Green Metallic Nanoparticles: Biosynthesis to Applications

Current advancements in nanotechnology and nanoscience have resulted in new nanomaterials, which may pose health and environmental risks. Furthermore, several researchers are working to optimize ecologically friendly procedures for creating metal and metal oxide nanoparticles. The primary goal is to decrease the adverse effects of synthetic processes, their accompanying chemicals, and the resulting complexes. Utilizing various biomaterials for nanoparticle preparation is a beneficial approach in green nanotechnology. Furthermore, using the biological qualities of nature through a variety of activities is an excellent way to achieve this goal. Algae, plants, bacteria, and fungus have been employed to make energy-efficient, low-cost, and nontoxic metallic nanoparticles in the last few decades. Despite the environmental advantages of using green chemistry-based biological synthesis over traditional methods as discussed in this article, there are some unresolved issues such as particle size and shape consistency, reproducibility of the synthesis process, and understanding of the mechanisms involved in producing metallic nanoparticles via biological entities. Consequently, there is a need for further research to analyze and comprehend the real biological synthesis-dependent processes. This is currently an untapped hot research topic that required more investment to properly leverage the green manufacturing of metallic nanoparticles through living entities. The review covers such green methods of synthesizing nanoparticles and their utilization in the scientific world.

Bioinformatics analysis of the differences in the binding profile of the wild-type and mutants of the SARS-CoV-2 spike protein variants with the ACE2 receptor

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Reports of new variants that potentially increase virulence and viral transmission, as well as reduce the efficacy of available vaccines, have recently emerged. In this study, we computationally analyzed the N439K, S477 N, and T478K variants for their ability to bind Angiotensin-converting enzyme 2 (ACE2). We used the protein-protein docking approach to explore whether the three variants displayed a higher binding affinity to the ACE2 receptor than the wild type. We found that these variants alter the hydrogen bonding network and the cluster of interactions. Additional salt bridges, hydrogen bonds, and a high number of non-bonded contacts (i.e., non-bonded interactions between atoms in the same molecule and those in other molecules) were observed only in the mutant complexes, allowing efficient binding to the ACE2 receptor. Furthermore, we used a 2.0-μs all-atoms simulation approach to detect differences in the structural dynamic features of the resulting protein complexes. Our findings revealed that the mutant complexes possessed stable dynamics, consistent with the global trend of mutations yielding variants with improved stability and enhanced affinity. Binding energy calculations based on molecular mechanics/generalized Born surface area (MM/GBSA) further revealed that electrostatic interactions principally increased net binding energies. The stability and binding energies of N439K, S477 N, and T478K variants were enhanced compared to the wild-type-ACE2 complex. The net binding energy of the systems was -31.86 kcal/mol for the wild-type-ACE2 complex, -67.85 kcal/mol for N439K, -69.82 kcal/mol for S477 N, and -69.64 kcal/mol for T478K. The current study provides a basis for exploring the enhanced binding abilities and structural features of SARS-CoV-2 variants to design novel therapeutics against the virus.

Virtual screening and molecular dynamics simulation analysis of Forsythoside A as a plant-derived inhibitor of SARS-CoV-2 3CLpro

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a more severe strain of coronavirus (CoV) that was first emerged in China in 2019. Available antiviral drugs could be repurposed and natural compounds with antiviral activity could be safer and cheaper source of medicine for SARS-CoV-2. 78 natural antiviral compounds database was identified from literature and virtual screening technique was applied to identify potential 3-chymotrypsin-like protease (3CLpro) inhibitors. Molecular docking studies were conducted to analyze the main protease (3CLpro) and inhibitors interactions with key residues of active site of target protein (PDB ID: 6LU7), active site constitute the part of active domain I and II of 3CLpro. 10 compounds with highest dock score were subjected to calculate ADMET parameters to figure out drug-likeness. Molecular dynamic (MD) simulation of the selected lead was performed by Amber simulation package to understand the conformational changes in docked complex. MD simulations analysis (RMSD, RMSF, Rg, BF, HBs, and SASA plots) of lead bounded with 3CLpro, hence revealed the important structural turns and twists during MD simulations from 0 to 100 ns. MM-PBSA/GBSA methods has also been applied for the estimation binding free energy (BFE) of the selected lead-complex. The present study has identified lead compound “Forsythoside A” an active extract of Forsythia suspense as SARS-CoV-2 3CLpro inhibitor that can block the viral replication and translation. Structural analysis of target protein and lead compound performed in this study could contribute to the development of potential drug against SARS-CoV-2 infection.

Sumoylation as an Emerging Target in Therapeutics against Cancer

Sumoylation is the Post-translational modification gaining most of the research interest recently. Sumoylation is involved in various crucial functions of the cell such as regulation of cell cycle, DNA damage repair, apoptosis, etc. Oncology is advancing in radiotherapy, targeted chemotherapy, various forms of immunotherapy and targeted gene therapy. Researches are being conducted to prove its connotation with a variety of cancers and inhibitors are being developed to obstruct the fatal effect caused by misbalance of the SUMO-catalytic cycle. It has been shown that up-regulation of certain enzymes of Sumoylation correlates with cancer incidence in most of the cases. However, in some cases, down-regulation also associates with cancer invasion such as underexpression of UBC9 in initial stage breast cancer. This can aid in future study, treatment, and diagnosis of a variety of cancers including breast cancer, prostate cancer, lung adenocarcinoma, melanoma, multiple myeloma, etc. Various mechanistic assays are being developed and used to identify potential inhibitors against the dysregulated proteins of Sumoylation. This review summarizes the normal roles of the enzymes involved in the SUMOcatalytic cycle, their misbalanced regulation leading to tumorigenesis and nearly all the potent inhibitors identified to date, while after detailed studied it was observed that ML-792 could be a promising inhibitor in treating cancers by inhibiting Sumoylation enzymes.

Molecular Docking Studies Reveal Rhein from rhubarb (Rheum rhabarbarum) as a Putative Inhibitor of ATP-binding Cassette Super-family G member 2

BACKGROUND

ATP-binding cassette Super-family G member 2 protein is an active ATPbinding cassette transporter with the potential to combat cancer stem cells.

OBJECTIVE

Due to the lack of potential ATP-binding cassette Super-family G member 2 inhibitors, we screened natural inhibitors, which could be a safe source to control multidrug resistance by blocking the regulation of ATP-binding cassette Super-family G member 2 protein.

METHODS

Three-dimensional structure of ATP-binding cassette Super-family G member 2 protein downloaded from the protein databank and chemical structures of 166 selected compounds of the training dataset were retrieved from PubChem. Drug-likeness and docking analysis was conducted to shortlist the dataset for pharmacophore generation. LigandScout 4.1.5 used for pharmacophorebased screening of Zbc library of ZINC database and Autodock Vina were utilized for molecular docking against the predicted active pocket of the target protein to evaluate the potential association of protein and ligands. The physiochemical properties of novel compounds were calculated by admetSAR respectively.

RESULTS

Through pharmacophore-based screening, ZINC4098704 (Rhein) was identified as a lead compound which demonstrates the least binding energy (-8.5) and the highest binding affinity with the target protein and showed optimal physiochemical profile. This compound is highly recommended for a laboratory test to confirm its activity as an ATP-binding cassette Super-family G member 2 inhibitors.

CONCLUSION

Our computer-based study systematically selected natural lead compounds, which could be effective in inhibiting ATP-binding cassette Super-family G member 2 and may help reverse the effect of multidrug resistance to increase the effectiveness of chemotherapy in cancer treatment.

Pharmacotherapeutic Potential of Natural Products to Target the SARS-CoV-2 PLpro Using Molecular Screening and Simulation Approaches

Because of the essential role of PLpro in the regulation of replication and dysregulation of the host immune sensing, it is considered a therapeutic target for novel drug development. To reduce the risk of immune evasion and vaccine effectiveness, small molecular therapeutics are the best complementary approach. Hence, we used a structure-based drug-designing approach to identify potential small molecular inhibitors for PLpro of SARS-CoV-2. Initial scoring and re-scoring of the best hits revealed that three compounds NPC320891 (2,2-Dihydroxyindene-1,3-Dione), NPC474594 (Isonarciclasine), and NPC474595 (7-Deoxyisonarciclasine) exhibit higher docking scores than the control GRL0617. Investigation of the binding modes revealed that alongside the essential contacts, i.e., Asp164, Glu167, Tyr264, and Gln269, these molecules also target Lys157 and Tyr268 residues in the active site. Moreover, molecular simulation demonstrated that the reported top hits also possess stable dynamics and structural packing. Furthermore, the residues' flexibility revealed that all the complexes demonstrated higher flexibility in the regions 120-140, 160-180, and 205-215. The 120-140 and 160-180 lie in the finger region of PLpro, which may open/close during the simulation to cover the active site and push the ligand inside. In addition, the total binding free energy was reported to be - 32.65 ± 0.17 kcal/mol for the GRL0617-PLpro, for the NPC320891-PLpro complex, the TBE was - 35.58 ± 0.14 kcal/mol, for the NPC474594-PLpro, the TBE was - 43.72 ± 0.22 kcal/mol, while for NPC474595-PLpro complex, the TBE was calculated to be - 41.61 ± 0.20 kcal/mol, respectively. Clustering of the protein's motion and FEL further revealed that in NPC474594 and NPC474595 complexes, the drug was seen to have moved inside the binding cavity along with the loop in the palm region harboring the catalytic triad, thus justifying the higher binding of these two molecules particularly. In conclusion, the overall results reflect favorable binding of the identified hits strongly than the control drug, thus demanding in vitro and in vivo validation for clinical purposes.

Structural-Dynamics and Binding Analysis of RBD from SARS-CoV-2 Variants of Concern (VOCs) and GRP78 Receptor Revealed Basis for Higher Infectivity

Glucose-regulated protein 78 (GRP78) might be a receptor for SARS-CoV-2 to bind and enter the host cell. Recently reported mutations in the spike glycoprotein unique to the receptor-binding domain (RBD) of different variants might increase the binding and pathogenesis. However, it is still not known how these mutations affect the binding of RBD to GRP78. The current study provides a structural basis for the binding of GRP78 to the different variants, i.e., B.1.1.7, B.1.351, B.1.617, and P.1 (spike RBD), of SARS-CoV-2 using a biomolecular simulation approach. Docking results showed that the new variants bound stronger than the wild-type, which was further confirmed through the free energy calculation results. All-atom simulation confirmed structural stability, which was consistent with previous results by following the global stability trend. We concluded that the increased binding affinity of the B.1.1.7, B.1.351, and P.1 variants was due to a variation in the bonding network that helped the virus induce a higher infectivity and disease severity. Consequently, we reported that the aforementioned new variants use GRP78 as an alternate receptor to enhance their seriousness.

Investigation of the binding and dynamic features of A.30 variant revealed higher binding of RBD for hACE2 and escapes the neutralizing antibody: A molecular simulation approach

With the emergence of Delta and Omicron variants, many other important variants of SARS-CoV-2, which cause Coronavirus disease-2019, including A.30, are reported to increase the concern created by the global pandemic. The A.30 variant, reported in Tanzania and other countries, harbors spike gene mutations that help this strain to bind more robustly and to escape neutralizing antibodies. The present study uses molecular modelling and simulation-based approaches to investigate the key features of this strain that result in greater infectivity. The protein-protein docking results for the spike protein demonstrated that additional interactions, particularly two salt-bridges formed by the mutated residue Lys484, increase binding affinity, while the loss of key residues at the N terminal domain (NTD) result in a change to binding conformation with monoclonal antibodies, thus escaping their neutralizing effects. Moreover, we deeply studied the atomic features of these binding complexes through molecular simulation, which revealed differential dynamics when compared to wild type. Analysis of the binding free energy using MM/GBSA revealed that the total binding free energy (TBE) for the wild type receptor-binding domain (RBD) complex was -58.25 kcal/mol in contrast to the A.30 RBD complex, which reported -65.59 kcal/mol. The higher TBE for the A.30 RBD complex signifies a more robust interaction between A.30 variant RBD with ACE2 than the wild type, allowing the variant to bind and spread more promptly. The BFE for the wild type NTD complex was calculated to be -65.76 kcal/mol, while the A.30 NTD complex was estimated to be -49.35 kcal/mol. This shows the impact of the reported substitutions and deletions in the NTD of A.30 variant, which consequently reduce the binding of mAb, allowing it to evade the immune response of the host. The reported results will aid the development of cross-protective drugs against SARS-CoV-2 and its variants.

Subtractive Proteomics and Immuno-informatics Approaches for Multi-peptide Vaccine Prediction Against Klebsiella oxytoca and Validation Through In Silico Expression

Klebsiella oxytoca is a gram-negative bacterium. It is opportunistic in nature and causes hospital acquired infections. Subtractive proteomics and reverse vaccinology approaches were employed to screen out the best proteins for vaccine designing. Whole proteome of K. oxytoca strain ATCC 8724, consisting of 5483 proteins, was used for designing the vaccine. Total 1670 cytotoxic T lymphocyte (CTL) epitope were predicted through NetCTL while 1270 helper T lymphocyte (HTL) epitopes were predicted through IEDB server. The epitopes were screened for non-toxicity, allergenicity, antigenicity and water solubility. After epitope screening 300 CTL and 250 HTL epitopes were submitted to IFN-γ epitope server to predict their Interferon-γ induction response. The selected IFN-γ positive epitopes were tested for their binding affinity with MHCI-DRB1 by MHCPred. The 15 CTL and 13 HTL epitopes were joined by linkers AAY and GPGPG respectively in vaccine construct. Chain C of Pam3CSK4 (PDB ID; 2Z7X) was linked to the vaccine construct as an adjuvant. A 450aa long vaccine construct was submitted to I-TASSER server for 3D structure prediction. Thirteen Linear B cells were predicted by ABCPred server and 10 sets of discontinues epitopes for 3D vaccine structure were predicted by DiscoTope server. The modeled 3D vaccine construct was docked with human Toll-like receptor 2 (PDB ID: 6NIG) by PatchDock. The docked complexes were refined by FireDock. The selected docked complex showed five hydrogen bonds and one salt bridge. The vaccine sequence was reverse transcribed to get nucleotide sequence for In silico cloning. The reverse transcribed sequence strand was cloned in pET28a(+) expression vector. A clone containing 6586 bp was constructed including the 450 bp of query gene sequence.

Physical and chemical mutagens improved Sporotrichum thermophile, strain ST20 for enhanced Phytase activity

OBJECTIVE

Phosphorous is an essential micronutrient of plants and involved in critical biological functions. In nature, phosphorous is mostly present in immobilized inorganic mineral and in the fixed organic form including phytic acid and phosphoesteric compounds. However, the bioavailability of bound phosphorous could be enhanced by the use of phosphate solubilizing microorganisms such as bacteria and fungi. The phytases are widespread in an environment and have been isolated from different sources comprising bacteria and fungi.

METHODOLOGY

In current studies, we show the successful use of gamma rays and EMS (Ethyl Methane Sulphonate) mutagenesis for enhanced activity of phytases in a fungal strain Sporotrichum thermophile.

RESULTS

We report an improved strain ST2 that could produce a clear halo zone around the colony, up to 24 mm. The maximum enzymatic activity was found of 382 U/mL on pH 5.5. However, the phytase activity was improved to 387 U/ml at 45 °C. We also report that the mutants produced through EMS showed the greater potential for phytase production.

CONCLUSION

The current study highlights the potential of EMS mutagenesis for strain improvement over physical mutagens.

In silico annotation of unreviewed acetylcholinesterase (AChE) in some lepidopteran insect pest species reveals the causes of insecticide resistance

Lepidoptera is the second most diverse insect order outnumbered only by the Coeleptera. Acetylcholinesterase (AChE) is the major target site for insecticides. Extensive use of insecticides, to inhibit the function of this enzyme, have resulted in the development of insecticide resistance. Complete knowledge of the target proteins is very important to know the cause of resistance. Computational annotation of insect acetylcholinesterase can be helpful for the characterization of this important protein. Acetylcholinesterase of fourteen lepidopteran insect pest species was annotated by using different bioinformatics tools. AChE in all the species was hydrophilic and thermostable. All the species showed lower values for instability index except L. orbonalis, S. exigua and T. absoluta. Highest percentage of Arg, Asp, Asn, Gln and Cys were recorded in P. rapae. High percentage of Cys and Gln might be reason for insecticide resistance development in P. rapae. Phylogenetic analysis revealed the AChE in T. absoluta, L. orbonalis and S. exigua are closely related and emerged from same primary branch. Three functional motifs were predicted in eleven species while only two were found in L. orbonalis, S. exigua and T. absoluta. AChE in eleven species followed secretory pathway and have signal peptides. No signal peptides were predicted for S. exigua, L. orbonalis and T. absoluta and follow non secretory pathway. Arginine methylation and cysteine palmotylation was found in all species except S. exigua, L. orbonalis and T. absoluta. Glycosylphosphatidylinositol (GPI) anchor was predicted in only nine species.

Interaction of human dynein light chain 1 (DYNLL1) with enterochelin esterase (Salmonella typhimurium) and protective antigen (Bacillus anthraci) might be the potential cause of human infection

The cytoplasmic dynein light chain 1 (DYNLL1) is an important constituent of motor proteins complex. In human it is encoded by DYNLL1 gene. It is involved in cargo transport functions and interacts with many viral proteins with the help of short linear consensus motif sequence (K/R) XTQT. Viral proteins bind to DYNLL1 through its consensus short linear motif (SLiM) sequence to reach the target site in the cell and cause different infections in the host. It is still unknown if bacterial proteins also contain the same conserved SLiMs sequence through which they bind to this motor protein and cause infections. So, it is important to investigate the role of DYNLL1 in human bacterial infections. The interaction partner proteins of DYNLL1 against conserved viral motif sequences were predicted through PDBSum. Pairwise sequence alignment, between viral motif sequence and that of predicted proteins, was performed to identify conserved region in predicted interaction partners. Docking between the DYNLL1 and new pathogenic interaction partners was performed, by using PatchDock, to explore the protein-protein binding quality. Interactions of docked complexes were visualized by DimPlot. Three pathogenic bacterial proteins i.e., enterochelin esterase (3MGA), protective antigen (3J9C) and putative lipoprotein (4KT3) were selected as candidate interaction partners of DYNLL1. The putative lipoprotein (4KT3) showed low quality binding with DYNLL1. So, enterochelin esterase (3MGA) and protective antigen (3J9C) were speculated to be involved in human bacterial infections by using DYNLL1 to reach their target sites.

In silico structural and functional characterization and phylogenetic study of alkaline phosphatase in bacterium, Rhizobium leguminosarum (Frank 1879)

Phosphorus is one of the primary macronutrient of plants, which is present in soil. It is essential for normal growth and development of plants. Plants use inorganic form of phosphate but organic form can also be assimilated with the help of soil inhabiting bacteria. Alkaline phosphatase is an enzyme present in Rizobium bacteria. This enzyme is responsible for solubilization and mineralization of organic phosphate and makes it readily available for plants. In the present study, nine different strains of Rhizobium leguminosarum were selected for a detailed computational structural and functional characterization and phylogenetic studies of alkaline phosphatase. Amino acid sequences were retrieved from UniProt and saved in FASTA format for use in analysis. Phylogenetic analysis of these strains was done by using MEGA7. 3D structure prediction was performed by using online server I-Tasser. Galaxy Web and 3D Refine were used for structure refinement. The refined structures were evaluated using two validation servers, QMEAN and SAVES. Protein-protein interaction analysis was done by using STRING. For detailed functional characterization, Cofactor, Coach, RaptorX, PSORT and MEME were used. Overall quality of predicted protein models was above 80%. Refined and validated models were submitted into PMDB. Seven out of nine strains were closely related and other two were distantly related. Protein-Protein interaction showed no significant co-expression among the interaction partners.

Polypharmacology Approach Against Migraine with Aura and Brain Edema for the Development of an Efficient Inhibitor and its Analogues

BACKGROUND

Polypharmacology is a design or use of pharmaceutical agents in which single drug is used to treat multiple diseases. Aquaporin proteins are identified to treat migraine with aura and brain edema. This study focuses on Aquaporin-1 and Aquaporin-4. AQP-1 is expressed in small afferent sensory nerve fibers. Over-expression of peripheral nervous system causes migraine.

METHODS

AQP-4 is an abundant channel water protein in brain that regulates water transport to prevent homeostasis. Over-expression of AQP-4 contributes to water imbalance in ischemic pathology resulting in cerebral edema. Purpose of this study is to identify a potent inhibitor for the treatment of migraine with aura and brain edema.

RESULTS

As in the recent studies, no conventional methodologies have been focused through the approach of polypharmacology. Structures of AQP-1 and AQP- 4 proteins were retrieved from PDB (Protein Data Bank). PyRx software was used to perform molecular docking.

CONCLUSION

Analogues of ligands were analyzed which contained significant similarities of associated proteins to get efficient inhibitor. Toxicity of lead compound was measured through admetSAR. A lead compound was predicted to treat these diseases.

Bioinformatics-Based Approaches to Study Virus-Host Interactions During SARS-CoV-2 Infection

As the knowledge of biomolecules is increasing from the last decades, it is helping the researchers to understand the unsolved issues regarding virology. Recent technologies in high-throughput sequencing are providing the swift generation of SARS-CoV-2 genomic data with the basic inside of viral infection. Owing to various virus-host protein interactions, high-throughput technologies are unable to provide complete details of viral pathogenesis. Identifying the virus-host protein interactions using bioinformatics approaches can assist in understanding the mechanism of SARS-CoV-2 infection and pathogenesis. In this chapter, recent integrative bioinformatics approaches are discussed to help the virologists and computational biologists in the identification of structurally similar proteins of human and SARS-CoV-2 virus, and to predict the potential of virus-host interactions. Considering experimental and time limitations for effective viral drug development, computational aided drug design (CADD) can reduce the gap between drug prediction and development. More research with respect to evolutionary solutions could be helpful to make a new pipeline for virus-host protein-protein interactions and provide more understanding to disclose the cases of host switch, and also expand the virulence of the pathogen and host range in developing viral infections.

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein-protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein-ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target's active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

Identification of Novel and Safe Fungicidal Molecules against Fusarium oxysporum from Plant Essential Oils: In Vitro and Computational Approaches

Phytopathogenic fungi are serious threats in the agriculture sector especially in fruit and vegetable production. The use of plant essential oil as antifungal agents has been in practice from many years. Plant essential oils (PEOs) of Cuminum cyminum, Trachyspermum ammi, Azadirachta indica, Syzygium aromaticum, Moringa oleifera, Mentha spicata, Eucalyptus grandis, Allium sativum, and Citrus sinensis were tested against Fusarium oxysporum. Three phase trials consist of lab testing (MIC and MFC), field testing (seed treatment and foliar spray), and computer-aided fungicide design (CAFD). Two concentrations (25 and 50 μl/ml) have been used to asses MIC while MFC was assessed at four concentrations (25, 50, 75, and 100 μl/ml). C. sinensis showed the largest inhibition zone (47.5 and 46.3 m2) for both concentrations. The lowest disease incidence and disease severity were recorded in treatments with C. sinensis PEO. Citrus sinensis that qualified in laboratory and field trials was selected for CAFD. The chemical compounds of C. sinensis PEO were docked with polyketide synthase beta-ketoacyl synthase domain of F. oxysporum by AutoDock Vina. The best docked complex was formed by nootkatone with -6.0 kcal/mol binding affinity. Pharmacophore of the top seven C. sinensis PEO compounds was used for merged pharmacophore generation. The best pharmacophore model with 0.8492 score was screened against the CMNP database. Top hit compounds from screening were selected and docked with polyketide synthase beta-ketoacyl synthase domain. Four compounds with the highest binding affinity and hydrogen bonding were selected for confirmation of lead molecule by doing MD simulation. The polyketide synthase-CMNPD24498 showed the highest stability throughout 80 ns run of MD simulation. CMNPD24498 (FW054-1) from Verrucosispora was selected as the lead compound against F. oxysporum.

Do Phagostimulants, Alone or Combined with Ammonium Acetate, Di-Ammonium Phosphate, and Acetic Acid, Effectively Attract Both Sexes of Peach Fruit Flies, Bactrocera zonata (Diptera: Tephritidae)?: Insights from Laboratory and Field Bioassays

Laboratory and field assays of three sets of experiments were conducted to evaluate the impact of different phagostimulants alone and in combination with other phagostimulant lure sources, such as ammonium acetate, DAP, and acetic acid, on the attractancy of both sexes of B. zonata. In the first experiment, the laboratory olfactometer study revealed that out of eleven phagostimulants, banana, mulberry, mango, guava, molasses, and protein hydrolysate exhibited moderate attractancy (15.2-60.2%) to B. zonata. Unexpectedly, banana and protein hydrolysate were demonstrated to be highly attractive phagostimulants for starved female B. zonata (53.6% and 60.2%, respectively). In the field study, none of the tested phagostimulants exhibited high attractancy; however, banana, mulberry, protein hydrolysate, guava, mango, and molasses demonstrated moderate attractancy (5.6-35.6%) to B. zonata. In the second experiment, out of five phagostimulant-mixtures, phagostimulant-mixture-4 proved highly attractive (40.5-68.6% and 45.5-51.2%), followed by phagostimulant-mixture-3, which proved to be moderately attractive (17.0-22.5% and 28.4-36.1%) to B. zonata in olfactometer and field studies, respectively. In the third experiment, out of five phagostimulant-AdMixtures, phagostimulant-AdMixture-4 demonstrated strong attractiveness in the olfactometer (41.6-68.7%) and field studies (52.7-58.7%) for B. zonata, while the rest of the AdMixtures demonstrated moderate to no attractiveness for B. zonata. So, phagostimulant-AdMixture-4 with GF-120 could be used in the development of a phagostimulant bait station which attracts the maximum B. zonata population and ultimately provides pest-free fruits to the farmers.

Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach

Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets.