Homology Modeling Research Articles

In silico evaluation of outer membrane protein S2 as a suitable vaccine candidate against Edwardsiella tarda infection of fish

AbstractObjectiveEdwardsiella tarda, the agent responsible for edwardsiellosis, is one of the primary emerging pathogens in fish aquaculture. The disease leads to significant economic loss for the farmers. Development of effective vaccines can minimize the disease burden.MethodsThe types of vaccinations that are currently at the center of the most significant research are subunit vaccines. Outer membrane proteins, which are a component of the bacteria, are very well known to be effective at stimulating immune responses in the host. In this study, the gene encoding for outer membrane protein S2 (OmpS2) of E. tarda was identified, cloned, and sequenced, followed by in silico analysis.ResultThe structure and subcellular localization of the protein were first confirmed. Homology modeling of the whole protein was performed, and the protein was checked for its eligibility as a vaccine candidate. This was followed by identifying antigenic sites, B‐cell epitopes, and cytotoxic T‐lymphocyte epitopes on OmpS2. We obtained a few distinct vaccine peptides from OmpS2. The complete genome of E. tarda was subjected to genome analysis to identify potential epitopes that would bind to the fish major histocompatibility complex molecule and elicit both humoral and cell‐mediated immune responses.ConclusionThis study provides valuable insights for consideration of OmpS2 as a potential vaccine candidate against E. tarda infection.

Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A3 Receptor.

A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.

G45 and V386 in Transmembrane Domains 1 and 8 Are Critical for the Activation of OATP1B3-Mediated E17βG Uptake by Clotrimazole.

Organic anion-transporting polypeptides (OATPs) 1B1 and 1B3 are two highly homologous transport proteins. However, OATP1B1- and 1B3-mediated estradiol-17β-glucuronide (E17βG) uptake can be differentially affected by clotrimazole. In this study, by functional characterization on chimeric transporters and single mutants, we find that G45 in transmembrane domain 1 (TM1) and V386 in TM8 are critical for the activation of OATP1B3-mediated E17βG uptake by clotrimazole. However, the effect of clotrimazole on the function of OATP1B3 is substrate-dependent as clotrimazole does not stimulate OATP1B3-mediated uptake of 4',5'-dibromofluorescein (DBF) and rosuvastatin. In addition, clotrimazole is not transported by OATP1B3, but it can efficiently permeate the plasma membrane due to its lipophilic properties. Homology modeling and molecular docking indicate that E17βG binds in a substrate binding pocket of OATP1B3 through hydrogen bonding and hydrophobic interactions, among which its sterol scaffold forms hydrophobic contacts with V386. In addition, a flexible glycine residue at position 45 is essential for the activation of OATP1B3. Finally, clotrimazole is predicted to bind at an allosteric site, which mainly consists of hydrophobic residues located at the cytoplasmic halves of TMs 4, 5, 10, and 11.

Identification of potential inhibitors against Staphylococcus aureus shikimate dehydrogenase through virtual screening and susceptibility test

Staphylococcus aureus shikimate dehydrogenase (SaSDH) plays a crucial role in the growth of Staphylococcus aureus (S. aureus), but absent in mammals and therefore a potential target for antibacterial drugs to treat drug-resistant S. aureus infection. In this study, a 3D model of SaSDH was constructed by homology modelling and inhibitors of SaSDH were screened through virtual screening. (-)-Gallocatechin gallate and rhodiosin were identified as inhibitors with Kis of 2.47 μM and 73.38 μM, respectively. Molecular docking and isothermal titration calorimetry showed that both inhibitors interact with SaSDH with a KD of 44.65 μM for (-)-gallocatechin gallate and 16.45 μM for rhodiosin. Both inhibitors had antibacterial activity, showing MICs of 50 μg/mL for (-)-gallocatechin gallate and 250 μg/mL for rhodiosin against S. aureus. The current findings have the potential for identification of drugs to treat S. aureus infections by targeting SaSDH.

Molecular phylogeny, Sequence-based drug design, Docking built virtual screening, dynamics simulations, and ADMET properties of thiazolino 2-pyridone amide derivatives as an inhibitor of Chlamydia trachomatis and SARS-CoV-2 protein

The propagation of emerging diseases and the expensive cost and time lost by using the classic methods, especially in the current scenario with the world being plagued by SARS-CoV-2 and Chlamydia trachomatis diseases, make finding another way to invent new medication very important. That's why we used computational approaches to predict protein-ligand interactions of thiazolino 2-pyridone amide derivatives. The high-throughput virtual screening requires extensive combing through existing datasets in the hope of finding possible matches to screen for new molecules able to inhibit SARS-CoV-2 and Chlamydia trachomatis diseases. In this study, 46 thiazolino-2-pyridone amide derivatives were chosen for planning the powerful inhibitors by utilizing various strategies: QSAR analysis, phylogenetic analysis, homology modeling, docking simulation, molecular dynamics (MD) simulation, as well as ADMET Screening. The 2D QSAR investigation uncovers that these compounds show a satisfactory connection with bioactivity. From that point onward, phylogenetic analysis and homology modeling were used to model the selected receptors, which were then evaluated using both the SAVES and PROSA servers, indicating the best correctness of the modeled protein with the experimental results. Additionally, a docking simulation investigation was carried out to comprehend the 46 thiazolino-2-pyridone amide derivatives' interactions with homologous proteins. Additionally, MD simulations coupled with MM/GBSA verified the chosen complex systems' stability over 1000 ps. Two compounds were chosen as possible inhibitors based on these findings. The expected thiazolino-2-pyridone amide's oral bioavailability and toxicity have been discovered under the ADMET. Thus, these discoveries can be leveraged to develop novel molecules with the necessary action.

Revealing the degrading-possibility of methyl red by two azoreductases of Anoxybacillus sp. PDR2 based on molecular docking

Azo dyes, as the most widely used synthetic dyes, are considered to be one of the culprits of water resources and environmental pollution. Anoxybacillus sp. PDR2 is a thermophilic bacterium with the ability to degrade azo dyes, whose genome contains two genes encoding azoreductases (named AzoPDR2-1 and AzoPDR2-2). In this study, through response surface methodology (RSM), when the initial pH, inoculation volume and Mg2+ addition amount were 7.18, 10.72% and 0.1 g/L respectively, the decolorization rate of methyl red (MR) (200 mg/L) could reach its maximum (98.8%). The metabolites after biodegradation were detected by UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and liquid chromatography mass spectrometry (LC-MS/MS), indicating that MR was successfully decomposed into 4-aminobenzoic acid and other small substrates. In homologous modeling, it was found that both azoreductases were flavin-dependent azoreductases, and belonged to the α/β structure, using the Rossmann fold. In their docking results with the cofactor flavin mononucleotide (FMN), FMN bound to the surface of the protein dimer. Nicotinamide adenine dinucleotide (NADH) was superimposed on the plane of the pyrazine ring between FMN and the activity pocket of protein. Besides, both azoreductase complexes (azoreductase-FMN-NADH) exhibited a substrate preference for MR. Asn104 and Tyr74 played an important role in the combination of the azoreductase AzoPDR2-1 complex and the azoreductase AzoPDR2-2 complex with MR, respectively. This provided assistance for studying the mechanism of azoreductase biodegradation of azo dyes in thermophilic bacteria.

Comprehensive computational investigation for ligand recognition and binding dynamics of SdiA: a degenerate LuxR -type receptor in Klebsiella pneumoniae.

SdiA is a LuxR-type receptor that controls the virulence of Klebsiella pneumoniae, a Gram-negative bacterium that causes various infections in humans. SdiA senses exogenous acyl-homoserine lactones (AHLs) and autoinducer-2 (AI-2), two types of quorum sensing signals produced by other bacterial species. However, the molecular details of how SdiA recognizes and binds to different ligands and how this affects its function and regulation in K. pneumoniae still need to be better understood. This study uses computational methods to explore the protein-ligand binding dynamics of SdiA with 11 AHLs and 2 AI-2 ligands. The 3D structure of SdiA was predicted through homology modeling, followed by molecular docking with AHLs and AI-2 ligands. Binding affinities were quantified using MM-GBSA, and complex stability was assessed via Molecular Dynamics (MD) simulations. Results demonstrated that SdiA in Klebsiella pneumoniae exhibits a degenerate binding nature, capable of interacting with multiple AHLs and AI-2. Specific ligands, namely C10-HSL, C8-HSL, 3-oxo-C8-HSL, and 3-oxo-C10-HSL, were found to have high binding affinities and formed critical hydrogen bonds with key amino acid residues of SdiA. This finding aligns with the observed preference of SdiA for AHLs having 8 to 10 carbon-length acyl chains and lacking hydroxyl groups. In contrast, THMF and HMF demonstrated poor binding properties. Furthermore, AI-2 exhibited a low affinity, corroborating the inference that SdiA is not the primary receptor for AI-2 in K. pneumoniae. These findings provide insights into the protein-ligand binding dynamics of SdiA and its role in quorum sensing and virulence of K. pneumoniae.

In silico identification of quorum sensing inhibitors against LasR protein in a clinical isolate of multidrug resistant Pseudomonas aeruginosa DMC-27b

Background: Pseudomonas aeruginosa is an opportunistic pathogen that uses quorum-sensing (QS) and biofilm formation to subvert antibiotic therapy. Antibiotic resistance has led to a demand for alternative methods of treatment, and destabilizing the LasR-OdDHL binding with inhibitors offers a potential solution. Methods: This study aimed to construct a homology model of the LasR protein using the genetic sequence of the P. aeruginosa DMC-27b strain (GenBank: SMRY00000000.2). Molecular docking, molecular mechanics-based binding free energy calculation, and pharmacokinetic analysis were performed on 1900 3D structures collected from synthetic and natural compound databases to identify three potential lead molecules. These compounds were evaluated using ADMET (absorption, distribution, metabolism, excretion, toxicity) analysis, and molecular dynamics protocols were used to refine the results. Results: The three lead compounds showed higher binding capability with the LasR receptor than the native ligand and passed the ADMET evaluation stage. In total, 44 properties remained within the range of 95% of known drugs, indicating their potential efficacy as drugs against P. aeruginosa and other bacteria that use a similar QS system. Conclusions: This study provides insights into potential drug designing and development against clinical isolates of emerging P. aeruginosa strains and other bacteria that use a similar QS system.

HTLV-1 reverse transcriptase homology model provides structural basis for sensitivity to existing nucleoside/nucleotide reverse transcriptase inhibitors

The human T-lymphotropic virus type 1 (HTLV-1) infects millions of people globally and is endemic to various resource-limited regions. Infections persist for life and are associated with increased susceptibility to opportunistic infections and severe diseases including adult T cell leukemia/lymphoma and HTLV-1-associated myelopathy-tropical spastic paraparesis. No HTLV-1-specific anti-retrovirals have been developed and it is unclear whether existing anti-retrovirals developed for treatment of human immunodeficiency virus (HIV) have efficacy against HTLV-1. To understand the structural basis for therapeutic binding, homology modelling and machine learning were used to develop a structural model of the HTLV-1 reverse transcriptase. With this, molecular docking experiments using a panel of FDA-approved inhibitors of viral reverse transcriptases to assess their capacity for binding, and in turn, inhibition. Importantly, nucleoside/nucleotide reverse transcriptase inhibitor but not non-nucleoside reverse transcriptase inhibitors were predicted to bind the HTLV-1 reverse transcriptase, with similar affinity to HIV-1 reverse transcriptase. By strengthening the rationale for clinical testing of therapies such as tenofovir alafenamide, zidovudine, lamivudine, and azvudine for treatment of HTLV-1, this study has demonstrated the power of in silico structural biology approaches in drug design and therapeutic testing.

CsMYB73 negatively regulates theanine accumulation mediated by CsGGT2 and CsGGT4 in tea shoots (Camellia sinensis).

Theanine metabolism is a necessary biological process during the planting and production of tea that determines tea quality. There is currently little knowledge about the transcriptional regulation of theanine metabolism in tea plants. In this study, we demonstrated that γ-glutamyl-transpeptidase CsGGT4, as a homologous protein of the theanine hydrolase CsGGT2, exhibited a higher theanine synthesis catalytic efficiency. Homology modeling and molecular docking showed that differential protein structures between CsGGT2 and CsGGT4 implied their different biological functions in tea plants. Theanine content correlated significantly with the expression of CsGGT2, CsGGT4 and the transcription factor CsMYB73 in tea shoots from different seasons. Additionally, CsMYB73 was confirmed to act as a nucleus-localized transcription factor (TF), directly interacts with the CsGGT2 and CsGGT4 promoters, serving as an activator of CsGGT2 and a suppressor of CsGGT4. Consequently, this leads to a negative association with theanine accumulation in tea shoots. Furthermore, the continuous increase in CsMYB73 produced a significantly increase in CsGGT2 expression and inhibited CsGGT4 expression. The present study reveals that the degradation of theanine has been observed to increase, concomitantly with the inhibition of theanine synthesis, resulting in a significant decline in the accumulation of theanine in tea shoots during the process of seasonal greening in 'Huangkui' leaves. This study contributes to the broader comprehension of the intricate transcriptional regulatory hierarchy that governs the metabolism of theanine in tea shoots, offering novel approaches for managing tea plantations and enhancing tea quality.

Whole-genome sequencing of a protease-producing strain isolated from fermented golden pompano and molecular docking of the protease to fish proteins

In fermented fish products, microorganisms catalyze protein degradation by secreting proteases, thereby altering the nutritional values of foods. In this study, we isolated a high proteinase-producing strain from fermented golden pompano (Trachinotus ovatus), and from the 16S rRNA, we identified the strain as Bacillus tropicus, which we named Bacillus tropicus MX-8. This strain could form a distinct proteolytic circle around the colony when plated on agar containing 3% skimmed milk powder and could grow under 0–5% salinity. Its protease significantly degraded fish proteins. Genome sequencing analysis revealed that the genome of B. tropicus MX-8 comprised one circular chromosome and three circular plasmids. A total of 27 genes encoding proteases, including a neutral protease and three serine proteases, were identified in the non-redundant protein database. Homology modeling showed that serine protease 2 had the best model quality and the highest sequence match. Molecular docking experiments revealed the presence of several amino acid active sites on serine protease 2. These active sites mainly rely on hydrogen bonding to interact with actin heavy chains and myosin to form complexes, which can promote further protein degradation. This study demonstrated that B. tropicus MX-8 has the potential to ferment fish, providing a theoretical basis for the production of rapidly fermented fish products.

From amino acid analysis to improved gel properties: The role of dl-valine in Landaise goose myofibrillar protein

The impact of exogenous limiting amino acids on protein gel formation was investigated to enhance the gelation properties of Landaise goose myofibrillar protein (MP). Amino acid composition and gel properties were analyzed, and homologous protein modeling and molecular docking techniques were used to simulate binding sites. Valine was identified as the first limiting amino acid. The addition of 0.075 % dl-valine proved optimal to enhance the gel strength (59.5 g) and water retention (76.76 %) of MP gels. Hydrophobic interactions and disulfide bonds were found to be the main forces maintaining conformational stability of the MP-dl-valine gels. The propyl group of dl-valine can form hydrophobic interactions with protein, contributing to stable complexes. DL valine could also strengthen chemical bonds and secondary structure, convert free water to immobile water, and improve the microstructure of the gel. Therefore, valine can be utilized as a nutritional and gel enhancer in Landaise goose meat products.

Chrysin Inhibits Indonesian Serotype Foot-and-Mouth-Disease Virus Replication: Insights from DFT, Molecular Docking and Dynamics Analyses

Chrysin, a predominant compound in Propolis, possesses diverse bioactivities, including antiviral properties. However, its antiviral efficacy against the Indonesian Foot-and-Mouth Disease Virus (FMDV) serotype remains unexplored. This study investigates Chrysin's inhibitory potential against FMDV Indonesian serotype by targeting the 3C Protease (3CP), a vital enzyme for viral replication. Multiple sequence alignment was used to reveal unique characteristics of the Indonesian serotype's 3CP compared to global serotypes. Density Functional Theory (DFT) calculations assessed Chrysin's interaction with 3CP based on electronegativity. Molecular docking and molecular dynamics analyses evaluated Chrysin's inhibitory activity against 3CP, using homology modeling for the Indonesian serotype's 3CP structure. Luteolin, a known FMDV 3CP inhibitor with a similar structure to Chrysin, served as a reference. Results showed distinct 3CP sequences in the Indonesian serotype compared to O serotypes and others. Chrysin exhibited potential electron-donor activity with lower HOMO and LUMO values than Luteolin, but they had similar energy gaps, i.e., 4.016 and 4.044 eV, respectively. Molecular docking indicated similar binding affinities, with Chrysin (-6.365 kcal/mol) and Luteolin (-6.864 kcal/mol) bound to active site residues. Molecular dynamics analysis demonstrated stable 3CP-Chrysin and 3CP-Luteolin complexes, with minor differences in Radius of gyration (Rg) and Root-Mean-Square Fluctuation (RMSF) below 1 Å. From the ligand stability point of view, Chrysin had comparable stability with Luteolin. However, Chrysin formed fewer hydrogen bonds and displayed greater free-binding energy than Luteolin during simulation periods. These findings suggest that Chrysin holds promise as an inhibitor of the Indonesian serotype's FMDV 3C Protease.

Pathway crosstalk between the central metabolic and heme biosynthetic pathways in Phanerochaete chrysosporium

A comprehensive analysis to survey heme-binding proteins produced by the white-rot fungus Phanerochaete chrysosporium was achieved using a biotinylated heme–streptavidin beads system. Mitochondrial citrate synthase (PcCS), glyceraldehyde 3-phosphate dehydrogenase (PcGAPDH), and 2-Cys thioredoxin peroxidase (mammalian HBP23 homolog) were identified as putative heme-binding proteins. Among these, PcCS and PcGAPDH were further characterized using heterologously expressed recombinant proteins. Difference spectra of PcCS titrated with hemin exhibited an increase in the Soret absorbance at 414 nm, suggesting that the axial ligand of the heme is a His residue. The activity of PcCS was strongly inhibited by hemin with Ki oxaloacetate of 8.7 μM and Ki acetyl-CoA of 5.8 μM. Since the final step of heme biosynthesis occurred at the mitochondrial inner membrane, the inhibition of PcCS by heme is thought to be a physiological event. The inhibitory mode of the heme was similar to that of CoA analogues, suggesting that heme binds to PcCS at His347 at the AcCoA–CoA binding site, which was supported by the homology model of PcCS. PcGAPDH was also inhibited by heme, with a lower concentration than that for PcCS. This might be caused by the different location of these enzymes. From the integration of these phenomena, it was concluded that metabolic regulations by heme in the central metabolic and heme synthetic pathways occurred in the mitochondria and cytosol. This novel pathway crosstalk between the central metabolic and heme biosynthetic pathways, via a heme molecule, is important in regulating the metabolic balance (heme synthesis, ATP synthesis, flux balance of the tricarboxylic acid (TCA) cycle and cellular redox balance (NADPH production) during fungal aromatic degradation.Key points• A comprehensive survey of heme-binding proteins in P. chrysosporium was achieved.• Several heme-binding proteins including CS and GAPDH were identified.• A novel metabolic regulation by heme in the central metabolic pathways was found.

In Silico Therapeutic Study: The Next Frontier in the Fight against SARS-CoV-2 and Its Variants

COVID-19 has claimed around 7 million lives (from December 2019–November 2023) worldwide and continues to impact global health. SARS-CoV-2, the virus causing COVID-19 disease, is characterized by a high rate of mutations, which contributes to its rapid spread, virulence, and vaccine escape. While several vaccines have been produced to minimize the severity of the coronavirus, and diverse treatment regimens have been approved by the US FDA under Emergency Use Authorization (EUA), SARS-CoV-2 viral mutations continue to derail the efforts of scientists as the emerging variants evade the recommended therapies. Nonetheless, diverse computational models exist that offer an opportunity for the swift development of new drugs or the repurposing of old drugs. In this review, we focus on the use of various virtual screening techniques like homology modeling, molecular docking, molecular dynamics simulations, QSAR, pharmacophore modeling, etc., in repurposing SARS-CoV-2 therapeutics against major variants of SARS-CoV-2 (Alpha, Beta, Gamma, Delta, and Omicron). The results have been promising from the computer-aided drug design (CADD) studies in suggesting potential compounds for the treatment of COVID-19 variants. Hence, in silico therapeutic studies represent a transformative approach that holds great promise in advancing our fight against the ever-evolving landscape of SARS-CoV-2 and its variants.

Phylogenetic conservation of Trop-2 across species-rodent and primate genomics model anti-Trop-2 therapy for pre-clinical benchmarks.

A phylogenetic conservation analysis of Trop-2 across vertebrate species showed a high degree of sequence conservation, permitting to explore multiple models as pre-clinical benchmarks. Sequence divergence and incomplete conservation of expression patterns were observed in mouse and rat. Primate Trop-2 sequences were found to be 95%-100% identical to the human sequence. Comparative three-dimension primate Trop-2 structures were obtained with AlphaFold and homology modeling. This revealed high structure conservation of Trop-2 (0.66 ProMod3 GMQE, 0.80-0.86 ± 0.05 QMEANDisCo scores), with conservative amino acid changes at variant sites. Primate TACSTD2/TROP2 cDNAs were cloned and transfectants for individual ORF were shown to be efficiently recognized by humanized anti-Trop-2 monoclonal antibodies (Hu2G10, Hu2EF). Immunohistochemistry analysis of Macaca mulatta (rhesus monkey) tissues showed Trop-2 expression patterns that closely followed those in human tissues. This led us to test Trop-2 targeting in vivo in Macaca fascicularis (cynomolgus monkey). Intravenously injected Hu2G10 and Hu2EF were well tolerated from 5 to 10mg/kg. Neither neurological, respiratory, digestive, urinary symptoms, nor biochemical or hematological toxicities were detected during 28-day observation. Blood serum pharmacokinetic (PK) studies were conducted utilizing anti-idiotypic antibodies in capture-ELISA assays. Hu2G10 (t1/2 = 6.5days) and Hu2EF (t1/2 = 5.5days) were stable in plasma, and were detectable in the circulation up to 3weeks after the infusion. These findings validate primates as reliable models for Hu2G10 and Hu2EF toxicity and PK, and support the use of these antibodies as next-generation anti-Trop-2 immunotherapy tools.

Molecular dynamic approach in the regulation of systemic XCT antiporter through biologically active molecules for ischemic stroke

ABSTRACT The heterodimeric amino acid transporter systemic XCT plays a crucial role in redox balance regulation by facilitating L-cystine and L-glutamate import/export in a 1:1 ratio. Translating findings from preclinical to clinical contexts poses challenges due to interspecies receptor variations. To understand these differences and achieve success during translating studies, in silico analysis of FDA-approved drugs was performed against three species for systemic XCT receptors with UniProt-ids D4ADU2 (Rattus norvegicus), Q9WTR6 (Mus musculus), and Q9UPY5 (Homo sapiens). Homology modelling produced validated 3D structures for D4ADU2 and Q9WTR6, achieving an excellent model quality score (∼84%). Virtual screening identified common hits in Rat and Mouse Homology Modelled Structures (RHMS and MHMS), including Avodart, Rolapitant, and Olmesartan. In Homo sapiens (PDBs 7P9U and 7P9 V), common hits Dihydroergotamine and Ergotamine showed binding affinities of −12.3 to −10.1 kcal/mol as compared to glutamate and cystine (−4.9 to −5.9 kcal/mol) within the same binding pocket. A 500 ns MD simulation confirmed structural stability, positive correlations and limited atomic displacements. Free energy calculations highlighted the top compounds highly favourable binding affinities across all receptors. These results shed light on structural and dynamical variations among the interspecies receptors-ligands interactions which provide valuable insights into transitioning from preclinical to clinical settings.

In Silico Study on Natural Chemical Compounds from Citric Essential Oils as Potential Inhibitors of an Omicron (BA.1) SARS-CoV-2 Mutants' Spike Glycoprotein.

SARS-CoV-2's remarkable capacity for genetic mutation enables it to swiftly adapt to environmental changes, influencing critical attributes, such as antigenicity and transmissibility. Thus, multi-target inhibitors capable of effectively combating various viral mutants concurrently are of great interest. This study aimed to investigate natural compounds that could unitedly inhibit spike glycoproteins of various Omicron mutants. Implementation of various in silico approaches allows us to scan a library of compounds against a variety of mutants in order to find the ones that would inhibit the viral entry disregard of occurred mutations. An extensive analysis of relevant literature was conducted to compile a library of chemical compounds sourced from citrus essential oils. Ten homology models representing mutants of the Omicron variant were generated, including the latest 23F clade (EG.5.1), and the compound library was screened against them. Subsequently, employing comprehensive molecular docking and molecular dynamics simulations, we successfully identified promising compounds that exhibited sufficient binding efficacy towards the receptor binding domains (RBDs) of the mutant viral strains. The scoring of ligands was based on their average potency against all models generated herein, in addition to a reference Omicron RBD structure. Furthermore, the toxicity profile of the highest-scoring compounds was predicted. Out of ten built homology models, seven were successfully validated and showed to be reliable for In Silico studies. Three models of clades 22C, 22D, and 22E had major deviations in their secondary structure and needed further refinement. Notably, through a 100 nanosecond molecular dynamics simulation, terpinen-4-ol emerged as a potent inhibitor of the Omicron SARS-CoV-2 RBD from the 21K clade (BA.1); however, it did not show high stability in complexes with other mutants. This suggests the need for the utilization of a larger library of chemical compounds as potential inhibitors. The outcomes of this investigation hold significant potential for the utilization of a homology modeling approach for the prediction of RBD's secondary structure based on its sequence when the 3D structure of a mutated protein is not available. This opens the opportunities for further advancing the drug discovery process, offering novel avenues for the development of multifunctional, non-toxic natural medications.

Synthesis, in vitro potency of inhibition, enzyme kinetics and in silico studies of quinoline-based α-glucosidase inhibitors

Diabetes mellitus is a multifactorial global health disorder that is rising at an alarming rate. One effective therapeutic approach for controlling hyperglycemia associated with type-2 diabetes is to target α-glucosidase, which catalyzes starch hydrolysis in the intestine. In an attempt to find potential α-glucosidase inhibitors, a series of twenty new quinoline linked benzothiazole hybrids (8a–t) were synthesized in good yields from suitable reaction procedures and their chemical structures were analyzed by 1HNMR, 13CNMR, IR, and ESI–MS analysis. The synthesized derivatives further screened for their activity against α-glucosidase. Among them, compounds 8b, 8h, 8n and 8o exhibited remarkable α-glucosidase inhibitory activity with IC50 values ranging from 38.2 ± 0.3 to 79.9 ± 1.2 µM compared with standard drug acarbose (IC50 = 750.0 ± 2.0 µM). Enzyme kinetic studies of the most active compound (8h) indicated a non-competitive inhibition with Ki value of 38.2 µM. Moreover, the homology modeling, molecular docking and molecular dynamics simulation studies were conducted to reveal key interactions between the most active compound 8h and the targeted enzyme. These results are complementary to the experimental observations. In order to predict the druggability of the novel derivatives, the pharmacokinetic properties were also applied. These findings could be useful for the design and development of new α-glucosidase inhibitors.

Control list of high-priority chemicals based on 5-HT-RI functionality and the human health interference effects selective CNN-GRU deep learning model

The antidepressant drug known as 5-HT reuptake inhibitor (5-HT-RI) was commonly detected in biological tissues and result in significant adverse health effects. Homology modeling was used to characterize the functionalities (efficacy and resistance), and the adverse outcome pathway was used to characterize its human health interferences (olfactory toxicity, neurotoxicity, and gut microbial interference). The convolutional neural network coupled with the gated recurrent unit (CNN-GRU) deep learning method was used to construct a comprehensive model of 5-HT-RI functionality and human health interference effects selectivity with small sample data. The architecture with 2 SE, 320 neuronal nodes and 6-folds cross-validation showed the best applicability. The results showed that the confidence interval of the constructed model reached 90 % indicating that the model had reliable prediction ability and generalization ability. Based on the CNN-GRU deep learning model, seven high-priority chemicals with a weak comprehensive effect, including D-VEN, (1R,4S)-SER, S-FLX, CTP, S-CTP, NEF, and VEN, were screened. Based on the molecular three-dimensional structure information, a comprehensive-effect three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed to confirm the reliability of the constructed control list of 5-HT-RI high-priority chemicals. Analysis with the ranking of calculated values based on the molecular dynamics method and predicted values based on the CNN-GRU deep learning model, we found that the consistency of the three methods was above 85 %. Additionally, by analyzing the sensitivity, molecular electrostatic potential, polar surface area of the comprehensive-effect CNN-GRU deep learning model, and the electrostatic field of the 3D-QSAR models, we found that the significant effects of five key characteristics (DM, Qyy, Qxz, I, and BP), molecular electronegativity, and polarity significantly affected the high-priority degree of 5-HT-RI. In this study, we provided reasonable and reliable prediction tools and discussed theoretical methods for the risk assessment of functionality and human health interference of emerging pollutants such as 5-HT-RI.