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Khaled H. Barakat on Muck Rack

Khaled H. Barakat

Edmonton
As seen in: Nature, Wiley Online Library, ACS Publications, BMC Biotechnology, Rebelion, El Salto
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Articles

Epigenetic control of telomeric RNA maintains heterochromatin in telomerase-driven cancers

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By Jared Price, Frederick Vizeacoumar, Omar Abuhussein, Vincent Maranda, Yue Zhang, Hironori Adachi, Kathryn Nguyen, Liliia Kyrylenko, Aline Rangel-Pozzo, He Dong, Prachi Walke, Connor Denomy, Anjali B. Saxena, Hardikkumar Bipinchandra Patel, Karthic Rajamanickam, Diego de Oliveira, Alain Morejón Morales, Aanchal Aggarwal, Jia Xu, Peng Gao, Jayme Salsman, Dinesh Kumar Dahiya, Cristina Gonzalez-Lopez, Patricia A. Thibault, Michael Levin, Graham Dellaire, Nicholas R. Jette, Gary Groot, Martin Köbel, Cheng-Han Lee, Laura Hopkins, Anand Krishnan, Shahid Ahmed, Christopher H. Eskiw, Khaled H. Barakat, Aneesh Thakur, Yuliang Wu, Ronald DePinho, Sabine Mai, Yi-Tao Yu, Judy Wong, Andrew Freywald, Franco J. Vizeacoumar, Lihui Gong, Ashlyn Materi, Ashtalakshmi Ganapathysamy, Tanya Freywald, Renuka Dahiya, Hussain Elhasasna, Jeff P. Vizeacoumar, Mary Lazell-Wright, Nezeka Alli, Erika P. Munhoz, Naga Suresh Kola
| Nature Verified
Abstract Tumor heterogeneity presents a major clinical challenge. Reactivation of telomerase (hTERT) is a near-universal hallmark of cancer, yet direct inhibition of hTERT has shown limited therapeutic benefit. To uncover tractable telomerase-related vulnerabilities, we applied a synthetic dosage lethality (SDL) strategy to identify genes required only when hTERT is overexpressed.
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AI-MedCraft: A Strategy-Driven AI Platform for Multi-Objective Molecular Design Click to copy article link Article link copied!

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By Khaled H. Barakat, Hazem Ahmed, Ehsan Shahini
| dx.doi.org
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AI-MedCraft: A Strategy-Driven AI Platform for Multi-Objective Molecular Design Click to copy article link Article link copied!

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By Khaled H. Barakat, Hazem Ahmed, Ehsan Shahini
| ACS Publications
Abstract Click to copy section linkSection link copied! Small-molecule drug discovery requires balancing potency, selectivity, solubility, safety, and synthetic feasibility, among other interdependent properties. Yet most computational workflows address these properties sequentially or collapse them into fixed weighted scores. Although artificial intelligence has accelerated molecular design, many platforms struggle to handle explicit multiobjective trade-offs.
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