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TACFormer: Transformer-Based Generative Model for Target-Conditioned De Novo PROTAC Design

Paper recorded by Signals 4 on 2026-10-29 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.LG · 机器学习 · first seen 2026-10-30

Abstract

Targeted protein degradation (TPD) represents a fundamental shift in drug discovery, moving beyond traditional target inhibition toward the event-driven removal of disease-causing proteins. A prominent strategy for TPD is the use of proteolysis-targeting chimeras (PROTACs), heterobifunctional molecules that selectively route a protein of interest (POI) to the ubiquitin-proteasome system for degrad

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#129 most recent of 737 cs.LG papers we have recorded · ↑ newer: Data-driven Random-feature Approximation of Koopman Generators of Nonl · ↓ older: sDMD: Sinkhorn Distribution Matching Distillation
Cite this page: TACFormer: Transformer-Based Generative Model for Target-Conditioned De Novo PROTAC Design: the #129 most recent of 737 cs.LG papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/tacformer-transformer-based-generative-model-for-target-conditioned-de-novo-prot.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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