Seasonal antigenic prediction of influenza A H3N2 using machine learning.

Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by using the hemagglutination inhibition (HI) assays for surveillance purposes. It is also used to determine the need for annual influenza vaccine updates as well as for pandemic preparedness. Performing antigenic characterization of IAV on a global scale is confronted with high costs, animal availability, and other practical challenges. Here we present a machine learning model that accurately predicts (normalized) outputs of HI assays involving circulating human IAV H3N2 viruses, using their hemagglutinin subunit 1 (HA1) sequences and associated metadata. Each season, the model learns an updated nonlinear mapping of genetic to antigenic changes using data from past seasons only. The model accurately distinguishes antigenic variants from non-variants and adaptively characterizes seasonal dynamics of HA1 sites having the strongest influence on antigenic change. Antigenic predictions produced by the model can aid influenza surveillance, public health management, and vaccine strain selection activities.

Sex and gender essentialism in textbooks.

Several widely used high school biology texts depart from established science.

Humane genomics education can reduce racism.

Moving instruction "beyond Mendel" can counter inaccurate, essentialist views.

Lauric acid provides neuroprotection against oxidative stress in mouse model of hyperglycaemic stroke.

During ischemic stroke, higher glucose level linked worse outcomes were reported even in patients without pre-existing diabetes. Evidence suggest that such worse stroke outcomes were mainly due to production of reactive, toxic glucose metabolites that expands oxidative damage inside the brain. As a consequence of high oxidative stress, microvasculature structures and tight junctions compromised their functionally, infarct volume expands and brain edema exacerbates. In a mouse model of ischemic stroke with induced acute hyperglycaemia, Lauric acid (LA) as a natural saturated fatty acid demonstrated neuroprotection by attenuating infarct volume and brain edema. In addition, in the ipsilateral hyperglycaemic brain, the LA significantly increased the expression of tight junction representative protein (occludin) as well as anti-oxidative markers; Manganese superoxide dismutase (Mn) SOD, Extracellular superoxide dismutase (Ec-SOD) and nuclear factor-erythroid factor 2-related factor 2 (Nrf2) in the ipsilateral region against hyperglycemic ischemic stroke. LA treated animals showed a significant reduction in the production of lipid peroxidation products (4-HNE) in the microvascular structures, maintained the blood brain barrier (BBB) integrity. LA linked neuroprotective outcomes were further confirmed by behavioral tests, where functional outcomes and motor coordination were improved significantly. Furthermore, LA treatment enhanced food intake, decreased mortality rate, and net body weight loss. Conclusively, LA modulated ischemic insult exacerbated by hyperglycemia and provided neuroprotection.

Bioinformatics and systems biology analysis revealed PMID26394986-Compound-10 as potential repurposable drug against covid-19.

The global health pandemic known as COVID-19, which stems from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a significant concern worldwide. Several treatment methods exist for COVID-19; however, there is an urgent demand for previously established drugs and vaccines to effectively combat the disease. Since, discovering new drugs poses a significant challenge, making the repurposing of existing drugs can potentially reduce time and costs compared to developing entirely new drugs from scratch. The objective of this study is to identify hub genes and associated repurposed drugs targeting them. We analyzed differentially expressed genes (DEGs) by analyzing RNA-seq transcriptomic datasets and integrated with genes associated with COVID-19 present in different databases. We detected 173 Covid-19 associated genes for the construction of a protein-protein interaction (PPI) network which resulted in the identification of the top 10 hub genes/proteins (STAT1, IRF7, MX1, IRF9, ISG15, OAS3, OAS2, OAS1, IRF3, and IRF1). Hub genes were subjected to GO functional and KEGG pathway enrichment analyses, which indicated some key roles and signaling pathways that were strongly related to SARS-CoV-2 infections. We conducted drug repurposing analysis using CMap, TTD, and DrugBank databases with these 10 hub genes, leading to the identification of Piceatannol, CKD-712, and PMID26394986-Compound-10 as top-ranked candidate drugs. Finally, drug-gene interactions analysis through molecular docking and validated via molecular dynamic simulation for 80 ns suggests PMID26394986-Compound-10 as the only potential drug. Our research demonstrates how in silico analysis might produce repurposing candidates to help respond faster to new disease outbreaks.Communicated by Ramaswamy H. Sarma.

In Silico Method for the Screening of Phytochemicals against Methicillin-Resistant Staphylococcus Aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) has evolved resistance even against the last resort ß-lactam antibiotics. This is because of the acquisition of an additional penicillin-binding protein 2a (PBP2a) which is a resistance determinant in MRSA. Currently, available PBP2a inhibitors are ineffective against life-threatening and fatal infections caused by microorganisms. Therefore, there is an urgent need to screen natural compounds that could overpass the resistance issue alone or in combination with antibacterial drugs. We studied the interactions of different phytochemicals with PBP2a so that crosslinking of peptidoglycans could be inhibited. In structure-based drug designing, in silico approach plays a key role in determining phytochemical interactions with PBP2a. In this study, a total of 284 antimicrobial phytochemicals were screened using the molecular docking approach. The binding affinity of methicillin, -11.241 kcal/mol, was used as the threshold value. The phytochemicals having binding affinities with PBP2a stronger than methicillin were identified, and the drug-likeness properties and toxicities of the screened phytochemicals were calculated. Out of the multiple phytochemicals screened, nine were found as good inhibitors to be PBP2a, among which cyanidin, tetrandrine, cyclomorusin, lipomycin, and morusin showed strong binding potential with the receptor protein. These best-selected phytochemicals were also docked to the allosteric site of PBP2a, and most of the compounds revealed strong interactions with the allosteric site. These compounds were safe to be used as drugs because they did not show any toxicity and had good bioactivity scores. Cyanidin had the highest binding affinity (S-score of -16.061 kcal/mol) with PBP2a and with high gastrointestinal (GI) absorption. Our findings suggest that cyanidin can be used as a drug against MRSA infection either in purified form or that its structure can lead to the development of more potent anti-MRSA medicines. However, experimental studies are required to evaluate the inhibitory potential of these phytochemicals against MRSA.

Identification of Plant Peptides as Novel Inhibitors of Orthohepevirus A (HEV) Capsid Protein by Virtual Screening.

Hepatitis E virus (HEV) is the notable causative agent of acute and chronic hepatic, renal, pancreatic, neurological, and hematopoietic blood cell infections with high risk in immunocompromised patients. Hepatic failure is mostly documented among adults, pregnant women, and patients with preexisting liver disease. HEV is a positive sense RNA virus of 7.2 kb genome size with typically three open reading frames (ORFs) which play essential roles in viral replication, genome assembly, and transcription. The mutational substitution in the viral RNA genome makes more it difficult to understand the actual relationship in the host-virus association. ORFs of HEV encode different structural and non-structural proteins and one of them is the capsid protein which is coded by ORF2. The capsid protein mediates the encapsulation of the viral genome as well as being involved in virion assembly. In the current study, the ligand-based docking approach was employed to inhibit the active amino acids of the viral capsid protein. Depending upon S-score, ADMET profiling, and drug scanning, the top ten tetrapeptides were selected as potential drug candidates with no toxicity counter to HEV receptor protein. The S-score or docking score is a mathematical function which predicts the binding affinities of docked complexes. The binding affinity of the predicted drug-target complexes helps in the selectivity of the desired compound as a potential drug. The best two selected peptides (i.e., TDGH with S-score of -8.5 and EGDE with S-score of -8.0) interacted with the active site amino acids of the capsid protein (i.e., Arg399, Gln420, and Asp444). The molecular dynamics simulations of RMSD trajectories of TDGH-capsid protein and EDGE-capsid protein have revealed that both docked complexes were structurally stable. The study revealed that these tetrapeptides would serve as strong potential inhibitors and a starting point for the development of new drug molecules against the HEV capsid protein. In future, in vivo studies are needed to explore selected peptides as potential drug candidates.

Hydrothermal assisted synthesis of hierarchical SnO2 micro flowers with CdO nanoparticles based membrane for energy storage applications.

Hierarchical nanostructures with appropriate morphology and surface functionalities are highly desired to achieve an optimized electrochemical property for active electrode materials. This work renders the facile hydrothermal synthesis of CdO, SnO2, and CdO-SnO2 nanocomposite, and their capacitive performance was tested. The formation of the pure samples and their composite was committed by low-temperature Raman spectroscopy and x-ray diffraction studies which revealed the tetragonal and cubic structures of CdO and SnO2 powder samples with good crystallinity and purity. The morphological postmortem reveals the formation of nanoparticles morphology of CdO with a highly smooth surface appearance. Besides, the SnO2 illustrates the morphology of the micro flowers composed of ultrathin nanosheets. More specifically, the electrochemical properties indicate the pseudocapacitive charge storage mechanism based on cyclic voltammetry and chronopotentiometry analysis. The CdO-SnO2 composite electrode displayed a higher capacitance due to additional pores/space offered for active sites and continuously allowed electrolyte ions to interact with the inner/outer surface of the electrode. These exciting findings led us to design and fabricate battery hybrid supercapacitors (BHSC) from CdO-SnO2, and activated carbon (AC), referred to as CdO-SnO2//AC BHSC, attains a high power delivery (5717 W/kg), and a maximum energy density of 42 Wh/kg at low discharge rate. Noteworthy, a stable cycling performance was obtained with only 91.3% retention after 8000 cycling at a large discharge current of 10 A/g, denoting the magnificent durability of the active electrode material.

Comparative molecular docking analysis for analyzing the inhibitory effect of Anakinra and Ustekinumab against IL17F.

Interleukin 17 F is a member of IL-17 cytokine family with a 50% structural homology to IL-17A and plays a significant role either alone or in combination with IL-17A towards inflammation in Rheumatoid arthritis (RA). A growing number of drugs targeting IL-17 pathway are being tested against population specific disease markers. The major objective of this research was to investigate the anti-inflammatory effect of Anakinra (an IL-1 R1 inhibitor) and Ustekinumab (an IL-12 and IL-23 inhibitor) by targeting IL17F. The three dimensional structures of IL17F was taken from PDB while structures of drugs were taken from PubChem database. Docking was performed using MOE and Schrodinger ligand docking software and binding energies, including s-score using London-dG fitness function and glide score using glide internal energy function, between drug and targets were compared. Furthermore, Protein-Drug complex were subjected to 150 ns Molecular Dynamics (MD) Simulations using Schrodinger's Desmond Module. Docking and MD simulation results suggest anakinra as a more potent IL17F inhibitor and forming a more structurally stable complex.Communicated by Ramaswamy H. Sarma.

Synthesis and performance evaluation of copper and magnesium-based metal organic framework supported ionic liquid membrane for CO2/N2 separation.

The CO2 emission is enhancing drastically because of the continuous emission from industries and transport sector. Although the CO2 emission had decreased in the first half of 2020 by 8.8% due to COVID-19 restrictions however, it is again on the rise and it might exceed the estimated level in 2030. The current methods used for CO2 separation have serious operational and environmental constraints. To overcome these problems we have devised a supported ionic liquid membrane (SILM) incorporated with the blend of bimetallic metal-organic framework (MOF) of copper and magnesium ions (CuxMgx) and Trihexyltetradecylphosphonium chloride [P66614] [Cl] ionic liquid (IL). CuxMgx MOF were synthesized and characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), and energy dispersive X-ray analysis (EDX). CuxMgx MOF with [P66614] [Cl] IL were immobilized on a flat sheet of polytetrafluoroethylene (PTFE) membrane. Single gas permeation tests of membranes loaded with 0.2/0.8 wt/wt% MOF/IL solution showed the highest CO2 permeability of 2937 Barrer and CO2/N2 selectivity of 33.26. The performance of SILM was also investigated with different water loadings of (30 wt % and 50 wt %) in addition to MOF/IL solution and at different feed pressure varying from 0.5 to 2 bars. Membranes showed enhancement in CO2 permeability to 3738 and 4628 Barrer whereas CO2/N2 selectivity decreased to 23.53 and 21.8 with membranes loaded with 30 and 50 wt % water, respectively, at a feed pressure of 2 bar. The gas permeation results show that the incorporation of CuxMgx MOF with IL in polymeric membrane enhances the CO2/N2 separation under humid conditions but slightly decreases CO2/N2 selectivity with an increase in feed pressure. The SILM synthesized in this research is highly viable for industrial flue gases because of the incorporation of phosphonium-based ILs that have high thermal stability.

Mendelian or Multifactorial? Current Undergraduate Genetics Assessments Focus on Genes and Rarely Include the Environment.

Undergraduate genetics courses have historically focused on simple genetic models, rather than taking a more multifactorial approach where students explore how traits are influenced by a combination of genes, the environment, and gene-by-environment interactions. While a focus on simple genetic models can provide straightforward examples to promote student learning, they do not match the current scientific understanding and can result in deterministic thinking among students. In addition, undergraduates are often interested in complex human traits that are influenced by the environment, and national curriculum standards include learning objectives that focus on multifactorial concepts. This research aims to discover to what extent multifactorial genetics is currently being assessed in undergraduate genetics courses. To address this, we analyzed over 1,000 assessment questions from a commonly used undergraduate genetics textbook; published concept assessments; and open-source, peer-reviewed curriculum materials. Our findings show that current genetics assessment questions overwhelmingly emphasize the impact of genes on phenotypes and that the effect of the environment is rarely addressed. These results indicate a need for the inclusion of more multifactorial genetics concepts, and we suggest ways to introduce them into undergraduate courses.

Concurrent Effects of Drought and Heat Stresses on Physio-Chemical Attributes, Antioxidant Status and Kernel Quality Traits in Maize (Zea mays L.) Hybrids.

Maize is one of the most important field crops considering its utilization as food, feed, fodder, and biofuel. However, the sustainability of its production is under serious threat of heat and drought stresses, as these stresses could hamper crop growth, causing a significant loss to kernel yield. The research study was carried out at Maize and Millets Research Institute, Yusafwala-Sahiwal for two consecutive spring seasons (2019-20 and 2020-21) under a split-split plot design. The current study explained the individual and combined effects of drought and heat stresses on morphology, phenology, physiology, reactive oxygen species (stocktickerROS), antioxidant status, and kernel quality traits in four indigenous (YH-5482, YH-5427, YH-5404, and YH-1898) and one multinational maize hybrid (P-1543). Stress treatments, i.e., drought, heat, and drought+heat, were applied ten days before tasseling and lasted for 21 days. The results revealed the incidence of oxidative stress due to overproduction of Hydrogen peroxide; H2O2 (control: 1.9, heat+drought: 5.8), and Malondialdehyde; stocktickerMDA (control: 116.5, heat+drought: 193), leading to reduced photosynthetic ability (control: 31.8, heat:16.5), alterations in plant morphology, decrease in kernel yield (control: 10865 kg ha-1, heat+drought: 5564 kg ha-1), and quality-related traits. Although all the stress treatments induced the accumulation of stress-responsive osmolytes and enzymatic antioxidants to cope with the negative impact of osmotic stress, the effect of combined drought + heat stress was much higher. The overall performance of indigenous maize hybrid YH-5427 was much more promising than the other hybrids, attributed to its better tolerance of drought and heat stresses. Such stress tolerance was attributed to maintaining photosynthetic activity, a potent antioxidant and osmolyte-based defense mechanisms, and minimum reductions in yield-related traits, which assured the maximum kernel yield under all stress treatments.

Discovery and characterization of dual inhibitors of human Vanin-1 and Vanin-2 enzymes through molecular docking and dynamic simulation-based approach.

The vanins are ectoenzymes with pantetheinase activity and are involved in recycling pantothenic acid (vitamin B5) from pantetheine. Elevated levels of vanin have been linked with the development and severity of several diseases, including steatosis, diabetes, skin diseases, cancer, inflammatory diseases etc. Therefore, vanins have previously been used as a potential drug target to combat related diseases. In this study, we used a molecular docking and molecular dynamic simulation-based approach to screen dual inhibitors of hVnn1, and hVnn2 from a library of 120 chemical candidates. Molecular docking of drug candidates with hVnn1, and hVnn2 using GOLD and MOE revealed that the chemical compound "methotrexate (CID: 126941)" has the highest binding affinity against both the target enzymes which was further validated through molecular dynamic simulation. Toxicity profiling of drug candidates evaluated using Lipinski's rule of five and Molsoft tool, and AdmetSar 2.0 confirms the drug suitability of methotrexate, therefore, suggesting its use as a potential therapeutic agent to inhibit the activity of vainin enzyme in related disease conditions.

A Nanoinformatics Approach to Evaluate the Pharmacological Properties of Nanoparticles for the Treatment of Alzheimer's Disease.

BACKGROUND: Alzheimer's disease is a destructive nervous system disease which causes structural, biochemical and electrical abnormalities inside the human brain and results due to genetic and various environmental factors. Traditional therapeutic agents of Alzheimer's disease such as tacrine and physostigmine have been found to cause adverse effects to the nervous system and gastrointestinal tract. Nanomaterials like graphene, metals, carbon-nanotubes and metal-oxides are gaining attention as potential drugs against Alzheimer's disease due to their properties such as large surface area, which provide clinical efficiency, targeted drug designing and delivery. OBJECTIVES: Designing new drugs by using experimental approaches is a time-consuming, tedious and laborious process which also requires advanced technologies. This study aims to identify some novel drug candidates against Alzheimer's disease with no or less associated side effects using molecular docking approaches Methods: In this study, we utilized nanoinformatics based approaches for evaluating the interaction properties of various nanomaterials and metal nanoparticles with the drug targets, including TRKB kinase domain, EphA4 and histone deacetylase. Furthermore, the drug-likeness of carbon nanotubes was confirmed through ADME analysis. RESULTS: Carbon nanotubes, either single or double-walled in all the three-configurations, including zigzag, chiral, and armchair forms, are found to interact with the target receptors with varying affinities Conclusion: This study provides novel and clearer insights into the interaction properties and drug suitability of known putative nanoparticles as potential agents for the treatment of Alzheimer's disease.

In Silico and In Vivo: Evaluating the Therapeutic Potential of Kaempferol, Quercetin, and Catechin to Treat Chronic Epilepsy in a Rat Model.

Recently, alternative therapies are gaining popularity in the treatment of epilepsy. The present study aimed to find out the antiepileptic potential of quercetin, catechin, and kaempferol. In vivo and in silico experiments were conducted to investigate their therapeutic potential. 25 mg/kg/day of pentylenetetrazole was administered for 4 weeks after epilepsy was induced in the rats; this was followed by the behavioral studies and histological analysis of rat brain slices. Binding affinities of kaempferol, quercetin, and catechin were assessed by performing in silico studies. Kaempferol, quercetin, and catechin were found to have the highest binding affinity with the synaptic vesicle 2A (SV2A) protein, comparable to standard levetiracetam (LEV). The mRNA levels of SV2A, as well as the expression of TNF, IL 6, IL 1 beta, NFkB, IL 1Ra, IL 4, and IL 10, were investigated using qPCR. Our results indicate for the first time that SV2A is also a transporter of understudied phytoflavonoids, due to which a significant improvement was observed in epileptic parameters. The mRNA levels of SV2A were found to be significantly elevated in the PF-treated rats when compared with those of the control rats with epilepsy. Additionally, downregulation of the pro-inflammatory cytokines and upregulation of the anti-inflammatory cytokines were also noted in the PF-treated groups. It is concluded that kaempferol, quercetin, and catechin can effectively decrease the epileptic seizures in our chronic epilepsy rat model to a level that is comparable to the antiepileptic effects induced by levetiracetam drug.

Repurposing the inhibitors of COVID-19 key proteins through molecular docking approach.

The severe acute respiratory syndrome coronavirus 2, famous as COVID-19, has recently emerged as a novel virus and imposed an unrecoverable loss to global health and the economy. At present, no effective drug against COVID-19 is available and currently available viral drugs targeting the viral key proteins of related RNA viruses have been found ineffective against COVID-19. This study evaluated the inhibitors of the viral proteases and other structural proteins, including Mpro (Main protease), RdRp (RNA-dependent RNA polymerase), and spike glycoprotein from synthetic and herbal sources. The molecular docking-based approach was used to identify and evaluate the putative inhibitors of key proteins involved in viral replication and survival. Furthermore, the pharmaceutical properties of these inhibitors were explored to predict the drug suitability as a therapeutic agent against COVID-19 by considering adsorption, distribution, metabolism, and excretion (ADME) using Lipinski's rule or SwissADME. Trandolapril, Benazepril, and Moexipril were evaluated as the best non-carcinogenic and non-toxic potential inhibitors of spike glycoprotein, Mpro, and RdRp, respectively. The drugs showed significant binding affinities against the active sites of respective SARS_CoV-2 target proteins; hence, they can be used as potential therapeutic agents for the treatment of COVID-19.

Molecular docking of alpha-enolase to elucidate the promising candidates against Streptococcus pneumoniae infection.

PURPOSE: To predict potential inhibitors of alpha-enolase to reduce plasminogen binding of Streptococcus pneumoniae (S. pneumoniae) that may lead as an orally active drug. S. pneumoniae remains dominant in causing invasive diseases. Fibrinolytic pathway is a critical factor of S. pneumoniae to invade and progression of disease in the host body. Besides the low mass on the cell surface, alpha-enolase possesses significant plasminogen binding among all exposed proteins. METHODS: In-silico based drug designing approach was implemented for evaluating potential inhibitors against alpha-enolase based on their binding affinities, energy score and pharmacokinetics. Lipinski's rule of five (LRo5) and Egan's (Brain Or IntestinaL EstimateD) BOILED-Egg methods were executed to predict the best ligand for biological systems. RESULTS: Molecular docking analysis revealed, Sodium (1,5-dihydroxy-2-oxopyrrolidin-3-yl)-hydroxy-dioxidophosphanium (SF-2312) as a promising inhibitor that fabricates finest attractive charges and conventional hydrogen bonds with S. pneumoniae alpha-enolase. Moreover, the pharmacokinetics of SF-2312 predict it as a therapeutic inhibitor for clinical trials. Like SF-2312, phosphono-acetohydroxamate (PhAH) also constructed adequate interactions at the active site of alpha-enolase, but it predicted less favourable than SF-2312 based on binding affinity. CONCLUSION: Briefly, SF-2312 and PhAH ligands could inhibit the role of alpha-enolase to restrain plasminogen binding, invasion and progression of S. pneumoniae. As per our investigation and analysis, SF-2312 is the most potent naturally existing inhibitor of S. pneumoniae alpha-enolase in current time.

A Molecular Docking Approach to Evaluate the Pharmacological Properties of Natural and Synthetic Treatment Candidates for Use against Hypertension.

Cardiovascular diseases (CVDs) have become the leading cause of disability and death worldwide, particularly in low- and middle-income countries. Hypertension, a major cause of CVD progression, is widely attributable to genetic, behavioral, and environmental risk factors. Among the genetic reasons, angiotensin II enzyme, produced as a result of abnormal functioning of the renin⁻angiotensin system, is reported as the foremost cause of hypertension. A cascade of genes, including those encoding for WNK kinases (WNK1 and WNK4), Bp1, Bp2, angiotensinogen, and other enzymes, is involved in the conversion of angiotensin I to angiotensin II. However, the angiotensin-converting enzyme (ACE) plays a crucial role in this pathway. Therefore, ACE could be a potential therapeutic target in regulating the conversion of angiotensin I to angiotensin II and eventually controlling hypertension. In this study, a molecular docking-based approach was utilized for identifying and evaluating potential inhibitors of ACE present in herbs, other natural sources, and synthetic sources, on the basis of these compounds' binding affinities and other physicochemical features. In addition, the suitability of these inhibitors as drugs for biological systems, considering their adsorption, distribution, metabolism, and excretion (ADME), was predicted using Lipinski's rule. In conclusion, our study provides a novel and clearer insight into the interaction properties of known putative inhibitors of ACE.