Cardiovascular diseases (CVDs) are a primary cause of death globally. A few classic and hybrid treatments exist to treat CVDs. However, they lack in both safety and effectiveness. Thus, innovative nanomaterials for disease diagnosis and treatment are urgently required. The tiny size of nanomaterials allows them to reach more areas of the heart and arteries, making them ideal for CVDs. Atherosclerosis causes arterial stenosis and reduced blood flow. The most common treatment is medication and surgery to stabilize the disease. Nanotechnologies are crucial in treating vascular disease. Nanomaterials may be able to deliver medications to lesion sites after being infused into the circulation. Newer point‐of‐care devices have also been considered together with nanomaterials. For example, this study will look at the use of nanomaterials in imaging, diagnosing, and treating CVDs.

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments. Communicated by Ramaswamy H. Sarma.

In early December 2019, a large pneumonia epidemic occurred in Wuhan, China. The World Health Organization is concerned about the outbreak of another coronavirus with the powerful, rapid, and contagious transmission. Anyone with minor symptoms like fever and cough or travel history to contaminated places might be suspected of having COVID-19. COVID-19 therapy focuses on treating the disease's symptoms. So far, no such therapeutic molecule has been shown effective in treating this condition. So the treatment is mostly supportive and plasma. Globally, numerous studies and researchers have recently started fighting this virus. Vaccines and chemical compounds are also being investigated against infection. COVID-19 was successfully diagnosed using RNA detection and very sensitive RT-PCR (reverse transcription-polymerase chain reaction). The evolution of particular vaccinations is required to reduce illness severity and spread. Numerous computational analyses and molecular docking have predicted various target compounds that might stop this condition. This paper examines the main characteristics of coronavirus and the computational analyses necessary to avoid infection.

Nanoparticles are extensively used in biomedical and biotechnological research. Their large surface area, excellent physical properties, high permeability, and retention effect make them ideal for biomedical applications including diagnosis and treatment. Silver nanoparticles proved to be the safest for therapeutic uses. In the present study, silver nanoparticles (AgNPs) were prepared using various ratios of Ziziphus nummularia fruit extract and silver nitrate solution. The nanoparticles were investigated for hair growth and antibacterial and antifungal activities. Characterization of AgNPs was done by using UV‐spectrophotometer, scanning electron microscope (SEM), X‐ray diffractometer (XRD), thermogravimeter (TG), energy dispersive X‐ray (EDX), Fourier transform infrared spectroscopy (FTIR), and master sizer. UV‐spectrophotometer results showed the best ratio 10 : 10 of Z. nummularia fruit aqueous extract to silver solution for nanoparticle production at 400 to 430 nm wavelength. The size of AgNPs was 40 nm as measured by SEM. Characterization of AgNPs through EDX resulted in a silver peak at 3 keV. In contrast, differential scanning calorimetry (DSC) spectra show that the AgNPs are stable up to 160°C. The XED spectra gave 12 nm size of crystallite at 2 theta degree angle. FTIR bands for the metal oxides were recorded at 665 cm^-1. Weight loss of the prepared nanoparticles was observed due to moisture loss when subjected to TGA, whereas particle size distribution 0.1 μm to 0.17 μm was recorded by the master seizer. The Z. nummularia fruit aqueous extract‐mediated AgNPs were noted highly effective against Gram‐positive bacteria compared to ethanolic, methanolic, chloroform, and ethyl acetate extracts of Z. nummularia fruit. The Gram‐negative bacteria fungal species showed less sensitivity to AgNPs. The hair growth activity was observed to be higher for AgNPs followed by minoxidil than ethanolic and methanolic extracts of Z. nummularia fruit. These findings have concluded that Z. nummularia‐AgNPs have an effective hair growth activity and exhibit several applications in distinctive biomedical and pharmaceutical industries.

Phytochemicals have been shown to possess multiple bioactives and have been reported to showcase many medicinal effects. A similar kind of evaluation of phytoconstituents for their antimicrobial action has been reported, based on in vitro and in silico data. The goal of the research was to explore bioactive phytoconstituents of Eclipta alba leaf for antimicrobial activity. The antimicrobial activity was validated by both molecular docking and antimicrobial assay. Bioactive metabolites were identified using GC-MS. The antimicrobial and antimycobacterial activity of Eclipta alba leaves was investigated using the KirbyBauer well diffusion method and the rapid cultureMGIT DST method against a variety of human pathogens, as well as Mycobacterium tuberculosis (H37Rv) and Mycobacterium tuberculosis bacteria resistant to isoniazid and rifampicin. Eclipta alba’s GC-MS studies confirmed the detection of 17 bioactive constituents. The extract demonstrates the highest antibacterial activity against Escherichia coli (sensitive), Pseudomonas aeruginosa (sensitive) and methicillin-resistant Staphylococcus aureus (MRSA), and Pseudomonas aeruginosa susceptible and MRSA (sensitive) with zone of inhibition of 27mm, 24mm, and 32mm respectively. The extract showed no effect on Mycobacterium tuberculosis (H37Rv) and Mycobacterium tuberculosis bacteria resistant to isoniazid and rifampicin in antimycobacterial activity testing. Molecular docking investigation revealed that three compounds (phthalic acid, isobutyl octadecyl ester, hexadecanoic acid, 1(hydroxymethyl)1,2-ethanediylester, and 2,myristynoyl pantetheine) have generated the best results in terms of binding energies and significant interactions with key residues of target protein 3-hydroxydecanoyl-acyl carrier protein dehydratase (FabA) and confirm its activity as antimicrobial inhibitors. These two-dimensional plots show significant protein-ligand binding interactions (van der Waals interactions, hydrogen bond, alkyl, and Pi-alkyl interactions). ADMET (absorption, distribution, metabolism, excretion, and toxicity) results additionally support the drug-likeness characteristics of concluded potential compounds. The experimental and computational results demonstrated that methanolic extract of Eclipta alba leaves had antimicrobial effects for specific infections due to the presence of phytochemical compounds.

SARS-CoV-2, a new world coronavirus belonging to class Nidovirales of Coronaviridae family causes COVID-19 infection which is the leading cause of death worldwide. Currently there are no approved drugs and vaccines available for the prevention of COVID-19 infection, although couples of immunizations are being tested in clinical trials. However, the present efforts are focused on computational vaccination technique for evaluating candidates to design multi-epitope-based vaccine against pathogenic mechanism of novel SARS-COV-2. Based on recent published evidence, we recognized spike glycoprotein and envelope small membrane protein are the potential targets to combat the pathogenic mechanism of SARS-CoV-2. Similarly, in the present study we identified epitope of both B and T cell associated with these proteins. Extremely antigenic, conserve, immunogenic and nontoxic epitope of B and T cell of Spike protein are WPWYVWLGFI, SRVKNLNSSEGVPDLLV whereas the CWCARPTCIK and YCCNIVNVSL are associated with envelope small membrane protein were selected as potential candidate for vaccine designing. These epitopes show virtuous interaction with HLAA0201 during molecular docking analysis. Under simulation protocol the predicted vaccine candidates show stability. Collectively, this work provides novel potential candidates for epitope-based vaccine designing against COVID-19 infection.