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14 articles for “Docking score”
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Grid based docking study of some 2-(4-methylsulfonyl phenyl) pyrimidine derivatives (designed after QSAR studies) with Cyclooxygenase
Abstract: Molecular docking helps in studying drug/ligand or receptor/ protein interactions by identifying the suitable active sites in protein, obtaining the best geometry of ligand-receptor complex and calculating the energy of interaction for different ligands to design more effective ligands. In Grid based docking, after unique conformers of the ligand are generated, the receptor cavity of interest is chosen and a grid is generated around the cavity. Cavity points are found …
Published in International Journal of Antibiotics · Vol. 1, Issue 1, 2024 · pp. 23–41 Read article
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Unveiling Nature’s Potential: In Silico Exploration and Identification of Herbal Remedies for Major Depressive Disorder Through Molecular Interaction Studies
Abstract: Major depressive disorder (MDD), a globally discussed mental health condition, has drawn significant attention because of its unique and intricate nature. This is marked by the enduring presence of negative emotions stemming from a lack of interest, diminished self-esteem, and excessive rumination. Despite the widespread availability of various antidepressant medications, their effectiveness is hindered by low response rates, prolonged treatment durations, and the prevalence of side effects, such as headaches, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 54–62 Read article
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Pharmacophore mapping, 3D QSAR, docking, and ADME prediction studies of novel Benzothiazinone derivatives
Abstract: Background Tuberculosis is a major public health concern worldwide which is caused by Mycobacterium tuberculosis. DprE1 (Decaprenyl Phosphoryl Ribose 2’- Epimerase) is the most challenging target for development of novel anti- tubercular agents because it is a small protein and located into cytoplasmic membrane. So, novel anti-TB drugs did not bound effectively with it. DprE1 catalyzes the oxidation of the 2’ hydroxyl group of DPR (Decaprenyl Phosphoryl D- Ribose) …
Published in International Journal of Antibiotics · Vol. 1, Issue 1, 2024 · pp. 59–82 Read article
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Drug Repurposing of Anticancer Agents JP-8g and REDX05358 Against the Target Protein Plectin 1a in Epidemolysis Bullosa Simplex with Muscular Dystrophy (EBS-MD)
Abstract: Epidermolysis Bullosa Simplex with Muscle Dystrophy is a genetic disease affecting the skin and muscles which can be seen at birth or start at adulthood due to the mutation in the protein Plectin 1a (PLEC gene) causing skin blisters and muscle weakness. This protein is seen in sarcolemma, Z disks in skeletal muscles, hemidesmosomes in skin and cardiac muscles giving stability to cytoskeleton, playing a crucial role in neuromuscular transmission …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 · pp. 22–34 Read article
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Screening of Newer Phytoconstituents on Novel Enzymes for their Biological Activity
Abstract: Background: Hyperlipidemia and gout are prevalent metabolic disorders significantly impacting global health. The xanthine oxidase and HMG-CoA reductase pathways play pivotal roles in the pathophysiology of these conditions. This study explores the potential of natural phytoconstituents—daidzein, resveratrol, and genistein—as dual inhibitors for these enzymatic targets, offering insights into innovative therapeutic strategies. Aim: To evaluate the potential of natural phytoconstituents—daidzein, resveratrol, and genistein—as dual inhibitors of xanthine oxidase and HMG-CoA reductase …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 81–86 Read article
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In-silico Approach of Few Selected Phytoconstituents on Newer Cancer Targets
Abstract: Background: Cancer’s high death rates are mainly due to, drug resistance and unmet medical demands. It necessitates novel anticancer medications. AI tools aid in efficient and faster drug discovery by analyzing data, modeling processes and optimizing pipeline stages. Aim: The aim of this present study is to evaluate phytoconstituents against novel and newer cancer targets. Methodology: The ligands Daidzein, Resveratrol and Genistein were targeted against the Glutamate dehydrogenase (PDB ID …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 12–17 Read article
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Molecular Docking, QSAR Modeling, and ADMET Evaluation of Novel Pyrazolo-Pyrimidine Derivatives as Potential CDK-2 Inhibitors for Cancer Therapy
Abstract: Cyclin-dependent kinase-2 (CDK-2) is an essential regulator in cell cycle progression and is an important therapeutic target in cancer drug development. In the present study, an integrated computational approach involving molecular docking studies, QSAR modeling, ADMET prediction, and artificial intelligence-based analysis was used to identify pyrazolo-pyrimidine derivatives as potential CDK-2 inhibitors. Based on the molecular docking results, it was found that selected compounds exhibited high binding affinity towards the ATP …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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Effectiveness of Temporins for the Treatment of HPV Infections
Abstract: Objectives: Human papillomavirus (HPV), especially high-risk variants like type-16 have been linked to the formation of malignant tumors. HPV-16 has been implicated in most cases of cervical cancer in women. This study aims to assess the effectiveness of three types of temporin molecules, i.e., antiviral peptides secreted by certain frog species, for the inhibition of the viral L1 protein. Methods: In the present study, various computational tools were used to …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 1, 2024 · pp. 41–53 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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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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Targeting PTPN22 in Arthritis: Molecular Docking and Pharmacokinetic Evaluation of Artemisia vestita Compounds
Abstract: Rheumatoid arthritis (RA) is a long-term autoimmune condition characterized by inflammation of the synovial membrane, commonly resulting in swelling, pain, stiffness, and overall fatigue. Protein tyrosine phosphatase non-receptor type 22 (PTPN22) has been identified as a risk factor linked to various autoimmune diseases, including RA. In the PTPN22 gene, two missense Single nucleotide polymorphisms (SNPs) are associated with autoimmune conditions. The R620W (C1858T, rs247660) variant in exon 14 has been …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 20–31 Read article
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Identification of Promising Lead Compounds from Capsicum annuum Targeting BACE-1 for Alzheimer’s Disease Therapy: A Molecular Docking Study
Abstract: Background: Alzheimer's disease (AD) is a neurodegenerative disorder affecting millions of people worldwide. Beta-secretase 1 (BACE-1) is an important therapeutic target for AD treatment. Capsicum annuum (CA) is a commonly consumed plant with potential neuroprotective properties. In this study, we aimed to identify potential lead compounds from CA that can target BACE-1 for AD therapy using molecular docking. Methods: A library of 15 compounds from CA was obtained from PubChem, …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 1, 2023 · pp. 40–49 Read article
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Investigating The Alkalizing Potential of Chandanasava For Restoring Acid-Base Homeostasis in Renal Tubular Acidosis: A Computational and In Silico Pharmacological Study
Abstract: Chandanasava, a traditional Ayurvedic formulation, is recognized for its potential alkalizing properties, which may help restore acid-base homeostasis in conditions such as renal tubular acidosis (RTA). This study aims to investigate the active components of Chandanasava and their interactions with key renal target proteins, Pendrin and Carbonic Anhydrase II, which are essential for maintaining acid-base balance. An in silico approach was utilized to explore the pharmacological potential of the phytochemicals …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 28–52 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