AIMC Topic: Molecular Structure
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Computational approaches for lead compound discovery in dipeptidyl peptidase-4 inhibition using machine learning and molecular dynamics techniques.
Computational biology and chemistry
Jul 10, 2024
The prediction of possible lead compounds from already-known drugs that may present DPP-4 inhibition activity imply a advantage in the drug development in terms of time and cost to find alternative medicines for the treatment of Type 2 Diabetes Melli...
Synthesis, Docking, and Machine Learning Studies of Some Novel Quinolinesulfonamides-Triazole Hybrids with Anticancer Activity.
Molecules (Basel, Switzerland)
Jul 2, 2024
In the presented work, a series of 22 hybrids of 8-quinolinesulfonamide and 1,4-disubstituted triazole with antiproliferative activity were designed and synthesised. The title compounds were designed using molecular modelling techniques. For this pur...
PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.
European journal of medicinal chemistry
Jun 25, 2024
Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial in...
From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.
ChemMedChem
Jun 20, 2024
Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effe...
Humans
Molecular Docking Simulation
Drug Discovery
Cell Proliferation
Dose-Response Relationship, Drug
Drug Screening Assays, Antitumor
Antineoplastic Agents
Deep Learning
Cell Line, Tumor
Protein Kinase Inhibitors
Structure-Activity Relationship
Molecular Structure
Vascular Endothelial Growth Factor Receptor-2
Synthetically Feasible De Novo Molecular Design of Leads Based on a Reinforcement Learning Model: AI-Assisted Discovery of an Anti-IBD Lead Targeting CXCR4.
Journal of medicinal chemistry
Jun 12, 2024
Artificial intelligence (AI) de novo molecular generation provides leads with novel structures for drug discovery. However, the target affinity and synthesizability of the generated molecules present critical challenges for the successful application...
Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute-Lipid Interactions.
Molecular pharmaceutics
May 23, 2024
This study explores the research area of drug solubility in lipid excipients, an area persistently complex despite recent advancements in understanding and predicting solubility based on molecular structure. To this end, this research investigated no...
Geometric deep learning methods and applications in 3D structure-based drug design.
Drug discovery today
May 16, 2024
3D structure-based drug design (SBDD) is considered a challenging and rational way for innovative drug discovery. Geometric deep learning is a promising approach that solves the accurate model training of 3D SBDD through building neural network model...
Protocol for creating representations of molecular structures using a polymer-specific decoder.
STAR protocols
May 2, 2024
To supply chemical structures of polymers for machine learning applications, decoding is necessary. Here, we present a protocol for generating polymer fingerprints (PFPs), which are representations of molecular structures, using a polymer-specific de...
Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design.
Journal of computer-aided molecular design
May 1, 2024
Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays...
Artificial Intelligence-Assisted Optimization of Antipigmentation Tyrosinase Inhibitors: Molecular Generation Based on a Low Activity Lead Compound.
Journal of medicinal chemistry
Apr 23, 2024
Artificial intelligence (AI) molecular generation is a highly promising strategy in the drug discovery, with deep reinforcement learning (RL) models emerging as powerful tools. This study introduces a fragment-by-fragment growth RL forward molecular...
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