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The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery

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Privacy-by-Design with Federated Learning will drive future Rare Disease Research

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Leveraging artificial intelligence and machine learning in kinase inhibitor development: advances, challenges, and future prospects

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Latest advances in aging research and drug discovery

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Deep Learning Applied to Ligand-Based De Novo Drug Design

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D3AI-CoV: a deep learning platform for predicting drug targets and for virtual screening against COVID-19

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MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules

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Medical IoT Record Security and Blockchain: Systematic Review of Milieu, Milestones, and Momentum

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Collagen remodeling-mediated signaling pathways and their impact on tumor therapy

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Token-Mol 1.0: tokenized drug design with large language models

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The application of artificial intelligence in lung cancer: a narrative review

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Insilico generation of novel ligands for the inhibition of SARS-CoV-2 main protease (3CLpro) using deep learning

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Recent Trends in Computer-aided Drug Design for Anti-cancer Drug Discovery

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AI-Driven Decision-Making Applications in Pharmaceutical Sciences

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Artifical intelligence: a virtual chemist for natural product drug discovery

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Revolutionizing adjuvant development: harnessing AI for next-generation cancer vaccines

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Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs

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New Ground in Antifungal Discovery and Therapy for Invasive Fungal Infections: Innovations, Challenges, and Future Directions

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Deep learning and generative artificial intelligence in aging research and healthy longevity medicine

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Identification of nanomolar adenosine A2A receptor ligands using reinforcement learning and structure-based drug design

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Digital Alchemy: The Rise of Machine and Deep Learning in Small-Molecule Drug Discovery

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Optimizing drug design by merging generative AI with a physics-based active learning framework

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FragNet, a Contrastive Learning-Based Transformer Model for Clustering, Interpreting, Visualizing, and Navigating Chemical Space

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Artificial Intelligence–Enabled De Novo Design of Novel Compounds that Are Synthesizable

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Using deep neural networks to explore chemical space

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Perplexity-Based Molecule Ranking and Bias Estimation of Chemical Language Models

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Few-shot deep learning for AFM force curve characterization of single-molecule interactions

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Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches

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The impact of AI on modern oncology from early detection to personalized cancer treatment

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Deregulation of Chromosome Segregation and Cancer

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Noise Robustness and Experimental Demonstration of a Quantum Generative Adversarial Network for Continuous Distributions

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Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model

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Retro Drug Design: From Target Properties to Molecular Structures

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A Review of Deep Learning-Based Approaches for Detection and Diagnosis of Diverse Classes of Drugs

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pBRICS: A Novel Fragmentation Method for Explainable Property Prediction of Drug-Like Small Molecules

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Deep neural network analysis of nanoparticle ordering to identify defects in layered carbon materials

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Hit and Lead Discovery with Explorative RL and Fragment-based Molecule GenerationPreprint

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Chemical design with GPU-based Ising machines

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Recent Advances in Simulation Software and Force Fields: Their Importance in Theoretical and Computational Chemistry and Biophysics

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Bridging chemical space and biological efficacy: advances and challenges in applying generative models in structural modification of natural products

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Artificial intelligence in pharmaceutical sciences: A comprehensive review

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Advances in machine learning for optimizing pharmaceutical drug discovery

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Generative AI for computational chemistry: A roadmap to predicting emergent phenomena

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Property-Aware Relation Networks for Few-Shot Molecular Property Prediction

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AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists

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Artificial intelligence in molecular de novo design: Integration with experiment

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De Novo Design of κ-Opioid Receptor Antagonists Using a Generative Deep-Learning Framework

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REINVENT4: Modern AI–Driven Generative Molecule DesignPreprint

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Pharma’s Bio-AI revolution

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Pharmacophore-oriented 3D molecular generation toward efficient feature-customized drug discovery

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Synthetic lethality in cancer drug discovery: challenges and opportunities

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An Artificial Intelligence Characterised Functional Ingredient, Derived from Rice, Inhibits TNF-α and Significantly Improves Physical Strength in an Inflammaging Population

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Crystal structure prediction in a continuous representative space

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A Quantum Generative Adversarial Network for distributions

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IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method

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On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach

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Designing molecules with autoencoder networks

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High-Temperature Polymer Dielectrics Designed Using an Invertible Molecular Graph Generative Model

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A Crystallization Robot for Generating True Random Numbers Based on Stochastic Chemical Processes

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Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular DesignPreprint

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Can Generative-Model-Based Drug Design Become a New Normal in Drug Discovery?

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Reprogramming the tumor microenvironment to overcome immunotherapy resistance in pancreatic cancer

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Application and assessment of deep learning for the generation of potential NMDA receptor antagonists

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GenUI: interactive and extensible open source software platform for de novo molecular generation and cheminformatics

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Advancing molecular graphs with descriptors for the prediction of chemical reaction yields

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High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders

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