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Frontiers in Immunology|September 2, 2024
TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasetsRajitha Rajeshwar T, Omar N A Demerdash, Jeremy C SmithBiophysical Journal|December 12, 2025
Allosteric prediction via convolutional neural networks and protein structural and dynamical featuresRajitha Rajeshwar T, John H Lagergren, Jeremy C Smith, et al.Proteins|April 11, 2022
Structural patterns in class 1 major histocompatibility complex-restricted nonamer peptide binding to T-cell receptorsRajitha Rajeshwar T, Jeremy C SmithJournal of the American Chemical Society|May 22, 2014
Hidden regularity and universal classification of fast side chain motions in proteinsRajitha Rajeshwar T, Jeremy C Smith, Marimuthu KrishnanJournal of Chemical Information and Modeling|November 16, 2023
Comparative Assessment of Pose Prediction Accuracy in RNA-Ligand DockingRupesh Agarwal, Rajitha Rajeshwar T, Jeremy C SmithThe Journal of Physical Chemistry. B|August 23, 2021
Correlated Response of Protein Side-Chain Fluctuations and Conformational Entropy to Ligand BindingRajitha Rajeshwar T, Moumita Saharay, Jeremy C Smith, et al.The Journal of Physical Chemistry. B|April 29, 2017
Direct Determination of Site-Specific Noncovalent Interaction Strengths of Proteins from NMR-Derived Fast Side Chain Motional ParametersRajitha Rajeshwar T, Marimuthu KrishnanJournal of Computer-Aided Molecular Design|October 28, 2021
Using diverse potentials and scoring functions for the development of improved machine-learned models for protein-ligand affinity and docking pose predictionOmar N A DemerdashNature Communications|August 4, 2023
Membrane mediated mechanical stimuli produces distinct active-like states in the AT1 receptorBharat Poudel, Rajitha Rajeshwar T, Juan M VanegasProteins|March 22, 2012
Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysisOmar N A Demerdash, Julie C MitchellPageof 34