AIMC Topic: Drug Design

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Integration of 3D-QSAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors.

Computational biology and chemistry Oct 10, 2024
Selective inhibitors of sirtuin-2 (SIRT2) are increasingly recognized as potential therapeutics for cancer and neurodegenerative diseases. Derivatives of 5-((3-amidobenzyl)oxy)nicotinamides have been identified as some of the most potent and selectiv...
Molecular Structure Machine Learning Enzyme Inhibitors Molecular Docking Simulation Humans Quantitative Structure-Activity Relationship Sirtuin 2 Drug Design Niacinamide
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High-throughput and computational techniques for aptamer design.

Expert opinion on drug discovery Oct 10, 2024
INTRODUCTION: Aptamers refer to short ssDNA/RNA sequences that target small molecules, proteins, or cells. Aptamers have significantly advanced diagnostic applications, including biosensors for detecting specific biomarkers, state-of-the-art imaging,...
Molecular Docking Simulation Drug Design Aptamers, Nucleotide Biosensing Techniques Computational Biology Humans Machine Learning High-Throughput Screening Assays SELEX Aptamer Technique Molecular Dynamics Simulation
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Deciphering Cathepsin K inhibitors: a combined QSAR, docking and MD simulation based machine learning approaches for drug design.

SAR and QSAR in environmental research Oct 9, 2024
Cathepsin K (CatK), a lysosomal cysteine protease, contributes to skeletal abnormalities, heart diseases, lung inflammation, and central nervous system and immune disorders. Currently, CatK inhibitors are associated with severe adverse effects, there...
Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Drug Design Cathepsin K
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AI-driven antibody design with generative diffusion models: current insights and future directions.

Acta pharmacologica Sinica Sep 30, 2024
Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specificity and binding affinity. Despite their potential, optimizing antibodies for superior efficacy presents significant challenges in both monetary and t...
Antibodies Complementarity Determining Regions Artificial Intelligence Animals Drug Design Humans
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Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.

Molecules (Basel, Switzerland) Sep 29, 2024
The field of computational protein engineering has been transformed by recent advancements in machine learning, artificial intelligence, and molecular modeling, enabling the design of proteins with unprecedented precision and functionality. Computati...
Proteins Models, Molecular Protein Engineering Drug Design Computational Biology Humans Artificial Intelligence Machine Learning
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Integrative residue-intuitive machine learning and MD Approach to Unveil Allosteric Site and Mechanism for β2AR.

Nature communications Sep 16, 2024
Allosteric drugs offer a new avenue for modern drug design. However, the identification of cryptic allosteric sites presents a formidable challenge. Following the allostery nature of residue-driven conformation transition, we propose a state-of-the-a...
Allosteric Regulation Receptors, Adrenergic, beta-2 Allosteric Site Molecular Dynamics Simulation Protein Conformation Machine Learning Drug Design Humans
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Automated design of multi-target ligands by generative deep learning.

Nature communications Sep 11, 2024
Generative deep learning models enable data-driven de novo design of molecules with tailored features. Chemical language models (CLM) trained on string representations of molecules such as SMILES have been successfully employed to design new chemical...
Ligands Polypharmacology Proteins Models, Chemical Humans Drug Discovery Deep Learning Drug Design
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Toward the Integration of Machine Learning and Molecular Modeling for Designing Drug Delivery Nanocarriers.

Advanced materials (Deerfield Beach, Fla.) Sep 10, 2024
The pioneering work on liposomes in the 1960s and subsequent research in controlled drug release systems significantly advances the development of nanocarriers (NCs) for drug delivery. This field is evolved to include a diverse array of nanocarriers ...
Humans Drug Design Nanoparticles Drug Carriers Machine Learning Drug Delivery Systems Models, Molecular
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From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 29, 2024
Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-based drug design. Despite recent advances in data-driven methods for affinity prediction, their accuracy is still limited, partially because they only ta...
Molecular Dynamics Simulation Protein Binding HSP90 Heat-Shock Proteins Drug Design Proteins Ligands Thermodynamics Deep Learning
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SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability.

Journal of chemical information and modeling Aug 23, 2024
Artificial intelligence (AI) has emerged as a pivotal force in enhancing productivity across various sectors, with its impact being profoundly felt within the pharmaceutical and biotechnology domains. Despite AI's rapid adoption, its integration into...
Drug Design Drug Discovery Deep Learning Anti-HIV Agents Humans Artificial Intelligence Quantum Theory Molecular Docking Simulation
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