AIMC Topic: Structure-Activity Relationship
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Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.
Drug design, development and therapy
Jun 14, 2025
OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the disease progression or reduce its harmful effects, and exhibit toxicity and side effects such as ga...
Discovery of CYP1A1 Inhibitors for Host-Directed Therapy against Sepsis.
Journal of medicinal chemistry
May 29, 2025
Bacterial sepsis remains a leading cause of death globally, exacerbated by the rise of multidrug resistance (MDR). Host-directed therapy (HDT) has emerged as a promising nonantibiotic approach to combat infections; thus, multiple HDT targets have bee...
Design, synthesis, and evaluation of triazolo[1,5-a]pyridines as novel and potent α‑glucosidase inhibitors.
Scientific reports
May 22, 2025
α-Glucosidase is a key enzyme responsible for controlling the blood glucose, making a pivotal target in the treatment of type 2 diabetes mellitus. Present work introducestriazolo[1,5-a]pyridine as a novel, potent scaffold for α-glucosidase inhibition...
Identification of nanoparticle infiltration in human breast milk: Chemical profiles and trajectory pathways.
Proceedings of the National Academy of Sciences of the United States of America
May 12, 2025
Breast milk is crucial for infant health, offering essential nutrients and immune protection. However, despite increasing exposure risks from nanoparticles (NPs), their potential infiltration into human breast milk remains poorly understood. This stu...
A new computational cross-structure-activity relationship (C-SAR) approach applies to a selective HDAC6 inhibitor dataset for accelerated structure development.
Computers in biology and medicine
Apr 30, 2025
Several structure-activity relationship (SAR) methodologies have been developed for the research community to improve the potential activity of prototype structures. To accomplish this, Topliss proposed the Topliss tree and the Topliss Batchwise sche...
Design and Synthesis of Magnolol Derivatives Using Integrated CNNs and Pharmacophore Approaches for Enhanced Parasiticidal Activity in Aquaculture.
Journal of agricultural and food chemistry
Apr 16, 2025
Aquaculture is a rapidly growing sector of global food production, playing a vital role in poverty alleviation, food security, and income generation. However, it faces substantial challenges, particularly due to infections caused by the protozoan , l...
Exploring 4 generation EGFR inhibitors: A review of clinical outcomes and structural binding insights.
European journal of pharmacology
Apr 9, 2025
Epidermal growth factor receptor (EGFR) is a potential target for anticancer therapies and plays a crucial role in cell growth, survival, and metastasis. EGFR gene mutations trigger aberrant signaling, leading to non-small cell lung cancer (NSCLC). T...
A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.
European journal of medicinal chemistry
Apr 5, 2025
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituent optimization, a process that is often both time-consuming and expensive. To address this challenge...
Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.
Bioorganic chemistry
Mar 26, 2025
Focal adhesion kinase (FAK) is a critical drug target implicated in various disease pathways, including hematological malignancies and breast cancer. Therefore, identifying FAK inhibitors with novel scaffolds could offer new opportunities for develop...
Humans
Drug Discovery
Antineoplastic Agents
Cell Proliferation
Dose-Response Relationship, Drug
Female
Breast Neoplasms
Molecular Docking Simulation
Focal Adhesion Kinase 1
Focal Adhesion Protein-Tyrosine Kinases
Molecular Dynamics Simulation
Drug Evaluation, Preclinical
Protein Kinase Inhibitors
Drug Screening Assays, Antitumor
Structure-Activity Relationship
Molecular Structure
Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques.
Experimental biology and medicine (Maywood, N.J.)
Mar 19, 2025
Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overd...
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