In Silico Study of the Structure and Ligand Interactions of Alcohol Dehydrogenase from Cyanobacterium Synechocystis Sp. PCC 6803 as a Key Enzyme for Biofuel Production

A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis

In the last century, the emergence of in silico tools has improved the quality of healthcare studies by providing high quality predictions. In the case of COVID-19, these tools have been advantageous for bioinformatics analysis of SARS-CoV-2 structures, studying potential drugs and introducing drug targets, investigating the efficacy of potential natural product components at suppressing COVID-19 infection, designing peptide-mimetic and optimizing their structure to provide a better clinical outcome, and repurposing of the previously known therapeutics. These methods have also helped medical biotechnologists to design various vaccines; such as multi-epitope vaccines using reverse vaccinology and immunoinformatics methods, among which some of them have showed promising results through in vitro, in vivo and clinical trial studies. Moreover, emergence of artificial intelligence and machine learning algorithms have helped to classify the previously known data and use them to provide precise predictions and make plan for future of the pandemic condition. At this contemporary review, by collecting related information from the collected literature on valuable data sources; such as PubMed, Scopus, and Web of Science, we tried to provide a brief outlook regarding the importance of in silico tools in managing different aspects of COVID-19 pandemic infection and how these methods have been helpful to biomedical researchers.

Screening cyclooxygenase-2 inhibitors from Allium sativum L. compounds: in silico approach

Inflammation is a natural protective response toward various simulators, including tissue damage or pathogens. The cyclooxygenase-2 (COX-2) is a very important protein in triggering pain and inflammation. Previous studies have claimed that Allium sativum offers a wide range of anti-inflammatory therapeutics for human consumption. Drug discovery is a complicated process, though in silico methods can make this procedure simpler and more cost-effective. At the current study, we performed the virtual screening of eight Allium sativum-derived compounds via molecular docking with COX-2 enzyme and confirmed the binding energy by docking score estimate followed by ADMET and drug-likeness investigation. The resulting highest-docking scored compound was exposed to molecular dynamics simulation (MDS) for evaluating stability of the docked enzyme-ligand complex and to gauge the oscillation and conformational alterations for the time of enzyme-ligand interaction. The factors of RMSD, RMSF, hydrogen bond interactions, and Rg after 100 ns of MDS proved the stability of alliin in the active site of COX-2 in comparison with celecoxib (CEL) as the control. Moreover, we investigated the binding affinity analysis of all compounds via MM/PBSA method. The results from this study suggest that alliin (a sulfuric compound) exhibits a higher binding affinity for the COX-2 enzyme compared to the other compounds and CEL. Alliin showed to be a possible anti-inflammatory therapeutic candidate for managing the inflammatory conditions.

In silico design of quadruplex aptamers against the spike protein of SARS-CoV-2

Nucleic acid aptamers are short sequences of nucleic acid ligands that bind to a specific target molecule. Aptamers are experimentally nominated using the well-designed SELEX (systematic evolution of ligands by exponential enrichment) method. Here, we designed a new method for diagnosis and blocking SARS-CoV-2 based on G-quadruplex aptamer. This aptamer was developed against the receptor-binding domain (RBD) region of the spike protein. In the current study, ten quadruplex DNA aptamers entitled AP1, AP2, AP3, AP4, AP5, AP6, AP7, AP8, AP9, and AP10 were designed in silico and had high HADDOCK scores. One quadruplex aptamer sequence (AP1) was selected based on the interaction with RBD of SARS-CoV-2. Results showed that AP1 aptamer could be used as an agent in the diagnosis and therapy of SARS-CoV-2, although more works are still needed.

Computational Design and Analysis of a Multi-epitope Against Influenza A virus

Influenza A viruses are among the most studied viruses, however no effective prevention against influenza infection has been developed. So, designing an effective vaccine against Influenza A virus is a critical issue in the field of medical biotechnology. For this reason, to combat this disease, we have designed a novel multi-epitope vaccine candidate based on the several conserved and potential linear B-cell and T-cell binding epitopes by using the in silico approach. This vaccine consists of an ER signal conserved sequence, the PADRE conserved epitope and two conserved epitopes of Influenza matrix protein 2. T-cell binding epitopes from Matrix protein 2 were predicted by in silico tools of epitope prediction. The selected epitopes were joined by flexible linkers and physicochemical properties, toxicity, and allergenecity were investigated. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. The final multi-epitope construct was modeled, confirmed by different programs and the molecular interactions with immune receptors were considered. The molecular docking assay indicated the interactions with immune-stimulatory toll-like receptor 3 (TLR3) and major histocompatibility complex class I (MHCI). The HADDOCK and H DOCK servers were used to make docking analysis, respectively. The docking analysis indicated a strong and stable binding interaction between the vaccine construct with major histocompatibility complex (MHC) class I and toll-like receptor 3. Overall, the findings suggest that the current vaccine may be a promising vaccine to prevent Influenza infection.

In Silico Study of the Structure and Ligand Preference of Pyruvate Kinases from Cyanobacterium Synechocystis sp. PCC 6803

Finding reliable cheap sources for producing chemicals and materials is always challenging. During recent decades, photosynthetic organisms such as cyanobacteria, which used CO₂ as a carbon source for making products, have attracted a great deal of attention. Among cyanobacteria, Synechocystis sp. PCC 6803 has been considered as a model strain and has some desirable features that make it suitable for use as an industrial strain. Pyruvate kinase (PK) catalyzes the transformation of phosphoenolpyruvate (PEP) to pyruvate in the last step of glycolysis that is an essential enzyme to produce adenosine triphosphate (ATP) in all organisms. Therefore, it plays a critical role in regulating cell metabolism. However, active and allosteric sites of PK and allosteric mechanisms governing PK activity are poorly understood in many bacteria. This study was aimed to provide more insight into PKs of Synechocystis sp. PCC 6803, using in silico methods. The results indicated that predicted structures of PKs from Synechocystis sp. PCC 6803 are reliable and can be considered for further studies. Molecular docking studies suggested that for predicted structures of sll0587 and sll1275, respectively, there are three and two possible active or allosteric sites. Furthermore, molecular interaction analysis of modeled structures proposes that sll0587 is strongly inhibited by ATP and when ATP concentration is low, this isoenzyme is active.

Tailor-made novel electrospun polystyrene/poly(d,l-lactide-co-glycolide) for oxidoreductases immobilization: Improvement of catalytic properties under extreme reaction conditions

Immobilized enzymes find applications in many areas such as pharmacy, medicine, food production and environmental protection. However, protecting these biocatalysts against harsh reaction conditions and retaining their enzymatic activity even after several biocatalytic cycles are major challenges. Properly selected supports and type of surface modifier therefore seem to be crucial for achieving high retention of catalytic activity of immobilized biomolecules. Here we propose production of novel composite electrospun fibers from polystyrene/poly(d,l-lactide-co-glycolide) (PS/PDLG) and its application as a support for immobilization of oxidoreductases such as alcohol dehydrogenase (ADH) and laccase (LAC). Two strategies of covalent binding, (i) (3-aminopropyl)triethoxysilane (APTES) with glutaraldehyde (GA) and (ii) polydopamine (PDA), were applied to attach oxidoreductases to PS/PDLG. The average fiber diameter was shown to increase from 1.252 µm to even 3.367 µm after enzyme immobilization. Effective production of PS/PDLG fibers and biomolecule attachment were confirmed by Fourier transform infrared spectroscopy analysis. The highest substrate conversion efficiency was observed at pH 6.5 and 5 for ADH and LAC, respectively, and at 25 °C for enzymes attached using the APTES + GA approach. Improvement of enzyme stabilization at high temperatures was confirmed in that relative activities of enzymes immobilized onto PS/PDLG fibers were over 20% higher than those of the free biomolecules, and enzyme leaching from the support using acetate and MES buffers was below 10 mg/g.

In silico design of a multi-epitope peptide construct as a potential vaccine candidate for Influenza A based on neuraminidase protein

Designing an effective vaccine against different subtypes of Influenza A virus is a critical issue in the field of medical biotechnology. At the current study, a novel potential multi-epitope vaccine candidate based on the neuraminidase proteins for seven subtypes of Influenza virus was designed, using the in silico approach. Potential linear B-cell and T-cell binding epitopes from each neuraminidase protein (N1, N2, N3, N4, N6, N7, N8) were predicted by in silico tools of epitope prediction. The selected epitopes were joined by three different linkers, and physicochemical properties, toxicity, and allergenecity were investigated. The final multi-epitope construct was modeled using GalaxyWEB server, and the molecular interactions with immune receptors were investigated and the immune response simulation assay was performed. A multi-epitope construct with GPGPGPG linker with the lowest allergenicity and highest stability was selected. The molecular docking assay indicated the interactions with immune system receptors, including HLA1, HLA2, and TLR-3. Immune response simulation detected both humoral and cellular response, including the elevated count of B-cells, T-cell, and Nk-cells.

In silico study of garlic (Allium sativum L.)-derived compounds molecular interactions with α-glucosidase

Diabetes mellitus is a metabolic syndrome characterized by elevated blood glucose. The α-glucosidase enzyme is responsible for the hydrolysis of carbohydrates. This in silico study aimed to evaluate the inhibitory effects of the isolated compounds from Allium sativum L. on α-glucosidase. At first, sulfur and phenolic compounds of A. sativum L. were obtained from PubChem database, and α-glucosidase enzyme structure was obtained from Protein Data Bank. Toxicity class of compounds and the Lipinski parameter were predicted by Toxtree and Protox II and the Swiss ADME tools, respectively. Finally, the molecular interaction analysis between α-glucosidase and compounds from A. sativum L. was performed by AutoDock 4.2.6. Molecular interactions were investigated using Discovery Studio Visulizer and Ligplot 2.1 program. All of the selected sulfur and phenolic compounds from A. sativum L. followed the Lipinski's rules, had an acceptable binding energy, and lacked toxicity; therefore, they were appropriate candidates for α-glucosidase inhibition. Among these compounds, methionol and caffeic acid showed the lowest binding energy, and the highest inhibitory effect on α-glucosidase enzyme with - 3.9 and - 4.8 kcal/mol, respectively. These compounds also indicated the lower binding energy than the standard inhibitor (miglitol). Among the sulfur and phenolic compounds in A. sativum L., methionol and caffeic acid were predicted to be the powerful inhibitors, due to having more hydrogen binds and hydrophobic interactions with the active site of α-glucosidase.

Application of decoy oligodeoxynucleotides strategy for inhibition of cell growth and reduction of metastatic properties in nonresistant and erlotinib-resistant SW480 cell line

Signal transducer and activator of transcription 3 (STAT3) is a critical regulator for angiogenesis, cell cycle progression, apoptosis, and drug resistance. Resistance toward EGF receptor (EGFR) inhibitors is a significant clinical concern for metastatic colon cancer patients. The present study aimed to evaluate the blocking influences of STAT3 decoy oligodeoxynucleotides (ODNs) on the STAT3 survival signaling pathway in nonresistant and erlotinib-resistant SW480 colon cancer cells. First, STAT3 decoy and scramble ODNs were designed according to STAT3 elements in the promoter region of MYCT1 gene and tested for the interaction of STAT3 protein with designed ODNs via in silico molecular docking study. Then, the efficiency of transfection and subcellular localization of ODNs were assessed using flow cytometry and fluorescence microscopy, respectively. Cell viability, cell cycle, and apoptosis tests, scratch and colony formation assays, and real-time PCR were also used to study the cancerous properties of cells. A considerable decrease in proliferation of colon cancer cells was observed with blockade of STAT3 signaling due to cell cycle arrest and induced apoptosis via downregulation of cyclin D1 and Bcl-XL, respectively. Furthermore, upon transfecting STAT3 decoy ODNs, colony formation potential and migration activity in both SW480 colon cancer cell lines were decreased compared to the control groups. From this study, it could be concluded that STAT3 is critical for cell growth inhibition and metastatic properties reduction of resistant SW480 colon cancer cells; therefore, STAT3 decoy ODNs could be considered as potential therapeutics along with current remedies for treating drug-resistant colon cancer.

NANOG Decoy Oligodeoxynucleotide-Encapsulated Niosomes Nanocarriers: A Promising Approach to Suppress the Metastatic Properties of U87 Human Glioblastoma Multiforme Cells

Recently, advances in the synthesis and development of multifunctional nanoparticle platforms have opened up great opportunities and advantages for specifically targeted delivery of genes of interest. BSA-coated niosome structures (NISM@B) can potentially improve the efficiency in vitro delivery of nucleic acid molecules and the transfection of genes. Few studies have reported the combined use of niosomes with nucleic acid as therapeutic agents or decoy oligodeoxynucleotides (ODNs). Herein, we synthesized NISM@B to encapsulate NANOG decoy ODN (NISM@B-DEC), after which the physicochemical characteristics and in vitro and in vivo properties of NISM@B-DEC were investigated. Our results regarding physicochemical characteristics revealed that the stable niosome nanocarrier system was successfully synthesized with a regular spherical shape and narrow size distribution with proper zeta-potential values and had an appropriate biocompatibility. The ODN release from the niosome nanocarrier system exhibited controlled and pH-dependent behavior as the best models to explain the ODN release profile. NISM@B-DEC was efficiently taken up by human glioblastoma cells (U87) and significantly inhibited cell growth. Finally, blockage of the NANOG pathway by NISM@B-DEC resulted in G1 cell cycle arrest, apoptosis, and cell death. In addition, NISM@B-DEC caused a significant decrease in tumor formation and improved wound-healing efficiency of the U87 cells. These findings confirm that NISM@B-DEC could potentially suppress the metastatic ability of these cells. It can be concluded that the presented nanocarrier system can be a promising approach for targeted gene delivery in cancer therapy.