Molecular Design Optimization For Drug Like Properties

via “application-domain-specific-paper-clustering”

List of molecular design using Generative AI and Deep Learning.

Unique: Hierarchical domain organization with both high-level application areas (drug discovery, protein design) and fine-grained task categorization (lead optimization, scaffold hopping, docking), enabling both broad surveys and deep dives into specific chemistry problems

vs others: More granular than generic ML paper repositories' domain tags, with chemistry-specific task hierarchies that reflect how practitioners actually frame their problems rather than generic 'application' categories

via “molecular design optimization for drug-like properties”

via “nature-inspired molecular design optimization”

via “molecular structure generation and optimization”

via “drug-discovery-molecular-optimization”

via “lead compound optimization”

via “multi-objective protein property optimization”

via “rna sequence design optimization”

via “lead-series-expansion”

via “molecular-interaction-prediction”

via “protein design iteration and variant generation”

via “protein-sequence-generation”