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1. Surface-based protein domains retrieval methods from a SHREC2021 challenge

Author

Florent Langenfeld, Tunde Aderinwale, Charles Christoffer, Woong-Hee Shin, Genki Terashi, Xiao Wang, Daisuke Kihara, Halim Benhabiles, Karim Hammoudi, Adnane Cabani, Feryal Windal, Mahmoud Melkemi, Ekpo Otu, Reyer Zwiggelaar, David Hunter, Yonghuai Liu, Léa Sirugue, Huu-Nghia H. Nguyen, Tuan-Duy H. Nguyen, Vinh-Thuyen Nguyen-Truong, Danh Le, Hai-Dang Nguyen, Minh-Triet Tran, Matthieu Montès, Laboratoire Génomique, bioinformatique et chimie moléculaire (GBCM), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Department of Computer Science [Purdue], Purdue University [West Lafayette], Suncheon National University [Suncheon, Corée du Sud], Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 (IEMN), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Bio-Micro-Electro-Mechanical Systems - IEMN (BIOMEMS - IEMN), Université catholique de Lille (UCL)-Université catholique de Lille (UCL)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-JUNIA (JUNIA), JUNIA (JUNIA), Université catholique de Lille (UCL), Institut de Recherche en Informatique Mathématiques Automatique Signal - IRIMAS - UR 7499 (IRIMAS), Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA)), Université de Strasbourg (UNISTRA), École Supérieure d’Ingénieurs en Génie Électrique (ESIGELEC), Aberystwyth University, Edge Hill University, Vietnam National University - Ho Chi Minh City (VNU-HCM), and Léa Sirugue, Matthieu Montès and Florent Langenfeld are supported by the European Research Council Executive Agency under the research grant number 640,283. Daisuke Kihara acknowledges supports from the National Institutes of Health (R01GM133840, R01GM123055) and the National Science Foundation (DBI2003635, CMMI1825941, and MCB1925643). Charles Christoffer is supported by NIGMS-funded pre–doctoral fellowship (T32 GM132024). Huu-Nghia H. Nguyen, Tuan-Duy H. Nguyen, Vinh-Thuyen Nguyen-Truong, Danh Le, Hai-Dang Nguyen, and Minh-Triet Tran are supported by National University Ho Chi Minh City (VNU-HCM) (DS2020-42-01).

Subjects
Models, Molecular, Static Electricity, Proteins, Ligands, Computer Graphics and Computer-Aided Design, Article, Proteins surface, [SPI]Engineering Sciences [physics], SHREC2021, Protein Domains, Materials Chemistry, Physical and Theoretical Chemistry, Spectroscopy, 2000 MSC: 92-08
Abstract

publication dans une revue suite à la communication hal-03467479 (SHREC 2021: surface-based protein domains retrieval); International audience; Proteins are essential to nearly all cellular mechanism and the effectors of the cells activities. As such, they often interact through their surface with other proteins or other cellular ligands such as ions or organic molecules. The evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions hence similar 3D surface properties (shape, physico-chemical properties, …). The protein surfaces are therefore of primary importance for their activity. In the present work, we assess the ability of different methods to detect such similarities based on the geometry of the protein surfaces (described as 3D meshes), using either their shape only, or their shape and the electrostatic potential (a biologically relevant property of proteins surface). Five different groups participated in this contest using the shape-only dataset, and one group extended its pre-existing method to handle the electrostatic potential. Our comparative study reveals both the ability of the methods to detect related proteins and their difficulties to distinguish between highly related proteins. Our study allows also to analyze the putative influence of electrostatic information in addition to the one of protein shapes alone. Finally, the discussion permits to expose the results with respect to ones obtained in the previous contests for the extended method. The source codes of each presented method have been made available online.

Published
2022
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2. Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology

Author

Libin Cao, Anne Poupon, Brian G. Pierce, Howook Hwang, Ying Chen, Victor L. Hsu, Hasup Lee, Yangyu Huang, Daisuke Kihara, Juan Fernández-Recio, Vladimir Potapov, Aroop Sircar, Chaok Seok, Timothy A. Whitehead, Jérôme Azé, Nir Ben Tal, Seren Soner, Brian Kuhlman, P. Benjamin Stranges, Nobuyuki Uchikoga, Sanbo Qin, Xinqi Gong, Yi Xiao, Carlos J. Camacho, Yaoqi Zhou, Gideon Schreiber, Ora Schueler-Furman, Paul A. Bates, Krishna Praneeth Kilambi, Joël Janin, Mati Cohen, Julie C. Mitchell, Panwen Wang, Cunxin Wang, Raed Khashan, Mayuko Takeda-Shitaka, Lin Li, Martin Zacharias, Alexander Tropsha, Genki Terashi, Xiaofan Li, David Baker, Jian Zhan, Julie Bernauer, Zohar Itzhaki, Mainak Guharoy, Eva-Maria Strauch, Xiaoqin Zou, Thom Vreven, Hahnbeom Park, Sheng-You Huang, Stephen Bush, Daron M. Standley, Feng Yang, Yuko Tsuchiya, Fan Jiang, Jacob E. Corn, Takashi Ishida, Chunhua Li, Junsu Ko, Robert G. Hall, Thomas Bourquard, Iain H. Moal, Weiyi Zhang, C.M. Driggers, Nir London, Jessica L. Morgan, Ron Jacak, Haruki Nakamura, Laura Pérez-Cano, Denis Fouches, Bin Liu, Yutaka Akiyama, Omar N. A. Demerdash, Yuval Inbar, Xianjin Xu, Yuedong Yang, Dachuan Guo, Masahito Ohue, Turkan Haliloglu, Jeffrey J. Gray, Juan Esquivel-Rodríguez, Alexandre M. J. J. Bonvin, Pemra Ozbek, Sarel J. Fleishman, Şefik Kerem Ovali, Charles H. Robert, Huan-Xiang Zhou, Eiji Kanamori, Yuri Matsuzaki, Carles Pons, Zhiping Weng, Kengo Kinoshita, Shoshana J. Wodak, Shiyong Liu, Panagiotis L. Kastritis, University of Washington [Seattle], Institute of Molecular Biophysics [Tallahassee], Florida State University [Tallahassee] (FSU), University of Wisconsin Whitewater, Kitasato University, Biomolecular Modelling laboratory [London], Cancer Research UK London Research Institute, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Seoul National University [Seoul] (SNU), Knowledge representation, reasonning (ORPAILLEUR), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Algorithms and Models for Integrative Biology (AMIB ), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Physiologie de la reproduction et des comportements [Nouzilly] (PRC), Institut National de la Recherche Agronomique (INRA)-Institut Français du Cheval et de l'Equitation [Saumur]-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS), Department of Chemical Engineering [Bogazici] (ChE), Boǧaziçi üniversitesi = Boğaziçi University [Istanbul], Tel Aviv University [Tel Aviv], University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Chinese Academy of Sciences [Beijing] (CAS), Beijing University of Technology, Laboratoire de biochimie théorique [Paris] (LBT (UPR_9080)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut de biologie physico-chimique (IBPC (FR_550)), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), Huazhong University of Science and Technology [Wuhan] (HUST), Hadassah Hebrew University Medical Center [Jerusalem], Weizmann Institute of Science [Rehovot, Israël], Institute for Protein Research [Osaka], Osaka University [Osaka], Japan Biological Informatics Consortium [Tokyo], WPI Immunology Frontier Research Center (IFREC), Graduate School of Information Sciences [Sendai], Tohoku University [Sendai], Oregon State University (OSU), Indiana University - Purdue University Indianapolis (IUPUI), Indiana University System, Bijvoet Center for Biomolecular Research [Utrecht], Utrecht University [Utrecht], University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Johns Hopkins University (JHU), Tokyo Institute of Technology [Tokyo] (TITECH), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Purdue University [West Lafayette], Dalton Cardiovascular Research Center [Columbia], University of Missouri [Columbia] (Mizzou), University of Missouri System-University of Missouri System, The Hospital for sick children [Toronto] (SickKids), Institut de biochimie et biophysique moléculaire et cellulaire (IBBMC), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), The authors thank Sameer Velankar and Marc Lensink for their help in coordinating this experiment and Raik Grunberg for many helpful suggestions on a draft. S.J.F. was supported by a long-term fellowship from the Human Frontier Science Program. S.J.W. is Canada Research Chair Tier 1, funded by the Canadian Institutes of Health Research. Research in the Baker laboratory was supported by the Howard Hughes Medical Institute, the Defense Advanced Research Projects Agency, the National Institutes of Health Yeast Resource Center, and the Defense Threat Reduction Agency., Technical University of Munich (TUM), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Laboratoire de Recherche en Informatique (LRI), Centre National de la Recherche Scientifique (CNRS)-Université de Tours-Institut Français du Cheval et de l'Equitation [Saumur]-Institut National de la Recherche Agronomique (INRA), Boğaziçi University [Istanbul], Centre National de la Recherche Scientifique (CNRS)-Institut de biologie physico-chimique (IBPC), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Weizmann Institute of Science, University of Missouri [Columbia], Institut National de la Recherche Agronomique (INRA)-Institut Français du Cheval et de l'Equitation [Saumur] (IFCE)-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS), Tel Aviv University (TAU), Institut de biologie physico-chimique (IBPC (FR_550)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Institut Français du Cheval et de l'Equitation [Saumur]-Université de Tours-Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7)-Institut de biologie physico-chimique (IBPC), and Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Models, Molecular, biochemistry and molecular biology, Computer science, Protein design, Nanotechnology, Machine learning, computer.software_genre, Article, 03 medical and health sciences, Structural Biology, protein protein interactions, Taverne, conformational plasticity, Computational design, Macromolecular docking, CASP, Design methods, Molecular Biology, 030304 developmental biology, Protein interface, 0303 health sciences, Binding Sites, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM], business.industry, 030302 biochemistry & molecular biology, Proteins, [SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biomolecules [q-bio.BM], negative design, Docking (molecular), computational protein design, Critical assessment, Artificial intelligence, business, computer, Protein Binding
Abstract

International audience; The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

Published
2011
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