Effective protein model structure refinement by loop modeling and overall relaxation

Identification and Design of Novel Potential Antimicrobial Peptides Targeting Mycobacterial Protein Kinase PknB

Antimicrobial peptides have gradually gained advantages over small molecule inhibitors for their multifunctional effects, synthesising accessibility and target specificity. The current study aims to determine an antimicrobial peptide to inhibit PknB, a serine/threonine protein kinase (STPK), by binding efficiently at the helically oriented hinge region. A library of 5626 antimicrobial peptides from publicly available repositories has been prepared and categorised based on the length. Molecular docking using ADCP helped to find the multiple conformations of the subjected peptides. For each peptide served as input the tool outputs 100 poses of the subjected peptide. To maintain an efficient binding for relatively a longer duration, only those peptides were chosen which were seen to bind constantly to the active site of the receptor protein over all the poses observed. Each peptide had different number of constituent amino acid residues; the peptides were classified based on the length into five groups. In each group the peptide length incremented upto four residues from the initial length form. Five peptides were selected for Molecular Dynamic simulation in Gromacs based on higher binding affinity. Post-dynamic analysis and the frame comparison inferred that neither the shorter nor the longer peptide but an intermediate length of 15 mer peptide bound well to the receptor. Residual substitution to the selected peptides was performed to enhance the targeted interaction. The new complexes considered were further analysed using the Elastic Network Model (ENM) for the functional site's intrinsic dynamic movement to estimate the new peptide's role. The study sheds light on prospects that besides the length of peptides, the combination of constituent residues equally plays a pivotal role in peptide-based inhibitor generation. The study envisages the challenges of fine-tuned peptide recovery and the scope of Machine Learning (ML) and Deep Learning (DL) algorithm development. As the study was primarily meant for generation of therapeutics for Tuberculosis (TB), the peptide proposed by this study demands meticulous invitro analysis prior to clinical applications.

Conjugation with the Carrier Helped to Reveal acidification-Induced Structural Shift in the Peptide from Phospholipase Domain of Parvovirus B19

Spectroscopic studies on domains and peptides of large proteins are complicated because of the tendency of short peptides to form oligomers in aquatic buffers, but conjugation of a peptide with a carrier protein may be helpful. In this study we approved that a fragment of SK30 peptide from phospholipase A2 domain of VP1 Parvovirus B19 capsid protein (residues: 144-159; 164; 171-183; sequence: SAVDSAARIHDFRYSQLAKLGINPYTHWTVADEELLKNIK) turns from random coil to alpha helix in the acidic medium only in case if it had been conjugated with BSA (through additional N-terminal Cys residue, turning it into CSK31 peptide, and SMCC linker) according to CD-spectroscopy results. In contrast, unconjugated SK30 peptide does not undergo such shift because it forms stable oligomers connected by intermolecular antiparallel beta sheet, according to IR-spectroscopy, CD-spectroscopy, blue native gel electrophoresis and centrifugal ultrafiltration, as, probably, the whole isolated phospholipase domain of VP1 protein does. However, being a part of the long VP1 capsid protein, phospholipase domain may change its fold during the acidification of the medium in the endolysosome by the way of the formation of contacts between protonated His153 and Asp175, promoting the shift from random coil to alpha helix in its N-terminal part. This study opens up a perspective of vaccine development, since rabbit polyclonal antibodies against the conjugate of CSK31 peptide with BSA, in which the structure of the second alpha helix from the phospholipase A2 domain should be reproduced, can bind epitopes of the complete recombinant unique part of VP1 Parvovirus B19 capsid (residues: 1-227).

Drug to genome to drug: a computational large-scale chemogenomics screening for novel drug candidates against sporotrichosis

Sporotrichosis is recognized as the predominant subcutaneous mycosis in South America, attributed to pathogenic species within the Sporothrix genus. Notably, in Brazil, Sporothrix brasiliensis emerges as the principal species, exhibiting significant sapronotic, zoonotic and enzootic epidemic potential. Consequently, the discovery of novel therapeutic agents for the treatment of sporotrichosis is imperative. The present study is dedicated to the repositioning of pharmaceuticals for sporotrichosis therapy. To achieve this goal, we designed a pipeline with the following steps: (a) compilation and preparation of Sporothrix genome data; (b) identification of orthologous proteins among the species; (c) identification of homologous proteins in publicly available drug-target databases; (d) selection of Sporothrix essential targets using validated genes from Saccharomyces cerevisiae; (e) molecular modeling studies; and (f) experimental validation of selected candidates. Based on this approach, we were able to prioritize eight drugs for in vitro experimental validation. Among the evaluated compounds, everolimus and bifonazole demonstrated minimum inhibitory concentration (MIC) values of 0.5 µg/mL and 4.0 µg/mL, respectively. Subsequently, molecular docking studies suggest that bifonazole and everolimus may target specific proteins within S. brasiliensis- namely, sterol 14-α-demethylase and serine/threonine-protein kinase TOR, respectively. These findings shed light on the potential binding affinities and binding modes of bifonazole and everolimus with their probable targets, providing a preliminary understanding of the antifungal mechanism of action of these compounds. In conclusion, our research advances the understanding of the therapeutic potential of bifonazole and everolimus, supporting their further investigation as antifungal agents for sporotrichosis in prospective hit-to-lead and preclinical investigations.

Isolation and Characterization of the Vascular Endothelial Growth Factor Receptor Targeting ScFv Antibody Fragments Derived from Phage Display Technology

Angiogenesis, as a tumor hallmark, plays an important role in the growth and development of the tumor vasculature system. There is a huge amount of evidence suggesting that the vascular endothelial growth factor receptor (VEGFR-2)/VEGF-A axis is one of the main contributors to tumor angiogenesis and metastasis. Thus, inhibition of the VEGFR-2 signaling pathway by anti-VEGFR-2 mAb can retard tumor growth. In this study, we employ phage display technology and solution-phase biopanning (SPB) to isolate specific single-chain variable fragments (scFvs) against VEGFR-2 and report on the receptor binding characteristics of the candidate scFvs A semisynthetic phage antibody library to isolate anti-VEGFR-2 scFvs through an SPB performed with decreasing concentrations of the VEGFR-2-His tag and VEGFR-2-biotin. After successful expression and purification, the specificity of the selected scFv clones was further analyzed by enzyme-linked immunosorbent assay (ELISA), flow cytometry, and immunoblotting. The competition assay was undertaken to identify the VEGFR-2 receptor-blocking properties of the scFvs. Furthermore, the molecular binding characteristics of candidate scFvs were extensively studied by peptide-protein docking. Polyclonal ELISA analysis subsequent to four rounds of biopanning showed a significant enrichment of VEGFR-2-specific phage clones by increasing positive signals from the first round toward the fourth round of selection. The individual VEGFR-2-reactive scFv phage clones were identified by monoclonal phage ELISA. The sequence analysis and complementarity-determining region alignment identified the four unique anti-VEGFR-2-scFv clones. The soluble and purified scFvs displayed binding activity against soluble and cell-associated forms of VEGFR-2 protein in the ELISA and flow cytometry assays. Based on the inference from the molecular docking results, scFvs D3, E1, H1, and E9 recognized domains 2 and 3 on the VEGFR-2 protein and displayed competition with VEGF-A for binding to VEGFR-2. The competition assay confirmed that scFvs H1 and D3 can block the VEGFR-2/VEGF-A interaction. In conclusion, we identified novel VEGFR-2-blocking scFvs that perhaps exhibit the potential for angiogenesis inhibition in VEGFR-2-overexpressed tumor cells.

Deflamin Attenuated Lung Tissue Damage in an Ozone-Induced COPD Murine Model by Regulating MMP-9 Catalytic Activity

Chronic obstructive pulmonary disease (COPD) is comprised of histopathological alterations such as pulmonary emphysema and peribronchial fibrosis. Matrix metalloproteinase 9 (MMP-9) is one of the key enzymes involved in both types of tissue remodeling during the development of lung damage. In recent studies, it was demonstrated that deflamin, a protein component extracted from Lupinus albus, markedly inhibits the catalytic activity of MMP-9 in experimental models of colon adenocarcinoma and ulcerative colitis. Therefore, in the present study, we investigated for the first time the biological effect of deflamin in a murine COPD model induced by chronic exposure to ozone. Ozone exposure was carried out in C57BL/6 mice twice a week for six weeks for 3 h each time, and the treated group was orally administered deflamin (20 mg/kg body weight) after each ozone exposure. The histological results showed that deflamin attenuated pulmonary emphysema and peribronchial fibrosis, as evidenced by H&E and Masson's trichrome staining. Furthermore, deflamin administration significantly decreased MMP-9 activity, as assessed by fluorogenic substrate assay and gelatin zymography. Interestingly, bioinformatic analysis reveals a plausible interaction between deflamin and MMP-9. Collectively, our findings demonstrate the therapeutic potential of deflamin in a COPD murine model, and suggest that the attenuation of the development of lung tissue damage occurs by deflamin-regulated MMP-9 catalytic activity.

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

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

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

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

Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by >89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct in vitro and in vivo.Communicated by Ramaswamy H. Sarma.

Designing a novel and combinatorial multi-antigenic epitope-based vaccine "MarVax" against Marburg virus-a reverse vaccinology and immunoinformatics approach

CONTEXT

Marburg virus (MARV) is a member of the Filoviridae family and causes Marburg virus disease (MVD) among humans and primates. With fatality rates going up to 88%, there is currently no commercialized cure or vaccine to combat the infection. The National Institute of Allergy and Infectious Diseases (NIAID) classified MARV as priority pathogen A, which presages the need for a vaccine candidate which can provide stable, long-term adaptive immunity. The surface glycoprotein (GP) and fusion protein (FP) mediate the adherence, fusion, and entry of the virus into the host cell via the TIM-I receptor. Being important antigenic determinants, studies reveal that GP and FP are prone to evolutionary mutations, underscoring the requirement of a vaccine construct capable of eliciting a robust and sustained immune response. In this computational study, a reverse vaccinology approach was employed to design a combinatorial vaccine from conserved and antigenic epitopes of essential viral proteins of MARV, namely GP, VP24, VP30, VP35, and VP40 along with an endogenous protein large polymerase (L).

METHODS

Epitopes for T-cell and B-cell were predicted using TepiTool and ElliPro, respectively. The surface-exposed TLRs like TLR2, TLR4, and TLR5 were used to screen high-binding affinity epitopes using the protein-peptide docking platform MdockPeP. The best binding epitopes were selected and assembled with linkers to design a recombinant multi-epitope vaccine construct which was then modeled in Robetta. The in silico biophysical and biochemical analyses of the recombinant vaccine were performed. The docking and MD simulation of the vaccine using WebGro and CABS-Flex against TLRs support the stable binding of vaccine candidates. A virtual immune simulation to check the immediate and long-term immunogenicity was carried out using the C-ImmSim server.

RESULTS

The biochemical characteristics and docking studies with MD simulation establish the recombinant protein vaccine construct MarVax as a stable, antigenic, and potent vaccine molecule. Immune simulation studies reveal 1-year passive immunity which needs to be validated by in vivo studies.

Multi-epitope vaccine candidates based on mycobacterial membrane protein large (MmpL) proteins against Mycobacterium ulcerans

Buruli ulcer (BU) is a neglected tropical disease. It is caused by the bacterium Mycobacterium ulcerans and is characterized by skin lesions. Several studies were performed testing the Bacillus Calmette-Guérin (BCG) vaccine in human and animal models and M. ulcerans-specific vaccines in animal models. However, there are currently no clinically accepted vaccines to prevent M. ulcerans infection. The aim of this study was to identify T-cell and B-cell epitopes from the mycobacterial membrane protein large (MmpL) proteins of M. ulcerans. These epitopes were analysed for properties including antigenicity, immunogenicity, non-allergenicity, non-toxicity, population coverage and the potential to induce cytokines. The final 8 CD8+, 12 CD4+ T-cell and 5 B-cell epitopes were antigenic, non-allergenic and non-toxic. The estimated global population coverage of the CD8+ and CD4+ epitopes was 97.71%. These epitopes were used to construct five multi-epitope vaccine constructs with different adjuvants and linker combinations. The constructs underwent further structural analyses and refinement. The constructs were then docked with Toll-like receptors. Three of the successfully docked complexes were structurally analysed. Two of the docked complexes successfully underwent molecular dynamics simulations (MDS) and post-MDS analysis. The complexes generated were found to be stable. However, experimental validation of the complexes is required.

Mining the ZINC database of natural products for specific, testosterone-like, OXER1 antagonists

OXER1, the receptor for the oxidized arachidonic acid metabolite 5-oxo-ETE has been reported to play a significant role in inflammatory responses, being responsible for leucocyte chemotactic responses. Recently, we have identified OXER1 (GPR170) as a membrane receptor for androgens in prostate and breast cancer cells. Testosterone action via OXER1 induces specific Ca2+ release from intracellular organelles, modifies polymerized actin distribution induces apoptosis and decreases cancer cell migration. These actions are antagonized by 5-oxo-ETE. In addition, 5-oxo-ETE through a Gαi protein decreases cAMP, an action antagonized by testosterone. In this work, we mined the ZINC15 database, using QSAR, for natural compounds able to signal through Gαi and Gβγ simultaneously, mimicking testosterone actions, as well as for specific Gβγ interactors, inhibiting 5-oxo-ETE tumor promoting actions. We were able to identify four druggable Gαβγ and seven Gβγ specific OXER1 interactors. We further confirmed by bio-informatic methods their binding to the 5-oxo-ETE/testosterone binding groove of the receptor, their ADME properties and their possible interaction with other receptor and/or enzyme targets. Two compounds, ZINC04017374 (Naphthofluorescein) and ZINC08589130 (Puertogaline A) were purchased, tested in vitro and confirmed their OXER1 Gβγ and Gαβγ activity, respectively. The methodology followed is useful for a better understanding of the mechanism by which OXER1 mediates its actions, it has the potential to provide structural insights, in order to design small molecular specific interactors and ultimately design new anti-inflammatory and anti-cancer agents. Finally, the methodology may also be useful for identifying specific agonists/antagonists of other GPCRs.

Conserved Domains in Variable Surface Lipoproteins A-G of Mycoplasma hyorhinis May Serve as Probable Multi-Epitope Candidate Vaccine: Computational Reverse Vaccinology Approach

Mycoplasma hyorhinis (M. hyorhinis) is responsible for infections in the swine population. Such infections are usually cured by using antimicrobials and lead to develop resistance. Until now, there has been no effective vaccine to eradicate the disease. This study used conserved domains found in seven members of the variable lipoprotein (VlpA-G) family in order to design a multi-epitope candidate vaccine (MEV) against M. hyorhinis. The immunoinformatics approach was followed to predict epitopes, and a vaccine construct consisting of an adjuvant, two B cell epitopes, two HTL epitopes, and one CTL epitope was designed. The suitability of the vaccine construct was identified by its non-allergen, non-toxic, and antigenic nature. A molecular dynamic simulation was executed to assess the stability of the TLR2 docked structure. An immune simulation showed a high immune response toward the antigen. The protein sequence was reverse-translated, and codons were optimized to gain a high expression level in E. coli. The proposed vaccine construct may be a candidate for a multi-epitope vaccine. Experimental validation is required in future to test the safety and efficacy of the hypothetical candidate vaccine.

Repurposing miconazole and tamoxifen for the treatment of Mycobacterium abscessus complex infections through in silico chemogenomics approach

Drug repositioning is an alternative to overcome the complexity of the drug discovery and approval procedures for the treatment of Mycobacterium abscessus Complex (MABSC) infections that are increasing globally due to the emergency of antimicrobial resistance mechanisms. Here, an in silico chemogenomics approach was performed to compare the sequences from 4942 M. abscessus subsp. abscessus (M. abscessus) proteins with 5258 or 3473 therapeutic targets registered in the DrugBank or Therapeutic Target Database, respectively. This comparison identified 446 drugs or drug candidates whose targets were homologous to M. abscessus proteins. These identified drugs were considered potential inhibitors of MABSC (anti-MABSC activity). Further screening and inspection resulted in the selection of ezetimibe, furosemide, itraconazole, miconazole (MCZ), tamoxifen (TAM), and thiabendazole (THI) for experimental validation. Among them, MCZ and TAM showed minimum inhibitory concentrations (MIC) of 32 and 24 µg mL-1 against M. abscessus, respectively. For M. bolletii and M. massiliense strains, MCZ and TAM showed MICs of 16 and 24 µg mL-1, in this order. Subsequently, the antibacterial activity of MCZ was confirmed in vivo, indicating its potential to reduce the bacterial load in the lungs of infected mice. These results show that MCZ and TAM can serve as molecular scaffolds for the prospective hit-2-lead optimization of new analogs with greater potency, selectivity, and permeability.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Potential of Onchocerca ochengi inosine-5'-monophosphate dehydrogenase (IMPDH) and guanosine-5'-monophosphate oxidoreductase (GMPR) as druggable and vaccine candidates: immunoinformatics screening

Onchocerciasis is a vector-borne disease caused by the filarial nematode Onchocerca volvulus, which is responsible for most of the visual impairments recorded in Africa, Asia and the Americas. It is known that O. volvulus has similar molecular and biological characteristics as Onchocerca ochengi in cattle. This study was designed to screen for immunogenic epitopes and binding pockets of O. ochengi IMPDH and GMPR ligands using immunoinformatic approaches. In this study, a total of 23 B cell epitopes for IMPDH and 7 B cell epitopes for GMPR were predicted using ABCpred tool, Bepipred 2.0 and Kolaskar and Tongaonkar methods. The CD4+ Th computational results showed 16 antigenic epitopes from IMPDH with strong binding affinity for DRB1_0301, DRB3_0101, DRB1_0103 and DRB1_1501 MHC II alleles while 8 antigenic epitopes from GMPR were predicted to bind DRB1_0101 and DRB1_0401 MHC II alleles, respectively. For the CD8+ CTLs analysis, 8 antigenic epitopes from IMPDH showed strong binding affinity to human leukocyte antigen HLA-A*26:01, HLA-A*03:01, HLA-A*24:02 and HLA-A*01:01 MHC I alleles while 2 antigenic epitopes from GMPR showed strong binding affinity to HLA-A*01:01 allele, respectively. The immunogenic B cell and T cell epitopes were further evaluated for antigenicity, non-alllergernicity, toxicity, IFN-gamma, IL4 and IL10. The docking score revealed favorable binding free energy with IMP and MYD scoring the highest binding affinity at -6.6 kcal/mol with IMPDH and -8.3 kcal/mol with GMPR. This study provides valuable insight on IMPDH and GMPR as potential drug targets and for the development of multiple epitope vaccine candidates.Communicated by Ramaswamy H. Sarma.

Identification of AHL Synthase in Desulfovibrio vulgaris Hildenborough Using an In-Silico Methodology

Sulfate-reducing bacteria (SRB) are anaerobic bacteria that form biofilm and induce corrosion on various material surfaces. The quorum sensing (QS) system that employs acyl homoserine lactone (AHL)-type QS molecules primarily govern biofilm formation. Studies on SRB have reported the presence of AHL, but no AHL synthase have been annotated in SRB so far. In this computational study, we used a combination of data mining, multiple sequence alignment (MSA), homology modeling and docking to decode a putative AHL synthase in the model SRB, Desulfovibrio vulgaris Hildenborough (DvH). Through data mining, we shortlisted 111 AHL synthase genes. Conserved domain analysis of 111 AHL synthase genes generated a consensus sequence. Subsequent MSA of the consensus sequence with DvH genome indicated that DVU_2486 (previously uncharacterized protein from acetyltransferase family) is the gene encoding for AHL synthase. Homology modeling revealed the existence of seven α-helices and six β sheets in the DvH AHL synthase. The amalgamated study of hydrophobicity, binding energy, and tunnels and cavities revealed that Leu99, Trp104, Arg139, Trp97, and Tyr36 are the crucial amino acids that govern the catalytic center of this putative synthase. Identifying AHL synthase in DvH would provide more comprehensive knowledge on QS mechanism and help design strategies to control biofilm formation.

In-silico design and evaluation of an epitope-based serotype-independent promising vaccine candidate for highly cross-reactive regions of pneumococcal surface protein A

BACKGROUND

The pathogenicity of pneumococcus with high morbidity, mortality, and multi-drug resistance patterns has been increasing. The limited coverage of the licensed polysaccharide-based vaccines and the replacement of the non-vaccine serotypes are the main reasons for producing a successful serotype-independent vaccine. Pneumococcal surface protein A (PspA) is an extremely important virulence factor and an interesting candidate for conserved protein-based pneumococcal vaccine classified into two prominent families containing five clades. PspA family-elicited immunity is clade-dependent, and the level of the PspA cross-reactivity is restricted to the same family.

METHODS

To cover and overcome the clade-dependent immunity of the PspAs in this study, we designed and tested a PspA_1-5c+p vaccine candidate composed of the highest immunodominant coverage of B- and T-cell epitope truncated domain of each clade focusing on two cross-reactive B and C regions of the PspAs. The antigenicity, toxicity, physicochemical properties, 3D structure prediction, stability and flexibility of the designed protein using molecular dynamic (MD) simulation, molecular docking of the construct withHLADRB1*(01:01) and human lactoferrin N-lop, and immune simulation were assessed using immunoinformatics tools. In the experimental section, after intraperitoneal immunization of the mice with Alum adjuvanted recombinant PspA_1-5c+p, we evaluated the immune response, cross-reactivity, and functionality of the Anti-PspA_1-5c+p antibody using ELISA, Opsonophagocytic killing activity, and serum bactericidal assay.

RESULTS

For the first time, this work suggested a novel PspA-based vaccine candidate using immunoinformatics tools. The designed PspA_1-5c+p protein is predicted to be highly antigenic, non-toxic, soluble, stable with low flexibility in MD simulation, and able to stimulate both humoral and cellular immune responses. The designed protein also could interact strongly with HLADRB1*(01:01) and human lactoferrin N-lop in the docking study. Our immunoinformatics predictions were validated using experimental data. Results showed that the anti-PspA_1-5c+p IgG not only had a high titer with strong and same cross-reactivity coverage against all pneumococcal serotypes used but also had high and effective bioactivity for pneumococcal clearance using complement system and phagocytic cells.

CONCLUSION

Our findings elucidated the potential application of the PspA_1-5c+p vaccine candidate as a serotype-independent pneumococcal vaccine with a strong cross-reactivity feature. Further in-vitro and in-vivo investigations against other PspA clades should be performed to confirm the full protection of the PspA_1-5c+p vaccine candidate.

Using Local Protein Model Quality Estimates to Guide a Molecular Dynamics-Based Refinement Strategy

The refinement of predicted 3D models aims to bring them closer to the native structure by fixing errors including unusual bonds and torsion angles and irregular hydrogen bonding patterns. Refinement approaches based on molecular dynamics (MD) simulations using different types of restraints have performed well since CASP10. ReFOLD, developed by the McGuffin group, was one of the many MD-based refinement approaches, which were tested in CASP 12. When the performance of the ReFOLD method in CASP12 was evaluated, it was observed that ReFOLD suffered from the absence of a reliable guidance mechanism to reach consistent improvement for the quality of predicted 3D models, particularly in the case of template-based modelling (TBM) targets. Therefore, here we propose to utilize the local quality assessment score produced by ModFOLD6 to guide the MD-based refinement approach to further increase the accuracy of the predicted 3D models. The relative performance of the new local quality assessment guided MD-based refinement protocol and the original MD-based protocol ReFOLD are compared utilizing many different official scoring methods. By using the per-residue accuracy (or local quality) score to guide the refinement process, we are able to prevent the refined models from undesired structural deviations, thereby leading to more consistent improvements. This chapter will include a detailed analysis of the performance of the local quality assessment guided MD-based protocol versus that deployed in the original ReFOLD method.

Designing multi-epitope monkeypox virus-specific vaccine using immunoinformatics approach

BACKGROUND

Monkeypox virus is an enveloped DNA virus that belongs to Poxviridae family. The virus is transmitted from rodents to primates via infected body fluids, skin lesions, and respiratory droplets. After being infected with virus, the patients experience fever, myalgia, maculopapular rash, and fluid-filled blisters. It is necessary to differentiate monkeypox virus from other poxviruses during diagnosis which can be appropriately envisioned via DNA analysis from swab samples. During small outbreaks, the virus is treated with therapies administered in other orthopoxviruses infections and does not have its own specific therapy and vaccine. Consequently, in this article, two potential peptides have been designed.

METHODS

For the purpose of designing a vaccine, protein sequences were retrieved followed by the prediction of B- and T-cell epitopes. Afterward, vaccine structures were predicted which were docked with toll-like receptors. The docked complexes were analyzed with iMODS. Moreover, vaccine constructs nucleotide sequences were optimized and expressed in silico.

RESULTS

COP-B7R vaccine construct (V1) has antigenicity score of 0.5400, instability index of 29.33, z-score of - 2.11-, and 42.11% GC content whereas COP-A44L vaccine construct (V2) has an antigenicity score of 0.7784, instability index of 23.33, z-score of - 0.61, and 48.63% GC content. It was also observed that COP-A44L can be expressed as a soluble protein in Escherichia coli as compared to COP-B7R which requires a different expression system.

CONCLUSION

The obtained results revealed that both vaccine constructs show satisfactory outcomes after in silico investigation and have significant potential to prevent the monkeypox virus. However, COP-A44L gave better results.

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 Characterization, Purification, and Mode of Action of Enterocin KAE01 from Lactic Acid Bacteria and Its In Silico Analysis against MDR/ESBL Pseudomonas aeruginosa

Bacteriocins are gaining immense importance in therapeutics since they show significant antibacterial potential. This study reports the bacteriocin KAE01 from Enterococcus faecium, along with its characterization, molecular modeling, and antibacterial potency, by targeting the matrix protein of Pseudomonas aeruginosa. The bacteriocin was purified by using ammonium sulfate precipitation and fast protein liquid chromatography (FPLC), and its molecular weight was estimated as 55 kDa by means of SDS-PAGE. The bacteriocin was found to show stability in a wide range of pH values (2.0-10.0) and temperatures (100 °C for 1 h and 121 °C for 15 min). Antimicrobial screening of the purified peptide against different strains of P. aeruginosa showed its significant antibacterial potential. Scanning electron microscopy of bacteriocin-induced bacterial cultures revealed significant changes in the cellular morphology of the pathogens. In silico molecular modeling of KAE01, followed by molecular docking of the matrix protein (qSA) of P. aeruginosa and KAE01, supported the antibacterial potency and SEM findings of this study.

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.

Recognition motifs for importin 4 [(L)PPRS(G/P)P] and importin 5 [KP(K/Y)LV] binding, identified by bio-informatic simulation and experimental in vitro validation

Nuclear translocation of large proteins is mediated through karyopherins, carrier proteins recognizing specific motifs of cargo proteins, known as nuclear localization signals (NLS). However, only few NLS signals have been reported until now. In the present work, NLS signals for Importins 4 and 5 were identified through an unsupervised in silico approach, followed by experimental in vitro validation. The sequences LPPRS(G/P)P and KP(K/Y)LV were identified and are proposed as recognition motifs for Importins 4 and 5 binding, respectively. They are involved in the trafficking of important proteins into the nucleus. These sequences were validated in the breast cancer cell line T47D, which expresses both Importins 4 and 5. Elucidating the complex relationships of the nuclear transporters and their cargo proteins is very important in better understanding the mechanism of nuclear transport of proteins and laying the foundation for the development of novel therapeutics, targeting specific importins.

A New Combination: Anti Glypican-3 scFv and Diphtheria Toxin with the Best Flexible Linker

Along with all cancer treatments, including chemotherapy, radiotherapy, and surgery, targeting therapy is a new treatment manner. Immunotoxins are new recombinant structures that kill cancer cells by targeting specific antigens. Immunotoxins are composed of two parts: toxin moiety, which disrupts protein synthesis process, and antigen binding moiety that bind to antigens on the surface of cancer cells. Glypican 3 (GPC3) is an oncofetal antigen on the surface of Hepatocellular carcinoma (HCC) cells. In this study, truncated Diphtheria toxin (DT389) was fused to humanized scFv YP7 by one, two and three repeats of GGGGS linkers (DT389-(GGGGS)_1-3YP7). In-silico and experimental investigation were performed to find out how many repeats of linker between toxin and scFv moieties are sufficient. Results of in-silico investigations revealed that the difference in the number of linkers does not have a significant effect on the main structures of the immunotoxin; however, the three-dimensional structure of two repeats of linker had a more appropriate structure compared to others with one and three linker replications. In addition, with enhancing the number of linkers, the probability of protein solubility has increased. Generally, the bioinformatics results of DT389-(GGGGS)₂-YP7 structure showed that expression and folding is suitable; and YP7 scFv has appropriate orientation to bind GPC3. The experimental investigations indicated that the fusion protein was expressed as near to 50% soluble. Due to the high binding affinity of YP7 scFv and the proven potency of diphtheria in inhibiting protein synthesis, the proposed DT389-(GGGGS)₂-YP7 immunotoxin is expected to function well in inhibiting HCC.

Bioinformatics, Computational Informatics, and Modeling Approaches to the Design of mRNA COVID-19 Vaccine Candidates

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response.

An Immunoinformatics Prediction of Novel Multi-Epitope Vaccines Candidate Against Surface Antigens of Nipah Virus

Nipah virus (NiV) is an emerging zoonotic virus causing outbreaks of encephalitis and respiratory illnesses in humans, with high mortality. NiV is considered endemic in Bangladesh and Southeast Asia. There are no licensed vaccines against NiV. This study aimed at predicting a dual-antigen multi-epitope subunit chimeric vaccine against surface-glycoproteins G and F of NiV. Targeted proteins were subjected to immunoinformatics analyses to predict antigenic B-cell and T-cell epitopes. The proposed vaccine designs were implemented based on the conservancy, population coverage, molecular docking, immune simulations, codon adaptation, secondary mRNA structure, and in-silico cloning. Total 40 T and B-cell epitopes were found to be conserved, antigenic (vaxijen-value > 0.4), non-toxic, non-allergenic, and human non-homologous. Of 12 hypothetical vaccines, two (NiV_BGD_V1 and NiV_BGD_V2) were strongly immunogenic, non-allergenic, and structurally stable. The proposed vaccine candidates show a negative Z-score (- 6.32 and - 6.67) and 83.6% and 89.3% of most rama-favored regions. The molecular docking confirmed the highest affinity of NiV_BGD_V1 and NiV_BGD_V2 with TLR-4 (ΔG = - 30.7) and TLR8 (ΔG = - 20.6), respectively. The vaccine constructs demonstrated increased levels of immunoglobulins and cytokines in humans and could be expressed properly using an adenoviral-based pAdTrack-CMV expression vector. However, more experimental investigations and clinical trials are needed to validate its efficacy and safety.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10989-022-10431-z.

Reverse vaccinology approach to design a multi-epitope vaccine construct based on the Mycobacterium tuberculosis biomarker PE_PGRS17

Mycobacterium tuberculosis (Mtb) is responsible for high mortality rates in many low- and middle-income countries. This infectious disease remains accountable for around 1.4 million deaths yearly. Finding effective control measures against Mtb has become imperative. Vaccination has been regarded as the safe and lasting control measure to curtail the impact of Mtb. This study used the Mtb protein biomarker PE_PGRS17 to design a multi-epitope vaccine. A previous study predicted a strong antigenic property of PE_PGRS17. Immunogenic properties such as antigenicity, toxicity, and allergenicity were predicted for the PE_PGRS17 biomarker, specific B- and T-cell epitope sequences, and the final multiple epitope vaccine (MEV) construct. Algorithmic tools predicted the T- and B-cell epitopes and those that met the immunogenic properties were selected to construct the MEV candidate for predicted vaccine development. The epitopes were joined via linkers and an adjuvant was attached to the terminals of the entire vaccine construct. Immunogenic properties, and physicochemical and structural predictions gave insight into the MEV construct. The assembled vaccine candidate was docked with a receptor and validated using web-based tools. An immune simulation was performed to imitate the immune response after exposure to a dosed administrated predicted MEV subunit. An in silico cloning and codon optimisation gave insight into optimal expression conditions regarding the MEV candidate. In conclusion, the generated MEV construct may potentially emit both cellular and humoral responses which are vital in the development of a peptide-based vaccine against Mtb; nonetheless, further experimental validation is still required.

Designing a novel multi‑epitope vaccine against Ebola virus using reverse vaccinology approach

Ebola virus (EBOV) is a dangerous zoonotic infectious disease. To date, more than 25 EBOV outbreaks have been documented, the majority of which have occurred in Central Africa. The rVSVG-ZEBOV-GP vaccine (ERVEBO), a live attenuated vaccine, has been approved by the US Food and Drug Administration (FDA) to combat EBOV. Because of the several drawbacks of live attenuated vaccines, multi-epitope vaccines probably appear to be safer than live attenuated vaccines. In this work, we employed immunoinformatics tools to design a multi-epitope vaccine against EBOV. We collected sequences of VP35, VP24, VP30, VP40, GP, and NP proteins from the NCBI database. T-cell and linear B-cell epitopes from target proteins were identified and tested for antigenicity, toxicity, allergenicity, and conservancy. The selected epitopes were then linked together in the vaccine's primary structure using appropriate linkers, and the 50S ribosomal L7/L12 (Locus RL7 MYCTU) sequence was added as an adjuvant to the vaccine construct's N-terminal. The physicochemical, antigenicity, and allergenicity parameters of the vaccine were all found to be satisfactory. The 3D model of the vaccine was predicted, refined, and validated. The vaccine construct had a stable and strong interaction with toll-like receptor 4 (TLR4) based on molecular docking and molecular dynamic simulation (MD) analysis. The results of codon optimization and in silico cloning revealed that the proposed vaccine was highly expressed in Escherichia coli (E. coli). The findings of this study are promising; however, experimental validations should be carried out to confirm these findings.

Molecular cloning, expression in Escherichia coli and structural-functional analysis of a pyruvate kinase from Pyrobaculum calidifontis

This manuscript describes recombinant production, characterization and structural analysis of wild-type and mutant Pcal_0029, a pyruvate kinase from Pyrobaculum calidifontis. Recombinant Pcal_0029 was produced in soluble and highly active form in Escherichia coli. Purified protein exhibited divalent metal-dependent activity which increased with the increase in temperature till 85 °C. Recombinant Pcal_0029 was highly thermostable with no significant loss in activity even after an incubation of 120 min at 100 °C. The enzyme exhibited apparent S_0.5 and V_max values of 0.44 ± 0.05 mM and 840 ± 39 units, respectively, towards phosphoenolpyruvate. These values towards adenosine-5'-diphosphate were 0.5 ± 0.07 mM and 870 ± 26 units, respectively. In silico structural analysis and comparison with the characterized enzymes revealed the presence of eight conserved regions. Two substitutions, K130E and S155G, resulted in a 10-fold decrease in activity. Secondary structure analysis indicated similar structures for the wild-type and the mutant enzymes. Bioinformatics analysis revealed disruption of interatomic interactions and hydrogen bond formation, leading to a decreased flexibility and solvent accessibility, which may have led to decrease in activity. To the best of our knowledge, Pcal_0029 is the most thermostable pyruvate kinase reported so far. Moreover, this is the first study on the role of non-catalytic residues in a pyruvate kinase.

A Vaccine Construction against COVID-19-Associated Mucormycosis Contrived with Immunoinformatics-Based Scavenging of Potential Mucoralean Epitopes

Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92-98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of -896.0, -948.4, and -925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.

Immmunoinformatics-based design of a multi-epitope vaccine with CTLA-4 extracellular domain to combat Helicobacter pylori

In view of the high infection rate of Helicobacter pylori, a safe and effective vaccine is urgently needed. Recent trends in vaccine design have shifted toward safe and specific epitope-based vaccines. In this study, by using different immunoinformatics approaches, a total of eight linear B cell epitopes, four HTL and three CTL epitopes of FlaA and UreB proteins of H. pylori G27 strain were screened out, we also predicted the conformational epitopes of the two proteins. Then, the dominant epitopes were sequentially linked by appropriate linkers, and the cytotoxic T lymphocyte-associated antigen 4 extracellular domain was attached to the N-terminal of the epitope sequence. Meanwhile, molecular docking, molecular dynamics simulations and principal component analysis were performed to show that the multi-epitope vaccine structure had strong interactions with B7 (B7-1, B7-2) and Toll-like receptors (TLR-2, -4). Eventually, the effectiveness of the vaccine was validated using in silico cloning. These analyses suggested that the designed vaccine could target antigen-presenting cells and had high potency against H. pylori, which could provide a reference for the future development of efficient H. pylori vaccines.

Evaluation of model refinement in CASP14

We report here an assessment of the model refinement category of the 14th round of Critical Assessment of Structure Prediction (CASP14). As before, predictors submitted up to five ranked refinements, along with associated residue-level error estimates, for targets that had a wide range of starting quality. The ability of groups to accurately rank their submissions and to predict coordinate error varied widely. Overall, only four groups out-performed a "naïve predictor" corresponding to the resubmission of the starting model. Among the top groups, there are interesting differences of approach and in the spread of improvements seen: some methods are more conservative, others more adventurous. Some targets were "double-barreled" for which predictors were offered a high-quality AlphaFold 2 (AF2)-derived prediction alongside another of lower quality. The AF2-derived models were largely unimprovable, many of their apparent errors being found to reside at domain and, especially, crystal lattice contacts. Refinement is shown to have a mixed impact overall on structure-based function annotation methods to predict nucleic acid binding, spot catalytic sites, and dock protein structures.

Physics-based protein structure refinement in the era of artificial intelligence

Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement protocol based on an improved sampling strategy via MD simulations. MD simulations were carried out at an elevated temperature (360 K). An optimized use of biasing restraints and the use of multiple starting models led to enhanced sampling. The new protocol generally improved the model quality. In comparison with our previous protocols, the CASP14 protocol showed clear improvements. Our approach was successful with most initial models, many based on deep learning methods. However, we found that our approach was not able to refine machine-learning models from the AlphaFold2 group, often decreasing already high initial qualities. To better understand the role of refinement given new types of models based on machine-learning, a detailed analysis via MD simulations and Markov state modeling is presented here. We continue to find that MD-based refinement has the potential to improve AI predictions. We also identified several practical issues that make it difficult to realize that potential. Increasingly important is the consideration of inter-domain and oligomeric contacts in simulations; the presence of large kinetic barriers in refinement pathways also continues to present challenges. Finally, we provide a perspective on how physics-based refinement could continue to play a role in the future for improving initial predictions based on machine learning-based methods.

New Antagonists of the Membrane Androgen Receptor OXER1 from the ZINC Natural Product Database

OXER1 (oxoeicosanoid receptor 1) was deorphanized in 1993 and found to be the specific receptor for the arachidonic acid metabolite 5-oxo-ETE. Recently, we have reported that androgen binds to this receptor also, being a membrane androgen receptor, triggering a number of its membrane-mediated actions (cell migration, apoptosis, cell proliferation, Ca²⁺ movements). In addition, our previous work suggested that a number of natural monomeric and oligomeric polyphenols interact with OXER1, acting similar to testosterone. Here, we interrogated the natural product chemical space and identified nine polyphenolic molecules with interesting in silico pharmacological activities as putative OXER1 antagonists. The molecule with the best pharmacokinetic-pharmacodynamic properties (ZINC15959779) was purchased and tested on OXER1, in prostate cancer cell cultures. It showed that it has actions similar to those of testosterone in inhibiting cAMP, while it had no action in intracellular Ca²⁺ mobilization or actin cytoskeleton rearrangement/migration. These results are discussed under the prism of structure-activity relationships and in silico models of the OXER1 binding groove. We suggest that these compounds, together with the previously reported (poly)phenolic compounds, can be lead structures for the exploration of the anti-inflammatory and antiproliferative effects of OXER1 antagonists.

Current approaches to flexible loop modeling

Loops are key components of protein structures, involved in many biological functions. Due to their conformational variability, the structural investigation of loops is a difficult topic, requiring a combination of experimental and computational methods. This paper provides a brief overview of current computational approaches to flexible loop modeling, and presents the main ingredients of the most standard protocols. Despite great progress in recent years, accurately modeling the conformational variability of long flexible loops remains a challenging problem. Future advances in this field will likely come from a tight coupling of experimental and computational techniques, which would enable a better understanding of the relationships between loop sequence, structural flexibility, and functional roles. In fine, accurate loop modeling will open the road to loop design problems of interest for applications in biomedicine and biotechnology.

p-cymene impairs SARS-CoV-2 and Influenza A (H1N1) viral replication: In silico predicted interaction with SARS-CoV-2 nucleocapsid protein and H1N1 nucleoprotein

Therapeutic regimens for the COVID-19 pandemics remain unmet. In this line, repurposing of existing drugs against known or predicted SARS-CoV-2 protein actions have been advanced, while natural products have also been tested. Here, we propose that p-cymene, a natural monoterpene, can act as a potential novel agent for the treatment of SARS-CoV-2-induced COVID-19 and other RNA-virus-induced diseases (influenza, rabies, Ebola). We show by extensive molecular simulations that SARS-CoV-2 C-terminal structured domain contains a nuclear localization signal (NLS), like SARS-CoV, on which p-cymene binds with low micromolar affinity, impairing nuclear translocation of this protein and inhibiting viral replication, as verified by preliminary in vitro experiments. A similar mechanism may occur in other RNA-viruses (influenza, rabies and Ebola), also verified in vitro for influenza, by interaction of p-cymene with viral nucleoproteins, and structural modification of their NLS site, weakening its interaction with importin A. This common mechanism of action renders therefore p-cymene as a possible antiviral, alone, or in combination with other agents, in a broad spectrum of RNA viruses, from SARS-CoV-2 to influenza A infections.

In Silico Design and Immunological Studies of Two Novel Multiepitope DNA-Based Vaccine Candidates Against High-Risk Human Papillomaviruses

Human papillomaviruses (HPV)-16 and 18 are the most prevalent types associated with cervical cancer. HPV L1 and L2 capsid proteins and E7 oncoprotein play crucial roles in HPV-related diseases. Hence, these proteins were proposed as target antigens for preventive and therapeutic vaccines. In this study, two multiepitope DNA-based HPV vaccine candidates were designed using in silico analysis including the immunogenic and conserved epitopes of HPV16/18 L1, L2 and E7 proteins (the L1-L2-E7 fusion DNA), and of heat shock protein 70 (HSP70) linked to the L1-L2-E7 DNA construct (the HSP70-L1-L2-E7 fusion DNA). Next, the expression of the L1-L2-E7 and HSP70-L1-L2-E7 multiepitope DNA constructs was evaluated in a mammalian cell line. Finally, immunological responses and antitumor effects of the DNA constructs were investigated in C57BL/6 mice. Our data indicated high expression rates of the designed multiepitope L1-L2-E7 DNA (~ 56.16%) and HSP70-L1-L2-E7 DNA (~ 80.45%) constructs in vitro. The linkage of HSP70 epitopes to the L1-L2-E7 DNA construct significantly increased the gene expression. Moreover, the HSP70-L1-L2-E7 DNA construct could significantly increase immune responses toward Th1 response and CTL activity, and induce stronger antitumor effects in mouse model. Thus, the designed HSP70-L1-L2-E7 DNA construct represents promising results for development of HPV DNA vaccine candidates.

Computational insights into the identification of a potent matrix metalloproteinase inhibitor from Indigofera aspalathoides to control cancer metastasis

Matrix metalloproteinases (MMPs) are the major proteolytic enzymes which assist in regulating the metastatic process by degrading the extracellular matrix proteins. In this study, we have investigated the anti-metastatic potential of major bioactive compounds in the medicinal plant Indigofera aspalathoides targeting matrix metalloproteinases (MMP2 & MMP9) and it's in silico pharmacokinetic profiles using computational studies. Indigofera aspalathoides (Sivanar vembu in Tamil) is a renowned medicinal herb in traditional Indian medicine which contains indigocarpan, mucronulatol, indigocarpan diacetate, erythroxydiol X and erythroxydiol Y as the major constituents. The 3-dimensional structure of MMP2 and MMP9 was designed by using I-tasser and Modeller and it was validated by PROCHECK. The structures of mucronulatol and indigocarpan have been retrieved from PubChem and indigocarpan diacetate, erythroxydiol X & Y were drawn by using Chemdraw Ultra 6.0. Batimastat was used as a positive control. Molecular docking was performed by using AutoDock 4.2 tools and AutoDock vina, an open-source program which signifies an effective interaction between the phytoligands and MMP2 & MMP9. From the results, AutoDock 4.2 have showed that indigocarpan possesses strong binding energy (ΔG) of - 7.68 kcal/mol towards MMP2 and - 6.35 kcal/mol towards MMP9, whereas batimastat showed binding energy (ΔG) of - 6.34 kcal/mol for MMP2 and - 5.66 kcal/mol for MMP9, meanwhile the results from AutoDock vina indicates that indigocarpan possesses strong binding energy (ΔG) of - 8.0 kcal/mol towards MMP2 and - 8.2 kcal/mol towards MMP9, whereas batimastat showed binding energy (ΔG) of - 7.2 kcal/mol for MMP2 and - 7.6 kcal/mol for MMP9. Also, the ADME and toxicity results suggest that the indigocarpan compound possesses a druggable pharmacokinetic potentiality and does not have carcinogenicity and Ames mutagenesis compared with other phytoligands. Hence, it is evident from our results that both AutoDock platforms strongly revealed that the phytoligand, indigocarpan possesses strong inhibitory activity against MMP2 and MMP9 to control cancer metastasis.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02731-w.

Computational exploration of vicine - an alkaloid glycoside mediated pathological hallmark of adenosine kinase to promote neurological disorder

Epilepsy disease is characterized by the neuronal dysfunction or abnormal neuronal activity of the brain which is regulated by astrocytes. These are glial cells and found to be the major regulators of the brain which are guided by the occurrence of adenosine kinase (ADK) enzyme in the central nervous system (CNS). During the normal physiological environment, ADK maintains the level of adenosine in the CNS. Dysfunction of ADK levels results in accumulation of adenosine levels in the CNS that leads to the pathophysiology of the brain such as astrogliosis which is a pathological hallmark of epileptic seizures. Vicine, an alkaloid glycoside in bitter gourd juice (Momordica charantia) is found to be toxic to the human system if the bitter gourd juice is consumed more. This compound inhibits ADK enzyme activity to lead epilepsy and seizure. Here, the toxic effect of vicine targeting ADK using computational predictions was investigated. The 3-dimensional structure of ADK has been constructed using I-Tasser, which has been refined by ModRefiner, GalaxyRefine, and 3D refine and it was endorsed using PROCHECK, ERRAT, and VADAR. 3D structure of the ligand molecule has been obtained from PubChem. Molecular docking has been achieved using AutoDock 4.2 software, from which the outcome showed the effective interaction between vicine and ADK, which attains binding free energy (∆G) of - 4.13 kcal/mol. Vicine molecule interacts with the active region ARG 149 of ADK and inhibits the functions of ADK that may cause imbalance in energy homeostasis. Also, pre-ADMET results robustly propose in which vicine possesses toxicity, and meanwhile, from the Ames test, it was shown as mutagenic. Hence, the results from our study suggest that vicine was shown to be toxic that suppresses the ADK activity to undergo pathological conditions in the neuronal junctions to lead epilepsy.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

The sequence [EKRKI(E/R)(K/L/R/S/T)] is a nuclear localization signal for importin 7 binding (NLS7)

BACKGROUND

Nuclear translocation of large proteins is mediated through specific protein carriers, collectively named karyopherins (importins, exportins and adaptor proteins). Cargo proteins are recognized by importins through specific motifs, known as nuclear localization signals (NLS). However, only the NLS recognized by importin α and transportin (M9 NLS) have been identified so far METHODS: An unsupervised in silico approach was used, followed by experimental validation.

RESULTS

We identified the sequence EKRKI(E/R)(K/L/R/S/T) as an NLS signal for importin 7 recognition. This sequence was validated in the breast cancer cell line T47D, which expresses importin 7. Finally, we verified that importin 7-mediated nuclear protein transport is affected by cargo protein phosphorylation.

CONCLUSIONS

The NLS sequence for importin 7 was identified and we propose this approach as an identification method of novel specific NLS sequences for β-karyopherin family members.

GENERAL SIGNIFICANCE

Elucidating the complex relationships of the nuclear transporters and their cargo proteins may help in laying the foundation for the development of novel therapeutics, targeting specific importins, with an immediate translational impact.

A computational approach to design potential siRNA molecules as a prospective tool for silencing nucleocapsid phosphoprotein and surface glycoprotein gene of SARS-CoV-2

An outbreak, caused by an RNA virus, SARS-CoV-2 named COVID-19 has become pandemic with a magnitude which is daunting to all public health institutions in the absence of specific antiviral treatment. Surface glycoprotein and nucleocapsid phosphoprotein are two important proteins of this virus facilitating its entry into host cell and genome replication. Small interfering RNA (siRNA) is a prospective tool of the RNA interference (RNAi) pathway for the control of human viral infections by suppressing viral gene expression through hybridization and neutralization of target complementary mRNA. So, in this study, the power of RNA interference technology was harnessed to develop siRNA molecules against specific target genes namely, nucleocapsid phosphoprotein gene and surface glycoprotein gene. Conserved sequence from 139 SARS-CoV-2 strains from around the globe was collected to construct 78 siRNA that can inactivate nucleocapsid phosphoprotein and surface glycoprotein genes. Finally, based on GC content, free energy of folding, free energy of binding, melting temperature, efficacy prediction and molecular docking analysis, 8 siRNA molecules were selected which are proposed to exert the best action. These predicted siRNAs should effectively silence the genes of SARS-CoV-2 during siRNA mediated treatment assisting in the response against SARS-CoV-2.

Functional and structural analyses for MlrC enzyme of Novosphingobium sp. THN1 in microcystin-biodegradation: Involving optimized heterologous expression, bioinformatics and site-directed mutagenesis

Enzymatic function of MlrC from Novosphingobium sp. THN1 (i.e., THN1-MlrC) towards linearized microcystins (MCs) and structural/physic-chemical properties of MlrC enzyme deserved urgent research, and heterologous expression (HE) optimization for MlrC is yet to be solved. This study achieved HE of THN1-MlrC by rapid-efficiently constructing HE system, and revealed that THN1-MlrC can degrade linearized MC-LR and linearized MC-RR to produce Adda, providing direct evidence for catalytic function of THN-MlrC and its ecological implication in MC-detoxification. Consequently, to maximize THN1-MlrC expression for production and application, induction conditions for HE of THN1-MlrC was optimized as at 0.1 mM of isopropyl-β-_D-thiogalactoside and 30 °C for 8 h, which could be widely applicable for heterologous production of other MlrC homologs. Using bioinformatics and site-mutation experiment, THN1-MlrC was evaluated as a cytoplasm-locating hydrophilic protein with theoretical isoelectric point of 5.57, and contained six verified active sites Glu³⁹, His¹³³, Asp¹⁶⁷, His¹⁶⁹, His¹⁹¹ and Asp³³² in two domains of its 3D structure, among which Glu³⁹, His¹³³ and Asp³³² were newly-discovered ones here. The Glu³⁹, His¹³³, Asp¹⁶⁷, His¹⁶⁹ and His¹⁹¹ gathered more closely in 3D structure than in amino acid sequence, while they and Asp³³² surrounded protein center to constitute a potential active pocket for mediating linearized MCs degradation. Due to MlrC sequence homology and conservative active sites, structural/physic-chemical characteristics of THN1-MlrC presented in this study provided a helpful reference for other MlrC homologs of diverse bacteria. This study shed novel insights for functional-structural relationships of THN1-MlrC during MC-biodegradation, and was crucial for research and practical applications in MC-decontamination.

A simple open source bioinformatic methodology for initial exploration of GPCR ligands' agonistic/antagonistic properties

Drug development is an arduous procedure, necessitating testing the interaction of a large number of potential candidates with potential interacting (macro)molecules. Therefore, any method which could provide an initial screening of potential candidate drugs might be of interest for the acceleration of the procedure, by highlighting interesting compounds, prior to in vitro and in vivo validation. In this line, we present a method which may identify potential hits, with agonistic and/or antagonistic properties on GPCR receptors, integrating the knowledge on signaling events triggered by receptor activation (GPCRs binding to Gα,β,γ proteins, and activating Gα , exchanging GDP for GTP, leading to a decreased affinity of the Gα for the GPCR). We show that, by integrating GPCR-ligand and Gα -GDP or -GTP binding in docking simulation, which correctly predicts crystallographic data, we can discriminate agonists, partial agonists, and antagonists, through a linear function, based on the ΔG (Gibbs-free energy) of liganded-GPCR/Gα -GDP. We built our model using two Gαs (β2-adrenergic and prostaglandin-D2 ), four Gαi (μ-opioid, dopamine-D3, adenosine-A1, rhodopsin), and one Gαo (serotonin) receptors and validated it with a series of ligands on a recently deorphanized Gαi receptor (OXER1). This approach could be a valuable tool for initial in silico validation and design of GPRC-interacting ligands.

A computational approach to validate novel drug targets of gentianine from Swertiya chirayita in Plasmodium falciparum

Gentianine is one of the compounds found in the plant Swertiya chirayita that is known for its antimalarial activity. However, its exact molecular mechanism of action is yet to be understood. In our present study, we applied several computational approaches to filter out and determine possible targets of gentianine in Plasmodium falciparum 3D7. Protein-protein networks formed the basis of one of our strategies along with orthologous protein analysis to establish essentiality. Out of 6 essential proteins from unique pathways, haloacid dehalogenase like-hydrolase (PfHAD1), phosphoenolpyruvate carboxykinase (PfPEPCK) and fumarate hydratase (PfFH) were screened as drug targets through this approach. Through our other strategy we established the predicted IC50 (PIC50) value of gentianine with a set of molecular descriptors from 123 Pathogen Box anti-malarial compounds. Afterwards through 2D structural similarity, L-lactate dehydrogenase (PfLDH) was established as another possible target. In our work, we performed in silico docking and analysed the binding of gentianine to the proteins. All of the proteins were reported with favourable binding results and were considered for complex molecular dynamics simulation approach. Our research clears up the molecular mechanism of antimalarial activity of gentianine to some extent paving way for experimental validation of the same in future.

refineD: improved protein structure refinement using machine learning based restrained relaxation

MOTIVATION

Protein structure refinement aims to bring moderately accurate template-based protein models closer to the native state through conformational sampling. However, guiding the sampling towards the native state by effectively using restraints remains a major issue in structure refinement.

RESULTS

Here, we develop a machine learning based restrained relaxation protocol that uses deep discriminative learning based binary classifiers to predict multi-resolution probabilistic restraints from the starting structure and subsequently converts these restraints to be integrated into Rosetta all-atom energy function as additional scoring terms during structure refinement. We use four restraint resolutions as adopted in GDT-HA (0.5, 1, 2 and 4 Å), centered on the Cα atom of each residue that are predicted by ensemble of four deep discriminative classifiers trained using combinations of sequence and structure-derived features as well as several energy terms from Rosetta centroid scoring function. The proposed method, refineD, has been found to produce consistent and substantial structural refinement through the use of cumulative and non-cumulative restraints on 150 benchmarking targets. refineD outperforms unrestrained relaxation strategy or relaxation that is restrained to starting structures using the FastRelax application of Rosetta or atomic-level energy minimization based ModRefiner method as well as molecular dynamics (MD) simulation based FG-MD protocol. Furthermore, by adjusting restraint resolutions, the method addresses the tradeoff that exists between degree and consistency of refinement. These results demonstrate a promising new avenue for improving accuracy of template-based protein models by effectively guiding conformational sampling during structure refinement through the use of machine learning based restraints.

AVAILABILITY AND IMPLEMENTATION

http://watson.cse.eng.auburn.edu/refineD/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DaReUS-Loop: a web server to model multiple loops in homology models

Loop regions in protein structures often have crucial roles, and they are much more variable in sequence and structure than other regions. In homology modeling, this leads to larger deviations from the homologous templates, and loop modeling of homology models remains an open problem. To address this issue, we have previously developed the DaReUS-Loop protocol, leading to significant improvement over existing methods. Here, a DaReUS-Loop web server is presented, providing an automated platform for modeling or remodeling loops in the context of homology models. This is the first web server accepting a protein with up to 20 loop regions, and modeling them all in parallel. It also provides a prediction confidence level that corresponds to the expected accuracy of the loops. DaReUS-Loop facilitates the analysis of the results through its interactive graphical interface and is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/DaReUS-Loop/.