arXiv (All)
open access
On the Selectivity of Generative Models in Structure-Based Drug Design
Designing small-molecule drugs that selectively bind to a target protein while avoiding unintended interactions with other proteins is essential for reducing side effects that contribute substantially to clinical attrition. Although structure-based drug design (SBDD) has advanced rapidly with deep l
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- FuseDiff: Symmetry-Preserving Joint Diffusion for Dual-Target Structure-Based Drug Design#974348
- Artificial Intelligence in Pharmaceutical Care: Transforming Drug Discovery, Development, and Patient-care Delivery.#421025
- PK/PD-integrated Bayesian platform design for phase II dose regimen optimization#1078143
- From Antibiotics to Cancer Therapeutics: In Silico Design of Novel Ribosomal Assembly Inhibitors / Theresa Clare Noonan#1119823
- Optimal Biological Dose Combination Finding: A Design Roadmap and Robust Cross-Indication Bayesian Borrowing#1049532
Record · ID 1388690
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive