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.

Leveraging protein language model embeddings and logistic regression for efficient and accurate in-silico acidophilic proteins classification.

The increasing demand for eco-friendly technologies in biotechnology necessitates effective and sustainable catalysts. Acidophilic proteins, functioning optimally in highly acidic environments, hold immense promise for various applications, including food production, biofuels, and bioremediation. However, limited knowledge about these proteins hinders their exploration. This study addresses this gap by employing in silico methods utilizing computational tools and machine learning. We propose a novel approach to predict acidophilic proteins using protein language models (PLMs), accelerating discovery without extensive lab work. Our investigation highlights the potential of PLMs in understanding and harnessing acidophilic proteins for scientific and industrial advancements. We introduce the ACE model, which combines a simple Logistic Regression model with embeddings derived from protein sequences processed by the ProtT5 PLM. This model achieves high performance on an independent test set, with accuracy (0.91), F1-score (0.93), and Matthew's correlation coefficient (0.76). To our knowledge, this is the first application of pre-trained PLM embeddings for acidophilic protein classification. The ACE model serves as a powerful tool for exploring protein acidophilicity, paving the way for future advancements in protein design and engineering.

Green synthesis of copper ions nanoparticles functionalized with rhamnolipid as potential antibacterial agent for pathogenic bacteria.

Copper-based nanoparticles possess broad-spectrum antibacterial activity against both gram-positive and gram-negative bacteria, making them a cost-effective alternative to other metal-based nanoparticles. The development of eco-friendly copper based nanopaticles using biodegradable and non-toxic biosurfactants, such as rhamnolipid is being explored in this study. In the present study, Cu(I)-rhamnolipid nanoparticles (Cu(I)-Rl Nps) was prepared by coprecipitation method. The structural analysis by using FTIR and XRD techniques revealed that Cu(I)-Rl Nps was successfully produced, as indicated by the detectable of ionic and covalent-coordinations bond between rhamnolipid and Cu(I) ions. Further analysis using TEM, PSA and ZPA suggest that the resulted Cu(I)-Rl Nps have spherical shape with the diameter range of 141.7-536.3 nm and the surface charge of -30 mV, respectively. The antibacterial activity of Cu(I)-Rl Nps surpassed that of the copper-based nanoparticles, free-state Cu(I) ions and rhamnolipid, which was determined by MIC/MBC methods. The Cu(I)-Rl Nps inhibition to the growth of Bacillus subtilis ATCC 6633 (Gram-positive) gave the MIC/MBC values of 19/19 µg/mL, while the copper-based nanoparticles, free-state Cu(I) ions and rhamnolipid gave the MIC/MBC value of 1250/2500, 1250/1250, 62/62 µg/mL, respectively. Further test on Escherichia coli ATCC 6538 (Gram-negative) showed that the Cu(I)-Rl Nps gave the MIC/MBC value of 78/78 µg/mL, while the copper-based nanoparticles, free-state Cu(I) ions and rhamnolipid gave the MIC/MBC value of 2500/2500, 2500/2500, 2000/2000 µg/mL, respectively. The increased antibacterial activity of Cu(I)-Rl Nps was due to the synergistic effects between Cu(I) and rhamnolipid.

Classifying alkaliphilic proteins using embeddings from protein language model.

Alkaliphilic proteins have great potential as biocatalysts in biotechnology, especially for enzyme engineering. Extensive research has focused on exploring the enzymatic potential of alkaliphiles and characterizing alkaliphilic proteins. However, the current method employed for identifying these proteins that requires web lab experiment is time-consuming, labor-intensive, and expensive. Therefore, the development of a computational method for alkaliphilic protein identification would be invaluable for protein engineering and design. In this study, we present a novel approach that uses embeddings from a protein language model called ESM-2(3B) in a deep learning framework to classify alkaliphilic and non-alkaliphilic proteins. To our knowledge, this is the first attempt to employ embeddings from a pre-trained protein language model to classify alkaliphilic protein. A reliable dataset comprising 1,002 alkaliphilic and 1,866 non-alkaliphilic proteins was constructed for training and testing the proposed model. The proposed model, dubbed ALPACA, achieves performance scores of 0.88, 0.84, and 0.75 for accuracy, f1-score, and Matthew correlation coefficient respectively on independent dataset. ALPACA is likely to serve as a valuable resource for exploring protein alkalinity and its role in protein design and engineering.

Synthesis of pyridinium-based ionic liquids and their application to improve Candida rugosa lipase stability in a methanol-water solvent system.

This paper studied the effect of pyridinium-based ionic liquids as cosolvents in a methanol-water solvent system on the hydrolytic activity of Candida rugosa lipase. These ionic liquids were successfully synthesized using imidazolium-based ionic liquid synthesizing methods with a certain adjustment. The hydrolytic activity of Candida rugosa lipase was analyzed using 4-nitrophenol acetate (pNPA) and 4-nitrophenol palmitate (pNPP) as substrates. The addition of ionic liquids had no significant effect on the hydrolytic activity of lipase in a water solvent, and it had a greater effect in methanol. The addition of [C6Py] Br ionic liquid as a methanol cosolvent (methanol: ionic liquid, 10:5) could increase the hydrolytic activity of lipase. The use of ionic liquid as a cosolvent could increase the hydrolytic activity of lipase by about 15.61% while using pNPP as a substrate in the methanol system. A molecular dynamics study for the interaction between lipase and ionic liquids supported the experimental results. The ionic liquid using bromide as an anion provided more stability on lipase conformation. It tends to form the short-range interaction between the lipase and bromide anion.

Graphene quantum dots functionalised with rhamnolipid produced from bioconversion of palm kernel oil by Pseudomonas stutzeri BK-AB12MT as a photocatalyst.

Methylene blue (MB) is a common organic dye found in textile wastewater and can harm the environment. Rhamnolipid-functionalized graphene quantum dots (RL-GQDs) are a newly developed eco-friendly photocatalyst to degrade MB. This photocatalyst is synthesized from graphene quantum dots (GQDs) and rhamnolipid. GQDs are already promising visible-light photocatalysts to degrade organic dyes. However, GQDs are not promising photocatalysts due to their reusability and photocatalytic performance. In this work, we used rhamnolipid to modify GQDs' structure and enhance their photocatalytic performance. The rhamnolipid used in this work was produced from bioconversion of palm kernel oil by mutated bacterial cells of Pseudomonas stutzeri BK-AB12MT. Meanwhile, GQDs were synthesized using the bottom-up method by pyrolysing citric acid. Transmission electron microscopy and Fourier-Transform Infrared spectroscopy were used to characterize these hybrid materials. These characterization techniques verified the formation of RL-GQDs. To prove the photocatalytic performance of RL-GQDs, we investigated the photocatalytic activity under visible light compared to some common photocatalysts, such as zinc oxide and titanium dioxide. Our findings showed that RL-GQDs could be applied as an eco-friendly photocatalyst to replace TiO2 with a degradation efficiency of 59% ± 3% under visible light irradiation, higher than TiO2.

BiCaps-DBP: Predicting DNA-binding proteins from protein sequences using Bi-LSTM and a 1D-capsule network.

Predicting DNA-binding proteins (DBPs) based solely on primary sequences is one of the most challenging problems in genome annotation. DBPs play a crucial role in various biological processes, including DNA replication, transcription, repair, and splicing. Some DBPs are essential in pharmaceutical research on various human cancers and autoimmune diseases. Existing experimental methods for identifying DBPs are time-consuming and costly. Therefore, developing a rapid and accurate computational technique is necessary to address the issue. This study introduces BiCaps-DBP, a deep learning-based method that improves DBP prediction performance by combining bidirectional long short-term memory with a 1D-capsule network. This study uses three training and independent datasets to evaluate the proposed model's generalizability and robustness. Based on three independent datasets, BiCaps-DBP achieved 1.05%, 5.79% and 0.40% higher accuracies than an existing predictor for PDB2272, PDB186 and PDB20000, respectively. These outcomes indicate that the proposed method is a promising DBP predictor.

Development of Chimeric Hepatitis B (HBV) - Norovirus (NoV) P particle as candidate vaccine against Hepatitis B and norovirus infection.

Introduction: Hepatitis B remains a global problem with no effective treatment. Here, a mucosal vaccine candidate was developed with HBsAg and HBcAg, to provide both prophylactic and therapeutic protection against hepatitis B. The antigens were presented using the P particle of human norovirus (HuNov). As a result, the chimeric HBV - HuNoV P particle can act as a dual vaccine for hepatitis B and HuNoV. Methods: The vaccine candidate was expressed and purified from Escherichia coli BL21 (DE3) cells. HBV-HuNoV chimeric P particles were successfully expressed and isolated, with sizes of approximately 25.64 nm. Then, the HBV-HuNoV chimeric P particles were evaluated for safety and immunogenicity in mice and gnotobiotic (Gn) pigs. After three doses (5 µg/dose in mice and 200 µg/dose in Gn pigs) of intranasal immunization, humoral and cellular immune responses, as well as toxicity, were evaluated. Results: The vaccine candidate induced strong HBV-HuNoV specific IFN-γ producing T-cell responses in the ileum, spleen, and blood of Gn pigs. Serum IgG and IgA antibodies against HBV-HuNoV chimeric P particles also increased significantly in Gn pigs. Increased HBsAg- and HuNoV-specific serum IgG responses were observed in mice and Gn pigs, although not statistically significant. The vaccine candidate did not show any toxicity in mice. Conclusions: In summary, the chimeric HBV-HuNoV P particle vaccine given intranasally was safe and induced strong cellular and humoral immune responses in Gn pig. Modifications to the vaccine structure and dosage need to be evaluated in future studies to further enhance immunogenicity and induce more balanced humoral and cellular responses.

Box-Wilson Design for Optimization of in vitro Levan Production and Levan Application as Antioxidant and Antibacterial Agents.

Background: Levan or fructan, a polysaccharide of fructose, is widely used in various commercial industries. Levan could be produced by many organisms, including plants and bacteria. The cloning of the gene from Bacillus licheniformis, which expressed levansucrase in Escherichia coli host, was carried out successfully. In the present study, we performed the in vitro production of levan and analyzed its potential application as antibacterial and antioxidant agents. Methods: In vitro levan production catalyzed by heterologous-expressed levansucrase Lsbl-bk1 and Lsbl-bk2 was optimized with Box-Wilson design. The antibacterial activity of the produced levan was carried out using agar well diffusion method, while its antioxidant activity was tested by free radical scavenging assays. Results: The optimum conditions for levan production were observed at 36 °C and pH 7 in 12% (w/v) sucrose for levansucrase Lsbl-bk1, while the optimum catalysis of levansucrase Lsbl-bk2 was obtained at 32 oC and pH 8 in the same sucrose concentration. The in vitro synthesized levan showed an antibacterial activity within a concentration range of 10-20% (w/v) against Staphylococcus aureus, E. coli, and Pseudomonas aeruginosa. The same levan was also able to inhibit the 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity with the antioxidant strength of 75% compared to ascorbic acid inhibition. Conclusion: Our study, therefore, shows that the optimized heterologous expression of levansucrases encoded by Lsbl-bk1 and Lsbl-bk2 could open the way for industrial levan production as an antibacterial and antioxidant agent.

Enhancement of antioxidant activity of levan through the formation of nanoparticle systems with metal ions.

Levan, a natural polymer, is widely used in biomedical applications, such as antioxidants, anti-inflammatory, and anti-tumor. The present study aimed to enhance the antioxidant activity of levan by combining it with various metal ions in the nanoparticle (NP) system. Levansucrase encoding gene from Bacillus licheniformis BK1 has been inserted into an expression vector and the obtained recombinant was labeled as Lsbl-bk1 (accession number MF774877.1). That enzyme was used for in vitro levan synthesis in 12% (w/v) sucrose as a substrate and about 4.28 mg/mL of levan was obtained. Levan-based metal ion NPs were synthesized using the coprecipitation method. In the production of NPs, levan acts as a reducing and stabilizing agent. Four types of levan-based metal ion NPs were synthesized, namely, levan-Fe2+ NPs, levan-Cu+ NPs, levan-Co2+ NPs, and levan-Zn2+ NPs. The transmission electron microscopy (TEM) technique was applied to visualize the size and shape of the synthesized levan-metal NPs. All levan-based metal ion NPs have a particle size of less than 100 nm, and even levan-Cu+ and levan-Zn2+ have particle sizes less than 50 nm. Levan-Fe2+ NPs and levan-Cu+ NPs exhibited prominent antioxidant activity with an inhibition level of up to 88% and 95%, respectively. And the inhibition level of two metal ion NPs had about 33%-40% higher antioxidant activity compared with the inhibition level of levan only. The two levan-metal ion NPs, therefore, have future prospects to be developed as the new formulation for the antioxidant drugs.

Heterologous Ectoine Production in Escherichia coli: Optimization Using Response Surface Methodology.

INTRODUCTION: A halophilic bacterium of the Halomonas elongata BK-AG25 has successfully produced ectoine with high productivity. To overcome the drawbacks of high levels of salt in the production process, a nonhalophilic bacteria of Escherichia coli (E. coli) was used to express the ectoine gene cluster of the halophilic bacteria, and the production of ectoine by the recombinant cell was optimized. METHODS: The ectoine gene cluster from the halophilic bacterium was isolated and inserted into an expression plasmid of pET30(a) and subsequently transformed into E. coli BL21 (DE3). Production of ectoine from the recombinant E. coli was investigated and then maximized by optimizing the level of nutrients in the medium, as well as the bioprocess conditions using response surface methodology. The experimental designs were performed using a central composite design. RESULTS: The recombinant E. coli successfully expressed the ectoine gene cluster of Halomonas elongata BK-AG25 under the control of the T7 promoter. The recombinant cell was able to produce ectoine, of which most were excreted into the medium. The optimization of ectoine production with the response surface methodology showed that the level of salt in the medium, the incubation temperature, the optical density of the bacteria before induction, and the final concentration of the inducer gave a significant effect on ectoine production by the recombinant E. coli. Interestingly, the level of salt in the medium and the incubation temperature showed an inverse effect on the production of intracellular and extracellular ectoine by the recombinant cell. At the optimum conditions, the production yield was about 418 mg ectoine/g cdw (cell dry weight) after 12 hours of incubation. CONCLUSION: This study is the first report on the expression of an ectoine gene cluster of Halomonas elongata BK-AG25 in E. coli BL21, under the control of the T7 promoter. Optimization of the level of nutrients in the medium, as well as the bioprocess condition using response surface methodology, has successfully increased the production of ectoine by the recombinant bacteria.

Molecular modeling on porphyrin derivatives as ß5 subunit inhibitor of 20S proteasome.

The ubiquitin-proteasome system plays an important role in protein quality control. Currently, inhibition of the proteasome has been validated as a promising approach in anticancer therapy. The 20S core particle of the proteasome harbors ß5 subunit which is a crucial active site in proteolysis. Targeting proteasome ß5 subunit which is responsible for the chymotrypsin-like activity of small molecules has been regarded as an important way for achieving therapeutics target. In the present study, a series of porphyrin derivatives bearing either pyridine or pyrazole rings as meso-substituents were designed and evaluated as an inhibitor for the ß5 subunit of the proteasome by employing molecular docking and dynamics simulations. The molecular docking was performed with the help of AutoDock 4.2, while molecular dynamics simulation was done using AMBER 14. All compounds bound to the proteasome with similar binding modes, and each porphyrin-proteasome complex was stable during 30 ns MD simulation as indicated by root-mean-square-deviation (RMSD) value. An analysis on protein residue fluctuation of porphyrin binding demonstrates that in all complexes, porphyrin binding produces minor fluctuation on amino acid residues. The molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculation shows that the binding affinities of mono-H2PyP, bis-H2PzP, and tetra-H2PyP were comparable with that of the potential inhibitor, HU10. It is noted that the electrostatic interaction increases with the number of meso-substituents, which was favourable for porphyrin binding. The present study shows that both electrostatic and van der Waals interaction are the main force which controls the interaction of porphyrin compounds with the proteasome.

Unfolding mechanics of multiple OspA substructures investigated with single molecule force spectroscopy.

We investigated mechanical unfolding of Borrelia burgdorferi outer surface protein A (OspA), a Lyme disease antigen containing a unique single-layer beta-sheet, with atomic force microscopy (AFM). We mechanically stretched a monomeric unit, rather than a tandem repeat, by pulling it from its N and C-terminal residues without using intervening polymer as a spacer. We detected two peaks in the force-extension profile before the final rupture of a fully extended polypeptide, which we interpreted as unfolding of multiple substructures in OspA. The double-peaked unfolding curves are consistent with results of previous thermodynamic studies showing two cooperative units in OspA. The mechanical unfolding processes were reversible, and the two substructures refolded within one second. Mutations near the boundary of the two thermodynamic cooperative units reduced the height of the first unfolding peak to undetectable levels and marginally affected the second one, indicating that the boundary between the two mechanical substructures is related to that previously assigned between the thermodynamic cooperative units. Based on a "worm-like chain" analysis of our AFM data, we propose a model for mechanical unfolding of OspA, where nearly a half of the chain is stretched with minimal resistive force, followed by sequential breakdown of C-terminal and N-terminal substructures. Based on these results, we discuss similarities and differences between mechanical and thermodynamic unfolding reactions of OspA. This work demonstrates that AFM study of monomeric proteins can elucidate details of the intramolecular mechanics of protein substructures.

Unfolding mechanics of holo- and apocalmodulin studied by the atomic force microscope.

The structural stability of calmodulin (CaM) has been investigated previously by chemical and thermal methods. The calcium-loaded form of CaM has been found to be exceptionally stable, because it can be exposed to temperatures >90 degrees C or to a 9 M urea solution without a marked change in its tertiary structure, and is therefore not experimentally accessible for unfolding studies using conventional analytical methods. In this study, we have developed a system for measuring the force for mechanically unfolding CaM using an atomic force microscope (AFM) by stretching the protein from its N- and C-terminal residues; we have been successful in obtaining force versus extension (F-E) curves for both apo and holo forms of CaM. In our experiment, distinguishable F-E curves have been obtained upon stretching of apoCaM and holoCaM to their full extensions. A very low force observed upon stretching of apoCaM indicated a relatively high flexibility of the apo form. On the contrary, a relatively high unfolding force and the appearance of a characteristic force peak were noted during full stretching of holoCaM. The F-E curve of the latter form of CaM most likely reflects a more rigid and probably more organized conformation of holoCaM than that of apoCaM. These experiments confirmed that the AFM is able to clearly distinguish two functionally distinct forms of CaM in terms of their mechanical properties.

The role of electrostatic interactions on klentaq1 insight for domain separation.

We investigated the relationship between the thermostability of Klentaq1 and factors stabilizing interdomain interactions. When thermal adaptation of Klentaq1 was analyzed at the atomic level, the protein was stable at 300 and 350 K. It gradually unfolded at 373 K and almost spontaneously unfolded at 400 K. Domain separation was induced by disrupting electrostatic interactions in two salt bridges formed by Lys354-Glu445 and Asp371-Arg435 on the interface domain. The role of these interactions in protein stability was evaluated by comparing free energy solvation (ΔΔG(solv)) between wild type and mutants. Substitution of Asp371 by Glu or Asn, and also Glu445 by Asn resulted in a positive value of ΔΔG(solv), suggesting that mutations destabilized the protein structure. Nevertheless, substitution of Glu445 by Asp gave a negative value to ΔΔG(solv) reflecting increasing protein stability. Our results demonstrate that interactions at the interface domains of Klentaq1 are essential factors correlated with the Klentaq1 thermostability.