InterProSurf: a web server for predicting interacting sites on protein surfaces

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

Peptide based vaccine designing against endemic causing mammarenavirus using reverse vaccinology approach

The rodent-borne Arenavirus in humans has led to the emergence of regional endemic situations and has deeply emerged into pandemic-causing viruses. Arenavirus have a bisegmented ambisense RNA that produces four proteins: glycoprotein, nucleocapsid, RdRp and Z protein. The peptide-based vaccine targets the glycoprotein of the virus encountered by the immune system. Screening of B-Cell and T-Cell epitopes was done based on their immunological properties like antigenicity, allergenicity, toxicity and anti-inflammatory properties were performed. Selected epitopes were then clustered and epitopes were stitched using linker sequences. The immunological and physico-chemical properties of the vaccine construct was checked and modelled structure was validated by a 2-step MD simulation. The thermostability of the vaccine was checked followed by the immune simulation to test the immunogenicity of the vaccine upon introduction into the body over the course of the next 100 days and codon optimization was performed. Finally a 443 amino acid long peptide vaccine was designed which could provide protection against several members of the mammarenavirus family in a variety of population worldwide as denoted by the epitope conservancy and population coverage analysis. This study of designing a peptide vaccine targeting the glycoprotein of mammarenavirues may help develop novel therapeutics in near future.

The structure of the diheme cytochrome c4 from Neisseria gonorrhoeae reveals multiple contributors to tuning reduction potentials

Cytochrome c4 (c4) is a diheme protein implicated as an electron donor to cbb3 oxidases in multiple pathogenic bacteria. Despite its prevalence, understanding of how specific structural features of c4 optimize its function is lacking. The human pathogen Neisseria gonorrhoeae (Ng) thrives in low oxygen environments owing to the activity of its cbb3 oxidase. Herein, we report characterization of Ng c4. Spectroelectrochemistry experiments of the wild-type (WT) protein have shown that the two Met/His-ligated hemes differ in potentials by ∼100 mV, and studies of the two His/His-ligated variants provided unambiguous assignment of heme A from the N-terminal domain of the protein as the high-potential heme. The crystal structure of the WT protein at 2.45 Å resolution has revealed that the two hemes differ in their solvent accessibility. In particular, interactions made by residues His57 and Ser59 in Loop1 near the axial ligand Met63 contribute to the tight enclosure of heme A, working together with the surface charge, to raise the reduction potential of the heme iron in this domain. The structure reveals a prominent positively-charged patch, which encompasses surfaces of both domains. In contrast to prior findings with c4 from Pseudomonas stutzeri, the interdomain interface of Ng c4 contributes minimally to the values of the heme iron potentials in the two domains. Analyses of the heme solvent accessibility, interface properties, and surface charges offer insights into the interplay of these structural elements in tuning redox properties of c4 and other multiheme proteins.

RGS6 drives cardiomyocyte death following nucleolar stress by suppressing Nucleolin/miRNA-21

BACKGROUND

Prior evidence demonstrated that Regulator of G protein Signaling 6 (RGS6) translocates to the nucleolus in response to cytotoxic stress though the functional significance of this phenomenon remains unknown.

METHODS

Utilizing in vivo gene manipulations in mice, primary murine cardiac cells, human cell lines and human patient samples we dissect the participation of a RGS6-nucleolin complex in chemotherapy-dependent cardiotoxicity.

RESULTS

Here we demonstrate that RGS6 binds to a key nucleolar protein, Nucleolin, and controls its expression and activity in cardiomyocytes. In the human myocyte AC-16 cell line, induced pluripotent stem cell derived cardiomyocytes, primary murine cardiomyocytes, and the intact murine myocardium tuning RGS6 levels via overexpression or knockdown resulted in diametrically opposed impacts on Nucleolin mRNA, protein, and phosphorylation.RGS6 depletion provided marked protection against nucleolar stress-mediated cell death in vitro, and, conversely, RGS6 overexpression suppressed ribosomal RNA production, a key output of the nucleolus, and triggered death of myocytes. Importantly, overexpression of either Nucleolin or Nucleolin effector miRNA-21 counteracted the pro-apoptotic effects of RGS6. In both human and murine heart tissue, exposure to the genotoxic stressor doxorubicin was associated with an increase in the ratio of RGS6/Nucleolin. Preventing RGS6 induction via introduction of RGS6-directed shRNA via intracardiac injection proved cardioprotective in mice and was accompanied by restored Nucleolin/miRNA-21 expression, decreased nucleolar stress, and decreased expression of pro-apoptotic, hypertrophy, and oxidative stress markers in heart.

CONCLUSION

Together, these data implicate RGS6 as a driver of nucleolar stress-dependent cell death in cardiomyocytes via its ability to modulate Nucleolin. This work represents the first demonstration of a functional role for an RGS protein in the nucleolus and identifies the RGS6/Nucleolin interaction as a possible new therapeutic target in the prevention of cardiotoxicity.

Application of temperature-dependent and steered molecular dynamics simulation to screen anti-dengue compounds against Marburg virus

Marburg virus infections are extremely fatal with a fatality range of 23% to 90%, therefore there is an urgent requirement to design and develop efficient therapeutic molecules. Here, a comprehensive temperature-dependent molecular dynamics (MD) simulation method was implemented to identify the potential molecule from the anti-dengue compound library that can inhibit the function of the VP24 protein of Marburg. Virtual high throughput screening identified five effective binders of VP24 after screening 484 anti-dengue compounds. These compounds were treated in MD simulation at four different temperatures: 300, 340, 380, and 420 K. Higher temperatures showed dissociation of hit compounds from the protein. Further, triplicates of 100 ns MD simulation were conducted which showed that compounds ID = 118717693, and ID = 5361 showed strong stability with the protein molecule. These compounds were further validated using Δ G binding free energies and they showed: -30.38 kcal/mol, and -67.83 kcal/mol binding free energies, respectively. Later, these two compounds were used in steered MD simulation to detect its dissociation. Compound ID = 5361 showed the maximum pulling force of 199.02 kcal/mol/nm to dissociate the protein-ligand complex while ID = 118717693 had a pulling force of 101.11 kcal/mol/nm, respectively. This ligand highest number of hydrogen bonds with varying occupancies at 89.93%, 69.80%, 57.93%, 52.33%, and 50.63%. This study showed that ID = 5361 can bind with the VP24 strongly and has the potential to inhibit its function which can be validated in the in-vitro experiment.Communicated by Ramaswamy H. Sarma.

In silico evaluation of the inhibitory potential of nucleocapsid inhibitors of SARS-CoV-2: a binding and energetic perspective

The COVID-19 outbreak brought on by the SARS-CoV-2 virus continued to infect a sizable population worldwide. The SARS-CoV-2 nucleocapsid (N) protein is the most conserved RNA-binding structural protein and is a desirable target because of its involvement in viral transcription and replication. Based on this aspect, this study focused to repurpose antiviral compounds approved or in development for treating COVID-19. The inhibitors chosen are either FDA-approved or are currently being studied in clinical trials against COVID-19. Initially, they were designed to target stress granules and other RNA biology. We have utilized structure-based molecular docking and all-atom molecular dynamics (MD) simulation approach to investigate in detail the binding energy and binding modes of the different anti-N inhibitors to N protein. The result showed that five drugs including Silmitasterib, Ninetanidinb, Ternatin, Luteolin, Fedratinib, PJ34, and Zotatafin were found interacting with RNA binding sites as well as to predicted protein interface with higher binding energy. Overall, drug binding increases the stability of the complex with maximum stability found in the order, Silmitasertib > PJ34 > Zotatatafin. In addition, the frustration changes due to drug binding brings a decrease in local frustration and this decrease is mainly observed in α-helix, β3, β5, and β6 strands and are important for drug binding. Our in-silico data suggest that an effective interaction occurs for some of the tested drugs and prompt their further validation to reduce the rapid outspreading of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

In silico characterization, molecular docking, and dynamic simulation of a novel fungal cell-death suppressing effector, MoRlpA as potential cathepsin B-like cysteine protease inhibitor during rice blast infection

The blast fungus Magnaporthe oryzae is one of the most notorious pathogens affecting rice production worldwide. The cereal killer employs a special class of small secreted proteins called effectors to manipulate and perturb the host metabolism. In turn, the host plants trigger effector-triggered immunity (ETI) via localized cell death and hypersensitive response (HR). We have identified and characterized a novel secreted effector MoRlpA from M. oryzae by extensive in silico methods. The localization studies suggested that it is exclusively secreted in the host apoplasts. Interestingly, MoRlpA interacts with a protease, cathepsin B from rice with highest affinity. The 3D structural models of both the proteins were generated. Cathepsin B-like cysteine proteases are usually involved in programmed cell death (PCD) and autophagy in plants which lead to generation of HR upon infection. Our results suggest that MoRlpA interacts with rice cathepsin B-like cysteine protease and demolish the host counter-attack by suppressing cell death and HR during an active blast infection. This was further validated by molecular docking and molecular dynamic simulation analyses. The important residues involved in the rice-blast pathogen interactions were deciphered. Overall, this research highlights stable interactions between MoRlpA-OsCathB during rice blast pathogenesis and providing an insight into how this novel RlpA protease inhibitor-cum-effector modulates the host's apoplast to invade the host tissues and establish a successful infection. Thus, this research will help to develop potential fungicide to block the binding region of MoRlpA target so that the cryptic pathogen would be recognized by the host. HIGHLIGHTSFor the first time, a novel secreted effector protein, MoRlpA has been identified and characterised from M. oryzae in silicoMoRlpA contains a rare lipoprotein A-like DPBB domain which is often an enzymatic domain in other systemsMoRlpA as an apoplastic effector interacts with the rice protease OsCathB to suppress the cell death and hypersensitive response during rice blast infectionThe three-dimensional structures of both the MoRlpA and OsCathB proteins were predictedMoRlpA-OsCathB interactions were analysed by molecular docking and molecular dynamic simulation studiesCommunicated by Ramaswamy H. Sarma.

In Vitro Affinity Maturation of Nanobodies against Mpox Virus A29 Protein Based on Computer-Aided Design

Mpox virus (MPXV), the most pathogenic zoonotic orthopoxvirus, caused worldwide concern during the SARS-CoV-2 epidemic. Growing evidence suggests that the MPXV surface protein A29 could be a specific diagnostic marker for immunological detection. In this study, a fully synthetic phage display library was screened, revealing two nanobodies (A1 and H8) that specifically recognize A29. Subsequently, an in vitro affinity maturation strategy based on computer-aided design was proposed by building and docking the A29 and A1 three-dimensional structures. Ligand-receptor binding and molecular dynamics simulations were performed to predict binding modes and key residues. Three mutant antibodies were predicted using the platform, increasing the affinity by approximately 10-fold compared with the parental form. These results will facilitate the application of computers in antibody optimization and reduce the cost of antibody development; moreover, the predicted antibodies provide a reference for establishing an immunological response against MPXV.

Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

Routinely screened antibody fragments usually require further in vitro maturation to achieve the desired biophysical properties. Blind in vitro strategies can produce improved ligands by introducing random mutations into the original sequences and selecting the resulting clones under more and more stringent conditions. Rational approaches exploit an alternative perspective that aims first at identifying the specific residues potentially involved in the control of biophysical mechanisms, such as affinity or stability, and then to evaluate what mutations could improve those characteristics. The understanding of the antigen-antibody interactions is instrumental to develop this process the reliability of which, consequently, strongly depends on the quality and completeness of the structural information. Recently, methods based on deep learning approaches critically improved the speed and accuracy of model building and are promising tools for accelerating the docking step. Here, we review the features of the available bioinformatic instruments and analyze the reports illustrating the result obtained with their application to optimize antibody fragments, and nanobodies in particular. Finally, the emerging trends and open questions are summarized.

RGS7 balances acetylation/de-acetylation of p65 to control chemotherapy-dependent cardiac inflammation

Cardiotoxicity remains a major limitation in the clinical utility of anthracycline chemotherapeutics. Regulator of G-protein Signaling 7 (RGS7) and inflammatory markers are up-regulated in the hearts of patients with a history of chemotherapy particularly those with reduced left-ventricular function. RGS7 knockdown in either the murine myocardium or isolated murine ventricular cardiac myocytes (VCM) or cultured human VCM provided marked protection against doxorubicin-dependent oxidative stress, NF-κB activation, inflammatory cytokine production, and cell death. In exploring possible mechanisms causally linking RGS7 to pro-inflammatory signaling cascades, we found that RGS7 forms a complex with acetylase Tip60 and deacetylase sirtuin 1 (SIRT1) and controls the acetylation status of the p65 subunit of NF-κB. In VCM, the detrimental impact of RGS7 could be mitigated by inhibiting Tip60 or activating SIRT1, indicating that the ability of RGS7 to modulate cellular acetylation capacity is critical for its pro-inflammatory actions. Further, RGS7-driven, Tip60/SIRT1-dependent cytokines released from ventricular cardiac myocytes and transplanted onto cardiac fibroblasts increased oxidative stress, markers of transdifferentiation, and activity of extracellular matrix remodelers emphasizing the importance of the RGS7-Tip60-SIRT1 complex in paracrine signaling in the myocardium. Importantly, while RGS7 overexpression in heart resulted in sterile inflammation, fibrotic remodeling, and compromised left-ventricular function, activation of SIRT1 counteracted the detrimental impact of RGS7 in heart confirming that RGS7 increases acetylation of SIRT1 substrates and thereby drives cardiac dysfunction. Together, our data identify RGS7 as an amplifier of inflammatory signaling in heart and possible therapeutic target in chemotherapeutic drug-induced cardiotoxicity.

A structural model of the iRhom-ADAM17 sheddase complex reveals functional insights into its trafficking and activity

Several membrane-anchored signal mediators such as cytokines (e.g. TNFα) and growth factors are proteolytically shed from the cell surface by the metalloproteinase ADAM17, which, thus, has an essential role in inflammatory and developmental processes. The membrane proteins iRhom1 and iRhom2 are instrumental for the transport of ADAM17 to the cell surface and its regulation. However, the structure-function determinants of the iRhom-ADAM17 complex are poorly understood. We used AI-based modelling to gain insights into the structure-function relationship of this complex. We identified different regions in the iRhom homology domain (IRHD) that are differentially responsible for iRhom functions. We have supported the validity of the predicted structure-function determinants with several in vitro, ex vivo and in vivo approaches and demonstrated the regulatory role of the IRHD for iRhom-ADAM17 complex cohesion and forward trafficking. Overall, we provide mechanistic insights into the iRhom-ADAM17-mediated shedding event, which is at the centre of several important cytokine and growth factor pathways.

AA16 Oxidoreductases Boost Cellulose-Active AA9 Lytic Polysaccharide Monooxygenases from Myceliophthora thermophila

Copper-dependent lytic polysaccharide monooxygenases (LPMOs) classified in Auxiliary Activity (AA) families are considered indispensable as synergistic partners for cellulolytic enzymes to saccharify recalcitrant lignocellulosic plant biomass. In this study, we characterized two fungal oxidoreductases from the new AA16 family. We found that MtAA16A from Myceliophthora thermophila and AnAA16A from Aspergillus nidulans did not catalyze the oxidative cleavage of oligo- and polysaccharides. Indeed, the MtAA16A crystal structure showed a fairly LPMO-typical histidine brace active site, but the cellulose-acting LPMO-typical flat aromatic surface parallel to the histidine brace region was lacking. Further, we showed that both AA16 proteins are able to oxidize low-molecular-weight reductants to produce H2O2. The oxidase activity of the AA16s substantially boosted cellulose degradation by four AA9 LPMOs from M. thermophila (MtLPMO9s) but not by three AA9 LPMOs from Neurospora crassa (NcLPMO9s). The interplay with MtLPMO9s is explained by the H2O2-producing capability of the AA16s, which, in the presence of cellulose, allows the MtLPMO9s to optimally drive their peroxygenase activity. Replacement of MtAA16A by glucose oxidase (AnGOX) with the same H2O2-producing activity could only achieve less than 50% of the boosting effect achieved by MtAA16A, and earlier MtLPMO9B inactivation (6 h) was observed. To explain these results, we hypothesized that the delivery of AA16-produced H2O2 to the MtLPMO9s is facilitated by protein-protein interaction. Our findings provide new insights into the functions of copper-dependent enzymes and contribute to a further understanding of the interplay of oxidative enzymes within fungal systems to degrade lignocellulose.

An inclusive study of deleterious missense PAX9 variants using user-friendly tools reveals structural, functional alterations, as well as potential therapeutic targets

Mutations in the PAX9 are responsible for non-syndromic tooth agenesis in humans, although their structural and functional consequences on protein phenotype, stability, and posttranslational modifications (PTMs) have not yet been adequately investigated. This in silico study focuses on retrieving the six most deleterious mutations (L21P, R26W, R28P, G51S, I87F, and K91E) of PAX9 that has been linked to severe oligodontia. Several computational algorithm methods were used to determine the deleterious effects of PAX9 mutations. Analysis of gene ontology, protein interactions, and PTMs indicated significant functional changes caused by PAX9 mutations. The structural superimposition of the wild-type and mutant PAX9 variants revealed structural changes in locations that were present in the structures of all six variations. The conserved domain analysis revealed that the areas shared by all six variations contained unique sections that lacked DNA binding or protein-protein interaction sites, suggesting prospective drug target sites for functional restoration. The protein-protein interaction network showed KDM5B as PAX9's strongest interacting partner similar to MSX1. The PAX9 protein's structural conformations, compactness, stiffness, and function may all be impacted by changes, according to MD simulations. In addition, research on cell lines and animal models may be valuable in establishing their specific roles in functional annotations.

The Molecular Chaperone Mechanism of the C-Terminal Domain of Large-Size Subunit Catalases

Large-size subunit catalases (LSCs) have an additional C-terminal domain (CT) that is structurally similar to Hsp31 and DJ-1 proteins, which have molecular chaperone activity. The CT of LSCs derives from a bacterial Hsp31 protein. There are two CT dimers with inverted symmetry in LSCs, one dimer in each pole of the homotetrameric structure. We previously demonstrated the molecular chaperone activity of the CT of LSCs. Like other chaperones, LSCs are abundant proteins that are induced under stress conditions and during cell differentiation in bacteria and fungi. Here, we analyze the mechanism of the CT of LSCs as an unfolding enzyme. The dimeric form of catalase-3 (CAT-3) CT (TDC3) of Neurospora crassa presented the highest activity as compared to its monomeric form. A variant of the CAT-3 CT lacking the last 17 amino acid residues (TDC3Δ17aa), a loop containing hydrophobic and charged amino acid residues only, lost most of its unfolding activity. Substituting charged for hydrophobic residues or vice versa in this C-terminal loop diminished the molecular chaperone activity in all the mutant variants analyzed, indicating that these amino acid residues play a relevant role in its unfolding activity. These data suggest that the general unfolding mechanism of CAT-3 CT involves a dimer with an inverted symmetry, and hydrophobic and charged amino acid residues. Each tetramer has four sites of interaction with partially unfolded or misfolded proteins. LSCs preserve their catalase activity under different stress conditions and, at the same time, function as unfolding enzymes.

Cryo-EM structure of human heptameric pannexin 2 channel

Pannexin 2 (Panx2) is a large-pore ATP-permeable channel with critical roles in various physiological processes, such as the inflammatory response, energy production and apoptosis. Its dysfunction is related to numerous pathological conditions including ischemic brain injury, glioma and glioblastoma multiforme. However, the working mechanism of Panx2 remains unclear. Here, we present the cryo-electron microscopy structure of human Panx2 at a resolution of 3.4 Å. Panx2 structure assembles as a heptamer, forming an exceptionally wide channel pore across the transmembrane and intracellular domains, which is compatible with ATP permeation. Comparing Panx2 with Panx1 structures in different states reveals that the Panx2 structure corresponds to an open channel state. A ring of seven arginine residues located at the extracellular entrance forms the narrowest site of the channel, which serves as the critical molecular filter controlling the permeation of substrate molecules. This is further verified by molecular dynamics simulations and ATP release assays. Our studies reveal the architecture of the Panx2 channel and provide insights into the molecular mechanism of its channel gating.

Influence of the Interdomain Interface on Structural and Redox Properties of Multiheme Proteins

Multiheme proteins are important in energy conversion and biogeochemical cycles of nitrogen and sulfur. A diheme cytochrome c4 (c4) was used as a model to elucidate roles of the interdomain interface on properties of iron centers in its hemes A and B. Isolated monoheme domains c4-A and c4-B, together with the full-length diheme c4 and its Met-to-His ligand variants, were characterized by a variety of spectroscopic and stability measurements. In both isolated domains, the heme iron is Met/His-ligated at pH 5.0, as in the full-length c4, but becomes His/His-ligated in c4-B at higher pH. Intradomain contacts in c4-A are minimally affected by the separation of c4-A and c4-B domains, and isolated c4-A is folded. In contrast, the isolated c4-B is partially unfolded, and the interface with c4-A guides folding of this domain. The c4-A and c4-B domains have the propensity to interact even without the polypeptide linker. Thermodynamic cycles have revealed properties of monomeric folded isolated domains, suggesting that ferrous (FeII), but not ferric (FeIII) c4-A and c4-B, is stabilized by the interface. This study illustrates the effects of the interface on tuning structural and redox properties of multiheme proteins and enriches our understanding of redox-dependent complexation.

Design of nanobody-based bispecific constructs by in silico affinity maturation and umbrella sampling simulations

Random mutagenesis is the natural opportunity for proteins to evolve and biotechnologically it has been exploited to create diversity and identify variants with improved characteristics in the mutant pools. Rational mutagenesis based on biophysical assumptions and supported by computational power has been proposed as a faster and more predictable strategy to reach the same aim. In this work we confirm that substantial improvements in terms of both affinity and stability of nanobodies can be obtained by using combinations of algorithms, even for binders with already high affinity and elevated thermal stability. Furthermore, in silico approaches allowed the development of an optimized bispecific construct able to bind simultaneously the two clinically relevant antigens TNF-α and IL-23 and, by means of its enhanced avidity, to inhibit effectively the apoptosis of TNF-α-sensitive L929 cells. The results revealed that salt bridges, hydrogen bonds, aromatic-aromatic and cation-pi interactions had a critical role in increasing affinity. We provided a platform for the construction of high-affinity bispecific constructs based on nanobodies that can have relevant applications for the control of all those biological mechanisms in which more than a single antigen must be targeted to increase the treatment effectiveness and avoid resistance mechanisms.

In silico study on miRNA regulation and NSs protein interactome characterization of the SFTS virus

Severe fever with thrombocytopenia syndrome causing virus i.e. SFTS virus has increased in the last few years. The underlying cause and mechanism of disease progression and development of symptoms is not well known. Many viruses including Hepatitis B, Hepatitis C, HIV-1, Herpes virus, Dengue virus and many others have been seen to regulate their functions at the miRNA level. This study aimed to find out those cellular miRNAs, which can be mimicked or antagonized by the viral genome and analyze the effect of these miRNAs on various gene functions. Investigations in this study suggest a correlation between miRNA regulation with the disease symptoms and progression. By exhaustive literature survey we have tried to identify the interacting partners of the Non Structural S (NSs) protein and characterized the protein-protein interactions. The binding interface that can serve as target for therapeutic studies involving the interfacial residues was analyzed. This study would serve as an avenue to design therapeutics making use of not only protein-protein interactions but also miRNA based regulation as well.

RGS11-CaMKII complex mediated redox control attenuates chemotherapy-induced cardiac fibrosis

Dose limiting cardiotoxicity remains a major limiting factor in the clinical use of several cancer chemotherapeutics including anthracyclines and the antimetabolite 5-fluorouracil (5-FU). Prior work has demonstrated that chemotherapeutics increase expression of R7 family regulator of G protein signaling (RGS) protein-binding partner Gβ5, which drives myocyte cytotoxicity. However, though several R7 family members are expressed in heart, the exact role of each protein in chemotherapy driven heart damage remains unclear. Here, we demonstrate that RGS11, downregulated in the human heart following chemotherapy exposure, possesses potent anti-apoptotic actions, in direct opposition to the actions of fellow R7 family member RGS6. RGS11 forms a direct complex with the apoptotic kinase CaMKII and stress responsive transcription factor ATF3 and acts to counterbalance the ability of CaMKII and ATF3 to trigger oxidative stress, mitochondrial dysfunction, cell death, and release of the cardiokine neuregulin-1 (NRG1), which mediates pathological intercommunication between myocytes and endothelial cells. Doxorubicin triggers RGS11 depletion in the murine myocardium, and cardiac-specific OE of RGS11 decreases doxorubicin-induced fibrosis, myocyte hypertrophy, apoptosis, oxidative stress, and cell loss and aids in the maintenance of left ventricular function. Conversely, RGS11 knockdown in heart promotes cardiac fibrosis associated with CaMKII activation and ATF3/NRG1 induction. Indeed, inhibition of CaMKII largely prevents the fibrotic remodeling resulting from cardiac RGS11 depletion underscoring the functional importance of the RGS11-CaMKII interaction in the pathogenesis of cardiac fibrosis. These data describe an entirely new role for RGS11 in heart and identify RGS11 as a potential new target for amelioration of chemotherapy-induced cardiotoxicity.

Correlation between the binding affinity and the conformational entropy of nanobody SARS-CoV-2 spike protein complexes

Understanding the structural principles that determine the binding affinity of nanobodies to the spike protein of severe acute respiratory syndrome coronavirus 2 has been difficult. We analyzed electron microscopy maps of nanobody-spike complexes and quantified the conformational entropy of binding. This informed the design of an engineered nanobody with improved binding to the spike protein. This result offers a guiding principle for the rational maturation of nanobodies directed against the spike. High-binding potency nanobodies have been shown to be effective in animal models; thus, this technology could have application in future pandemics.

Camelid single-domain antibodies, also known as nanobodies, can be readily isolated from naïve libraries for specific targets but often bind too weakly to their targets to be immediately useful. Laboratory-based genetic engineering methods to enhance their affinity, termed maturation, can deliver useful reagents for different areas of biology and potentially medicine. Using the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and a naïve library, we generated closely related nanobodies with micromolar to nanomolar binding affinities. By analyzing the structure–activity relationship using X-ray crystallography, cryoelectron microscopy, and biophysical methods, we observed that higher conformational entropy losses in the formation of the spike protein–nanobody complex are associated with tighter binding. To investigate this, we generated structural ensembles of the different complexes from electron microscopy maps and correlated the conformational fluctuations with binding affinity. This insight guided the engineering of a nanobody with improved affinity for the spike protein.

A review of bioinformatics tools and web servers in different microarray platforms used in cancer research

Over the past decade, conventional lab work strategies have gradually shifted from being limited to a laboratory setting towards a bioinformatics era to help manage and process the vast amounts of data generated by omics technologies. The present work outlines the latest contributions of bioinformatics in analyzing microarray data and their application to cancer. We dissect different microarray platforms and their use in gene expression in cancer models. We highlight how computational advances empowered the microarray technology in gene expression analysis. The study on protein-protein interaction databases classified into primary, derived, meta-database, and prediction databases describes the strategies to curate and predict novel interaction networks in silico. In addition, we summarize the areas of bioinformatics where neural graph networks are currently being used, such as protein functions, protein interaction prediction, and in silico drug discovery and development. We also discuss the role of deep learning as a potential tool in the prognosis, diagnosis, and treatment of cancer. Integrating these resources efficiently, practically, and ethically is likely to be the most challenging task for the healthcare industry over the next decade; however, we believe that it is achievable in the long term.

In Silico Identification of Potential Inhibitors of the SARS-CoV-2 Nucleocapsid Through Molecular Docking-Based Drug Repurposing

SARS-CoV-2 is the virus responsible for the COVID-19 pandemic, and its effects on people worldwide continue to grow. Protein-targeted therapeutics are currently unavailable for this virus. As with other coronaviruses, the nucleocapsid (N) protein is the most conserved RNA-binding structural protein of SARS-CoV-2. The N protein is an appealing target because of its functional role in viral transcription and replication. Therefore, molecular docking method for structure-based drug design was used to investigate the binding energy and binding modes of various anti-N inhibitors in depth. The inhibitors selected were originally developed to target stress granules and other molecules involved in RNA biology, and were either FDA-approved or in the process of clinical trials for COVID-19. We aimed at targeting the N-terminal RNA binding domain (NTD) for molecular docking-based screening, on the basis of the first resolved crystal structure of SARS-CoV-2 N protein (PDB ID: 6M3M) and C-terminal domain (CTD) dimerization of the nucleocapsid phosphoprotein of SARS-COV-2 (PDB ID: 6WJI). Silmitasertib, nintedanib, ternatin, luteolin, and fedratinib were found to interact with RNA binding sites and to form a predicted protein interface with high binding energy. Similarly, silmitasertib, sirolimus-rapamycin, dovitinib, nintedanib, and fedratinib were found to interact with the SARS-CoV-2 N protein at its CTD dimerization sites, according to previous studies. In addition, we investigated an information gap regarding the relationships among the energetic landscape and stability and drug binding of the SARS-CoV-2 N NTD and CTD. Our in silico results clearly indicated that several tested drugs as potent putative inhibitors for COVID-19 therapeutics, thus indicating that they should be further validated as treatments to slow the spread of SARS-CoV-2.

Structural insights into the activation of blood coagulation factor XI zymogen by thrombin: A computational molecular dynamics study

Activation of human blood coagulation factor XI zymogen to factor XIa plays a significant role in the upstream coagulation pathway, in which factor XIa activates factor IX zymogen. The mechanistic details of the proteolytic activation of factor XI by the activating enzyme thrombin are not well-understood at atomic level. In this study, we employed a combination of molecular docking and microsecond time-scale molecular dynamics simulations to identify the key regions of interaction between fXI and thrombin. The activating complex between the substrate and enzyme was modeled to represent the initial acylation step of the serine-protease hydrolysis mechanism. The proposed solution structural complex, fIX:fIIa, obtained from 3 microseconds of MD refinement, suggests that the activation of factor XI is mediated by thrombin's anion binding exosite-II interactions with A3 and A4 domains. We predict that the two positively charged arginine residues (Arg409 and Arg413) in the exosite-2 region, the β- and γ-insertion loops of thrombin play an important structural role in the initial activating complex between fXI and thrombin.

Designing of nanobodies against Dengue virus Capsid: a computational affinity maturation approach

Dengue virus, an arbovirus, is one of the most prevalent diseases in the tropical environment and leads to huge number of casualties every year. No therapeutics are available till date against the viral disease and the only medications provide symptomatic relief. In this study, we have focused on utilizing conventional nanobodies and repurposing them for Dengue. Computationally affinity matured, best binding nanobodies tagged with constant antibody regions, could be proposed as therapeutics. These could also be applied for drug delivery purposes due to their high specificity against the viral Capsid. Another application of these nanobodies has been thought to utilize them for diagnostic purposes, to use the nanobodies for viral detection from patient samples at the earliest stage using ELISA. This study may open a new avenue for immunologic study in foreseeable future with the usage of the same molecules for multiple purposes. HighlightsNatural nanobodies against viruses were modified for use against Dengue virus Capsid conserved regions.Computational affinity maturation was performed making use of change in binding affinities upon mutating various residues in the complementary determining regions.Docking studies performed to inspect the docking groove, interface analysis and energy calculations.MM/GBSA calculations done to calculate binding free energy of the complex to determine stability of the complex.Communicated by Ramaswamy H. Sarma.

Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis

SARS-CoV-2 has steadily mutated during its spread to > 300 million people throughout the world. The WHO has designated strains with certain mutations, "variants of concern" (VOC), as they may have higher infectivity and/or resist neutralization by antibodies in sera of vaccinated individuals and convalescent patients. Methods to detect regionally emerging VOC are needed to guide treatment and vaccine design. Cluster and network analysis was applied to over 1.2 million sequences of the SARS-CoV-2 spike protein from 36 countries in the GISAID database. While some mutations rapidly spread throughout the world, regionally specific groups of variants were identified. Strains circulating in each country contained different sets of high frequency mutations, many of which were known VOCs. Mutations within clusters increased in frequency simultaneously. Low frequency, but highly correlated mutations detected by the method could signal emerging VOCs, especially if they occur at higher frequency in other regions. An automated version of our method to find high frequency mutations in a set of SARS-COV-2 spike sequences is available online at http://curie.utmb.edu/SAR.html .

AI-based protein structure databases have the potential to accelerate rare diseases research: AlphaFoldDB and the case of IAHSP/Alsin

Artificial intelligence (AI)-based protein structure databases are expected to have an impact on drug discovery. Here, we show how AlphaFold could support rare diseases research programs. We focus on Alsin, a protein responsible for rare motor neuron diseases, such as infantile-onset ascending hereditary spastic paralysis (IAHSP) and juvenile primary lateral sclerosis (JPLS), and involved in some cases of amyotrophic lateral sclerosis (ALS). First, we compared the AlphaFoldDB human Alsin model with homology models of alsin domains. We then evaluated the flexibility profile of Alsin and of experimentally characterized mutants present in patients with IAHSP. Next, we compared preliminary models of dimeric/tetrameric Alsin responsible for its physiological action with hypothetical models reported in the literature. Finally, we suggest the best animal model for drug candidates testing. Overall, we computationally show that drug discovery efforts toward Alsin-involving diseases should be pursued.

A Novel Type of PD-L1 Inhibitor rU1 snRNPA From Human-Derived Protein Scaffolds Library

Three marketed anti-PD-L1 antibodies almost have severe immune-mediated side effects. The therapeutic effects of anti-PD-L1 chemical inhibitors are not satisfied in the clinical trials. Here we constructed human-derived protein scaffolds library and screened scaffolds with a shape complementary to the PD-1 binding domain of PD-L1. The RNA binding domain of U1 snRNPA was selected as one of potential binders because it had the most favorable binding energies with PD-L1 and conformed to pre-established biological criteria for the screening of candidates. The recombinant U1 snRNPA (rU1 snRNPA) in Escherichia coli exhibits anti-cancer activity in melanoma and breast cancer by reactivating tumor-suppressed T cells in vitro and anti-melanoma activity in vivo. Considering hydrophobic and electrostatic interactions, three residues were mutated on the interface of U1 snRNPA and PD-L1 complex, and the ranked variants by PatchDock and A32D showed an increased active phenotype. The screening of human-derived protein scaffolds may become the potential development of therapeutic agents.

Decoding Partner Specificity of Opioid Receptor Family

This paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family (μ (MOR), δ (DOR), κ (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: Gi1, Gi2, Gi3, Go, Gob, Gz, Gq, G11, G14, G15, G12, Gssh, Gslo) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.

Binding characteristics of staphylococcal protein A and streptococcal protein G for fragment crystallizable portion of human immunoglobulin G

In the wide array of physiological processes, protein-protein interactions and their binding are the most basal activities for achieving adequate biological metabolism. Among the studies on binding proteins, the examination of interactions between immunoglobulin G (IgG) and natural immunoglobulin-binding ligands, such as staphylococcal protein A (spA) and streptococcal protein G (spG), is essential in the development of pharmaceutical science, biotechnology, and affinity chromatography. The widespread utilization of IgG-spA/spG binding characteristics has allowed researchers to investigate these molecular interactions. However, the detailed binding strength of each ligand and the corresponding binding mechanisms have yet to be fully investigated. In this study, the authors analyzed the binding strengths of IgG-spA and IgG-spG complexes and identified the mechanisms enabling these bindings using molecular dynamics simulation, steered molecular dynamics, and advanced Poisson-Boltzmann Solver simulations. Based on the presented data, the binding strength of the spA ligand was found to significantly exceed that of the spG ligand. To find out which non-covalent interactions or amino acid sites have a dominant role in the tight binding of these ligands, further detailed analyses of electrostatic interactions, hydrophobic bonding, and binding free energies have been performed. In investigating their binding affinity, a relatively independent and different unbinding mechanism was found in each ligand. These distinctly different mechanisms were observed to be highly correlated to the protein secondary and tertiary structures of spA and spG ligands, as explicated from the perspective of hydrogen bonding.

Computational designing of a peptide that potentially blocks the entry of SARS-CoV, SARS-CoV-2 and MERS-CoV

Last decade has witnessed three major pandemics caused by SARS-CoV, SARS-CoV-2 and MERS-CoV that belong to Coronavirus family. Currently, there are no effective therapies available for corona virus infections. Since the three viruses belong to the same family and share many common features, we can theoretically design a drug that can be effective on all the three of them. In this study, using computational approach, we designed a peptide (Peptide 7) that can bind to the Receptor Binding Domain (RBD) of SARS-CoV, SARS-CoV-2 and MERS-CoV thereby preventing the entry of the viruses into the host cell. The peptide inhibitor was designed as a consensus peptide from three different peptides that might individually bind to the RBD of the three viruses. Docking studies and molecular dynamic simulations using Peptide 7 has shown that it binds with higher affinity than the native receptors of the RBD and forms a stable complex thereby preventing further viral-receptor interaction and inhibiting their cellular entry. This effective binding is observed for the three RBDs, despite the Peptide 7 interactions being slightly different. Hence; this peptide inhibitor can be used as a potential candidate for the development of peptide based anti-viral therapy against Corona viruses.

In-silico structural analysis of Pseudomonas syringae effector HopZ3 reveals ligand binding activity and virulence function

Bacterial acetyltransferase effectors belonging to the Yersinia outer protein J (YopJ) group inhibit multiple immune signaling pathways in human and plants. The present study determines in-silico acetyl-coenzyme A (AcCoA) binding and Arabidopsis immune regulator RPM1-interacting protein4 (RIN4) peptide interactions to YopJ effector hypersensitivity and pathogenesis-dependent outer proteinZ3 (HopZ3) from Pseudomonas syringae. Phylogenetic analysis revealed that HopZ3 was clustered by acetyltransferase effectors from plant bacterial pathogens. Structural juxtaposition shows HopZ3 comprises topology matched closer with HopZ1a than PopP2 effectors, respectively. AcCoA binds HopZ3 at two sites i.e., substrate binding pocket and catalytic site. AcCoA interactions to substrate binding pocket was transient and dissipated upon in-silico mutation of Ser 279 residue whereas, attachment to catalytic site was found to be stable in the presence of inositol hexaphosphate (IP6) as a co-factor. Interface atoms used for measuring hydrogen bond distances, bound or accessible surface area, and root-mean-square fluctuation (RMSF) values, suggests that the HopZ3 complex stabilizes after binding to AcCoA ligand and RIN4 peptide. The few non-conserved polymorphic residues that have been displayed on HopZ3 surface presumably confer intracellular recognitions within hosts. Collectively, homology modeling and interactive docking experiments were used to substantiate Arabidopsis immune 'guardee' interactions to HopZ3.

Role of a cysteine residue in substrate entry and catalysis in MtHIBADH: Analysis by chemical modifications and site-directed mutagenesis

Despite sharing conserved substrate-binding residues, members of 3-hydroxyisobutyrate dehydrogenase (HIBADH) superfamily show remarkable differences in substrate preference. Cysteine residues were identified within a radius of 6 Å surrounding both the active site and the substrate entry site of HIBADH enzyme from Mycobacterium tuberculosis (MtHIBADH). Chemical modification with thiol-modifying reagents, pCMB and DTNB, abrogated the dehydrogenase activity of the enzyme. The loss in activity followed pseudo-first-order kinetics as a function of the concentration of pCMB. S-HIBA (substrate) binding provided partial protection, while NAD (cofactor) binding provided ~70% protection from thiol-modifying reagent. Site-directed mutagenesis of cysteine residues present in the MtHIBADH enzyme identified the indispensable role of Cys-210 residue, located at C-terminal domain, for its dehydrogenase activity. Cys-210 mutation to serine reduced the dehydrogenase activity by ~2-fold while mutation to alanine strikingly reduced the activity by ~140-fold. C210A mutation did not perturb the state of oligomerization of the enzyme but perturbed the secondary structure content. Structural analysis revealed the involvement of Cys-210 residue in inter-chain interaction with Gln-178, which acts as hydrogen bond donor and coordinates with Cys-210 and Gly-208 of the adjacent subunit. The data demonstrate a critical role of Cys-210 residue in maintaining the conformation and rigidity of loop composed of substrate-interacting residues involved in the entry of S-HIBA substrate in MtHIBADH.

Structural studies of RNase M5 reveal two-metal-ion supported two-step dsRNA cleavage for 5S rRNA maturation

All species transcribe ribosomal RNA in an immature form that requires several enzymes for processing into mature rRNA. The number and types of enzymes utilized for these processes vary greatly between different species. In low G + C Gram-positive bacteria including Bacillus subtilis and Geobacillus stearothermophilus, the endoribonuclease (RNase) M5 performs the final step in 5S rRNA maturation, by removing the 3'- and 5'-extensions from precursor (pre) 5S rRNA. This cleavage activity requires initial complex formation between the pre-rRNA and a ribosomal protein, uL18, making the full M5 substrate a ribonucleoprotein particle (RNP). M5 contains a catalytic N-terminal Toprim domain and an RNA-binding C-terminal domain, respectively, shown to assist in processing and binding of the RNP. Here, we present structural data that show how two Mg²⁺ ions are accommodated in the active site pocket of the catalytic Toprim domain and investigate the importance of these ions for catalysis. We further perform solution studies that support the previously proposed 3'-before-5' order of removal of the pre-5S rRNA extensions and map the corresponding M5 structural rearrangements during catalysis.

Effect of Humanizing Mutations on the Stability of the Llama Single-Domain Variable Region

In vivo clinical applications of nanobodies (VHHs) require molecules that induce minimal immunoresponse and therefore possess sequences as similar as possible to the human VH domain. Although the relative sequence variability in llama nanobodies has been used to identify scaffolds with partially humanized signature, the transformation of the Camelidae hallmarks in the framework2 still represents a major problem. We assessed a set of mutants in silico and experimentally to elucidate what is the contribution of single residues to the VHH stability and how their combinations affect the mutant nanobody stability. We described at molecular level how the interaction among residues belonging to different structural elements enabled a model llama nanobody (C8WT, isolated from a naïve library) to be functional and maintain its stability, despite the analysis of its primary sequence would classify it as aggregation-prone. Five chimeras formed by grafting CDRs isolated from different nanobodies into C8WT scaffold were successfully expressed as soluble proteins and both tested clones preserved their antigen binding specificity. We identified a nanobody with human hallmarks that seems suitable for humanizing selected camelid VHHs by grafting heterologous CDRs in its scaffold and could serve for the preparation of a synthetic library of human-like single domains.

Decoding Protein-protein Interactions: An Overview

Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

Targeting SARS-CoV-2 nucleocapsid oligomerization: Insights from molecular docking and molecular dynamics simulations

The outbreak of COVID-19 caused by SARS-CoV-2 virus continually led to infect a large population worldwide. Currently, there is no specific viral protein-targeted therapeutics. The Nucleocapsid (N) protein of the SARS-CoV-2 virus is necessary for viral RNA replication and transcription. The C-terminal domain of N protein (CTD) involves in the self-assembly of N protein into a filament that is packaged into new virions. In this study, the CTD (PDB ID: 6WJI) was targeted for the identification of possible inhibitors of oligomerization of N protein. Herein, multiple computational approaches were employed to explore the potential mechanisms of binding and inhibitor activity of five antiviral drugs toward CTD. The five anti-N drugs studied in this work are 4E1RCat, Silmitasertib, TMCB, Sapanisertib, and Rapamycin. Among the five drugs, 4E1RCat displayed highest binding affinity (-10.95 kcal/mol), followed by rapamycin (-8.91 kcal/mol), silmitasertib (-7.89 kcal/mol), TMCB (-7.05 kcal/mol), and sapanisertib (-6.14 kcal/mol). Subsequently, stability and dynamics of the protein-drug complex were examined with molecular dynamics (MD) simulations. Overall, drug binding increases the stability of the complex with maximum stability observed in the case of 4E1RCat. The CTD-drug complex systems behave differently in terms of the free energy landscape and showed differences in population distribution. Overall, the MD simulation parameters like RMSD, RMSF, Rg, hydrogen bonds analysis, PCA, FEL, and DCCM analysis indicated that 4E1RCat and TMCB complexes were more stable as compared to silmitasertib and sapanisertib and thus could act as effective drug compounds against CTD.Communicated by Ramaswamy H. Sarma.

Structure of fish Toll-like receptors (TLR) and NOD-like receptors (NLR)

Innate immunity driven by pattern recognition receptor (PRR) protects the host from invading pathogens. Aquatic animals like fish where the adaptive immunity is poorly developed majorly rely on their innate immunity modulated by PRRs like toll-like receptors (TLR) and NOD-like receptors (NLR). However, current development to improve the fish immunity via TLR/NLR signaling is affected by a poor understanding of its mechanistic and structural features. This review discusses the structure of fish TLRs/NLRs and its interaction with pathogen associated molecular patterns (PAMPs) and downstream signaling molecules. Over the past one decade, significant progress has been done in studying the structure of TLRs/NLRs in higher eukaryotes; however, structural studies on fish innate immune receptors are undermined. Several novel TLR genes are identified in fish that are absent in higher eukaryotes, but the function is still poorly understood. Unlike the fundamental progress achieved in developing antagonist/agonist to modulate human innate immunity, analogous studies in fish are nearly lacking due to structural inadequacy. This underlies the importance of exploring the structural and mechanistic details of fish TLRs/NLRs at an atomic and molecular level. This review outlined the mechanistic and structural basis of fish TLR and NLR activation.

A double role of the Gal80 N terminus in activation of transcription by Gal4p

Activation of gene expression by Gal4p in K. lactis requires an element in the N terminus of KlGal80p that mediates nuclear co-import of KlGal1p and galactokinase inhibition to support the co-inducer function of KlGal1p.

The yeast galactose switch operated by the Gal4p–Gal80p–Gal3p regulatory module is a textbook model of transcription regulation in eukaryotes. The Gal80 protein inhibits Gal4p-mediated transcription activation by binding to the transcription activation domain. In Saccharomyces cerevisiae, inhibition is relieved by formation of an alternative Gal80–Gal3 complex. In yeasts lacking a Gal3p ortholog, such as Kluyveromyces lactis, the Gal1 protein (KlGal1p) combines regulatory and enzymatic activity. The data presented here reveal a yet unknown role of the KlGal80 N terminus in the mechanism of Gal4p activation. The N terminus contains an NLS, which is responsible for nuclear accumulation of KlGal80p and KlGal1p and for KlGal80p-mediated galactokinase inhibition. Herein, we present a model where the N terminus of KlGal80p reaches the catalytic center of KlGal1p causing enzyme inhibition in the nucleus and stabilization of the KlGal1–KlGal80p complex. We corroborate this model by genetic analyses and structural modelling and provide a rationale for the divergent evolution of the mechanism activating Gal4p.

Efficient detection of eukaryotic calcium-sensing receptor (CaSR) by polyclonal antibody against prokaryotic expressed truncated CaSR

Calcium-sensing receptor (CaSR), which is better known for its action as regulating calcium homeostasis, can bind various ligands. To facilitate research on CaSR and understand the receptor's function further, an in silico designed truncated protein was developed. The resulting protein folding indicated that 99% of predicted three dimensional (3D) structure residues are located in favored and allowed Ramachandran plots. However, it was found that such protein does not fold properly when expressed in prokaryotic host cells. Thioredoxin (Trx) tag was conjugated to increase the final protein's solubility, which could help obtain the soluble antigen with better immunogenic properties. The truncated recombinant proteins were expressed and purified in two forms (Trx-CaSR: RR19 and CaSR: RRJ19). The polyclonal antibody was induced by the rabbit immunization with the form of RR19. Western blot on mouse kidney lysates evidenced the proper immune recognition of the receptor by the produced antibody. The specificity and sensitivity of antibodies were also assayed by immunohistofluorescence. These experiments affirmed antibody's ability to indicate the receptor on the cell surface in native form and the possibility of applying such antibodies in further cellular and tissue assays.

Interference of dengue replication by blocking the access of 3' SL RNA to the viral RNA-dependent RNA polymerase

The four circulating serotypes of dengue virus (DENV) occasionally cause potentially fetal symptoms of severe dengue, which there is currently no specific treatment available. Extensive efforts have been made to inhibit viral replication processes by impeding the activity of an exclusive RNA-dependent RNA polymerase (RdRp) in the viral non-structural protein 5 (NS5). In our earlier work, we identified the characteristic, specific interaction between the C-terminal thumb subdomain of RdRp and an apical loop in the 3' stem-loop (SL) element in the DENV RNA genome, which is fundamental for viral replication. Here, we demonstrated a new approach for interfering viral replication via blocking of 3' SL RNA binding to RdRp by the single-chain variable fragments (scFvs). We isolated and cloned 3 different human scFvs that bound to RdRp from DENV serotype 2 and interfered with 3' SL-binding, utilizing a combination of phage-display panning and Alpha methods. When tagged with a cell penetrating peptide, a selected scFv clone, 2E3, entered cells and partially colocalized with NS5 in the cytoplasm of infected HuH-7 cells. 2E3 significantly inhibited DENV RNA replication with sub-nanomolar EC50 values and significantly reduced the production of infectious particles. The molecular docking models suggested that 2E3 recognized both palm and thumb subdomains of RdRp, and interacted with Lys⁸⁴¹, a key residue involved in RNA binding. Our results provide a new potential therapeutic molecule specific for flaviviral infection.

Computational investigation for modeling the protein-protein interaction of TasA(28-261)-TapA(33-253): a decisive process in biofilm formation by Bacillus subtilis

Biofilms have a significant role in microbial persistence, antibiotic resistance, and chronic infections; consequently, there is a pressing need for development of novel "anti-biofilm strategies." One of the fundamental mechanisms involved in biofilm formation is protein-protein interactions of "amyloid-like proteins" (ALPs) in the extracellular matrix. Such interactions could be potential targets for development of novel anti-biofilm strategies; therefore, assessing the structural features of these interactions could be of great scientific value. Characterization of structural features the of protein-protein interaction with conventional structure biology tools including X-ray diffraction and nuclear magnetic resonance is technically challenging, expensive, and time-consuming. In contrast, modeling such interactions is time-efficient and economical, and might provide deeper understanding of structural basis of interactions. Although it is often acknowledged that molecular modeling methods have varying accuracy, their careful implementation with supplementary verification methods can provide valuable insight and directions for future studies. With this reasoning, during the present study, the protein-protein interaction of TasA_(28-261)-TapA_(33-253) (which is a decisive process for biofilm formation by Bacillus subtilis) was modeled using in silico approaches, viz., molecular modeling, protein-protein docking, and molecular dynamics simulations. Results obtained here identified amino acid residues present within intrinsically disordered regions of both proteins to be critical for interaction. These results were further supported with principal component analyses (PCA) and free energy landscape (FEL) analyses. Results presented here represent novel finding, and we hypothesize that amino acid residues identified during the present study could be targeted for inhibition of biofilm formation by B. subtilis.

Understanding the Binding Specificity of G-Protein Coupled Receptors toward G-Proteins and Arrestins: Application to the Dopamine Receptor Family

G-Protein coupled receptors (GPCRs) are involved in a myriad of pathways key for human physiology through the formation of complexes with intracellular partners such as G-proteins and arrestins (Arrs). However, the structural and dynamical determinants of these complexes are still largely unknown. Herein, we developed a computational big-data pipeline that enables the structural characterization of GPCR complexes with no available structure. This pipeline was used to study a well-known group of catecholamine receptors, the human dopamine receptor (DXR) family and its complexes, producing novel insights into the physiological properties of these important drug targets. A detailed description of the protein interfaces of all members of the DXR family (D1R, D2R, D3R, D4R, and D5R) and the corresponding protein interfaces of their binding partners (Arrs: Arr2 and Arr3; G-proteins: Gi1, Gi2, Gi3, Go, Gob, Gq, Gslo, Gssh, Gt2, and Gz) was generated. To produce reliable structures of the DXR family in complex with either G-proteins or Arrs, we performed homology modeling using as templates the structures of the β2-adrenergic receptor (β2AR) bound to Gs, the rhodopsin bound to Gi, and the recently acquired neurotensin receptor-1 (NTSR1) and muscarinic 2 receptor (M2R) bound to arrestin (Arr). Among others, the work demonstrated that the three partner groups, Arrs and Gs- and Gi-proteins, are all structurally and dynamically distinct. Additionally, it was revealed the involvement of different structural motifs in G-protein selective coupling between D1- and D2-like receptors. Having constructed and analyzed 50 models involving DXR, this work represents an unprecedented large-scale analysis of GPCR-intracellular partner interface determinants. All data is available at www.moreiralab.com/resources/dxr.

HIV-1 Nef promotes ubiquitination and proteasomal degradation of p53 tumor suppressor protein by using E6AP

Human Immunodeficiency Virus-1 (HIV-1) Nef promotes p53 protein degradation to protect HIV-1 infected cells from p53 induced apoptosis. We found that Nef mediated p53 degradation is accomplished through ubiquitin proteasome pathway in an Mdm2-independent manner. By GST pulldown and immunoprecipitation assays, we have shown that Nef interacts with E3 ubiquitin ligase E6AP in both Nef transfected HEK-293T cells and HIV-1 infected MOLT3 cells. The p53 ubiquitination and degradation was found to be enhanced by Nef with E6AP but not by Nef with E6AP-C843A, a dominant negative E6AP mutant. We show that Nef binds with E6AP and promotes E6AP dependent p53 ubiquitination. Further, Nef inhibits apoptosis of p53 null H1299 cells after exogenous expression of p53 protein. The p53 dependent apoptosis of H1299 cells was further reduced after the expression of Nef with E6AP. However, Nef mediated reduction in p53 induced apoptosis of H1299 cells was restored when Nef was co-expressed with E6AP-C843A. Thus, Nef and E6AP co-operate to promote p53 ubiquitination and degradation in order to suppress p53 dependent apoptosis. CHME3 cells, which are a natural host of HIV-1, also show p53 ubiquitination and degradation by Nef and E6AP. These results establish that Nef induces p53 degradation via cellular E3 ligase E6AP to inhibit apoptosis during HIV-1 infection.

In vitro affinity maturation to improve the efficacy of a hypoxia-inducible factor 1α single-domain intrabody

Affinity is an important property of therapeutic antibodies, so improving affinity is critical to the biological activity and clinical efficacy. An anti-HIF-1α nanobody, VHH212, was screened via a native ribosome display library with a 26.6 nM of K_D value was used as the parent. In this paper, a Venn-intersection of multi-algorithms screening (VIMAS) strategy for computer-aided binding affinity prediction was designed. Homology modeling and protein docking methods were used to substitute the need for a crystal structure. Finally, a mutant with a 17.5-fold enhancement in binding affinity (1.52 nM) was obtained by using the VIMAS strategy. Furthermore, the biological activity of mutants was verified at the cellular level. Targeting HIF-1α can sensitize PDAC (pancreatic ductal adenocarcinoma) tumors to gemcitabine, which is a potential co-treatment method for pancreatic cancer patients. Our results showed that the cytotoxicity of gemcitabine on pancreatic cancer cell lines increased with the enhanced-affinity of an intrabody under combined treatment.

CoRNeA: A Pipeline to Decrypt the Inter-Protein Interfaces from Amino Acid Sequence Information

Decrypting the interface residues of the protein complexes provides insight into the functions of the proteins and, hence, the overall cellular machinery. Computational methods have been devised in the past to predict the interface residues using amino acid sequence information, but all these methods have been majorly applied to predict for prokaryotic protein complexes. Since the composition and rate of evolution of the primary sequence is different between prokaryotes and eukaryotes, it is important to develop a method specifically for eukaryotic complexes. Here, we report a new hybrid pipeline for predicting the protein-protein interaction interfaces in a pairwise manner from the amino acid sequence information of the interacting proteins. It is based on the framework of Co-evolution, machine learning (Random Forest), and Network Analysis named CoRNeA trained specifically on eukaryotic protein complexes. We use Co-evolution, physicochemical properties, and contact potential as major group of features to train the Random Forest classifier. We also incorporate the intra-contact information of the individual proteins to eliminate false positives from the predictions keeping in mind that the amino acid sequence of a protein also holds information for its own folding and not only the interface propensities. Our prediction on example datasets shows that CoRNeA not only enhances the prediction of true interface residues but also reduces false positive rates significantly.

The Toxicological Intersection between Allergen and Toxin: A Structural Comparison of the Cat Dander Allergenic Protein Fel d1 and the Slow Loris Brachial Gland Secretion Protein

Slow lorises are enigmatic animal that represent the only venomous primate lineage. Their defensive secretions have received little attention. In this study we determined the full length sequence of the protein secreted by their unique brachial glands. The full length sequences displayed homology to the main allergenic protein present in cat dander. We thus compared the molecular features of the slow loris brachial gland protein and the cat dander allergen protein, showing remarkable similarities between them. Thus we postulate that allergenic proteins play a role in the slow loris defensive arsenal. These results shed light on these neglected, novel animals.

Prediction and targeting of GPCR oligomer interfaces

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.