Hypertension is considered as one of the most common diseases that affect human beings (both male and female) due to its high prevalence and also extending widely to both industrialize and developing ...countries. Angiotensin-converting enzyme (ACE) has a significant role in the regulation of blood pressure and ACE inhibition with inhibitory peptides is considered as a major target to prevent hypertension. In the current study, a blood pressure regulating honey protein (MRJP1) was examined to identify the ACE inhibitory peptides. The 3D structure of MRJP1 was predicted by utilizing the threading approach and further optimized by performing molecular dynamics simulation for 30 nanoseconds (ns) to improve the quality factor up to 92.43%. Root mean square deviation and root mean square fluctuations were calculated to evaluate the structural features and observed the fluctuations in the timescale of 30 ns. AHTpin server based on scoring vector machine of regression models, proteolysis and structural characterization approaches were implemented to identify the potential inhibitory peptides. The anti-hypertensive peptides were scrutinized based on the QSAR models of anti-hypertensive activity and the molecular docking analyses were performed to explore the binding affinities and potential interacting residues. The peptide "EALPHVPIFDR" showed the strong binding affinity and higher anti-hypertensive activity along with the global energy of -58.29 and docking score of 9590. The aromatic amino acids especially Tyr was observed as the key residue to design the dietary peptides and drugs like ACE inhibitors.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Synapsin II regulates neurotransmitter release from mature nerve terminals and plays important role in the formation of new nerve terminals. The associations of SYN II are identified in various ...studies that are linked to the onset of Schizophrenia. Schizophrenia is characterized by abnormal behavior like obsession, dampening of emotions and auditory hallucination.
The bioinformatics approaches were utilized for structural modeling and docking analyses of SYN II followed by pharmacophore generation to identify potent inhibitors.
The comparative modeling approach was employed to generate the 3D model having 82.404% quality factor calculated by Errat. Pharmacophore was constructed by utilizing merge molecular and chemical features of selected five FDA approved Schizophrenia drugs by LigandScout 4.1.5. Comparative docking analyses were performed by utilizing the selected drugs and top screened hits by GOLD and AutoDock Vina.
It was proposed that Aripiprazole drug and scrutinized compounds have strong binding affinities among the other selected drugs. The reported compounds may be used for further analyses in the drug discovery processes, as they have shown good human intestinal absorption and are noncarcinogenic. The present study provides the structural insights which may be used for further understating of the Schizophrenia therapeutic purposes by targeting SYN II and other inhibitors haunting.
Backgound: Cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) is an imperative enzyme due to its immersion in the biotransformation of a wide range of drugs and other xenobiotics. The ...involvement of enzymes in drug metabolism indicates an effective drug target for the development of novel therapeutics. The discovery of CYP1A1 specific inhibitors would be of particular relevance for the clinical pharmacology.
In the current work, in silico approaches were utilized to identify the novel potential compounds through a diverse set of reported inhibitors against CYP1A1. A dataset of reported compounds against CYP1 belongs to 10 different classes (alkaloids, coumarins, flavonoids, natural compounds, synthetic inhibitors, drugs, MBI's, PAHs, naphthoquinone and stilbenoids) was retrieved and utilized for the comparative molecular docking analyses followed by pharmacophore modeling. The total eleven novel compounds were scrutinized on the basis of the highest binding affinities and least binding energy values.
ZINC08792486 compound attained the highest gold fitness score of 90.11 against CYP1A1 among all the scrutinized molecules.
It has been elucidated that the residues Phe-224, Gly-316 and Ala-317 were conserved in all ligand-receptor interactions and critical for the development of effective therapies. The ADMET property analyses also predict better absorption and distribution of the selected hits that may be used in the future for in vitro validations and drug development.
Snow and glaciers are very sensitive to changing climate. Glaciers in the central Karakoram, western Himalaya and eastern Hindukush mountain ranges are not responding to global warming in the same ...manner as their counterparts around the world. Glaciers in this region are behaving differently. Some are retreating, while others are stable or surging. It is important to monitor these changes to protect downstream communities from the negative consequences. This study is conducted to monitor the state of the selected glaciers of Hunza River Basin, such as Batura, Passu, Ghulkin, Gulmit, Baulter, Barpu, Samaiyar Bar, Muchuhar, and Shishper glaciers were analysed using Digital Elevation Model and satellite images for 1972, 1979, 1990, 1998, 2008 and 2018. A semi-automatic approach was adopted to delineate the glacier boundary supplemented by manual editing. These glaciers show different fluctuations over the last fifty years. The Batura glacier showed surge in the 1970s and then retreated followed by quiescence. There is no prominent change in Ghulkin, Barpu, and Samaiyar Bar glaciers while almost 40 m per year retreat was observed in Passu and Gulmit glaciers but Muchuhar retreated at a faster rate. The surge of Shishper results in the formation of glacier-dammed lake which has so far triggered four Glacial Lake Outburst Floods (GLOFs). Overall, area of nine glaciers decreased from 596.54 ± 31.02 km
2
in 1972 to 568.52 ± 8.51 km
2
in 2018, which accounts for 4.8% decrease in area. This decrease will affect landscape development, regional hydrology and people living downstream.
•De novo synthesis of longifolene was carried out for the first time in yeast cell factory.•Constitutive Promoters were characterized.•Screening of potential longifolene synthase for the production ...of longifolene in the S.cerevisiae.•Longifolene production was 36 mg/L in batch fermentation.
Longifolene is a woody aroma compound that is typically extracted from plants and has strong antimicrobial activity. In this study, three potential longifolene synthase candidates from Pinus trees were tested for the de novo production of longifolene in Saccharomyces cerevisiae. Among them, the longifolene synthase from Pinus sylvestris (PsTPS) exhibited the highest catalytic efficiency, leading to the production of 1.22 mg/L longifolene in S. cerevisiae. Longifolene production in engineered yeast was optimized using multiple metabolic engineering strategies. For example, the acetyl-CoA flux in the MVA pathway was enhanced by overexpressing the genes atoB from E. coli and tHMG1, IDI1, and ERG20 from S. cerevisiae; the ethanol metabolic pathway was downregulated; the expression genes in the MVA pathway was performed using newly characterized constitutive promoters; and the DGA1 gene was overexpressed to promote the biogenesis of lipid droplets and enhance longifolene accumulation. Finally, the engineered strain produced 17.7 mg/L longifolene in a shake flask and 36.8 mg/L during fed-batch fermentation.
Circular RNAs (circRNAs) are a distinctive type of endogenous non-coding RNAs, and their regulatory roles in neurological disorders have received immense attention. CircRNAs significantly contribute ...to the regulation of gene expression and progression of neurodegenerative disorders including Alzheimer’s disease (AD). The current study aimed to identify circRNAs as prognostic and potential biomarkers in AD. The differentially expressed circRNAs among subjective cognitive decline, amnestic mild cognitive impairment, and age-matched normal donors were determined through Arraystar Human circRNA Array V2 analysis. The annotations of circRNAs-microRNA interactions were predicted by employing Arraystar’s homemade microRNAs (miRNA) target prediction tool. Bioinformatics analyses comprising gene ontology enrichment, KEGG pathway, and network analysis were conducted. Microarray analysis revealed the 33 upregulated and 11 downregulated differentially expressed circRNAs (FC ≥ 1.5 and
p
-values ≤ 0.05). The top 10 differentially expressed upregulated and downregulated circRNAs have been chosen for further expression validation through quantitative real-time PCR and subsequently, hsa-circRNA_001481 and hsa_circRNA_000479 were confirmed experimentally. Bioinformatics analyses determined the circRNA-miRNA-mRNA interactions and microRNA response elements to inhibit the expression of miRNAs and mRNA targets. Gene ontology enrichment and KEGG pathways analysis revealed the functional clustering of target mRNAs suggesting the functional verification of these two promising circRNAs. It is concluded that human circRNA_001481 and circRNA_000479 could be utilized as potential biomarkers for the early onset detection of AD and the development of effective therapeutics.
Cancer is considered one of the deadliest diseases globally, and continuous research is being carried out to find novel potential therapies for myriad cancer types that affect the human body. ...Researchers are hunting for innovative remedies to minimize the toxic effects of conventional therapies being driven by cancer, which is emerging as pivotal causes of mortality worldwide. Cancer progression steers the formation of heterogeneous behavior, including self-sustaining proliferation, malignancy, and evasion of apoptosis, tissue invasion, and metastasis of cells inside the tumor with distinct molecular features. The complexity of cancer therapeutics demands advanced approaches to comprehend the underlying mechanisms and potential therapies. Precision medicine and cancer therapies both rely on drug discovery.
drug screening and
animal trials are the mainstays of traditional approaches for drug development; however, both techniques are laborious and expensive. Omics data explosion in the last decade has made it possible to discover efficient anti-cancer drugs
computational drug discovery approaches. Computational techniques such as computer-aided drug design have become an essential drug discovery tool and a keystone for novel drug development methods. In this review, we seek to provide an overview of computational drug discovery procedures comprising the target sites prediction, drug discovery based on structure and ligand-based design, quantitative structure-activity relationship (QSAR), molecular docking calculations, and molecular dynamics simulations with a focus on cancer therapeutics. The applications of artificial intelligence, databases, and computational tools in drug discovery procedures, as well as successfully computationally designed drugs, have been discussed to highlight the significance and recent trends in drug discovery against cancer. The current review describes the advanced computer-aided drug design methods that would be helpful in the designing of novel cancer therapies.
Aging is an unavoidable process, leading to cell senescence due to physiochemical changes in an organism. Anti-aging remedies have always been of great interest since ancient times. The purpose of ...anti-aging activities is to increase the life span and the quality of life. Anti-aging activities are primarily involved in the therapies of age-related disorders such as Parkinson's Disease (PD), Alzheimer's Disease (AD), cardiovascular diseases, cancer, and chronic obstructive pulmonary diseases. These diseases are triggered by multiple factors that are involved in numerous molecular pathways including telomere shortening, NF-κB pathway, adiponectin receptor pathway, insulin, and IGF signaling pathway, AMPK, mTOR, and mitochondria dysfunction. Natural products are known as effective molecules to delay the aging process through influencing metabolic pathways and thus ensure an extended lifespan. These natural compounds are being utilized in drug design and development through computational and high throughput techniques for effective pro-longevity drugs. A comprehensive study on natural compounds demonstrating their anti-aging activities along with databases of natural products for drug designing was executed and summarized in this review article.
Background: As the number of elderly persons increases, neurodegenerative diseases are
becoming ubiquitous. There is currently a great need for knowledge concerning management of oldage
...neurodegenerative diseases; the most important of which are: Alzheimer's disease, Parkinson's
disease, Amyotrophic Lateral Sclerosis, and Huntington’s disease.
Objective: To summarize the potential of computationally predicted molecules and targets against
neurodegenerative diseases.
Method: Review of literature published since 1997 against neurodegenerative diseases, utilizing as
keywords: in silico, Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis ALS,
and Huntington's disease was conducted.
Results and Conclusion: Due to the costs associated with experimentation and current ethical law,
performing experiments directly on living organisms has become much more difficult. In this scenario,
in silico techniques have been successful and have become powerful tools in the search to
cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3-
dimensional structures of target proteins through homology modeling 2) achieves stabilization
through molecular dynamics simulation, and 3) exploits molecular docking through large compound
libraries. Next generation sequencing is continually producing enormous amounts of raw
sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing
problems, these new tools and algorithms are required. This review elaborates precise in silico
tools and techniques for drug targets, active molecules, and molecular docking studies, together
with future prospects and challenges concerning possible breakthroughs in Alzheimer's, Parkinson's,
Amyotrophic Lateral Sclerosis, and Huntington's disease.
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