QMEAN: A comprehensive scoring function for model quality assessment

Recent advances and challenges in protein complex model accuracy estimation

Estimation of model accuracy plays a crucial role in protein structure prediction, aiming to evaluate the quality of predicted protein structure models accurately and objectively. This process is not only key to screening candidate models that are close to the real structure, but also provides guidance for further optimization of protein structures. With the significant advancements made by AlphaFold2 in monomer structure, the problem of single-domain protein structure prediction has been widely solved. Correspondingly, the importance of assessing the quality of single-domain protein models decreased, and the research focus has shifted to estimation of model accuracy of protein complexes. In this review, our goal is to provide a comprehensive overview of the reference and statistical metrics, as well as representative methods, and the current challenges within four distinct facets (Topology Global Score, Interface Total Score, Interface Residue-Wise Score, and Tertiary Residue-Wise Score) in the field of complex EMA.

Structural and functional effects of the L84S mutant in the SARS-COV-2 ORF8 dimer based on microsecond molecular dynamics study

The L84S mutation has been observed frequently in the ORF8 protein of SARS-CoV-2, which is an accessory protein involved in various important functions such as virus propagation, pathogenesis, and evading the immune response. However, the specific effects of this mutation on the dimeric structure of ORF8 and its impacts on interactions with host components and immune responses are not well understood. In this study, we performed one microsecond molecular dynamics (MD) simulation and analyzed the dimeric behavior of the L84S and L84A mutants in comparison to the native protein. The MD simulations revealed that both mutations caused changes in the conformation of the ORF8 dimer, influenced protein folding mechanisms, and affected the overall structural stability. In particular, the 73YIDI76 motif has found to be significantly affected by the L84S mutation, leading to structural flexibility in the region connecting the C-terminal β4 and β5 strands. This flexibility might be responsible for virus immune modulation.  The free energy landscape (FEL) and principle component analysis (PCA) have also supported our investigation. Overall, the L84S and L84A mutations affect the ORF8 dimeric interfaces by reducing the frequency of protein-protein interacting residues (Arg52, Lys53, Arg98, Ile104, Arg115, Val117, Asp119, Phe120, and Ile121) in the ORF8 dimer.  Our findings provide detail insights for further research in designing structure-based therapeutics against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Structure-based modeling to assess binding and endocrine disrupting potential of polycyclic aromatic hydrocarbons in Danio rerio

Environmental contaminants, such as polycyclic aromatic hydrocarbons (PAHs), have raised concerns regarding their potential endocrine-disrupting effects on aquatic organisms, including fish. In this study, molecular docking and molecular dynamics techniques were employed to evaluate the endocrine-disrupting potential of PAHs in zebrafish, as a model organism. A virtual screening with 72 PAHs revealed a correlation between the number of PAH aromatic rings and their binding affinity to proteins involved in endocrine regulation. Furthermore, PAHs with the highest binding affinities for each protein were identified: cyclopenta[cd]pyrene for AR (-9.7 kcal/mol), benzo(g)chrysene for ERα (-11.5 kcal/mol), dibenzo(a,e)pyrene for SHBG (-8.7 kcal/mol), dibenz(a,h)anthracene for StAR (-11.2 kcal/mol), and 2,3-benzofluorene for TRα (-9.8 kcal/mol). Molecular dynamics simulations confirmed the stability of the protein-ligand complexes formed by the PAHs with the highest binding affinities throughout the simulations. Additionally, the effectiveness of the protocol used in this study was demonstrated by the receiver operating characteristic curve (ROC) analysis, which effectively distinguished decoys from true ligands. Therefore, this research provides valuable insights into the endocrine-disrupting potential of PAHs in fish, highlighting the importance of assessing their impact on aquatic ecosystems.

Interaction Between Vpx and SAMHD1, Vital for SAMHD1 Inhibition

It was confirmed that the sterile alpha motif and HD domain 1 (SAMHD1) limits human immunodeficiency virus type 1 (HIV-1) replication. In contrast, viral protein x (Vpx) in HIV-2 and some simian immunodeficiency viruses can counteract this effect. The possible interaction between SAMHD1 and Vpx was suggested by previous studies; however, there are no data to confirm this interaction. Therefore, this study aimed to study the interaction between two proteins and the properties of Vpx protein for the first time using bioinformatic tools. Vpx and SAMHD1 sequences were obtained from the National Center for Biotechnology Information GenBank. Several software were used to define Vpx properties and the interaction between Vpx and different SAMHD1 isoforms. Our findings indicated the difference in interaction sites among different Vpx. However, in all Vpx proteins, this region is from amino acids 4 to 90. In addition, two regions (26-31 and 134-139) and two amino acids 425 and 429 in SAMHD1 are vital in the possible interaction. In addition, our analysis determined the physicochemical and immunological properties of the Vpx. Considering all factors, this study could confirm that Vpx interacts with SAMHD1, which could inhibit SAMHD1. Moreover, our findings can pave the way for future studies to express and purify Vpx in the laboratory and study this protein in vitro.

Structural and functional analysis of Cyanovirin-N homologs: Carbohydrate binding affinities and antiviral potential of cyanobacterial peptides

Cyanobacteria, a group of photosynthetic prokaryotes, can sinthesize several substances due to their secondary metabolism, with notable properties, such as Cyanovirin-N(CVN), a carbohydrate-binding lectin, that exhibits antiviral activity against several pathogens, due to its ability to bind viral surface carbohydrates such as mannose, thus interfering with the viral entry on the cell. CVN has been described in several cyanobacterial strains and shows biotechnological potential for the development of drugs of pharmaceutical interest. This study focuses on the genomic exploration and characterization of Cyanovirin-N homologs to assess the conservation of carbohydrate-binding affinity within the group. The analysis of their antiviral properties was carried out using bioinformatics tools to study protein models through an in silico pipeline, following the steps of genomic prospection on public databases, homology modeling, docking, molecular dynamics and energetic analysis. Mannose served as the reference ligand, and the lectins' binding affinity with mannose was assessed across Cyanovirin-N homologs. Genomic mining identified 33 cyanobacterial lectin sequences, which underwent structural and functional characterization. The results obtained from this work indicate strong carbohydrate affinity on several homologs, pointing to the conservation of antiviral properties alongside the group. However, this affinity was not uniformly distributed among sequences, exhibiting significant heterogeneity in binding site residues, suggesting potential multi-ligand binding capabilities on the Cyanovirin-N homologs group. Studies focused on the properties involved in these molecules and the investigation of the genetic diversity of Cyanovirin-N homologs could provide valuable insights into the discovery of new drug candidates, harvesting the potential of bioinformatics for large-scale functional and structural analysis.

The evolutionary novelty of insect defensins: from bacterial killing to toxin neutralization

Insect host defense comprises two complementary dimensions, microbial killing-mediated resistance and microbial toxin neutralization-mediated resilience, both jointly providing protection against pathogen infections. Insect defensins are a class of effectors of innate immunity primarily responsible for resistance to Gram-positive bacteria. Here, we report a newly originated gene from an ancestral defensin via genetic deletion following gene duplication in Drosophila virilis, which confers an enhanced resilience to Gram-positive bacterial infection. This gene encodes an 18-mer arginine-rich peptide (termed DvirARP) with differences from its parent gene in its pattern of expression, structure and function. DvirARP specifically expresses in D. virilis female adults with a constitutive manner. It adopts a novel fold with a 310 helix and a two CXC motif-containing loop stabilized by two disulfide bridges. DvirARP exhibits no activity on the majority of microorganisms tested and only a weak activity against two Gram-positive bacteria. DvirARP knockout flies are viable and have no obvious defect in reproductivity but they are more susceptible to the DvirARP-resistant Staphylococcus aureus infection than the wild type files, which can be attributable to its ability in neutralization of the S. aureus secreted toxins. Phylogenetic distribution analysis reveals that DvirARP is restrictedly present in the Drosophila subgenus, but independent deletion variations also occur in defensins from the Sophophora subgenus, in support of the evolvability of this class of immune effectors. Our work illustrates for the first time how a duplicate resistance-mediated gene evolves an ability to increase the resilience of a subset of Drosophila species against bacterial infection.

The Dark Side of the pollen: BSA-seq identified genomic regions linked to male sterility in globe artichoke

Globe artichoke (Cynara cardunculus var. scolymus; 2n = 2x = 34) is a food crop consumed for its immature flower heads. Traditionally, globe artichoke varietal types are vegetatively propagated. However, seed propagation makes it possible to treat the crop as annual, increasing field uniformity and reducing farmers costs, as well as pathogens diffusion. Despite globe artichoke's significant agricultural value and the critical role of heterosis in the development of superior varieties, the production of hybrids remains challenging without a reliable system for large-scale industrial seed production. Male sterility (MS) presents a promising avenue for overcoming these challenges by simplifying the hybridization process and enabling cost-effective seed production. However, within the Cynara genus, genic male sterility has been linked to three recessive loci in globe artichoke, with no definitive genetic mechanism elucidated to date. A 250 offsprings F2 population, derived from a cross between a MS globe artichoke and a male fertile (MF) cultivated cardoon (C. cardunculus var. altilis) and fitting a monogenic segregation model (3:1), was analyzed through BSA-seq, aiming at the identification of genomic regions/genes affecting male sterility. Four QTL regions were identified on chromosomes 4, 12, and 14. By analyzing the sequence around the highest pick on chromosome 14, a cytochrome P450 (CYP703A2) was identified, carrying a deleterious substitution (R/Q) fixed in the male sterile parent. A single dCAPS marker was developed around this SNP, allowing the discrimination between MS and MF genotypes within the population, suitable for applications in plant breeding programs. A 3D model of the protein was generated by homology modeling, revealing that the mutated amino acid is part of a highly conserved motif crucial for protein folding.

Functional characterization of two DH44R genes associated with starvation and desiccation in Rhopalosiphum padi (Hemiptera: Aphididae)

CRF-like diuretic hormone receptor (CRF/DHR), also known as DH44R in insects, are G-protein coupled receptors (GPCRs) that play a role in regulating osmotic balance in various insect species. These receptors have the potential to be targeted for the development of insecticides. However, our understanding of the role of DHR genes in aphids, including Rhopalosiphum padi, a major wheat pest, is currently limited. In this study, we isolated and characterized two R. padi DHRs (RpDHR1 and RpDHR2). The expression levels of RpDHR1 increased after starvation and were restored after re-feeding. The expression levels of RpDHR1 gene decreased significantly 24 h after injection of dsRNA targeting the gene. Knockdown of RpDHR1 increased aphid mortality under starvation conditions (24, 36, 48 and 60 h). Under starvation and desiccation condition, the aphid mortality decreased after knockdown of RpDHR1. This is the first study to report the role of DHR genes in the starvation and desiccation response of aphids. The results suggest that RpDHR1 is involved in the resistance of R. padi to starvation and dehydration, making it a potential target for insecticide development. Novel insecticides could be created by utilizing DHR agonists to disrupt the physiological processes of insect pests.

Frequency of Fusion Inhibitor Resistance Mutations Among Therapy-Naïve HIV Patients

Glycoprotein 41 (gp41) of the human immunodeficiency virus type 1 (HIV-1) protein plays a critical role in membrane fusion. Gp41 binds to proteins in the plasma membrane of CD4+ T cells, particularly the T-cell antigen receptor (TCR). These findings indicate that gp41 is involved in the assembly of HIV-1 at the plasma membrane of T cells and affects the stimulation of the TCR. To control HIV-1, new inhibitors were introduced to target the gp41 protein. However, mutations in this region might reduce their efficacy. The Gp41 region was amplified from the sera of 30 patients using nested polymerase chain reaction. The sequences were analyzed by bioinformatics tools to identify mutations and gp41 structural features. Subtyping and the interaction between fusion inhibitors and gp41 proteins were also examined. As the first report from Iran, docking analysis between fusion inhibitors and Iranian gp41 proteins showed that mutations in gp41 could not reduce the efficacy of the fusion inhibitors. Most of the patients were infected with CRF35-AD. Several post-modification positions, including glycosylation and phosphorylation sites, were identified in the gp41 protein. Our findings revealed no known multinational drug resistance to gp41 inhibitors; thus, fusion inhibitors can effectively inhibit HIV in Iranian patients. In addition, the present study introduced a new gp41 region (36-44 aa), which considerably influences the interactions between gp41 inhibitors and the gp41 protein. This region may play a pivotal role in suppressing gp41 inhibitors in CFR35-AD. Furthermore, gp41 can be considered a good target for subtyping analysis via the phylogenetic method.

Oleic Acid Could Act as a Channel Blocker in the Inhibition of nAChR: Insights from Molecular Dynamics Simulations

The activation of the muscular nicotinic acetylcholine receptor (nAChR) produces the opening of the channel, with the consequent increase in the permeability of cations, triggering an excitatory signal. Free fatty acids (FFA) are known to modulate the activity of the receptor as noncompetitive antagonists, acting at the membrane-AChR interface. We present molecular dynamics simulations of a model of nAChR in a desensitized closed state embedded in a lipid bilayer in which distinct membrane phospholipids were replaced by two different monounsaturated FFA that differ in the position of a double bond. This allowed us to detect and describe that the cis-18:1ω-9 FFA were located at the interface between the transmembrane segments of α2 and γ subunits diffused into the channel lumen with the consequent potential ability to block the channel to the passage of ions.

Experimental and Molecular Docking Studies on Enzyme-Driven Biohybrid-Inspired Micromotors Based on Amylose-b-(PEG-co-PBA) Inclusion Complexes

Amylose is a linear polysaccharide with a unique ability to form helical inclusion complexes with the appropriate guest components. Numerous studies have been conducted on encapsulation of bioactive compounds for various applications. In the biomedical field, biohybrid micro/nanomotors (MNMs) have emerged as innovative candidates due to their excellent biocompatible and biodegradable properties. This study was inspired by the biohybrid- and enzymatic-propelled MNMs and explored the potential of amylose inclusion complexes (ICs) in creating these MNMs. The study developed a new type of micromotor made from (PEG-co-PBA)-b-amylose. Nanoprecipitation, dimethyl sulfoxide (DMSO), and ultrasound-treated methods were employed to create spherical, thick crystalline, and rod-bacterial-like morphologies, respectively. Candida antarctica lipase B (CALB) was used as the catalytic fuel to induce the motion by the enzymatic degradation of ester linkages in the polymeric segment. Optical microscopy was utilized to observe the motion of the motors following incubation with enzyme concentrations of 5, 10, and 20% (w/w). The results demonstrated that the velocity of the motors increased proportionally with the percentage of added enzyme. Additionally, a comprehensive molecular docking evaluation with PyRx software provided insight into the interaction of the CALB enzyme with polymeric moieties and demonstrated a good affinity between the enzyme and polymer in the binding site. This study provides novel insight into the design and development of enzymatically driven polymeric micromotors and nanomotors.

Unveiling the structure and interactions of SOG1, a NAC domain transcription factor: An in-silico perspective

SOG1 is a crucial plant-specific NAC domain family transcription factor and functions as the central regulator of DNA damage response, acting downstream of ATM and ATR kinases. In this study, various in-silico approaches have been employed for the characterization of SOG1 transcription factor in a comparative manner with its orthologues from various plant species. Amino acid sequences of more than a hundred SOG1 or SOG1-like proteins were retrieved and their relationship was determined through phylogenetic and motif analyses. Various physiochemical properties and secondary structural components of SOG1 orthologues were determined in selective plant species including Arabidopsis thaliana, Oryza sativa, Amborella trichopoda, and Physcomitrella patens. Furthermore, fold recognition or threading and homology-based three-dimensional models of SOG1 were constructed followed by subsequent evaluation of quality and accuracy of the generated protein models. Finally, extensive DNA-Protein and Protein-Protein interaction studies were performed using the HADDOCK server to give an insight into the mechanism of how SOG1 binds with the promoter region of its target genes or interacts with other proteins to regulate the DNA damage responses in plants. Our docking analysis data have shown the molecular mechanism of SOG1's binding with 5'-CTT(N)7AAG-3' and 5'-(N)4GTCAA(N)4-3' consensus sequences present in the promoter region of its target genes. Moreover, SOG1 physically interacts and forms a thermodynamically stable complex with NAC103 and BRCA1 proteins, which possibly serve as coactivators or mediators in the transcription regulatory network of SOG1. Overall, our in-silico study will provide meaningful information regarding the structural and functional characterization of the SOG1 transcription factor.

Identification of the odorant binding proteins of Western Flower Thrips (Frankliniella occidentalis), characterization and binding analysis of FoccOBP3 with molecular modelling, molecular dynamics simulations and a confirmatory field trial

Olfactory systems are indispensable for insects as they, including Western Flower Thrips (Frankliniella occidentalis), use olfactory cues for ovipositing and feeding. F. occidentalis use odorant binding proteins (OBPs) to transport semiochemicals to odorant receptors to induce a behavioural response from the sensillum lymph of the insect's antennae. This study identifies four OBPs of F. occidentalis and analyses their expression at three stages of growth: larvae, adult males and adult females. Further, it investigates the presence of conserved motifs and their phylogenetic relationship to other insect species. Moreover, FoccOBP3 was in silico characterized to analyse its structure along with molecular docking and molecular dynamics simulations to understand its binding with semiochemicals of F. occidentalis. Molecular docking revealed the interactions of methyl isonicotinate, p-anisaldehyde and (S)-(-)-verbenone with FoccOBP3. Moreover, molecular dynamics simulations showed bonding stability of these ligands with FoccOBP3, and field trials validated that Lurem TR (commercial product) and p-anisaldehyde had greater attraction as compared to (S)-(-)-verbenone, given the compound's binding with FoccOBP3. The current study helps in understanding the tertiary structure and interaction of FoccOBP3 with lures using computational and field data and will help in the identification of novel lures of insects in the future, given the importance of binding with OBPs.Communicated by Ramaswamy H. Sarma.

Core-genome-mediated promising alternative drug and multi-epitope vaccine targets prioritization against infectious Clostridium difficile

Prevention of Clostridium difficile infection is challenging worldwide owing to its high morbidity and mortality rates. C. difficile is currently being classified as an urgent threat by the CDC. Devising a new therapeutic strategy become indispensable against C. difficile infection due to its high rates of reinfection and increasing antimicrobial resistance. The current study is based on core proteome data of C. difficile to identify promising vaccine and drug candidates. Immunoinformatics and vaccinomics approaches were employed to construct multi-epitope-based chimeric vaccine constructs from top-ranked T- and B-cell epitopes. The efficacy of the designed vaccine was assessed by immunological analysis, immune receptor binding potential and immune simulation analyses. Additionally, subtractive proteomics and druggability analyses prioritized several promising and alternative drug targets against C. difficile. These include FMN-dependent nitroreductase which was prioritized for pharmacophore-based virtual screening of druggable molecule databases to predict potent inhibitors. A MolPort-001-785-965 druggable molecule was found to exhibit significant binding affinity with the conserved residues of FMN-dependent nitroreductase. The experimental validation of the therapeutic targets prioritized in the current study may worthy to identify new strategies to combat the drug-resistant C. difficile infection.

Ketoprofen attenuates Las/Rhl quorum-sensing (QS) systems of Pseudomonas aeruginosa: molecular and docking studies

BACKGROUND

Quorum sensing (QS) is the leading cause of persistent infections and recalcitrance to antibiotic treatment of Pseudomonas aeruginosa. Hence, QS inhibitors are promising agents for the potential treatment of P. aeruginosa infections.

METHODS AND RESULTS

Herein, the reducing effect of ketoprofen on virulence factors production including protease, hemolysin, pyocyanin, hydrogen cyanide, biofilm, and motility of P. aeruginosa strains was investigated. Furthermore, the quorum quenching activity of ketoprofen at the molecular level was examined by real-time PCR assessment. Our results showed that ketoprofen significantly attenuates virulence factors and biofilm formation in P. aeruginosa strains. Moreover, ketoprofen down-regulated the expression of lasI, lasR, rhlI, and rhlR genes, by 35-47, 22-48, 34-67, and 43-56%, respectively. As well, molecular docking simulation showed a high binding affinity of ketoprofen with QS regulatory proteins.

CONCLUSIONS

Consequently, this study confirmed the quorum quenching activity of ketoprofen, which could be employed as a useful agent for the treatment of P. aeruginosa infections.

Innate extracellular Hsp70 inflammatory properties are mediated by the interaction of Siglec-E and LOX-1 receptors

Innate immune responses to cell damage-associated molecular patterns induce a controlled degree of inflammation, ideally avoiding the promotion of intense unwanted inflammatory adverse events. When released by damaged cells, Hsp70 can stimulate different responses that range from immune activation to immune suppression. The effects of Hsp70 are mediated through innate receptors expressed primarily by myeloid cells, such as dendritic cells (DCs). The regulatory innate receptors that bind to extracellular mouse Hsp70 (mHsp70) are not fully characterized, and neither are their potential interactions with activating innate receptors. Here, we describe that extracellular mHsp70 interacts with a receptor complex formed by inhibitory Siglec-E and activating LOX-1 on DCs. We also find that this interaction takes place within lipid microdomains, and Siglec-E acts as a negative regulator of LOX-1-mediated innate activation upon mHsp70 or oxidized LDL binding. Thus, HSP70 can both bind to and modulate the interaction of inhibitory and activating innate receptors on the cell surface. These findings add another dimension of regulatory mechanism to how self-molecules contribute to dampening of exacerbated inflammatory responses.

Estimating protein complex model accuracy based on ultrafast shape recognition and deep learning in CASP15

This article reports and analyzes the results of protein complex model accuracy estimation by our methods (DeepUMQA3 and GraphGPSM) in the 15th Critical Assessment of techniques for protein Structure Prediction (CASP15). The new deep learning-based multimeric complex model accuracy estimation methods are proposed based on the ensemble of three-level features coupling with deep residual/graph neural networks. For the input multimeric complex model, we describe it from three levels: overall complex features, intra-monomer features, and inter-monomer features. We designed an overall ultrafast shape recognition (USR) to characterize the relationship between local residues and the overall complex topology, and an inter-monomer USR to characterize the relationship between the residues of one monomer and the topology of other monomers. DeepUMQA3 (Group name: GuijunLab-RocketX) ranked first in the interface residue accuracy estimation of CASP15. The Pearson correlation between the interface residue Local Distance Difference Test (lDDT) predicted by DeepUMQA3 and the real lDDT is 0.570, the only method that exceeds 0.5. Among the top 5 methods, DeepUMQA3 achieved the highest Pearson correlation of lDDT on 25 out of 39 targets. GraphGPSM (Group name: GuijunLab-PAthreader) has TM-score Pearson correlations greater than 0.9 on 14 targets, showing a good ability to estimate the overall fold accuracy. The DeepUMQA3 server is available at http://zhanglab-bioinf.com/DeepUMQA/ and the GraphGPSM server is available at http://zhanglab-bioinf.com/GraphGPSM/.

Tubulin as a potential molecular target for resveratrol in Giardia lamblia trophozoites, in vitro and in silico approaches

Giardia lamblia is a globally distributed protozoan parasite that causes intestinal disease. Recently, there is an increase in refractory cases of giardiasis to chemotherapeutic agents, and drugs available cause side effects that may limit its use or cause therapeutic non-compliance. Therefore, search for alternative and less harmful drugs to treat giardiasis is an important task. In this sense, resveratrol (RSV) is a polyphenol with a wide range of pharmacological effects such as antimicrobial, anticarcinogenic and antioxidant. The aim of this study was to evaluate the effects of RSV on Giardia lamblia trophozoites in vitro and in silico, focusing on tubulin affectation, a major protein of the Giardia cytoskeleton which participates in relevant processes for cell survival. In vitro determinations showed that RSV inhibits parasite growth and adherence, causes morphological changes, and induces apoptosis-like cell death through tubulin alterations demonstrated by immunolocalization and Western blot assays. Bioinformatic analysis by molecular docking suggested that RSV binds to Giardia tubulin interface heterodimer, sharing binding residues to those reported with depolymerization inhibitors. These findings suggest that RSV affects microtubular dynamics and make it an interesting compound to study for its safety and antigiardiasic potential.

A computational simulation appraisal of banana lectin as a potential anti-SARS-CoV-2 candidate by targeting the receptor-binding domain

BACKGROUND

The ongoing concern surrounding coronavirus disease 2019 (COVID-19) primarily stems from continuous mutations in the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to the emergence of numerous variants. The receptor-binding domain (RBD) in the S1 subunit of the S protein of the virus plays a crucial role in recognizing the host's angiotensin-converting enzyme 2 (hACE2) receptor and facilitating cell membrane fusion processes, making it a potential target for preventing viral entrance into cells. This research aimed to determine the potential of banana lectin (BanLec) proteins to inhibit SARS-CoV-2 attachment to host cells by interacting with RBD through computational modeling.

MATERIALS AND METHODS

The BanLecs were selected through a sequence analysis process. Subsequently, the genes encoding BanLec proteins were retrieved from the Banana Genome Hub database. The FGENESH online tool was then employed to predict protein sequences, while web-based tools were utilized to assess the physicochemical properties, allergenicity, and toxicity of BanLecs. The RBDs of SARS-CoV-2 were modeled using the SWISS-MODEL in the following step. Molecular docking procedures were conducted with the aid of ClusPro 2.0 and HDOCK web servers. The three-dimensional structures of the docked complexes were visualized using PyMOL. Finally, molecular dynamics simulations were performed to investigate and validate the interactions of the complexes exhibiting the highest interactions, facilitating the simulation of their dynamic properties.

RESULTS

The BanLec proteins were successfully modeled based on the RNA sequences from two species of banana (Musa sp.). Moreover, an amino acid modification in the BanLec protein was made to reduce its mitogenicity. Theoretical allergenicity and toxicity predictions were conducted on the BanLecs, which suggested they were likely non-allergenic and contained no discernible toxic domains. Molecular docking analysis demonstrated that both altered and wild-type BanLecs exhibited strong affinity with the RBD of different SARS-CoV-2 variants. Further analysis of the molecular docking results showed that the BanLec proteins interacted with the active site of RBD, particularly the key amino acids residues responsible for RBD's binding to hACE2. Molecular dynamics simulation indicated a stable interaction between the Omicron RBD and BanLec, maintaining a root-mean-square deviation (RMSD) of approximately 0.2 nm for a duration of up to 100 ns. The individual proteins also had stable structural conformations, and the complex demonstrated a favorable binding-free energy (BFE) value.

CONCLUSIONS

These results confirm that the BanLec protein is a promising candidate for developing a potential therapeutic agent for combating COVID-19. Furthermore, the results suggest the possibility of BanLec as a broad-spectrum antiviral agent and highlight the need for further studies to examine the protein's safety and effectiveness as a potent antiviral agent.

Assessing protein model quality based on deep graph coupled networks using protein language model

Model quality evaluation is a crucial part of protein structural biology. How to distinguish high-quality models from low-quality models, and to assess which high-quality models have relatively incorrect regions for improvement, are remain a challenge. More importantly, the quality assessment of multimer models is a hot topic for structure prediction. In this study, we propose GraphCPLMQA, a novel approach for evaluating residue-level model quality that combines graph coupled networks and embeddings from protein language models. The GraphCPLMQA consists of a graph encoding module and a transform-based convolutional decoding module. In encoding module, the underlying relational representations of sequence and high-dimensional geometry structure are extracted by protein language models with Evolutionary Scale Modeling. In decoding module, the mapping connection between structure and quality is inferred by the representations and low-dimensional features. Specifically, the triangular location and residue level contact order features are designed to enhance the association between the local structure and the overall topology. Experimental results demonstrate that GraphCPLMQA using single-sequence embedding achieves the best performance compared with the CASP15 residue-level interface evaluation methods among 9108 models in the local residue interface test set of CASP15 multimers. In CAMEO blind test (20 May 2022 to 13 August 2022), GraphCPLMQA ranked first compared with other servers (https://www.cameo3d.org/quality-estimation). GraphCPLMQA also outperforms state-of-the-art methods on 19, 035 models in CASP13 and CASP14 monomer test set.

Biochemical Activity of 17 Cancer-Associated Variants of DNA Polymerase Kappa Predicted by Electrostatic Properties

DNA damage and repair have been widely studied in relation to cancer and therapeutics. Y-family DNA polymerases can bypass DNA lesions, which may result from external or internal DNA damaging agents, including some chemotherapy agents. Overexpression of the Y-family polymerase human pol kappa can result in tumorigenesis and drug resistance in cancer. This report describes the use of computational tools to predict the effects of single nucleotide polymorphism variants on pol kappa activity. Partial Order Optimum Likelihood (POOL), a machine learning method that uses input features from Theoretical Microscopic Titration Curve Shapes (THEMATICS), was used to identify amino acid residues most likely involved in catalytic activity. The μ4 value, a metric obtained from POOL and THEMATICS that serves as a measure of the degree of coupling between one ionizable amino acid and its neighbors, was then used to identify which protein mutations are likely to impact the biochemical activity. Bioinformatic tools SIFT, PolyPhen-2, and FATHMM predicted most of these variants to be deleterious to function. Along with computational and bioinformatic predictions, we characterized the catalytic activity and stability of 17 cancer-associated DNA pol kappa variants. We identified pol kappa variants R48I, H105Y, G147D, G154E, V177L, R298C, E362V, and R470C as having lower activity relative to wild-type pol kappa; the pol kappa variants T102A, H142Y, R175Q, E210K, Y221C, N330D, N338S, K353T, and L383F were identified as being similar in catalytic efficiency to WT pol kappa. We observed that POOL predictions can be used to predict which variants have decreased activity. Predictions from bioinformatic tools like SIFT, PolyPhen-2, and FATHMM are based on sequence comparisons and therefore are complementary to POOL but are less capable of predicting biochemical activity. These bioinformatic and computational tools can be used to identify SNP variants with deleterious effects and altered biochemical activity from a large data set.

Asn215Ser, Ala143Thr, and Arg112Cys variants in α-galactosidase A protein confer stability loss in Fabry's disease

Alpha galactosidase A (α-GalA) gene contains nine exons localized at the q-arm of the X chromosome. Generally, an α-GalA enzyme is involved in the removal of galactosyl moieties from the glycoproteins and glycolipids. Dysregulation results in the accumulation of glycoproteins as well as glycolipids in various organs leading to Fabry disease (FD). In this study, we examine the impact of Asn215Ser, Ala143Thr and Arg112Cys variants on the α-GalA protein structure contributing to functional dynamic changes in FD. The seven computational pathogenicity prediction methods were used to predict the effects of these variants on the α-GalA protein. The three-dimensional structure of α-GalA variants was modeled with the Swiss Model and Robetta server and validated using a variety of tools. Then, molecular dynamics (MD) simulation was performed to understand the stability and dynamic behavior of the wild-type and variants structures. Most of our analyzed pathogenicity prediction tools showed that Asn215Ser, Ala143Thr and Arg112Cys variants cause a deleterious effect on the α-GalA protein. Further, MD trajectory analysis showed the destabilizing effect of variants on α-GalA structure based on the root mean square deviation, root mean square fluctuation, solvent accessible surface area, the radius of gyration, hydrogen bond, cluster analysis and PCA analysis. This concludes that the presence of these variants could potentially affect the protein functional process of galactosyl moieties removal which might lead to Fabry disease.Communicated by Ramaswamy H. Sarma.

High-throughput virtual screening approach of natural compounds as target inhibitors of plasmepsin-II

Plasmepsin II is a key enzyme in the life cycle of the Plasmodium falciparum parasite responsible for malaria, a disease that is causing deaths on a worldwide scale. Recently, plasmepsin II enzyme has gained much importance as an attractive drug target for the investigation of antimalarial drugs. In this sense, structure-based virtual screening have been utilized as tools in the process of discovering novel natural compounds based on quinoline as potential plasmepsin II inhibitors. Among the 58 quinoline derivatives isolated from different plants was screened by utilizing docking molecular, ADMET approaches, molecular dynamics simulation and MM-PBSA binding free energy. The first step in this work is building the 3 D structures of the plasmepsin II enzyme by using the SWISS-MODEL software. The optimized structures were subjected to virtual screening by Autodock Vina, an entity implicated in PyRx software. 21 were selected based on their binding affinity. The binding modes and interactions of the top-21 selected compounds were evaluated using AutoDock 4.2. Then, the pharmacokinetic proprieties and toxicity of these compounds were evaluated using ADMET analysis. Ten compounds were predicted to have ADMET characteristics with no side effects. Compounds M49 and M53 were found to be potential inhibitors. The stability of the selected two compounds was confirmed by MD simulation and MM/PBSA calculation during 200 ns. This study can be used to predict and to design new antimalarial drugs.Communicated by Ramaswamy H. Sarma.

The Enolase of the Haemophilus influenzae Mediates Binding to Collagens: An Extracellular Matrix Component

Enolase proteins play a significant role as moonlighting proteins. In their role as surface-associated enolase, they have multiple functions as they interact with extracellular matrix proteins. Type I and III collagens are the major constituents of this extracellular matrix, and collagen is one of the targets of interaction with the enolase of many pathogens, thereby helping the colonization process and promoting the subsequent invasion of the host. This work aimed to determine the participation of non-typeable H. influenzae enolase as a collagen-binding protein. In this study, through the use of in vitro tests it was demonstrated that recombinant enolase of non-typeable H. influenzae (rNTHiENO) strongly binds to type I collagen. Using molecular docking, the residues that could take part in the interaction of non-typeable H. influenzae enolase-type I collagen (NTHiENO-Cln I) and non-typeable H. influenzae enolase-type III collagen (NTHiENO-Cln III) were identified. However, in vitro assays show that NTHiENO has a better affinity to interact with Cln I, concerning type Cln III. The interaction of NTHiENO with collagen could play a significant role in the colonization process; this would allow H. influenzae to increase its virulence factors and strengthen its pathogenesis.

Functional annotation of haloacid dehalogenase superfamily structural genomics proteins

Haloacid dehalogenases (HAD) are members of a large superfamily that includes many Structural Genomics proteins with poorly characterized functionality. This superfamily consists of multiple types of enzymes that can act as sugar phosphatases, haloacid dehalogenases, phosphonoacetaldehyde hydrolases, ATPases, or phosphate monoesterases. Here, we report on predicted functional annotations and experimental testing by direct biochemical assay for Structural Genomics proteins from the HAD superfamily. To characterize the functions of HAD superfamily members, nine representative HAD proteins and 21 structural genomics proteins are analyzed. Using techniques based on computed chemical and electrostatic properties of individual amino acids, the functions of five structural genomics proteins from the HAD superfamily are predicted and validated by biochemical assays. A dehalogenase-like hydrolase, RSc1362 (Uniprot Q8XZN3, PDB 3UMB) is predicted to be a dehalogenase and dehalogenase activity is confirmed experimentally. Four proteins predicted to be sugar phosphatases are characterized as follows: a sugar phosphatase from Thermophilus volcanium (Uniprot Q978Y6) with trehalose-6-phosphate phosphatase and fructose-6-phosphate phosphatase activity; haloacid dehalogenase-like hydrolase from Bacteroides thetaiotaomicron (Uniprot Q8A2F3; PDB 3NIW) with fructose-6-phosphate phosphatase and sucrose-6-phosphate phosphatase activity; putative phosphatase from Eubacterium rectale (Uniprot D0VWU2; PDB 3DAO) as a sucrose-6-phosphate phosphatase; and hypothetical protein from Geobacillus kaustophilus (Uniprot Q5L139; PDB 2PQ0) as a fructose-6-phosphate phosphatase. Most of these sugar phosphatases showed some substrate promiscuity.

Identification and characterization of the Cyamopsis tetragonoloba transcription factor MYC (CtMYC) under drought stress

The MYC transcription factor (TF) has a variety of roles in abiotic stress responses of plants. In the present work, MYC TF named CtMYC (Cymopsis tetragonoloba) from guar plant, which is induced by drought stress, was identified. The mature leaves of guar were employed to detect the full-length CtMYC TF on the 8th day of drought stress. The CtMYC gene showed tissue-specific expression and up regulated under drought stress conditions as compared to the control and maximum expression was observed in mature leaves. Additionally, CtMYC TF was cloned and expressed in E. coli Rosetta cells and CtMYC protein was purified. The circular dichroism (CD) analysis revealed the presence of helical content and beta sheets and in the presence of genomic DNA the conformational changes were observed in secondary structure, which showed DNA binding potential of CtMYC. These results were analyzed by CD and fluorescence studies. In silico studies reveal the presence of conserved bHLH domain and DNA-binding amino acid residues His, Glu and Arg in CtMYC. This is first report on CtMYC TF with DNA binding potential that is responsive to drought. This study provides the structure and characterization of CtMYC TF and DNA binding ability in drought tolerance mechanism in guar.

Revealing the Salmo salar NLRP3 Inflammasome: Insights from Structural Modeling and Transcriptome Analysis

The NLRP3, one of the most heavily studied inflammasome-related proteins in mammals, remains inadequately characterized in Atlantic salmon (Salmo salar), despite the significant commercial importance of this salmonid. The NLRP3 inflammasome is composed of the NLRP3 protein, which is associated with procaspase-1 via an adapter molecule known as ASC. This work aims to characterize the Salmo salar NLRP3 inflammasome through in silico structural modeling, functional transcript expression determination in the SHK-1 cell line in vitro, and a transcriptome analysis on Atlantic salmon. The molecular docking results suggested a similar arrangement of the ternary complex between NLRP3, ASC, and caspase-1 in both the Atlantic salmon and the mammalian NLRP3 inflammasomes. Moreover, the expression results confirmed the functionality of the SsNLRP3 inflammasome in the SHK-1 cells, as evidenced by the lipopolysaccharide-induced increase in the transcription of genes involved in inflammasome activation, including ASC and NLRP3. Additionally, the transcriptome results revealed that most of the inflammasome-related genes, including ASC, NLRP3, and caspase-1, were down-regulated in the Atlantic salmon following its adaptation to seawater (also known as parr-smolt transformation). This is correlated with a temporary detrimental effected on the immune system. Collectively, these findings offer novel insights into the evolutionarily conserved role of NLRP3.

Carbonic Anhydrase Inhibition as a Target for Antibiotic Synergy in Enterococci

Enterococcus faecalis is a hospital-associated opportunistic pathogen that can cause infections with high mortality, such as infective endocarditis. With an increasing occurrence of multidrug-resistant enterococci, there is a need for alternative strategies to treat enterococcal infections. We isolated a gentamicin-hypersusceptible E. faecalis strain from a patient with infective endocarditis that carried a mutation in the alpha-carbonic anhydrase (α-CA) and investigated how disruption of α-CA sensitized E. faecalis to killing with gentamicin. The gentamicin-hypersusceptible α-CA mutant strain showed increased intracellular gentamicin uptake in comparison to an isogenic strain encoding full-length, wild-type α-CA. We hypothesized that increased gentamicin uptake could be due to increased proton motive force (PMF), increased membrane permeability, or both. We observed increased intracellular ATP production in the α-CA mutant strain, suggesting increased PMF-driven gentamicin uptake contributed to the strain's gentamicin susceptibility. We also analyzed the membrane permeability and fatty acid composition of isogenic wild-type and α-CA mutant strains and found that the mutant displayed a membrane composition that was consistent with increased membrane permeability. Finally, we observed that exposure to the FDA-approved α-CA inhibitor acetazolamide lowered the gentamicin MIC of eight genetically diverse E. faecalis strains with intact α-CA but did not change the MIC of the α-CA mutant strain. These results suggest that α-CA mutation or inhibition increases PMF and alters membrane permeability, leading to increased uptake of gentamicin into E. faecalis. This connection could be exploited clinically to provide new combination therapies for patients with enterococcal infections. IMPORTANCE Enterococcal infections can be difficult to treat, and new therapeutic approaches are needed. In studying an E. faecalis clinical strain from an infected patient, we found that the bacteria were rendered hypersusceptible to aminoglycoside antibiotics through a mutation that disrupted the α-CA. Our follow-on work suggested two different ways that α-CA disruption causes increased gentamicin accumulation in E. faecalis: increased proton motive force-powered uptake and increased membrane permeability. We also found that a mammalian CA inhibitor could sensitize a variety of E. faecalis strains to killing with gentamicin. Given that mammalian CA inhibitors are frequently used to treat conditions such as glaucoma, hypertension, and epilepsy, our findings suggest that these "off-the-shelf" inhibitors could also be useful partner antibiotics for the treatment of E. faecalis infections.

In Silico and Experimental Studies on the Effect of α3 and α5 Deletion on the Biochemical Properties of Bacillus thermocatenulatus Lipase

To investigate the effect of α3 and α5 helices on the biochemical characterization of Bacillus thermocatenulatus lipase (BTL2), both helices were deleted from native BTL2 lipase. After structural modeling and characterization, the truncated btl2 gene (Δbtl2) was cloned into E. coli BL21 under the control of the T7 promoter. After cultivation and induction of the recombinant bacteria, the Δα3α5 lipase was purified by Ni-NTA column chromatography. Next, the biochemical properties of the Δα3α5 lipase were compared with the previously expressed and purified native lipase. In the presence of the substrate tributyrin (C4), the maximum activity of native and Δα3α5 lipase was 9360 and 5000 U/mg, respectively. The deletion changed the substrate specificity from tributyrin (C4) to tricaprylin (C8) substrate. Native and Δα3α5 lipase showed similar activity patterns at all temperatures and pH values, with the activity of Δα3α5 lipase being approximately 20% lower than native lipase. Triton X100 increased the activity of native and Δα3α5 lipases by 2.1- and 2.5-fold, respectively.

Structure-based prediction of Ras-effector binding affinities and design of "branchegetic" interface mutations

Ras is a central cellular hub protein controlling multiple cell fates. How Ras interacts with a variety of potential effector proteins is relatively unexplored, with only some key effectors characterized in great detail. Here, we have used homology modeling based on X-ray and AlphaFold2 templates to build structural models for 54 Ras-effector complexes. These models were used to estimate binding affinities using a supervised learning regressor. Furthermore, we systematically introduced Ras "branch-pruning" (or branchegetic) mutations to identify 200 interface mutations that affect the binding energy with at least one of the model structures. The impacts of these branchegetic mutants were integrated into a mathematical model to assess the potential for rewiring interactions at the Ras hub on a systems level. These findings have provided a quantitative understanding of Ras-effector interfaces and their impact on systems properties of a key cellular hub.

H2S-Generating Cytosolic L-Cysteine Desulfhydrase and Mitochondrial D-Cysteine Desulfhydrase from Sweet Pepper (Capsicum annuum L.) Are Regulated During Fruit Ripening and by Nitric Oxide

Aims: Pepper fruit is a horticultural product worldwide consumed that has great nutritional and economic relevance. Besides the phenotypical changes that undergo pepper fruit during ripening, there are many associated modifications at transcriptomic, proteomic, biochemical, and metabolic levels. Nitric oxide (NO) and hydrogen sulfide (H2S) are recognized signal molecules that can exert regulatory functions in diverse plant processes. This study aims at analyzing the interrelationship between NO and H2S during fruit ripening. Results: Our data indicate that the H2S-generating cytosolic L-cysteine desulfhydrase (LCD) and the mitochondrial D-cysteine desulfhydrase (DCD) activities are downregulated during ripening but this effect was reverted after NO treatment of fruits. Innovation and Conclusion: Using as a model the non-climacteric pepper fruits at different ripening stages and under an NO-enriched atmosphere, the activity of the H2S-generating LCD and DCD was analyzed. LCD and DCD activities were downregulated during ripening, but this effect was reverted after NO treatment of fruits. The analysis of LCD activity by non-denaturing polyacrylamide gel electrophoresis (PAGE) allowed identifying three isozymes designated CaLCD I to CaLCD III, which were differentially modulated by NO and strictly dependent on pyridoxal 5'-phosphate (PLP). In vitro analyses of green fruit samples in the presence of different compounds including NO donors, peroxynitrite (ONOO-), and reducing agents such as reduced glutathione (GSH) and L-cysteine (L-Cys) triggered an almost 100% inhibition of CaLCD II and CaLCD III. This redox adaptation process of both enzymes could be cataloged as a hormesis phenomenon. The protein tyrosine (Tyr) nitration (an NO-promoted post-translational modification) of the recombinant LCD was corroborated by immunoblot and by mass spectrometry (MS) analyses. Among the 11 Tyr residues present in this enzyme, MS of the recombinant LCD enabled us to identify that Tyr82 and Tyr254 were nitrated by ONOO-, this occurring near the active center on the enzyme, where His237 and Lys260 together with the cofactor PLP are involved. These data support the relationship between NO and H2S during pepper fruit ripening, since LCD and DCD are regulated by NO during this physiological event, and this could also be extrapolated to other plant species.

Glypican-3 (GPC-3) Structural Analysis and Cargo in Serum Small Extracellular Vesicles of Hepatocellular Carcinoma Patients

Glypican-3 (GPC-3) is a heparin sulfate proteoglycan located extracellularly and anchored to the cell membrane of transformed hepatocytes. GPC-3 is not expressed in normal or cirrhotic liver tissue but is overexpressed in hepatocellular carcinoma (HCC). Because of this, GPC-3 is one of the most important emerging immunotargets for treatment and as an early detection marker of HCC. To determine if GPC-3 domains associated with serum small extracellular vesicles (sEVs) could be used as an HCC diagnostic marker, we predicted in silico GPC-3 structural properties and tested for the presence of its full-length form and/or cleaved domains in serum sEVs isolated from patients with HCC. Structural analysis revealed that the Furin cleavage site of GPC-3 is exposed and readily accessible, suggesting the facilitation of GPC-3 cleavage events. Upon isolation of sEVs from both hepatocytes, culture media and serum of patients with HCC were studied for GPC-3 content. This data suggests that Furin-dependent GPC-3 cleaved domains could be a powerful tool for detection of initial stages of HCC and serve as a predictor for disease prognosis.

A VEGFB-Based Peptidomimetic Inhibits VEGFR2-Mediated PI3K/Akt/mTOR and PLCγ/ERK Signaling and Elicits Apoptotic, Antiangiogenic, and Antitumor Activities

Vascular endothelial growth factor receptor 2 (VEGFR2) mediates VEGFA signaling mainly through the PI3K/AKT/mTOR and PLCγ/ERK1/2 pathways. Here we unveil a peptidomimetic (VGB3) based on the interaction between VEGFB and VEGFR1 that unexpectedly binds and neutralizes VEGFR2. Investigation of the cyclic and linear structures of VGB3 (named C-VGB3 and L-VGB3, respectively) using receptor binding and cell proliferation assays, molecular docking, and evaluation of antiangiogenic and antitumor activities in the 4T1 mouse mammary carcinoma tumor (MCT) model showed that loop formation is essential for peptide functionality. C-VGB3 inhibited proliferation and tubulogenesis of human umbilical vein endothelial cells (HUVECs), accounting for the abrogation of VEGFR2, p-VEGFR2 and, subsequently, PI3K/AKT/mTOR and PLCγ/ERK1/2 pathways. In 4T1 MCT cells, C-VGB3 inhibited cell proliferation, VEGFR2 expression and phosphorylation, the PI3K/AKT/mTOR pathway, FAK/Paxillin, and the epithelial-to-mesenchymal transition cascade. The apoptotic effects of C-VGB3 on HUVE and 4T1 MCT cells were inferred from annexin-PI and TUNEL staining and activation of P53, caspase-3, caspase-7, and PARP1, which mechanistically occurred through the intrinsic pathway mediated by Bcl2 family members, cytochrome c, Apaf-1 and caspase-9, and extrinsic pathway via death receptors and caspase-8. These data indicate that binding regions shared by VEGF family members may be important in developing novel pan-VEGFR inhibitors that are highly relevant in the pathogenesis of angiogenesis-related diseases.

GraphGPSM: a global scoring model for protein structure using graph neural networks

The scoring models used for protein structure modeling and ranking are mainly divided into unified field and protein-specific scoring functions. Although protein structure prediction has made tremendous progress since CASP14, the modeling accuracy still cannot meet the requirements to a certain extent. Especially, accurate modeling of multi-domain and orphan proteins remains a challenge. Therefore, an accurate and efficient protein scoring model should be developed urgently to guide the protein structure folding or ranking through deep learning. In this work, we propose a protein structure global scoring model based on equivariant graph neural network (EGNN), named GraphGPSM, to guide protein structure modeling and ranking. We construct an EGNN architecture, and a message passing mechanism is designed to update and transmit information between nodes and edges of the graph. Finally, the global score of the protein model is output through a multilayer perceptron. Residue-level ultrafast shape recognition is used to describe the relationship between residues and the overall structure topology, and distance and direction encoded by Gaussian radial basis functions are designed to represent the overall topology of the protein backbone. These two features are combined with Rosetta energy terms, backbone dihedral angles and inter-residue distance and orientations to represent the protein model and embedded into the nodes and edges of the graph neural network. The experimental results on the CASP13, CASP14 and CAMEO test sets show that the scores of our developed GraphGPSM have a strong correlation with the TM-score of the models, which are significantly better than those of the unified field score function REF2015 and the state-of-the-art local lDDT-based scoring models ModFOLD8, ProQ3D and DeepAccNet, etc. The modeling experimental results on 484 test proteins demonstrate that GraphGPSM can greatly improve the modeling accuracy. GraphGPSM is further used to model 35 orphan proteins and 57 multi-domain proteins. The results show that the average TM-score of the models predicted by GraphGPSM is 13.2 and 7.1% higher than that of the models predicted by AlphaFold2. GraphGPSM also participates in CASP15 and achieves competitive performance in global accuracy estimation.

Rational Engineering of (S)-Norcoclaurine Synthase for Efficient Benzylisoquinoline Alkaloids Biosynthesis

(S)-Norcoclaurine is synthesized in vivo through a metabolic pathway that ends with (S)-norcoclaurine synthase (NCS). The former constitutes the scaffold for the biosynthesis of all benzylisoquinoline alkaloids (BIAs), including many drugs such as the opiates morphine and codeine and the semi-synthetic opioids oxycodone, hydrocodone, and hydromorphone. Unfortunately, the only source of complex BIAs is the opium poppy, leaving the drug supply dependent on poppy crops. Therefore, the bioproduction of (S)-norcoclaurine in heterologous hosts, such as bacteria or yeast, is an intense area of research nowadays. The efficiency of (S)-norcoclaurine biosynthesis is strongly dependent on the catalytic efficiency of NCS. Therefore, we identified vital NCS rate-enhancing mutations through the rational transition-state macrodipole stabilization method at the Quantum Mechanics/Molecular Mechanics (QM/MM) level. The results are a step forward for obtaining NCS variants able to biosynthesize (S)-norcoclaurine on a large scale.

Identification of Potential TMPRSS2 Inhibitors for COVID-19 Treatment in Chinese Medicine by Computational Approaches and Surface Plasmon Resonance Technology

BACKGROUND

Coronavirus disease-19 (COVID-19) pneumonia continues to spread in the entire globe with limited medication available. In this study, the active compounds in Chinese medicine (CM) recipes targeting the transmembrane serine protease 2 (TMPRSS2) protein for the treatment of COVID-19 were explored.

METHODS

The conformational structure of TMPRSS2 protein (TMPS2) was built through homology modeling. A training set covering TMPS2 inhibitors and decoy molecules was docked to TMPS2, and their docking poses were re-scored with scoring schemes. A receiver operating characteristic (ROC) curve was applied to select the best scoring function. Virtual screening of the candidate compounds (CCDs) in the six highly effective CM recipes against TMPS2 was conducted based on the validated docking protocol. The potential CCDs after docking were subject to molecular dynamics (MD) simulations and surface plasmon resonance (SPR) experiment.

RESULTS

A training set of 65 molecules were docked with modeled TMPS2 and LigScore2 with the highest area under the curve, AUC, value (0.886) after ROC analysis selected to best differentiate inhibitors from decoys. A total of 421 CCDs in the six recipes were successfully docked into TMPS2, and the top 16 CCDs with LigScore2 higher than the cutoff (4.995) were screened out. MD simulations revealed a stable binding between these CCDs and TMPS2 due to the negative binding free energy. Lastly, SPR experiments validated the direct combination of narirutin, saikosaponin B1, and rutin with TMPS2.

CONCLUSIONS

Specific active compounds including narirutin, saikosaponin B1, and rutin in CM recipes potentially target and inhibit TMPS2, probably exerting a therapeutic effect on COVID-19.

Antiviral activity of some benzo[g]quinazolines against coxsackievirus B4: biological screening and docking study

BACKGROUND

Serotype coxsackievirus B (CVB) infection has been linked to viral myocarditis, dilated cardiomyopathy, meningitis, and pancreatitis in children and young adults. As of yet, no antiviral drug has been authorized for the treatment of coxsackievirus infection. Therefore, there is perpetual demand for new therapeutic agents and the improvement of existing ones. Benzo[g]quinazolines, the subject of several well-known heterocyclic systems, have risen to prominence and played a significant role in the development of antiviral agents, particularly those for anti-coxsackievirus B4 infection.

METHODS

This study investigated the cytotoxicity of the target benzo[g]quinazolines (1-16) in the BGM cells line as well as their anti-coxsackievirus B4 activity. Determination of CVB4 titers using a plaque assay.

RESULTS

Most of the target benzoquinazolines exhibited antiviral activity, however, compounds 1-3 appeared to be the most effective (reduction percentages of 66.7, 70, and 83.3%, respectively). The binding mechanisms and interactions of the three most active 1-3 with the constitutive amino acids in the active site of the multi-target of coxsackievirus B4 (3Clpro and RdRp) targets were also investigated using molecular docking.

CONCLUSION

The anti coxsackievirus B4 activity has resulted, and the top three active benzoquinazolines (1-3) have bonded to and interacted with the constitutive amino acids in the active region of the multi-target coxsackievirus B4 (RdRp and 3Clpro). Further research is required in the lab. to determine the exact benzoquinazolines mechanism of action.

Exploring allosteric hits of the NS2B-NS3 protease of DENV2 by structure-guided screening

Despite the rising number of cases and increasing global disease burden, there is no definitive therapy against dengue to date, which necessitates the urgent discovery of inhibitors against the virus. The NS2B-NS3 serine protease of the dengue virus (DENV) catalyses polyprotein cleavage and is a potential target for drug discovery. The protease possesses a potentially druggable allosteric site, and the binding of inhibitors to this site locks the protease in an inactive conformation. The allosteric site is a potential druggable target for drug discovery against flaviviruses. This study aimed to identify serotype-specific hits against the allosteric site in the NS2B-NS3 protease of DENV serotype 2 (DENV2) from the Enamine, Selleck, and ChemDiv antiviral libraries. The prepared libraries were screened using a redocking and rescoring-based strategy with Glide SP and Glide XP, and the hitlist was initially screened by comparing their docking scores with that of reported allosteric inhibitors, myricetin and curcumin. The hitlist was subsequently screened by comparing the molecular mechanics with generalised Born and surface area solvation (MM-GBSA) energy with that of the standards. Ten hits were finally selected by virtual screening, and the stability of the hit-receptor complexes was determined with 100 ns molecular dynamics (MD) simulations in an explicit solvent. Trajectory visualisation and analyses of the RMSD and RMSF values revealed that three hits, including two catechins, remained stably bound to the allosteric binding site throughout the production run. Hit-receptor interaction analyses revealed that the hits formed highly stable interactions with Glu 88, Trp 89, Leu 149, Ile 165, and Asn 167, and MM-GBSA energy analysis revealed that the three hits had high binding affinity to the allosteric site. The findings obtained herein can aid in identifying novel serotype-specific inhibitors of DENV protease in future.

Functional assessment of AtPAP17; encoding a purple acid phosphatase involved in phosphate metabolism in Arabidopsis thaliana

PURPOSE

Purple acid phosphatases (PAPs) includ the largest classes of non-specific plant acid phosphatases. Most characterized PAPs were found to play physiological functions in phosphorus metabolism. In this study, we investigated the function of AtPAP17 gene encoding an important purple acid phosphatase in Arabidopsis thaliana.

METHODS

The full-length cDNA sequence of AtPAP17 gene under the control of CaMV-35S promoter was transferred to the A. thaliana WT plant. The generated homozygote AtPAP17-overexpressed plants were compared by the types of analyses with corresponding homozygote atpap17-mutant plant and WT in both + P (1.2 mM) and - P (0 mM) conditions.

RESULTS

In the + P condition, the highest and the lowest amount of Pi was observed in AtPAP17-overexpressed plants and atpap17-mutant plants by 111% increase and 38% decrease compared with the WT plants, respectively. Furthermore, under the same condition, APase activity of AtPAP17-overexpressed plants increased by 24% compared to the WT. Inversely, atpap17-mutant plant represented a 71% fall compared to WT plants. The comparison of fresh weight and dry weight in the studied plants showed that the highest and the lowest amount of absorbed water belonged to OE plants (with 38 and 12 mg plant^-1) and Mu plants (with 22 and 7 mg plant^-1) in + P and - P conditions, respectively.

CONCLUSION

The lack of AtPAP17 gene in the A. thaliana genome led to a remarkable reduction in the development of root biomass. Thus, AtPAP17 could have an important role in the root but not shoot developmental and structural programming. Consequently, this function enables them to absorb more water and eventually associated with more phosphate absorption.

In Silico-Based Structural Evaluation to Categorize the Pathogenicity of Mutations Identified in the RAD Class of Proteins

RAD genes, known as double-strand break repair proteins, play a major role in maintaining the genomic integrity of a cell by carrying out essential DNA repair functions via double-strand break repair pathways. Mutations in the RAD class of proteins show high susceptibility to breast and ovarian cancers; however, adequate research on the mutations identified in these genes has not been extensively reported for their deleterious effects. Changes in the folding pattern of RAD proteins play an important role in protein-protein interactions and also functions. Missense mutations identified from four cancer databases, cBioPortal, COSMIC, ClinVar, and gnomAD, cause aberrant conformations, which may lead to faulty DNA repair mechanisms. It is therefore necessary to evaluate the effects of pathogenic mutations of RAD proteins and their subsequent role in breast and ovarian cancers. In this study, we have used eight computational prediction servers to analyze pathogenic mutations and understand their effects on the protein structure and function. A total of 5122 missense mutations were identified from four different cancer databases, of which 1165 were predicted to be pathogenic using at least five pathogenicity prediction servers. These mutations were characterized as high-risk mutations based on their location in the conserved domains and subsequently subjected to structural stability characterization. The mutations included in the present study were selected from clinically relevant mutants in breast cancer pedigrees. Comparative folding patterns and intra-atomic interaction results showed alterations in the structural behavior of RAD proteins, specifically RAD51C triggered by mutations G125V and L138F and RAD51D triggered by mutations S207L and E233G.

Computational Analysis and Experimental Testing of the Molecular Mode of Action of Gatastatin and Its Derivatives

Given its critical role in cell mitosis, the tubulin γ chain represents a viable chemotherapeutic target to solve the specificity issues associated with targeting α and β tubulin. Since γ tubulin is overexpressed in glioblastoma multiforme (GBM) and some breast lesions, the glaziovianin A derivative gatastatin, presented as a γ-tubulin-specific inhibitor, could yield a successful therapeutic strategy. The present work aims to identify the binding sites and modes of gatastatin and its derivatives through molecular-docking simulations. Computational binding free energy predictions were compared to experimental microscale thermophoresis assay results. The computational simulations did not reveal a strong preference toward γ tubulin, suggesting that further derivatization may be needed to increase its specificity.

The Trypanosoma brucei MISP family of invariant proteins is co-expressed with BARP as triple helical bundle structures on the surface of salivary gland forms, but is dispensable for parasite development within the tsetse vector

Trypanosoma brucei spp. develop into mammalian-infectious metacyclic trypomastigotes inside tsetse salivary glands. Besides acquiring a variant surface glycoprotein (VSG) coat, little is known about the metacyclic expression of invariant surface antigens. Proteomic analyses of saliva from T. brucei-infected tsetse flies identified, in addition to VSG and Brucei Alanine-Rich Protein (BARP) peptides, a family of glycosylphosphatidylinositol (GPI)-anchored surface proteins herein named as Metacyclic Invariant Surface Proteins (MISP) because of its predominant expression on the surface of metacyclic trypomastigotes. The MISP family is encoded by five paralog genes with >80% protein identity, which are exclusively expressed by salivary gland stages of the parasite and peak in metacyclic stage, as shown by confocal microscopy and immuno-high resolution scanning electron microscopy. Crystallographic analysis of a MISP isoform (MISP360) and a high confidence model of BARP revealed a triple helical bundle architecture commonly found in other trypanosome surface proteins. Molecular modelling combined with live fluorescent microscopy suggests that MISP N-termini are potentially extended above the metacyclic VSG coat, and thus could be tested as a transmission-blocking vaccine target. However, vaccination with recombinant MISP360 isoform did not protect mice against a T. brucei infectious tsetse bite. Lastly, both CRISPR-Cas9-driven knock out and RNAi knock down of all MISP paralogues suggest they are not essential for parasite development in the tsetse vector. We suggest MISP may be relevant during trypanosome transmission or establishment in the vertebrate's skin.

Three-dimensional models of antigens with serodiagnostic potential for leprosy: An in silico study

BACKGROUND

Leprosy is a disease caused by Mycobacterium leprae (M. leprae), an intracellular pathogen that has tropism and affects skin and nervous system cells. The disease has two forms of presentation: Paucibacillary and multibacillary, with different clinical and immunological manifestations. Unlike what occurs in the multibacillary form , the diagnostic tests for the paucibacillary form are nonspecific and not very sensitive, allowing the existence of infected individuals without treatment, which contributes to the spread of the pathogen in the population. To mitigate this contamination, more sensitive diagnostic tests capable of detecting paucibacillary patients are needed.

AIM

To predict the three-dimensional structure models of M. leprae antigens with serodiagnostic potential for leprosy.

METHODS

In this in silico study, satisfactory templates were selected in the Protein Data Bank (PDB) using Basic Local Alignment Search Tool to predict the structural templates of ML2038, ML0286, ML0050, and 85B antigens by comparative modeling. The templates were selected according to general criteria such as sequence identity, coverage, X-ray resolution, Global Model Quality Estimate value and phylogenetic relationship; Clustal X 2.1 software was used in this analysis. Molecular modeling was completed using the software Modeller 9v13. Visualization of the models was made using ViewerLite 4.2 and PyMol software, and analysis of the quality of the predicted models was performed using the QMEAN score and Z-score. Finally, the three-dimensional moels were validated using the MolProbity and Verify 3D platforms.

RESULTS

The three-dimensional structure models of ML2038, ML0286, ML0050, and 85B antigens of M. leprae were predicted using the templates PDB: 3UOI (90.51% identity), PDB: 3EKL (87.46% identity), PDB: 3FAV (40.00% identity), and PDB: 1F0N (85.21% identity), respectively. The QMEAN and Z-score values indicated the good quality of the structure models. These data refer to the monomeric units of antigens, since some of these antigens have quaternary structure. The validation of the models was performed with the final three-dimensional structure - monomer (ML0050 and 85B antigens) and quaternary structures (ML2038 and ML0286). The majority of amino acid residues were observed in favorable and allowed regions in the Ramachandran plot, indicating correct positioning of the side chain and absence of steric impediment. The MolProbity score value and Verify 3D results of all models indicated a satisfactory prediction.

CONCLUSION

The polarized immune response against M. leprae creates a problem in leprosy detection. The selection of immunodominant epitopes is essential for the development of more sensitive serodiagnostic tests, for this it is important to know the three-dimensional structure of the antigens, which can be predicted with bioinformatics tools.

A comparative study on structural proteins of viruses that belong to the identical family

Recent studies have focused on the similarity between SARS Cov-2 and various viruses from the Coronaviridae family (such as MERS Cov,  SARS Cov and Bat Cov RaTG13) to uncover the mystery of SARS Cov-2. Specifically, some studies identified that the SARS Cov-2 is closely related to Bat Cov RaTG13 (a SARS-related coronavirus found in bats) rather than the other viruses in that family. These studies are mainly focusing on the biological techniques to show the similarity between the SARS Cov-2 and other viruses. Examining proteins is not easy for common researchers unless for biologists. To rectify this flaw, we have to convert the protein to one of the known formats, which are easy to understand. Consequently, this study uses viral structural proteins to analyse the relationship between SARS Cov-2 and the rest of the coronavirus with the help of mathematical and statistical parameters and explores the various graph representations of MERS Cov,  SARS Cov,  Bat Cov RaTG13 and SARS Cov-2 structural proteins, such as zig-zag curve, Protein Contact Map ( PCM ) and Chaos Game Representation ( CGR ). Though these graph interpretations are visually similar, a slight variation between the graphs reflects their structural and functional differences. Thus, we use an elegant parameter known as the fractal dimension to observe their minor changes. According to the nature of the graph, we employ different types of fractal dimensions, namely mass dimension and box dimension. Furthermore, we perform the similarity tests with normalized cross-correlation and cosine similarity to assess the comparability of the PCM and CGR graphs. The acquired C C n values are near the sequence identity between SARS Cov-2 and MERS Cov,  SARS Cov,  Bat Cov RaTG13.

Structural analysis of human G-protein-coupled receptor 17 ligand binding sites

The human G protein coupled membrane receptor (GPR17), the sensor of brain damage, is identified as a biomarker for many neurological diseases. In human brain tissue, GPR17 exist in two isoforms, long and short. While cryo-electron microscopy technology has provided the structure of the long isoform of GPR17 with Gi complex, the structure of the short isoform and its activation mechanism remains unclear. Recently, we theoretically modeled the structure of the short isoform of GPR17 with Gi signaling protein and identified novel ligands. In the present work, we demonstrated the presence of two distinct ligand binding sites in the short isoform of GPR17. The molecular docking of GPR17 with endogenous (UDP) and synthetic ligands (T0510.3657, MDL29950) found the presence of two distinct binding pockets. Our observations revealed that endogenous ligand UDP can bind stronger in two different binding pockets as evidenced by glide and autodock vina scores, whereas the other two ligand's binding with GPR17 has less docking score. The analysis of receptor-UDP interactions shows complexes' stability in the lipid environment by 100 ns atomic molecular dynamics simulations. The amino acid residues VAL83, ARG87, and PHE111 constitute ligand binding site 1, whereas site 2 constitutes ASN67, ARG129, and LYS232. Root mean square fluctuation analysis showed the residues 83, 87, and 232 with higher fluctuations during molecular dynamics simulation in both binding pockets. Our findings imply that the residues of GPR17's two binding sites are crucial, and their interaction with UDP reveals the protein's hidden signaling and communication properties. Furthermore, this finding may assist in the development of targeted therapies for the treatment of neurological diseases.

Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs

Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based methods. Ligand-based methods encompass techniques including pharmacophore modelling and quantitative structure activity relationships (QSARs), which use the relationship between biological activity and chemical structure to ascertain suitable lead molecules. In contrast, structure-based methods use information about the binding site architecture from an established protein structure to select suitable molecules for further investigation. In recent years, deep learning techniques have been applied in drug design and present an exciting addition to CADD workflows. Despite the difficulties associated with CNS drug discovery, advances towards new pharmaceutical treatments continue to be made, and CADD has supported these findings. This review explores various CADD techniques and discusses applications in CNS drug discovery from 2018 to November 2022.

Improved model quality assessment using sequence and structural information by enhanced deep neural networks

Protein model quality assessment plays an important role in protein structure prediction, protein design and drug discovery. In this work, DeepUMQA2, a substantially improved version of DeepUMQA for protein model quality assessment, is proposed. First, sequence features containing protein co-evolution information and structural features reflecting family information are extracted to complement model-dependent features. Second, a novel backbone network based on triangular multiplication update and axial attention mechanism is designed to enhance information exchange between inter-residue pairs. On CASP13 and CASP14 datasets, the performance of DeepUMQA2 increases by 20.5 and 20.4% compared with DeepUMQA, respectively (measured by top 1 loss). Moreover, on the three-month CAMEO dataset (11 March to 04 June 2022), DeepUMQA2 outperforms DeepUMQA by 15.5% (measured by local AUC0,0.2) and ranks first among all competing server methods in CAMEO blind test. Experimental results show that DeepUMQA2 outperforms state-of-the-art model quality assessment methods, such as ProQ3D-LDDT, ModFOLD8, and DeepAccNet and DeepUMQA2 can select more suitable best models than state-of-the-art protein structure methods, such as AlphaFold2, RoseTTAFold and I-TASSER, provided themselves.

New simulation insights on the structural transition mechanism of bovine rhodopsin activation

Inactive rhodopsin can absorb photons, which induces different structural transitions that finally activate rhodopsin. We have examined the change in spatial configurations and physicochemical factors that result during the transition mechanism from the inactive to the active rhodopsin state via intermediates. During the activation process, many existing atomic contacts are disrupted, and new ones are formed. This is related to the movement of Helix 5, which tilts away from Helix 3 in the intermediate state in lumirhodopsin and moves closer to Helix 3 again in the active state. Similar patterns of changing atomic contacts are observed between Helices 3 and 5 of the adenosine and neurotensin receptors. In addition, residues 220-238 of rhodopsin, which are disordered in the inactive state, fold in the active state before binding to the Gα, where it catalyzes GDP/GTP exchange on the Gα subunit. Finally, molecular dynamics simulations in the membrane environment revealed that the arrestin binding region adopts a more flexible extended conformation upon phosphorylation, likely promoting arrestin binding and inactivation. In summary, our results provide additional structural understanding of specific rhodopsin activation which might be relevant to other Class A G protein-coupled receptor proteins.

Novel CaLB-like Lipase Found Using ProspectBIO, a Software for Genome-Based Bioprospection

Enzymes have been highly demanded in diverse applications such as in the food, pharmaceutical, and industrial fuel sectors. Thus, in silico bioprospecting emerges as an efficient strategy for discovering new enzyme candidates. A new program called ProspectBIO was developed for this purpose as it can find non-annotated sequences by searching for homologs of a model enzyme directly in genomes. Here we describe the ProspectBIO software methodology and the experimental validation by prospecting for novel lipases by sequence homology to Candida antarctica lipase B (CaLB) and conserved motifs. As expected, we observed that the new bioprospecting software could find more sequences (1672) than a conventional similarity-based search in a protein database (733). Additionally, the absence of patent protection was introduced as a criterion resulting in the final selection of a putative lipase-encoding gene from Ustilago hordei (UhL). Expression of UhL in Pichia pastoris resulted in the production of an enzyme with activity towards a tributyrin substrate. The recombinant enzyme activity levels were 4-fold improved when lowering the temperature and increasing methanol concentrations during the induction phase in shake-flask cultures. Protein sequence alignment and structural modeling showed that the recombinant enzyme has high similarity and capability of adjustment to the structure of CaLB. However, amino acid substitutions identified in the active pocket entrance may be responsible for the differences in the substrate specificities of the two enzymes. Thus, the ProspectBIO software allowed the finding of a new promising lipase for biotechnological application without the need for laborious and expensive conventional bioprospecting experimental steps.