Team, Visitors, External Collaborators
Overall Objectives
Research Program
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
Dissemination
Bibliography
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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

[1]
F. Rousse.
Incremental algorithms for Orbital-Free Density Functional Theory, Université Grenoble - Alpes, October 2019.
https://hal.archives-ouvertes.fr/tel-02435781

Articles in International Peer-Reviewed Journals

[2]
J. E. Fajardo, R. Shrestha, N. Gil, A. Belsom, S. Crivelli, C. Czaplewski, K. Fidelis, S. Grudinin, M. Karasikov, A. Karczyńska, A. Kryshtafovych, A. Leitner, A. Liwo, E. Lubecka, B. Monastyrskyy, G. Pagès, J. Rappsilber, A. Sieradzan, C. Sikorska, E. Trabjerg, A. Fiser.
Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13, in: Proteins - Structure, Function and Bioinformatics, 2019, forthcoming. [ DOI : 10.1002/prot.25816 ]
https://hal.inria.fr/hal-02315542
[3]
G. Fonti, M. Marcaida, L. Bryan, S. Träger, A. Kalantzi, P.-Y. J. Helleboid, D. Demurtas, M. Tully, S. Grudinin, D. Trono, B. Fierz, M. Dal Peraro.
KAP1 is an antiparallel dimer with a functional asymmetry, in: Life Science Alliance, August 2019, vol. 2, no 4, e201900349. [ DOI : 10.26508/lsa.201900349 ]
https://hal.archives-ouvertes.fr/hal-02291553
[4]
G. Hura, C. Hodge, D. Rosenberg, D. Guzenko, J. Duarte, B. Monastyrskyy, S. Grudinin, A. Kryshtafovych, J. Tainer, K. Fidelis, S. Tsutakawa.
Small angle X‐ray scattering‐assisted protein structure prediction in CASP13 and emergence of solution structure differences, in: Proteins - Structure, Function and Bioinformatics, 2019, pp. 1-17, forthcoming. [ DOI : 10.1002/prot.25827 ]
https://hal.inria.fr/hal-02315292
[5]
M. Kadukova, V. Chupin, S. Grudinin.
Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4, in: Journal of Computer-Aided Molecular Design, November 2019, pp. 1-10. [ DOI : 10.1007/s10822-019-00263-3 ]
https://hal.archives-ouvertes.fr/hal-02434514
[6]
M. Karasikov, G. Pagès, S. Grudinin.
Smooth orientation-dependent scoring function for coarse-grained protein quality assessment, in: Bioinformatics, August 2019, vol. 35, no 16, pp. 2801–2808. [ DOI : 10.1093/bioinformatics/bty1037 ]
https://hal.inria.fr/hal-01971128
[7]
M. Lensink, G. Brysbaert, N. Nadzirin, S. Velankar, R. A. Chaleil, T. Gerguri, P. Bates, E. Laine, A. Carbone, S. Grudinin, R. Kong, R. Liu, X. Xu, H. Shi, S. Chang, M. Eisenstein, A. Karczyńska, C. Czaplewski, E. Lubecka, A. Lipska, P. Krupa, M. Mozolewska, Ł. Golon, S. Samsonov, A. Liwo, S. Crivelli, G. Pagès, M. Karasikov, M. Kadukova, Y. Yan, S. Huang, M. Rosell, L. A. Rodríguez‐Lumbreras, M. Romero‐Durana, L. Díaz‐Bueno, J. Fernandez‐Recio, C. Christoffer, G. Terashi, W. Shin, T. Aderinwale, S. Raghavendra Maddhuri Venkata Subram, D. Kihara, D. Kozakov, S. Vajda, K. Porter, D. Padhorny, I. Desta, D. Beglov, M. Ignatov, S. Kotelnikov, I. Moal, D. Ritchie, I. Chauvot de Beauchêne, B. Maigret, M. E. R. Echartea, D. Barradas‐Bautista, Z. Cao, L. Cavallo, R. Oliva, Y. Cao, Y. Shen, M. Baek, T. Park, H. Woo, C. Seok, M. Braitbard, L. Bitton, D. Scheidman‐Duhovny, J. DapkŪnas, K. Olechnovič, Č. Venclovas, P. J. Kundrotas, S. Belkin, D. Chakravarty, V. Badal, I. A. Vakser, T. Vreven, S. Vangaveti, T. M. Borrman, Z. Weng, J. D. Guest, R. Gowthaman, B. G. Pierce, X. Xu, R. Duan, L. Qiu, J. Hou, B. Ryan Merideth, Z. Ma, J. Cheng, X. Zou, P. Koukos, J. Roel‐Touris, F. Ambrosetti, C. Geng, J. Schaarschmidt, M. Trellet, A. S. Melquiond, L. Xue, B. Jiménez‐García, C. Noort, R. Honorato, A. M. Bonvin, S. J. Wodak.
Blind prediction of homo‐ and hetero‐ protein complexes: The CASP13‐CAPRI experiment, in: Proteins - Structure, Function and Bioinformatics, October 2019, vol. 87, no 12, pp. 1200-1221. [ DOI : 10.1002/prot.25838 ]
https://hal.inria.fr/hal-02320974
[8]
G. Pagès, B. Charmettant, S. Grudinin.
Protein model quality assessment using 3D oriented convolutional neural networks, in: Bioinformatics, September 2019, vol. 35, no 18, pp. 3313–3319. [ DOI : 10.1093/bioinformatics/btz122 ]
https://hal.inria.fr/hal-01899468
[9]
G. Pagès, S. Grudinin.
DeepSymmetry : Using 3D convolutional networks for identification of tandem repeats and internal symmetries in protein structures, in: Bioinformatics, June 2019, pp. 1-24, https://arxiv.org/abs/1810.12026, forthcoming. [ DOI : 10.1093/bioinformatics/btz454 ]
https://hal.inria.fr/hal-01903624
[10]
P. Popov, S. Grudinin, A. Kurdiuk, P. Buslaev, S. Redon.
Controlled‐advancement rigid‐body optimization of nanosystems, in: Journal of Computational Chemistry, October 2019, vol. 40, no 27, pp. 2391-2399. [ DOI : 10.1002/jcc.26016 ]
https://hal.inria.fr/hal-02315276
[11]
F. Rousse, S. Redon.
Incremental solver for Orbital-Free Density Functional Theory, in: Journal of Computational Chemistry, September 2019, vol. 40, no 23, pp. 2013-2027. [ DOI : 10.1002/jcc.25854 ]
https://hal.inria.fr/hal-02135603

Other Publications

[12]
S. Grudinin, E. Laine, A. Hoffmann.
Predicting protein functional motions: an old recipe with a new twist, September 2019, working paper or preprint. [ DOI : 10.1101/703652 ]
https://hal.archives-ouvertes.fr/hal-02291552
[13]
A. H. Larsen, Y. Wang, A. Bottaro, S. Grudinin, L. Arleth, K. Lindorff-Larsen.
Combining molecular dynamics simulations with small-angle X-ray and neutron scattering data to study multi-domain proteins in solution, January 2020, working paper or preprint. [ DOI : 10.1101/2019.12.26.888834 ]
https://hal.archives-ouvertes.fr/hal-02434585
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D3R Grand Challenge 2: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies, in: Journal of Computer-Aided Molecular Design, 2018, vol. 32, no 1, pp. 1–20.
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