Sergey Ovchinnikov

Sergey Ovchinnikov

Helen and Irwin Sizer Career Development Professor

Sergey Ovchinnikov studies protein structure and evolution at environmental, organismal, genomic, structural, and molecular scales.

68-533A

Office

so3@mit.edu

Email

Building 68 - Koch Biology Building

Location

Lab Website
Martha Pham

Assistant

617-258-7851

Assistant Phone

Education

  • Graduate: PhD, 2017, University of Washington
  • Undergraduate: BS, 2010, Micro/Molecular Biology, Portland State University

Research Summary

Sergey Ovchinnikov uses phylogenetic inference, protein structure prediction/determination, protein design, deep learning, energy-based models, and differentiable programming to tackle evolutionary questions at environmental, organismal, genomic, structural, and molecular scales, with the aim of developing a unified model of protein evolution.

Recent Publications

  1. AF2BIND: predicting small-molecule binding sites using the pair representation of AlphaFold2. Gazizov, A, Lian, A, Goverde, C, Mou, J, Ovchinnikov, S, Polizzi, NF. 2026. Nat Methods , .
    doi: 10.1038/s41592-026-03011-2PMID:41814061
  2. Stable de novo protein design via joint conformational landscape and sequence optimization. Cho, Y, Dauparas, J, Tsuboyama, K, Rocklin, GJ, Ovchinnikov, S. 2025. Nat Commun 17, 8.
    doi: 10.1038/s41467-025-66526-wPMID:41444215
  3. Designing novel solenoid proteins with in silico evolution. Pretorius, D, Nikov, GI, Washio, K, Florent, SW, Taunt, HN, Ovchinnikov, S, Murray, JW. 2025. Commun Chem 9, 10.
    doi: 10.1038/s42004-025-01817-3PMID:41345299
  4. CIRPIN: Learning Circular Permutation-Invariant Representations to Uncover Putative Protein Homologs. Kolodziej, AR, Abulnaga, SM, Ovchinnikov, S. 2025. bioRxiv , .
    doi: 10.1101/2025.11.18.689110PMID:41332582
  5. Democratizing protein language model training, sharing and collaboration. Su, J, Li, Z, Tao, T, Han, C, He, Y, Dai, F, Yuan, Q, Gao, Y, Si, T, Zhang, X et al.. 2025. Nat Biotechnol , .
    doi: 10.1038/s41587-025-02859-7PMID:41136773
  6. One-shot design of functional protein binders with BindCraft. Pacesa, M, Nickel, L, Schellhaas, C, Schmidt, J, Pyatova, E, Kissling, L, Barendse, P, Choudhury, J, Kapoor, S, Alcaraz-Serna, A et al.. 2025. Nature 646, 483-492.
    doi: 10.1038/s41586-025-09429-6PMID:40866699
  7. De novo design of a peptide modulator to reverse sodium channel dysfunction linked to cardiac arrhythmias and epilepsy. Mahling, R, Hegyi, B, Cullen, ER, Cho, TM, Rodriques, AR, Fossier, L, Yehya, M, Yang, L, Chen, BX, Katchman, AN et al.. 2025. Cell 188, 6170-6185.e19.
    doi: 10.1016/j.cell.2025.07.038PMID:40829586
  8. Magnetic order in disordered NiCr(BO3)O. Gokhfeld, YS, Kazak, NV, Tarasova, AS, Sukhikh, AS, Velikanov, DA, Eremin, EV, Kondratev, OA, Belyaeva, AO, Gavrilkin, SY, Vasiliev, AD et al.. 2025. Dalton Trans 54, 13271-13281.
    doi: 10.1039/d5dt01230aPMID:40827123
  9. Does Sequence Clustering Confound AlphaFold2? Wayment-Steele, HK, Ovchinnikov, S, Colwell, L, Kern, D. 2025. J Mol Biol 437, 169376.
    doi: 10.1016/j.jmb.2025.169376PMID:40780395
  10. Accurate de novo design of high-affinity protein-binding macrocycles using deep learning. Rettie, SA, Juergens, D, Adebomi, V, Bueso, YF, Zhao, Q, Leveille, AN, Liu, A, Bera, AK, Wilms, JA, Üffing, A et al.. 2025. Nat Chem Biol 21, 1948-1956.
    doi: 10.1038/s41589-025-01929-wPMID:40542165
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