Point-specific interactions of isovitexin with the neighboring amino acid residues of the hACE2 receptor as a targeted therapeutic agent in suppressing the SARS-CoV-2 influx mechanism

Structural and energetic analysis of NS5 protein inhibition by small molecules in Japanese encephalitis virus using machine learning and steered molecular dynamics approach

One of the viral diseases that affect millions of people around the world, particularly in developing countries, is Japanese encephalitis (JE). In this study, the conserved protein of this virus, that is, non-structural protein 5 (NS5), was used as a target protein for this study, and a compound library of 749 antiviral molecules was screened against NS5. The current study employed machine learning-based virtual screening combined with molecular docking. Here, three hits (24360, 123519051 and 213039) had lower binding energies (< -8 kcal/mol) than the control, S-Adenosyl-L-homocysteine (SAH). All the compounds showed significant H-bond interactions with functional residues, which were also observed by the control. Molecular dynamics simulation, MM/GBSA for binding free energy analysis, principal component analysis and free energy landscape were also performed to study the stability of the complex formation. All three compounds had similar root mean square deviation trends, which were comparable to the control, SAH. Post-MD, the 123519051-receptor complex had the highest number of H-bonds (4 to 5) after the control, out of which three exhibited the highest percentage occupancy (50%, 24% and 79%). Both docking and MD, 123519051 showed an H-bond with the residue Gly111, which was also found for the control-protein complex. 123519051 showed the lowest binding free energy with ΔGbind of -89 kJ/mol. Steered molecular dynamics depicted that 123519051 had the maximum magnitude of dissociation (1436.43 kJ/mol/nm), which was more than the control, validating its stable complex formation. This study concluded that 123519051 is a binder and could inhibit the protein NS5 of JE.Communicated by Ramaswamy H. Sarma.

Identification of selective plant-derived natural carotenoid and flavonoids as the potential inhibitors of DHHC-mediated protein S-palmitoylation: an in silico study

Protein S-palmitoylation mediated by DHHCs is recognized as a distinct and reversible form of lipid modification connected with several health perturbations, including neurodegenerative disorders, cancer, and autoimmune conditions. However, the pharmacological characteristics of current pan-DHHC inhibitors, particularly their toxicity and off-target effects, have hindered their in-depth cellular investigations. The therapeutic properties of the natural compounds, with minimal side effects, allowed us to evaluate them as DHHC-targeting inhibitors. Here, we performed an insilico screening of 115 phytochemicals to assess their interactions with the DHHC20 binding site. Among these compounds, lutein, 5-hydroxyflavone, and 6-hydroxyflavone exhibited higher binding energy (-9.2, -8.5, and -8.5 kcal/mol) in the DHHC20 groove compared to pan-DHHC inhibitor 2-BP (-7.0 kcal/mol). Furthermore, we conducted a 100 ns MD simulation to evaluate the stability of these complexes under physiological conditions. The MDsimulation results indicated that DHHC20 formed a more stable conformation with lutein compared to 5-hydroxyflavone and 6-hyroxyflavone via hydrophobic and H-bond interactions. Conclusively, these results could serve as a promising starting point for exploring the use of these natural molecules as DHHC20 inhibitors.Communicated by Ramaswamy H. Sarma.

Chemical library design, QSAR modeling and molecular dynamics simulations of naturally occurring coumarins as dual inhibitors of MAO-B and AChE

Coumarins are a highly privileged scaffold in medicinal chemistry. It is present in many natural products and is reported to display various pharmacological properties. A large plethora of compounds based on the coumarin ring system have been synthesized and were found to possess biological activities such as anticonvulsant, antiviral, anti-inflammatory, antibacterial, antioxidant as well as neuroprotective properties. Despite the wide activity spectrum of coumarins, its naturally occurring derivatives are yet to be investigated in detail. In the current study, a chemical library was created to assemble all chemical information related to naturally occurring coumarins from the literature. Additionally, a multi-stage virtual screening combining QSAR modeling, molecular docking, and ADMET prediction was conducted against monoamine oxidase B and acetylcholinesterase, two relevant targets known for their neuroprotective properties and 'disease-modifying' potential in Parkinson's and Alzheimer's disease. Our findings revealed ten coumarin derivatives that may act as dual-target drugs against MAO-B and AChE. Two coumarin candidates were selected from the molecular docking study: CDB0738 and CDB0046 displayed favorable interactions for both proteins as well as suitable ADMET profiles. The stability of the selected coumarins was assessed through 100 ns molecular dynamics simulations which revealed promising stability through key molecular interactions for CDB0738 to act as dual inhibitor of MAO-B and AChE. However, experimental studies are necessary to evaluate the bioactivity of the proposed candidate. The current results may generate an increasing interest in bioprospecting naturally occurring coumarins as potential candidates against relevant macromolecular targets by encouraging virtual screening studies against our chemical library.Communicated by Ramaswamy H. Sarma.

Oncoinformatic screening of the gene clusters involved in the HER2-positive breast cancer formation along with the in silico pharmacodynamic profiling of selective long-chain omega-3 fatty acids as the metastatic antagonists

The HER2-positive patients occupy ~ 30% of the total breast cancer patients globally where no prevalent drugs are available to mitigate the frequent metastasis clinically except lapatinib and neratinib. This scarcity reinforced researchers' quest for new medications where natural substances are significantly considered. Valuing the aforementioned issues, this research aimed to study the ERBB2-mediated string networks that work behind the HER2-positive breast cancer formation regarding co-expression, gene regulation, GAMA-receptor-signaling pathway, cellular polarization, and signal inhibition. Following the overexpression, promotor methylation, and survivability profiles of ERBB2, the super docking position of HER2 was identified using the quantum tunneling algorithm. Supramolecular docking was conducted to study the target specificity of EPA and DHA fatty acids followed by a comprehensive molecular dynamic simulation (100 ns) to reveal the RMSD, RMSF, Rg, SASA, H-bonds, and MM/GBSA values. Finally, potential drug targets for EPA and DHA in breast cancer were constructed to determine the drug-protein interactions (DPI) at metabolic stages. Considering the values resulting from the combinational models of the oncoinformatic, pharmacodynamic, and metabolic parameters, long-chain omega-3 fatty acids like EPA and DHA can be considered as potential-targeted therapeutics for HER2-positive breast cancer treatment.

WGS-based screening of the co-chaperone protein DjlA-induced curved DNA binding protein A (CbpA) from a new multidrug-resistant zoonotic mastitis-causing Klebsiella pneumoniae strain: a novel molecular target of selective flavonoids

The research aimed to establish a multidrug-resistant Klebsiella pneumoniae-induced genetic model for mastitis considering the alternative mechanisms of the DjlA-mediated CbpA protein regulation. The Whole Genome Sequencing of the newly isolated K. pneumoniae strain was conducted to annotate the frequently occurring antibiotic resistance and virulence factors following PCR and MALDI-TOF mass-spectrophotometry. Co-chaperon DjlA was identified and extracted via restriction digestion on PAGE. Based on the molecular string property analysis of different DnaJ and DnaK type genes, CbpA was identified to be regulated most by the DjlA protein during mastitis. Based on the quantum tunnel-cluster profiles, CbpA was modeled as a novel target for diversified biosynthetic, and chemosynthetic compounds. Pharmacokinetic and pharmacodynamic analyses were conducted to determine the maximal point-specificity of selective flavonoids in complexing with the CbpA macromolecule at molecular docking. The molecular dynamic simulation (100 ns) of each of the flavonoid-protein complexes was studied regarding the parameters RMSD, RMSF, Rg, SASA, MMGBSA, and intramolecular hydrogen bonds; where all of them resulted significantly. To ratify all the molecular dynamic simulation outputs, the potential stability of the flavonoids in complexing with CbpA can be remarked as Quercetin > Biochanin A > Kaempherol > Myricetin, which were all significant in comparison to the control Galangin. Finally, a comprehensive drug-gene interaction pathway for each of the flavonoids was developed to determine the simultaneous and quantitative-synergistic effects of different operons belonging to the DnaJ-type proteins on the metabolism of the tested pharmacophores in CbpA. Considering all the in vitro and in silico parameters, DjlA-mediated CbpA can be a novel target for the tested flavonoids as the potential therapeutics of mastitis as futuristic drugs.

Khan R, Kumalo HM. Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors

The COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, and transmembrane protease serine 2 (TMPRSS2). In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat Mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of the drug candidates to target receptors, providing insight into their potential efficacy. This study is aimed at assessing the useful contributions of the application of computational instruments in the discovery of receptors targeted in SARS-CoV-2. It further highlights some identified advantages and limitations of these studies, thereby revealing some complementary experimental validation to ensure the efficacy and safety of identified drug candidates.

Phyllanthus emblica (Amla) methanolic extract regulates multiple checkpoints in 15-lipoxygenase mediated inflammopathies: Computational simulation and in vitro evidence

Amla (Phyllanthus emblica) has long been used in traditional folk medicine to prevent and cure a variety of inflammatory diseases. In this study, the antioxidant activity (DPPH scavenging and reducing power), anti-inflammatory activity (RBC Membrane Stabilization and 15-LOX inhibition), and anticoagulation activity (Serin protease inhibition and Prothrombin Time assays) of the methanolic extract of amla were conducted. Amla exhibited a substantial amount of phenolic content (TPC: 663.53 mg GAE/g) and flavonoid content (TFC: 418.89 mg GAE/g). A strong DPPH scavenging effect was observed with an IC50 of 311.31 µg/ml as compared to standard ascorbic acid with an IC50 of 130.53 µg/ml. In reducing power assay, the EC50 value of the extract was found to be 196.20 µg/ml compared to standard ascorbic acid (EC50 = 33.83 µg/ml). The IC50 value of the RBC membrane stabilization and 15-LOX assays was observed as 101.08 µg/ml (IC50 of 58.62 µg/ml for standard aspirin) and 195.98 µg/ml (IC50 of 19.62 µg/ml for standard quercetin), respectively. The extract also strongly inhibited serine protease (trypsin) activity with an IC50 of 505.81 µg/ml (IC50 of 295.44 µg/ml for standard quercetin). The blood coagulation time (PTT) was found to be 11.91 min for amla extract and 24.11 min for standard Warfarin. Thus, the findings of an in vitro study revealed that the methanolic extract of amla contains significant antioxidant, anti-inflammatory, and anticoagulation activity. Furthermore, in silico docking and simulation of reported phytochemicals of amla with human 15-LOXA and 15-LOXB were carried out to validate the anti-inflammatory activity of amla. In this analysis, epicatechin and catechin showed greater molecular interaction and were considerably stable throughout the 100 ns simulation with 15-lipoxygenase A (15-LOXA) and 15-lipoxygenase B (15-LOXB) respectively.

Target-specificity of different amyrin subunits in impeding HCV influx mechanism inside the human cells considering the quantum tunnel profiles and molecular strings of the CD81 receptor: a combined in silico and in vivo study

HCV is a hepatotropic RNA virus recognized for its frequent virulence and fatality worldwide. Despite many vaccine development programs underway, researchers are on a quest for natural bioactive compounds due to their multivalent efficiencies against viral infections, considering which the current research aimed to figure out the target-specificity and therapeutic potentiality of α, β, and δ subunits of amyrin, as novel bioactive components against the HCV influx mechanism. Initially, the novelty of amyrin subunits was conducted from 203 pharmacophores, comparing their in-silico pharmacokinetic and pharmacodynamic profiles. Besides, the best active site of CD81 was determined following the quantum tunneling algorithm. The molecular dynamic simulation was conducted (100 ns) following the molecular docking steps to reveal the parameters- RMSD (Å); Cα; RMSF (Å); MolSA (Ų); Rg (nm); PSA (Å); SASA (Ų), and the MM-GBSA dG binding scores. Besides, molecular strings of CD81, along with the co-expressed genes, were classified, as responsible for encoding CD81-mediated protein clusters during HCV infection, resulting in the potentiality of amyrins as targeted prophylactics in HCV infection. Finally, in vivo profiling of the oxidative stress marker, liver-specific enzymes, and antioxidant markers was conducted in the DMN-induced mice model, where β-amyrin scored the most significant values in all aspects.

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.

Molecular Dynamics Simulation and Pharmacoinformatic Integrated Analysis of Bioactive Phytochemicals from Azadirachta indica (Neem) to Treat Diabetes Mellitus

Diabetes mellitus is a chronic hormonal and metabolic disorder in which our body cannot generate necessary insulin or does not act in response to it, accordingly, ensuing in discordantly high blood sugar (glucose) levels. Diabetes mellitus can lead to systemic dysfunction in the multiorgan system, including cardiac dysfunction, severe kidney disease, lowered quality of life, and increased mortality risk from diabetic complications. To uncover possible therapeutic targets to treat diabetes mellitus, the in silico drug design technique is widely used, which connects the ligand molecules with target proteins to construct a protein-ligand network. To identify new therapeutic targets for type 2 diabetes mellitus, Azadirachta indica is subjected to phytochemical screening using in silico molecular docking, pharmacokinetic behavior analysis, and simulation-based molecular dynamic analysis. This study has analyzed around 63 phytochemical compounds, and the initial selection of the compounds was made by analyzing their pharmacokinetic properties by comparing them with Lipinski’s rule of 5. The selected compounds were subjected to molecular docking. The top four ligand compounds were reported along with the control drug nateglinide based on their highest negative molecular binding affinity. The protein-ligand interaction of selected compounds has been analyzed to understand better how compounds interact with the targeted protein structure. The results of the in silico analysis revealed that 7-Deacetyl-7-oxogedunin had the highest negative docking score of −8.9 Kcal/mol and also demonstrated standard stability in a 100 ns molecular dynamic simulation performed with insulin receptor ectodomain. It has been found that these substances may rank among the essential supplementary antidiabetic drugs for treating type 2 diabetes mellitus. It is suggested that more in vivo and in vitro research studies be carried out to support the conclusions drawn from this in silico research strategy.

Advanced implications of nanotechnology in disease control and environmental perspectives

Nanotechnology encompasses a wide range of devices derived from biology, engineering, chemistry, and physics, and this scientific field is composed of great collaboration among researchers from several fields. It has diverse implications notably smart sensing technologies, effective disease diagnosis, and sometimes used in treatment. In medical science, the implications of nanotechnology include the development of elements and devices that interact with the body at subcellular (i.e., molecular) levels exhibiting high sensitivity and specificity. There is a plethora of new chances for medical science and disease treatment to be discovered and exploited in the rapidly developing field of nanotechnology. In different sectors, nanomaterials are used just because of their special characteristics. Their large surface area of them enables higher reactivity with greater efficiency. Furthermore, special surface chemistry is displayed by nanomaterials which compare to conventional materials and facilitate the nanomaterials to decrease pollutants efficiently. Recently, nanomaterials are used in some countries to reduce the levels of contaminants in water, air, and soil. Moreover, nanomaterials are used in the cosmetics and medical industry, and it develops the drug discovery (DD) system. Among a huge number of nanomaterials, Cu, Ag, TiO₂, ZnO, Fe₃O₄, and carbon nanotubes (CNTs) are extensively used in different industries for various purposes. This extensive review study has introduced the major scientific and technical features of nanotechnology, as well as some possible clinical applications and positive feedback in environmental waste management and drug delivery systems.

Molecular identification, characterization, and antagonistic activity profiling of Bacillus cereus LOCK 1002 along with the in-silico analysis of its presumptive bacteriocins

Objectives

This research aimed to isolate, identify, and characterize a new strain of Bacillus cereus through different molecular biology approaches so that it could be further studied for therapeutic purposes against selective enteric pathogens.

Materials and Methods

Pure isolates of B. cereus were prepared from buffalo yogurt samples in REMBA medium. Initially, the morphological, physiological, and biochemical properties were studied accordingly. Following the tests, the molecular identification for the strain identification was conducted through plasmid DNA extraction, PCR, agarose gel electrophoresis, and 16S rRNA sequencing up to 1.37 kb. Afterward, the antibiotic sensitivity [Epsilometer test (E-Test)] and antifungal activity were tested considering different concentrations. Being classified from the aforementioned tests, a comprehensive antimicrobial activity test was conducted using the cell-free-supernatant (CFS) of the test strain against selective enteric pathogens in humans in vitro. Besides, the different clusters of genes were identified and characterized for understanding the presumptive bacteriocins present in the CFS of the strain in silico, where molecular string properties were calculated. Finally, the evolutionary relationship among diversified bacteriocins synthesized by different Bacillus strains was studied to predict the CFS-containing bacteriocins of the new strain.

Results

Purified isolates of B. cereus were Gram-positive rods and showed significant tolerance (p < 0.0001) to different concentrations of pH, phenol, bile salt, and NaCl. 16S rRNA revealed the strain as LOCK 1002, which was strongly sensitive to all the antibiotics used and resistant to selective antifungal agents. The CFS of B. cereus LOCK 1002 was found to be a very promising antagonist to all the enteric pathogens used in the culture condition. Two gene clusters were predicted to be interconnected and responsible for different presumptive bacteriocins.

Conclusion

The newly identified LOCK 1002 can be a very potent strain of B. cereus in use as an antimicrobial agent for having different bacteriocin coding gene clusters.