Systematic Benchmarking of AI-Based Molecular Generation Models for Structure-Based Drug Design

Perspectives on Hybridizing Quantum Mechanics and Artificial Intelligence for Drug Design.

Engineering Intelligence for Drug Discovery: Atomica as an AI-Powered Computational Platform for Real-Time Molecular Design and Bioactivity Analysis

Atomica is presented, a web-based engineering-intelligence platform designed to integrate AI-driven molecular generation with reproducible cheminformatics validation and bioactivity-context retrieval in a single workflow that bridges algorithmic molecular generation and applied, collaboration-ready drug-discovery workflows.

Emerging Trends in Artificial Intelligence-Driven Drug Discovery: Balancing Chemical Design and Pharmacological Properties for Cancer Therapy.

This review emphasizes the influence of new AI platforms like AlphaFold3, molecular interactions are structurally optimized (MISATO), and ZairaChem on the discovery of oncology drugs and examines how AI reconciles chemical design with pharmacological feasibility.

MolecularCanvas: LLM-assisted Small-Molecule Drug Discovery via Structure-Guided Constraints

MolecularCanvas is an interactive system that enables users to iteratively construct an optimization context by integrating high-level goals, structure-level annotations, property constraints, and reference-based preferences that guides the generation of candidate molecules across diverse molecular structures.

Deep generative models for 3D structure-based drug design and molecular optimisation: a comprehensive survey

This survey provides a comprehensive review of over 100 methods in 3D structure-based drug design (SBDD) and molecular optimisation, and proposes a unified taxonomy covering four primary generative paradigms: autoregressive models, diffusion models, flow matching, and Bayesian Flow Networks.

Open-Sourced In Silico Drug Screening.

This chapter describes a structure-based computational approach to perform high-throughput ligand screens of chemical libraries using open-source software programs and illustrates this workflow with the enzymatic molecular target NAD(P)H:quinone oxidoreductase1 (NQO1), which is overexpressed in a number of human solid tumors.