Search

Your search keyword '"Romero-Durana, Miguel"' showing total 39 results
Start Over Author "Romero-Durana, Miguel"
39 results on '"Romero-Durana, Miguel"'

2. Architecture of the ESCPE-1 membrane coat

Author

Lopez-Robles, Carlos, Scaramuzza, Stefano, Astorga-Simon, Elsa N., Ishida, Morié, Williamson, Chad D., Baños-Mateos, Soledad, Gil-Carton, David, Romero-Durana, Miguel, Vidaurrazaga, Ander, Fernandez-Recio, Juan, Rojas, Adriana L., Bonifacino, Juan S., Castaño-Díez, Daniel, and Hierro, Aitor

Published
2023
Full Text
View/download PDF

3. Architecture of the ESCPE-1 membrane coat

Author

Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), National Institutes of Health (US), Swiss National Science Foundation, Eunice Kennedy Shriver National Institute of Child Health and Human Development (US), European Commission, Electron Biology Imaing Centre (UK), University of Leicester, López-Robles, Carlos, Scaramuzza, Stefano, Astorga-Simón, Elsa N., Ishida, Morié, Williamson, Chad D., Baños-Mateos, Soledad, Gil-Cartón, David, Romero-Durana, Miguel, Vidaurrazaga, Ander, Fernández-Recio, Juan, Rojas, Adriana L., Bonifacino, Juan S., Castaño-Díez, Daniel, Hierro, Aitor, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), National Institutes of Health (US), Swiss National Science Foundation, Eunice Kennedy Shriver National Institute of Child Health and Human Development (US), European Commission, Electron Biology Imaing Centre (UK), University of Leicester, López-Robles, Carlos, Scaramuzza, Stefano, Astorga-Simón, Elsa N., Ishida, Morié, Williamson, Chad D., Baños-Mateos, Soledad, Gil-Cartón, David, Romero-Durana, Miguel, Vidaurrazaga, Ander, Fernández-Recio, Juan, Rojas, Adriana L., Bonifacino, Juan S., Castaño-Díez, Daniel, and Hierro, Aitor

Abstract

Recycling of membrane proteins enables the reuse of receptors, ion channels and transporters. A key component of the recycling machinery is the endosomal sorting complex for promoting exit 1 (ESCPE-1), which rescues transmembrane proteins from the endolysosomal pathway for transport to the trans-Golgi network and the plasma membrane. This rescue entails the formation of recycling tubules through ESCPE-1 recruitment, cargo capture, coat assembly and membrane sculpting by mechanisms that remain largely unknown. Herein, we show that ESCPE-1 has a single-layer coat organization and suggest how synergistic interactions between ESCPE-1 protomers, phosphoinositides and cargo molecules result in a global arrangement of amphipathic helices to drive tubule formation. Our results thus define a key process of tubule-based endosomal sorting.

Published
2023

4. The Evolution of Local Energetic Frustration in Protein Families

Author

Freiberger, Maria I., primary, Ruiz-Serra, Victoria I., additional, Pontes, Camila, additional, Romero-Durana, Miguel, additional, Galaz-Davison, Pablo, additional, Ramírez-Sarmiento, Cesar, additional, Schuster, Claudio D., additional, Marti, Marcelo A., additional, Wolynes, Peter G., additional, Ferreiro, Diego U., additional, Parra, R. Gonzalo, additional, and Valencia, Alfonso, additional

Published
2023
Full Text
View/download PDF

5. Susceptibility of Domestic Goat (Capra aegagrus hircus) to Experimental Infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) B.1.351/Beta Variant

Author

Fernández-Bastit, Leira, primary, Roca, Núria, additional, Romero-Durana, Miguel, additional, Rodon, Jordi, additional, Cantero, Guillermo, additional, García, Óscar, additional, López, Carlos, additional, Pérez, Mònica, additional, López, Rosa, additional, Carrillo, Jorge, additional, Izquierdo-Useros, Nuria, additional, Blanco, Julià, additional, Clotet, Bonaventura, additional, Pujols, Joan, additional, Vergara-Alert, Júlia, additional, Segalés, Joaquim, additional, and Lorca-Oró, Cristina, additional

Published
2022
Full Text
View/download PDF

7. Heterogeneous infectivity and pathogenesis of SARS-CoV-2 variants Beta, Delta and Omicron in transgenic K18-hACE2 and wildtype mice

Author

Barcelona Supercomputing Center, Tarrés Freixas, Ferran, Trinité, Benjamin, Pons Grífols, Anna, Romero Durana, Miguel, Riveira Muñoz, Eva, Guallar, Victor, Lepore, Rosalba, Valencia, Alfonso, Barcelona Supercomputing Center, Tarrés Freixas, Ferran, Trinité, Benjamin, Pons Grífols, Anna, Romero Durana, Miguel, Riveira Muñoz, Eva, Guallar, Victor, Lepore, Rosalba, and Valencia, Alfonso

Abstract

The emerging SARS-CoV-2 variants of concern (VOCs) may display enhanced transmissibility, more severity and/or immune evasion; however, the pathogenesis of these new VOCs in experimental SARS-CoV-2 models or the potential infection of other animal species is not completely understood. Here we infected K18-hACE2 transgenic mice with B.1, B.1.351/Beta, B.1.617.2/Delta and BA.1.1/Omicron isolates and demonstrated heterogeneous infectivity and pathogenesis. B.1.351/Beta variant was the most pathogenic, while BA.1.1/Omicron led to lower viral RNA in the absence of major visible clinical signs. In parallel, we infected wildtype (WT) mice and confirmed that, contrary to B.1 and B.1.617.2/Delta, B.1.351/Beta and BA.1.1/Omicron can infect them. Infection in WT mice coursed without major clinical signs and viral RNA was transient and undetectable in the lungs by day 7 post-infection. In silico modeling supported these findings by predicting B.1.351/Beta receptor binding domain (RBD) mutations result in an increased affinity for both human and murine ACE2 receptors, while BA.1/Omicron RBD mutations only show increased affinity for murine ACE2., The research of CBIG consortium (constituted by IRTA-CReSA, BSC & IrsiCaixa) is supported by Grifols. We thank Foundation Dormeur for financial support for the acquisition of the QuantStudio-5 real time PCR system. CÁ-N has a grant by Secretaria d’Universitats i Recerca de la Generalitat de Catalunya and Fons Social Europeu. EG-V is a research fellow from PERIS (SLT017/20/000090). This work was partially funded by grant PID2020-117145RB-I00 from the Spanish Ministry of Science and Innovation (NI-U) the Departament de Salut of the Generalitat de Catalunya (grant SLD016 to JB and Grant SLD015 to JC), the Spanish Health Institute Carlos III (Grant PI17/01518. PI20/00093 to JB and PI18/01332 to JC), Fundació La Marató de TV3 (Project202126-30-21), CERCA Programme/Generalitat de Catalunya 2017 SGR 252, and the crowdfunding initiatives #joemcorono (https://www.yomecorono.com), BonPreu/Esclat and Correos. Funded in part by Fundació Glòria Soler (JB). The funders had no role in study design, data collection and analysis, the decision to publish, or the preparation of the manuscript., Peer Reviewed, "Article signat per 27 autors/es: Ferran Tarrés-Freixas, Benjamin Trinité, Anna Pons-Grífols, Miguel Romero-Durana, Eva Riveira-Muñoz, Carlos Ávila-Nieto, Mónica Pérez, Edurne Garcia-Vidal, Daniel Perez-Zsolt, Jordana Muñoz-Basagoiti, Dàlia Raïch-Regué, Nuria Izquierdo-Useros, Cristina Andrés, Andrés Antón, Tomàs Pumarola, Ignacio Blanco, Marc Noguera-Julián, Victor Guallar, Rosalba Lepore, Alfonso Valencia, Victor Urrea, Júlia Vergara-Alert, Bonaventura Clotet, Ester Ballana, Jorge Carrillo, Joaquim Segalés and Julià Blanco", Postprint (published version)

Published
2022

8. Heterogeneous Infectivity and Pathogenesis of SARS-CoV-2 Variants Beta, Delta and Omicron in Transgenic K18-hACE2 and Wildtype Mice

Author

Tarrés-Freixas, Ferran, primary, Trinité, Benjamin, additional, Pons-Grífols, Anna, additional, Romero-Durana, Miguel, additional, Riveira-Muñoz, Eva, additional, Ávila-Nieto, Carlos, additional, Pérez, Mónica, additional, Garcia-Vidal, Edurne, additional, Perez-Zsolt, Daniel, additional, Muñoz-Basagoiti, Jordana, additional, Raïch-Regué, Dàlia, additional, Izquierdo-Useros, Nuria, additional, Andrés, Cristina, additional, Antón, Andrés, additional, Pumarola, Tomàs, additional, Blanco, Ignacio, additional, Noguera-Julián, Marc, additional, Guallar, Victor, additional, Lepore, Rosalba, additional, Valencia, Alfonso, additional, Urrea, Victor, additional, Vergara-Alert, Júlia, additional, Clotet, Bonaventura, additional, Ballana, Ester, additional, Carrillo, Jorge, additional, Segalés, Joaquim, additional, and Blanco, Julià, additional

Published
2022
Full Text
View/download PDF

9. SARS-CoV-2 B.1.351 (beta) variant shows enhanced infectivity in K18-hACE2 transgenic mice and expanded tropism to wildtype mice compared to B.1 variant

Author

Tarrés-Freixas, Ferran, primary, Trinité, Benjamin, additional, Pons-Grífols, Anna, additional, Romero-Durana, Miguel, additional, Riveira-Muñoz, Eva, additional, Ávila-Nieto, Carlos, additional, Pérez, Mónica, additional, Garcia-Vidal, Edurne, additional, Pérez-Zsolt, Daniel, additional, Muñoz-Basagoiti, Jordana, additional, Raïch-Regué, Dàlia, additional, Izquierdo-Useros, Nuria, additional, Blanco, Ignacio, additional, Noguera-Julián, Marc, additional, Guallar, Victor, additional, Lepore, Rosalba, additional, Valencia, Alfonso, additional, Vergara-Alert, Júlia, additional, Clotet, Bonaventura, additional, Ballana, Ester, additional, Carrillo, Jorge, additional, Segalés, Joaquim, additional, and Blanco, Julià, additional

Published
2021
Full Text
View/download PDF

10. The pyDock interface scoring functions

Author

Rodríguez-Lumbreras, Luis A., Rosell, Mireia, Romero-Durana, Miguel, and Fernández-Recio, Juan

Abstract

Trabajo presentado en el 3D-Bioinformatics 2020 Annual Workshop, celebrado online del 24 al 26 de noviembre de 2020, We describe here the application of pyDock [1] methodology for the scoring of protein-protein interfaces, which can be relevant for the Activity II of the ELIXIR 3D-BioInfo Community "Open resources for sharing, integrating and benchmarking software tools for modelling the proteome in 3D". A major goal of this 3D-BioInfo activity is the application of computational tools for the identification of physiological dimer interfaces and the correct description of functional oligomerization states of proteins and protein assemblies. Indeed, this is an important problem that needs to be targeted before attempting more ambitious structural interactomics projects, such as the structure- and docking-based impact of interface mutations in genes related to diseases detected by newborn screening programs [2]. The capabilities of pyDock for the scoring of modelled assemblies, as recently shown in the recent CASP13-CAPRI and 7th CAPRI rounds, prompted us to explore its application to the characterization of biologically relevant assembly modes. The scoring function of pyDock is composed of electrostatics, desolvation, and van der Waals energy terms (the latter weighted by 10%). This combination was optimized for the scoring of poses from ab initio docking, and seems also suitable for models generated by template-based docking. Here we will apply this function to the proposed benchmark of dimer interfaces, and we will also discuss the performance of each individual pyDock energy term and their different combinations on the discrimination of physiological and non-physiological dimer interfaces. In addition, pyDock binding energy can be easily partitioned per residue, as implemented in the pyDockEneRes web server (https://life.bsc.es/pid/pydockeneres/) [3], which can provide additional information to further characterize the benchmark of dimer interfaces. [1] Cheng TM, Blundell TL, Fernandez-Recio J (2007) Proteins 68, 503¿515. [2] Navío D, Rosell M, Aguirre J, de la Cruz X, Fernánde-Recio J (2019) Int J Mol Sci 20, 1583. [3] Romero-Durana M, Jiménez-García B, Fernández-Recio J (2020) Bioinformatics 36, 2284-2285.

Published
2020

11. Integrative modeling of protein-protein interactions with pyDock for the new docking challenges

Author

Ministerio de Economía y Competitividad (España), European Commission, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Romero-Durana, Miguel, Jiménez-García, Brian, Díaz, Lucía, Fernández-Recio, Juan, Ministerio de Economía y Competitividad (España), European Commission, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Romero-Durana, Miguel, Jiménez-García, Brian, Díaz, Lucía, and Fernández-Recio, Juan

Abstract

The seventh CAPRI edition imposed new challenges to the modeling of protein-protein complexes, such as multimeric oligomerization, protein-peptide, and protein-oligosaccharide interactions. Many of the proposed targets needed the efficient integration of rigid-body docking, template-based modeling, flexible optimization, multiparametric scoring, and experimental restraints. This was especially relevant for the multimolecular assemblies proposed in the CASP12-CAPRI37 and CASP13-CAPRI46 joint rounds, which were described and evaluated elsewhere. Focusing on the purely CAPRI targets of this edition (rounds 38-45), we have participated in all 17 assessed targets (considering heteromeric and homomeric interfaces in T125 as two separate targets) both as predictors and as scorers, by using integrative modeling based on our docking and scoring approaches: pyDock, IRaPPA, and LightDock. In the protein-protein and protein-peptide targets, we have also participated with our webserver (pyDockWeb). On these 17 CAPRI targets, we submitted acceptable models (or better) within our top 10 models for 10 targets as predictors, 13 targets as scorers, and 4 targets as servers. In summary, our participation in this CAPRI edition confirmed the capabilities of pyDock for the scoring of docking models, increasingly used within the context of integrative modeling of protein interactions and multimeric assemblies.

Published
2020

12. PyDockEneRes: Per-residue decomposition of protein-protein docking energy

Author

Ministerio de Economía y Competitividad (España), European Commission, Romero-Durana, Miguel, Jiménez-García, Brian, Fernández-Recio, Juan, Ministerio de Economía y Competitividad (España), European Commission, Romero-Durana, Miguel, Jiménez-García, Brian, and Fernández-Recio, Juan

Abstract

Motivation: Protein-protein interactions are key to understand biological processes at the molecular level. As a complement to experimental characterization of protein interactions, computational docking methods have become useful tools for the structural and energetics modeling of protein-protein complexes. A key aspect of such algorithms is the use of scoring functions to evaluate the generated docking poses and try to identify the best models. When the scoring functions are based on energetic considerations, they can help not only to provide a reliable structural model for the complex, but also to describe energetic aspects of the interaction. This is the case of the scoring function used in pyDock, a combination of electrostatics, desolvation and van der Waals energy terms. Its correlation with experimental binding affinity values of protein-protein complexes was explored in the past, but the per-residue decomposition of the docking energy was never systematically analyzed. Results: Here, we present pyDockEneRes (pyDock Energy per-Residue), a web server that provides pyDock docking energy partitioned at the residue level, giving a much more detailed description of the docking energy landscape. Additionally, pyDockEneRes computes the contribution to the docking energy of the side-chain atoms. This fast approach can be applied to characterize a complex structure in order to identify energetically relevant residues (hot-spots) and estimate binding affinity changes upon mutation to alanine.

Published
2020

16. Protein scaffolds in endosomal cargo retrieval.

Author

López-Robles, Carlos, Rojas, Adriana L., Romano-Moreno, Miguel, Baños-Mateos, Soledad, Romero-Durana, Miguel, Fernández-Recio, Juan, Hierro, Aitor, López-Robles, Carlos, Rojas, Adriana L., Romano-Moreno, Miguel, Baños-Mateos, Soledad, Romero-Durana, Miguel, Fernández-Recio, Juan, and Hierro, Aitor

Published
2019

17. Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment

Author

Agence Nationale de la Recherche (France), Cancer Research UK, European Commission, Medical Research Council (UK), National Institutes of Health (US), National Natural Science Foundation of China, National Research Foundation of Korea, National Science Foundation (US), Ministerio de Economía y Competitividad (España), Università degli Studi di Napoli PARTHENOPE, Wellcome Trust, Lensink, Marc F., Brysbaert, Guillaume, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphaël A. G., Gerguri, Tereza, Bates, Paul A., Laine, Elodie, Carbone, Alessandra, Grudinin, Sergei, Kong, Ren, Weng, Zhiping, Guest, Johnathan D., Gowthaman, Ragul, Pierce, Brian G., Xu, Xianjin, Duan, Rui, Qiu, Liming, Hou, Jie, Merideth, Benjamin Ryan, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Koukos, Panagiotis I., Roel-Touris, Jorge, Ambrosetti, Francesco, Geng, Cunliang, Schaarschmidt, Jörg, Trellet, Mikael E., Melquiond, Adrien S. J., Xue, Li, Jiménez-García, Brian, Noort, Charlotte W. van, Honorato, Rodrigo V., Bonvin, A. M. J. J., Wodak, Shoshana J., Liu, Ran-Ran, Xu, Xi-Ming, Shi, Hang, Chang, Shan, Eisenstein, Miriam, Karczynska, Agnieszka, Czaplewski, Cezary, Emilia Lubecka, Emilia, Lipska, Agnieszka, Krupa, Paweł, Mozolewska, Magdalena, Golon, Łukasz, Samsonov, Sergey, Liwo, Adam, Crivelli, Silvia, Pagès, Guillaume, Karasikov, Mikhaill, Kadukova, Maria, Yan, Yumeng, Huang, Sheng-You, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Romero-Durana, Miguel, Díaz-Bueno, Lucía, Fernández-Recio, Juan, Christoffer, Charles, Terashi, Genki, Shin, Woong-Hee, Aderinwale, Tunde, Venkata Subraman, Sai Raghavendra Maddhuri, Kihara, Daisuke, Kozakov, Dima, Vajda, Sandor, Porter, Kathryn, Padhorny, Dzmitry, Desta, Israel, Beglov, Dmitri, Ignatov, Mikhail, Kotelnikov, Sergey, Moal, Iain H., Ritchie, David W., Chauvot de Beauchêne, Isaure, Maigret, Bernard, Devignes, Marie-Dominique, Ruiz Echartea, Maria E., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Cao, Yue, Shen, Yang, Baek, Minkyung, Park, Taeyong, Woo, Hyeonuk, Seok, Chaok, Braitbard, Merav, Bitton, Lirane, Scheidman-Duhovny, Dina, Dapkunas, Justas, Olechnovic, Kliment, Venclovas, Česlovas, Kundrotas, Petras J., Belkin, Saveliy, Chakravarty, Devlina, Badal, Varsha D., Vakser, Ilya A., Vreven, Thom, Vangaveti, Sweta, Borrman, Tyler, Agence Nationale de la Recherche (France), Cancer Research UK, European Commission, Medical Research Council (UK), National Institutes of Health (US), National Natural Science Foundation of China, National Research Foundation of Korea, National Science Foundation (US), Ministerio de Economía y Competitividad (España), Università degli Studi di Napoli PARTHENOPE, Wellcome Trust, Lensink, Marc F., Brysbaert, Guillaume, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphaël A. G., Gerguri, Tereza, Bates, Paul A., Laine, Elodie, Carbone, Alessandra, Grudinin, Sergei, Kong, Ren, Weng, Zhiping, Guest, Johnathan D., Gowthaman, Ragul, Pierce, Brian G., Xu, Xianjin, Duan, Rui, Qiu, Liming, Hou, Jie, Merideth, Benjamin Ryan, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Koukos, Panagiotis I., Roel-Touris, Jorge, Ambrosetti, Francesco, Geng, Cunliang, Schaarschmidt, Jörg, Trellet, Mikael E., Melquiond, Adrien S. J., Xue, Li, Jiménez-García, Brian, Noort, Charlotte W. van, Honorato, Rodrigo V., Bonvin, A. M. J. J., Wodak, Shoshana J., Liu, Ran-Ran, Xu, Xi-Ming, Shi, Hang, Chang, Shan, Eisenstein, Miriam, Karczynska, Agnieszka, Czaplewski, Cezary, Emilia Lubecka, Emilia, Lipska, Agnieszka, Krupa, Paweł, Mozolewska, Magdalena, Golon, Łukasz, Samsonov, Sergey, Liwo, Adam, Crivelli, Silvia, Pagès, Guillaume, Karasikov, Mikhaill, Kadukova, Maria, Yan, Yumeng, Huang, Sheng-You, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Romero-Durana, Miguel, Díaz-Bueno, Lucía, Fernández-Recio, Juan, Christoffer, Charles, Terashi, Genki, Shin, Woong-Hee, Aderinwale, Tunde, Venkata Subraman, Sai Raghavendra Maddhuri, Kihara, Daisuke, Kozakov, Dima, Vajda, Sandor, Porter, Kathryn, Padhorny, Dzmitry, Desta, Israel, Beglov, Dmitri, Ignatov, Mikhail, Kotelnikov, Sergey, Moal, Iain H., Ritchie, David W., Chauvot de Beauchêne, Isaure, Maigret, Bernard, Devignes, Marie-Dominique, Ruiz Echartea, Maria E., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Cao, Yue, Shen, Yang, Baek, Minkyung, Park, Taeyong, Woo, Hyeonuk, Seok, Chaok, Braitbard, Merav, Bitton, Lirane, Scheidman-Duhovny, Dina, Dapkunas, Justas, Olechnovic, Kliment, Venclovas, Česlovas, Kundrotas, Petras J., Belkin, Saveliy, Chakravarty, Devlina, Badal, Varsha D., Vakser, Ilya A., Vreven, Thom, Vangaveti, Sweta, and Borrman, Tyler

Abstract

We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher‐order assemblies. These were more difficult to model, as their prediction mainly involved “ab‐initio” docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance “gap” was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template‐based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

Published
2019

18. Improving the description of protein-protein association energy

Author

Romero Durana, Miguel Alfonso, Fernández-Recio, Juan, Universitat de Barcelona. Facultat de Biologia, and Gelpí Buchaca, Josep Lluís

Subjects
Ciències biomèdiques, Ciencias biomédicas, Proteínas, Proteins, Proteïnes, Biomedical engineering, Ciències Experimentals i Matemàtiques
Abstract

Proteins play a crucial role in virtually every biological process taking place within our cells. Most of the times, proteins do not participate in these processes alone but forming complexes of two or more proteins. Therefore, the study of protein-protein interactions (PPIs) and complex formation has become an important field of research in the last decades due to its scientific relevance and therapeutic interest. Protein docking is one of the several computational approaches that have been applied to study protein interactions over the last years. It aims to determine the three-dimensional structure of a protein complex based on the structure of its subunits. Although the field has experienced important advances in recent years, it faces significant challenges ahead. New strategies are necessary to overcome current sampling limitations and enhance the physico-chemical description of protein-protein association, understanding its intrinsic mechanisms and identifying the most relevant residues involved, i.e., hot-spot residues. This Ph.D. thesis has focused on developing new computational tools to address some of these challenges. We have developed pyDockLite, a simplified scoring function derived from pyDock, the docking scoring function developed within our lab, which is up to 10 times faster at comparable performance. The key element in pyDockLite development is the new distance-based desolvation term, which drastically reduces the computation time required to calculate the desolvation contribution to pyDock docking energy. Based on pyDockLite, we have developed a fast rigid-body minimization algorithm, which is very efficient when the complex subunits are in their bound conformation. To model backbone flexibility we have included normal modes in the minimization algorithm. This new feature improves the results, especially for the medium-flexible and flexible cases. Most protein-protein docking protocols use scoring functions to evaluate docking poses and discriminate between good, i.e., near- native, and bad conformations. The implicit assumption is that the different energetic minima forming the docking energy landscape are represented by single docking poses which are scored individually. In this thesis, we have analyzed the concept that each energetic minima of the docking energy landscape can be formed by ensembles of docking orientations or conformations, and we have explored the consequences of scoring each minimum by such ensembles. We propose a novel ensemble-based description of the docking landscapes, integrating clustering, conformational sampling and consensus scoring, which improves docking performance. In some circumstances, we might want to have a more detailed description, at the level of residue or atoms, of the docking energy of the different states conforming the docking landscapes. We have developed a method to partition pyDock docking energy at the residue level. Interestingly, we will show how we can use this partitioned energy to identify energetically relevant residues in the binding process (hot-spots) and to estimate changes in binding affinity upon mutation to alanine, i.e., as an in-silico alanine scanning mutagenesis predictor. Regarding mutations to other residues, we have developed a new method to predict binding affinity changes upon mutation by combining MODELLER and pyDock. Results are in line with previous methods when tested on an external validation dataset. Finally, we have explored how to apply the knowledge and tools we have developed to other protein interactions such as those between proteins and RNA molecules. We present a new scoring function that combines FTDock score and pyDock electrostatics and van der Waals energy terms. This scoring function can be used to evaluate docking models of protein-RNA complexes. Our work indicates that protein-protein and protein-RNA interactions may have distinctive features that prevent the direct application of protein-protein scoring functions to protein-RNA docking studies

Published
2018

20. Blind prediction of homo‐ and hetero‐protein complexes: The CASP13‐CAPRI experiment

Author

Lensink, Marc F., primary, Brysbaert, Guillaume, additional, Nadzirin, Nurul, additional, Velankar, Sameer, additional, Chaleil, Raphaël A. G., additional, Gerguri, Tereza, additional, Bates, Paul A., additional, Laine, Elodie, additional, Carbone, Alessandra, additional, Grudinin, Sergei, additional, Kong, Ren, additional, Liu, Ran‐Ran, additional, Xu, Xi‐Ming, additional, Shi, Hang, additional, Chang, Shan, additional, Eisenstein, Miriam, additional, Karczynska, Agnieszka, additional, Czaplewski, Cezary, additional, Lubecka, Emilia, additional, Lipska, Agnieszka, additional, Krupa, Paweł, additional, Mozolewska, Magdalena, additional, Golon, Łukasz, additional, Samsonov, Sergey, additional, Liwo, Adam, additional, Crivelli, Silvia, additional, Pagès, Guillaume, additional, Karasikov, Mikhail, additional, Kadukova, Maria, additional, Yan, Yumeng, additional, Huang, Sheng‐You, additional, Rosell, Mireia, additional, Rodríguez‐Lumbreras, Luis A., additional, Romero‐Durana, Miguel, additional, Díaz‐Bueno, Lucía, additional, Fernandez‐Recio, Juan, additional, Christoffer, Charles, additional, Terashi, Genki, additional, Shin, Woong‐Hee, additional, Aderinwale, Tunde, additional, Maddhuri Venkata Subraman, Sai Raghavendra, additional, Kihara, Daisuke, additional, Kozakov, Dima, additional, Vajda, Sandor, additional, Porter, Kathryn, additional, Padhorny, Dzmitry, additional, Desta, Israel, additional, Beglov, Dmitri, additional, Ignatov, Mikhail, additional, Kotelnikov, Sergey, additional, Moal, Iain H., additional, Ritchie, David W., additional, Chauvot de Beauchêne, Isaure, additional, Maigret, Bernard, additional, Devignes, Marie‐Dominique, additional, Ruiz Echartea, Maria E., additional, Barradas‐Bautista, Didier, additional, Cao, Zhen, additional, Cavallo, Luigi, additional, Oliva, Romina, additional, Cao, Yue, additional, Shen, Yang, additional, Baek, Minkyung, additional, Park, Taeyong, additional, Woo, Hyeonuk, additional, Seok, Chaok, additional, Braitbard, Merav, additional, Bitton, Lirane, additional, Scheidman‐Duhovny, Dina, additional, Dapkūnas, Justas, additional, Olechnovič, Kliment, additional, Venclovas, Česlovas, additional, Kundrotas, Petras J., additional, Belkin, Saveliy, additional, Chakravarty, Devlina, additional, Badal, Varsha D., additional, Vakser, Ilya A., additional, Vreven, Thom, additional, Vangaveti, Sweta, additional, Borrman, Tyler, additional, Weng, Zhiping, additional, Guest, Johnathan D., additional, Gowthaman, Ragul, additional, Pierce, Brian G., additional, Xu, Xianjin, additional, Duan, Rui, additional, Qiu, Liming, additional, Hou, Jie, additional, Ryan Merideth, Benjamin, additional, Ma, Zhiwei, additional, Cheng, Jianlin, additional, Zou, Xiaoqin, additional, Koukos, Panagiotis I., additional, Roel‐Touris, Jorge, additional, Ambrosetti, Francesco, additional, Geng, Cunliang, additional, Schaarschmidt, Jörg, additional, Trellet, Mikael E., additional, Melquiond, Adrien S. J., additional, Xue, Li, additional, Jiménez‐García, Brian, additional, van Noort, Charlotte W., additional, Honorato, Rodrigo V., additional, Bonvin, Alexandre M. J. J., additional, and Wodak, Shoshana J., additional

Published
2019
Full Text
View/download PDF

21. LightDock: a new multi-scale approach to protein-protein docking

Author

Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions, Jimenez Garcia, Brian, Roel Touris, Jorge, Romero Durana, Miguel, Vidal, Miquel, Jiménez González, Daniel, Fernández Recio, Juan, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions, Jimenez Garcia, Brian, Roel Touris, Jorge, Romero Durana, Miguel, Vidal, Miquel, Jiménez González, Daniel, and Fernández Recio, Juan

Abstract

Motivation: Computational prediction of protein-protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed. Results: We describe here a new multi-scale protein-protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigidbody docking, especially in flexible cases., Postprint (author's final draft)

Published
2018

22. LightDock: a new multi-scale approach to protein–protein docking

Author

Ministerio de Economía y Competitividad (España), European Commission, Generalitat de Catalunya, Jiménez-García, Brian, Roel-Touris, Jorge, Romero-Durana, Miguel, Vidal, Miquel, Jiménez-González, Daniel, Fernández-Recio, Juan, Ministerio de Economía y Competitividad (España), European Commission, Generalitat de Catalunya, Jiménez-García, Brian, Roel-Touris, Jorge, Romero-Durana, Miguel, Vidal, Miquel, Jiménez-González, Daniel, and Fernández-Recio, Juan

Abstract

[Motivation] Computational prediction of protein–protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed., [Results] We describe here a new multi-scale protein–protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigidbody docking, especially in flexible cases.

Published
2018

23. Integrative modeling of protein‐protein interactions with pyDock for the new docking challenges.

Author

Rosell, Mireia, Rodríguez‐Lumbreras, Luis A., Romero‐Durana, Miguel, Jiménez‐García, Brian, Díaz, Lucía, and Fernández‐Recio, Juan

Abstract

The seventh CAPRI edition imposed new challenges to the modeling of protein‐protein complexes, such as multimeric oligomerization, protein‐peptide, and protein‐oligosaccharide interactions. Many of the proposed targets needed the efficient integration of rigid‐body docking, template‐based modeling, flexible optimization, multiparametric scoring, and experimental restraints. This was especially relevant for the multimolecular assemblies proposed in the CASP12‐CAPRI37 and CASP13‐CAPRI46 joint rounds, which were described and evaluated elsewhere. Focusing on the purely CAPRI targets of this edition (rounds 38‐45), we have participated in all 17 assessed targets (considering heteromeric and homomeric interfaces in T125 as two separate targets) both as predictors and as scorers, by using integrative modeling based on our docking and scoring approaches: pyDock, IRaPPA, and LightDock. In the protein‐protein and protein‐peptide targets, we have also participated with our webserver (pyDockWeb). On these 17 CAPRI targets, we submitted acceptable models (or better) within our top 10 models for 10 targets as predictors, 13 targets as scorers, and 4 targets as servers. In summary, our participation in this CAPRI edition confirmed the capabilities of pyDock for the scoring of docking models, increasingly used within the context of integrative modeling of protein interactions and multimeric assemblies. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

24. LightDock: a new multi-scale approach to protein–protein docking

Author

Barcelona Supercomputing Center, Jiménez-García, Brian, Roel-Touris, Jorge, Romero-Durana, Miguel, Vidal, Miquel, Jiménez-González, Daniel, Fernández-Recio, Juan, Barcelona Supercomputing Center, Jiménez-García, Brian, Roel-Touris, Jorge, Romero-Durana, Miguel, Vidal, Miquel, Jiménez-González, Daniel, and Fernández-Recio, Juan

Abstract

Computational prediction of protein–protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed. We describe here a new multi-scale protein–protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigid-body docking, especially in flexible cases., B.J-G was supported by a FPI fellowship from the Spanish Ministry of Economy and Competitiveness. This work was supported by I+D+I Research Project grants BIO2013-48213-R and BIO2016-79930-R from the Spanish Ministry of Economy and Competitiveness. This work is partially supported by the European Union H2020 program through HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (TIN2015-65316-P) and the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR: Models de Programaciói Entorns d’Execució Paral·lels (2014-SGR-1051)., Peer Reviewed, Postprint (author's final draft)

Published
2017

25. Structural and energy determinants in protein-RNA docking

Author

Barcelona Supercomputing Center, Pérez-Cano, Laura, Romero-Durana, Miguel, Fernández-Recio, Juan, Barcelona Supercomputing Center, Pérez-Cano, Laura, Romero-Durana, Miguel, and Fernández-Recio, Juan

Abstract

Deciphering the structural and energetic determinants of protein-RNA interactions harbors the potential to understand key cell processes at molecular level, such as gene expression and regulation. With this purpose, computational methods like docking aim to complement current biophysical and structural biology efforts. However, the few reported docking algorithms for protein-RNA interactions show limited predictive success rates, mainly due to incomplete sampling of the conformational space of both the protein and the RNA molecules, as well as to the difficulties of the scoring function in identifying the correct docking models. Here, we have tested the predictive value of a variety of knowledge-based and energetic scoring functions on a recently published protein-RNA docking benchmark and developed a scoring function able to efficiently discriminate docking decoys. We first performed docking calculations with the bound conformation, which allowed us to analyze the problem in optimal conditions. We found that geometry-based terms and electrostatics were the most important scoring terms, while binding propensities and desolvation were much less relevant for the scoring of protein-RNA models. This is in contrast with what we observed for protein-protein docking. The results also showed an interesting dependence of the predictive rates on the flexibility of the protein molecule, which arises from the observed higher positive charge of flexible interfaces and provides hints for future development of more efficient protein-RNA docking methods., This work is supported by grant BIO2013-48213-R from Plan Nacional I+D+i (Spanish Ministry of Economy and Competitiveness). LP-C was recipient of an FPU fellowship from the Spanish Ministry of Science., Peer Reviewed, Postprint (author's final draft)

Published
2017

26. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

Author

Lensink, Marc F., Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Viswanath, Shruthi, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Lee, Gyu Rie, Seok, Chaok, Qin, Sanbo, Zhou, Huan Xiang, Ritchie, David W., Maigret, Bernard, Devignes, Marie Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël A.G., Bates, Paul A., Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra S., Weng, Zhiping, Vreven, Thom, Pierce, Brian G., Borrman, Tyler M., Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Rodrigues, João P.G.L.M., Van Zundert, Gydo, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien S.J., Visscher, Koen, Kastritis, Panagiotis L., Bonvin, Alexandre M.J.J., Xu, Xianjin, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna X., Kim, Hyung Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil J., Fuller, Jonathan C., Wade, Rebecca C., Anishchenko, Ivan, Kundrotas, Petras J., Vakser, Ilya A., Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain H., Férnandez-Recio, Juan, Joung, Jong Young, Kim, Jong Yun, Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David R., Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, Del Carpio, Carlos A., Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Roy Burman, Shourya S., Gray, Jeffrey J., Chermak, Edrisse, Cavallo, Luigi, Oliva, Romina, Tovchigrechko, Andrey, Wodak, Shoshana J., Molecular and Computational Toxicology, and AIMMS

Subjects
Protein docking, CASP, Protein interaction, SDG 1 - No Poverty, Oligomer state, Blind prediction, CAPRI
Abstract

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

Published
2016

29. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

Author

NMR Spectroscopy, Sub NMR Spectroscopy, Lensink, Marc F., Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Viswanath, Shruthi, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Rie Lee, Gyu, Seok, Chaok, Qin, Sanbo, Zhou, Huan Xiang, Ritchie, David W., Maigret, Bernard, Devignes, Marie Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël A G, Bates, Paul A., Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra S., Weng, Zhiping, Vreven, Thom, Pierce, Brian G., Borrman, Tyler M., Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Garcia Lopes Maia Rodrigues, João, van Zundert, Gydo, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien S J, Visscher, Koen, Kastritis, Panagiotis L., Bonvin, Alexandre M J J, Xu, Xianjin, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna X., Kim, Hyung Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil J., Fuller, Jonathan C., Wade, Rebecca C., Anishchenko, Ivan, Kundrotas, Petras J., Vakser, Ilya A., Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain H., Férnandez-Recio, Juan, Joung, Jong Young, Kim, Jong Yun, Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David R., Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, Del Carpio, Carlos A., Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Roy Burman, Shourya S., Gray, Jeffrey J., Chermak, Edrisse, Cavallo, Luigi, Oliva, Romina, Tovchigrechko, Andrey, Wodak, Shoshana J., NMR Spectroscopy, Sub NMR Spectroscopy, Lensink, Marc F., Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Viswanath, Shruthi, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Rie Lee, Gyu, Seok, Chaok, Qin, Sanbo, Zhou, Huan Xiang, Ritchie, David W., Maigret, Bernard, Devignes, Marie Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël A G, Bates, Paul A., Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra S., Weng, Zhiping, Vreven, Thom, Pierce, Brian G., Borrman, Tyler M., Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Garcia Lopes Maia Rodrigues, João, van Zundert, Gydo, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien S J, Visscher, Koen, Kastritis, Panagiotis L., Bonvin, Alexandre M J J, Xu, Xianjin, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna X., Kim, Hyung Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil J., Fuller, Jonathan C., Wade, Rebecca C., Anishchenko, Ivan, Kundrotas, Petras J., Vakser, Ilya A., Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain H., Férnandez-Recio, Juan, Joung, Jong Young, Kim, Jong Yun, Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David R., Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, Del Carpio, Carlos A., Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Roy Burman, Shourya S., Gray, Jeffrey J., Chermak, Edrisse, Cavallo, Luigi, Oliva, Romina, Tovchigrechko, Andrey, and Wodak, Shoshana J.

Published
2016

30. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

Author

Lensink, Marc, Lensink, Marc, Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen-You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Viswanath, Shruthi, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Rie Lee, Gyu, Seok, Chaok, Qin, Sanbo, Zhou, Huan-Xiang, Ritchie, David, Maigret, Bernard, Devignes, Marie-Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël, Bates, Paul, Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra, Weng, Zhiping, Vreven, Thom, Pierce, Brian, Borrman, Tyler, Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Rodrigues, João, van Zundert, Gydo, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien, Visscher, Koen, Kastritis, Panagiotis, Bonvin, Alexandre, Xu, Xianjin, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna, Kim, Hyung-Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil, Fuller, Jonathan, Wade, Rebecca, Anishchenko, Ivan, Kundrotas, Petras, Vakser, Ilya, Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain, Férnandez-Recio, Juan, Joung, Jong, Kim, Jong, Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David, Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, Del Carpio, Carlos, Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Roy Burman, Shourya, Gray, Jeffrey, Chermak, Edrisse, Cavallo, Luigi, Lensink, Marc, Lensink, Marc, Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen-You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Viswanath, Shruthi, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Rie Lee, Gyu, Seok, Chaok, Qin, Sanbo, Zhou, Huan-Xiang, Ritchie, David, Maigret, Bernard, Devignes, Marie-Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël, Bates, Paul, Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra, Weng, Zhiping, Vreven, Thom, Pierce, Brian, Borrman, Tyler, Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Rodrigues, João, van Zundert, Gydo, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien, Visscher, Koen, Kastritis, Panagiotis, Bonvin, Alexandre, Xu, Xianjin, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna, Kim, Hyung-Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil, Fuller, Jonathan, Wade, Rebecca, Anishchenko, Ivan, Kundrotas, Petras, Vakser, Ilya, Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain, Férnandez-Recio, Juan, Joung, Jong, Kim, Jong, Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David, Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, Del Carpio, Carlos, Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Roy Burman, Shourya, Gray, Jeffrey, Chermak, Edrisse, and Cavallo, Luigi

Abstract

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

Published
2016

31. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

Author

Barcelona Supercomputing Center, Lesink, Marc F., Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen-You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Shruthi, Viswanath, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Lee, Gyu R., Seok, Chaok, Qin, Sanbo, Zhou, Huan-Xiang, Ritchie, David W., Maigret, Bernard, Devignes, Marie-Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël A.G., Bates, Paul A., Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra S., Weng, Zhiping, Vreven, Thom, Pierce, Brian G., Borrman, Tyler M., Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Rodrigues, Joao P.G.L.M., Zundert, Gydo van, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien S.J., Visscher, Koen, Kastritis, Panagiotis L., Bonvin, Alexandre M.J.J., Xianjin, Xu, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna X., Kim, Hyung-Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil J., Fuller, Jonathan C., Wade, Rebecca C., Anishchenko, Ivan, Kundrotas, Petras J., Vakser, Ilya A., Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain H., Fernández-Recio, Juan, Joung, Jong Y., Kim, Jong Y., Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David R., Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, del Carpio, Carlos A., Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Burman, Shourya S., Gray, Jeffrey J., Chermak, Edrisse, Cavallo, Luigi, Oliva, Romina, Tovchigrechko, Andrey, Wodak, Shoshana J., Barcelona Supercomputing Center, Lesink, Marc F., Velankar, Sameer, Kryshtafovych, Andriy, Huang, Shen-You, Schneidman-Duhovny, Dina, Sali, Andrej, Segura, Joan, Fernandez-Fuentes, Narcis, Shruthi, Viswanath, Elber, Ron, Grudinin, Sergei, Popov, Petr, Neveu, Emilie, Lee, Hasup, Baek, Minkyung, Park, Sangwoo, Heo, Lim, Lee, Gyu R., Seok, Chaok, Qin, Sanbo, Zhou, Huan-Xiang, Ritchie, David W., Maigret, Bernard, Devignes, Marie-Dominique, Ghoorah, Anisah, Torchala, Mieczyslaw, Chaleil, Raphaël A.G., Bates, Paul A., Ben-Zeev, Efrat, Eisenstein, Miriam, Negi, Surendra S., Weng, Zhiping, Vreven, Thom, Pierce, Brian G., Borrman, Tyler M., Yu, Jinchao, Ochsenbein, Françoise, Guerois, Raphaël, Vangone, Anna, Rodrigues, Joao P.G.L.M., Zundert, Gydo van, Nellen, Mehdi, Xue, Li, Karaca, Ezgi, Melquiond, Adrien S.J., Visscher, Koen, Kastritis, Panagiotis L., Bonvin, Alexandre M.J.J., Xianjin, Xu, Qiu, Liming, Yan, Chengfei, Li, Jilong, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Shen, Yang, Peterson, Lenna X., Kim, Hyung-Rae, Roy, Amit, Han, Xusi, Esquivel-Rodriguez, Juan, Kihara, Daisuke, Yu, Xiaofeng, Bruce, Neil J., Fuller, Jonathan C., Wade, Rebecca C., Anishchenko, Ivan, Kundrotas, Petras J., Vakser, Ilya A., Imai, Kenichiro, Yamada, Kazunori, Oda, Toshiyuki, Nakamura, Tsukasa, Tomii, Kentaro, Pallara, Chiara, Romero-Durana, Miguel, Jiménez-García, Brian, Moal, Iain H., Fernández-Recio, Juan, Joung, Jong Y., Kim, Jong Y., Joo, Keehyoung, Lee, Jooyoung, Kozakov, Dima, Vajda, Sandor, Mottarella, Scott, Hall, David R., Beglov, Dmitri, Mamonov, Artem, Xia, Bing, Bohnuud, Tanggis, del Carpio, Carlos A., Ichiishi, Eichiro, Marze, Nicholas, Kuroda, Daisuke, Burman, Shourya S., Gray, Jeffrey J., Chermak, Edrisse, Cavallo, Luigi, Oliva, Romina, Tovchigrechko, Andrey, and Wodak, Shoshana J.

Abstract

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy., We are most grateful to the PDBe at the European Bioinformatics Institute in Hinxton, UK, for hosting the CAPRI website. Our deepest thanks go to all the structural biologists and to the following structural genomics initiatives: Northeast Structural Genomics Consortium, Joint Center for Structural Genomics, NatPro PSI:Biology, New York Structural Genomics Research Center, Midwest Center for Structural Genomics, Structural Genomics Consortium, for contributing the targets for this joint CASP-CAPRI experiment. MFL acknowledges support from the FRABio FR3688 Research Federation “Structural & Functional Biochemistry of Biomolecular Assemblies.”, Peer Reviewed, Postprint (published version)

Published
2016

32. Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment

Author

Lensink, Marc F., primary, Velankar, Sameer, additional, Kryshtafovych, Andriy, additional, Huang, Shen‐You, additional, Schneidman‐Duhovny, Dina, additional, Sali, Andrej, additional, Segura, Joan, additional, Fernandez‐Fuentes, Narcis, additional, Viswanath, Shruthi, additional, Elber, Ron, additional, Grudinin, Sergei, additional, Popov, Petr, additional, Neveu, Emilie, additional, Lee, Hasup, additional, Baek, Minkyung, additional, Park, Sangwoo, additional, Heo, Lim, additional, Rie Lee, Gyu, additional, Seok, Chaok, additional, Qin, Sanbo, additional, Zhou, Huan‐Xiang, additional, Ritchie, David W., additional, Maigret, Bernard, additional, Devignes, Marie‐Dominique, additional, Ghoorah, Anisah, additional, Torchala, Mieczyslaw, additional, Chaleil, Raphaël A.G., additional, Bates, Paul A., additional, Ben‐Zeev, Efrat, additional, Eisenstein, Miriam, additional, Negi, Surendra S., additional, Weng, Zhiping, additional, Vreven, Thom, additional, Pierce, Brian G., additional, Borrman, Tyler M., additional, Yu, Jinchao, additional, Ochsenbein, Françoise, additional, Guerois, Raphaël, additional, Vangone, Anna, additional, Rodrigues, João P.G.L.M., additional, van Zundert, Gydo, additional, Nellen, Mehdi, additional, Xue, Li, additional, Karaca, Ezgi, additional, Melquiond, Adrien S.J., additional, Visscher, Koen, additional, Kastritis, Panagiotis L., additional, Bonvin, Alexandre M.J.J., additional, Xu, Xianjin, additional, Qiu, Liming, additional, Yan, Chengfei, additional, Li, Jilong, additional, Ma, Zhiwei, additional, Cheng, Jianlin, additional, Zou, Xiaoqin, additional, Shen, Yang, additional, Peterson, Lenna X., additional, Kim, Hyung‐Rae, additional, Roy, Amit, additional, Han, Xusi, additional, Esquivel‐Rodriguez, Juan, additional, Kihara, Daisuke, additional, Yu, Xiaofeng, additional, Bruce, Neil J., additional, Fuller, Jonathan C., additional, Wade, Rebecca C., additional, Anishchenko, Ivan, additional, Kundrotas, Petras J., additional, Vakser, Ilya A., additional, Imai, Kenichiro, additional, Yamada, Kazunori, additional, Oda, Toshiyuki, additional, Nakamura, Tsukasa, additional, Tomii, Kentaro, additional, Pallara, Chiara, additional, Romero‐Durana, Miguel, additional, Jiménez‐García, Brian, additional, Moal, Iain H., additional, Férnandez‐Recio, Juan, additional, Joung, Jong Young, additional, Kim, Jong Yun, additional, Joo, Keehyoung, additional, Lee, Jooyoung, additional, Kozakov, Dima, additional, Vajda, Sandor, additional, Mottarella, Scott, additional, Hall, David R., additional, Beglov, Dmitri, additional, Mamonov, Artem, additional, Xia, Bing, additional, Bohnuud, Tanggis, additional, Del Carpio, Carlos A., additional, Ichiishi, Eichiro, additional, Marze, Nicholas, additional, Kuroda, Daisuke, additional, Roy Burman, Shourya S., additional, Gray, Jeffrey J., additional, Chermak, Edrisse, additional, Cavallo, Luigi, additional, Oliva, Romina, additional, Tovchigrechko, Andrey, additional, and Wodak, Shoshana J., additional

Published
2016
Full Text
View/download PDF

33. Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Author

Moretti, Rocco, Fleishman, Sarel J, Agius, Rudi, Torchala, Mieczyslaw, Bates, Paul A, Kastritis, Panagiotis L, Garcia Lopes Maia Rodrigues, João, Trellet, Mikaël, Bonvin, Alexandre M J J, Cui, Meng, Rooman, Marianne, Gillis, Dimitri, Dehouck, Yves, Moal, Iain, Romero-Durana, Miguel, Perez-Cano, Laura, Pallara, Chiara, Jimenez, Brian, Fernandez-Recio, Juan, Flores, Samuel, Pacella, Michael, Praneeth Kilambi, Krishna, Gray, Jeffrey J, Popov, Petr, Grudinin, Sergei, Esquivel-Rodríguez, Juan, Kihara, Daisuke, Zhao, Nan, Korkin, Dmitry, Zhu, Xiaolei, Demerdash, Omar N A, Mitchell, Julie C, Kanamori, Eiji, Tsuchiya, Yuko, Nakamura, Haruki, Lee, Hasup, Park, Hahnbeom, Seok, Chaok, Sarmiento, Jamica, Liang, Shide, Teraguchi, Shusuke, Standley, Daron M, Shimoyama, Hiromitsu, Terashi, Genki, Takeda-Shitaka, Mayuko, Iwadate, Mitsuo, Umeyama, Hideaki, Beglov, Dmitri, Hall, David R, Kozakov, Dima, Vajda, Sandor, Pierce, Brian G, Hwang, Howook, Vreven, Thom, Weng, Zhiping, Huang, Yangyu, Li, Haotian, Yang, Xiufeng, Ji, Xiaofeng, Liu, Shiyong, Xiao, Yi, Zacharias, Martin, Qin, Sanbo, Zhou, Huan-Xiang, Huang, Sheng-You, Zou, Xiaoqin, Velankar, Sameer, Janin, Joël, Wodak, Shoshana J, Baker, David, Sub NMR Spectroscopy, and NMR Spectroscopy

Subjects
binding, deep mutational scanning, Mutation, Protein Interaction Mapping, Taverne, hemagglutinin, yeast display, Databases, Protein, CAPRI, Algorithms, Protein Binding
Abstract

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.

Published
2013

34. LightDock: a new multi-scale approach to protein--protein docking.

Author

Jiménez-García, Brian, Roel-Touris, Jorge, Romero-Durana, Miguel, Vidal, Miquel, Jiménez-González, Daniel, and Fernández-Recio, Juan

Subjects
STRUCTURAL bioinformatics, PROTEIN-protein interactions, INTERMOLECULAR interactions, MOLECULAR docking, MOLECULAR structure
Abstract

Motivation: Computational prediction of protein--protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed. Results: We describe here a new multi-scale protein--protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigidbody docking, especially in flexible cases. [ABSTRACT FROM AUTHOR]

Published
2018
Full Text
View/download PDF

35. Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Author

Sub NMR Spectroscopy, NMR Spectroscopy, Moretti, Rocco, Fleishman, Sarel J, Agius, Rudi, Torchala, Mieczyslaw, Bates, Paul A, Kastritis, Panagiotis L, Garcia Lopes Maia Rodrigues, João, Trellet, Mikaël, Bonvin, Alexandre M J J, Cui, Meng, Rooman, Marianne, Gillis, Dimitri, Dehouck, Yves, Moal, Iain, Romero-Durana, Miguel, Perez-Cano, Laura, Pallara, Chiara, Jimenez, Brian, Fernandez-Recio, Juan, Flores, Samuel, Pacella, Michael, Praneeth Kilambi, Krishna, Gray, Jeffrey J, Popov, Petr, Grudinin, Sergei, Esquivel-Rodríguez, Juan, Kihara, Daisuke, Zhao, Nan, Korkin, Dmitry, Zhu, Xiaolei, Demerdash, Omar N A, Mitchell, Julie C, Kanamori, Eiji, Tsuchiya, Yuko, Nakamura, Haruki, Lee, Hasup, Park, Hahnbeom, Seok, Chaok, Sarmiento, Jamica, Liang, Shide, Teraguchi, Shusuke, Standley, Daron M, Shimoyama, Hiromitsu, Terashi, Genki, Takeda-Shitaka, Mayuko, Iwadate, Mitsuo, Umeyama, Hideaki, Beglov, Dmitri, Hall, David R, Kozakov, Dima, Vajda, Sandor, Pierce, Brian G, Hwang, Howook, Vreven, Thom, Weng, Zhiping, Huang, Yangyu, Li, Haotian, Yang, Xiufeng, Ji, Xiaofeng, Liu, Shiyong, Xiao, Yi, Zacharias, Martin, Qin, Sanbo, Zhou, Huan-Xiang, Huang, Sheng-You, Zou, Xiaoqin, Velankar, Sameer, Janin, Joël, Wodak, Shoshana J, Baker, David, Sub NMR Spectroscopy, NMR Spectroscopy, Moretti, Rocco, Fleishman, Sarel J, Agius, Rudi, Torchala, Mieczyslaw, Bates, Paul A, Kastritis, Panagiotis L, Garcia Lopes Maia Rodrigues, João, Trellet, Mikaël, Bonvin, Alexandre M J J, Cui, Meng, Rooman, Marianne, Gillis, Dimitri, Dehouck, Yves, Moal, Iain, Romero-Durana, Miguel, Perez-Cano, Laura, Pallara, Chiara, Jimenez, Brian, Fernandez-Recio, Juan, Flores, Samuel, Pacella, Michael, Praneeth Kilambi, Krishna, Gray, Jeffrey J, Popov, Petr, Grudinin, Sergei, Esquivel-Rodríguez, Juan, Kihara, Daisuke, Zhao, Nan, Korkin, Dmitry, Zhu, Xiaolei, Demerdash, Omar N A, Mitchell, Julie C, Kanamori, Eiji, Tsuchiya, Yuko, Nakamura, Haruki, Lee, Hasup, Park, Hahnbeom, Seok, Chaok, Sarmiento, Jamica, Liang, Shide, Teraguchi, Shusuke, Standley, Daron M, Shimoyama, Hiromitsu, Terashi, Genki, Takeda-Shitaka, Mayuko, Iwadate, Mitsuo, Umeyama, Hideaki, Beglov, Dmitri, Hall, David R, Kozakov, Dima, Vajda, Sandor, Pierce, Brian G, Hwang, Howook, Vreven, Thom, Weng, Zhiping, Huang, Yangyu, Li, Haotian, Yang, Xiufeng, Ji, Xiaofeng, Liu, Shiyong, Xiao, Yi, Zacharias, Martin, Qin, Sanbo, Zhou, Huan-Xiang, Huang, Sheng-You, Zou, Xiaoqin, Velankar, Sameer, Janin, Joël, Wodak, Shoshana J, and Baker, David

Published
2013

37. pyDockEneRes: per-residue decomposition of protein–protein docking energy.

Author

Romero-Durana, Miguel, Jiménez-García, Brian, and Fernández-Recio, Juan

Subjects
*INTERNET servers, *PROTEIN-protein interactions, *STRUCTURAL models, *DESOLVATION, *ELECTROSTATICS
Abstract

Motivation Protein–protein interactions are key to understand biological processes at the molecular level. As a complement to experimental characterization of protein interactions, computational docking methods have become useful tools for the structural and energetics modeling of protein–protein complexes. A key aspect of such algorithms is the use of scoring functions to evaluate the generated docking poses and try to identify the best models. When the scoring functions are based on energetic considerations, they can help not only to provide a reliable structural model for the complex, but also to describe energetic aspects of the interaction. This is the case of the scoring function used in pyDock, a combination of electrostatics, desolvation and van der Waals energy terms. Its correlation with experimental binding affinity values of protein–protein complexes was explored in the past, but the per-residue decomposition of the docking energy was never systematically analyzed. Results Here, we present pyDockEneRes (pyDock Energy per-Residue), a web server that provides pyDock docking energy partitioned at the residue level, giving a much more detailed description of the docking energy landscape. Additionally, pyDockEneRes computes the contribution to the docking energy of the side-chain atoms. This fast approach can be applied to characterize a complex structure in order to identify energetically relevant residues (hot-spots) and estimate binding affinity changes upon mutation to alanine. Availability and implementation The server does not require registration by the user and is freely accessible for academics at https://life.bsc.es/pid/pydockeneres. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

38. Modeling Binding Affinity of Pathological Mutations for Computational Protein Design.

Author

Romero-Durana M, Pallara C, Glaser F, and Fernández-Recio J

Subjects
Amino Acids chemistry, Binding Sites, Computer Simulation, Databases, Protein, Molecular Docking Simulation, Molecular Dynamics Simulation, Mutation, Protein Binding, Protein Conformation, Protein Interaction Mapping methods, Software, Web Browser, Computational Biology methods, Models, Molecular, Protein Engineering methods, Proteins chemistry, Proteins genetics, Proteins metabolism
Abstract

An important aspect of protein functionality is the formation of specific complexes with other proteins, which are involved in the majority of biological processes. The functional characterization of such interactions at molecular level is necessary, not only to understand biological and pathological phenomena but also to design improved, or even new interfaces, or to develop new therapeutic approaches. X-ray crystallography and NMR spectroscopy have increased the number of 3D protein complex structures deposited in the Protein Data Bank (PDB). However, one of the more challenging objectives in biological research is to functionally characterize protein interactions and thus identify residues that significantly contribute to the binding. Considering that the experimental characterization of protein interfaces remains expensive, time-consuming, and labor-intensive, computational approaches represent a significant breakthrough in proteomics, assisting or even replacing experimental efforts. Thanks to the technological advances in computing and data processing, these techniques now cover a vast range of protocols, from the estimation of the evolutionary conservation of amino acid positions in a protein, to the energetic contribution of each residue to the binding affinity. In this chapter, we review several existing computational protocols to model the phylogenetic, structural, and energetic properties of residues within protein-protein interfaces.

Published
2017
Full Text
View/download PDF

39. Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.

Author

Moretti R, Fleishman SJ, Agius R, Torchala M, Bates PA, Kastritis PL, Rodrigues JP, Trellet M, Bonvin AM, Cui M, Rooman M, Gillis D, Dehouck Y, Moal I, Romero-Durana M, Perez-Cano L, Pallara C, Jimenez B, Fernandez-Recio J, Flores S, Pacella M, Praneeth Kilambi K, Gray JJ, Popov P, Grudinin S, Esquivel-Rodríguez J, Kihara D, Zhao N, Korkin D, Zhu X, Demerdash ON, Mitchell JC, Kanamori E, Tsuchiya Y, Nakamura H, Lee H, Park H, Seok C, Sarmiento J, Liang S, Teraguchi S, Standley DM, Shimoyama H, Terashi G, Takeda-Shitaka M, Iwadate M, Umeyama H, Beglov D, Hall DR, Kozakov D, Vajda S, Pierce BG, Hwang H, Vreven T, Weng Z, Huang Y, Li H, Yang X, Ji X, Liu S, Xiao Y, Zacharias M, Qin S, Zhou HX, Huang SY, Zou X, Velankar S, Janin J, Wodak SJ, and Baker D

Subjects
Algorithms, Mutation, Protein Binding, Databases, Protein, Protein Interaction Mapping
Abstract

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies., (© 2013 Wiley Periodicals, Inc.)

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results