1. Morozov, Alexander, Davide Zgyatti, and Petr Popov. “Equidistant and Uniform Data Augmentation for 3D Objects.” IEEE Access (2022).
  2. Kozlovskii, Igor, and Petr Popov. “Structure-based deep learning for binding site detection in nucleic acid macromolecules.” NAR genomics and bioinformatics 3.4 (2021): lqab111.
  3. Kozlovskii, Igor, and Petr Popov. “Protein–peptide binding site detection using 3D convolutional neural networks.” Journal of chemical information and modeling 61.8 (2021): 3814-3823.
  4. Michaelian, Nairie, et al. “Structural insights on ligand recognition at the human leukotriene B4 receptor 1.” Nature communications 12.1 (2021): 1-12.
  5. Popov, Petr, et al. “Rationalizing Viral Drug Target Identification Using Computational Approaches: The SARS-CoV-2 Spike Glycoprotein S Case Study.” (2020).
  6. Kozlovskii, Igor, and Petr Popov. “Spatiotemporal identification of druggable binding sites using deep learning.” Nature Communications Biology (2020).
  7. Zaucha, Jan, et al. “Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins.” Briefings in Bioinformatics (2020).
  8. Karlov, Dmitry S., et al. “graphDelta: MPNN Scoring Function for the Affinity Prediction of Protein–Ligand Complexes.” ACS omega 5.10 (2020): 5150-5159.
  9. Wang, Jingjing, et al. “The structural study of mutation-induced inactivation of human muscarinic receptor M4.” IUCrJ 7.2 (2020).
  10. Gusach, Anastasiia, et al. “Structural basis of ligand selectivity and disease mutations in cysteinyl leukotriene receptors.” Nature Communications 10.1 (2019): 1-9.
  11. Luginina, Aleksandra, et al. “Structure-based mechanism of cysteinyl leukotriene receptor inhibition by antiasthmatic drugs.” Science advances (2019).
  12. Popov, Petr, et al. “Prediction of disease-associated mutations in the transmembrane regions of proteins with known 3D structure.” PloS one 14.7 (2019): e0219452.
  13. Popov, Petr, et al. “Controlled‐advancement rigid‐body optimization of nanosystems.” Journal of computational chemistry (2019).
  14. Popov, Petr, et al. “Computational design for thermostabilization of GPCRs.” Current Opinion in Structural Biology 55 (2019): 25-33
  15. Li, Xiaoting, et al. “Crystal Structure of the Human Cannabinoid Receptor CB2.” Cell 176.3 (2019): 459-467.
  16. Audet, Martin, et al. “Crystal structure of misoprostol bound to the labor inducer prostaglandin E 2 receptor.” Nature chemical biology (2019): 1.
  17. Yang, Shifan, et al. “Crystal structure of the Frizzled 4 receptor in a ligand-free state.” Nature 560.7720 (2018): 666.
  18. Popov, Petr, et al. “Computational design of thermostabilizing point mutations for G protein-coupled receptors.” eLife 7 (2018): e34729.
  19. Peng, Yao, et al. “5-HT2C receptor structures reveal the structural basis of GPCR polypharmacology.” Cell 172.4 (2018): 719-730.
  20. Popov, Petr et al. “Eurecon: Equidistant uniform rigid-body ensemble constructor.” Journal of Molecular Graphics and Modelling 80 (2018): 313-319.
  21. Neveu, Emilie, et al. “RapidRMSD: Rapid determination of RMSDs corresponding to motions of flexible molecules.” Bioinformatics (2018).
  22. Batyuk, Alexander, et al. “Native phasing of x-ray free-electron laser data for a G protein–coupled receptor.” Science Advances 2.9 (2016): e1600292.
  23. Neveu, Emilie, et al. “PEPSI-Dock: a detailed data-driven protein–protein interaction potential accelerated by polar Fourier correlation.” Bioinformatics 32.17 (2016): i693-i701.
  24. Lensink, Marc F., et al. “Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment.” Proteins: Structure, Function, and Bioinformatics (2016).
  25. S Grudinin et al., Predicting binding poses and affinities in the CSAR 2013-2014 docking exercises using the knowledge-based Convex-PL potential, Journal of Chemical Information and Modeling, 2015.
  26. P Popov et al., Knowledge of Native Protein–Protein Interfaces Is Sufficient To Construct Predictive Models for the Selection of Binding Candidates, Journal of Chemical Information and Modeling, 2015.
  27. P Popov et al., Rapid determination of RMSDs corresponding to macromolecular rigid body motions, Journal of computational chemistry, 2014.
  28. P Popov et al., DockTrina: Docking triangular protein trimers, Proteins: Structure, Function, and Bioinformatics, 2014.
  29. Moretti, Rocco, et al. “Community‐wide evaluation of methods for predicting the effect of mutations on protein–protein interactions.” Proteins: Structure, Function, and Bioinformatics 81.11 (2013): 1980-1987.