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208 articles for “target identification”
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Comprehensive Analysis of MRSA Peptides Via Maldi
Abstract: The present study employed Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry to analyze methicillin-resistant Staphylococcus aureus peptides, focusing on various parameters associated with mass-to-charge (m/z) values. Through systematic data collection and analysis, including time, intensity, signal-to-noise ratios, quality factors, resolutions, areas under the peaks, relative intensities, full widths at half maximum, Chi-squared values, and background peaks, comprehensive insights into the spectral characteristics of methicillin-resistant Staphylococcus aureus peptides were obtained. Methicillin-resistant Staphylococcus …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 98–101 Read article
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Precision Medicine for Neurofibromatosis Type 1: Progress and Prospects in Drug Discovery
Abstract: Objective: The development of neurofibromas, café-au-lait spots, and other neurological problems are the hallmarks of neurofibromatosis type 1 (NF1), a hereditary disorder. The dearth of efficacious pharmaceutical therapies underscores the need for novel therapeutic approaches, even in the face of clinical variability. Through very accurate prediction of the binding affinity of possible therapeutic drugs with the target protein, the computational technique known as “molecular docking” has become a potent tool …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 01–15 Read article
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Sentinels of Safety: A Robotic Revolution in Autonomous Landmine Detection for Humanitarian Resilience
Abstract: Landmine Detection Robotic Vehicle Project is to create an autonomous robotic system that can identify landmines in dangerous locations. The rover navigates through a variety of terrains by using modern sensor technology, such as metal detectors and infrared photography, to detect buried landmines. The rover can distinguish between potentially dangerous items and harmless ones. The principal aim of the project is to optimise the efficacy and security of landmine removal …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 28–34 Read article
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Microwave Signals: A New Frontier in Non-Invasive Medical Diagnostics: A Study
Abstract: Imagine a future where medical diagnoses are quicker, safer, and more accessible, and where therapies are more precise and less invasive. This future is rapidly approaching, driven in part by the quiet revolution of microwave signals in medicine. Far from their everyday use in ovens and communication, these non-ionizing electromagnetic waves are proving to be powerful tools, offering unprecedented insights into the human body and innovative ways to treat disease. …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 27–41 Read article
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AI and ML-Driven Immersive Technologies: A New Era in Education
Abstract: The very fast adoption of Artificial Intelligence (AI) and Machine Learning (ML) in education has transformed contemporary teaching and learning ecosystems driven by advances in immersive technologies and the growing engagement of global technology leaders with virtual environments. AI-powered educational platforms enable adaptive and personalized learning pathways by dynamically adjusting content, pace and instructional strategies to learners’ preferences, abilities and learning styles by improving engagement, retention and academic outcomes. Deep …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 116–123 Read article
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Current Drugs Target the EGFR
Abstract: Cancer is a devastating disease, but there have recently been significant advancements in therapy that have identified EGFR and its related proteins as valuable indicators and targets for treatment. The ERBB receptor tyrosine kinase superfamily includes EGFR, which is a transmembrane glycoprotein. When the EGFR receptor interacts to its particular ligand, EGF, it causes tyrosine residues to be phosphorylated and forms receptor dimers with other members of the receptor family. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 1–8 Read article
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Targeting Vasopressin 2 Receptor (V2R) in Renal Cystogenesis by Exploring the Nephroprotective Potential of “Terminalia arjuna”
Abstract: Objectives: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder, leading to the formation of multiple cysts in the kidneys. It is a major cause of end-stage renal disease (ESRD), which often requires dialysis or a kidney transplant for survival. This research focuses on identifying potential bioactive compounds derived from natural sources that show promise for drug development targeting the V2R gene. Methods: The naturally occurred …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 14–24 Read article
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Molecular Docking and Interaction of Anthocyanin Derivatives in Regulating Hippo-taz Pathway for Renal Injuries
Abstract: Introduction: The Hippo pathway plays a pivotal role in renal disease, with Yes-associated protein (YAP) exhibiting promise for combined treatments. The crucial evaluation of YAP-targeted drug safety and efficacy through preclinical studies is imperative. Additionally, α-SMA and SMAD3 emerge as potential therapeutic targets in renal fibrosis, driving ongoing research toward innovative interventions. Materials and Methods: In the systematic identification of therapeutic secondary metabolites, Anthocyanin derivatives were methodically retrieved from the …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 1, 2024 · pp. 23–38 Read article
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In Silico Assessment of Demethoxycurcumin: Molecular Docking and Computational Insights into its various therapeutic Potential
Abstract: Natural compounds are increasingly explored for their therapeutic potential in medical research. Here, we focused on demethoxycurcumin (DMC), a polyphenolic bioactive compound extracted from Curcuma longa, commonly found in turmeric. DMC, with a chemical formula of C20H18O5 and a molecular weight of 340 g/mol, possesses two aromatic ring systems, each featuring a β-diketone moiety connected by a seven-carbon chain. This unique structure allows DMC to engage in tautomerism, which is …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 1, 2024 · pp. 9–15 Read article
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Advancing Brain Tumor MRI Segmentation
Abstract: Segmentation of brain tumors in MRI scans is an integral part of neuroimaging carried out for diagnostic and therapeutic interventions. Given that manual segmentation is cumbersome and highly variable, there arises a need for automated, more precise segmentation solutions. This project, ‘Machine Learning and Deep Neural Networks to Advance Brain Tumor MRI Segmentation’ will develop a better, efficient, and accurate segmentation model to help clinicians identify brain tumors with greater …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 28–33 Read article
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Computational Identification of Antigenic Proteins and Epitopes in Hantavirus sp. for Drug Repurposing
Abstract: Hantavirus is an emerging virus that spreads from animals to humans and can cause serious illnesses like hantavirus pulmonary syndrome (HPS) and hemorrhagic fever with renal syndrome (HFRS). there are no FDA-approved treatments available for these diseases. This study explores in-silico drug repurposing as a strategy to identify potential therapeutic candidates. The physicochemical, secondary structure, antigenicity, and post-translational modification analysis of hantavirus proteins – specifically the glycoprotein precursor, N protein, …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 20–26 Read article
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Computational Biomodeling: Transforming Drug Design with Advanced Simulations
Abstract: Computational biomodeling has emerged as a transformative approach in the field of drug discovery, significantly enhancing the efficiency and precision of identifying and optimizing potential drug candidates. This article explores the various computational techniques utilized in drug design, including molecular docking, molecular dynamics (MD) simulations, free energy calculations, and virtual screening, and examines how these methods collectively contribute to the drug development process. The integration of these advanced simulations allows …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 24–29 Read article
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Molecular Docking Evaluation of Cedrus deodara Secondary Metabolites as a Potent Anti-ovarian Cancer Agent
Abstract: Objective: According to the statistics for the year 2022 it was seen that cancer total cases is 14,61,427. After breast cancer, ovarian cancer is the second most frequent cancer among women. The estrogen receptor (PDB ID: 1X7E), progesterone receptor (PDB ID: 1A28), and Phosphoinositide 3-kinases (PDB ID: 4FJY) can be considered as target protein for ovarian cancer. The plant Cedrus deodara and its phytochemicals were chosen in this study to …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 77–93 Read article
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Molecular Docking Study: Targeting mycobacterium leprae ML2640 Protein Using Active Compounds from Coscinium fenestratum
Abstract: Objectives: Leprosy is an infectious disease in skin, peripheral nerve and mucosa of upper airway. Around 70% of this infection is caused by Mycobacterium leprae, which was discovered during1873. Multi drug therapy is used for the treatment, still multiple drug resistance and reactions has been reported among patients. Hence, this work focused on identifying bioactive compounds from Coscinium fenestratum that can target mycobacterium leprae ML2640 protein by in-silico approach. Method: …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 21–33 Read article
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Identification of Hub Genes and Enriched Gene Ontology & Pathways in Idiopathic Pulmonary Fibrosis Through Bioinformatics Approaches
Abstract: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease marked by aberrant remodeling of lung tissue and excessive extracellular matrix deposition, ultimately leading to respiratory failure. Despite ongoing research, the molecular mechanisms underlying IPF remain incompletely understood. This research aims to uncover differentially expressed genes (DEGs) and related biological pathways through an integrated analysis of microarray data. Two publicly available datasets, GSE110147 and GSE53845, were obtained from the Gene …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 1–13 Read article
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Screening Phytocompounds of Tinospora cordifolia to Find Potential Drug Targets for Cystic Fibrosis
Abstract: This study aimed to evaluate the therapeutic potential of phytocompounds derived from Tinospora cordifolia in treating cystic fibrosis (CF), a genetic disorder caused by mutations in the CFTR gene that lead to severe respiratory and digestive complications. Phytocompounds were retrieved from the IMPPAT database and subjected to molecular docking simulations using PyRx to assess their binding affinity to the CFTR protein. The top-scoring compounds – sterol, magnoflorine, tembetarine, kaempferol, and …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 16–24 Read article
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Exploring Potential Phytochemicals for Myasthenia Gravis Treatment: A Molecular Docking and ADME Analysis Approach
Abstract: Objective: Muscle feebleness and exhaustion derived from a disruption in neuromuscular transference are hallmarks of the crippling autoimmune disease myasthenia gravis (MG). The drawbacks of the current MG therapy options are frequently partial efficacy and adverse effects. To investigate the potential of phytochemicals in MG control, in this work we integrated molecular docking with ADME (absorption, distribution, metabolism, and excretion) analysis using a computer method. We identified molecules exhibiting favorable …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 1–13 Read article
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A Critique of Advanced Instrumentation for Supervising and Regulating Renewable Energy Systems
Abstract: The integration of renewable strength property into the power grid necessitates modern-day tracking and manipulate systems to ensure highest best average overall performance, reliability, and performance. This paper offers a comprehensive analysis of advanced instrumentation applied for monitoring and controlling renewable strength systems. Beginning with an outline of renewable energy assets and their importance in addressing environmental worries and electricity sustainability, the compare delves into the challenges inherent in monitoring …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–12 Read article
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Clone-Specific Drug Delivery Systems: Targeted Approaches and Future Clinical Applications
Abstract: Clone-specific drug delivery systems represent a transformative frontier in personalized medicine, addressing the longstanding challenge of clonal heterogeneity within diseases such as cancer, infectious diseases, and autoimmune disorders. Traditional drug delivery platforms often fail to discriminate between pathogenic and healthy cells, leading to systemic toxicity and reduced therapeutic efficacy. In contrast, clone-specific systems aim to selectively target and eliminate disease-driving cellular clones based on unique molecular signatures, thereby improving treatment …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 21–29 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article