Template-based protein structure modeling using the RaptorX web server

Unified Aedes aegypti Protein Resource Database (UAAPRD): An Integrated High-Throughput In Silico Platform for Comprehensive Protein Structure Modeling and Functional Target Analysis to Enhance Vector Control Strategies

A comprehensive examination of Aedes aegypti's proteome to detect key proteins that can be targeted with small molecules can disrupt blood feeding and disease transmission. However, research currently only focuses on finding repellent-like compounds, limiting studies on identifying unexplored proteins in its proteome. High-throughput analysis generates vast amounts of data, raising concerns about accessibility and usability. Establishing a dedicated database is a solution, centralizing information on identified proteins, functions, and modeled structures for easy access and research. This study focuses on scrutinizing key proteins in A. aegypti, modeling their structures using RaptorX standalone tool, identification of druggable binding sites using BiteNet, validating the models via Ramachandran plot studies and refining them via 50-ns molecular dynamic simulations using Schrodinger Maestro. By analyzing ~ 18 k proteins in the proteome of A. aegypti in our previous studies, all proteins involved in the light and dark circadian rhythm of the mosquito, inclusive of proteins in blood feeding, metabolism, etc. were chosen for the current study. The outcome is UAAPRD, a unique repository housing information on hundreds of previously unmodeled and un-simulated mosquito proteins. This robust MYSQL database ( https://uaaprd.onrender.com/user ) houses data on 309 modeled & simulated proteins of A. aegypti. It allows users to obtain protein data, view evolutionary analysis data of the protein categories, visualize proteins of interest, and send request to screen against the pharmacophore models present in UAAPRD against ligand of interest. This study offers crucial insights for developing targeted studies, which will ultimately contribute to more effective vector control strategies.

The VanS sensor histidine kinase from type-B vancomycin-resistant enterococci recognizes vancomycin directly

Vancomycin-resistant enterococci (VRE) are high-priority targets for new therapeutic development. In VRE, expression of the resistance phenotype is controlled by the VanRS two-component system, which senses the presence of the antibiotic and responds by initiating transcription of resistance genes. VanS is a transmembrane sensor histidine kinase that is known to detect the antibiotic and then transduce this signal to the VanR transcription factor; however, fundamental questions remain about how exactly VanS senses vancomycin. Here, we focus on a purified VanRS system from one of the most clinically prevalent forms of VRE, type B. We show that in a native-like membrane environment, vancomycin strongly stimulates the autokinase activity of type-B VanS. We additionally demonstrate that this effect is mediated by a direct physical interaction between the antibiotic and the VanS periplasmic domain. This represents the first time that a direct sensing mechanism has been confirmed for any VanS protein from a human pathogen.

Evolutionary and Structural Assessment of the Human Secreted Frizzled-Related Protein (SFRP) Family

It has been observed that five members of Secreted Frizzled-Related proteins act as antagonists for the Wnt signaling pathway in humans. These glycoproteins have two functional domains: the cysteine-rich domain (CRD) and the netrin-related domain (NTR), with a completely conserved disulfide bond in the CRD domain. Phylogenetic analysis revealed that this protein family can be divided into two subgroups, SFRP1/SFRP2/SFRP5 versus SFRP3/SFRP4. The SFRP3/SFRP4 group was found to be more closely related to the sponge Lubomirskia baicalensis, which is believed to represent the ancient origin of SFRPs. The model evaluation demonstrated high-quality conformational homology modeling in the predicted Human SFRP models compared to the Sizzled crystal structure of Xenopus laevis. The molecular dynamic simulation illustrated that SFRP1 and SFRP2 exhibit the most stable structures during 100 ns of simulation. Multiple sequence alignment and conservation analysis of Human SFRPs showed that the CRD domain of SFRPs is more conserved than the NTR domain. The docking result indicated that SFRP3 has the highest binding affinity to Wnt3, while SFRP1 and SFRP5 have the lowest. Despite the lower affinity of SFRP1/SFRP5 for Wnt3, a higher positive charge in their NTR domains leads to an increase in their local concentration near the secreting cells and an enhancement in the antagonistic activity. In contrast, SFRP3/SFRP4 can act as an antagonist in distant cells due to less positive regions in their NTR domain and weakly binding to the heparin of the intercellular matrix.

Differential molecular interactions between iberiotoxin and human SLO3 and SLO1 potassium channels

CONTEXT

SLO1and SLO3 are similar voltage-gated K + channels. However, SLO3 expression is sperm specific and plays an important role in the hyperpolarization of the sperm membrane potential that is crucial for sperm fertilization. This makes SLO3 an excellent molecular target for the development of male contraceptives, and computational methods can facilitate structural insights for this drug development. Here, we evaluated the differential molecular interactions between the human SLO3 (hSLO3) and SLO1 (hSLO1) potassium channels and iberiotoxin (IbTX), a toxin that selectively blocks SLO channels. To do this, molecular docking and dynamics were implemented on the channel-toxin complexes to help elucidate atomistic details of their interaction and binding energy. Our analysis found that IbTX has a similar binding energy to both channels but interacts in a distinct manner with them. Particularly, Trp14 and Arg25 residues of IbTX diverges in their interaction with the residues Val283 and Asn260 residues of hSLO3 and the corresponding residues Tyr359 and Ala336 of hSLO1. Knowledge of key residues in the molecular interface of IbTX blockage can help guide and hasten non-hormonal contraceptive development. Our results encourage the use of toxins as scaffolds for specific SLO3 blockers.

METHODS

Atomistic molecular dynamics were implemented on the channel-toxin complexes. To generate the complexes, IbTX was docked to the channels using HADDOCK. CHARMM-GUI was used to generate simulation systems. GROMACS v2023.1 was used to run the simulations for 500 ns in an NPT ensemble at 297.26 K employing the CHARMM36 force field. Binding energy was evaluated by molecular mechanics generalized born surface area (MM/GBSA) with gmxMMPBGBSA.py.

Main methods and tools for peptide development based on protein-protein interactions (PPIs)

Protein-protein interactions (PPIs) regulate essential physiological and pathological processes. Due to their large and shallow binding surfaces, PPIs are often considered challenging drug targets for small molecules. Peptides offer a viable alternative, as they can bind these targets, acting as regulators or mimicking interaction partners. This review focuses on competitive peptides, a class of orthosteric modulators that disrupt PPI formation. We provide a concise yet comprehensive overview of recent advancements in in-silico peptide design, highlighting computational strategies that have improved the efficiency and accuracy of PPI-targeting peptides. Additionally, we examine cutting-edge experimental methods for evaluating PPI-based peptides. By exploring the interplay between computational design and experimental validation, this review presents a structured framework for developing effective peptide therapeutics targeting PPIs in various diseases.

Functional characterization and structural prediction of hypothetical proteins in monkeypox virus and identification of potential inhibitors

The excessive activation of the monkeypox virus (MPXV-Congo_8-156) is linked to various skin and respiratory disorders such as rashes, fluid-filled blisters, swollen lymph nodes and encephalitis (inflammation of the brain), highlighting MPXV-Congo_8-156 as a promising target for drug intervention. Despite the effectiveness of Cidofovir, in inhibiting MPXV activity, its limited ability to penetrate the skin and its strong side effects restrict its application. To address this challenge, we screened 500 compounds capable of penetrating the skin and gastrointestinal tract to identify potent MPXV inhibitors. Various characterization schemes and structural models of MPXV-Congo_8-156 were explored with bioinformatics tools like PROTPARAM, SOPMA, SWISS-MODEL and PROCHECK. Using molecular docking in PyRx, we evaluated the binding affinities of these compounds with MPXV-Congo_8-156 and identified the top five candidates ranging from - 9.2 to - 8.8 kcal/mol. ADMET analysis indicated that all five compounds were safer alternatives, showing no AMES toxicity or carcinogenicity in toxicological assessments. Molecular dynamics (MD) simulations, conducted for 100 ns each, confirmed the docking interactions of the top five compounds alongside the control (Cidofovir), validating their potential as MPXV inhibitors. The compounds with PubChem CID numbers 4061636, 4422538, 3583576, 4856107 and 4800629 demonstrated strong support in terms of root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA) value, hydrogen bond analysis, and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) analysis. Thus, our investigation identified these five compounds as promising inhibitors of MPXV, offering potential therapeutic avenues. However, further in vivo studies are necessary to validate our findings.

Predicting 3D Structures of Lasso Peptides

Lasso peptides (LaPs), characterized by their entangled slipknot-like structures, are a large class of ribosomally synthesized and post-translationally modified peptides (RiPPs), with examples functioning as antibiotics, enzyme inhibitors, and molecular switches. Despite thousands of LaP sequences predicted by bioinformatics, only around 50 distinct LaPs have been structurally characterized in the past 30 years. Existing computational tools, such as AlphaFold2, AlphaFold3 and ESMfold, fail to accurately predict LaP structures due to their irregular scaffold featuring a lariat knot-like fold and the presence of an isopeptide bond. To address this challenge, we developed LassoPred, designed with a classifier to annotate the ring, loop, and tail of an LaP sequence and a constructor to build a 3D structure. Leveraging LassoPred, we predicted 3D structures for 4,749 unique LaP core sequences, creating the largest in silico -predicted lasso peptide structure database to date. LassoPred is publicly available through a web interface (https://lassopred.accre.vanderbilt.edu/) and a command-line tool, supporting future structure-function relationship studies and aiding in the discovery of functional lasso peptides for chemical and biomedical applications.

Long-term editing of brain circuits in mice using an engineered electrical synapse

Electrical signaling across distinct populations of brain cells underpins cognitive and emotional function; however, approaches that selectively regulate electrical signaling between two cellular components of a mammalian neural circuit remain sparse. Here, we engineered an electrical synapse composed of two connexin proteins found in Morone americana (white perch fish) - connexin34.7 and connexin35 - to accomplish mammalian circuit modulation. By exploiting protein mutagenesis, devising a new in vitro system for assaying connexin hemichannel docking, and performing computational modeling of hemichannel interactions, we uncovered a structural motif that contributes to electrical synapse formation. Targeting these motifs, we designed connexin34.7 and connexin35 hemichannels that dock with each other to form an electrical synapse, but not with other major connexins expressed in the mammalian central nervous system. We validated this electrical synapse in vivo using C. elegans and mice, demonstrating that it can strengthen communication across neural circuits composed of pairs of distinct cell types and modify behavior accordingly. Thus, we establish 'Long-term integration of Circuits using connexins' (LinCx) for precision circuit-editing in mammals.

Bacterial XopR subverts RIN4 complex-mediated plant immunity via plasma membrane-associated percolation

Phytobacteria release type 3 effectors (T3Es) abundant in intrinsically disordered regions (IDRs) to undermine plant defenses. How flexible IDRs contribute to T3Es' function in subverting plant immunity remains unclear. Here, we identify a plant plasma membrane (PM)-associated macromolecular condensation mechanism that governs the sophisticated interplay between T3E XopR and the plant's Resistance to Pseudomonas syringae pv. maculicola 1 (RPM1)-interacting protein 4 (RIN4) immune complex. Upon deployment into plants, XopR undergoes PM association, percolation clustering, and spanning networking on the PM, ranging from subnanomolar to tens of nanomolar. This spatiotemporal building of the XopR network enables an efficient manipulation of plant surface immune regulators, including a coiled-coil nucleotide-binding leucine-rich repeat receptor (CNL)-guardee complex with highly disordered RIN4. When XopR hijacks and fluidizes the RIN4-RPM1 condensates, Arabidopsis shows reduced RIN4 phosphorylation and diminished RPM1-activated defense in vivo, consistent with XopR-impaired RIN4 phosphorylation by RPM1-interacting protein kinase (RIPK). Our research illuminates the mechanism underlying the dynamic interplay between bacterial T3Es and plant receptor complex condensates during infection.

Identification of variants in exon 4 of the LDLR gene and assessment of their effects on the produced proteins in saudi women with metabolic syndrome

BACKGROUND

Genetic factors might influence metabolic syndrome (MetS) or any of its components. It was postulated that low density lipoprotein receptor (LDLR) gene variants could play a role in cholesterol hemostasis and the development of MetS. However, the causal-effect relationship between such variants and the development of MetS is not clearly identified or even studied before in Saudi Arabian women. This study aims to identify the variants of LDLR exon-4 in Saudi Arabian women with MetS in comparison to healthy women and to assess the expected effect of amino acids alterations on the structure and functions of the LDLR proteins. A total of 208 female Saudi patients with MetS and 104 controls were included in the study. The exon 4 of LDLR gene was studied by DNA sequencing (Sanger) and structural analysis was performed using Project HOPE software.

RESULTS

Four variants were identified; 2 were missense variants (2.4%; 5/208): (p.D172N and p.D178N) and 2 were nonsense variants (stop gained) (1.44%; 3/208): (p.E140* and p.L135*). Structural analysis of the expected effects of such variants revealed that they might disrupt their interactions with other proteins or biomolecules, additionally, the nonsense variants via expressing a stop codon, these will produce a truncated protein resulting in a defective function of LDL receptor.

CONCLUSIONS

Four variants in the LDLR gene, exon 4 (2 missense and 2 nonsense variants) have been identified and their expected structural effects were assessed in Saudi Arabian women with MetS in Makkah region.

Enlightening the multifarious attributes of the Escherichia coli Sap transport system: a computational perspective

Antimicrobial peptides (AMPs) are majorly utilized by the hosts to clear off the invading bacterial pathogens. The AMPs help in the clearance of bacterial pathogens primarily by disrupting their membrane homeostasis. However, most Gram-negative pathogens have developed multiple machineries, enabling them to resist the action of AMPs. One such machinery is the sensitivity to the antimicrobial peptides (Sap) transport system. The Sap system belongs to the ATP-binding cassette (ABC) transporters and consists of five components, viz. SapABCDF. It is reported that it uptakes AMPs inside the cell that are proteolytically degraded by proteases. In contrast, in Escherichia coli, the Sap (EcSap) transport system was suggested as a putrescine exporter. In this study, with the aid of computational biological approaches, the functional prospects of the EcSap transporter were investigated. The results of this study suggest that the protein EcSapA can bind dipeptides having aromatic amino acids. Further, it can bind to oligopeptides, including AMPs. AMPs such as protamine and protegrin-1 show binding to the protein EcSapA. In addition, the molecule heme shows binding affinity toward the protein EcSapA. In summary, EcSapA seems to be involved in the uptake of a wide range of molecules, such as dipeptides, AMPs and heme. The results of this study can be utilized to design inhibitors targeting the protein SapA, as inhibiting this protein may render the bacterial system sensitive to the attacking AMPs, hence allowing the host machinery to clear off the invading pathogen.

A miniature low-immunogenic platform for the biosynthesis of self-assembling protein nanoparticles

Aims: Previously, to obtain antigen-presenting self-assembling protein nanoparticles (SAPN), we developed a biosynthetic platform combining the self-associating peptide L6KD and the SUMO protein. In the current work, the immunogenic SUMO was replaced with an artificial 30 amino acid long peptide pepA1. Methods: The immunogenic properties of the pepA1-SAPN were tested in mice using the pneumococcal PhtD19 and ovalbumin OVA257-280 antigens in the absence of adjuvants. Results and Conclusions: The updated SAPN showed a 100% seroconversion rate and low immunogenicity of the platform. Given the effective synthesis and improved purification procedure, the pepA1-based miniature platform looks promising for development of vaccines and vehicles for targeted delivery.

Importance of Inter-residue Contacts for Understanding Protein Folding and Unfolding Rates, Remote Homology, and Drug Design

Inter-residue interactions in protein structures provide valuable insights into protein folding and stability. Understanding these interactions can be helpful in many crucial applications, including rational design of therapeutic small molecules and biologics, locating functional protein sites, and predicting protein-protein and protein-ligand interactions. The process of developing machine learning models incorporating inter-residue interactions has been improved recently. This review highlights the theoretical models incorporating inter-residue interactions in predicting folding and unfolding rates of proteins. Utilizing contact maps to depict inter-residue interactions aids researchers in developing computer models for detecting remote homologs and interface residues within protein-protein complexes which, in turn, enhances our knowledge of the relationship between sequence and structure of proteins. Further, the application of contact maps derived from inter-residue interactions is highlighted in the field of drug discovery. Overall, this review presents an extensive assessment of the significant models that use inter-residue interactions to investigate folding rates, unfolding rates, remote homology, and drug development, providing potential future advancements in constructing efficient computational models in structural biology.

Polêto M, Verli H, Almeida VM, Marana SR, Bender A, Godoi BF, Rodrigues VL, da S. Emery F, Trossini GHG. Fragment Screening Reveals Novel Scaffolds against Sirtuin-2-Related Protein 1 from Trypanosoma brucei

Sirtuin-2 (Sir2) is a histone deacetylase recognized as an antitrypanosomal target, yet there is limited knowledge regarding their potent inhibitors. This investigation employs the fragment-based drug discovery (FBDD) framework to identify novel inhibitors against Trypanosoma brucei Sir2-related protein 1. Initially, frequent residue-ligand interactions extracted from the crystallographic structures of human Sir2 and key features of human and parasitic Sir2 active sites were utilized to curate a targeted fragment library. Screening identified ten fragment hits, which introduced nine novel substructures compared to known Sir2 inhibitors. Among these, fragment 1 was the most potent, with an IC50 value of 17.8 μM and a ligand efficiency of 0.41. Further chemical space exploration of 30 compounds from the two most promising hits confirmed fragment 1 as the most potent. This study underscores the effectiveness of FBDD in discovering chemically distinct starting points with favorable ligand efficiency against protein targets in infectious diseases.

Structural and Functional Characterization of Obesumbacterium proteus Phytase: A Comprehensive In-Silico Study

Phytate, also known as myoinositol hexakisphosphate, exhibits anti-nutritional properties and possesses a negative environmental impact. Phytase enzymes break down phytate, showing potential in various industries, necessitating thorough biochemical and computational characterizations. The present study focuses on Obesumbacterium proteus phytase (OPP), indicating its similarities with known phytases and its potential through computational analyses. Structure, functional, and docking results shed light on OPP's features, structural stability, strong and stable interaction, and dynamic conformation, with flexible sidechains that could adapt to different temperatures or specific functions. Root Mean Square fluctuation (RMSF) highlighted fluctuating regions in OPP, indicating potential sites for stability enhancement through mutagenesis. The systematic approach developed here could aid in enhancing enzyme properties via a rational engineering approach. Computational analysis expedites enzyme discovery and engineering, complementing the traditional biochemical methods to accelerate the quest for superior enzymes for industrial applications.

In silico design of an epitope-based vaccine ensemble for fasliolopsiasis

Introduction

Fasciolopsiasis, a food-borne intestinal disease is most common in Asia and the Indian subcontinent. Pigs are the reservoir host, and fasciolopsiasis is most widespread in locations where pigs are reared and aquatic plants are widely consumed. Human infection has been most commonly documented in China, Bangladesh, Southeast Asia, and parts of India. It predominates in school-age children, and significant worm burdens are not uncommon. The causal organism is Fasciolopsis buski, a giant intestinal fluke that infects humans and causes diarrhoea, fever, ascites, and intestinal blockage. The increasing prevalence of medication resistance and the necessity for an effective vaccination make controlling these diseases challenging.

Methods

Over the last decade, we have achieved major advances in our understanding of intestinal fluke biology by in-depth interrogation and analysis of evolving F. buski omics datasets. The creation of large omics datasets for F. buski by our group has accelerated the discovery of key molecules involved in intestinal fluke biology, toxicity, and virulence that can be targeted for vaccine development. Finding successful vaccination antigen combinations from these huge number of genes/proteins in the available omics datasets is the key in combating these neglected tropical diseases. In the present study, we developed an in silico workflow to select antigens for composing a chimeric vaccine, which could be a significant technique for developing a fasciolopsiasis vaccine that prevents the parasite from causing serious harm.

Results and discussion

This chimeric vaccine can now be tested experimentally and compared to other vaccine candidates to determine its potential influence on human health. Although the results are encouraging, additional validation is needed both in vivo and in vitro. Considering the extensive genetic data available for intestinal flukes that has expanded with technological advancements, we may need to reassess our methods and suggest a more sophisticated technique in the future for identifying vaccine molecules.

Virtual screening of targeted acrylamide warheads for identification of covalent inhibitors of Cryptopain, a cysteine protease of Cryptosporidium parvum

Cryptosporidiosis is an infection induced by the single-celled protozoan Cryptosporidium parasite. This parasite commonly infects the intestines of humans and animals, leading to gastrointestinal symptoms such as diarrhea, stomach cramps, nausea, and vomiting. Cryptopain protein, a type of cysteine protease found in the genome of Cryptosporidium parvum plays an important role in cell invasion and its survival. In this study, we mainly focused on the structural validation and reliability of docking aspects of the Cryptopain protein of C. parvum. The best-modeled structure of Cryptopain protein was run in a water environment through a 200 ns Molecular Dynamics (MD) simulation study. We employed a covalent docking scheme to screen suitable inhibitors against our target protein. Furthermore, the reliability of the binding mode for the best possible inhibitors was validated at a 100 ns time frame through a complex MD simulation study. From docking and simulation studies, we found Z3952175270 as a possible inhibitor on the basis of docking score and binding affinity for the possible binding site in the Cryptopain protein. Our findings highlight the potential of targeting Cryptopain protein with specific inhibitors, which could pave the way for the development of novel therapeutic strategies against cryptosporidiosis. This work contributes to the field by providing a deeper understanding of the molecular interactions involved in Cryptopain inhibition, potentially leading to effective treatments for a disease that significantly impacts public health, particularly in immunocompromised individuals and in areas with limited access to clean water.

Identification of Potential Inhibitors of Three NDM Variants of Klebsiella Species from Natural Compounds: A Molecular Docking, Molecular Dynamics Simulation and MM-PBSA Study

BACKGROUND

Klebsiella species have emerged as well-known opportunistic pathogens causing nosocomial infections with β-lactamase-mediated resistance as a prevalent antibiotic resistance mechanism. The discovery and emergence of metallo-β-lactamases, mainly new- Delhi metallo-β-lactamases (NDMs), have increased the threat and challenges in healthcare facilities.

OBJECTIVES

A computational screening was conducted using 570 natural compounds from Dr. Duke's Phytochemical and Ethnobotanical data to discover promising inhibitors for NDM-6, NDM-9, and NDM-23 of the Klebsiella species.

METHODS

Using homology modeling on the Raptor-X web server, the structures of the three NDM variants were predicted. The structures were validated using various computational tools and MD simulation for 50 ns. Lipinski - Vebers' Filter and ADMET Screening were used to screen 570 compounds, followed by docking in Biovia Discovery Studio 2019 using the CDOCKER module. GROMACS was used to simulate the compounds with the highest scores with the proteins for 50 ns. Using the MM-PBSA method and g_mmpbsa tool, binding free energies were estimated and per-residue decomposition analysis was conducted.

RESULTS

The three structures predicted were found stable after the 50 ns MD Simulation run. The compounds Budmunchiamine-A and Rhamnocitrin were found to have the best binding energy towards NDM-6, NDM-9, and NDM-23, respectively. From the results of MD Simulation, MM-PBSA binding free energy calculations, and per-residue decomposition analysis, the Protein-ligand complex of NDM-6 with Budmunchiamine A and NDM-9 with Rhamnocitrin was relatively more stable than the complex of NDM-23 and Rhamnocitrin.

CONCLUSION

The study suggests that Budmunchiamine-A and Rhamnocitrin are potential inhibitors of NDM-6 and NDM-9, respectively, and may pave a path for in-vivo and in-vitro studies in the future.

Beyond AlphaFold2: The Impact of AI for the Further Improvement of Protein Structure Prediction

Protein structure prediction is fundamental to molecular biology and has numerous applications in areas such as drug discovery and protein engineering. Machine learning techniques have greatly advanced protein 3D modeling in recent years, particularly with the development of AlphaFold2 (AF2), which can analyze sequences of amino acids and predict 3D structures with near experimental accuracy. Since the release of AF2, numerous studies have been conducted, either using AF2 directly for large-scale modeling or building upon the software for other use cases. Many reviews have been published discussing the impact of AF2 in the field of protein bioinformatics, particularly in relation to neural networks, which have highlighted what AF2 can and cannot do. It is evident that AF2 and similar approaches are open to further development and several new approaches have emerged, in addition to older refinement approaches, for improving the quality of predictions. Here we provide a brief overview, aimed at the general biologist, of how machine learning techniques have been used for improvement of 3D models of proteins following AF2, and we highlight the impacts of these approaches. In the most recent experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP15), the most successful groups all developed their own tools for protein structure modeling that were based at least in some part on AF2. This improvement involved employing techniques such as generative modeling, changing parameters such as dropout to generate more AF2 structures, and data-driven approaches including using alternative templates and MSAs.

How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology

The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditional Score Networks (NCSNs), and Graph NNs (GNNs) have impacted computer vision, language editing and translation, automated conversation, image generation, and social network management. Proteins can be viewed as texts written with the alphabet of amino acids, as images, or as graphs of interacting residues. Each of these perspectives suggests the use of tools from a different area of deep learning for protein structural biology. Here, I review how CNNs, LLMs, DDPMs/NCSNs, and GNNs have led to major advances in protein structure prediction, inverse folding, protein design, and small molecule design. This review is primarily intended as a deep learning primer for practicing experimental structural biologists. However, extensive references to the deep learning literature should also make it relevant to readers who have a background in machine learning, physics or statistics, and an interest in protein structural biology.

Insight into Protein Engineering: From In silico Modelling to In vitro Synthesis

Protein engineering alters the polypeptide chain to obtain a novel protein with improved functional properties. This field constantly evolves with advanced in silico tools and techniques to design novel proteins and peptides. Rational incorporating mutations, unnatural amino acids, and post-translational modifications increases the applications of engineered proteins and peptides. It aids in developing drugs with maximum efficacy and minimum side effects. Currently, the engineering of peptides is gaining attention due to their high stability, binding specificity, less immunogenic, and reduced toxicity properties. Engineered peptides are potent candidates for drug development due to their high specificity and low cost of production compared with other biologics, including proteins and antibodies. Therefore, understanding the current perception of designing and engineering peptides with the help of currently available in silico tools is crucial. This review extensively studies various in silico tools available for protein engineering in the prospect of designing peptides as therapeutics, followed by in vitro aspects. Moreover, a discussion on the chemical synthesis and purification of peptides, a case study, and challenges are also incorporated.

Design, synthesis, biological evaluations and in silico studies of (Z)-2-(2,4-dioxothiazolidin-5-ylidene)methyl)-2-ethoxyphenyl-alkyl/arylsulfonates as potential α-glucosidase inhibitors

Diabetes mellitus is considered one of the major worldwide health emergencies of the twenty-first century. This work described development, synthesis, and characterization of new (Z)-2-(2,4-dioxothiazolidin-5-ylidene)methyl)-2-ethoxyphenyl-alkyl/aryl-sulfonates. Compounds 7j and 7m were shown to be the most potent among the newly developed (Z)-2-(2,4-dioxothiazolidin-5-ylidene)methyl)-2-ethoxyphenyl-alkyl/aryl-sulfonates after in vitro testing for α-glucosidase inhibitory activity. Following that, an in-vivo disaccharide loading test was performed on these compounds. From the cytotoxicity studies, the most potent substance (7m) was also founded non-toxic. To investigate the binding mechanism and important interactions of α-glucosidase's amino acid residues, docking analyses were completed and binding affinities of the synthesised compounds were observed from -7.1 to 9.6 kcal/mol. To determine the binding stability of the α-glucosidase protein with chemicals 7j and 7m, molecular dynamic simulations were employed. In silico research and prediction studies for absorption, distribution, metabolism, and excretion (ADME) were used to identify the "druggable" pharmacokinetic profiles. In this instance, we developed unique (Z)-2-(2,4-dioxothiazolidin-5-ylidene)methyl)-2-ethoxyphenyl-alkyl/aryl-sulfonates as α-glucosidase inhibitors.

Expression of Random Sequences and de novo Evolved Genes From the Mouse in Human Cells Reveals Functional Diversity and Specificity

Proteins that emerge de novo from noncoding DNA could negatively or positively influence cellular physiology in the sense of providing a possible adaptive advantage. Here, we employ two approaches to study such effects in a human cell line by expressing random sequences and mouse de novo genes that lack homologs in the human genome. We show that both approaches lead to differential growth effects of the cell clones dependent on the sequences they express. For the random sequences, 53% of the clones decreased in frequency, and about 8% increased in frequency in a joint growth experiment. Of the 14 mouse de novo genes tested in a similar joint growth experiment, 10 decreased, and 3 increased in frequency. When individually analysed, each mouse de novo gene triggers a unique transcriptomic response in the human cells, indicating mostly specific rather than generalized effects. Structural analysis of the de novo gene open reading frames (ORFs) reveals a range of intrinsic disorder scores and/or foldability into alpha-helices or beta sheets, but these do not correlate with their effects on the growth of the cells. Our results indicate that de novo evolved ORFs could easily become integrated into cellular regulatory pathways, since most interact with components of these pathways and could therefore become directly subject to positive selection if the general conditions allow this.

WUREN: Whole-modal union representation for epitope prediction

B-cell epitope identification plays a vital role in the development of vaccines, therapies, and diagnostic tools. Currently, molecular docking tools in B-cell epitope prediction are heavily influenced by empirical parameters and require significant computational resources, rendering a great challenge to meet large-scale prediction demands. When predicting epitopes from antigen-antibody complex, current artificial intelligence algorithms cannot accurately implement the prediction due to insufficient protein feature representations, indicating novel algorithm is desperately needed for efficient protein information extraction. In this paper, we introduce a multimodal model called WUREN (Whole-modal Union Representation for Epitope predictioN), which effectively combines sequence, graph, and structural features. It achieved AUC-PR scores of 0.213 and 0.193 on the solved structures and AlphaFold-generated structures, respectively, for the independent test proteins selected from DiscoTope3 benchmark. Our findings indicate that WUREN is an efficient feature extraction model for protein complexes, with the generalizable application potential in the development of protein-based drugs. Moreover, the streamlined framework of WUREN could be readily extended to model similar biomolecules, such as nucleic acids, carbohydrates, and lipids.

Prostruc: an open-source tool for 3D structure prediction using homology modeling

Introduction

Homology modeling is a widely used computational technique for predicting the three-dimensional (3D) structures of proteins based on known templates,evolutionary relationships to provide structural insights critical for understanding protein function, interactions, and potential therapeutic targets. However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.

Methods

Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. Integrating Biopython for sequence alignment, BLAST for template identification, and ProMod3 for structure generation, Prostruc streamlines complex workflows into a user-friendly interface. The tool enables researchers to input protein sequences, identify homologous templates from databases such as the Protein Data Bank (PDB), and generate high-quality 3D structures with minimal computational expertise. Prostruc implements a two-stage vSquarealidation process: first, it uses TM-align for structural comparison, assessing Root Mean Deviations (RMSD) and TM scores against reference models. Second, it evaluates model quality via QMEANDisCo to ensure high accuracy.

Results

The top five models are selected based on these metrics and provided to the user. Prostruc stands out by offering scalability, flexibility, and ease of use. It is accessible via a cloud-based web interface or as a Python package for local use, ensuring adaptability across research environments. Benchmarking against existing tools like SWISS-MODEL,I-TASSER and Phyre2 demonstrates Prostruc's competitive performance in terms of structural accuracy and job runtime, while its open-source nature encourages community-driven innovation.

Discussion

Prostruc is positioned as a significant advancement in homology modeling, making high-quality protein structure prediction more accessible to the scientific community.

Challenge for Deep Learning: Protein Structure Prediction of Ligand-Induced Conformational Changes at Allosteric and Orthosteric Sites

In the realm of biomedical research, understanding the intricate structure of proteins is crucial, as these structures determine how proteins function within our bodies and interact with potential drugs. Traditionally, methods like X-ray crystallography and cryo-electron microscopy have been used to unravel these structures, but they are often challenging, time-consuming and costly. Recently, a breakthrough in computational biology has emerged with the development of deep learning algorithms capable of predicting protein structures based on their amino acid sequences (Jumper, J., et al. Nature 2021, 596, 583. Lane, T. J. Nature Methods 2023, 20, 170. Kryshtafovych, A., et al. Proteins: Structure, Function and Bioinformatics 2021, 89, 1607). This study focuses on predicting the dynamic changes that proteins undergo upon ligand binding, specifically when they bind to allosteric sites, i.e. a pocket different from the active site. Allosteric modulators are particularly important for drug discovery, as they open new avenues for designing drugs that can target proteins more effectively and with fewer side effects (Nussinov, R.; Tsai, C. J. Cell 2013, 153, 293). To study this, we curated a data set of 578 X-ray structures comprised of proteins displaying orthosteric and allosteric binding as well as a general framework to evaluate deep learning-based structure prediction methods. Our findings demonstrate the potential and current limitations of deep learning methods, such as AlphaFold2 (Jumper, J., et al. Nature 2021, 596, 583), NeuralPLexer (Qiao, Z., et al. Nat Mach Intell 2024, 6, 195), and RoseTTAFold All-Atom (Krishna, R., et al. Science 2024, 384, eadl2528) to predict not just static protein structures but also the dynamic conformational changes. Herein we show that predicting the allosteric induce-fit conformation still poses a challenge to deep learning methods as they more accurately predict the orthosteric bound conformation compared to the allosteric induce fit conformation. For AlphaFold2, we observed that conformational diversity, and sampling between the apo and holo state could be increased by modifying the MSA depth, but this did not enhance the ability to generate conformations close to the allosteric induced-fit conformation. To further support advancements in protein structure prediction field, the curated data set and evaluation framework are made publicly available.

Structure of the human TIP60-C histone exchange and acetyltransferase complex

Chromatin structure is a key regulator of DNA transcription, replication and repair1. In humans, the TIP60-EP400 complex (TIP60-C) is a 20-subunit assembly that affects chromatin structure through two enzymatic activities: ATP-dependent exchange of histone H2A-H2B for H2A.Z-H2B, and histone acetylation. In yeast, however, these activities are performed by two independent complexes-SWR1 and NuA4, respectively2,3. How the activities of the two complexes are merged into one supercomplex in humans, and what this association entails for the structure and mechanism of the proteins and their recruitment to chromatin, are unknown. Here we describe the structure of the endogenous human TIP60-C. We find a three-lobed architecture composed of SWR1-like (SWR1L) and NuA4-like (NuA4L) parts, which associate with a TRRAP activator-binding module. The huge EP400 subunit contains the ATPase motor, traverses the junction between SWR1L and NuA4L twice and constitutes the scaffold of the three-lobed architecture. NuA4L is completely rearranged compared with its yeast counterpart. TRRAP is flexibly tethered to NuA4L-in stark contrast to its robust connection to the completely opposite side of NuA4 in yeast4-7. A modelled nucleosome bound to SWR1L, supported by tests of TIP60-C activity, suggests that some aspects of the histone exchange mechanism diverge from what is seen in yeast8,9. Furthermore, a fixed actin module (as opposed to the mobile actin subcomplex in SWR1; ref. 8), the flexibility of TRRAP and the weak effect of extranucleosomal DNA on exchange activity lead to a different, activator-based mode of enlisting TIP60-C to chromatin.

Current Technologies in Snake Venom Analysis and Applications

This comprehensive review explores the cutting-edge advancements in snake venom research, focusing on the integration of proteomics, genomics, transcriptomics, and bioinformatics. Highlighting the transformative impact of these technologies, the review delves into the genetic and ecological factors driving venom evolution, the complex molecular composition of venoms, and the regulatory mechanisms underlying toxin production. The application of synthetic biology and multi-omics approaches, collectively known as venomics, has revolutionized the field, providing deeper insights into venom function and its therapeutic potential. Despite significant progress, challenges such as the functional characterization of toxins and the development of cost-effective antivenoms remain. This review also discusses the future directions of venom research, emphasizing the need for interdisciplinary collaborations and new technologies (mRNAs, cryo-electron microscopy for structural determinations of toxin complexes, synthetic biology, and other technologies) to fully harness the biomedical potential of venoms and toxins from snakes and other animals.

Predictive immunoinformatics reveal promising safety and anti-onchocerciasis protective immune response profiles to vaccine candidates (Ov-RAL-2 and Ov-103) in anticipation of phase I clinical trials

Onchocerciasis (river blindness) is a debilitating tropical disease that causes significant eye and skin damage, afflicting millions worldwide. As global efforts shift from disease management to elimination, vaccines have become crucial supplementary tools. The Onchocerciasis Vaccine for Africa (TOVA) Initiative was established in 2015, to advance at least one vaccine candidate initially targeting onchocerciasis in infants and children below 5 years of age, through Phase I human trials by 2025. Notably, Ov-RAL-2 and Ov-103 antigens have shown great promise during pre-clinical development, however, the overall success rate of vaccine candidates during clinical development remains relatively low due to certain adverse effects and immunogenic limitations. This study, thus, aimed at predicting the safety and immunogenicity of Ov-RAL-2 and Ov-103 potential onchocerciasis vaccine candidates prior to clinical trials. Advanced molecular simulation models and analytical immunoinformatics algorithms were applied to predict potential adverse side effects and efficacy of these antigens in humans. The analyses revealed that both Ov-RAL-2 and Ov-103 demonstrate favourable safety profiles as toxicogenic and allergenic epitopes were found to be absent within each antigen. Also, both antigens were predicted to harbour substantial numbers of a wide range of distinct epitopes (antibodies, cytokines, and T- Cell epitopes) associated with protective immunity against onchocerciasis. In agreement, virtual vaccination simulation forecasted heightened, but sustained levels of primary and secondary protective immune responses to both vaccine candidates over time. Ov-103 was predicted to be non-camouflageable, as it lacked epitopes identical to protein sequences in the human proteome. Indeed, both antigens were able to bind with high affinity and activate the innate immune TLR4 receptor, implying efficient immune recognition. These findings suggest that Ov-RAL-2 and Ov-103 can induce sufficient protective responses through diverse humoral and cellular mechanisms. Overall, our study provides additional layer of evidence for advancing the clinical development of both vaccine candidates against onchocerciasis.

Computational targeting of iron uptake proteins in Covid-19 induced mucormycosis to identify inhibitors via molecular dynamics, molecular mechanics and density function theory studies

Mucormycosis is a concerning invasive fungal infection with difficult diagnosis, high mortality rates, and limited treatment options. Iron availability is crucial for fungal growth that causes this disease. This study aimed to computationally target iron uptake proteins in Rhizopus arrhizus, Lichtheimia corymbifera, and Mucor circinelloides to identify inhibitors, thereby halting fungal growth and intervening in mucormycosis pathogenesis. Seven important iron uptake proteins were identified, modeled, and validated using Ramachandran plots. An in-house antifungal library of ~ 15,401 compounds was screened in molecular docking studies with these proteins. The best small molecule-protein complexes were simulated at 100 ns using Maestro, Schrodinger. Toxicity predictions suggested all six molecules, identified as the best binding compounds to seven proteins, belonged to lower toxicity levels per GHS classification. A molecular mechanics GBSA study for all seven complexes indicated low standard deviations after calculating free binding energies every 10 ns of the 100 ns trajectory. Density functional theory via quantum mechanics approaches highlighted the HOMO, LUMO, and other properties of the six best-bound molecules, revealing their binding capabilities and behaviour. This study sheds light on the molecular mechanisms and protein-ligand interactions, providing a multi-dimensional view towards the use of FDBD01920, FDBD01923, and FDBD01848 as stable antifungal ligands.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00264-7.

ALS-associated C21ORF2 variant disrupts DNA damage repair, mitochondrial metabolism, neuronal excitability and NEK1 levels in human motor neurons

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease leading to motor neuron loss. Currently mutations in > 40 genes have been linked to ALS, but the contribution of many genes and genetic mutations to the ALS pathogenic process remains poorly understood. Therefore, we first performed comparative interactome analyses of five recently discovered ALS-associated proteins (C21ORF2, KIF5A, NEK1, TBK1, and TUBA4A) which highlighted many novel binding partners, and both unique and shared interactors. The analysis further identified C21ORF2 as a strongly connected protein. The role of C21ORF2 in neurons and in the nervous system, and of ALS-associated C21ORF2 variants is largely unknown. Therefore, we combined human iPSC-derived motor neurons with other models and different molecular cell biological approaches to characterize the potential pathogenic effects of C21ORF2 mutations in ALS. First, our data show C21ORF2 expression in ALS-relevant mouse and human neurons, such as spinal and cortical motor neurons. Further, the prominent ALS-associated variant C21ORF2-V58L caused increased apoptosis in mouse neurons and movement defects in zebrafish embryos. iPSC-derived motor neurons from C21ORF2-V58L-ALS patients, but not isogenic controls, show increased apoptosis, and changes in DNA damage response, mitochondria and neuronal excitability. In addition, C21ORF2-V58L induced post-transcriptional downregulation of NEK1, an ALS-associated protein implicated in apoptosis and DDR. In all, our study defines the pathogenic molecular and cellular effects of ALS-associated C21ORF2 mutations and implicates impaired post-transcriptional regulation of NEK1 downstream of mutant C21ORF72 in ALS.

ANO7 African-ancestral genomic diversity and advanced prostate cancer

BACKGROUND

Prostate cancer (PCa) is a significant health burden for African men, with mortality rates more than double global averages. The prostate specific Anoctamin 7 (ANO7) gene linked with poor patient outcomes has recently been identified as the target for an African-specific protein-truncating PCa-risk allele.

METHODS

Here we determined the role of ANO7 in a study of 889 men from southern Africa, leveraging exomic genotyping array PCa case-control data (n = 780, 17 ANO7 alleles) and deep sequenced whole genome data for germline and tumour ANO7 interrogation (n = 109), while providing clinicopathologically matched European-derived sequence data comparative analyses (n = 57). Associated predicted deleterious variants (PDVs) were further assessed for impact using computational protein structure analysis.

RESULTS

Notably rare in European patients, we found the common African PDV p.Ile740Leu (rs74804606) to be associated with PCa risk in our case-control analysis (Wilcoxon rank-sum test, false discovery rate/FDR = 0.03), while sequencing revealed co-occurrence with the recently reported African-specific deleterious risk variant p.Ser914* (rs60985508). Additional findings included a novel protein-truncating African-specific frameshift variant p.Asp789Leu, African-relevant PDVs associated with altered protein structure at Ca2+ binding sites, early-onset PCa associated with PDVs and germline structural variants in Africans (Linear regression models, -6.42 years, 95% CI = -10.68 to -2.16, P-value = 0.003) and ANO7 as an inter-chromosomal PCa-related gene fusion partner in African derived tumours.

CONCLUSIONS

Here we provide not only validation for ANO7 as an African-relevant protein-altering PCa-risk locus, but additional evidence for a role of inherited and acquired ANO7 variance in the observed phenotypic heterogeneity and African-ancestral health disparity.

Structural and biochemical characterization of the C-terminal region of the human RTEL1 helicase

RTEL1 is an essential DNA helicase which plays an important role in various aspects of genome stability, from telomere metabolism to DNA replication, repair and recombination. RTEL1 has been implicated in a number of genetic diseases and cancer development, including glioma, breast, lung and gastrointestinal tumors. RTEL1 is a FeS helicase but, in addition to the helicase core, it comprises a long C-terminal region which includes a number of folded domains connected by intrinsically disordered loops and mediates RTEL1 interaction with factors involved in pivotal cellular pathways. However, information on the architecture and the function of this region is still limited. We expressed and purified a variety of fragments encompassing the folded domains and the unstructured regions. We determined the crystal structure of the second repeat, confirming that it has a fold similar to the harmonin homology domains. SAXS data provide low-resolution information on all the fragments and suggest that the presence of the RING domain affects the overall architecture of the C-terminal region, making the structure significantly more compact. NMR data provide experimental information on the interaction between PCNA and the RTEL1 C-terminal region, revealing a putative low-affinity additional site of interaction. A biochemical analysis shows that the C-terminal region, in addition to a preference for telomeric RNA and DNA G-quadruplexes, has a high affinity for R-loops and D-loops, consistent with the role played by the RTEL1 helicase in homologous recombination, telomere maintenance and preventing replication-transcription conflicts. We further dissected the contribution of each domain in binding different substrates.

Structural analysis of the BisI family of modification dependent restriction endonucleases

The BisI family of restriction endonucleases is unique in requiring multiple methylated or hydroxymethylated cytosine residues within a short recognition sequence (GCNGC), and in cleaving directly within this sequence, rather than at a distance. Here, we report that the number of modified cytosines that are required for cleavage can be tuned by the salt concentration. We present crystal structures of two members of the BisI family, NhoI and Eco15I_Ntd (N-terminal domain of Eco15I), in the absence of DNA and in specific complexes with tetra-methylated GCNGC target DNA. The structures show that NhoI and Eco15I_Ntd sense modified cytosine bases in the context of double-stranded DNA (dsDNA) without base flipping. In the co-crystal structures of NhoI and Eco15I_Ntd with DNA, the internal methyl groups (G5mCNGC) interact with the side chains of an (H/R)(V/I/T/M) di-amino acid motif near the C-terminus of the distal enzyme subunit and arginine residue from the proximal subunit. The external methyl groups (GCNG5mC) interact with the proximal enzyme subunit, mostly through main chain contacts. Surface plasmon resonance analysis for Eco15I_Ntd shows that the internal and external methyl binding pockets contribute about equally to sensing of cytosine methyl groups.

Breaking barriers: pCF10 type 4 secretion system relies on a self-regulating muramidase to modulate the cell wall

Conjugative type 4 secretion systems (T4SSs) are the main driver for the spread of antibiotic resistance genes and virulence factors in bacteria. To deliver the DNA substrate to recipient cells, it must cross the cell envelopes of both donor and recipient bacteria. In the T4SS from the enterococcal conjugative plasmid pCF10, PrgK is known to be the active cell wall degrading enzyme. It has three predicted extracellular hydrolase domains: metallo-peptidase (LytM), soluble lytic transglycosylase (SLT), and cysteine, histidine-dependent amidohydrolases/peptidases (CHAP). Here, we report the structure of the LytM domain and show that its active site is degenerate and lacks the active site metal. Furthermore, we show that only the predicted SLT domain is functional in vitro and that it unexpectedly has a muramidase instead of a lytic transglycosylase activity. While we did not observe any peptidoglycan hydrolytic activity for the LytM or CHAP domain, we found that these domains downregulated the SLT muramidase activity. The CHAP domain was also found to be involved in PrgK dimer formation. Furthermore, we show that PrgK interacts with PrgL, which likely targets PrgK to the rest of the T4SS. The presented data provides important information for understanding the function of Gram-positive T4SSs.IMPORTANCEAntibiotic resistance is a large threat to human health and is getting more prevalent. One of the major contributors to the spread of antibiotic resistance among different bacteria is type 4 secretion systems (T4SS). However, mainly T4SSs from Gram-negative bacteria have been studied in detail. T4SSs from Gram-positive bacteria, which stand for more than half of all hospital-acquired infections, are much less understood. The significance of our research is in identifying the function and regulation of a cell wall hydrolase, a key component of the pCF10 T4SS from Enterococcus faecalis. This system is one of the best-studied Gram-positive T4SSs, and this added knowledge aids in our understanding of horizontal gene transfer in E. faecalis as well as other medically relevant Gram-positive bacteria.

Genetic and in silico analysis of Indian sporadic young onset patient with amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is an old onset devastating neurodegenerative disorder. Young-onset ALS cases especially sporadic ones who are between 25 and 45 years are rarely affected by the disease. Despite the identification of numerous candidate genes associated with ALS, the etiology of the disease remains elusive due to extreme genetic and phenotypic variability. The advent of affordable whole exome sequencing (WES) has opened new avenues for unraveling the disease's pathophysiology better.

METHODS AND RESULTS

We aimed to determine the genetic basis of an Indian-origin, young onset sporadic ALS patient with very rapid deterioration of the disease course without any cognitive decline who was screened for mutations in major ALS candidate genes by WES. Variants detected were reconfirmed by Sanger sequencing. The clinicopathological features were investigated and two heterozygous missense variants were identified: R452W, not previously associated with ALS, present in one of the four conserved C terminal domains in ANXA11 and R208W in SIGMAR1, respectively. Both of these variants were predicted to be damaging by pathogenicity prediction tools and various in silico methods.

CONCLUSION

Our study revealed two potentially pathogenic variants in two ALS candidate genes. The genetic makeup of ALS patients from India has been the subject of a few prior studies, but none of them examined ANXA11 and SIGMAR1 genes so far. These results establish the framework for additional research into the pathogenic processes behind these variations that result in sporadic ALS disease and further our understanding of the genetic makeup of Indian ALS patients.

Structural basis for Mis18 complex assembly and its implications for centromere maintenance

The centromere, defined by the enrichment of CENP-A (a Histone H3 variant) containing nucleosomes, is a specialised chromosomal locus that acts as a microtubule attachment site. To preserve centromere identity, CENP-A levels must be maintained through active CENP-A loading during the cell cycle. A central player mediating this process is the Mis18 complex (Mis18α, Mis18β and Mis18BP1), which recruits the CENP-A-specific chaperone HJURP to centromeres for CENP-A deposition. Here, using a multi-pronged approach, we characterise the structure of the Mis18 complex and show that multiple hetero- and homo-oligomeric interfaces facilitate the hetero-octameric Mis18 complex assembly composed of 4 Mis18α, 2 Mis18β and 2 Mis18BP1. Evaluation of structure-guided/separation-of-function mutants reveals structural determinants essential for cell cycle controlled Mis18 complex assembly and centromere maintenance. Our results provide new mechanistic insights on centromere maintenance, highlighting that while Mis18α can associate with centromeres and deposit CENP-A independently of Mis18β, the latter is indispensable for the optimal level of CENP-A loading required for preserving the centromere identity.

Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis

Tuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette-Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine's physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system's intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine's efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.

Pepper catalase: a broad analysis of its modulation during fruit ripening and by nitric oxide

Catalase is a major antioxidant enzyme located in plant peroxisomes that catalyzes the decomposition of H2O2. Based on our previous transcriptomic (RNA-Seq) and proteomic (iTRAQ) data at different stages of pepper (Capsicum annuum L.) fruit ripening and after exposure to nitric oxide (NO) enriched atmosphere, a broad analysis has allowed us to characterize the functioning of this enzyme. Three genes were identified, and their expression was differentially modulated during ripening and by NO gas treatment. A dissimilar behavior was observed in the protein expression of the encoded protein catalases (CaCat1-CaCat3). Total catalase activity was down-regulated by 50% in ripe (red) fruits concerning immature green fruits. This was corroborated by non-denaturing polyacrylamide gel electrophoresis, where only a single catalase isozyme was identified. In vitro analyses of the recombinant CaCat3 protein exposed to peroxynitrite (ONOO-) confirmed, by immunoblot assay, that catalase underwent a nitration process. Mass spectrometric analysis identified that Tyr348 and Tyr360 were nitrated by ONOO-, occurring near the active center of catalase. The data indicate the complex regulation at gene and protein levels of catalase during the ripening of pepper fruits, with activity significantly down-regulated in ripe fruits. Nitration seems to play a key role in this down-regulation, favoring an increase in H2O2 content during ripening. This pattern can be reversed by the exogenous NO application. While plant catalases are generally reported to be tetrameric, the analysis of the protein structure supports that pepper catalase has a favored quaternary homodimer nature. Taken together, data show that pepper catalase is down-regulated during fruit ripening, becoming a target of tyrosine nitration, which provokes its inhibition.

An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Assembly of the Tn7 targeting complex by a regulated stepwise process

The Tn7 family of transposons is notable for its highly regulated integration mechanisms, including programmable RNA-guided transposition. The targeting pathways rely on dedicated target selection proteins from the TniQ family and the AAA+ adaptor TnsC to recruit and activate the transposase at specific target sites. Here, we report the cryoelectron microscopy (cryo-EM) structures of TnsC bound to the TniQ domain of TnsD from prototypical Tn7 and unveil key regulatory steps stemming from unique behaviors of ATP- versus ADP-bound TnsC. We show that TnsD recruits ADP-bound dimers of TnsC and acts as an exchange factor to release one protomer with exchange to ATP. This loading process explains how TnsC assembles a heptameric ring unidirectionally from the target site. This unique loading process results in functionally distinct TnsC protomers within the ring, providing a checkpoint for target immunity and explaining how insertions at programmed sites precisely occur in a specific orientation across Tn7 elements.

Screening of bioactive compounds from selected mushroom species against putative drug targets in Mycobacterium tuberculosis: a multi-target approach

Mycobacterium tuberculosis (Mtb) is a notorious pathogen that causes one of the highest mortalities globally. Due to a pressing demand to identify novel therapeutic alternatives, the present study aims to focus on screening the putative drug targets and prioritizing their role in antibacterial drug development. The most vital proteins involved in the Biotin biosynthesis pathway and the Lipoarabinomannan (LAM) pathway such as biotin synthase (bioB) and alpha-(1->6)-mannopyranosyltransferase A (mptA) respectively, along with other essential virulence proteins of Mtb were selected as drug targets. Among these, the ones without native structures were modelled and validated using standard bioinformatics tools. Further, the interactions were performed with naturally available lead molecules present in selected mushroom species such as Agaricus bisporus, Pleurotus djamor, Hypsizygus ulmarius. Through Gas Chromatography-Mass Spectrometry (GC-MS), 15 bioactive compounds from the methanolic extract of mushrooms were identified. Further, 4 were selected based on drug-likeness and pharmacokinetic screening for molecular docking analysis against our prioritized targets wherein Benz[e]azulene from Pleurotus djamor illustrated a good binding affinity with a LF rank score of -9.036 kcal mol -1 against nuoM (NADH quinone oxidoreductase subunit M) and could be used as a prospective candidate in order to combat Tuberculosis (TB). Furthermore, the stability of the complex are validated using MD Simulations and subsequently, the binding free energy was calculated using MM-GBSA analysis. Thus, the current in silico analysis suggests a promising role of compounds extracted from mushrooms in tackling the TB burden.

Comparative RNA-seq analysis of Arabidopsis thaliana response to AtPep1 and flg22, reveals the identification of PP2-B13 and ACLP1 as new members in pattern-triggered immunity

In this research, a high-throughput RNA sequencing-based transcriptome analysis technique (RNA-Seq) was used to evaluate differentially expressed genes (DEGs) in the wild type Arabidopsis seedlings in response to AtPep1, a well-known peptide representing an endogenous damage-associated molecular pattern (DAMP), and flg22, a well-known microbe-associated molecular pattern (MAMP). We compared and dissected the global transcriptional landscape of Arabidopsis thaliana in response to AtPep1 and flg22 and could identify shared and unique DEGs in response to these elicitors. We found that while a remarkable number of flg22 up-regulated genes were also induced by AtPep1, 256 genes were exclusively up-regulated in response to flg22, and 328 were exclusively up-regulated in response to AtPep1. Furthermore, among down-regulated DEGs upon flg22 treatment, 107 genes were exclusively down-regulated by flg22 treatment, while 411 genes were exclusively down-regulated by AtPep1. We found a number of hitherto overlooked genes to be induced upon treatment with either flg22 or with AtPep1, indicating their possible involvement general pathways in innate immunity. Here, we characterized two of them, namely PP2-B13 and ACLP1. pp2-b13 and aclp1 mutants showed increased susceptibility to infection by the virulent pathogen Pseudomonas syringae DC3000 and its mutant Pst DC3000 hrcC (lacking the type III secretion system), as evidenced by increased proliferation of the two pathogens in planta. Further, we present evidence that the aclp1 mutant is deficient in ethylene production upon flg22 treatment, while the pp2-b13 mutant is deficient in the production of reactive oxygen species (ROS). The results from this research provide new information for a better understanding of the immune system in Arabidopsis.

Cloning, expression and purification of cellobiohydrolase gene from Caldicellulosiruptor bescii for efficient saccharification of plant biomass

Anthropogenic activities have led to a drastic shift from natural fuels to alternative renewable energy reserves that demand heat-stable cellulases. Cellobiohydrolase is an indispensable member of cellulases that play a critical role in the degradation of cellulosic biomass. This article details the process of cloning the cellobiohydrolase gene from the thermophilic bacterium Caldicellulosiruptor bescii and expressing it in Escherichia coli (BL21) CondonPlus DE3-(RIPL) using the pET-21a(+) expression vector. Multi-alignments and structural modeling studies reveal that recombinant CbCBH contained a conserved cellulose binding domain III. The enzyme's catalytic site included Asp-372 and Glu-620, which are either involved in substrate or metal binding. The purified CbCBH, with a molecular weight of 91.8 kDa, displayed peak activity against pNPC (167.93 U/mg) at 65°C and pH 6.0. Moreover, it demonstrated remarkable stability across a broad temperature range (60-80°C) for 8 h. Additionally, the Plackett-Burman experimental model was employed to assess the saccharification of pretreated sugarcane bagasse with CbCBH, aiming to evaluate the cultivation conditions. The optimized parameters, including a pH of 6.0, a temperature of 55°C, a 24-hour incubation period, a substrate concentration of 1.5% (w/v), and enzyme activity of 120 U, resulted in an observed saccharification efficiency of 28.45%. This discovery indicates that the recombinant CbCBH holds promising potential for biofuel sector.

Hippo and PI5P4K signaling intersect to control the transcriptional activation of YAP

Phosphoinositides are essential signaling molecules. The PI5P4K family of phosphoinositide kinases and their substrates and products, PI5P and PI4,5P2, respectively, are emerging as intracellular metabolic and stress sensors. We performed an unbiased screen to investigate the signals that these kinases relay and the specific upstream regulators controlling this signaling node. We found that the core Hippo pathway kinases MST1/2 phosphorylated PI5P4Ks and inhibited their signaling in vitro and in cells. We further showed that PI5P4K activity regulated several Hippo- and YAP-related phenotypes, specifically decreasing the interaction between the key Hippo proteins MOB1 and LATS and stimulating the YAP-mediated genetic program governing epithelial-to-mesenchymal transition. Mechanistically, we showed that PI5P interacted with MOB1 and enhanced its interaction with LATS, thereby providing a signaling connection between the Hippo pathway and PI5P4Ks. These findings reveal how these two important evolutionarily conserved signaling pathways are integrated to regulate metazoan development and human disease.

Transmembrane protein modulates seizure in epilepsy: evidence from temporal lobe epilepsy patients and mouse models

Transmembrane protein (TMEM230) is located in secretory/recycling vesicles, including synaptic vesicles in neurons. However, the functional relationship between TMEM230 and epilepsy is still a mystery. The aims of this study were to investigate the expression of TMEM230 in patients with temporal lobe epilepsy (TLE) and two different mice models of chronic epilepsy, and to determine the probable roles of TMEM230 in epilepsy. Our results showed that TMEM230 expression was increased in the temporal neocortex of epileptic patients and the hippocampus and cortex of epileptic mice compared with that in the control tissues. Moreover, TMEM230 was mainly expressed in the neurons in both humans and mice epileptic brain. TMEM230 co-localized with glutamate vesicular transporter 1 (VGLUT-1), but not with vesicular γ-aminobutyric acid (GABA) transporter (VGAT). Mechanistically, coimmunoprecipitation confirmed that TMEM230 interacted with VGLUT-1, but not with VGAT in the hippocampus of epileptic mice. Lentivirus mediated overexpression of TMEM230 increased mice susceptibility to epilepsy and behavioural phenotypes of epileptic seizures during the kainite (KA)-induced chronic phase of epileptic seizures and the pentylenetetrazole (PTZ) kindling process, whereas lentivirus-mediated TMEM230 downregulation had the opposite effect. These results shed light on the functions of TMEM230 in neurons, suggesting that TMEM230 may play a critical role in the regulation of epileptic activity via influencing excitatory neurotransmission.

Multi-epitopevaccines, from design to expression; an in silico approach

The development of vaccines against a wide range of infectious diseases and pathogens often relies on multi-epitope strategies that can effectively stimulate both humoral and cellular immunity. Immunoinformatics tools play a pivotal role in designing such vaccines, enhancing immune response potential, and minimizing the risk of failure. This review presents a comprehensive overview of practical tools for epitope prediction and the associated immune responses. These immunoinformatics tools facilitate the selection of epitopes based on parameters such as antigenicity, absence of toxic and allergenic sequences, secondary and tertiary structures, sequence conservation, and population coverage. The chosen epitopes can be tailored for B-cells or T-cells, both of which require further assessments covered in this study. We offer a range of suitable linkers that effectively separate cytotoxic T lymphocyte and helper T lymphocyte epitopes while preserving their functionality. Additionally, we identify various adjuvants for specific purposes. We delve into the evaluation of MHC-epitope interactions, MHC clusters, and the simulation of final constructs through molecular docking techniques. We provide diverse linkers and adjuvants optimized for epitope functions to bolster immune responses through epitope attachment. By leveraging these comprehensive tools, the development of multi-epitope vaccines holds the promise of robust immunity and a significant reduction in experimental costs.

The structural landscape and diversity of Pyricularia oryzae MAX effectors revisited

Magnaporthe AVRs and ToxB-like (MAX) effectors constitute a family of secreted virulence proteins in the fungus Pyricularia oryzae (syn. Magnaporthe oryzae), which causes blast disease on numerous cereals and grasses. In spite of high sequence divergence, MAX effectors share a common fold characterized by a ß-sandwich core stabilized by a conserved disulfide bond. In this study, we investigated the structural landscape and diversity within the MAX effector repertoire of P. oryzae. Combining experimental protein structure determination and in silico structure modeling we validated the presence of the conserved MAX effector core domain in 77 out of 94 groups of orthologs (OG) identified in a previous population genomic study. Four novel MAX effector structures determined by NMR were in remarkably good agreement with AlphaFold2 (AF2) predictions. Based on the comparison of the AF2-generated 3D models we propose a classification of the MAX effectors superfamily in 20 structural groups that vary in the canonical MAX fold, disulfide bond patterns, and additional secondary structures in N- and C-terminal extensions. About one-third of the MAX family members remain singletons, without strong structural relationship to other MAX effectors. Analysis of the surface properties of the AF2 MAX models also highlights the high variability within the MAX family at the structural level, potentially reflecting the wide diversity of their virulence functions and host targets.

A Multi-epitope Subunit Vaccine Identification and Development Against Scrub Typhus (Orientia tsutsugamushi) Using Immunoinformatics Approaches

Background The pathogen Orientia tsutsugamushi, which causes scrub typhus, is rapidly spreading throughout the tropics. As a measure to improve public health, the development of a vaccine for human use is essential. Scrub typhus is listed as one of the underdiagnosed and underreported febrile infections. This vector-borne zoonotic infection appears as eschar on the patient's skin. Methods Immunoinformatics was employed to predict the multi-epitope subunit vaccine that will activate both B and T cells. The final vaccine includes lipoprotein LprA as an adjuvant at the N-terminus along with B-cell, helper T lymphocyte (HTL), and cytotoxic T lymphocyte (CTL)-binding epitopes to boost immunogenicity. Assessing the vaccine's physiochemistry demonstrates that it is both antigenic and non-allergic. The vaccine structure was developed, enhanced, confirmed, and disulfide-engineered to provide the best possible model. Using molecular docking, the interaction of the produced vaccine with toll-like receptor 2 (TLR2) was analyzed, and the vaccine-receptor complex was stabilized by molecular dynamics (MD) simulation. According to in silico cloning, Escherichia coli can efficiently produce the recommended vaccine. Additionally, the efficacy of the in silico-developed vaccine must be evaluated in an in vitro and in vivo experiment. Results The developed vaccine successfully stimulates cellular and humoral immune responses. The vaccine, which has three B-cell epitopes, three HCL epitopes, and nine CTL epitopes, can bind firmly to immunological receptors. Dynamic investigations of the vaccine-receptor complex show a strong interaction and stable conformation. Conclusion In this study, the vaccine candidate demonstrated strong antigenicity, stability, and solubility while also being non-allergenic to host cells. The vaccine candidate's stability with the TLR2 immune receptor is established by binding studies, and in silico cloning verifies efficient and stable expression in the bacterial system.

Putative pseudolysogeny-dependent phage gene implicated in the superinfection resistance of Cutibacterium acnes

Objectives: Cutibacterium acnes, formerly Propionibacterium acnes, is a bacterial species characterized by tenacious acne-contributing pathogenic strains. Therefore, bacteriophage therapy has become an attractive treatment route to circumvent issues such as evolved bacterial antibiotic resistance. However, medical and commercial use of phage therapy for C. acnes has been elusive, necessitating ongoing exploration of phage characteristics that confer bactericidal capacity. Methods: A novel phage (Aquarius) was isolated and analyzed. Testing included genomic sequencing and annotation, electron microscopy, patch testing, reinfection assays, and qPCR to confirm pseudolysogeny and putative superinfection exclusion (SIE) protein expression. Results: Given a superinfection-resistant phenotype was observed, reinfection assays and patch tests were performed, which confirmed the re-cultured bacteria were resistant to superinfection. Subsequent qPCR indicated pseudolysogeny was a concomitantly present phenomenon. Phage genomic analysis identified the presence of a conserved gene (gp41) with a product containing Ltp family-like protein signatures which may contribute to phage-mediated bacterial superinfection resistance (SIR) in a pseudolysogeny-dependent manner. qPCR was performed to analyze and roughly quantify gp41 activity, and mRNA expression was high during infection, implicating a role for the protein during the phage life cycle. Conclusions: This study confirms that C. acnes bacteria are capable of harboring phage pseudolysogens and suggests that this phenomenon plays a role in bacterial SIR. This mechanism may be conferred by the expression of phage proteins while the phage persists within the host in the pseudolysogenic state. This parameter must be considered in future endeavors for efficacious application of C. acnes phage-based therapeutics.