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38 results on '"Lipska, Agnieszka"'

1. The Influence of Multiple Classes on Learning Online Classifiers from Imbalanced and Concept Drifting Data Streams

Author

Lipska, Agnieszka and Stefanowski, Jerzy

Subjects
Computer Science - Machine Learning
Abstract

This work is aimed at the experimental studying the influence of local data characteristics and drifts on the difficulties of learning various online classifiers from multi-class imbalanced data streams. Firstly we present a categorization of these data factors and drifts in the context of imbalanced streams, then we introduce the generators of synthetic streams that model these factors and drifts. The results of many experiments with synthetically generated data streams have shown a much greater role of the overlapping between many minority classes (the type of borderline examples) than for streams with one minority class. The presence of rare examples in the stream is the most difficult single factor. The local drift of splitting minority classes is the third influential factor. Unlike binary streams, the specialized UOB and OOB classifiers perform well enough for even high imbalance ratios. The most challenging for all classifiers are complex scenarios integrating the drifts of the identified factors simultaneously, which worsen the evaluation measures in the case of a several minority classes stronger than for binary ones. This is an extended version of the short paper presented at LIDTA'2022 workshop at ECMLPKDD2022., Comment: 21 pages

Published
2022

3. An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12.

Author

Keasar, Chen, McGuffin, Liam J, Wallner, Björn, Chopra, Gaurav, Adhikari, Badri, Bhattacharya, Debswapna, Blake, Lauren, Bortot, Leandro Oliveira, Cao, Renzhi, Dhanasekaran, BK, Dimas, Itzhel, Faccioli, Rodrigo Antonio, Faraggi, Eshel, Ganzynkowicz, Robert, Ghosh, Sambit, Ghosh, Soma, Giełdoń, Artur, Golon, Lukasz, He, Yi, Heo, Lim, Hou, Jie, Khan, Main, Khatib, Firas, Khoury, George A, Kieslich, Chris, Kim, David E, Krupa, Pawel, Lee, Gyu Rie, Li, Hongbo, Li, Jilong, Lipska, Agnieszka, Liwo, Adam, Maghrabi, Ali Hassan A, Mirdita, Milot, Mirzaei, Shokoufeh, Mozolewska, Magdalena A, Onel, Melis, Ovchinnikov, Sergey, Shah, Anand, Shah, Utkarsh, Sidi, Tomer, Sieradzan, Adam K, Ślusarz, Magdalena, Ślusarz, Rafal, Smadbeck, James, Tamamis, Phanourios, Trieber, Nicholas, Wirecki, Tomasz, Yin, Yanping, Zhang, Yang, Bacardit, Jaume, Baranowski, Maciej, Chapman, Nicholas, Cooper, Seth, Defelicibus, Alexandre, Flatten, Jeff, Koepnick, Brian, Popović, Zoran, Zaborowski, Bartlomiej, Baker, David, Cheng, Jianlin, Czaplewski, Cezary, Delbem, Alexandre Cláudio Botazzo, Floudas, Christodoulos, Kloczkowski, Andrzej, Ołdziej, Stanislaw, Levitt, Michael, Scheraga, Harold, Seok, Chaok, Söding, Johannes, Vishveshwara, Saraswathi, Xu, Dong, Foldit Players consortium, and Crivelli, Silvia N

Subjects
Foldit Players consortium, Humans, Caspases, Computational Biology, Protein Conformation, Models, Molecular, Software, Caspase 12, Models, Molecular, Biochemistry and Cell Biology, Other Physical Sciences
Abstract

Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.

Published
2018

4. Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment

Author

Antoniak, Anna, Biskupek, Iga, Bojarski, Krzysztof K., Czaplewski, Cezary, Giełdoń, Artur, Kogut, Mateusz, Kogut, Małgorzata M., Krupa, Paweł, Lipska, Agnieszka G., Liwo, Adam, Lubecka, Emilia A., Marcisz, Mateusz, Maszota-Zieleniak, Martyna, Samsonov, Sergey A., Sieradzan, Adam K., Ślusarz, Magdalena J., Ślusarz, Rafał, Wesołowski, Patryk A., and Ziȩba, Karolina

Published
2021
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6. Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field

Author

Sieradzan, Adam K., primary, Czaplewski, Cezary, additional, Krupa, Paweł, additional, Mozolewska, Magdalena A., additional, Karczyńska, Agnieszka S., additional, Lipska, Agnieszka G., additional, Lubecka, Emilia A., additional, Gołaś, Ewa, additional, Wirecki, Tomasz, additional, Makowski, Mariusz, additional, Ołdziej, Stanisław, additional, and Liwo, Adam, additional

Published
2021
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7. Evaluation of the scale-consistent UNRES force field in template-free prediction of protein structures in the CASP13 experiment

Author

Lubecka, Emilia A., Karczyńska, Agnieszka S., Lipska, Agnieszka G., Sieradzan, Adam K., Ziȩba, Karolina, Sikorska, Celina, Uciechowska, Urszula, Samsonov, Sergey A., Krupa, Paweł, Mozolewska, Magdalena A., Golon, Łukasz, Giełdoń, Artur, Czaplewski, Cezary, Ślusarz, Rafał, Ślusarz, Magdalena, Crivelli, Silvia N., and Liwo, Adam

Published
2019
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9. Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers

Author

Liwo, Adam, primary, Czaplewski, Cezary, additional, Sieradzan, Adam K., additional, Lubecka, Emilia A., additional, Lipska, Agnieszka G., additional, Golon, Łukasz, additional, Karczyńska, Agnieszka, additional, Krupa, Paweł, additional, Mozolewska, Magdalena A., additional, Makowski, Mariusz, additional, Ganzynkowicz, Robert, additional, Giełdoń, Artur, additional, and Maciejczyk, Maciej, additional

Published
2020
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13. A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. III. Determination of scale-consistent backbone-local and correlation potentials in the UNRES force field and force-field calibration and validation

Author

Liwo, Adam, Sieradzan, Adam K., Lipska, Agnieszka G., Czaplewski, Cezary, Joung, InSuk, Żmudzińska, Wioletta, Hałabis, Anna, and Ołdziej, Stanisław

Subjects
ENERGY function, BASIC proteins, POLYMERS, PROTEIN folding, PROTEIN structure
Abstract

The general theory of the construction of scale-consistent energy terms in the coarse-grained force fields presented in Paper I of this series has been applied to the revision of the UNRES force field for physics-based simulations of proteins. The potentials of mean force corresponding to backbone-local and backbone-correlation energy terms were calculated from the ab initio energy surfaces of terminally blocked glycine, alanine, and proline, and the respective analytical expressions, derived by using the scale-consistent formalism, were fitted to them. The parameters of all these potentials depend on single-residue types, thus reducing their number and preventing over-fitting. The UNRES force field with the revised backbone-local and backbone-correlation terms was calibrated with a set of four small proteins with basic folds: tryptophan cage variant (TRP1; α), Full Sequence Design (FSD; α + β), villin headpiece (villin; α), and a truncated FBP-28 WW-domain variant (2MWD; β) (the NEWCT-4P force field) and, subsequently, with an enhanced set of 9 proteins composed of TRP1, FSD, villin, 1BDC (α), 2I18 (α), 1QHK (α + β), 2N9L (α + β), 1E0L (β), and 2LX7 (β) (the NEWCT-9P force field). The NEWCT-9P force field performed better than NEWCT-4P in a blind-prediction-like test with a set of 26 proteins not used in calibration and outperformed, in a test with 76 proteins, the most advanced OPT-WTFSA-2 version of UNRES with former backbone-local and backbone-correlation terms that contained more energy terms and more optimizable parameters. The NEWCT-9P force field reproduced the bimodal distribution of backbone-virtual-bond angles in the simulated structures, as observed in experimental protein structures. [ABSTRACT FROM AUTHOR]

Published
2019
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14. Optimization of parallel implementation of UNRES package for coarse‐grained simulations to treat large proteins.

Author

Sieradzan, Adam K., Sans‐Duñó, Jordi, Lubecka, Emilia A., Czaplewski, Cezary, Lipska, Agnieszka G., Leszczyński, Henryk, Ocetkiewicz, Krzysztof M., Proficz, Jerzy, Czarnul, Paweł, Krawczyk, Henryk, and Liwo, Adam

Subjects
MOLECULAR dynamics, DIHEDRAL angles, PROTEINS
Abstract

We report major algorithmic improvements of the UNRES package for physics‐based coarse‐grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time‐consuming energy/force terms to minimize the number of operations and to improve numerical stability, (iv) using OpenMP to parallelize those sections of the code for which distributed‐memory parallelization involves unfavorable computing/communication time ratio, and (v) careful memory management to minimize simultaneous access of distant memory sections. The new code enables us to run molecular dynamics simulations of protein systems with size exceeding 100,000 amino‐acid residues, reaching over 1 ns/day (1 μs/day in all‐atom timescale) with 24 cores for proteins of this size. Parallel performance of the code and comparison of its performance with that of AMBER, GROMACS and MARTINI 3 is presented. [ABSTRACT FROM AUTHOR]

Published
2023
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16. Prediction of protein assemblies, the next frontier: The CASP14‐CAPRI experiment

Author

Lensink, Marc F., primary, Brysbaert, Guillaume, additional, Mauri, Théo, additional, Nadzirin, Nurul, additional, Velankar, Sameer, additional, Chaleil, Raphael A. G., additional, Clarence, Tereza, additional, Bates, Paul A., additional, Kong, Ren, additional, Liu, Bin, additional, Yang, Guangbo, additional, Liu, Ming, additional, Shi, Hang, additional, Lu, Xufeng, additional, Chang, Shan, additional, Roy, Raj S., additional, Quadir, Farhan, additional, Liu, Jian, additional, Cheng, Jianlin, additional, Antoniak, Anna, additional, Czaplewski, Cezary, additional, Giełdoń, Artur, additional, Kogut, Mateusz, additional, Lipska, Agnieszka G., additional, Liwo, Adam, additional, Lubecka, Emilia A., additional, Maszota‐Zieleniak, Martyna, additional, Sieradzan, Adam K., additional, Ślusarz, Rafał, additional, Wesołowski, Patryk A., additional, Zięba, Karolina, additional, Del Carpio Muñoz, Carlos A., additional, Ichiishi, Eiichiro, additional, Harmalkar, Ameya, additional, Gray, Jeffrey J., additional, Bonvin, Alexandre M. J. J., additional, Ambrosetti, Francesco, additional, Vargas Honorato, Rodrigo, additional, Jandova, Zuzana, additional, Jiménez‐García, Brian, additional, Koukos, Panagiotis I., additional, Van Keulen, Siri, additional, Van Noort, Charlotte W., additional, Réau, Manon, additional, Roel‐Touris, Jorge, additional, Kotelnikov, Sergei, additional, Padhorny, Dzmitry, additional, Porter, Kathryn A., additional, Alekseenko, Andrey, additional, Ignatov, Mikhail, additional, Desta, Israel, additional, Ashizawa, Ryota, additional, Sun, Zhuyezi, additional, Ghani, Usman, additional, Hashemi, Nasser, additional, Vajda, Sandor, additional, Kozakov, Dima, additional, Rosell, Mireia, additional, Rodríguez‐Lumbreras, Luis A., additional, Fernandez‐Recio, Juan, additional, Karczynska, Agnieszka, additional, Grudinin, Sergei, additional, Yan, Yumeng, additional, Li, Hao, additional, Lin, Peicong, additional, Huang, Sheng‐You, additional, Christoffer, Charles, additional, Terashi, Genki, additional, Verburgt, Jacob, additional, Sarkar, Daipayan, additional, Aderinwale, Tunde, additional, Wang, Xiao, additional, Kihara, Daisuke, additional, Nakamura, Tsukasa, additional, Hanazono, Yuya, additional, Gowthaman, Ragul, additional, Guest, Johnathan D., additional, Yin, Rui, additional, Taherzadeh, Ghazaleh, additional, Pierce, Brian G., additional, Barradas‐Bautista, Didier, additional, Cao, Zhen, additional, Cavallo, Luigi, additional, Oliva, Romina, additional, Sun, Yuanfei, additional, Zhu, Shaowen, additional, Shen, Yang, additional, Park, Taeyong, additional, Woo, Hyeonuk, additional, Yang, Jinsol, additional, Kwon, Sohee, additional, Won, Jonghun, additional, Seok, Chaok, additional, Kiyota, Yasuomi, additional, Kobayashi, Shinpei, additional, Harada, Yoshiki, additional, Takeda‐Shitaka, Mayuko, additional, Kundrotas, Petras J., additional, Singh, Amar, additional, Vakser, Ilya A., additional, Dapkūnas, Justas, additional, Olechnovič, Kliment, additional, Venclovas, Česlovas, additional, Duan, Rui, additional, Qiu, Liming, additional, Xu, Xianjin, additional, Zhang, Shuang, additional, Zou, Xiaoqin, additional, and Wodak, Shoshana J., additional

Published
2021
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18. Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

Author

Lensink, Marc F., Brysbaert, Guillaume, Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphael A.G., Clarence, Tereza, Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Shan, Roy, Raj S., Quadir, Farhan, Liu, Jian, Cheng, Jianlin, Antoniak, Anna, Czaplewski, Cezary, Giełdoń, Artur, Kogut, Mateusz, Lipska, Agnieszka G., Liwo, Adam, Lubecka, Emilia A., Maszota-Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Del Carpio Muñoz, Carlos A., Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Bonvin, Alexandre M.J.J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez-García, Brian, Koukos, Panagiotis I., Van Keulen, Siri, Van Noort, Charlotte W., Réau, Manon, Roel-Touris, Jorge, Kotelnikov, Sergei, Padhorny, Dzmitry, Porter, Kathryn A., Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Fernandez-Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Yuya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda-Shitaka, Mayuko, Kundrotas, Petras J., Singh, Amar, Vakser, Ilya A., Dapkūnas, Justas, Olechnovič, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, Wodak, Shoshana J., Lensink, Marc F., Brysbaert, Guillaume, Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphael A.G., Clarence, Tereza, Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Shan, Roy, Raj S., Quadir, Farhan, Liu, Jian, Cheng, Jianlin, Antoniak, Anna, Czaplewski, Cezary, Giełdoń, Artur, Kogut, Mateusz, Lipska, Agnieszka G., Liwo, Adam, Lubecka, Emilia A., Maszota-Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Del Carpio Muñoz, Carlos A., Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Bonvin, Alexandre M.J.J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez-García, Brian, Koukos, Panagiotis I., Van Keulen, Siri, Van Noort, Charlotte W., Réau, Manon, Roel-Touris, Jorge, Kotelnikov, Sergei, Padhorny, Dzmitry, Porter, Kathryn A., Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Fernandez-Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Yuya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda-Shitaka, Mayuko, Kundrotas, Petras J., Singh, Amar, Vakser, Ilya A., Dapkūnas, Justas, Olechnovič, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, and Wodak, Shoshana J.

Abstract

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Published
2021

19. Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

Author

Sub NMR Spectroscopy, Sub Overig UiLOTS, Sub Mathematics Education, NMR Spectroscopy, Lensink, Marc F., Brysbaert, Guillaume, Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphael A.G., Clarence, Tereza, Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Shan, Roy, Raj S., Quadir, Farhan, Liu, Jian, Cheng, Jianlin, Antoniak, Anna, Czaplewski, Cezary, Giełdoń, Artur, Kogut, Mateusz, Lipska, Agnieszka G., Liwo, Adam, Lubecka, Emilia A., Maszota-Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Del Carpio Muñoz, Carlos A., Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Bonvin, Alexandre M.J.J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez-García, Brian, Koukos, Panagiotis I., Van Keulen, Siri, Van Noort, Charlotte W., Réau, Manon, Roel-Touris, Jorge, Kotelnikov, Sergei, Padhorny, Dzmitry, Porter, Kathryn A., Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Fernandez-Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Yuya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda-Shitaka, Mayuko, Kundrotas, Petras J., Singh, Amar, Vakser, Ilya A., Dapkūnas, Justas, Olechnovič, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, Wodak, Shoshana J., Sub NMR Spectroscopy, Sub Overig UiLOTS, Sub Mathematics Education, NMR Spectroscopy, Lensink, Marc F., Brysbaert, Guillaume, Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphael A.G., Clarence, Tereza, Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Shan, Roy, Raj S., Quadir, Farhan, Liu, Jian, Cheng, Jianlin, Antoniak, Anna, Czaplewski, Cezary, Giełdoń, Artur, Kogut, Mateusz, Lipska, Agnieszka G., Liwo, Adam, Lubecka, Emilia A., Maszota-Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Del Carpio Muñoz, Carlos A., Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Bonvin, Alexandre M.J.J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez-García, Brian, Koukos, Panagiotis I., Van Keulen, Siri, Van Noort, Charlotte W., Réau, Manon, Roel-Touris, Jorge, Kotelnikov, Sergei, Padhorny, Dzmitry, Porter, Kathryn A., Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Fernandez-Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Yuya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda-Shitaka, Mayuko, Kundrotas, Petras J., Singh, Amar, Vakser, Ilya A., Dapkūnas, Justas, Olechnovič, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, and Wodak, Shoshana J.

Published
2021

20. Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

Author

Cancer Research UK, Department of Energy and Climate Change (UK), European Commission, Institut National de Recherche en Informatique et en Automatique (France), Medical Research Council (UK), Japan Society for the Promotion of Science, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), National Institute of General Medical Sciences (US), National Institutes of Health (US), National Natural Science Foundation of China, National Science Foundation (US), Lensink, Marc F., Brysbaert, Guillaume, Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphaël A. G., Clarence, Tereza, Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Xang, Roy, Raj S., Quadir, Farhan, Liu, Jian, Cheng, Jianlin, Antoniak, Anna, Czaplewski, Cezary, Giełdón, Artur, Kogut, Mateusz, Lipska, Agnieszka, Liwo, Adam, Lubecka, Emilia, Maszota-Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Carpio Muñoz, Carlos A. del, Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Bonvin, Alexandre M. J. J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez-García, Brian, Koukos, Panagiotis I., Keulen, Siri van, Noort, Charlotte W. van, Réau, Manon, Roel-Touris, Jorge, Kotelnikov, Sergey, Padhorny, Dzmitry, Porter, Kathryn, Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Fernández-Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng-You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Huya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda-Shitaka, Mayuko, Kundrotas, Petras J., Singh, Amar, Vakser, Ilya A., Dapkunas, Justas, Olechnovic, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, Wodak, Shoshana J., Cancer Research UK, Department of Energy and Climate Change (UK), European Commission, Institut National de Recherche en Informatique et en Automatique (France), Medical Research Council (UK), Japan Society for the Promotion of Science, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), National Institute of General Medical Sciences (US), National Institutes of Health (US), National Natural Science Foundation of China, National Science Foundation (US), Lensink, Marc F., Brysbaert, Guillaume, Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphaël A. G., Clarence, Tereza, Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Xang, Roy, Raj S., Quadir, Farhan, Liu, Jian, Cheng, Jianlin, Antoniak, Anna, Czaplewski, Cezary, Giełdón, Artur, Kogut, Mateusz, Lipska, Agnieszka, Liwo, Adam, Lubecka, Emilia, Maszota-Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Carpio Muñoz, Carlos A. del, Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Bonvin, Alexandre M. J. J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez-García, Brian, Koukos, Panagiotis I., Keulen, Siri van, Noort, Charlotte W. van, Réau, Manon, Roel-Touris, Jorge, Kotelnikov, Sergey, Padhorny, Dzmitry, Porter, Kathryn, Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Fernández-Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng-You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Huya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda-Shitaka, Mayuko, Kundrotas, Petras J., Singh, Amar, Vakser, Ilya A., Dapkunas, Justas, Olechnovic, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, and Wodak, Shoshana J.

Abstract

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Published
2021

23. Extension of the Unres Package for Physics-Based Coarse-Grained Simulations of Proteins and Protein Complexes to Very Large Systems

Author

Sieradzan, Adam K., primary, Czaplewski, Cezary R., additional, Lubecka, Emilia A., additional, Lipska, Agnieszka G., additional, Karczynska, Agnieszka S., additional, Gieldon, Artur P., additional, Slusarz, Rafal, additional, Makowski, Mariusz, additional, Krupa, Pawel, additional, Kogut, Mateusz, additional, Antoniak, Anna, additional, Wesolowski, Patryk A., additional, Augustynowicz, Antoni, additional, Leszczynski, Henryk, additional, and Liwo, Jozef A., additional

Published
2021
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24. Alienacja rodzicielska jako problem społeczny z punktu widzenia prawa.

Author

Lipska, Agnieszka

Abstract

A child to raise the parents of both parents. Unfortunately divorce has become more and more common nowadays, and hence, establishing contacts in the matter of child, childcare. Often in such cases disputes arise between the parties. Children are usually silent witnesses to the whole situation through which their psyche suffers. There is parental alienation. If the parents are unable to communicate on this level by themselves, the law and all regulations, which in principle constitute a remedy, come to the rescue. [ABSTRACT FROM AUTHOR]

Published
2022
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25. Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13

Author

Karczyńska, Agnieszka S., primary, Ziȩba, Karolina, additional, Uciechowska, Urszula, additional, Mozolewska, Magdalena A., additional, Krupa, Paweł, additional, Lubecka, Emilia A., additional, Lipska, Agnieszka G., additional, Sikorska, Celina, additional, Samsonov, Sergey A., additional, Sieradzan, Adam K., additional, Giełdoń, Artur, additional, Liwo, Adam, additional, Ślusarz, Rafał, additional, Ślusarz, Magdalena, additional, Lee, Jooyoung, additional, Joo, Keehyoung, additional, and Czaplewski, Cezary, additional

Published
2020
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26. Molecular dynamics of protein A and a WW domain with a united-residue model including hydrodynamic interaction.

Author

Lipska, Agnieszka G., Seidman, Steven R., Sieradzan, Adam K., Giełdoń, Artur, Liwo, Adam, and Scheraga, Harold A.

Subjects
*MOLECULAR dynamics, *PHASE transitions, *HYDRODYNAMICS, *CARRIER proteins, *PROTEIN folding
Abstract

The folding of the N-terminal part of the B-domain of staphylococcal protein A (PDB ID: 1BDD, a 46-residue three-α-helix bundle) and the formin-binding protein 28 WW domain (PDB ID: 1E0L, a 37-residue three-stranded anti-parallel β protein) was studied by means of Langevin dynamics with the coarse-grained UNRES force field to assess the influence of hydrodynamic interactions on protein-folding pathways and kinetics. The unfolded, intermediate, and native-like structures were identified by cluster analysis, and multi-exponential functions were fitted to the time dependence of the fractions of native and intermediate structures, respectively, to determine bulk kinetics. It was found that introducing hydrodynamic interactions slows down both the formation of an intermediate state and the transition from the collapsed structures to the final native-like structures by creating multiple kinetic traps. Therefore, introducing hydrodynamic interactions considerably slows the folding, as opposed to the results obtained from earlier studies with the use of G?o-like models. [ABSTRACT FROM AUTHOR]

Published
2016
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27. 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

28. 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
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30. Performance of protein-structure predictions with the physics-based UNRES force field in CASP11

Author

Krupa, Paweł, primary, Mozolewska, Magdalena A., additional, Wiśniewska, Marta, additional, Yin, Yanping, additional, He, Yi, additional, Sieradzan, Adam K., additional, Ganzynkowicz, Robert, additional, Lipska, Agnieszka G., additional, Karczyńska, Agnieszka, additional, Ślusarz, Magdalena, additional, Ślusarz, Rafał, additional, Giełdoń, Artur, additional, Czaplewski, Cezary, additional, Jagieła, Dawid, additional, Zaborowski, Bartłomiej, additional, Scheraga, Harold A., additional, and Liwo, Adam, additional

Published
2016
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32. Evolutionary diversification and characterization of the eubacterial gene family encoding DXR type II, an alternative isoprenoid biosynthetic enzyme

Author

Universitat Politècnica de València. Instituto Universitario Mixto de Biología Molecular y Celular de Plantas - Institut Universitari Mixt de Biologia Molecular i Cel·lular de Plantes, Ministerio de Ciencia e Innovación, Generalitat de Catalunya, Carretero Paulet, Lorenzo, Lipska, Agnieszka, Perez-Gil, J., Sangari, J., Albert, VA, Rodriguez-Concepción, M, Universitat Politècnica de València. Instituto Universitario Mixto de Biología Molecular y Celular de Plantas - Institut Universitari Mixt de Biologia Molecular i Cel·lular de Plantes, Ministerio de Ciencia e Innovación, Generalitat de Catalunya, Carretero Paulet, Lorenzo, Lipska, Agnieszka, Perez-Gil, J., Sangari, J., Albert, VA, and Rodriguez-Concepción, M

Abstract

[EN] Background: Isoprenoids constitute a vast family of natural compounds performing diverse and essential functions in all domains of life. In most eubacteria, isoprenoids are synthesized through the methylerythritol 4-phosphate (MEP) pathway. The production of MEP is usually catalyzed by deoxyxylulose 5-phosphate reductoisomerase (DXR-I) but a few organisms use an alternative DXR-like enzyme (DXR-II). Results: Searches through 1498 bacterial complete proteomes detected 130 sequences with similarity to DXR-II. Phylogenetic analysis identified three well-resolved clades: the DXR-II family (clustering 53 sequences including eleven experimentally verified as functional enzymes able to produce MEP), and two previously uncharacterized NAD(P)-dependent oxidoreductase families (designated DLO1 and DLO2 for DXR-II-like oxidoreductases 1 and 2). Our analyses identified amino acid changes critical for the acquisition of DXR-II biochemical function through type-I functional divergence, two of them mapping onto key residues for DXR-II activity. DXR-II showed a markedly discontinuous distribution, which was verified at several levels: taxonomic (being predominantly found in Alphaproteobacteria and Firmicutes), metabolic (being mostly found in bacteria with complete functional MEP pathways with or without DXR-I), and phenotypic (as no biological/phenotypic property was found to be preferentially distributed among DXR-II-containing strains, apart from pathogenicity in animals). By performing a thorough comparative sequence analysis of GC content, 3: 1 dinucleotide frequencies, codon usage and codon adaptation indexes (CAI) between DXR-II sequences and their corresponding genomes, we examined the role of horizontal gene transfer (HGT), as opposed to an scenario of massive gene loss, in the evolutionary origin and diversification of the DXR-II subfamily in bacteria. Conclusions: Our analyses support a single origin of the DXR-II family through functional divergence, in which const

Published
2013

33. Evolutionary diversification and characterization of the eubacterial gene family encoding DXR type II, an alternative isoprenoid biosynthetic enzyme

Author

Carretero-Paulet, Lorenzo, Lipska, Agnieszka, Pérez-Gil, Jordi, Sangari, Félix J., Albert, Víctor A., Rodriguez-Concepcion, Manuel, Carretero-Paulet, Lorenzo, Lipska, Agnieszka, Pérez-Gil, Jordi, Sangari, Félix J., Albert, Víctor A., and Rodriguez-Concepcion, Manuel

Abstract

Background Isoprenoids constitute a vast family of natural compounds performing diverse and essential functions in all domains of life. In most eubacteria, isoprenoids are synthesized through the methylerythritol 4-phosphate (MEP) pathway. The production of MEP is usually catalyzed by deoxyxylulose 5-phosphate reductoisomerase (DXR-I) but a few organisms use an alternative DXR-like enzyme (DXR-II). Results Searches through 1498 bacterial complete proteomes detected 130 sequences with similarity to DXR-II. Phylogenetic analysis identified three well-resolved clades: the DXR-II family (clustering 53 sequences including eleven experimentally verified as functional enzymes able to produce MEP), and two previously uncharacterized NAD(P)-dependent oxidoreductase families (designated DLO1 and DLO2 for DXR-II-like oxidoreductases 1 and 2). Our analyses identified amino acid changes critical for the acquisition of DXR-II biochemical function through type-I functional divergence, two of them mapping onto key residues for DXR-II activity. DXR-II showed a markedly discontinuous distribution, which was verified at several levels: taxonomic (being predominantly found in Alphaproteobacteria and Firmicutes), metabolic (being mostly found in bacteria with complete functional MEP pathways with or without DXR-I), and phenotypic (as no biological/phenotypic property was found to be preferentially distributed among DXR-II-containing strains, apart from pathogenicity in animals). By performing a thorough comparative sequence analysis of GC content, 3:1 dinucleotide frequencies, codon usage and codon adaptation indexes (CAI) between DXR-II sequences and their corresponding genomes, we examined the role of horizontal gene transfer (HGT), as opposed to an scenario of massive gene loss, in the evolutionary origin and diversification of the DXR-II subfamily in bacteria. Conclusions Our analyses support a single origin of the DXR-II family through functional divergence, in which const

Published
2013

35. Analysis of Procollagen C-Proteinase Enhancer-1/Glycosaminoglycan Binding Sites and of the Potential Role of Calcium Ions in the Interaction.

Author

Potthoff, Jan, Bojarski, Krzysztof K., Kohut, Gergely, Lipska, Agnieszka G., Liwo, Adam, Kessler, Efrat, Ricard-Blum, Sylvie, and Samsonov, Sergey A.

Subjects
CALCIUM ions, GLYCOSAMINOGLYCANS, COLLAGEN, EXTRACELLULAR matrix proteins, BINDING sites, SURFACE plasmon resonance
Abstract

In this study, we characterize the interactions between the extracellular matrix protein, procollagen C-proteinase enhancer-1 (PCPE-1), and glycosaminoglycans (GAGs), which are linear anionic periodic polysaccharides. We applied molecular modeling approaches to build a structural model of full-length PCPE-1, which is not experimentally available, to predict GAG binding poses for various GAG lengths, types and sulfation patterns, and to determine the effect of calcium ions on the binding. The computational data are analyzed and discussed in the context of the experimental results previously obtained using surface plasmon resonance binding assays. We also provide experimental data on PCPE-1/GAG interactions obtained using inhibition assays with GAG oligosaccharides ranging from disaccharides to octadecasaccharides. Our results predict the localization of GAG-binding sites at the amino acid residue level onto PCPE-1 and is the first attempt to describe the effects of ions on protein-GAG binding using modeling approaches. In addition, this study allows us to get deeper insights into the in silico methodology challenges and limitations when applied to GAG-protein interactions. [ABSTRACT FROM AUTHOR]

Published
2019
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36. Secondary Structure in Free and Assisted Modeling of Proteins with the Coarse-Grained UNRES Force Field.

Author

Lubecka EA, Czaplewski C, Sieradzan AK, Lipska AG, Dziadek Ł, and Liwo A

Subjects
Computational Biology methods, Models, Molecular, Proteins chemistry, Thermodynamics, Protein Structure, Secondary, Molecular Dynamics Simulation
Abstract

Secondary structure is a solid scaffold on which the three-dimensional structure of a protein is built. Therefore, care must be taken to reproduce the secondary structure as accurately as possible in the simulations of protein systems. In this chapter, we summarize the physics-based energy terms that govern secondary-structure formation, the auxiliary restraints on secondary structure derived from bioinformatics and from the experimental data, and the role of those in the modeling of protein structures, dynamics, and thermodynamics with the physics-based coarse-grained UNRES force field. Examples illustrating the methodology discussed and further directions of development are presented., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Published
2025
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37. Mean-Field Coupling Between Local Interactions in Proteins in Relation to Chirality, Secondary, and Supersecondary Structure Formation, and Allostery.

Author

Liwo A, Sikorska C, Lipska AG, Sieradzan AK, Atmaca S, and Czaplewski C

Subjects
Molecular Dynamics Simulation, Allosteric Regulation, Protein Structure, Secondary, Protein Conformation, Models, Molecular, Proteins chemistry
Abstract

Coarse graining is usually considered as a tool to extend the time and size scale of simulations. However, leaving out the atomistic details to keep their fingerprints in a coarse-grained model also enables us to understand better structure formation and dynamics. In this chapter, by using our scale-consistent theory of coarse graining, we demonstrate that the coarse-grained terms corresponding to the coupling between local conformational states of amino-acid residues explain secondary-structure propagation along polypeptide backbone to stabilize α -helices and β -strands in proteins and direct the loops preceding and following such segments of protein structure. These and related correlations are probably the still missing terms in both physics- and knowledge-based approaches to protein-structure modeling, including AlphaFold. We also show that the chirality of coarse-grained torsional potentials and, thereby, that of polypeptide backbone emerge from putting together achiral site-based torsional potentials given the phase shift due to residue chirality, and that the improper-torsional potentials that correspond to the coupling between local conformational states of the sites adjacent to a given α -carbon atom enable us to model amino-acid-residue enantiomerization., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Published
2025
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38. Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field.

Author

Sieradzan AK, Czaplewski C, Krupa P, Mozolewska MA, Karczyńska AS, Lipska AG, Lubecka EA, Gołaś E, Wirecki T, Makowski M, Ołdziej S, and Liwo A

Subjects
Entropy, Molecular Dynamics Simulation, Protein Folding, Proteins, Protein Conformation
Abstract

The physics-based united-residue (UNRES) model of proteins ( www.unres.pl ) has been designed to carry out large-scale simulations of protein folding. The force field has been derived and parameterized based on the principles of statistical-mechanics, which makes it independent of structural databases and applicable to treat nonstandard situations such as, proteins that contain D-amino-acid residues. Powered by Langevin dynamics and its replica-exchange extensions, UNRES has found a variety of applications, including ab initio and database-assisted protein-structure prediction, simulating protein-folding pathways, exploring protein free-energy landscapes, and solving biological problems. This chapter provides a summary of UNRES and a guide for potential users regarding the application of the UNRES package in a variety of research tasks., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)

Published
2022
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