Published January 10, 2026
| Version v3
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The Bio-Synthetic Unification: Topological Discovery of the Pharmaceutical 'Sweet Spot' via Spectral Entropy Minimization
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Description
We present a deterministic framework for drug discovery that unifies biological efficacy and synthetic accessibility into a single topological metric: the Pirolo Unified Score (PUS). By modeling molecules as spectral graphs and minimizing their "Synthetic Entropy" (derived from the Laplacian Fiedler vector), the algorithm autonomously rediscovered Imatinib (Gleevec) as an optimal "blockbuster" candidate in a blind retro-validation study. This work demonstrates that pharmaceutical success is a function of thermodynamic modularity encoded in the molecular graph, effectively filtering out "academic traps" and unmanufacturable targets.
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CHANGELOG
V 10 intermal
V 20 prerelease
V 23 Graphics are included.
V 25 some general fixes
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ASP2026BioSynth25CCBYNCND.pdf
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Additional details
References
- Ertl, P., & Schuffenhauer, A. (2009). Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. Journal of Cheminformatics, 1(8).
- Kola, I., & Landis, J. (2004). Can the pharmaceutical industry reduce attrition rates? Nature Reviews Drug Discovery, 3(8), 711-716.
- Lipinski, C. A. (2001). Drug-like properties and the causes of poor solubility and poor permeability. Journal of Pharmacological and Toxicological Methods, 44(1), 235-249.