Identification of phytochemical compounds of Fagopyrum dibotrys and their targets by metabolomics, network pharmacology and molecular docking studies.

Acute lung injury (ALI) is a clinically severe lung illness with high incidence rate and mortality. Especially, coronavirus disease 2019 (COVID-19) poses a serious threat to world wide governmental fitness. It has distributed to almost from corner to corner of the universe, and the situation in the prevention and control of COVID-19 remains grave. Traditional Chinese medicine plays a vital role in the precaution and therapy of sicknesses. At present, there is a lack of drugs for treating these diseases, so it is necessary to develop drugs for treating COVID-19 related ALI. Fagopyrum dibotrys (D. Don) Hara is an annual plant of the Polygonaceae family and one of the long-history used traditional medicine in China. In recent years, its rhizomes (medicinal parts) have attracted the attention of scholars at home and abroad due to their significant anti-inflammatory, antibacterial and anticancer activities. It can work on SARS-COV-2 with numerous components, targets, and pathways, and has a certain effect on coronavirus disease 2019 (COVID-19) related acute lung injury (ALI). However, there are few systematic studies on its aerial parts (including stems and leaves) and its potential therapeutic mechanism has not been studied. The phytochemical constituents of rhizome of F. dibotrys were collected using TCMSP database. And metabolites of F. dibotrys' s aerial parts were detected by metabonomics. The phytochemical targets of F. dibotrys were predicted by the PharmMapper website tool. COVID-19 and ALI-related genes were retrieved from GeneCards. Cross targets and active phytochemicals of COVID-19 and ALI related genes in F. dibotrys were enriched by gene ontology (GO) and KEGG by metscape bioinformatics tools. The interplay network entre active phytochemicals and anti COVID-19 and ALI targets was established and broke down using Cytoscape software. Discovery Studio (version 2019) was used to perform molecular docking of crux active plant chemicals with anti COVID-19 and ALI targets. We identified 1136 chemicals from the aerial parts of F. dibotrys, among which 47 were active flavonoids and phenolic chemicals. A total of 61 chemicals were searched from the rhizome of F. dibotrys, and 15 of them were active chemicals. So there are 6 commonly key active chemicals at the aerial parts and the rhizome of F. dibotrys, 89 these phytochemicals's potential targets, and 211 COVID-19 and ALI related genes. GO enrichment bespoken that F. dibotrys might be involved in influencing gene targets contained numerous biological processes, for instance, negative regulation of megakaryocyte differentiation, regulation of DNA metabolic process, which could be put down to its anti COVID-19 associated ALI effects. KEGG pathway indicated that viral carcinogenesis, spliceosome, salmonella infection, coronavirus disease - COVID-19, legionellosis and human immunodeficiency virus 1 infection pathway are the primary pathways obsessed in the anti COVID-19 associated ALI effects of F. dibotrys. Molecular docking confirmed that the 6 critical active phytochemicals of F. dibotrys, such as luteolin, (+) -epicatechin, quercetin, isorhamnetin, (+) -catechin, and (-) -catechin gallate, can combine with kernel therapeutic targets NEDD8, SRPK1, DCUN1D1, and PARP1. In vitro activity experiments showed that the total antioxidant capacity of the aerial parts and rhizomes of F. dibotrys increased with the increase of concentration in a certain range. In addition, as a whole, the antioxidant capacity of the aerial part of F. dibotrys was stronger than that of the rhizome. Our research afford cues for farther exploration of the anti COVID-19 associated ALI chemical compositions and mechanisms of F. dibotrys and afford scientific foundation for progressing modern anti COVID-19 associated ALI drugs based on phytochemicals in F. dibotrys. We also fully developed the medicinal value of F. dibotrys' s aerial parts, which can effectively avoid the waste of resources. Meanwhile, our work provides a new strategy for integrating metabonomics, network pharmacology, and molecular docking techniques which was an efficient way for recognizing effective constituents and mechanisms valid to the pharmacologic actions of traditional Chinese medicine.

Computational tools for exploring peptide-membrane interactions in gram-positive bacteria.

The vital cellular functions in Gram-positive bacteria are controlled by signaling molecules known as quorum sensing peptides (QSPs), considered promising therapeutic interventions for bacterial infections. In the bacterial system QSPs bind to membrane-coupled receptors, which then auto-phosphorylate and activate intracellular response regulators. These response regulators induce target gene expression in bacteria. One of the most reliable trends in drug discovery research for virulence-associated molecular targets is the use of peptide drugs or new functionalities. In this perspective, computational methods act as auxiliary aids for biologists, where methodologies based on machine learning and in silico analysis are developed as suitable tools for target peptide identification. Therefore, the development of quick and reliable computational resources to identify or predict these QSPs along with their receptors and inhibitors is receiving considerable attention. The databases such as Quorumpeps and Quorum Sensing of Human Gut Microbes (QSHGM) provide a detailed overview of the structures and functions of QSPs. The tools and algorithms such as QSPpred, QSPred-FL, iQSP, EnsembleQS and PEPred-Suite have been used for the generic prediction of QSPs and feature representation. The availability of compiled key resources for utilizing peptide features based on amino acid composition, positional preferences, and motifs as well as structural and physicochemical properties, including biofilm inhibitory peptides, can aid in elucidating the QSP and membrane receptor interactions in infectious Gram-positive pathogens. Herein, we present a comprehensive survey of diverse computational approaches that are suitable for detecting QSPs and QS interference molecules. This review highlights the utility of these methods for developing potential biomarkers against infectious Gram-positive pathogens.

Bioinformatics evaluation of anticancer properties of GP63 protein-derived peptides on MMP2 protein of melanoma cancer.

Background: GP63, also known as Leishmanolysin, is a multifunctional virulence factor abundant on the surface of Leishmania spp. small peptides with anticancer capabilities that are selective and toxic to cancer cells are known as anticancer peptides. We aimed to demonstrate the activity of GP63 and its anticancer properties on melanoma using a range of in silico tools and screening methods to identify predicted and designed anticancer peptides. Methods: Various in silico modeling methodologies are used to establish the three-dimensional (3D) structure of GP63. Refinement and re-evaluation of the modeled structures and the built models' quality evaluated using the different docking used to find the interacting amino acids between MMP2 and GP63 and its anticancer peptides. AntiCP2.0 is used for screening anticancer peptides. 2D interaction plots of protein-ligand complexes evaluated by Protein-Ligand Interaction Profiler server. It is for the first time that used anticancer peptides of GP63 and the predicted and designed peptides. Results: We used 3 peptides of GP63 based on the AntiCP 2.0 server with scores of 0.63, 0.53, and 0.49, and common peptides of GP63/MMP2 (continues peptide: mean the completely selected peptide after docking with non-anticancer effect, predicted with 0.58 score and designed peptides with 0.47 and 0.45 scores by AntiCP 2.0 server). Conclusions: The antileishmanial and anticancer peptide research topics exemplify the multidisciplinary nature of peptide research. The advancement of therapeutics targeting cancer and/or Leishmania requires an interconnected research strategy shown in this work.

Repurposing of drugs for combined treatment of COVID-19 cytokine storm using machine learning.

Severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) induced cytokine storm is the major cause of COVID-19 related deaths. Patients have been treated with drugs that work by inhibiting a specific protein partly responsible for the cytokines production. This approach provided very limited success, since there are multiple proteins involved in the complex cell signaling disease mechanisms. We targeted five proteins: Angiotensin II receptor type 1 (AT1R), A disintegrin and metalloprotease 17 (ADAM17), Nuclear Factor­Kappa B (NF­κB), Janus kinase 1 (JAK1) and Signal Transducer and Activator of Transcription 3 (STAT3), which are involved in the SARS­CoV­2 induced cytokine storm pathway. We developed machine-learning (ML) models for these five proteins, using known active inhibitors. After developing the model for each of these proteins, FDA-approved drugs were screened to find novel therapeutics for COVID­19. We identified twenty drugs that are active for four proteins with predicted scores greater than 0.8 and eight drugs active for all five proteins with predicted scores over 0.85. Mitomycin C is the most active drug across all five proteins with an average prediction score of 0.886. For further validation of these results, we used the PyRx software to conduct protein-ligand docking experiments and calculated the binding affinity. The docking results support findings by the ML model. This research study predicted that several drugs can target multiple proteins simultaneously in cytokine storm-related pathway. These may be useful drugs to treat patients because these therapies can fight cytokine storm caused by the virus at multiple points of inhibition, leading to synergistically effective treatments.

Unexpected diversity of dye-decolorizing peroxidases.

Dye-decolorizing peroxidase (DyP)-type peroxidases are a family of heme-containing peroxidases. Because DyP-type peroxidases can degrade recalcitrant anthraquinone dyes and lignin, their potential applications in the treatment of wastewater containing dyes and lignin degradation are expected. Although many DyP-type peroxidases have been characterized experimentally, most of the reported DyP-type peroxidases are from basidiomycetous fungi and bacteria. Therefore, the taxonomic distribution of the DyP-type peroxidases remains unclear. In this study, we analyzed the phylogenetic tree using all DyP-type peroxidase sequences available in the InterPro database. The findings mainly divided this family into three classes. Metazoa and Archaea also have the genes coding for DyP-type peroxidases, and the sequences belonging to two subclasses have the pyruvate formate lyase or cytochrome P450 domain in addition to the DyP domain. This study reveals differences in the conservation of important residues among classes. The findings will accelerate research on the DyP-type peroxidase family.

Fully automated virtual screening pipeline of FDA-approved drugs using Caver Web.

Protein tunnels are essential in transporting small molecules into the active sites of enzymes. Tunnels' geometrical and physico-chemical properties influence the transport process. The tunnels are attractive hot spots for protein engineering and drug development. However, studying the ligand binding and unbinding using experimental techniques is challenging, while in silico methods come with their limitations, especially in the case of resource-demanding virtual screening pipelines. Caver Web 1.2 is a new version of the web server combining the capabilities for the detection of protein tunnels with the calculation of the ligand trajectories. The new version of the Caver Web server was expanded with the ability to fetch novel ligands from the Integrated Database of Small Molecules and with the fully automated virtual screening pipeline allowing for the fast evaluation of the predefined set of over 4,300 currently approved drugs. The virtual screening pipeline is accompanied by a comprehensive user interface, making it a viable service for the broader spectrum of companies and the academic user community. The web server is freely available for academic use at https://loschmidt.chemi.muni.cz/caverweb.

Recent developments on UDP-N-acetylmuramoyl-L-alanine-D-gutamate ligase (Mur D) enzyme for antimicrobial drug development: An emphasis on in-silico approaches.

Introduction: The rapid emergence of antibiotic resistance among various bacterial pathogens has been one of the major concerns of health organizations across the world. In this context, for the development of novel inhibitors against antibiotic-resistant bacterial pathogens, UDP-N-Acetylmuramoyl-L-Alanine-D-Glutamate Ligase (MurD) enzyme represents one of the most apposite targets. Body: The present review focuses on updated advancements on MurD-targeted inhibitors in recent years along with genetic regulation, structural and functional characteristics of the MurD enzyme from various bacterial pathogens. A concise account of various crystal structures of MurD enzyme, submitted into Protein Data Bank is also discussed. Discussion: MurD, an ATP dependent cytoplasmic enzyme is an important target for drug discovery. The genetic organization of MurD enzyme is well elucidated and many crystal structures of MurD enzyme are submitted into Protein Data bank. Various inhibitors against MurD enzyme have been developed so far with an increase in the use of in-silico methods in the recent past. But cell permeability barriers and conformational changes of MurD enzyme during catalytic reaction need to be addressed for effective drug development. So, a combination of in-silico methods along with experimental work is proposed to counter the catalytic machinery of MurD enzyme.

Bellidifolin from Gentianella acuta (Michx.) Hulten protects H9c2 cells from hydrogen peroxide-induced injury via the PI3K-Akt signal pathway.

Cardiovascular disease is the most common disease in the world and the first among the causes of human death. Its morbidity and mortality increase annually, but no effective treatment is available. Therefore, new drugs should be developed to treat cardiovascular disease. Gentianella acuta (Michx.) Hulten (G. acuta) is an important Mongolian medicine in China and elicits protective effects on cardiovascular health. In this study, liquid chromatography-mass spectrometry (LC-MS) combined with network pharmacology was used to screen the main active ingredients and confirm that bellidifolin was one of the main components for the treatment of ischemic heart disease. Then, rat myocardial (H9c2) cells injury model induced by hydrogen peroxide (H2O2) in vitro was established to verify the effect of bellidifolin on oxidative stress stimulation, including determination of antioxidant enzyme activity and apoptosis. Transcriptome sequencing, qRT-PCR, and western blot were performed to further verify the antioxidant stress mechanism of bellidifolin. Results showed that bellidifolin pretreatment decreased the rate of apoptosis and the levels of lactate dehydrogenase (LDH), creatine kinase (CK), and alanine aminotransferase (ALT). Conversely, it increased the contents of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in a dose-dependent manner, indicating that bellidifolin caused a protective effect on cardiomyocyte injury. Bellidifolin minimized the H2O2-induced cell injury by activating the PI3K-Akt signal pathway and downregulating glycogen synthase kinase-3ß (GSK-3ß) and p-Akt1/Akt1. Therefore, this work revealed that G. acuta has a good development prospect as an edible medicinal plant in cardiovascular disease. Its bellidifolin component is a potential therapeutic agent for cardiovascular disease induced by oxidative stress damage.

Curvature model for nanoparticle size effects on peptide fibril stability and molecular dynamics simulation data.

Nanostructured surfaces are widespread in nature and are being further developed in materials science. This makes them highly relevant for biomolecules, such as peptides. In this data article, we present a curvature model and molecular dynamics (MD) simulation data on the influence of nanoparticle size on the stability of amyloid peptide fibrils related to our research article entitled "Mechanistic insights into the size-dependent effects of nanoparticles on inhibiting and accelerating amyloid fibril formation" (John et al., 2022) [1]. We provide the code to perform MD simulations in GROMACS 4.5.7 software of arbitrarily chosen biomolecule oligomers adsorbed on a curved surface of chosen nanoparticle size. We also provide the simulation parameters and data for peptide oligomers of Aß40, NNFGAIL, GNNQQNY, and VQIYVK. The data provided allows researchers to further analyze our MD simulations and the curvature model allows for a better understanding of oligomeric structures on surfaces.

Multiscale modelling of claudin-based assemblies: A magnifying glass for novel structures of biological interfaces.

Claudins (Cldns) define a family of transmembrane proteins that are the major determinants of the tight junction integrity and tissue selectivity. They promote the formation of either barriers or ion-selective channels at the interface between two facing cells, across the paracellular space. Multiple Cldn subunits form complexes that include cis- (intracellular) interactions along the membrane of a single cell and trans- (intercellular) interactions across adjacent cells. The first description of Cldn assemblies was provided by electron microscopy, while electrophysiology, mutagenesis and cell biology experiments addressed the functional role of different Cldn homologs. However, the investigation of the molecular details of Cldn subunits and complexes are hampered by the lack of experimental native structures, currently limited to Cldn15. The recent implementation of computer-based techniques greatly contributed to the elucidation of Cldn properties. Molecular dynamics simulations and docking calculations were extensively used to refine the first Cldn multimeric model postulated from the crystal structure of Cldn15, and contributed to the introduction of a novel, alternative, arrangement. While both these multimeric assemblies were found to account for the physiological properties of some family members, they gave conflicting results for others. In this review, we illustrate the major findings on Cldn-based systems that were achieved by using state-of-the-art computational methodologies. The information provided by these results could be useful to improve the characterization of the Cldn properties and help the design of new efficient strategies to control the paracellular transport of drugs or other molecules.

Biochemical, structural, and computational studies of a γ-carbonic anhydrase from the pathogenic bacterium Burkholderia pseudomallei.

Melioidosis is a severe disease caused by the highly pathogenic gram-negative bacterium Burkholderia pseudomallei. Several studies have highlighted the broad resistance of this pathogen to many antibiotics and pointed out the pivotal importance of improving the pharmacological arsenal against it. Since γ-carbonic anhydrases (γ-CAs) have been recently introduced as potential and novel antibacterial drug targets, in this paper, we report a detailed characterization of BpsγCA, a γ-CA from B. pseudomallei by a multidisciplinary approach. In particular, the enzyme was recombinantly produced and biochemically characterized. Its catalytic activity at different pH values was measured, the crystal structure was determined and theoretical pKa calculations were carried out. Results provided a snapshot of the enzyme active site and dissected the role of residues involved in the catalytic mechanism and ligand recognition. These findings are an important starting point for developing new anti-melioidosis drugs targeting BpsγCA.

Gene and protein interaction network analysis in the epithelial-mesenchymal transition of Hertwig's Epithelial Root Sheath reveals periodontal regenerative drug targets - An in silico study.

Background and aim: Hertwig's Εpithelial Root Sheath (HΕRS) has a major function in the developing tooth roots. Earlier research revealed that it undergoes epithelial-mesenchymal transition, a vital process for the morphogenesis and complete development of the tooth and its surrounding periodontium. Few studies have demonstrated the role of HERS in cementogenesis through ΕMΤ. The background of this in-silico system biology approach is to find a hub protein and gene involved in the EMT of HERS that may uncover novel insights in periodontal regenerative drug targets. Materials and methods: The protein and gene list involved in epithelial-mesenchymal transition were obtained from literature sources. The protein interaction was constructed using STRING software and the protein interaction network was analyzed. Molecular docking simulation checks the binding energy and stability of protein-ligand complex. Results: Results revealed the hub gene to be DYRK1A(Hepcidin), and the ligand was identified as isoetharine. SΤRIΝG results showed a confidence cutoff of 0.9 in sensitivity analysis with a condensed protein interaction network. Overall, 98 nodes from 163 nodes of expected edges were found with an average node degree of 11.9. Docking results show binding energy of -4.70, and simulation results show an RMSD value of 5.6 Å at 50 ns. Conclusion: Isoetharine could be a potential drug for periodontal regeneration.

Unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitors: Molecular docking, molecular dynamics, and ADME scoring investigations.

COVID-19 pandemic caused by very severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) agent is an ongoing major global health concern. The disease has caused more than 452 million affected cases and more than 6 million death worldwide. Hence, there is an urgency to search for possible medications and drug treatments. There are no approved drugs available to treat COVID-19 yet, although several vaccine candidates are already available and some of them are listed for emergency use by the world health organization (WHO). Identifying a potential drug candidate may make a significant contribution to control the expansion of COVID-19. The in vitro biological activity of asymmetric disulfides against coronavirus through the inhibition of SARS-CoV-2 main protease (Mpro) protein was reported. Due to the lack of convincing evidence those asymmetric disulfides have favorable pharmacological properties for the clinical treatment of Coronavirus, in silico evaluation should be performed to assess the potential of these compounds to inhibit the SARS-CoV-2 Mpro. In this context, we report herein the molecular docking for a series of 40 unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitor. The optimal binding features of disulfides within the binding pocket of SARS-CoV-2 endoribonuclease protein (Protein Data Bank [PDB]: 6LU7) was described. Studied compounds were ranked for potential effectiveness, and those have shown high molecular docking scores were proposed as novel drug candidates against SARS-CoV-2. Moreover, the outcomes of drug similarity and ADME (Absorption, Distribution, Metabolism, and Excretion) analyses have may have the effectiveness of acting as medicines, and would be of interest as promising starting point for designing compounds against SARS-CoV-2. Finally, the stability of these three compounds in the complex with Mpro was validated through molecular dynamics (MD) simulation, in which they displayed stable trajectory and molecular properties with a consistent interaction profile.

Inactivation of SARS-CoV-2 by charged particles for Future Vaccine Production Applications: A Monte Carlo study.

The world is still suffering from the SARS-CoV-2 pandemic, and the number of infected people is still growing in many countries in 2022. Although great strides have been made to produce effective vaccines, efforts in this field should be accelerated, particularly due to the emergence of new variants. Using inactivated viruses is a conventional method of vaccine production. High levels of ionizing radiation can effectively inactivate viruses. Recently, studies on SARS-CoV-2 irradiation using low-LET radiations (e.g., gamma rays) have been performed. However, there are insufficient studies on the impact of charged particles on the inactivation of this virus. In this study, a realistic structure of SARS-CoV-2 is simulated by using Geant4 Monte Carlo toolkit, and the effect of electrons, protons, alphas, C-12, and Fe-56 ions on the inactivation of SARS-CoV-2 is investigated. The simulation results indicated that densely ionizing (high-LET) particles have the advantage of minimum number of damaged spike proteins per single RNA break. The RNA breaks induced by hydroxyl radicals produced in the surrounding water medium were significant only for electron beam radiation. Hence, indirect RNA breaks induced by densely ionizing particles is negligible. From a simulation standpoint, alpha particles (with energies up to 30 MeV) as well as C-12 ions (with energies up to 80 MeV/n), and Fe-56 ions (with any energy) can be introduced as particles of choice for effective SARS-CoV-2 inactivation.

A cryptic phosphate-binding pocket on the SPFH domain of human stomatin that regulates a novel fibril-like self-assembly.

Human stomatin (hSTOM) is a component of the membrane skeleton of erythrocytes that maintains the membrane's shape and stiffness through interconnecting spectrin and actin. hSTOM is a member of the protein family that possesses a single stomatin/prohibitin/flotillin/HflK (SPFH) domain at the center of the molecule. Although SPFH domain proteins are widely distributed from archaea to mammals, the detailed function of the domain remains unclear. In this study, we first determined the solution structure of the SPFH domain of hSTOM (hSTOM(SPFH)) via NMR. The solution structure of hSTOM(SPFH) is essentially identical to the already reported crystal structure of the STOM SPFH domain (mSTOM(SPFH)) of mice, except for the existence of a small hydrophilic pocket on the surface. We identified this pocket as a phosphate-binding site by comparing its NMR spectra with and without phosphate ions. Meanwhile, during the conventional process of protein NMR analysis, we eventually discovered that hSTOM(SPFH) formed a unique solid material after lyophilization. This lyophilized hSTOM(SPFH) sample was moderately slowly dissolved in a physiological buffer. Interestingly, it was resistant to dissolution against the phosphate buffer. We then found that the lyophilized hSTOM(SPFH) formed a fibril-like assembly under electron microscopy. Finally, we succeeded in reproducing this fibril-like assembly of hSTOM(SPFH) using a centrifugal ultrafiltration device, thus demonstrating that the increased protein concentration may promote self-assembly of hSTOM(SPFH) into fibril forms. Our observations may help understand the molecular function of the SPFH domain and its involvement in protein oligomerization as a component of the membrane skeleton. (245 words).

Development of Metal Complexes for Treatment of Coronaviruses.

Coronavirus disease (SARS-CoV-2) is a global epidemic. This pandemic, which has been linked to high rates of death, has forced some countries throughout the world to implement complete lockdowns in order to contain the spread of infection. Because of the advent of new coronavirus variants, it is critical to find effective treatments and vaccines to prevent the virus's rapid spread over the world. In this regard, metal complexes have attained immense interest as antibody modifiers and antiviral therapies, and they have a lot of promise towards SARS-CoV-2 and their suggested mechanisms of action are discussed, i.e., a new series of metal complexes' medicinal vital role in treatment of specific proteins or SARS-CoV-2 are described. The structures of the obtained metal complexes were fully elucidated by different analytical and spectroscopic techniques also. Molecular docking and pharmacophore studies presented that most of complexes studied influenced good binding affinity to the main protease SARS-CoV-2, which also was attained as from the RCSB pdb (Protein Data Bank) data PDB ID: 6 W41, to expect the action of metal complexes in contradiction of COVID-19. Experimental research is required to determine the pharmacokinetics of most of the complexes analyzed for the treatment of SARS-CoV-2-related disease. Finally, the toxicity of a metal-containing inorganic complex will thus be discussed by its capability to transfer metals which may bind with targeted site.

Free energy perturbation (FEP)-guided scaffold hopping.

Scaffold hopping refers to computer-aided screening for active compounds with different structures against the same receptor to enrich privileged scaffolds, which is a topic of high interest in organic and medicinal chemistry. However, most approaches cannot efficiently predict the potency level of candidates after scaffold hopping. Herein, we identified potent PDE5 inhibitors with a novel scaffold via a free energy perturbation (FEP)-guided scaffold-hopping strategy, and FEP shows great advantages to precisely predict the theoretical binding potencies ΔG FEP between ligands and their target, which were more consistent with the experimental binding potencies ΔG EXP (the mean absolute deviations | Δ G FEP - Δ G EXP |  < 2 kcal/mol) than those ΔG MM-PBSA or ΔG MM-GBSA predicted by the MM-PBSA or MM-GBSA method. Lead L12 had an IC50 of 8.7 nmol/L and exhibited a different binding pattern in its crystal structure with PDE5 from the famous starting drug tadalafil. Our work provides the first report via the FEP-guided scaffold hopping strategy for potent inhibitor discovery with a novel scaffold, implying that it will have a variety of future applications in rational molecular design and drug discovery.

Inhibition of Porphyromonas gingivalis peptidyl arginine deiminase, a virulence factor, by antioxidant-rich Cratoxylum cochinchinense: In vitro and in silico evaluation.

Porphyromonas gingivalis, the cause of periodontitis, is also linked to many systemic disorders due to its citrullination capability from a unique peptidyl arginine deiminase (PPAD). Protein citrullination is able to trigger an autoimmune response, increasing the severity of rheumatoid arthritis. The main objective of this study is to evaluate the inhibitory activity of Cratoxylym cochinchinense leaves extract towards the PPAD in vitro and in silico. Methanolic extract of Cratoxylum cochinchinense (CCM) was tested for total phenolic and flavonoid contents along with antioxidative assays. Inhibition of PPAD activities was conducted thereafter using recombinant PPAD in cell lysate. Phytocompounds postulated present in the CCM such as mangiferin, vismiaquinone A, δ-tocotrienol and α-tocotrienol and canophyllol were used as ligands in a simulated docking study against PPAD. Results obtained indicated high antioxidant potential in CCM while recording abundant phenolic (129.0 ± 2.5495 mg GA/g crude extract) and flavonoid (159.0 ± 2.1529 mg QE/g crude extract) contents. A dose-dependent inhibition of PPAD was observed when CCM was evaluated at various concentrations. CCM at 1 mg/mL exhibited citrulline concentration of 24.37 ± 3.25 mM which was 5 times lower than the negative control (114.23 ± 3.31 mM). Molecular docking simulation revealed that mangiferin and vismiaquinone A engaged in H-bonding and pi-pi interactions with important active site residues (Asp130, Arg152, Arg154 and Trp127) of PPAD and could be the potential phytochemicals that accounted for the inhibitory activities observed in the methanolic leaves extract. As such, CCM could be further explored for its therapeutic properties not only for periodontitis, but also for other systemic diseases like rheumatoid arthritis.

Plant-Based Natural Bioactive Compounds 2,4-Ditert-Butylphenolas: A Potential Candidates Against SARS-Cov-2019.

The novel coronavirus 2019 is spreading around the world and causing serious concern. However, there is limited information about novel coronavirus that hinders the design of effective drug. Bioactive compounds are rich source of chemo preventive ingredients. In our present research focuses on identifying and recognizing bioactive chemicals in Lantana camara, by evaluating their potential toward new coronaviruses and confirming the findings using molecular docking, ADMET, network analysis and dynamics investigations.. The spike protein receptor binding domain were docked with 25 identified compounds and 2,4-Ditertbutyl-phenol (-6.3kcal/mol) shows highest docking score, its interactions enhances the increase in binding and helps to identify the biological activity. The ADME/toxicity result shows that all the tested compounds can serve as inhibitors of the enzymes CYP1A2 and CYP2D6. In addition, Molecular dynamics simulations studies with reference inhibitors were carried out to test the stability. This study identifies the possible active molecules against the receptor binding domain of spike protein, which can be further exploited for the treatment of novel coronavirus 2019. The results of the toxicity risk for phytocompounds and their active derivatives showed a moderate to good drug score.

Structural bioinformatics enhances the interpretation of somatic mutations in KDM6A found in human cancers.

The histone demethylase KDM6A has recently elicited significant attention because its mutations are associated with a rare congenital disorder (Kabuki syndrome) and various types of human cancers. However, distinguishing KDM6A mutations that are deleterious to the enzyme and their underlying mechanisms of dysfunction remain to be fully understood. Here, we report the results from a multi-tiered approach evaluating the impact of 197 KDM6A somatic mutations using information derived from combining conventional genomics data with computational biophysics. This comprehensive approach incorporates multiple scores derived from alterations in protein sequence, structure, and molecular dynamics. Using this method, we classify the KDM6A mutations into 136 damaging variants (69.0%), 32 tolerated variants (16.2%), and 29 variants of uncertain significance (VUS, 14.7%), which is a significant improvement from the previous classification based on the conventional tools (over 40% VUS). We further classify the damaging variants into 15 structural variants (SV), 88 dynamic variants (DV), and 33 structural and dynamic variants (SDV). Comparison with variant scoring methods used in current clinical diagnosis guidelines demonstrates that our approach provides a more comprehensive evaluation of damaging potential and reveals mechanisms of dysfunction. Thus, these results should be taken into consideration for clinical assessment of the damaging potential of each mutation, as they provide hypotheses for experimental validation and critical information for the development of mutant-specific drugs to fight diseases caused by KDM6A dysfunctions.