Arrangement Of Amino Acids Research Articles

The Potential Application of Mung Bean (Vigna radiata L.) Protein in Plant‐Based Food Analogs: A Review

ABSTRACTThe increasing demand for plant‐based food products by consumers along with the growing global population requires the discovery of novel and sustainable protein sources to address environmental challenges and meet nutritional requirements. Among various plant proteins, mung bean protein (MBP) exhibits several unique characteristics that make it a valuable ingredient in the field of plant‐based food analogs. This literature review aims to express the unique structure and composition of MBP, in addition to its physicochemical, functional, and nutritional properties. Furthermore, its potential applications in novel meat, dairy, and egg analogs are highlighted to meet the growing demand for sustainable, nutritious, and delicious plant‐based food alternatives. Structurally, MBP consists of a complex arrangement of amino acids, forming a globular protein with distinct functional properties. Its composition is also rich in essential amino acids, particularly leucine and lysine, making it a promising protein source for plant‐based diets. From a techno‐functional perspective, MBP exhibits remarkable gelling, emulsifying, foaming, and binding properties, which are necessary for the development of stable emulsions, airy foams, firm gels, and cohesive textures in various plant‐based food formulations. Moreover, MBP and its derivatives can possess notable bio‐functional properties, including antioxidant activity and anti‐inflammatory benefits, as well as cholesterol‐lowering, anti‐obesity, antidiabetic, antihypertensive, and anticancer effects. Consequently, the production of food analogs based on MBP not only improves the techno‐functional attributes of the final products but also can promote consumer health and well‐being.

Identification of natural curcumins as potential dual inhibitors of PTP1B and α-glucosidase through experimental and computational study

Curcuma longa is a rich source of curcumin (1) and its major analogs, demethoxycurcumin (2), and bisdemethoxycurcumin (3), among the Curcuma species. In this study, curcumins (1–3) were purified from C. longa, and their inhibitory effects against protein tyrosine phosphatase 1B (PTP1B) and α-glucosidase enzymes were assayed. These compounds potential inhibited PTP1B and α-glucosidase activities with IC50 values ranging from 37.8 to 72.6 μM, and 78.2–90.6 μM, respectively. In addition, density functional theory (DFT) accompanied by molecular docking (MD) were employed to analyze the ligand stability and the interaction of curcumins 1–3 with PTP1B and glucoside hydrolase proteins. The assay-based results and MD data obtained showed a high correlation, suggesting that the deterioration of enzyme activity caused by the distortion of the structural conformation of PTP1B and glucoside hydrolase may be related to the arrangement of amino acids in the protein structure. Our findings reveal the significant role of methoxylation in the variation of inhibitory effects of these curcumins against PTP1B and α-glucosidase. These in vitro and in silico activities of curcumins (1–3) against PTP1B and glucoside hydrolase have been examined and reported for the first time.

In-Silico Identification, Characterization and Expression Analysis of Genes Involved in Resistant Starch Biosynthesis in Potato (Solanum tuberosum L.) Varieties.

Potato (Solanum tuberosum L.), an important horticultural crop is a member of the family Solanaceae and is mainly grown for consumption at global level. Starch, the principal component of tubers, is one of the significant elements for food and non-food-based applications. The genes associated with biosynthesis of starch have been investigated extensively over the last few decades. However, a complete regulation pathway of constituent of amylose and amylopectin are still not deeply explored. The current in-silico study of genes related to amylose and amylopectin synthesis and their genomic organization in potato is still lacking. In the current study, the nucleotide and amino acid arrangement in genome and twenty-two genes linked to starch biosynthesis pathway in potato were analysed. The genomic structure analysis was also performed to find out the structural pattern and phylogenetic relationship of genes. The genome mining and structure analysis identified ten specific motifs and phylogenetic analysis of starch biosynthesis genes divided them into three different clades on the basis of their functioning and phylogeny. Quantitative real-time PCR (qRT-PCR) of amylose biosynthesis pathway genes in three contrast genotypes revealed the down-gene expression that leads to identify potential cultivar for functional genomic approaches. These potential lines may help to achieve higher content of resistant starch.

Omics data analysis reveals the system-level constraint on cellular amino acid composition

Proteins play a pivotal role in coordinating the functions of organisms, essentially governing their traits, as the dynamic arrangement of diverse amino acids leads to a multitude of folded configurations within peptide chains. Despite dynamic changes in amino acid composition of an individual protein (referred to as AAP) and great variance in protein expression levels under different conditions, our study, utilizing transcriptomics data from four model organisms uncovers surprising stability in the overall amino acid composition of the total cellular proteins (referred to as AACell). Although this value may vary between different species, we observed no significant differences among distinct strains of the same species. This indicates that organisms enforce system-level constraints to maintain a consistent AACell, even amid fluctuations in AAP and protein expression. Further exploration of this phenomenon promises insights into the intricate mechanisms orchestrating cellular protein expression and adaptation to varying environmental challenges.

Cyclic Peptide Conjugate Vaccines and Physically Mixed Cyclic Peptide Vaccines for Subcutaneous Immunization.

Immune stimulants (adjuvants) enhance immune system recognition to provide an effective and individualized immune response when delivered with an antigen. Synthetic cyclic deca-peptides, co-administered with a toll-like receptor targeting lipopeptide, have shown self-adjuvant properties, dramatically boosting the immune response in a murine model as a subunit peptide-based vaccine containing group A Streptococcus peptide antigens.Here, we designed a novel peptide and lipid adjuvant system for the delivery of group A Streptococcus peptide antigen and a T helper peptide epitope. Following linear peptide synthesis on 2-chlorotrityl chloride resin, the linear peptide was cleaved and head-to-tail cyclized in solution. The selective arrangement of amino acids in the deca-peptide allowed for selective conjugation of lipids and/or peptide antigens following cyclisation. Using both solution-phase peptide chemistry and copper-catalyzed azide-alkyne cycloaddition reaction were covalently (and selectively) ligated lipid and/or peptide antigens onto the cyclic deca-peptide core. Subcutaneous administration of the vaccine design to mice resulted in the generation of a large number of serum immunoglobulin (Ig) G antibodies.

Exploring the folding landscape of leptin: Insights into threading pathways

The discovery of new protein topologies with entanglements and loop-crossings have shown the impact of local amino acid arrangement and global three-dimensional structures. This phenomenon plays a crucial role in understanding how protein structure relates to folding and function, affecting the global stability, and biological activity. Protein entanglements encompassing knots and non-trivial topologies add complexity to their folding free energy landscapes. However, the initial native contacts driving the threading event for entangled proteins remains elusive. The Pierced Lasso Topology (PLT) represents an entangled topology where a covalent linker creates a loop in which the polypeptide backbone is threaded through. Compared to true knotted topologies, PLTs are simpler topologies where the covalent-loop persists in all conformations. In this work, the PLT protein leptin, is used to visualize and differentiate the preference for slipknotting over plugging transition pathways along the folding route. We utilize the Energy Landscape Visualization Method (ELViM), a multidimensional projection technique, to visualize and distinguish early threaded conformations that cannot be observed in an in vitro experiment. Critical contacts for the leptin threading mechanisms were identified where the competing pathways are determined by the formation of a hairpin loop in the unfolded basin. Thus, prohibiting the dominant slipknotting pathway. Furthermore, ELViM offers insights into distinct folding pathways associated with slipknotting and plugging providing a novel tool for de novo design and in vitro experiments with residue specific information of threading events in silico.

Construction of a myoglobin scaffold-based biocatalyst for the biodegradation of sulfadiazine and sulfathiazole

Sulfonamide antibiotics, a family of broad-spectrum antibiotic drugs, are increasingly used in aquaculture and are frequently detected in aquatic environments. This poses a potential threat to organisms and may cause the evolution of antimicrobial resistance. Therefore, it is important to develop an environmentally friendly and efficient biocatalyst to degrade sulfonamides (SAs) such as sulfadiazine (SD) and sulfathiazole (ST). Here, we realized the direct and efficient degradation of SD and ST using a hydrogen peroxide-dependent artificial catalytic system based on myoglobin (Mb). The arrangements of amino acids at positions 29, 43, 64, and 68 were found to influence catalytic activity. An L29H/H64D/V68I myoglobin mutant showed the best catalytic efficiency (i.e., kcat/Km = 720.42 M−1 s−1) against SD. Next, mutant H64D/V68I showed the best degradation rate against SD (i.e., 91.45 ± 0.16%). Moreover, L29H/H64D/V68I Mb was found to efficiently catalyze ST oxidation (kcat/Km = 670.08 M−1 s−1), while H64D/V68I had the best degradation rate against ST (i.e., 99.45 ± 0.23%). Our results demonstrate that SAs can be efficiently degraded by artificial peroxygenases constructed using a myoglobin scaffold. This therefore provides a simple and economical method for the biodegradation of SD and ST.

Starting at Go: Protein structure prediction succumbs to machine learning

This year’s Albert Lasker Basic Medical Research Award recognizes the invention of AlphaFold, a revolutionary advance in the history of protein research which for the first time offers the practical ability to accurately predict the three-dimensional arrangement of amino acids in the vast majority of proteins on a genomic scale on the basis of sequence alone [J. Jumper et al., Nature 596, 583–589 (2021) and K. Tunyasuvunakool et al., Nature 596, 590–596 (2021)]. This extraordinary achievement by Demis Hassabis and John Jumper and their coworkers at Google’s DeepMind and other collaborators was built on decades of experimental protein structure determination (structural biology) as well as the gradual development of multiple strategies incorporating biologically inspired statistical approaches. But when Jumper and Hassabis added a brew of innovative neural network-based machine learning approaches to the mix, the results were explosive. Realizing the half-century-old dream of predicting protein structure has already accelerated the pace and creativity of many areas of Chemistry, Biology, and Medicine.

Construction of Biocatalysts Using the P450 Scaffold for the Synthesis of Indigo from Indole.

With the increasing demand for blue dyes, it is of vital importance to develop a green and efficient biocatalyst to produce indigo. This study constructed a hydrogen peroxide-dependent catalytic system for the direct conversion of indole to indigo using P450BM3 with the assistance of dual-functional small molecules (DFSM). The arrangements of amino acids at 78, 87, and 268 positions influenced the catalytic activity. F87G/T268V mutant gave the highest catalytic activity with kcat of 1402 min-1 and with a yield of 73%. F87A/T268V mutant was found to produce the indigo product with chemoselectivity as high as 80%. Moreover, F87G/T268A mutant was found to efficiently catalyze indole oxidation with higher activity (kcat/Km = 1388 mM-1 min-1) than other enzymes, such as the NADPH-dependent P450BM3 (2.4-fold), the Ngb (32-fold) and the Mb (117-fold). Computer simulation results indicate that the arrangements of amino acid residues in the active site can significantly affect the catalytic activity of the protein. The DFSM-facilitated P450BM3 peroxygenase system provides an alternative, simple approach for a key step in the bioproduction of indigo.

Structural similarities between SAM and ATP recognition motifs and detection of ATP binding in a SAM binding DNA methyltransferase

S-adenosylmethionine (SAM) is a ubiquitous co-factor that serves as a donor for methylation reactions and additionally serves as a donor of other functional groups such as amino and ribosyl moieties in a variety of other biochemical reactions. Such versatility in function is enabled by the ability of SAM to be recognized by a wide variety of protein molecules that vary in their sequences and structural folds. To understand what gives rise to specific SAM binding in diverse proteins, we set out to study if there are any structural patterns at their binding sites. A comprehensive analysis of structures of the binding sites of SAM by all-pair comparison and clustering, indicated the presence of 4 different site-types, only one among them being well studied. For each site-type we decipher the common minimum principle involved in SAM recognition by diverse proteins and derive structural motifs that are characteristic of SAM binding. The presence of the structural motifs with precise three-dimensional arrangement of amino acids in SAM sites that appear to have evolved independently, indicates that these are winning arrangements of residues to bring about SAM recognition. Further, we find high similarity between one of the SAM site types and a well known ATP binding site type. We demonstrate using in vitro experiments that a known SAM binding protein, HpyAII.M1, a type 2 methyltransferase can bind and hydrolyse ATP. We find common structural motifs that explain this, further supported through site-directed mutagenesis. Observation of similar motifs for binding two of the most ubiquitous ligands in multiple protein families with diverse sequences and structural folds presents compelling evidence at the molecular level in favour of convergent evolution.

Sequential Properties Representation Scheme for Recurrent Neural Network-Based Prediction of Therapeutic Peptides.

The discovery of therapeutic peptides is often accelerated by means of virtual screening supported by machine learning-based predictive models. The predictive performance of such models is sensitive to the choice of data and its representation scheme. While the peptide physicochemical and compositional representations fail to distinguish sequence permutations, the amino acid arrangement within the sequence lacks the important information contained in physicochemical, conformational, topological, and geometrical properties. In this paper, we propose a solution to the identified information gap by implementing a hybrid scheme that complements the best traits from both approaches with the aim of predicting antimicrobial and antiviral activities based on experimental data from DRAMP 2.0, AVPdb, and Uniprot data repositories. Using the Friedman test of statistical significance, we compared our hybrid, sequential properties approach to peptide properties, one-hot vector encoding, and word embedding schemes in the 10-fold cross-validation setting, with respect to the F1 score, Matthews correlation coefficient, geometric mean, recall, and precision evaluation metrics. Moreover, the sequence modeling neural network was employed to gain insight into the synergic effect of both properties- and amino acid order-based predictions. The results suggest that sequential properties significantly (P < 0.01) surpasses the aforementioned state-of-the-art representation schemes. This makes it a strong candidate for increasing the predictive power of screening methods based on machine learning, applicable to any category of peptides.

Computational Modeling of the Effect of Trifluoroethanol on the Conformation of α-Synuclein Peptide

Alpha-Synuclein is a presynaptic neuronal protein whose masses are involved in Parkinson’s disease, a chronic and progressive neurodegenerative disorder of the central nervous system. It has been observed that upon exposure to anionic surfactants, fluorinated alcohols and membranes in vitro, [Formula: see text]-synuclein adopts alpha helix structure and can be fibrillated, while in aqueous solution, the protein is intrinsically disordered and the fibrillation is undesirable. Solvent is one of the most critical environmental parameters in biological studies as well as computer simulations. In this paper, we have investigated the effect of solvent composition on the conformation of [Formula: see text]-synuclein protein using molecular dynamics (MD) simulations. For this purpose, the effect of different combinations of water and trifluoroethanol (TFE) solvents on the secondary structure of a fragment of [Formula: see text]-synuclein was investigated. Moreover, thermodynamic calculations were performed through a coarse-grained (CG) model of solutions with different concentrations of [Formula: see text]-synuclein in the aqueous phase and in TFE medium. The potential of mean force (PMF) calculations was performed as a function of separation distance between the centers of masses of two peptides. The results indicated that in the presence of TFE, the secondary structures have a regular arrangement of amino acids stabilized by hydrogen bonding patterns. In addition, decreasing the TFE concentration reduces the stability of [Formula: see text]-helix structures of the protein. It seems that in diluted TFE solutions, high concentrations of water in the medium lead to the breakage of peptide–TFE hydrogen bonds. However, the hydrophobic nature of TFE and [Formula: see text]-synuclein molecules prevents further aggregation in the concentrated solutions.

Overview of Thaumatococcus Daniellii Plant, History, Uses, Benefits, and Characterization

Thaumatococcus daniellii (Benn.) Benth, known as “katempe” or “katemfe”. It grows in humid tropical forests and the coastal areas of West Africa, especially in Nigeria, Ghana, Central African Republic, Uganda, and Cote d'Ivoire. T. daniellii contains chemical compounds that have several uses in many fields and contain thaumatin protein, which plays an essential role in the food industry, used as a natural sweetener, and pharmaceutical industry. T. daniellii can play a significant role in economic growth in many countries in which it grows. This study summarises some crucial aspects of T. daniellii. As the study highlight, some of the chemical components are contained in the plant. In addition to the other medicinal benefits and applications used from T. daniellii. the study presented the importance of the plant in the production of thaumatin and highlighted the two types of this protein and the difference between them in the arrangement of amino acids.

In silico prediction of peptide variants from chia (S. hispanica L.) with antimicrobial, antibiofilm, and antioxidant potential

Plants are known as a rich source of bioactive peptides, and a variety of plant peptides have been studied as potential alternatives to conventional antimicrobial, antibiofilm, and antioxidant agents in food products to prolong their shelf-life, which could pose potential health risks for consumers. Regardless of their high functional potential, no plant peptides are currently used in the food industry for these purposes. In this study, it is performed the selection and optimization of peptides that are not currently reported in any database, derived from a chia peptide fraction. Computer-aided tools were used to identify multifunctional peptides with antimicrobial, antibiofilm, and antioxidant potential. Two peptide sequences (YACLKVK and KLKKNL) showing the highest probability scores for antimicrobial activity were identified from a total of 1067 de novo sequences in a chia peptide fraction (F<1 kDa). Subsequently, the peptides YACLKVK and KLKKNL were used to create scrambled libraries containing permutations of these sequences to explore the antibiofilm potential of different amino acid arrangements. The peptide variants with the highest probability scores for antibiofilm activity were subjected to optimization for the improvement of their activity. Finally, the optimized sequences were analyzed to determine the presence of antioxidant fragments. This computational approach could be a solution for the screening of a large number of peptides with more than one function, allowing the development of multifunctional peptides as alternatives to traditional food preservatives.

Sequencing Analysis of cvaC Gene in Acinetobacter Baumannii That Isolates from Different Infections

Acinetobacter baumannii is one of the opportunistic nurses responsible for many acquired infections in hospitals due to its ability to resist many antibiotics. This is one of the problems facing hospitals in the world. Identification of the cvaC gene and sequence analysis in Acinetobacter baumannii isolates from various infections, and mutation detection in this gene. From 1st of September to 30th of November, 2016, 200 Acinetobacter baumannii isolates were obtained from various clinical samples. Follow fifty isolates from blood, twenty isolates from urinary tract infections, thirty isolates from wound infections, forty isolates from burn infections and twenty-five isolates from stool samples from various hospitals (Central Children's Hospital, Al Karama Hospital, Karkh General Hospital, Al-Ameen Medical City Hospital, Educational Labs, Baghdad Teaching Hospital, Child Protection Hospital, Burns and Wounds Hospital) in Baghdad city. Identification forty isolates confirmed that they belong to Acinetobacter baumannii, including fourteen isolates from a stool sample, nine isolates from blood, eight isolates from burns, four isolates from wound infections, and Respiratory tract infection, , and only one isolate from urinary tract infections sample. Genotypic detection of the cvaC gene of Acinetobacter baumannii showed the presence of this gene in 16 isolates (40%) and Sequencing analysis of cvaC has shown seven genetic mutations and only one mutation has been converted amino acid Alanine to Valine.The amino acid Alanine was changed to Valine in Position 656 at Subject 678, resulting in silent mutations that did not affect protein translation and other mutations that resulted in a change in the amino acid arrangement and protein translation.

Feature-extraction and analysis based on spatial distribution of amino acids for SARS-CoV-2 Protein sequences

Background and objectiveThe world is currently facing a global emergency due to COVID-19, which requires immediate strategies to strengthen healthcare facilities and prevent further deaths. To achieve effective remedies and solutions, research on different aspects, including the genomic and proteomic level characterizations of SARS-CoV-2, are critical. In this work, the spatial representation/composition and distribution frequency of 20 amino acids across the primary protein sequences of SARS-CoV-2 were examined according to different parameters. MethodTo identify the spatial distribution of amino acids over the primary protein sequences of SARS-CoV-2, the Hurst exponent and Shannon entropy were applied as parameters to fetch the autocorrelation and amount of information over the spatial representations. The frequency distribution of each amino acid over the protein sequences was also evaluated. In the case of a one-dimensional sequence, the Hurst exponent (HE) was utilized due to its linear relationship with the fractal dimension (D), i.e. D+HE=2, to characterize fractality. Moreover, binary Shannon entropy was considered to measure the uncertainty in a binary sequence then further applied to calculate amino acid conservation in the primary protein sequences. Results and conclusionFourteen (14) SARS-CoV protein sequences were evaluated and compared with 105 SARS-CoV-2 proteins. The simulation results demonstrate the differences in the collected information about the amino acid spatial distribution in the SARS-CoV-2 and SARS-CoV proteins, enabling researchers to distinguish between the two types of CoV. The spatial arrangement of amino acids also reveals similarities and dissimilarities among the important structural proteins, E, M, N and S, which is pivotal to establish an evolutionary tree with other CoV strains.

Insights into Structure and Aggregation Behavior of Elastin-like Polypeptide Coacervates: All-Atom Molecular Dynamics Simulations.

The stimuli-responsive character of elastin-like polypeptides (ELP) has led to their use in a wide range of applications. The temperature-triggered aggregation, or LCST behavior, of ELPs is a complex and multistep phenomenon, which proposed to include the structural transitions, loss of hydrophobic hydration, expulsion of water molecules and physical association of chains. Thus, the origin and detailed mechanism of LCST in ELPs is difficult to elucidate. Here, to gain insights into structure and dynamics of coacervates, we performed all-atom molecular dynamics simulations of 27 90-mer ELPs in explicit water at 350 K. Two sequences, poly(VGPVG)18 and poly(VPGVG)18, were examined due to their experimentally observed differences in thermal hysteresis albeit identical overall composition but different arrangement of amino acids. The simulation results indicate that surface hydrophobicity of poly(VGPVG) aggregate is less than that of the poly(VPGVG) aggregate, and there are marked changes in torsion angles and the propensities of secondary structural motifs during the aggregation process. Moreover, there are significant differences between structure of a single polypeptide in water and structure within the aggregate. Overall, the aggregation process is driven by the formation of peptide-peptide interactions whereas the average hydration of peptides remains almost the same between dissolved and aggregated states. Even though the aggregation is driven by the hydrophobic interactions, ELP coacervate has no hydrophobic core and contains many water molecules. Overall, our findings provide an insight into the sequence-dependent structure of coacervates and molecular behavior of individual peptides during aggregation.

Active sites of peptides Asp-Asp-Asp-Tyr and Asp-Tyr-Asp-Asp protect against cellular oxidative stress

The protective effects of the peptides Asp-Asp-Asp-Tyr (DDDY) and Asp-Tyr-Asp-Asp (DYDD) against AAPH-induced HepG2 cells are unclear. Our objective was to investigate the active sites of these peptides and their cellular antioxidant mechanism. DDDY and DYDD show a direct free radical scavenging effect in reducing ROS levels and maintained cellular antioxidant enzymes at normal levels. The quantum chemistry analysis of the electronic properties of antioxidant activity showed that DYDD has a greater energy in the highest occupied molecular orbital than DDDY, and O58-H59 and N10-H12 were identified as the active antioxidant sites in DYDD and DDDY, respectively, indicating that the inconsistent arrangement of amino acids affects the distribution of the highest occupied orbital energy as well as the active sites; thus, influences the antioxidant activity of peptides. It provide valuable insights into the antioxidant active sites of peptides.

Stimuli-responsive biphenyl-tripeptide supramolecular hydrogels as biomimetic extracellular matrix scaffolds for cartilage tissue engineering

Supramolecular hydrogel composed of aromatic short peptide gelator was an attractive biomaterial owing to its simple and convenient synthetic route, nano-fibrillar microstructure resembling natural collagen fibers and intelligent response to external stimulus. Herein, stimuli-responsive biphenyl-tripeptide supramolecular hydrogels was prepared to simulate extracellular matrix scaffolds by temperature switch, ion induction and pH switch. The amino acid arrangement substantially affected gelation behavior, only BPAA-βAFF and BPAA-FFβA could form nanostructured supramolecular hydrogels with 8-10 nm nanotubes or nanofibers by potential intermolecular hydrogen bond interactions and π-π stacking. The minimum gelation concentration (MGC) and maximum storage modulus were 0.4 mM (0.023 wt%) and around 8.2 KPa. The two supramolecular hydrogels could support adhesion and proliferation of L929 cells. Moreover, the BPAA-βAFF hydrogel promoted proliferation and ECM secretion of chondrocytes in vitro, and facilitate the phenotype maintenance of hyaline cartilage. All the results demonstrated that BPAA-βAFF hydrogel hold great potential application prospects in cartilage tissue engineering. Statement of SignificanceDiphenylalanine was served as a core segment conjugating with 4-biphenylacetic acid (BPAA) to produce biphenyl-tripeptide compounds with transforming amino sequence, and multiple external stimuli was applied to study the gelation properties of the aromatic short peptide gelators. “FF” brick (phenylalanine-phenylalanine) was crucial for formation of fibrous supramolecular hydrogels. Meanwhile, the sequence of amino acids arrangement also had an essential effect on the gelation behavior. Optimal BPAA-βAFF with ultra-low minimum gelation concentration (0.4 mM, about 0.023 wt%) and similar microstructure to extracellular matrix (ECM) of nature cartilage tissue could promote the proliferation and ECM secretion of chondrocytes in vitro, and facilitate the formation of hyaline cartilage.

Repurposing potential of posaconazole and grazoprevir as inhibitors of SARS-CoV-2 helicase

As the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic engulfs millions worldwide, the quest for vaccines or drugs against the virus continues. The helicase protein of SARS-CoV-2 represents an attractive target for drug discovery since inhibition of helicase activity can suppress viral replication. Using in silico approaches, we have identified drugs that interact with SARS-CoV-2 helicase based on the presence of amino acid arrangements matching binding sites of drugs in previously annotated protein structures. The drugs exhibiting an RMSD of ≤ 3.0 Å were further analyzed using molecular docking, molecular dynamics (MD) simulation, and post-MD analyses. Using these approaches, we found 12 drugs that showed strong interactions with SARS-CoV-2 helicase amino acids. The analyses were performed using the recently available SARS-CoV-2 helicase structure (PDB ID: 5RL6). Based on the MM-GBSA approach, out of the 12 drugs, two drugs, namely posaconazole and grazoprevir, showed the most favorable binding energy, − 54.8 and − 49.1 kcal/mol, respectively. Furthermore, of the amino acids found conserved among all human coronaviruses, 10/11 and 10/12 were targeted by, respectively, grazoprevir and posaconazole. These residues are part of the crucial DEAD-like helicase C and DEXXQc_Upf1-like/ DEAD-like helicase domains. Strong interactions of posaconazole and grazoprevir with conserved amino acids indicate that the drugs can be potent against SARS-CoV-2. Since the amino acids are conserved among the human coronaviruses, the virus is unlikely to develop resistance mutations against these drugs. Since these drugs are already in use, they may be immediately repurposed for SARS-CoV-2 therapy.