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41 articles for “protein modeling”
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Antimicrobial Peptides in Fiddler Crabs: Structural Analysis and Potential Applications
Abstract: Crustaceans represent the largest and most ecologically and economically significant group of marine and aquatic arthropods. Their biomass and critical role in ecosystems highlight their importance. Among crustaceans, decapods are frequently used as model organisms in studies of immune responses due to their significant commercial value and the need to mitigate disease outbreaks in shellfish aquaculture. Antimicrobial host-defense peptides (AMPs) are pivotal in metazoan immunity, especially for invertebrates lacking adaptive …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 26–32 Read article
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Insilico Structural Analysis and Homology Modeling of Crustin Protein from Fiddler Crab Species
Abstract: In terms of biomass and ecological or economic importance, the crustacea are the largest, most noticeable, and possibly, the most significance group of marine or aquatic arthropods. Because of their enormous commercial value and the necessity to prevent disease outbreaks in the shellfish aquaculture industry, decapods are the experimental animals of choice for practically all biological studies involving immune responses. Antimicrobial host-defense peptides (AMPs) are major components of metazoan immunity, …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article
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In Silico Identification of Therapeutic Agents for Dengue Virus by Molecular Docking
Abstract: The dengue virus causes serious health issues and a loss of quality of life. Dengue poses a yearly threat to half of the world’s population. The drugs that are based on allopathy are expensive and also exhibit toxic effects on tissues and biological activities. It is also generally accepted that most pharmacologically active drugs, including those derived from medicinal plants, are isolated from natural sources. The present study is directed …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 · pp. 01–14 Read article
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The Intersection of Bioinformatics and Cellular Function in Disease Modeling
Abstract: The integration of bioinformatics and cellular biology has revolutionized our understanding of disease mechanisms, offering unprecedented opportunities to model complex biological systems. Bioinformatics is an interdisciplinary field that merges biology, computer science, and statistics, offering advanced tools to analyze vast biological datasets. Cellular functions, including gene expression, protein interactions, and metabolic pathways, form the foundation of physiological and pathological states. Disruptions in these processes can result in diseases like cancer, …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Advancements in Drug Design Technology and Its Impact on COVID-19 Treatment
Abstract: The deadly coronavirus disease 19 (COVID-19) pandemic has recently spread, raising concerns about global health. The search for novel therapeutic compounds is made more necessary by the persistent problem of the absence of licensed medications or vaccinations. By saving money and time, computer-aided drug design has sped up the process of finding and developing new drugs. The structured-based and ligand-based drug discovery subcategories of computer-aided drug design (CADD) are the …
Published in International Journal of Virus Studies · Vol. 1, Issue 1, 2024 · pp. 1–15 Read article
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Development of a Machine Learning and Artificial Intelligence Based Model Aimed at Forecasting the Prognostic Impact of C-Reactive Protein in Myocarditis
Abstract: The specific role of inflammation markers in myocarditis remains uncertain. We investigated the diagnostic and prognostic significance of C-reactive protein (CRP) levels at the initial diagnosis among myocarditis patients. Our retrospective study enrolled patients clinically suspected (CS) or biopsy-proven (BP) with myocarditis, with available CRP data at diagnosis. We collected patient information, including clinical, laboratory, and imaging findings at diagnosis and follow-up visits. We utilized machine learning methods, specifically random …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 12–24 Read article
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Computer-aided Drug Design Method for Anti-hepatitis C Drug Design
Abstract: Hepatitis C is a disease caused by the hepatitis C virus and can cause serious liver damage. There is currently no vaccine for this disease and the number of infections continues to increase worldwide. Currently used antiviral drugs are interferon alfa-2a and ribavirin, but about half of patients do not respond to therapy. Therefore, new drugs that protect against hepatitis C need to be investigated. Computational drug methods have been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Rheumatoid Arthritis and Stem Cell Therapies Perspectives for It
Abstract: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by systemic inflammation, primarily affecting synovial joints, leading to joint destruction and systemic complications. The pathogenesis involves immune system dysregulation, autoantibody production, and enzymatic imbalances. Enzymes, including matrix metalloproteinases (MMPs), serine proteases, and kinases, play crucial roles in these processes. Their dysregulation contributes significantly to disease progression through the imbalance of pro-inflammatory cytokines, oxidative stress, and extracellular matrix (ECM) degradation. MMPs, …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 2, 2025 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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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Harnessing Biomass for Sustainable Insect Farming and Biotechnology: Ecological Roles, Industrial Applications, and Future Opportunities
Abstract: Biomass, derived from biological materials, such as plant residues, animal waste, and agricultural by-products, plays a pivotal role in ecological systems, including those involving insects. Insects interact with biomass at multiple levels, serving as decomposers, pollinators, and converters of organic matter into valuable resources. The integration of biomass into insect ecology and farming has garnered significant attention for its potential in sustainable agriculture, waste management, and biotechnology. This review highlights …
Published in International Journal of Insects · Vol. 2, Issue 1, 2025 · pp. 17–21 Read article
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Recent Developments in Structural Genomics: Uncovering Cellular Functions
Abstract: Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 30–35 Read article
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Exploration of 5-Hydroxybowdichione Flavonoids As Inhibitors of Dengue Virus Ns5 RNA-Dependent RNA Polymerase Using Molecular Docking Approach
Abstract: Objectives: Human lives are now seriously threatened by dengue fever, which is brought on by the dengue virus (DENV). Aedes aegypti mosquitoes, which reproduce in still water, are the primary vectors of the arboviral virus known as dengue. It is well-recognized that phytochemicals have a high potential to eliminate bacterial, viral, and fungal infections in people. Thus, it demonstrates its inhibitory effects on the dengue virus. This study identifies some …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 1, 2023 · pp. 1–16 Read article
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Digital Frontiers in Life Sciences: The Transformative Role of Computing in Modern Biology
Abstract: The integration of computers in the biological sciences has revolutionized research and experimentation, facilitating advancements in areas such as genomics, bioinformatics, systems biology, and ecological modeling. The ability to process vast amounts of biological data efficiently has transformed how scientists study complex biological systems and phenomena. Computational tools enable the analysis of DNA sequences, protein structures, metabolic pathways, and ecological dynamics, which were previously beyond the reach of traditional laboratory …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Arabidopsis thaliana. (L.) Heynh Multifunctional Sensor Proteins and Signaling Networks Plant Photoreceptors
Abstract: Light is a crucial environmental cue for the growth and development of plants as well as the production of photosynthetic energy. In order to recognize and process information from incoming light, plants employ sophisticated mechanisms. With the model plant Arabidopsis thaliana, five different types of photoreceptors have been found. (L.) Heynh Photoreceptors play a specialized and/or recurring role in fine-tuning many aspects of the plant's life cycle. Unlike mobile animals, …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 1, Issue 2, 2023 · pp. 08–24 Read article
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Extraction Properties of Mangifera indica Seed Kernels: A Comprehensive Analysis of Their Industrial Potential
Abstract: Mango (Mangifera indica) is widely regarded as one of the world's finest fruits, with a rich nutritional profile, including fiber, riboflavin, carotene, and ascorbic acid. Among its lesser-known components, the mango seed kernel offers significant nutritional and industrial value. Mango kernels are composed of protein, fat, carbohydrates, crude fiber, and ash, and contain bioactive compounds such as polyphenols, phytosterols, and tocopherols. The fat extracted from mango seed kernels has shown …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 22–28 Read article
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Polymer Composite-Integrated Food Waste Management Across the Supply Chain: Quantification, Process Modelling, and Techno-Economic Valorization
Abstract: Food waste produced throughout the global food supply chain constitutes one of the most impactful forms of inefficiency within the current food production system, producing roughly 931 million tons per year and resulting in economic losses above $1 trillion worldwide each year. One aspect that has not been sufficiently studied systematically is how polymer composite materials, such as membrane separation systems, polymer-coated extraction equipment, fiber-reinforced polymer (FRP) biorefinery infrastructure, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 819–836 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article