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Current Protocols|October 13, 2025
Automated Deep Learning-Based Pipelines for Multi-Objective De Novo Protein DesignAmrita Nallathambi, Brian KuhlmanJournal of the American Chemical Society|August 15, 2023
Characterizing Protonation-Coupled Conformational Ensembles in RNA via pH-Differential Mutational Profiling with DMS ProbingEdgar M Faison, Amrita Nallathambi, Qi ZhangProtein Science : a Publication of the Protein Society|March 12, 2023
Allosteric inhibition of TEM-1 β lactamase: Microsecond molecular dynamics simulations provide mechanistic insightsErich Hellemann, Amrita Nallathambi, Jacob D DurrantBiorxiv : the Preprint Server for Biology|May 19, 2023
In silico evolution of protein binders with deep learning models for structure prediction and sequence designOdessa J Goudy, Amrita Nallathambi, Tomoaki Kinjo, et al.Proceedings of the National Academy of Sciences of the United States of America|November 30, 2023
In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning modelsOdessa J Goudy, Amrita Nallathambi, Tomoaki Kinjo, et al.Biorxiv : the Preprint Server for Biology|February 23, 2026
Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologiesZhiyuan Yao, McGuire Metts, Avery K Huber, et al.Protein Science : a Publication of the Protein Society|July 10, 2026
Enhancing machine learning-based binder design with high-throughput screening: A comparison of mRNA and yeast display technologiesZhiyuan Yao, McGuire Metts, Avery K Huber, et al.Nature|May 21, 2026
De novo design of miniproteins targeting GPCRsEdin Muratspahić, David Feldman, David E Kim, et al.Pageof 1