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Avogadro–Scaled Hypergeometric–Chebyshev Feature Maps and Entanglement-Inspired Kernels for Generative-Docking Pattern Recognition in SARS-CoV-2 Targets

2026-04-25

Abstract excerpt

<title>Abstract</title> <p>We describe a docking-oriented pattern-recognition framework for structure-based ligand generation and screening that combines (i) Avogadro-number scaling as a deterministic magnitude stabilizer and (ii) special-function feature maps—regularized hypergeometric expansions and Chebyshev polynomial embeddings—as high-capacity descriptors of pocket–ligand interactions. Similarity is impleme...

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Literature Corpus work
58d06bbd-9351-53f9-9f50-8ff5b4d790fb
DOI
10.21203/rs.3.rs-9361450/v1
Open publication

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Avogadro–Scaled Hypergeometric–Chebyshev Feature Maps and Entanglement-Inspired Kernels for Generative-Docking Pattern Recognition in SARS-CoV-2 TargetsDOI 10.21203/rs.3.rs-9361450/v1
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