AIMC Topic: Drug Design
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Exploring the role of density functional theory in the design of gold nanoparticles for targeted drug delivery: a systematic review.
Journal of molecular modeling
Jun 10, 2025
CONTEXT: Targeted drug delivery systems leveraging gold nanoparticles (AuNPs) demand precise atomic-level design to overcome current limitations in drug-loading efficiency and controlled release. Unlike previous focused reviews, this systematic analy...
Improving Covalent and Noncovalent Molecule Generation via Reinforcement Learning with Functional Fragments.
Journal of chemical information and modeling
Jun 5, 2025
Small-molecule drugs play a critical role in cancer therapy by selectively targeting key signaling pathways that drive tumor growth. While deep learning models have advanced drug discovery, there remains a lack of generative frameworks for covalent ...
Molecular Optimization Based on a Monte Carlo Tree Search and Multiobjective Genetic Algorithm.
Journal of chemical information and modeling
Jun 2, 2025
In the realm of medicinal chemistry, the predominant challenge in molecular design lies in managing extensive molecular data sets and effectively screening for, as well as preserving, molecules with potential value. Traditional methodologies typicall...
AMPGen: an evolutionary information-reserved and diffusion-driven generative model for de novo design of antimicrobial peptides.
Communications biology
May 30, 2025
The rapid advancement of artificial intelligence (AI) has enabled de novo design of functional proteins, circumventing the reliance on natural templates or sequencing databases. However, current protein design models are ineffective in generating pro...
Role of artificial intelligence in cancer drug discovery and development.
Cancer letters
May 23, 2025
The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform the traditionally time-consuming and expensive processes involved in bringing new therapies to mark...
Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.
Nature communications
May 23, 2025
Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appears limited. In this study, we use several artificial intelligence techniques and patient-based mult...
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...
Applying computational protein design to therapeutic antibody discovery - current state and perspectives.
Frontiers in immunology
May 22, 2025
Machine learning applications in protein sciences have ushered in a new era for designing molecules in silico. Antibodies, which currently form the largest group of biologics in clinical use, stand to benefit greatly from this shift. Despite the prol...
Cyclic peptide structure prediction and design using AlphaFold2.
Nature communications
May 21, 2025
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here...
Effective and Explainable Molecular Property Prediction by Chain-of-Thought Enabled Large Language Models and Multi-Modal Molecular Information Fusion.
Journal of chemical information and modeling
May 20, 2025
Molecular property prediction (MPP) plays a critical role in drug design and discovery. Due to the multimodal nature of molecular data (e.g., 1D SMILES strings and 2D molecular graphs), multimodal information fusion can generally achieve better perfo...
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