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80 articles for “drug target identification”
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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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Pathways in Drug Discovery and Development: From Molecular Targets to Market Approval
Abstract: A complicated, multidisciplinary, and resource-intensive process, the discovery and development of new pharmacological drugs is essential to the advancement of contemporary medicine. Finding and optimising lead chemicals comes after a disease-relevant biological target has been identified and validated. Through preclinical research in animal models, these leads are thoroughly assessed for toxicity, pharmacokinetics, safety, and efficacy. Clinical trials, which are carried out in several stages to evaluate safety, efficacy, ideal dosage, …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 1, 2026 · pp. 01–04 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Analysis of Bioinformatics Software Applied in Computer-Aided Drug Design
Abstract: The integration of bioinformatic tools with computational methods has revolutionized the field of Computer-aided Drug Design (CADD), enabling researchers to expedite the discovery and optimization of new therapeutics. This review provides an in-depth analysis of the bioinformatic tools utilized in CADD, encompassing molecular docking, molecular dynamics simulation, virtual screening, homology modelling, and molecular visualization. We go over the tenets, approaches, and uses of these instruments, emphasizing their value in expediting …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Introduction to Biological Networks and their Contributions to Systems Biology
Abstract: Biological networks provide a conceptual framework to represent and analyze the intricate interconnections among the numerous components that make up living systems. This review paper elucidates the foundational principles of networks and their diverse applications in systems biology, highlighting their crucial role in understanding the inherent complexity of biological processes. Utilizing graph theory, these networks represent entities like genes, proteins, and metabolites as nodes, with their interactions depicted as edges. …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 53–70 Read article
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Integrating Network Pharmacology and Molecular Docking to Assess Rutin’s Pharmacological Properties
Abstract: Objectives: In the present research, the network pharmacology process was applied to determine the underlying mechanism of the pharmacological properties of Rutin. Network pharmacology was utilized to reveal the interactions between medications and the targets of illnesses, and it is capable of completely articulating the complexity between diseases and medications. The identification of diverse drug-target interactions using network pharmacology may be utilized to discover novel medications for difficult conditions like …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 20–33 Read article
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Ligand Based Drug Virtual Screening in Computer Aided Drug Design: A Review
Abstract: Computer-Aided Drug Design (CADD) has revolutionized the drug discovery process by providing efficient and cost-effective methods for identifying potential drug candidates. Within CADD, ligandbased virtual screening techniques play a pivotal role in the early stages of drug discovery. This review provides a comprehensive overview of ligand-based drug virtual screening, focusing on its principles, applications, challenges, and future directions. Fundamentals of ligand-based virtual screening, including pharmacophore-based methods, similarity searching, and machine …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Computational Exploration of Bhrijraj-derived Phytochemicals as Potential Anti-inflammatory Agents: A Molecular Docking Study with Cyclooxygenase-II Complex
Abstract: The molecular docking analysis was meticulously conducted using state-of-the-art computational tools, notably Chimera and Python. These tools were employed to unravel the complex interactions between the identified phytochemicals from Bhrijraj and the target protein, COX-II. The 3D structures of the phytochemicals were prepared with precision using ChemSketch, ensuring accuracy in the subsequent molecular docking simulations. This rigorous approach enhances the reliability and validity of the findings. This research aims to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 31–37 Read article
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Application of Artificial Intelligence in Drug Discovery
Abstract: The application of artificial intelligence (AI) in medicine, especially through machine learning (ML), is revolutionizing new-age drug discovery research. AI is found as an efficient and powerful tool to narrow the gap between disease detection and developing and identifying potential therapeutic agents for a cure. This review provides a summary of the latest developments in AI and its potential application in drug discovery for untreatable diseases. The review also examines …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
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An Extensive Analysis of Computer-Aided Drug Design for Novel Psychotropic and Neurological Substances
Abstract: A comprehensive review of the use of computer-aided drug design (CADD) in the creation of innovative neurologic and neuropsychiatric medications is given in this article. It discusses the challenges in traditional drug discovery approaches and highlights the role of computational methods in accelerating the identification and optimization of drug candidates targeting psychiatric and neurological disorders. The method of finding new drugs has been completely transformed by Computer-Aided Drug Design (CADD), …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 19–27 Read article
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Biomarkers in Cancer Research: Discovery and Future Directions
Abstract: Biomarkers have transformed the study of cancer, providing critical information regarding prognosis and therapy response and promoting earlier diagnosis. This paper discusses the different parts of cancer biomarkers, starting with their description, classification, and major types, which are the groundwork for understanding their clinical role. The discussion on the development and validation process of biomarkers is then undertaken, focusing on state-of-the-art techniques and the importance of ensuring accuracy and reproducibility. …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 22–26 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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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 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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Repurposing Approved Immunomodulatory Drugs for Target Proteins in the Pancreas of European eel: A Molecular Docking Approach
Abstract: Leishmaniasis is a disease caused by tiny parasites called Leishmania, which spread to humans through the bite of an infected female sand fly. The disease manifests in three different forms, and the protein calcitonin promotes the disease’s spread. By reducing blood calcium levels, inhibiting osteoclast activity, increasing calcium excretion, and possibly playing a role in neurotransmitter modulation, calcitonin, a hormone released by vertebrates, promotes the progression of pathogenesis and lessens …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 12–19 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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Zebrafish in Drug Research: Decoding Biological Mechanisms and Finding Novel Therapeutic Targets
Abstract: The zebrafish, scientifically known as Danio rerio, is a powerful model organism in biological research because of its favorable traits, which include rapid development, genetic tractability, and transparent embryos. Zebrafish were first identified for their use in studies of vertebrate development, but they have since spread to a variety of disciplines, such as pharmacology, clinical research as a disease model, and most notably, drug development. Zebrafish have emerged as a …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 · pp. 1–8 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