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Author

S. Durdağı

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Open access Aug 2026

Prioritizing Candidate YB‑1 Cold Shock Domain Ligands via 5D-ElectroShape and Boltz Generative Cofolding

Y-box binding protein 1 (YB-1) acts as a key oncoprotein, with its highly conserved cold shock domain (CSD) driving core nucleic acid-binding functions in cancer progression. Despite its therapeutic relevance, the CSD is considered “undruggable” due to the lack of a well-defined hydrophobic pocket. To overcome the limi...

Lalehan Oktay, Cem Uguz, S. Durdağı · 0 citations
Sep 2026

Hot spot-driven discovery of β-catenin/Tcf4 interaction inhibitors via virtual drug repurposing study and experimental validation in colorectal cancer cells.

Findings provide compelling evidence for the feasibility of targeting β-catenin/Tcf4 interactions using small molecules and suggest that Carbenicillin and Ceforanide may serve as promising repurposed candidates for therapeutic intervention in Wnt-driven malignancies.

K. Şahin, A. Coker, S. Durdağı · 0 citations
Aug 2026

Machine-learning-guided library screening and drug resistance profiling of HIV-1 protease inhibitors.

Coupling ML-based large-scale prioritization with structure-based and dynamical validation can prospectively enrich for resistance-robust HIV-1 protease inhibitors and provide a generalizable framework for anticipating drug resistance in rapidly evolving viral targets.

H. Tunc, Sumeyye Yilmaz, Ehsan Sayyah et al. · 0 citations
Open access Jul 2026

New 3H-1,2-Dithiole-3-thione derivatives: Design and synthesis, H2S-release profile, in vitro anticancer activity, and in silico multi-target assessment.

The findings identify particularly compound DTT-S8, as a promising in vitro anticancer candidate, while the computational results suggest a putative involvement of inflammation-related targets, particularly the COX-2/5-LOX axis, which requires direct biochemical and cellular validation.

Semra Altunsoy, Y. Yilmaz, T. Güngör et al. · 0 citations
Open access Aug 2026

Targeting BCL‑2 through Deep Learning-Based Drug Repurposing: A Multimodal Approach Combining Diffusion-Based Generative Modeling, Neural Relational Inference, and In Vitro Validation

A multimodal BCL-2 repurposing workflow built with diffusion-based generative modeling for ligand-specific complex generation and an extended neural relational inference (NRI) framework for trajectory-level interaction analysis is presented, establishing a strategy that couples generative complex prediction with graph-...

Ehsan Sayyah, H. Tunc, A. Çelebi et al. · 0 citations

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