CABS-flex 2.0: a web server for fast simulations of flexibility of protein structures

Exploring staphylococcal superantigens to design a potential multi-epitope vaccine against Staphylococcus aureus: an in-silico reverse vaccinology approach

Staphylococcus aureus is a horrifying bacteria capable of causing millions of deaths yearly across the globe. A major contribution to the success of S. aureus as an ESKAPE pathogen is the abundance of virulence factors that can manipulate the innate and adaptive immune system of the individual. Currently, no vaccine is available to treat S. aureus-mediated infections. In this study, we present in-silico approaches to design a stable, safe and immunogenic vaccine that could help to control the infections associated with the bacteria. Three vital pathogenic secreted toxins of S. aureus, such as staphylococcal enterotoxin A (SEA), staphylococcal enterotoxin B (SEB), Toxic-shock syndrome toxin (TSST-1), were selected using the reverse vaccinology approach to design the multi-epitope vaccine (MEV). Linear B-lymphocyte, cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes were predicted from these selected proteins. For designing the multi-epitope vaccine (MEV), B-cell epitopes were joined with the KK linker, CTL epitopes were joined with the AAY linker, and HTL epitopes were joined with the GPGPG linker. Finally, to increase the immune response to the vaccine, a human β-defensin-3 (hBD-3) adjuvant was added to the N-terminus of the MEV construct. The final MEV was found to be antigenic and non-allergen in nature. In-silico immune simulation and cloning analysis predicted the immune-stimulating potential of the designed MEV construct along with the cloning feasibility in the pET28a(+) vector with the E. coli expression system. This immunoinformatics study provides a platform for designing a suitable, safe and effective vaccine against S. aureus.Communicated by Ramaswamy H. Sarma.

Phytocompounds From Edible Oil Seeds Target Hub Genes To Control Breast Cancer

Breast cancer is one of the most commonly diagnosed cancers in woman which accounts for more than 1 in 10 new cancers in the entire world. The recently found four new potential hub genes that show a strong expression in breast cancer are CCNA2, CCNB1, MAD2L1, and RAD51. Nowadays, food habits and lifestyle of an individual are one of the factors for causing cancers. Consumption of seeds on a regular basis is the key factor for leading a good health. Sesame seeds and Sunflower seeds are few examples of cancer fighting seeds. Sesame (Sesamum indicum) is one of the earliest oil seed plant with various phytocompounds present which include lignans, tocopherols, phenolics, polyunsaturated fatty acids, and phytosterols. Sunflower (Helianthus annuus L.) is primarily harvested as an oil seed plant with various phytocompounds present which include flavonoids, phenolic acids, tocopherols, and vitamin B3. These are the few seeds that help women to prevent and also to fight against Breast cancer with its potential anti-cancer activity. The main objective of the current study is to identify the potential phytocompounds present in the cancer fighting seeds using molecular docking and dynamic simulation approach which can further help pharmaceuticals industries in producing targeted drugs against breast cancer hub genes as well as food industries in producing products combining the potential phytocompounds present in the seeds.

Assessing chemical hazard and unraveling binding affinity of priority pollutants to lignin modifying enzymes for environmental remediation

Lignin-modifying enzymes (LMEs) are impactful biocatalysts in environmental remediation applications. However, LMEs-assisted experimental degradation neglects the molecular basis of pollutant degradation. Furthermore, throughout the remediation process, the inherent hazards of environmental pollutants remain untapped for in-depth toxicological endpoints. In this investigation, a predictive toxicological framework and a computational framework adopting LMEs were employed to assess the hazards of Priority Pollutants (PP) and its possible LMEs-assisted catalytic screening. The potential hazardous outcomes of PP were assessed using Quantitative structure-activity relationship (QSARs)-based techniques including Toxtree, ECOSAR, and T.E.S.T. tools. Toxicological findings revealed positive outcomes in a multitude of endpoints for all PP. The PP compound 2,3,7,8-TCDD (dioxin) was found to exhibit the lowest concentration of aquatic toxicity implementing aquatic model systems; LC₅₀ as 0.01, 0.01, 0.04 (mg L^-1) for Fish (96 H), Daphnid (48 H), Green algae (96 H) respectively. T.E.S.T. results revealed that chloroform, and 2-chlorophenol both seem to be developmental toxicants. Subsequently, LMEs-assisted docking procedure was employed in predictive mitigation of PP. The docking approach as predicted degradation revealed the far lowest docking energy score for Versatile peroxidase (VP)- 2,3,7,8-TCDD docked complex with a binding energy of -9.2 (kcal mol^-1), involved PHE-46, PRO-139, PRO-141, ILE-148, LEU-165, HIS-169, LEU-228, MET-262, and MET-265 as key interacting amino acid residues. Second most ranked but lesser than VP, Lignin peroxidase (LiP)- 2,3,7,8-TCDD docked complex exhibited a rather lower binding affinity score (-8.8 kcal mol^-1). Predictive degradation screening employing comparative docking revealed varying binding affinities, portraying that each LMEs member has independent feasibility to bind PP as substrate. Predictive findings endorsed the hazardous nature of associated PP in a multitude of endpoints, which could be attenuated by undertaking LMEs as a predictive approach to protect the environment and implement it in regulatory considerations.

Analysis of critical protein-protein interactions of SARS-CoV-2 capping and proofreading molecular machineries towards designing dual target inhibitory peptides

In recent years, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as the cause of the coronavirus disease (COVID-19) global pandemic, and its variants, especially those with higher transmissibility and substantial immune evasion, have highlighted the imperative for developing novel therapeutics as sustainable solutions other than vaccination to combat coronaviruses (CoVs). Beside receptor recognition and virus entry, members of the SARS-CoV-2 replication/transcription complex are promising targets for designing antivirals. Here, the interacting residues that mediate protein-protein interactions (PPIs) of nsp10 with nsp16 and nsp14 were comprehensively analyzed, and the key residues' interaction maps, interaction energies, structural networks, and dynamics were investigated. Nsp10 stimulates both nsp14's exoribonuclease (ExoN) and nsp16's 2'O-methyltransferase (2'O-MTase). Nsp14 ExoN is an RNA proofreading enzyme that supports replication fidelity. Nsp16 2'O-MTase is responsible for the completion of RNA capping to ensure efficient replication and translation and escape from the host cell's innate immune system. The results of the PPIs analysis proposed crucial information with implications for designing SARS-CoV-2 antiviral drugs. Based on the predicted shared protein-protein interfaces of the nsp16-nsp10 and nsp14-nsp10 interactions, a set of dual-target peptide inhibitors was designed. The designed peptides were evaluated by molecular docking, peptide-protein interaction analysis, and free energy calculations, and then further optimized by in silico saturation mutagenesis. Based on the predicted evolutionary conservation of the interacted target residues among CoVs, the designed peptides have the potential to be developed as dual target pan-coronavirus inhibitors.

Exploring the pharmacological aspects of natural phytochemicals against SARS-CoV-2 Nsp14 through an in silico approach

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), possesses an important bifunctional nonstructural protein (nsp14) with a C-terminal N7-methyltransferase (N7-MTase) domain and an N-terminal domain with exoribonuclease (ExoN) activity that is required for maintaining high-fidelity viral replication. Viruses use the error-prone replication mechanism, which results in high mutation rates, to adapt quickly to stressful situations. The efficiency with which nsp14 removes mismatched nucleotides due to the presence of ExoN activity protects viruses from mutagenesis. We investigated the pharmacological role of the phytochemicals (Baicalein, Bavachinin, Emodin, Kazinol F, Lycorine, Sinigrin, Procyanidin A2, Tanshinone IIA, Tanshinone IIB, Tomentin A, and Tomentin E) against the highly conserved nsp14 protein using docking-based computational analyses in search of new potential natural drug targets. The selected eleven phytochemicals failed to bind the active site of N7-Mtase in the global docking study, while the local docking study identified the top five phytochemicals with high binding energy scores ranging from - 9.0 to - 6.4 kcal/mol. Procyanidin A2 and Tomentin A showed the highest docking score of - 9.0 and - 8.1 kcal/mol, respectively. Local docking of isoform variants was also conducted, yielding the top five phytochemicals, with Procyanidin A1 having the highest binding energy value of - 9.1 kcal/mol. The phytochemicals were later tested for pharmacokinetics and pharmacodynamics analysis for Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) which resulted in choosing Tomentin A as a potential candidate. The molecular dynamics simulations studies of nsp14 revealed significant conformational changes upon complex formation with the identified compound, implying that these phytochemicals could be used as safe nutraceuticals which will impart long-term immunological competence in the human population against CoVs.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00143-7.

Clinically significant findings of high-risk mutations in human SLC29A4 gene associated with diabetes mellitus type 2 in Pakistani population

This study conducted an in-depth analysis combining computational and experimental verifications of the deleterious missense mutations associated with the SLC29A4 protein. The functional annotation of the non-synonymous single nucleotide polymorphism (nsSNPs), followed by structure-function analysis, revealed 13 single nucleotide polymorphisms (SNP) as the most damaging. Among these, six mutants P429T/S, L144S, M108V, N86H, and V79E, were predicted as structurally and functionally damaging by protein stability analysis. Also, these variants are located at evolutionary conserved regions, either buried, contributing to the structural damage, or exposed, causing functional changes in the protein. These mutants were further taken for molecular docking studies. When verified via experimental analysis, the SNPs M108V (rs149798710), N86H (rs151039853), and V79E (rs17854505) showed an association with type 2 diabetes mellitus (T2DM). Minor allele frequency for rs149798710 (A > G) was 0.23 in controls, 0.29 in metformin responders, 0.37 in metformin non-responder, for rs151039853 (A > C) was 0.21 in controls, 0.28 in metformin responders, 0.36 in metformin non-responder and for rs17854505 (T > A) was 0.20 in controls, 0.25 in metformin responders, 0.37 in metformin non-responder. Hence, this study concludes that SLC29A4 M108V (rs149798710), N86H (rs151039853), and V79E (rs17854505) polymorphisms were associated with the increased risk of T2DM as well as with the increased risk towards the failure of metformin therapeutic response in T2DM patients of Pakistan. Communicated by Ramaswamy H. Sarma.

Exploring novel and potent molecules for disrupting DEPTOR-mTOR interaction through structure-steered screening, extra-exactitude molecular docking, prime binding free energy estimation and voguish molecular dynamics

Dep domain containing mTOR interacting protein (DEPTOR) has critical implications in the development and progression of human malignancies. Increased expression of DEPTOR promotes the growth of tumor cells by inhibiting the mTORC1, which alleviates the negative feedback inhibition by mTORC1 downstream target S6Ks on PI3K/AKT pathway thereby promotes cell survival and prevents apoptosis. This clearly suggests that targetting DEPTOR-mTOR interactions through small molecules may prove as an effective strategy for circumventing distinct cancers. In this study, we employed a top-down approach for finding three novel molecules which may prove effective in disrupting Deptor-mTOR interaction. Following DEPTOR modelling and validation we performed grid-directed structure-based screening by specifying the residues of DEPTOR known to interact with mTOR. A library of 10,000 protein-protein disrupting molecules was screened against the defined region of DEPTOR. From the screened molecules, 30 molecules with highest binding affinity were chosen for molecular docking. Thirty (30) extra-precision molecular docking experiments and 30 molecular mechanics generalized born surface area (MMGBSA) assays were performed. Following this top 10 molecules in terms of binding affinity were selected and the interaction profile of their corresponding docked files was generated. The top three molecules were finally selected after taking all the three parameters including docking score, binding energy value and interaction profile into consideration. For atomistic insights regarding DEPTOR-topmost hit interactions, molecular dynamics was performed for 100 ns. This molecule after further evaluation may prove as promising candidate for anticancer therapy.Communicated by Ramaswamy H. Sarma.

Molecular insights into MYO3A kinase domain variants explain variability in both severity and progression of DFNB30 hearing impairment

Hereditary hearing impairment (HI) is a common disease with the highest incidence among sensory defects. Several genes have been identified to affect stereocilia structure causing HI, including the unconventional myosin3A. Interestingly, we noticed that variants in MYO3A gene have been previously found to cause variable HI onset and severity. Using clinical exome sequencing, we identified a novel pathogenic variant p.(Lys50Arg) in the MYO3A kinase domain (MYO3A-KD). Previous in vitro studies supported its damaging effect as a 'kinase-dead' mutant. We further analyzed this variation through molecular dynamics which predicts that changes in flexibility of MYO3A structure would influence the protein-ATP binding properties. This Lys50Arg mutation segregated with congenital profound non-syndromic HI. To better investigate this variability, we collected previously identified MYO3A-KDs variants, p.(Tyr129Cys), p.(His142Gln) and p.(Pro189Thr), and built both wild type and mutant 3 D MYO3A-KD models to assess their impact on the protein structure and function. Our results suggest that KD mutations could either cause a congenital profound form of HI, when particularly affecting the kinase activity and preventing the auto-phosphorylation of the motor, or a late onset and progressive form, when partially or completely inactivating the MYO3A protein. In conclusion, we report a novel pathogenic variant affecting the ATP-binding site within the MYO3A-KD causing congenital profound HI. Through computational approaches we provide a deeper understanding on the correlation between the effects of MYO3A-KD mutations and the variable hearing phenotypes. To the best of our knowledge this is the first study to correlate mutations' genotypes with the variable phenotypes of DFNB30.Communicated by Ramaswamy H. Sarma.

Identification of intrinsically disordered regions in hub genes of acute myeloid leukemia: A bioinformatics approach

Acute myeloid leukemia (AML) is the most common acute leukemia in adults. Over the past decades, there has been a great challenge in the treatment of AML. A combination of gene expression profiling with computational approaches can lead to the identification of hub genes in AML. However, it is important to study the structure of these hub genes considering their importance in the protein-protein interaction (PPI) network of specific cancer. In this study, we designed an integrated method to analyze the presence of intrinsically disordered regions (IDRs) in selected hub genes of AML. A gene expression profile of AML was obtained from Gene Expression Omnibus (GEO) database. Further analysis identified differentially expressed genes (DEGs) in AML. Additionally, the top 15 hub genes following construction and analysis of the PPI network of DEGs were selected. Validation of hub genes revealed that there is a reverse relationship between overexpression of FLT3, PPBP, and PF4 genes and the survival of AML patients. Based on IDRs investigation, FLT3 and PF4 are partially disordered, while PPBP is mostly disordered. Through clustering the network into structural modules, we identified two important modules in the PPI network of DEGs that showed the important position of PPBP in module 1. Based on further analysis of protein flexibility and its important role in biological processes, we suggest that PPBP can be considered as a potential drug target in AML.

Immunoinformatics design of multi-epitope peptide-based vaccine against Haemophilus influenzae strain using cell division protein

Haemophilus influenzae is a pathogen that causes invasive bacterial infections in humans. The highest prevalence lies in both young children and adults. Generally, there are no vaccines available that target all the strains of Haemophilus influenzae. Hence, the purpose of this research is to employ bioinformatics and immunoinformatics approaches to design a Multi-Epitope Vaccine candidate employing the pathogenic cell division protein FtsN that specifically combat all the Haemophilus influenzae strains. The current research focuses on developing subunit vaccine in contrast to vaccines generated from the entire pathogen. This will be accomplished by combining multiple bioinformatics and immunoinformatics approaches. As a result, prospective T cells (helper T lymphocyte and cytotoxic T lymphocytes) and B cells epitopes were investigated. The human leukocyte antigen allele having strong associations with the antigenic and overlapping epitopes were chosen, with 70% of the total coverage of the world population. To construct a linked vaccine design, multiple linkers were used. To increase the immunogenic profile, an adjuvant was linked using EAAAK linker. The final vaccine construct with 149 amino acids was obtained after adjuvants and linkers were added. The developed Multi-Epitope Vaccine has a high antigenicity as well as viable physiochemical features. The 3D conformation was modeled and undergoes refinement and validation using bioinformatics methods. Furthermore, protein-protein molecular docking analysis was performed to predict the effective binding poses of Multi-Epitope Vaccine with the Toll-like receptor 4 protein. Besides, vaccine underwent the codon translational optimization and computational cloning to verify the reliability and proper Multi-Epitope Vaccine expression. In addition, it is necessary to conduct experiments and research in the laboratory to demonstrate that the vaccine that has been developed is immunogenic and protective.

Identification of potential candidate vaccines against Mycobacterium ulcerans based on the major facilitator superfamily transporter protein

Buruli ulcer is a neglected tropical disease that is characterized by non-fatal lesion development. The causative agent is Mycobacterium ulcerans (M. ulcerans). There are no known vectors or transmission methods, preventing the development of control methods. There are effective diagnostic techniques and treatment routines; however, several socioeconomic factors may limit patients' abilities to receive these treatments. The Bacillus Calmette-Guérin vaccine developed against tuberculosis has shown limited efficacy, and no conventionally designed vaccines have passed clinical trials. This study aimed to generate a multi-epitope vaccine against M. ulcerans from the major facilitator superfamily transporter protein using an immunoinformatics approach. Twelve M. ulcerans genome assemblies were analyzed, resulting in the identification of 11 CD8+ and 7 CD4+ T-cell epitopes and 2 B-cell epitopes. These conserved epitopes were computationally predicted to be antigenic, immunogenic, non-allergenic, and non-toxic. The CD4+ T-cell epitopes were capable of inducing interferon-gamma and interleukin-4. They successfully bound to their respective human leukocyte antigens alleles in in silico docking studies. The expected global population coverage of the T-cell epitopes and their restricted human leukocyte antigens alleles was 99.90%. The population coverage of endemic regions ranged from 99.99% (Papua New Guinea) to 21.81% (Liberia). Two vaccine constructs were generated using the Toll-like receptors 2 and 4 agonists, LprG and RpfE, respectively. Both constructs were antigenic, non-allergenic, non-toxic, thermostable, basic, and hydrophilic. The DNA sequences of the vaccine constructs underwent optimization and were successfully in-silico cloned with the pET-28a(+) plasmid. The vaccine constructs were successfully docked to their respective toll-like receptors. Molecular dynamics simulations were carried out to analyze the binding interactions within the complex. The generated binding energies indicate the stability of both complexes. The constructs generated in this study display severable favorable properties, with construct one displaying a greater range of favorable properties. However, further analysis and laboratory validation are required.

Immuno-informatics profiling of monkeypox virus cell surface binding protein for designing a next generation multi-valent peptide-based vaccine

Monkeypox is a viral etiological agent with hallmarks analogous to those observed in smallpox cases in the past. The ongoing outbreak of Monkeypox viral infection is becoming a global health problem. Multi-valent peptide based next generation vaccines provides us a promising solution to combat these emerging infectious diseases by eliciting cell-mediated and humoral immune response. Considering the success rate of subtractive proteomics pipeline and reverse vaccinology approach, in this study, we have developed a novel, next-generation, multi-valent, in silico peptide based vaccine construct by employing cell surface binding protein. After analyzing physiochemical and biological properties of the selected target, the protein was subjected to B cell derived T cell epitope mapping. Iterative scrutinization lead to the identification of two highly antigenic, virulent, non-allergic, non-toxic, water soluble, and Interferon-gamma inducer epitopes i.e. HYITENYRN and TTSPVRENY. We estimated that the shortlisted epitopes for vaccine construction, roughly correspond to 99.74% of the world’s population. UK, Finland and Sweden had the highest overall population coverage at 100% which is followed by Austria (99.99%), Germany (99.99%), France (99.98%), Poland (99.96), Croatia (99.93), Czech Republic (99.87%), Belgium (99.87), Italy (99.86%), China (97.83%), India (97.35%) and Pakistan (97.13%). The designed vaccine construct comprises of 150 amino acids with a molecular weight of 16.97242 kDa. Molecular docking studies of the modelled MEMPV (Multi-epitope Monkeypox Vaccine) with MHC I (PDB ID: 1I1Y), MHC II (PDB ID: 1KG0), and other immune mediators i.e. toll like receptors TLR3 (PDB ID: 2A0Z), and TLR4 (PDB ID: 4G8A) revealed strong binding affinity with immune receptors. Host immune simulation results predicted that the designed vaccine has strong potency to induce immune responses against target pathogen in the form of cellular and antibody-dependent immunity. Our findings suggest that the hypothesized vaccine candidate can be utilized as a potential therapeutic against Monkeypox however experimental study is required to validate the results and safe immunogenicity.

Computational approach to attenuate virulence of Pseudomonas aeruginosa through bioinspired silver nanoparticles

In this study we aim to investigate the computational docking approach of biofabricated silver nanoparticles against P. aeruginosa virulent exoenzymes, such as ExoS and ExoY. Therefore, the synthesis and characterization of biofabricated silver nanoparticles using Piper betle leaves (Pb-AgNPs) were carried out. The surface topology and functional group attachment on the surface of Pb-AgNPs were analyzed using UV-visible spectroscopy, Scanning Electron Microscopy, Fourier Transformed Infrared Spectroscopy (FTIR), and X-Ray Diffraction. The FTIR analysis revealed that the synthesized silver nanoparticles were capped with P. betle phytochemicals importantly Eugenol and Hydroxychavicol. These are the major bioactive compounds present in P. betle leaves; therefore, computational docking of Eugenol-conjugated AgNPs (PbEu-AgNPs) and Hydroxychavicol-conjugated AgNPs (PbHy-AgNPs) against ExoS and ExoY was performed. The active residues of PbEu-AgNPs and PbHy-AgNPs interacted with the active site of ExoS and ExoY exoenzymes. Biofabricated AgNP-mediated inhibition of these virulent exoenzymes blocked the adverse effect of P. aeruginosa on the host cell. The computational analysis provides new approach into the design of biofabricated AgNPs as promising anti-infective nanomedicine agents.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03367-0.

Designing a novel chimeric multi-epitope vaccine against Burkholderia pseudomallei, a causative agent of melioidosis

Burkholderia pseudomallei, a gram-negative soil-dwelling bacterium, is primarily considered a causative agent of melioidosis infection in both animals and humans. Despite the severity of the disease, there is currently no licensed vaccine on the market. The development of an effective vaccine against B. pseudomallei could help prevent the spread of infection. The purpose of this study was to develop a multi-epitope-based vaccine against B. pseudomallei using advanced bacterial pan-genome analysis. A total of four proteins were prioritized for epitope prediction by using multiple subtractive proteomics filters. Following that, a multi-epitopes based chimeric vaccine construct was modeled and joined with an adjuvant to improve the potency of the designed vaccine construct. The structure of the construct was predicted and analyzed for flexibility. A population coverage analysis was performed to evaluate the broad-spectrum applicability of B. pseudomallei. The computed combined world population coverage was 99.74%. Molecular docking analysis was applied further to evaluate the binding efficacy of the designed vaccine construct with the human toll-like receptors-5 (TLR-5). Furthermore, the dynamic behavior and stability of the docked complexes were investigated using molecular dynamics simulation, and the binding free energy determined for Vaccine-TLR-5 was delta total -168.3588. The docking result revealed that the vaccine construct may elicit a suitable immunological response within the host body. Hence, we believe that the designed in-silico vaccine could be helpful for experimentalists in the formulation of a highly effective vaccine for B. pseudomallei.

Predicted Structure and Functions of the Prototypic Alphaherpesvirus Herpes Simplex Virus Type-1 UL37 Tegument Protein

The alphaherpesvirus UL37 tegument protein is a highly conserved, multi-functional protein. Mutagenesis analysis delineated the UL37 domains necessary for retrograde transport and viral replication. Specifically, the amino-terminal 480 amino acids are dispensable for virus replication in epithelial cell culture, but it is unknown whether this amino-terminal deletion affects UL37 structure and intracellular transport in epithelial cells and neurons. To investigate the structure and function of UL37, we utilized multiple computational approaches to predict and characterize the secondary and tertiary structure and other functional features. The structure of HSV-1 UL37 and Δ481N were deduced using publicly available predictive algorithms. The predicted model of HSV-1 UL37 is a stable, multi-functional, globular monomer, rich in alpha helices, with unfolded regions within the linker and the C-tail domains. The highly flexible C-tail contains predicted binding sites to the dynein intermediate chain, as well as DNA and RNA. Predicted interactions with the cytoplasmic surface of the lipid membrane suggest UL37 is a peripheral membrane protein. The Δ481N truncation did not alter the predicted structure of the UL37 C-terminus protein and its predicted interaction with dynein. We validated these models by examining the replication kinetics and transport of the Δ481N virus toward the nuclei of infected epithelial and neuronal cells. The Δ481N virus had substantial defects in virus spread; however, it exhibited no apparent defects in virus entry and intracellular transport. Using computational analyses, we identified several key features of UL37, particularly the flexible unstructured tail; we then demonstrated that the UL37 C-terminus alone is sufficient to effectively transport the virus towards the nucleus of infected epithelial and neuronal cells.

Identification of potential inhibitory analogs of metastasis tumor antigens (MTAs) using bioactive compounds: revealing therapeutic option to prevent malignancy

The deeper understanding of metastasis phenomenon and detection of drug targets could be a potential approach to minimize cancer mortality. In this study, attempts were taken to unmask novel therapeutics to prevent metastasis and cancer progression. Initially, we explored the physiochemical, structural and functional insights of three metastasis tumor antigens (MTAs) and evaluated some plant-based bioactive compounds as potent MTA inhibitors. From 50 plant metabolites screened, isoflavone, gingerol, citronellal and asiatic acid showed maximum binding affinity with all three MTA proteins. The ADME analysis detected no undesirable toxicity that could reduce the drug likeness properties of top plant metabolites. Moreover, molecular dynamics studies revealed that the complexes were stable and showed minimum fluctuation at molecular level. We further performed ligand-based virtual screening to identify similar drug molecules using a large collection of 376,342 compounds from DrugBank. The results suggested that several structural analogs (e.g., tramadol, nabumetone, DGLA and hydrocortisone) may act as agonist to block the MTA proteins and inhibit cancer progression at early stage. The study could be useful to develop effective medications against cancer metastasis in future. Due to encouraging results, we highly recommend further in vitro and in vivo trials for the experimental validation of the findings.

SARS-CoV-2 Spatiotemporal Genomic and Molecular Analysis of the First Wave of the COVID-19 Pandemic in Macaé, the Brazilian Capital of Oil

The SARS-CoV-2 virus infection led to millions of deaths during the COVID-19 pandemic. Hundreds of workers from several other Brazilian cities, as well as from other countries, arrive daily in Macaé to work in the oil supply chain, making this city a putative hotspot for the introduction of new viral lineages. In this study, we performed a genomic survey of SARS-CoV-2 samples from Macaé during the first outbreak of COVID-19, combined with clinical data and a molecular integrative analysis. First, phylogenomic analyses showed a high occurrence of viral introduction events and the establishment of local transmissions in Macaé, including the ingression and spread of the B.1.1.28 lineage in the municipality from June to August 2020. Second, SARS-CoV-2 mutations were identified in patients with distinct levels of COVID-19 severity. Third, molecular interactions of the mutated spike protein from three B.1.1.33 local samples and human ACE2 showed higher interactions than that of the wild-type spike protein from the ancestral virus. Altogether, these results elucidate the SARS-CoV-2 genomic profile in a strategic Brazilian city and further explore the functional aspects of SARS-CoV-2 with a characterization of emerging viral mutations associated with clinical data and the potential targets for drug development against SARS-CoV-2.

Designing multi-epitope-based vaccine targeting surface immunogenic protein of Streptococcus agalactiae using immunoinformatics to control mastitis in dairy cattle

Background

Milk provides energy as well as the basic nutrients required by the body. In particular, milk is beneficial for bone growth and development in children. Based on scientific evidence, cattle milk is an excellent and highly nutritious dietary component that is abundant in vitamins, calcium, potassium, and protein, among other minerals. However, the commercial productivity of cattle milk is markedly affected by mastitis. Mastitis is an economically important disease that is characterized by inflammation of the mammary gland. This disease is frequently caused by microorganisms and is detected as abnormalities in the udder and milk. Streptococcus agalactiae is a prominent cause of mastitis. Antibiotics are rarely used to treat this infection, and other available treatments take a long time to exhibit a therapeutic effect. Vaccination is recommended to protect cattle from mastitis. Accordingly, the present study sought to design a multi-epitope vaccine using immunoinformatics.

Results

The vaccine was designed to be antigenic, immunogenic, non-toxic, and non-allergic, and had a binding affinity with Toll-like receptor 2 (TLR2) and TLR4 based on structural modeling, docking, and molecular dynamics simulation studies. Besides, the designed vaccine was successfully expressed in E. coli. expression vector (pET28a) depicts its easy purification for production on a larger scale, which was determined through in silico cloning. Further, immune simulation analysis revealed the effectiveness of the vaccine with an increase in the population of B and T cells in response to vaccination.

Conclusion

This multi-epitope vaccine is expected to be effective at generating an immune response, thereby paving the way for further experimental studies to combat mastitis.

Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation

The pandemic of COVID-19 caused by SARS-CoV-2 has made a worldwide health emergency. Despite the fact that current vaccines are readily available, several SARSCoV-2 variants affecting the existing vaccine are to be less effective due to the mutations in the structural proteins. Furthermore, the appearance of the new variants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vaccines are still pivotal works for preventing the spread of the virus. In the present investigation, the computational analysis through immunoinformatics, molecular docking, and molecular dynamics (MD) simulation is employed to construct an effective vaccine against SARS-CoV2. The structural proteins of SARS-CoV2 are utilized to create a multiepitope-based vaccine (MEV). According to our findings presented by systematic procedures in the current investigation, the MEV construct may be able to trigger a strong immunological response against the virus. Therefore, the designed MEV could be a potential vaccine candidate against SARS-CoV-2, and also it is expected to be effective for other variants.

SARS-CoV-2 Spike mutations modify the interaction between virus Spike and human ACE2 receptors

The high mutability of the SARS-CoV-2 virus is a growing concern among scientific communities and health professionals since it brings the effectiveness of repurposed drugs and vaccines for COVID-19 into question. Although the mutational investigation of the Spike protein of the SARS-CoV-2 virus has been confirmed by many different researchers, there is no thorough investigation carried out at the interacting region to reveal the mutational status and its associated severity. All the energetically favorable mutations and their detailed analytical features that could impact the infection severity of the SARS-CoV-2 virus need to be identified. Therefore, we have thoroughly investigated the most important site of the SARS-CoV-2 virus, which is the interface region (Residue 417–505) of the virus Spike that interacts with the human ACE2 receptor. Further, we have utilized molecular dynamic simulation to observe the relative stability of the Spike protein with partner ACE2, as a consequence of these mutations. In our study, we have identified 52 energetically favorable Spike mutations at the interface while binding to ACE2, of which only 36 significantly enhance the stabilization of the Spike-ACE2 complex. The stability order and molecular interactions of these mutations were also identified. The highest stabilizing mutation V503D confirmed in our study is also known for neutralization resistance.

In silico analysis of mutations near S1/S2 cleavage site in SARS-CoV-2 spike protein reveals increased propensity of glycosylation in Omicron strain

Cleavage of the severe respiratory syndrome coronavirus-2 (SARS-CoV-2) spike protein has been demonstrated to contribute to viral-cell fusion and syncytia formation. Studies have shown that variants of concern (VOC) and variants of interest (VOI) show differing membrane fusion capacity. Mutations near cleavage motifs, such as the S1/S2 and S2' sites, may alter interactions with host proteases and, thus, the potential for fusion. The biochemical basis for the differences in interactions with host proteases for the VOC/VOI spike proteins has not yet been explored. Using sequence and structure-based bioinformatics, mutations near the VOC/VOI spike protein cleavage sites were inspected for their structural effects. All mutations found at the S1/S2 sites were predicted to increase affinity to the furin protease but not TMPRSS2. Mutations at the spike residue P681 in several strains, such P681R in the Delta strain, resulted in the disruption of a proline-directed kinase phosphorylation motif at the S1/S2 site, which may lessen the impact of phosphorylation for these variants. However, the unique N679K mutation in the Omicron strain was found to increase the propensity for O-linked glycosylation at the S1/S2 cleavage site, which may prevent recognition by proteases. Such glycosylation in the Omicron strain may hinder entry at the cell surface and, thus, decrease syncytia formation and induce cell entry through the endocytic pathway as has been shown in previous studies. Further experimental work is needed to confirm the effect of mutations and posttranslational modifications on SARS-CoV-2 spike protein cleavage sites.

MurC ligase of multi-drug resistant Salmonella Typhi can be inhibited by novel Curcumin derivative: Evidence from molecular docking and dynamics simulations

Emerging multi-drug resistance in recent Salmonella Typhi isolates, causative agent of enteric Typhoid fever, compelled us to investigate alternative therapeutic strategies. The present study encompassed virtual screening, ADMET screening as well as antibacterial activity prediction to shortlist potent lead molecules whose binding affinities (BAs) were checked against major druggable S. Typhi targets. BA profile revealed a deoxy-tetradeutero- curcumin derivative to be novel bioactive compound having high BA towards UDP-N-acetylmuramate-L-alanine ligase (MurC) protein involved in peptidoglycan synthesis. Molecular docking indicated that our lead {Binding energy (BE)= -8.00 ± 0.02 kcal/mol}could competitively bind to MurC with respect to its natural ligand ATP (BE= -7.65 ± 0.19 kcal/mol). The lead also possessed superior binding and inhibition profile against MurC than other commercial antibiotics. This BE was contributed by Hydrogen (H-) bonds and numerous non-canonical interactions with the evolutionary conserved active-site residues. From molecular docking and coarse-grained dynamics simulations, it was inferred that the novel curcumin derivative was predicted to be potential competitive inhibitor of ATP for MurC-catalytic domain having low relative RMSF (0.59 Å) to inhibit MurC-induced peptidoglycan biosynthesis. The inferences drawn from the study can open new portals for designing efficient therapeutic strategies against S. Typhi.

Structure-Activity Relationship of the Dimeric and Oligomeric Forms of a Cytotoxic Biotherapeutic Based on Diphtheria Toxin

Protein aggregation is a well-recognized problem in industrial preparation, including biotherapeutics. These low-energy states constantly compete with a native-like conformation, which is more pronounced in the case of macromolecules of low stability in the solution. A better understanding of the structure and function of such aggregates is generally required for the more rational development of therapeutic proteins, including single-chain fusion cytotoxins to target specific receptors on cancer cells. Here, we identified and purified such particles as side products of the renaturation process of the single-chain fusion cytotoxin, composed of two diphtheria toxin (DT) domains and interleukin 13 (IL-13), and applied various experimental techniques to comprehensively understand their molecular architecture and function. Importantly, we distinguished soluble purified dimeric and fractionated oligomeric particles from aggregates. The oligomers are polydisperse and multimodal, with a distribution favoring lower and even stoichiometries, suggesting they are composed of dimeric building units. Importantly, all these oligomeric particles and the monomer are cystine-dependent as their innate disulfide bonds have structural and functional roles. Their reduction triggers aggregation. Presumably the dimer and lower oligomers represent the metastable state, retaining the native disulfide bond. Although significantly reduced in contrast to the monomer, they preserve some fraction of bioactivity, manifested by their IL-13RA2 receptor affinity and selective cytotoxic potency towards the U-251 glioblastoma cell line. These molecular assemblies probably preserve structural integrity and native-like fold, at least to some extent. As our study demonstrated, the dimeric and oligomeric cytotoxin may be an exciting model protein, introducing a new understanding of its monomeric counterpart’s molecular characteristics.

In-silico design of an immunoinformatics based multi-epitope vaccine against Leishmania donovani

BACKGROUND

Visceral Leishmaniasis (VL) is a fatal vector-borne parasitic disorder occurring mainly in tropical and subtropical regions. VL falls under the category of neglected tropical diseases with growing drug resistance and lacking a licensed vaccine. Conventional vaccine synthesis techniques are often very laborious and challenging. With the advancement of bioinformatics and its application in immunology, it is now more convenient to design multi-epitope vaccines comprising predicted immuno-dominant epitopes of multiple antigenic proteins. We have chosen four antigenic proteins of Leishmania donovani and identified their T-cell and B-cell epitopes, utilizing those for in-silico chimeric vaccine designing. The various physicochemical characteristics of the vaccine have been explored and the tertiary structure of the chimeric construct is predicted to perform docking studies and molecular dynamics simulations.

RESULTS

The vaccine construct is generated by joining the epitopes with specific linkers. The predicted tertiary structure of the vaccine has been found to be valid and docking studies reveal the construct shows a high affinity towards the TLR-4 receptor. Population coverage analysis shows the vaccine can be effective on the majority of the world population. In-silico immune simulation studies confirms the vaccine to raise a pro-inflammatory response with the proliferation of activated T and B cells. In-silico codon optimization and cloning of the vaccine nucleic acid sequence have also been achieved in the pET28a vector.

CONCLUSION

The above bioinformatics data support that the construct may act as a potential vaccine. Further wet lab synthesis of the vaccine and in vivo works has to be undertaken in animal model to confirm vaccine potency.

The expanding role of split protein complementation in opsin-free optogenetics

A comprehensive understanding of signaling mechanisms helps interpret fundamental biological processes and restore cell behavior from pathological conditions. Signaling outcome depends not only on the activity of each signaling component but also on their dynamic interaction in time and space, which remains challenging to probe by biochemical and cell-based assays. Opsin-based optogenetics has transformed neural science research with its spatiotemporal modulation of the activity of excitable cells. Motivated by this advantage, opsin-free optogenetics extends the power of light to a larger spectrum of signaling molecules. This review summarizes commonly used opsin-free optogenetic strategies, presents a historical overview of split protein complementation, and highlights the adaptation of split protein recombination as optogenetic sensors and actuators.

In-silico study for the screening and preparation of ionic liquid-AVDs conjugate to combat COVID-19 surge

The pandemic due to COVID-19 caused by SARS-CoV-2 has led to the recorded deaths worldwide and is still a matter of concern for scientists to find an effective counteragent. The combination therapy is always been a successful attempt in treating various threatful diseases. Recently, Ionic liquids (ILs) are known for their antiviral activity. Fascinating tunable properties of ILs make them a potential candidate for designing the therapeutic agent. The concern while using ILs in biomedical field remains is toxicity therefore, choline-based ILs were used in the study as they are considered to be greener as compared to other ILs. In the present study strategically, we performed the blind molecular docking of antiviral drug (Abacavir, Acyclovir, and Galidesivir)-choline based ILs conjugates with the target protein (M_pro protease). The molecules were screened on the basis of binding energy. The data suggested that the combination of AVDs-ILs have greater antiviral potential as compared to the drugs and ILs alone. Further, the ADME properties and toxicity analysis of the screened conjugates was done which revealed the non-toxicity of the conjugates. Additionally, the energetic profiling of the ILs drugs and their conjugates was done using DFT calculations which revealed the stability of the conjugates and have a better option to be developed as a therapeutic agent. Also, from molecular dynamic simulation was done and results showed the stability of the complex formed between target protein and the designed conjugates of AVDs and ILs.

The role of conserved arginine and proline residues in enterovirus VP1 protein

BACKGROUND

High diversity of VP1 protein among enteroviruses has been a barrier in developing universally effective antiviral drugs. To maintain structure stability during evolution, several residues of VP1 protein of enteroviruses are conserved. Therefore, investigation of highly conserved residues in VP1 protein may provide information for antiviral drug candidates against enteroviruses.

METHODS

To identify highly conserved amino acid sequences of the VP1 in enterovirus genus, the Consurf and CABS-flex 2.0 web software were applied. Through the combination with secondary structure information, we focused on conserved amino acids of VP1 property analysis.

RESULTS

Most conserved residues of VP1 were in the interior and interacted with VP2, VP3 and VP4 capsid proteins. Structure of EV-A71 (PDB code 4AED) showed conserved residues were at hydrophobic pocket and close to the junction between the loop and β-barrel. Interestingly, arginine was the most common conserved residue of VP1. Proline was the second most common conserved residue and was found in the loop and β-barrel intersection areas. VP1 protein flexibility was associated with the secondary structure. Conserved residues of VP1 in β-barrel showed significantly low flexibility.

CONCLUSION

Through large scale sequence analysis, we identified the amino acid distribution and location of conserved residues in VP1. This knowledge can be extrapolated for the Enterovirus genus and may contribute to developing the potential compound as an anti-enteroviral agent.

A comprehensive in silico exploration of the impacts of missense variants on two different conformations of human pirin protein

BACKGROUND

Pirin, a member of the cupin superfamily, is an iron-binding non-heme protein. It acts as a coregulator of several transcription factors, especially the members of NFκB transcription factor family. Based on the redox state of its iron cofactor, it can assume two different conformations and thereby act as a redox sensor inside the nucleus. Previous studies suggested that pirin may be associated with cancer, inflammatory diseases as well as COVID-19 severities. Hence, it is important to explore the pathogenicity of its missense variants. In this study, we used a number of in silico tools to investigate the effects of missense variants of pirin on its structure, stability, metal cofactor binding affinity and interactions with partner proteins. In addition, we used protein dynamics simulation to elucidate the effects of selected variants on its dynamics. Furthermore, we calculated the frequencies of haplotypes containing pirin missense variants across five major super-populations (African, Admixed American, East Asian, European and South Asian).

RESULTS

Among a total of 153 missense variants of pirin, 45 were uniformly predicted to be pathogenic. Of these, seven variants can be considered for further experimental studies. Variants R59P and L116P were predicted to significantly destabilize and damage pirin structure, substantially reduce its affinity to its binding partners and alter pirin residue fluctuation profile via changing the flexibility of several key residues. Additionally, variants R59Q, F78V, G98D, V151D and L220P were found to impact pirin structure and function in multiple ways. As no haplotype was identified to be harboring more than one missense variant, further interrogation of the individual effects of these seven missense variants is highly recommended.

CONCLUSIONS

Pirin is involved in the transcriptional regulation of several genes and can play an important role in inflammatory responses. The variants predicted to be pathogenic in this study may thus contribute to a better understanding of the underlying molecular mechanisms of various inflammatory diseases. Future studies should be focused on clarifying if any of these variants can be used as disease biomarkers.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s42269-022-00917-7.

Design of Multi-Epitope Vaccine for Staphylococcus saprophyticus: Pan-Genome and Reverse Vaccinology Approach

Staphylococcus saprophyticus is a Gram-positive coccus responsible for the occurrence of cystitis in sexually active, young females. While effective antibiotics against this organism exist, resistant strains are on the rise. Therefore, prevention via vaccines appears to be a viable solution to address this problem. In comparison to traditional techniques of vaccine design, computationally aided vaccine development demonstrates marked specificity, efficiency, stability, and safety. In the present study, a novel, multi-epitope vaccine construct was developed against S. saprophyticus by targeting fully sequenced proteomes of its five different strains, which were examined using a pangenome and subtractive proteomic strategy to characterize prospective vaccination targets. The three immunogenic vaccine targets which were utilized to map the probable immune epitopes were verified by annotating the entire proteome. The predicted epitopes were further screened on the basis of antigenicity, allergenicity, water solubility, toxicity, virulence, and binding affinity towards the DRB*0101 allele, resulting in 11 potential epitopes, i.e., DLKKQKEKL, NKDLKKQKE, QDKLKDKSD, NVMDNKDLE, TSGTPDSQA, NANSDGSSS, GSDSSSSNN, DSSSSNNDS, DSSSSDRNN, SSSDRNNGD, and SSDDKSKDS. All these epitopes have the efficacy to cover 99.74% of populations globally. Finally, shortlisted epitopes were joined together with linkers and three different adjuvants to find the most stable and immunogenic vaccine construct. The top-ranked vaccine construct was further scrutinized on the basis of its physicochemical characterization and immunological profile. The non-allergenic and antigenic features of modeled vaccine constructs were initially validated and then subjected to docking with immune receptor major histocompatibility complex I and II (MHC-I and II), resulting in strong contact. In silico cloning validations yielded a codon adaptation index (CAI) value of 1 and an ideal percentage of GC contents (46.717%), indicating a putative expression of the vaccine in E. coli. Furthermore, immune simulation demonstrated that, after injecting the proposed MEVC, powerful antibodies were produced, resulting in the sharpest peaks of IgM + IgG formation (>11,500) within 5 to 15 days. Experimental testing against S. saprophyticus can evaluate the safety and efficacy of these prophylactic vaccination designs.

Antibacterial Peptide NP-6 Affects Staphylococcus aureus by Multiple Modes of Action

Our previous study extracted and identified an antibacterial peptide that was named NP-6. Herein, we investigated the physicochemical properties of NP-6, and elucidated the mechanisms underlying its antimicrobial activity against Staphylococcus aureus. The results showed that the hemolysis activity of NP-6 was 2.39 ± 0.13%, lower than Nisin A (3.91 ± 0.43%) at the same concentration (512 µg/mL). Negligible cytotoxicity towards RAW264.7 cells was found when the concentration of NP-6 was lower than 512 µg/mL. In addition, it could keep most of its activity in fetal bovine serum. Moreover, transmission electron microscopy, confocal laser scanning microscopy, and flow cytometry results showed that NP-6 can destroy the integrity of the bacterial cell membrane and increase the membrane permeability. Meanwhile, NP-6 had binding activity with bacterial DNA and RNA in vitro and strongly inhibited the intracellular β-galactosidase activity of S. aureus. Our findings suggest that NP-6 could be a promising candidate against S. aureus.

Neprosin belongs to a new family of glutamic peptidase based on in silico evidence

Neprosin was first discovered in the insectivorous tropical pitcher plants of Nepenthes species as a novel protease with prolyl endopeptidase (PEP) activity. Neprosin has two uncharacterized domains of neprosin activation peptide and neprosin. A previous study has shown neprosin activity in hydrolyzing proline-rich gliadin, a gluten component that triggers celiac disease. In this study, we performed in silico structure-function analysis to investigate the catalytic mechanism of neprosin. Neprosin sequences lack the catalytic triad and motifs of PEP family S9. Protein structures of neprosins from Nepenthes × ventrata (NvNpr) and N. rafflesiana (NrNpr1) were generated by ab initio methods and comparatively assessed to obtain high-quality models. Structural alignment of models to experimental structures in the Protein Data Bank (PDB) found a high structural similarity to glutamic peptidases. Further investigations reveal other resemblances to the glutamic peptidases with low optimum pH that activates the enzyme via autoproteolysis for maturation. Two highly conserved glutamic acid residues, which are stable according to the molecular dynamics simulation, can be found at the active site of the substrate cleft. Protein docking demonstrated that mature neprosins bind well with potent antigen αI-gliadin at the putative active site. Taken together, neprosins represent a new glutamic peptidase family, with a putative catalytic dyad of two glutamic acids. This study illustrates a hypothetical enzymatic mechanism of the neprosin family and demonstrates the useful application of an accurate ab initio protein structure prediction in the structure-function study of a novel protein family.

Targeting Streptomyces-Derived Streptenol Derivatives against Gynecological Cancer Target PIK3CA: An In Silico Approach

Streptomyces is amongst the most amenable genera for biotechnological applications, and it is extensively used as a scaffold for drug development. One of the most effective therapeutic applications in the treatment of cancer is targeted therapy. Small molecule therapy is one of them, and it has gotten a lot of attention recently. Streptomyces derived compounds namely streptenols A, C, and F-I and streptazolin were subjected for ADMET property assessment. Our computational studies based on molecular docking effectively displayed the synergistic effect of streptomyces-derived compounds on the gynecological cancer target PIK3CA. These compounds were observed with the highest docking scores as well as promising intermolecular interaction stability throughout the molecular dynamic simulation. Molecular docking and molecular dynamic modeling techniques were utilized to investigate the binding mode stability of drugs using a pharmacophore scaffold, as well as physicochemical and pharmacokinetic aspects linked to alpelisib. With a root mean square fluctuation of the protein backbone of less than 0.7 nm, they demonstrated a steady binding mode in the target binding pocket. They have also prompted hydrogen bonding throughout the simulations, implying that the chemicals have firmly occupied the active site. A comprehensive study showed that streptenol D, streptenol E, streptenol C, streptenol G, streptenol F, and streptenol B can be considered as lead compounds for PIK3CA-based inhibitor design. To warrant the treatment efficacy against cancer, comprehensive computational research based on proposed chemicals must be assessed through in vitro studies.

A multi-epitope vaccine designed against blood-stage of malaria: an immunoinformatic and structural approach

Malaria is a complex disease caused by parasites of the genus Plasmodium and is the leading cause of morbidity and mortality worldwide. The most severe form of malaria disease is caused by Plasmodium falciparum. Thus, a combination of different approaches is needed to control malaria. Resistance to first-line drugs and insecticides, on the other hand, makes the need for an effective vaccination more urgent than ever. Because erythrocyte parasites cause the most clinical symptoms, developing a vaccination for this stage of infection might be highly beneficial. In this research, we employed various bioinformatics methods to create an efficient multi-epitope vaccine that induces antibodies against the blood stage of malaria infection. For this purpose, we selected the malaria PfGARP protein as the target here. The B, HTL epitopes, and epitope conservation were predicted. The predicted epitopes (including 5 B and 5 HTL epitopes) were connected using suitable linkers, and the flagellin molecule was used as an adjuvant to improve its immunogenicity. The final construct vaccine with 414 amino acids long was designed. The vaccine's allergenicity, antigenicity, solubility, physicochemical characteristics, 2D and 3D structure modeling, molecular docking, molecular dynamics simulation, in silico cloning, and immunological simulation were tested. In silico immune simulation results showed significantly elevated IgG1 and IgM and T helper cells, INF γ, IL 2, and B-cell populations after the injection of the designed vaccine. These significant computational analyses indicated that our proposed vaccine candidate might activate suitable immune responses against malaria. However, in vitro and in vivo studies are essential for further validation.

Application of Phytochemicals To Combat Fungal Pathogens of Pulses: An Approach toward Inhibition of Fungal Propagation and Invasin Activity

The present study represented an innovative strategy for inactivating the secreted invasins (lignocellulolytic enzymes) of fungal phytopathogens using natural phytochemicals to combat fungal infection to the pulses. A fungal pathogen (Aspergillus niger SKP1) was isolated from the white lentil (Vigna mungo), which has the ability to synthesize different lignocellulolytic enzymes. An in silico docking study elucidated that quercetin, naringin, epigallocatechin gallate, curcumin, and cinnamic acid were the prime efficient phytochemicals to inhibit the activity of fungal invasive enzymes like endoglucanase, endo-1,4-β-xylanase, and glucoamylase. Considering this observation, extracted phytochemicals in different mixtures were applied to prevent growth of the isolated pathogen under in situ experimental studies. The minimal inhibitory concentrations (MIC₅₀) and minimal fungicidal concentration (MFC₅₀) values of the first mixture (naringenin, epicatechin gallate, and cinnamic acid) and second mixture (quercetin and curcumin) were 170 and 220 mg/L and 320 and 380 mg/L, respectively. The studied phytochemicals were established to be cytosafe when compared to the commercial fungicides. The seeds of the white lentil were subjected to 1 year of long-term storage with the two aforementioned combinatorial phytochemicals. Subsequent morphological and physiological analyses revealed the complete protection of the stored seeds from the fungal infection. The present work has enough potentiality for the storage of pulses using natural preservatives that circumvent the adverse effect of the chemical preservatives on the ecosystem.

Computationally Decoding NudF Residues To Enhance the Yield of the DXP Pathway

Terpenoids form a large pool of highly diverse organic compounds possessing several economically important properties, including nutritional, aromatic, and pharmacological properties. The 1-deoxy-d-xylulose 5-phosphate (DXP) pathway's end enzyme, nuclear distribution protein (NudF), interacting with isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), is critical for the synthesis of isoprenol/prenol/downstream compounds. The enzyme is yet to be thoroughly investigated to increase the overall yield of terpenoids in the Bacillus subtilis, which is widely used in industry and is generally regarded as a safe (GRAS) bacterium. The study aims to analyze the evolutionary conservation across the active site for mapping the key residues for mutagenesis studies. The 37-sequence data set, extracted from 103 Bacillus subtilis entries, shows a high phylogenetic divergence, and only six one-motif sequences ASB92783.1, ASB69297.1, ASB56714.1, AOR97677.1, AOL97023.1, and OAZ71765.1 show a monophyly relationship, unlike a complete polyphyly relationship between the other 31 three-motif sequences. Furthermore, only 47 of 179 residues of the representative sequence CUB50584.1 are observed to be significantly conserved. Docking analysis suggests a preferential bias of adenosine diphosphate (ADP)-ribose pyrophosphatase toward IPP, and a nearly threefold energetic difference is observed between IPP and DMAPP. The loops are hereby shown to play a regulatory role in guiding the promiscuity of NudF toward a specific ligand. Computational saturation mutagenesis of the seven hotspot residues identifies two key positions LYS78 and PHE116, orderly encoded within loop1 and loop7, majorly interacting with the ligands DMAPP and IPP, and their mutants K78I/K78L and PHE116D/PHE116E are found to stabilize the overall conformation. Molecular dynamics analysis shows that the IPP complex is significantly more stable than the DMAPP complex, and the NudF structure is very unstable. Besides showing a promiscuous binding of NudF with ligands, the analysis suggests its rate-limiting nature. The study would allow us to customize the metabolic load toward the synthesis of any of the downstream molecules. The findings would pave the way for the development of catalytically improved NudF mutants for the large-scale production of specific terpenoids with significant nutraceutical or commercial value.

In Silico Analysis of the Apoptotic and HPV Inhibitory Roles of Some Selected Phytochemicals Detected from the Rhizomes of Greater Cardamom

Occurrence of cervical cancer, caused due to persistent human papilloma virus (HPV) infection, is common in women of developing countries. As the conventional treatments are expensive and associated with severe side effects, there is a need to find safer alternatives, which is affordable and less toxic to the healthy human cells. Present study aimed to evaluate the anti-HPV and apoptotic potential of four compounds from the greater cardamom (Amomum subulatum Roxb. var. Golsey), namely rhein, phytosphingosine, n-hexadecenoic acid and coronarin E. Their anti-HPV and apoptotic potential were studied against viral E6, E7 and few anti-apoptotic proteins of host cell (BCL2, XIAP, LIVIN) by in silico docking technique. Phytochemicals from the plant extract were analysed and identified by LC/MS and GC/MS. Involvement of the target proteins in various biological pathways was determined through KEGG. Structural optimization of the three-dimensional structures of the ligands (four phytochemicals and control drug) was done by Avogadro1.1. Receptor protein models were built using ProMod3 and other advanced tools. Pharmacophore modelling of the selected phytochemicals was performed in ZINCPharmer. Swiss ADME studies were undertaken to determine drug likeness. The ligands and proteins were digitally docked in DockThor docking program. Protein flexibility-molecular dynamic simulation helped to study protein–ligand stability in real time. Finally, the correlation of evaluated molecules was studied by the use of principal component analysis (PCA) based on the docking scores. All the ligands were found to possess apoptotic and anti-cancer activities and did not violate Lipinsky criteria. n-Hexadecanoic acid and its analogues showed maximum efficacy against the target proteins. All the protein–ligand interactions were found to be stable. The uncommon phytochemicals identified from rhizomes of greater cardamom have anti-cancer, apoptotic and HPV inhibitory potentials as analysed by docking and other in silico studies, which can be utilized in drug development after proper experimental validation.

Relative, local and global dimension in complex networks

Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical spaces, which can be constrained by boundaries and distorted by inhomogeneities, or to intrinsically discrete systems such as networks. To take into account locality, finiteness and discreteness, dynamical processes can be used to probe the space geometry and define its dimension. Here we show that each point in space can be assigned a relative dimension with respect to the source of a diffusive process, a concept that provides a scale-dependent definition for local and global dimension also applicable to networks. To showcase its application to physical systems, we demonstrate that the local dimension of structural protein graphs correlates with structural flexibility, and the relative dimension with respect to the active site uncovers regions involved in allosteric communication. In simple models of epidemics on networks, the relative dimension is predictive of the spreading capability of nodes, and identifies scales at which the graph structure is predictive of infectivity. We further apply our dimension measures to neuronal networks, economic trade, social networks, ocean flows, and to the comparison of random graphs.

Defining the dimension in bounded, inhomogeneous or discrete physical systems may be challenging. The authors introduce here a dynamics-based notion of dimension by analysing diffusive processes in space, relevant for non-ideal physical systems and networks.

Deciphering the substrate specificity of housekeeping sortase A and pilus-specific sortase C of probiotic bacterium Lactococcus lactis

Several strains and species of lactic acid bacteria (LAB) are widely used in fermented foods, including dairy products and also as probiotics, because of their contribution to various health benefits in humans. Sortase enzymes decorate the bacterial cell wall with different surface proteins and pili for facilitating the interactions with host and environment for the colonization and beneficial effects. While the sortases and sortase anchored proteins from pathogens have been the prime focus of the research in the past, sortases from many non-pathogenic bacteria, including LAB strains, have attracted attention for their potential applications in vaccine delivery and other clinical interventions. Here, we report the purification and functional characterization of two sortases (housekeeping SrtA and pilus-specific SrtC) from a probiotic Lactococcus lactis. The purified sortases were found to be active against the putative LPXTG motif-based peptide substrates, albeit with differences. The in-silico analysis provides insights into the residues involved in substrate binding and specificity. Overall, this study sheds new light on the aspects of structure, substrate specificity, and function of sortases from non-pathogenic bacteria, which may have physiological ramifications as well as their applications in sortase-mediated protein bioconjugation.

Effect of pH on structural dynamics of HMG-CoA reductase and binding affinity to β-sitosterol

Human 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR; EC 1.1.1.34) catalyzes the conversion of (3S)-hydroxy-3-methylglutaryl-CoA (HMG-CoA) to mevalonic acid, which has been defined as the rate-limiting step in the synthesis of cholesterol and other isoprenoids, thus playing a critical role in cellular cholesterol homeostasis. In this study, the effect of changing pH on the structural dynamics and binding affinity of HMGCR were investigated by molecular dynamics simulation using OpenMM, and molecular docking using Autodock Vina. The results pinpoint pH 8.0 for optimum structural stability/activity of HMGCR, and the insightful relationships between pH, structural dynamics radius of gyration (Rg) or root mean square deviation (RMSD), and binding affinity of HMGCR. This method will be useful to predict the pH for the uncharacterized human proteins, toward biomedical and biotechnological applicationsCommunicated by Ramaswamy H. Sarma.

Structural insights into choline-O-sulfatase reveal the molecular determinants for ligand binding

The first structures of a choline-O-sulfatase bound to different ligands are reported.

Choline-O-sulfatase (COSe; EC 3.1.6.6) is a member of the alkaline phosphatase (AP) superfamily, and its natural function is to hydrolyze choline-O-sulfate into choline and sulfate. Despite its natural function, the major interest in this enzyme resides in the landmark catalytic/substrate promiscuity of sulfatases, which has led to attention in the biotechnological field due to their potential in protein engineering. In this work, an in-depth structural analysis of wild-type Sinorhizobium (Ensifer) meliloti COSe (SmeCOSe) and its C54S active-site mutant is reported. The binding mode of this AP superfamily member to both products of the reaction (sulfate and choline) and to a substrate-like compound are shown for the first time. The structures further confirm the importance of the C-terminal extension of the enzyme in becoming part of the active site and participating in enzyme activity through dynamic intra-subunit and inter-subunit hydrogen bonds (Asn146^A–Asp500^B–Asn498^B). These residues act as the ‘gatekeeper’ responsible for the open/closed conformations of the enzyme, in addition to assisting in ligand binding through the rearrangement of Leu499 (with a movement of approximately 5 Å). Trp129 and His145 clamp the quaternary ammonium moiety of choline and also connect the catalytic cleft to the C-terminus of an adjacent protomer. The structural information reported here contrasts with the proposed role of conformational dynamics in promoting the enzymatic catalytic proficiency of an enzyme.

Chemical Reactivity and Optical and Pharmacokinetics Studies of 14 Multikinase Inhibitors and Their Docking Interactions Toward ACK1 for Precision Oncology

Activated Cdc42-associated kinase 1 (ACK1/TNK2) has a significant role in cell endocytosis, survival, proliferation, and migration. Mutations in ACK1 are closely associated with the occurrence and development of cancers. In this work, a conceptual density functional theory (CDFT)-based computational peptidology (CDFT-CP) method is used to study the chemical reactivity of 14 multikinase inhibitors. Optical properties of these inhibitors are studied by time-dependent density functional theory (TDDFT). Various biological and pharmacokinetic parameters are studied by Osiris, Molinspiration, and BOILED-Egg in SwissADME software tools. Physicochemical and biopharmaceutical (PCB), Salmonella typhimurium reverse mutation assay (AMES) mutagenicity, toxicity, and risk prediction are estimated by Simulations plus ADMET Predictor 10.2 software. MD simulations for an active model of ACK1 is carried out by the CABS-flex 2.0 web server, and potential binding pockets for ACK1 are searched using the PrankWeb server. SwissTargetPrediction is used to predict the potential targets for the multikinase inhibitors. Docking studies are carried out for ACK1–multikinase inhibitors using Autodock 4.2 software. Noncovalent interactions for ACK1–multikinase inhibitor complexes are studied using the Protein–Ligand Interaction Profiler (PLIP) server. Results indicated higher binding affinities and strong noncovalent interactions in ACK1–multikinase inhibitor complexes.

Complex Autism Spectrum Disorder with Epilepsy, Strabismus and Self-Injurious Behaviors in a Patient with a De Novo Heterozygous POLR2A Variant

Autism spectrum disorder (ASD) describes a complex and heterogenous group of neurodevelopmental disorders. Whole genome sequencing continues to shed light on the multifactorial etiology of ASD. Dysregulated transcriptional pathways have been implicated in neurodevelopmental disorders. Emerging evidence suggests that de novo POLR2A variants cause a newly described phenotype called ‘Neurodevelopmental Disorder with Hypotonia and Variable Intellectual and Behavioral Abnormalities’ (NEDHIB). The variable phenotype manifests with a spectrum of features; primarily early onset hypotonia and delay in developmental milestones. In this study, we investigate a patient with complex ASD involving epilepsy and strabismus. Whole genome sequencing of the proband−parent trio uncovered a novel de novo POLR2A variant (c.1367T>C, p. Val456Ala) in the proband. The variant appears deleterious according to in silico tools. We describe the phenotype in our patient, who is now 31 years old, draw connections between the previously reported phenotypes and further delineate this emerging neurodevelopmental phenotype. This study sheds new insights into this neurodevelopmental disorder, and more broadly, the genetic etiology of ASD.

In silico profiling of non-synonymous SNPs in IDS gene for early diagnosis of Hunter syndrome

Background

Single amino acid substitutions in the Iduronate-2-sulfatase enzyme result in destabilization of the protein and cause a genetic disorder called Hunter syndrome. To gain functional insight into the mutations causing Hunter syndrome, various bioinformatics tools were employed, and special significance is given to molecular docking.

Results

In-silico tools available online for preliminary analysis including SIFT, PolyPhen 2.0, etc., were primarily employed and have identified 51 Non-synonymous Single Nucleotide Polymorphisms (ns-SNPs) as possibly deleterious. Further, modelling and energy minimization followed by Root Mean Square Deviation (RMSD) calculation has labelled 42 mutations as probably deleterious ns-SNPs. Later, trajectory analysis was performed using online tools like PSIPRED, SRide, etc., and has predicted six ns-SNPs as potentially deleterious. Additionally, docking was performed, and three candidate ns-SNPs were identified. Finally, these three ns-SNPs were confirmed to play a significant role in causing syndrome through root mean square fluctuation (RMSF) calculations.

Conclusion

From the observed results, G134E, V503D, and E521D were predicted to be candidate ns-SNPs in comparison with other in-silico tools and confirmed by RMSF calculations. Thus, the identified candidate ns-SNPs can be employed as a potential genetic marker in the early diagnosis of Hunter syndrome after clinical validation.

Design and Study of In Silico Binding Dynamics of Certain Isoxazole Bearing Leads Against Aβ-42 and BACE-1 Loop in Protein Fibrillation

Aims:

Design isoxazole bearing leads as dual inhibitors against Amyloid β and BACE-1 loop in protein fibrillation.

Background:

Protein fibrillation is one of the key reasons for several diseases, namely Alzheimer’s, Parkinson’s, and many others. One of the key strategies of preventing protein fibrillation is destabilizing the protein fibrils themselves or inhibiting the amyloid fibril-forming pathway in the initial stage.

Introduction:

Attempts have been taken to design newer leads to inhibit protein fibrillation by targeting the β-amyloidogenesis pathway in the brain. To exploit interfenestration between Amyloid β -42 protein and BACE-1 (β-site amyloid precursor protein cleaving enzyme) for amyloidogenesis, studies are undertaken to design dual inhibitors against the same.

Method:

In vitro binding interactions were found using docking, de novo ligand design, and MD simulation study.

Results:

Three compounds bearing an isoxazole heterocyclic nucleus were designed which could successfully bind to the hydrophobic raft and salt bridge residues Asp 23-Lys-26 of Amyloid β, destabilizing the growing fibril. Additionally, one of our candidate compounds exhibited force of interaction with Thr232 at the S3 pocket of BACE-1, interacted with key residue Asp228, Tyr71, and Thr72 of the β-hairpin flap and hydrogen bonding with Gly11 at loop 10s.

Conclusion:

Protein flexibility dynamics of the Aβ-42 protein revealed that there is a considerable conformational change of the same with or without ligand binding. The lower RMSF of the bound region and reprogramming residual contacts within the Aβ-42 protein suggested successful binding of the ligand with the protein, lowering the access for further β-β dimerization.

Computational methods to predict protein aggregation

In most cases, protein aggregation stems from the establishment of non-native intermolecular contacts. The formation of insoluble protein aggregates is associated with many human diseases and is a major bottleneck for the industrial production of protein-based therapeutics. Strikingly, fibrillar aggregates are naturally exploited for structural scaffolding or to generate molecular switches and can be artificially engineered to build up multi-functional nanomaterials. Thus, there is a high interest in rationalizing and forecasting protein aggregation. Here, we review the available computational toolbox to predict protein aggregation propensities, identify sequential or structural aggregation-prone regions, evaluate the impact of mutations on aggregation or recognize prion-like domains. We discuss the strengths and limitations of these algorithms and how they can evolve in the next future.

In silico and in vivo approaches to recombinant multi-epitope immunogen of GroEL provides efficient cross protection against S. Typhimurium, S. flexneri, and S. dysenteriae

OBJECTIVES

Stress or Heat Shock Proteins (HSPs) have been included in various operations like protein folding, autophagy, and apoptosis. HSP families recognize as protective antigens in a wide range of bacteria because they have been conserved through evolution. Due to their homology as well as antigenicity they are competent for applying in cross-protection against bacterial diseases.

METHODS

In the present study, bioinformatics approaches utilized to design epitope-based construction of Hsp60 (or GroEL) protein. In this regard, potential B-cell and T-cell epitopes except for allergenic sequences were selected by immunoinformatic tools. The structural and functional aspects of the DNA, RNA, and protein levels were assessed by bioinformatics software. Following in silico investigations, recombinant GroEL multi-epitope of Salmonella typhi was expressed, purified, and validated. Mouse groups were immunized with recombinant protein and humoral immune response was measured by enzyme linked immunosorbent assay (ELISA). Animal challenge against Salmonella Typhimurium, Shigella flexneri, and Shigella dysenteriae was evaluated.

RESULTS

recombinant protein expression and purification with 14.3 kilodaltons (kDa) was confirmed by SDS-PAGE and western blotting. After animal administration, the immunoglobulins evaluated increase after each immunization. Immunized antisera exhibited 80%, 40%, and 40% protection against the lethal dose infection by S. Typhimurium, S. flexneri, and S. dysenteriae respectively. Passive immunization conferred 50%, 30%, and 30% protection in mice against S. Typhimurium, S. flexneri and S. dysentery respectively. In addition, bacterial organ load had exhibited a significant decrease in colony forming unit (CFU) in the liver and spleen of the immunized mice compared to the control.

CONCLUSION

Our study demonstrates the efficacy of S. Typhi recombinant GroEL multi-epitope to consider as a universal immunogen candidate versus multiple bacterial pathogens.

Bioinformatics Methods in Predicting Amyloid Propensity of Peptides and Proteins

Several computational methods have been developed to predict amyloid propensity of a protein or peptide. These bioinformatics tools are time- and cost-saving alternatives to expensive and laborious experimental methods which are used to confirm self-aggregation of a protein. Computational approaches not only allow preselection of reliable candidates for amyloids but, most importantly, are capable of a thorough and informative analysis of a protein, indicating the sequence determinants of protein aggregation, identifying the potential causal mutations and likely mechanisms. Bioinformatics modeling applies several different approaches, which most typically include physicochemical or structure-based modeling, machine learning, or statistics based modeling. Bioinformatics methods typically use the amino acid sequence of a protein as an input, some also include additional information, for example, an available structure. This chapter describes the methods currently used to computationally predict amyloid propensity of a protein or peptide. Since the accuracy of bioinformatics methods may be highly dependent on reference data used to develop and evaluate the predictors, we also briefly present the main databases of amyloids used by the authors of bioinformatics tools.

Identification of a Potential mRNA-based Vaccine Candidate against the SARS-CoV-2 Spike Glycoprotein: A Reverse Vaccinology Approach

The emergence of the novel coronavirus (SARS-CoV-2) in December 2019 has generated a devastating global consequence which makes the development of a rapidly deployable, effective and safe vaccine candidate an imminent global health priority. The design of most vaccine candidates has been directed at the induction of antibody responses against the trimeric spike glycoprotein of SARS-CoV-2, a class I fusion protein that aids ACE2 (angiotensin-converting enzyme 2) receptor binding. A variety of formulations and vaccinology approaches are being pursued for targeting the spike glycoprotein, including simian and human replication-defective adenoviral vaccines, subunit protein vaccines, nucleic acid vaccines and whole-inactivated SARS-CoV-2. Here, we directed a reverse vaccinology approach towards the design of a nucleic acid (mRNA-based) vaccine candidate. The "YLQPRTFLL" peptide sequence (position 269-277) which was predicted to be a B cell epitope and likewise a strong binder of the HLA*A-0201 was selected for the design of the vaccine candidate, having satisfied series of antigenicity assessments. Through the codon optimization protocol, the nucleotide sequence for the vaccine candidate design was generated and targeted at the human toll-like receptor 7 (TLR7). Bioinformatics analyses showed that the sequence "UACCUGCAGCCGCGUACCUUCCUGCUG" exhibited a strong affinity and likewise was bound to a stable cavity in the TLR7 pocket. This study is therefore expected to contribute to the research efforts directed at securing definitive preventive measures against the SARS-CoV-2 infection.