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Chemical Science|June 25, 2021
Accelerating high-throughput virtual screening through molecular pool-based active learningDavid E Graff, Eugene I Shakhnovich, Connor W ColeyBiofizika|March 1, 1988
[The role of topological limitations in the kinetics of homopolymer collapse and self-assembly of biopolymers]A Iu Grosberg, S K Nechaev, E I ShakhnovichBiochemistry|August 23, 1994
Specific nucleus as the transition state for protein folding: evidence from the lattice modelV I Abkevich, A M Gutin, E I ShakhnovichProceedings of the National Academy of Sciences of the United States of America|February 28, 1995
Evolution-like selection of fast-folding model proteinsA M Gutin, V I Abkevich, E I ShakhnovichProceedings of the National Academy of Sciences of the United States of America|January 9, 2020
Cotranslational folding allows misfolding-prone proteins to circumvent deep kinetic trapsAmir Bitran, William M Jacobs, Xiadi Zhai, et al.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|January 1, 1997
Computer simulations of prebiotic evolutionV I Abkevich, A M Gutin, E I ShakhnovichFolding & Design|June 18, 1998
A protein engineering analysis of the transition state for protein folding: simulation in the lattice modelA M Gutin, V I Abkevich, E I ShakhnovichVoprosy Kurortologii, Fizioterapii, I Lechebnoi Fizicheskoi Kultury|November 11, 2025
[The role of capillaroscopy in assessing the effectiveness of non-medicamental treatment methods. (Literature review)]A A Simanovsky, V A Shakhnovich, F N MustafinaBiorxiv : the Preprint Server for Biology|November 16, 2022
Cotranslational formation of disulfides guides folding of the SARS COV-2 receptor binding domainAmir Bitran, Kibum Park, Eugene Serebryany, et al.Proceedings of the National Academy of Sciences of the United States of America|June 9, 2025
Predicting high-fitness viral protein variants with Bayesian active learning and biophysicsMarian Huot, Dianzhuo Wang, Jiacheng Liu, et al.Pageof 626