PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants.

Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitation has resulted into underdevelopment of plant regulatory research and rampant use of Arabidopsis-like model species, generating misleading results. Here, we report a revolutionary transformers-based deep-learning approach, PTFSpot, which learns from TF structures and their binding regions' co-variability to bring a universal TF-DNA interaction model to detect TFBR with complete freedom from TF and species-specific models' limitations. During a series of extensive benchmarking studies over multiple experimentally validated data, it not only outperformed the existing software by >30% lead but also delivered consistently >90% accuracy even for those species and TF families that were never encountered during the model-building process. PTFSpot makes it possible now to accurately annotate TFBRs across any plant genome even in the total lack of any TF information, completely free from the bottlenecks of species and TF-specific models.

Computational Analysis Reveals Monomethylated Triazolopyrimidine as a Novel Inhibitor of SARS-CoV-2 RNA-Dependent RNA Polymerase (RdRp).

The human population is still facing appalling conditions due to several outbreaks of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. The absence of specific drugs, appropriate vaccines for mutants, and knowledge of potential therapeutic agents makes this situation more difficult. Several 1, 2, 4-triazolo [1, 5-a] pyrimidine (TP)-derivative compounds were comprehensively studied for antiviral activities against RNA polymerase of HIV, HCV, and influenza viruses, and showed immense pharmacological interest. Therefore, TP-derivative compounds can be repurposed against the RNA-dependent RNA polymerase (RdRp) protein of SARS-CoV-2. In this study, a meta-analysis was performed to ensure the genomic variability and stability of the SARS-CoV-2 RdRp protein. The molecular docking of natural and synthetic TP compounds to RdRp and molecular dynamic (MD) simulations were performed to analyse the dynamic behaviour of TP compounds at the active site of the RdRp protein. TP compounds were also docked against other non-structural proteins (NSP1, NSP2, NSP3, NSP5, NSP8, NSP13, and NSP15) of SARS-CoV-2. Furthermore, the inhibition potential of TP compounds was compared with Remdesivir and Favipiravir drugs as a positive control. Additionally, TP compounds were analysed for inhibitory activity against SARS-CoV RdRp protein. This study demonstrates that TP analogues (monomethylated triazolopyrimidine and essramycin) represent potential lead molecules for designing an effective inhibitor to control viral replication. Furthermore, in vitro and in vivo studies will strengthen the use of these inhibitors as suitable drug candidates against SARS-CoV-2.

SARS-CoV-2 transcriptome analysis and molecular cataloguing of immunodominant epitopes for multi-epitope based vaccine design.

Genomics-led researches are engaged in tracing virus expression pattern, and induced immune responses in human to develop effective vaccine against COVID-19. In this study, targeted expression profiling and differential gene expression analysis of major histocompatibility complexes and innate immune system genes were performed through SARS-CoV-2 infected RNA-seq data of human cell line, and virus transcriptome was generated for T-and B-cell epitope prediction. Docking studies of epitopes with MHC and B-cell receptors were performed to identify potential T-and B-cell epitopes. Transcriptome analysis revealed the specific multiple allele expressions in cell line, genes for elicited induce immune response, and virus gene expression. Proposed T- and B-cell epitopes have high potential to elicit equivalent immune responses caused by SARS-CoV-2 infection which can be useful to provide links between elicited immune response and virus gene expression. This study will facilitate in vitro and in vivo vaccine related research studies in disease control.

Bisbenzylisoquinolines from Cissampelos pareira L. as antimalarial agents: Molecular docking, pharmacokinetics analysis, and molecular dynamic simulation studies.

Malaria is a major global health issue due to the emergence of resistance to most of the available antimalarial drugs. There is an urgent need to discover new antimalarials to tackle the resistance issue. The present study aims to explore the antimalarial potential of chemical constituents reported from Cissampelos pareira L., a medicinal plant traditionally known for treating malaria. Phytochemically, benzylisoquinolines and bisbenzylisoquinolines are the major classes of alkaloids reported from this plant. In silico molecular docking revealed prominent interactions of bisbenzylisoquinolines such as hayatinine and curine with Pfdihydrofolate reductase (-6.983 Kcal/mol and -6.237 Kcal/mol), PfcGMP-dependent protein kinase (-6.652 Kcal/mol and -7.158 Kcal/mol), and Pfprolyl-tRNA synthetase (-7.569 Kcal/mol and -7.122 Kcal/mol). The binding affinity of hayatinine and curine with identified antimalarial targets was further evaluated using MD-simulation analysis. Among the identified antimalarial targets, the RMSD, RMSF, the radius of gyration, and PCA indicated the formation of stable complexes of hayatinine and curine with Pfprolyl-tRNA synthetase. The outcomes of in silico investigation putatively suggested that bisbenzylisoquinolines may act on the translation of the Plasmodium parasite to exhibit antimalarial potency.

Non-Synonymous Variants in Fat QTL Genes among High- and Low-Milk-Yielding Indigenous Breeds.

The effect of breed on milk components-fat, protein, lactose, and water-has been observed to be significant. As fat is one of the major price-determining factors for milk, exploring the variations in fat QTLs across breeds would shed light on the variable fat content in their milk. Here, on whole-genome sequencing, 25 differentially expressed hub or bottleneck fat QTLs were explored for variations across indigenous breeds. Out of these, 20 genes were identified as having nonsynonymous substitutions. A fixed SNP pattern in high-milk-yielding breeds in comparison to low-milk-yielding breeds was identified in the genes GHR, TLR4, LPIN1, CACNA1C, ZBTB16, ITGA1, ANK1, and NTG5E and, vice versa, in the genes MFGE8, FGF2, TLR4, LPIN1, NUP98, PTK2, ZTB16, DDIT3, and NT5E. The identified SNPs were ratified by pyrosequencing to prove that key differences exist in fat QTLs between the high- and low-milk-yielding breeds.

Electroactive reduced graphene oxide for highly sensitive detection of secretory non-structural 1 protein: A potential diagnostic biomarker for Japanese encephalitis virus.

Fluorine Doped Tin Oxide (FTO) electrode was fabricated with reduced Graphene Oxide (rGO) for sensitive detection of Japanese encephalitis virus (JEV) non-structural 1 (NS1) protein. Beforehand, in-silico 3D structure, stability, and docking of recombinant JEV NS1 antigen (NS1-Ag) and antibody (Ab) was evaluated. The recombinant NS1 Ag of 42 kDa was produced in-house by successful cloning into pET-28a(+) plasmid and further expressed using BL21 Escherichia coli (E. coli) cells. The NS1 Ag was used to raise polyclonal antibodies (Ab) and both were characterized via Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Western Blot, Matrix-Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF), and Enzyme-Linked Immunosorbent Assay (ELISA). Further characterisation of all binding events such as rGO synthesis, and its conjugation with NS1 Ab, and NS1 Ag were confirmed through Fourier-Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy, Energy Dispersive X-Ray Analysis (EDX), Scanning Electron Microscopy (SEM), Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV). The fabricated FTO electrode was optimised for various parameters such as pH, response time, temperature, concentration, and scan rate. The detection of JEV NS1 Ag was performed in buffer (LOD- 0.92 fM) as well in spiked serum (LOD- 1.3 fM) samples. The JEV NS1 Ab showed negligible cross-reactivity with other flaviviral NS1 Ag, provided a rapid response within 5 s, and remained stable up to 4 weeks. Furthermore, the fabricated immunosensor may be a potential candidate for further miniaturisation for accurate and early diagnosis of JEV in clinical samples.

Polymeric biocompatible iron oxide nanoparticles labeled with peptides for imaging in ovarian cancer.

Compared with other nanomaterials, surface-modified iron oxide nanoparticles (IONPs) have gained attraction for cancer therapy applications due to its low toxicity, and long retention time. An innocuous targeting strategy was developed by generation of fluorescein isothiocyanate (FITC)-labeled peptide (growth factor domain (GFD) and somatomedin B domain (SMB)) functionalized, chitosan-coated IONPs (IONPs/C). It can be used to target urokinase plasminogen activator receptor (uPAR), which is a surface biomarker, in ovarian cancer. Binding affinity between uPAR and peptides (GFD and SMB) were revealed by in-silico docking studies. The biophysical characterizations of IONPs, IONPs/C, and IONPs/C/GFD-FITC or SMB-FITC nanoprobes were assessed via Vibrating Sample Magnetometer (VSM), Transmission Electron Microscopy (TEM), Dynamic Light Scattering (DLS), and Fourier Transform Infrared Spectroscopy (FT-IR). Prussian Blue staining, fluorescence spectroscopy, and fluorescence imaging were performed to confirm the targeting of nanoprobes with the surface receptor uPAR. The combination of IONPs/C/GFD+SMB showed efficient targeting of uPAR in the tumor microenvironment, and thus can be implemented as a molecular magnetic nanoprobe for cancer cell imaging and targeting.

Anti-biofilm activity of caffeine against uropathogenic E. coli is mediated by curli biogenesis.

Biofilms are assemblages of sessile microorganisms that form an extracellular matrix around themselves and mediate attachment to surfaces. The major component of the extracellular matrix of Uropathogenic E. coli and other Enterobacteriaceae are curli fibers, making biofilms robust and resistant to antimicrobials. It is therefore imperative to screen antibiofilm compounds that can impair biofilm formation. In the present study, we investigated the curli-dependent antibiofilm activity of caffeine against UPEC strain CFT073 and commensal strain E. coli K-12MG1655.Caffeine significantly reduced the biofilm formation of both UPEC and E. coli K-12 by 86.58% and 91.80% respectively at 48 mM caffeine as determined by Crystal Violet assay. These results were further confirmed by fluorescence microscopy and Scanning Electron Microscope (SEM). Caffeine significantly reduced the cytotoxicity and survivability of UPEC. Molecular docking analysis revealed a strong interaction between caffeine and curli regulator protein (Csg D) of E. coli. The qRT-PCR data also showed significant downregulation in the expression of CsgBA and the CsgDEFG operon at both 24 mM and 48 mM caffeine. The findings revealed that caffeine could inhibit E. coli biofilm formation by regulating curli assembly and thus may be used as an alternative therapeutic strategy for the treatment of chronic E. coli biofilm-related infections.

Self-assembled chitosan polymer intercalating peptide functionalized gold nanoparticles as nanoprobe for efficient imaging of urokinase plasminogen activator receptor in cancer diagnostics.

Targeting cell surface receptors for specific drug delivery in cancer has garnered lot of attention. Urokinase plasminogen activator receptor (uPAR), a surface biomarker, is overexpressed on many tumours including breast, colorectal, prostate, and ovarian cancers. Binding of growth factor domain (GFD) of urokinase plasminogen activator (uPA) with uPAR lead to its close conformation, and allow somatomedin B domain (SMB) of vitronectin binding by allosteric modulation. In-silico docking of uPAR with GFD and SMB peptides was performed to identify potential binding affinity. Herein, we report fluorescently labeled peptide functionalized AuNPs with a mixed self-assembled monolayer of intercalating chitosan polymer for efficient targeting and imaging of uPAR-positive cells. The biophysical characterization of nanoconjugates and uPAR-specific targeting was assessed by FACS, cell adhesion, and fluorescence imaging. AuNPs/chitosan/GFD+SMB peptides showed higher uptake as compared to AuNPs/chitosan/GFD, and AuNPs/chitosan/SMB that can be utilized as a tool for molecular targeting and imaging in metastasis.

Identification of Unique Peptides for SARS-CoV-2 Diagnostics and Vaccine Development by an In Silico Proteomics Approach.

Ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus strains is posing new COVID-19 diagnosis and treatment challenges. To help efforts to meet these challenges we examined data acquired from proteomic analyses of human SARS-CoV-2-infected cell lines and samples from COVID-19 patients. Initially, 129 unique peptides were identified, which were rigorously evaluated for repeats, disorders, polymorphisms, antigenicity, immunogenicity, toxicity, allergens, sequence similarity to human proteins, and contributions from other potential cross-reacting pathogenic species or the human saliva microbiome. We also screened SARS-CoV-2-infected NBHE and A549 cell lines for presence of antigenic peptides, and identified paratope peptides from crystal structures of SARS-CoV-2 antigen-antibody complexes. We then selected four antigen peptides for docking with known viral unbound T-cell receptor (TCR), class I and II peptide major histocompatibility complex (pMHC), and identified paratope sequences. We also tested the paratope binding affinity of SARS-CoV T- and B-cell peptides that had been previously experimentally validated. The resultant antigenic peptides have high potential for generating SARS-CoV-2-specific antibodies, and the paratope peptides can be directly used to develop a COVID-19 diagnostics assay. The presented genomics and proteomics-based in-silico approaches have apparent utility for identifying new diagnostic peptides that could be used to fight SARS-CoV-2.

A Recent Update on Advanced Molecular Diagnostic Techniques for COVID-19 Pandemic: An Overview.

Coronavirus disease 2019 (COVID-19), which started out as an outbreak of pneumonia, has now turned into a pandemic due to its rapid transmission. Besides developing a vaccine, rapid, accurate, and cost-effective diagnosis is essential for monitoring and combating the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its related variants on time with precision and accuracy. Currently, the gold standard for detection of SARS-CoV-2 is Reverse Transcription Polymerase Chain Reaction (RT-PCR), but it lacks accuracy, is time-consuming and cumbersome, and fails to detect multi-variant forms of the virus. Herein, we have summarized conventional diagnostic methods such as Chest-CT (Computed Tomography), RT-PCR, Loop Mediated Isothermal Amplification (LAMP), Reverse Transcription-LAMP (RT-LAMP), as well new modern diagnostics such as CRISPR-Cas-based assays, Surface Enhanced Raman Spectroscopy (SERS), Lateral Flow Assays (LFA), Graphene-Field Effect Transistor (GraFET), electrochemical sensors, immunosensors, antisense oligonucleotides (ASOs)-based assays, and microarrays for SARS-CoV-2 detection. This review will also provide an insight into an ongoing research and the possibility of developing more economical tools to tackle the COVID-19 pandemic.

SARS-CoV-2 Spike Glycoprotein and ACE2 Interaction Reveals Modulation of Viral Entry in Wild and Domestic Animals.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a viral pathogen causing life-threatening diseases in humans. Interaction between the spike protein of SARS-CoV-2 and angiotensin-converting enzyme 2 (ACE2) is a potential factor in the infectivity of a host. In this study, the interaction of SARS-CoV-2 spike protein with its receptor, ACE2, in different hosts was evaluated to predict the probability of viral entry. Phylogeny and alignment comparison of the ACE2 sequences did not lead to any meaningful conclusion on viral entry in different hosts. The binding ability between ACE2 and the spike protein was assessed to delineate several spike binding parameters of ACE2. A significant difference between the known infected and uninfected species was observed for six parameters. However, these parameters did not specifically categorize the Orders into infected or uninfected. Finally, a logistic regression model constructed using spike binding parameters of ACE2, revealed that in the mammalian class, most of the species of Carnivores, Artiodactyls, Perissodactyls, Pholidota, and Primates had a high probability of viral entry. However, among the Proboscidea, African elephants had a low probability of viral entry. Among rodents, hamsters were highly probable for viral entry with rats and mice having a medium to low probability. Rabbits have a high probability of viral entry. In Birds, ducks have a very low probability, while chickens seemed to have medium probability and turkey showed the highest probability of viral entry. The findings prompt us to closely follow certain species of animals for determining pathogenic insult by SARS-CoV-2 and for determining their ability to act as a carrier and/or disseminator.