 (PGLYRP2) primarily produced by the liver, is increased in subjects with CAD. Furthermore, the concentration of PGLYRP2 in the blood correlates with the severity of coronary artery disease. Thus, it raises interest in understanding the exact role of the protein in aortic inflammation and plaque progression.

METHODS

We evaluated the plasma concentration of PGLYRP2 in three distinct groups: patients with CAD (N = 68), asymptomatic individuals (N = 34), and healthy volunteers (N = 20). Furthermore, we investigated the correlation between disease severity and PGLYRP2 levels in CAD patients. To identify potential binding partners of PGLYRP2, we employed computational analysis. We verified the PGLYRP2-NOD2 interaction in macrophage cells and elucidated the inflammatory pathways activated by PGLYRP2 within these cells. To assess the impact of PGLYRP2, we examined its effects in the atherosclerotic mice model (ApoE-/-).

RESULTS

In this study, we report for the first time that Nucleotide-binding Oligomerization domain 2 (NOD2) which is expressed on the surface of macrophages, is a receptor of PGLYRP2. The N-terminal domain of PGLYRP2 directly binds to NOD2 and activates the NOD2-RIP2-NFκB cascade that promotes the secretion of proinflammatory cytokines like TNFα, IL1β, and IL-8. In the atherosclerotic mice model (ApoE-/-) we demonstrate that elevated PGLYRP2 level is parallel with increased proinflammatory cytokines in the plasma when fed a High Cholesterol Diet (HCD). Immunohistochemical analysis reveals that PGLYRP2 is co-localized with NOD2 on the macrophages at the site of the lesion.

CONCLUSIONS

Taken together, our data demonstrate that NOD2 acts as a receptor of PGLYRP2 on macrophages, which mediates the activation of the NOD2-RIP2-NFκB pathway and promotes inflammation, thus significantly contributing to the development and progression of atherosclerosis.

APRF1 Interactome Reveals HSP90 as a New Player in the Complex That Epigenetically Regulates Flowering Time in Arabidopsis thaliana

WD40 repeat proteins (WDRs) are present in all eukaryotes and include members that are implicated in numerous cellular activities. They act as scaffold proteins and thus as molecular "hubs" for protein-protein interactions, which mediate the assembly of multifunctional complexes that regulate key developmental processes in Arabidopsis thaliana, such as flowering time, hormonal signaling, and stress responses. Despite their importance, many aspects of their putative functions have not been elucidated yet. Here, we show that the late-flowering phenotype of the anthesis promoting factor 1 (aprf1) mutants is temperature-dependent and can be suppressed when plants are grown under mild heat stress conditions. To gain further insight into the mechanism of APRF1 function, we employed a co-immunoprecipitation (Co-IP) approach to identify its interaction partners. We provide the first interactome of APRF1, which includes proteins that are localized in several subcellular compartments and are implicated in diverse cellular functions. The dual nucleocytoplasmic localization of ARRF1, which was validated through the interaction of APRF1 with HEAT SHOCK PROTEIN 1 (HSP90.1) in the nucleus and with HSP90.2 in the cytoplasm, indicates a dynamic and versatile involvement of APRF1 in multiple biological processes. The specific interaction of APRF1 with the chaperon HSP90.1 in the nucleus expands our knowledge regarding the epigenetic regulation of flowering time in A. thaliana and further suggests the existence of a delicate thermoregulated mechanism during anthesis.

2B4: A potential target in Staphylococcus aureus associated allergic inflammation

Staphylococcus aureus (SA) and its exotoxins activate eosinophils (Eos) and mast cells (MCs) via CD48, a GPI-anchored receptor belonging to the signaling lymphocytes activation molecules (SLAM) family. 2B4 (CD244), an immuno-regulatory transmembrane receptor also belonging to the SLAM family, is the high-affinity ligand for CD48. 2B4 is expressed on several leukocytes including NK cells, T cells, basophils, monocytes, dendritic cells (DCs), and Eos. In the Eos and MCs crosstalk carried out by physical and soluble interactions (named the 'allergic effector unit', AEU), 2B4-CD48 binding plays a central role. As CD48 and 2B4 share some structural characteristics and SA colonization accompanies most of the allergic diseases, we hypothesized that SA exotoxins (e.g. Staphylococcus enterotoxin B, SEB) can also bind and activate 2B4 and thereby possibly further aggravate inflammation. To check our hypothesis, we used in vitro, in silico, and in vivo methods. By enzyme-linked immunosorbent assay (ELISA), flow cytometry (FC), fluorescence microscopy, and microscale thermophoresis, we have shown that SEB can bind specifically to 2B4. By Eos short- and long-term activation assays, we confirmed the functionality of the SEB-2B4 interaction. Using computational modeling, we identified possible SEB-binding sites on human and mouse 2B4. Finally, in vivo, in an SEB-induced peritonitis model, 2B4-KO mice showed a significant reduction of inflammatory features compared with WT mice. Altogether, the results of this study confirm that 2B4 is an important receptor in SEB-mediated inflammation, and therefore a role is suggested for 2B4 in SA associated inflammatory conditions.

Aggregation Dynamics Characteristics of Seven Different Aβ Oligomeric Isoforms-Dependence on the Interfacial Interaction

The aggregation of β-amyloid (Aβ) peptides has been confirmed to be associated with the onset of Alzheimer's disease (AD). Among the three phases of Aβ aggregation, the lag phase has been considered to be the best time for early Aβ pathological deposition clinical intervention and prevention for potential patients with normal cognition. Aβ peptide exists in various lengths in vivo, and Aβ oligomer in the early lag phase is neurotoxic but polymorphous and metastable, depending on Aβ length (isoform), molecular weight, and specific phase, and therefore hardly characterized experimentally. To cope with the problem, molecular dynamics simulation was used to investigate the aggregation process of five monomers for each of the seven common Aβ isoforms during the lag phase. Results showed that Aβ(1-40) and Aβ(1-38) monomers aggregated faster than their truncated analogues Aβ(4-40) and Aβ(4-38), respectively. However, the aggregation rate of Aβ(1-42) was slower than that of its truncated analogues Aβ(4-42) rather than that of Aβpe(3-42). More importantly, Aβ(1-38) is first predicted as more likely to form stable hexamer than the remaining five Aβ isoforms, as Aβ(1-42) does. It is hydrophobic interaction mainly (>50%) from the interfacial β1 and β2 regions of two reactants, pentamer and monomer, aggregated by Aβ(1-38)/Aβ(1-42) rather than by other Aβ isoforms, that drives the hexamer stably as a result of the formation of the effective hydrophobic collapse. This paper provides new insights into the aggregation characteristics of Aβ with different lengths and the conditions necessary for Aβ to form oligomers with a high molecular weight in the early lag phase, revealing the dependence of Aβ hexamer formation on the specific interfacial interaction.

Interaction of Tau with G-Protein-Coupled Purinergic P2Y12 Receptor by Molecular Docking and Molecular Dynamic Simulation

Alzheimer's disease, a progressive neurological disorder, is characterized by the accumulation of neurofibrillary tangles and senile plaques by Tau and amyloid-β, respectively, in the brain microenvironment. The misfolded protein aggregates interact with several components of neuronal and glial cells such as membrane lipids, receptors, transporters, enzymes, cytoskeletal proteins, etc. Under pathological conditions, Tau interacts with several G-protein-coupled receptors (GPCRs), which undergoes either receptor signaling or desensitization followed by internalization of the protein complex. The purinergic GPCR, P2Y12 which is expressed in microglial cells, plays a key role in its activation and migration. Microglial cells sense and migrate to the site of injury aided by P2Y12 receptor that interacts with ADP released from damaged cells. P2Y12 receptor also interacts with misfolded Tau accumulated at the extracellular space and promotes receptor-mediated internalization. Immunocolocalization and co-immunoprecipitation studies demonstrated the interaction of Tau species with the P2Y12 receptor. Later, in-silico analyses were carried out with the repeat domain of Tau (TauRD), which has been identified as the interacting partner of P2Y12 receptor by in-vitro studies. Molecular docking and molecular dynamics simulation studies show the stability and the type of interaction in TauRD-receptor complex. Tau interaction with P2Y12 receptor plays a significant role in maintaining the active state of microglia which could lead to neuroinflammation and neuronal damage in AD brain. Hence, blocking P2Y12-Tau interaction and P2Y12-mediated Tau internalization in microglial cells could be possible therapeutic strategies in downregulating the severity of neuroinflammation in AD.

Substrate profiling of the metalloproteinase ovastacin uncovers specific enzyme-substrate interactions and discloses fertilization-relevant substrates

The metalloproteinase ovastacin is released by the mammalian egg upon fertilization and cleaves a distinct peptide bond in zona pellucida protein 2 (ZP2), a component of the enveloping extracellular matrix. This limited proteolysis causes zona pellucida hardening, abolishes sperm binding, and thereby regulates fertility. Accordingly, this process is tightly controlled by the plasma protein fetuin-B, an endogenous competitive inhibitor. At present, little is known about how the cleavage characteristics of ovastacin differ from closely related proteases. Physiological implications of ovastacin beyond ZP2 cleavage are still obscure. In this study, we employed N-terminal amine isotopic labeling of substrates (N-TAILS) contained in the secretome of mouse embryonic fibroblasts to elucidate the substrate specificity and the precise cleavage site specificity. Furthermore, we were able to unravel the physicochemical properties governing ovastacin-substrate interactions as well as the individual characteristics that distinguish ovastacin from similar proteases, such as meprins and tolloid. Eventually, we identified several substrates whose cleavage could affect mammalian fertilization. Consequently, these substrates indicate newly identified functions of ovastacin in mammalian fertilization beyond zona pellucida hardening.

A computational procedure for predicting excipient effects on protein-protein affinities

Protein-protein interactions lie at the center of much biology and are a challenge in formulating biological drugs such as antibodies. A key to mitigating protein association is to use small molecule additives, i.e. excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials and a thermodynamic perturbation theory. In a proof of principle, this method successfully rank orders four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.