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26 results on '"Caballero, Iracema"'

1. Detection of translational noncrystallographic symmetry in Patterson functions.

Author

Caballero, Iracema, Sammito, Massimo D, Afonine, Pavel V, Usón, Isabel, Read, Randy J, and McCoy, Airlie J

Subjects
intensity statistics, maximum likelihood, molecular replacement, translational noncrystallographic symmetry
Abstract

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution.

Published
2021

2. A conserved filamentous assembly underlies the structure of the meiotic chromosome axis.

Author

West, Alan Mv, Rosenberg, Scott C, Ur, Sarah N, Lehmer, Madison K, Ye, Qiaozhen, Hagemann, Götz, Caballero, Iracema, Usón, Isabel, MacQueen, Amy J, Herzog, Franz, and Corbett, Kevin D

Subjects
Chromosomes, Synaptonemal Complex, Animals, Mice, Saccharomyces cerevisiae, Zygosaccharomyces, Arabidopsis, Cell Cycle Proteins, Saccharomyces cerevisiae Proteins, Nuclear Proteins, Chromosomal Proteins, Non-Histone, Two-Hybrid System Techniques, Protein Interaction Mapping, Meiosis, Recombination, Genetic, Kinetics, Haploidy, Mutation, Synchrotrons, Scattering, Radiation, Mass Spectrometry, DNA Breaks, Double-Stranded, Protein Domains, A. thaliana, HORMAD protein, S. cerevisiae, Zygosaccharomyces rouxii, chromosomes, coiled-coil, gene expression, meiotic chromosome axis, meiotic recombination, molecular biophysics, mouse, structural biology, Biochemistry and Cell Biology
Abstract

The meiotic chromosome axis plays key roles in meiotic chromosome organization and recombination, yet the underlying protein components of this structure are highly diverged. Here, we show that 'axis core proteins' from budding yeast (Red1), mammals (SYCP2/SYCP3), and plants (ASY3/ASY4) are evolutionarily related and play equivalent roles in chromosome axis assembly. We first identify 'closure motifs' in each complex that recruit meiotic HORMADs, the master regulators of meiotic recombination. We next find that axis core proteins form homotetrameric (Red1) or heterotetrameric (SYCP2:SYCP3 and ASY3:ASY4) coiled-coil assemblies that further oligomerize into micron-length filaments. Thus, the meiotic chromosome axis core in fungi, mammals, and plants shares a common molecular architecture, and likely also plays conserved roles in meiotic chromosome axis assembly and recombination control.

Published
2019

3. ARCIMBOLDO at low resolution: Verification for coiled coils and globular proteins.

Author

Caballero, Iracema, Castellví, Albert, Triviño, Josep, Jiménez, Elisabet, Soler, Nicolas, Borges, Rafael Junqueira, and Usón, Isabel

Abstract

Crystallography at low resolution must determine the atomic model from less experimental observations, which is challenging in the absence of a model. In addition, model bias is more severe when independent experimental data are scarce. Our methods solve the phase problem by combining the location of accurate model fragments using Phaser with density modification and interpretation of the resulting maps using SHELXE. From a partial, correct structure, the density modification process and the stereochemical constraints draw the rest of the structure, validating the result. This same principle is now exploited at low resolution. Coiled coils are important, ubiquitous structures but notoriously difficult to phase and to predict. Both correct solutions and incorrect ones are poorly discriminated by the crystallographic figures of merit as long as helices are correctly oriented. We incorporate coiled‐coil verification, designed to set up competing, incompatible structural hypotheses to probe both the results and establish the power of the data to discriminate them. Efficiency of coiled‐coil phasing and validation in test cases from 3 to 4 Å is demonstrated in ARCIMBOLDO_LITE, placing single helices, and in ARCIMBOLDO_SHREDDER, with fragments derived from AlphaFold models. SHELXE tracing at low resolution has been enhanced, maintaining its local character but extending the environment assessment. For non‐helical structures, verification is demonstrated in the fragment location process. Its use is exemplified with the solution of the VSR1 structure at 3.5 Å, depending on LLG optimization and the emergence of new features in the electron density. Relying on verification, we have extended the use of the ARCIMBOLDO software to low resolution. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Predicted models and CCP4

Author

Simpkin, Adam J., primary, Caballero, Iracema, additional, McNicholas, Stuart, additional, Stevenson, Kyle, additional, Jiménez, Elisabet, additional, Sánchez Rodríguez, Filomeno, additional, Fando, Maria, additional, Uski, Ville, additional, Ballard, Charles, additional, Chojnowski, Grzegorz, additional, Lebedev, Andrey, additional, Krissinel, Eugene, additional, Usón, Isabel, additional, Rigden, Daniel J., additional, and Keegan, Ronan M., additional

Published
2023
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5. Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER

Author

Ministerio de Ciencia e Innovación (España), Science and Technology Facilities Council (UK), Medina, Ana [0000-0001-7146-8987], Jiménez, Elisabet [0000-0001-7521-8619], Caballero, Iracema [0000-0001-8992-4194], Sammito, Massimo D. [0000-0002-8346-9247], Medina, Ana, Jiménez, Elisabet, Caballero, Iracema, Castellví, Albert, Triviño, Josep, Alcorlo, Martín, Molina, Rafael, Hermoso, Juan A., Sammito, Massimo D., Borges, Rafael J., Usón, Isabel, Ministerio de Ciencia e Innovación (España), Science and Technology Facilities Council (UK), Medina, Ana [0000-0001-7146-8987], Jiménez, Elisabet [0000-0001-7521-8619], Caballero, Iracema [0000-0001-8992-4194], Sammito, Massimo D. [0000-0002-8346-9247], Medina, Ana, Jiménez, Elisabet, Caballero, Iracema, Castellví, Albert, Triviño, Josep, Alcorlo, Martín, Molina, Rafael, Hermoso, Juan A., Sammito, Massimo D., Borges, Rafael J., and Usón, Isabel

Abstract

Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios.

Published
2022

6. The CCP4 suite: integrative software for macromolecular crystallography

Author

Agirre, Jon, Atanasova, Mihaela, Bagdonas, Haroldas, Ballard, Charles B., Basle, Arnaud, Beilsten-Edmands, James, Borges, Rafael J., Brown, David G., Burgos-Marmol, J. Javier, Berrisford, John M., Bond, Paul S., Caballero, Iracema, Catapano, Lucrezia, Chojnowski, Grzegorz, Cook, Atlanta G., Cowtan, Kevin D., Croll, Tristan I., Debreczeni, Judit E., Devenish, Nicholas E., Dodson, Eleanor J., Drevon, Tarik R., Emsley, Paul, Evans, Gwyndaf, Evans, Phil R., Fando, Maria, Foadi, James, Fuentes-Montero, Luis, Garman, Elspeth F., Gerstel, Markus, Gildea, Richard J., Hatti, Kaushik, Hekkelman, Maarten L., Heuser, Philipp, Hoh, Soon Wen, Hough, Michael A., Jenkins, Huw T., Jimenez, Elisabet, Joosten, Robbie P., Keegan, Ronan M., Keep, Nicholas, Krissinel, Eugene B., Kolenko, Petr, Kovalevskiy, Oleg, Lamzin, Victor S., Lawson, David M., Lebedev, Andrey A., Leslie, Andrew G. W., Lohkamp, Bernhard, Long, Fei, Maly, Martin, McCoy, Airlie J., McNicholas, Stuart J., Medina, Ana, Millan, Claudia, Murray, James W., Murshudov, Garib N., Nicholls, Robert A., Noble, Martin E. M., Oeffner, Robert, Pannu, Navraj S., Parkhurst, James M., Pearce, Nicholas, Pereira, Joana, Perrakis, Anastassis, Powell, Harold R., Read, Randy J., Rigden, Daniel J., Rochira, William, Sammito, Massimo, Rodriguez, Filomeno Sanchez, Sheldrick, George M., Shelley, Kathryn L., Simkovic, Felix, Simpkin, Adam J., Skubak, Pavol, Sobolev, Egor, Steiner, Roberto A., Stevenson, Kyle, Tews, Ivo, Thomas, Jens M. H., Thorn, Andrea, Trivino Valls, Josep, Uski, Ville, Uson, Isabel, Vagin, Alexei, Velankar, Sameer, Vollmar, Melanie, Walden, Helen, Waterman, David, Wilson, Keith S., Winn, Martyn D., Winter, Graeme, Wojdyr, Marcin, Yamashita, Keitaro, Agirre, Jon, Atanasova, Mihaela, Bagdonas, Haroldas, Ballard, Charles B., Basle, Arnaud, Beilsten-Edmands, James, Borges, Rafael J., Brown, David G., Burgos-Marmol, J. Javier, Berrisford, John M., Bond, Paul S., Caballero, Iracema, Catapano, Lucrezia, Chojnowski, Grzegorz, Cook, Atlanta G., Cowtan, Kevin D., Croll, Tristan I., Debreczeni, Judit E., Devenish, Nicholas E., Dodson, Eleanor J., Drevon, Tarik R., Emsley, Paul, Evans, Gwyndaf, Evans, Phil R., Fando, Maria, Foadi, James, Fuentes-Montero, Luis, Garman, Elspeth F., Gerstel, Markus, Gildea, Richard J., Hatti, Kaushik, Hekkelman, Maarten L., Heuser, Philipp, Hoh, Soon Wen, Hough, Michael A., Jenkins, Huw T., Jimenez, Elisabet, Joosten, Robbie P., Keegan, Ronan M., Keep, Nicholas, Krissinel, Eugene B., Kolenko, Petr, Kovalevskiy, Oleg, Lamzin, Victor S., Lawson, David M., Lebedev, Andrey A., Leslie, Andrew G. W., Lohkamp, Bernhard, Long, Fei, Maly, Martin, McCoy, Airlie J., McNicholas, Stuart J., Medina, Ana, Millan, Claudia, Murray, James W., Murshudov, Garib N., Nicholls, Robert A., Noble, Martin E. M., Oeffner, Robert, Pannu, Navraj S., Parkhurst, James M., Pearce, Nicholas, Pereira, Joana, Perrakis, Anastassis, Powell, Harold R., Read, Randy J., Rigden, Daniel J., Rochira, William, Sammito, Massimo, Rodriguez, Filomeno Sanchez, Sheldrick, George M., Shelley, Kathryn L., Simkovic, Felix, Simpkin, Adam J., Skubak, Pavol, Sobolev, Egor, Steiner, Roberto A., Stevenson, Kyle, Tews, Ivo, Thomas, Jens M. H., Thorn, Andrea, Trivino Valls, Josep, Uski, Ville, Uson, Isabel, Vagin, Alexei, Velankar, Sameer, Vollmar, Melanie, Walden, Helen, Waterman, David, Wilson, Keith S., Winn, Martyn D., Winter, Graeme, Wojdyr, Marcin, and Yamashita, Keitaro

Abstract

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world., Funding Agencies|Royal Society [UF160039, URF\R\221006, RGF/R1/181006]; UK Engineering and Physical Sciences Research Council (EPSRC) [EP/R513386/1]; BBSRC [BB/S007105/1, BB/S007083/1, BB/T012935/1, BB/S005099/1, BB/S007040/1]; European Union [871037]; CCP4; Medical Research Council as part of United Kingdom Research and Innovation; UK Research and Innovation: MRC [MC_UP_A025_1012]; European Molecular Biology Laboratory-European Bioinformatics Institute; German Federal Ministry of Education and Research [05K19WWA, 05K22GU5]; Deutsche Forschungsgemeinschaft [TH2135/2-1]; MEYS CR [CZ.02.1.01/0.0/0.0/16_019/0000778]; Czech Academy of Sciences [86652036]; CCP4/STFC [521862101]; iNEXT [653706]; iNEXT-Discovery [871037]; West-Life [675858]; EOSC-Life - Horizon 2020 program of the European Commission [824087]; Netherlands Organization for Scientific Research (NWO) [722.011.011, 723.013.003]; Dutch Cancer Society; Dutch Ministry of Health, Welfare and Sport; Wellcome Trust [209407/Z/17/Z]; Wellcome Trust SRF [200898]; Wellcome Centre for Cell Biology core grant [203149]; STFC-UK/CCP4: Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW; Spanish MICINN/AEI/FEDER/UE [PID2021-128751NB-I00]; NWOApplied Sciences and Engineering Domain; CCP4 [13337, 16219]; Rontgen Angstrom Cluster [349-2013-597]; SciLifeLab and Wallenberg Data Driven Life Science Program [KAW 2020.0239]; Dutch Research Council (NWO) [VI.Veni.192.143]; EMBO fellowship [ALTF 609-2017]; EPSRC [EP/G037280/1]; BBSRC Institute Strategic Programme Grants [BB/P012523/1, BB/P012574/1]; STFC/CCP4 [7920 S2 2020 007]

Published
2023
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7. Predicted models and CCP4

Author

University of Liverpool, Diamond Light Source (UK), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Simpkin, A. J., Caballero, Iracema, McNicholas, S., Stevenson, Kyle, Jiménez, Elisabet, Sánchez Rodríguez, Filomeno, Fando, M., Uski, V., Ballard, Charles B., Chojnowski, G., Lebedev, Andrey, Krissinel, E., Usón, Isabel, Rigden, D. J., Keegan, R. M., University of Liverpool, Diamond Light Source (UK), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Simpkin, A. J., Caballero, Iracema, McNicholas, S., Stevenson, Kyle, Jiménez, Elisabet, Sánchez Rodríguez, Filomeno, Fando, M., Uski, V., Ballard, Charles B., Chojnowski, G., Lebedev, Andrey, Krissinel, E., Usón, Isabel, Rigden, D. J., and Keegan, R. M.

Abstract

In late 2020, the results of CASP14, the 14th event in a series of competitions to assess the latest developments in computational protein structure-prediction methodology, revealed the giant leap forward that had been made by Google's Deepmind in tackling the prediction problem. The level of accuracy in their predictions was the first instance of a competitor achieving a global distance test score of better than 90 across all categories of difficulty. This achievement represents both a challenge and an opportunity for the field of experimental structural biology. For structure determination by macromolecular X-ray crystallography, access to highly accurate structure predictions is of great benefit, particularly when it comes to solving the phase problem. Here, details of new utilities and enhanced applications in the CCP4 suite, designed to allow users to exploit predicted models in determining macromolecular structures from X-ray diffraction data, are presented. The focus is mainly on applications that can be used to solve the phase problem through molecular replacement.

Published
2023

8. The CCP4 suite: integrative software for macromolecular crystallography

Author

Royal Society (UK), Engineering and Physical Sciences Research Council (UK), European Commission, Medical Research Council (UK), Federal Ministry of Education and Research (Germany), German Research Foundation, Institute of Geology of the Czech Academy of Sciences, Netherlands Organization for Scientific Research, Dutch Cancer Society, Wellcome Trust, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Agirre, Jon, Atanasova, Mihaela, Bagdonas, Haroldas, Ballard, Charles B., Basle, A., Beilsten-Edmands, James, Borges, Rafael J., Brown, D. G., Burgos-Mármol, J. Javier, Berrisford, J., Bond, Paul S., Caballero, Iracema, Catapano, Lucrezia, Chojnowski, G., Cook, Atlanta G., Cowtan, K., Croll, Tristan I., Debreczeny, Judith E., Devenish, Nicholas E., Dodson, Eleanor J., Drevon, Tarik R., Emsley, Paul, Evans, Gwyndaf, Evans, Phil R., Fando, M., Foadi, James, Fuentes-Montero, Luis, Garman, Elspeth F., Gerstel, Markus, Gildea, Richard J., Hatti, Kaushik, Hekkelman, Maarten L., Heuser, Philipp, Wen Hoh, Soon, Hough, Michael A., Jenkins, Huw T., Jiménez, Elisabet, Joosten, Robbie P., Keegan, R. M., Keep, Nicholas, Krissinel, E., Kolenko, Petr, Kovalevskiy, O., Lamzin, V., Lawson, David M., Lebedev, Andrey, Leslie, A. G. W., Lohkamp, B., Long, Fei, Maly, Martin, McCoy, Airlie J., McNicholas, S., Medina, Ana, Millán, Claudia, Murray, James W., Murshudov, Garib, Nicholls, R. A., Noble, Martin E. M., Oeffner, Robert D., Pannu, Navraj S., Parkhurst, James M., Pearce, Nicholas, Pereira, Joana, Perrakis, Anastassis, Powell, Harold R., Read, Randy J., Rigden, D. J., Rochira, William, Sammito, Massimo, Sánchez Rodríguez, Filomeno, Sheldrick, George M., Shelley, Kathryn L., Simkovic, Felix, Simpkin, A. J., Skubák, P., Sobolev, Egor, Steiner, Roberto A., Stevenson, Kyle, Tews, I., Thomas, J. M. H., Thorn, Andrea, Triviño, Josep, Uski, V., Usón, Isabel, Vagin, Alexei, Velankar, Sameer, Vollmar, Melanie, Walden, Helen, Waterman, David, Wilson, Keith S., Winn, Martyn D., Winter, Graeme, Wojdyr, M., Yamashita, Keitaro, Royal Society (UK), Engineering and Physical Sciences Research Council (UK), European Commission, Medical Research Council (UK), Federal Ministry of Education and Research (Germany), German Research Foundation, Institute of Geology of the Czech Academy of Sciences, Netherlands Organization for Scientific Research, Dutch Cancer Society, Wellcome Trust, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Agirre, Jon, Atanasova, Mihaela, Bagdonas, Haroldas, Ballard, Charles B., Basle, A., Beilsten-Edmands, James, Borges, Rafael J., Brown, D. G., Burgos-Mármol, J. Javier, Berrisford, J., Bond, Paul S., Caballero, Iracema, Catapano, Lucrezia, Chojnowski, G., Cook, Atlanta G., Cowtan, K., Croll, Tristan I., Debreczeny, Judith E., Devenish, Nicholas E., Dodson, Eleanor J., Drevon, Tarik R., Emsley, Paul, Evans, Gwyndaf, Evans, Phil R., Fando, M., Foadi, James, Fuentes-Montero, Luis, Garman, Elspeth F., Gerstel, Markus, Gildea, Richard J., Hatti, Kaushik, Hekkelman, Maarten L., Heuser, Philipp, Wen Hoh, Soon, Hough, Michael A., Jenkins, Huw T., Jiménez, Elisabet, Joosten, Robbie P., Keegan, R. M., Keep, Nicholas, Krissinel, E., Kolenko, Petr, Kovalevskiy, O., Lamzin, V., Lawson, David M., Lebedev, Andrey, Leslie, A. G. W., Lohkamp, B., Long, Fei, Maly, Martin, McCoy, Airlie J., McNicholas, S., Medina, Ana, Millán, Claudia, Murray, James W., Murshudov, Garib, Nicholls, R. A., Noble, Martin E. M., Oeffner, Robert D., Pannu, Navraj S., Parkhurst, James M., Pearce, Nicholas, Pereira, Joana, Perrakis, Anastassis, Powell, Harold R., Read, Randy J., Rigden, D. J., Rochira, William, Sammito, Massimo, Sánchez Rodríguez, Filomeno, Sheldrick, George M., Shelley, Kathryn L., Simkovic, Felix, Simpkin, A. J., Skubák, P., Sobolev, Egor, Steiner, Roberto A., Stevenson, Kyle, Tews, I., Thomas, J. M. H., Thorn, Andrea, Triviño, Josep, Uski, V., Usón, Isabel, Vagin, Alexei, Velankar, Sameer, Vollmar, Melanie, Walden, Helen, Waterman, David, Wilson, Keith S., Winn, Martyn D., Winter, Graeme, Wojdyr, M., and Yamashita, Keitaro

Abstract

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Published
2023

9. The CCP4 suite: integrative software for macromolecular crystallography

Author

Agirre, Jon, primary, Atanasova, Mihaela, additional, Bagdonas, Haroldas, additional, Ballard, Charles B., additional, Baslé, Arnaud, additional, Beilsten-Edmands, James, additional, Borges, Rafael J., additional, Brown, David G., additional, Burgos-Mármol, J. Javier, additional, Berrisford, John M., additional, Bond, Paul S., additional, Caballero, Iracema, additional, Catapano, Lucrezia, additional, Chojnowski, Grzegorz, additional, Cook, Atlanta G., additional, Cowtan, Kevin D., additional, Croll, Tristan I., additional, Debreczeni, Judit É., additional, Devenish, Nicholas E., additional, Dodson, Eleanor J., additional, Drevon, Tarik R., additional, Emsley, Paul, additional, Evans, Gwyndaf, additional, Evans, Phil R., additional, Fando, Maria, additional, Foadi, James, additional, Fuentes-Montero, Luis, additional, Garman, Elspeth F., additional, Gerstel, Markus, additional, Gildea, Richard J., additional, Hatti, Kaushik, additional, Hekkelman, Maarten L., additional, Heuser, Philipp, additional, Hoh, Soon Wen, additional, Hough, Michael A., additional, Jenkins, Huw T., additional, Jiménez, Elisabet, additional, Joosten, Robbie P., additional, Keegan, Ronan M., additional, Keep, Nicholas, additional, Krissinel, Eugene B., additional, Kolenko, Petr, additional, Kovalevskiy, Oleg, additional, Lamzin, Victor S., additional, Lawson, David M., additional, Lebedev, Andrey A., additional, Leslie, Andrew G. W., additional, Lohkamp, Bernhard, additional, Long, Fei, additional, Malý, Martin, additional, McCoy, Airlie J., additional, McNicholas, Stuart J., additional, Medina, Ana, additional, Millán, Claudia, additional, Murray, James W., additional, Murshudov, Garib N., additional, Nicholls, Robert A., additional, Noble, Martin E. M., additional, Oeffner, Robert, additional, Pannu, Navraj S., additional, Parkhurst, James M., additional, Pearce, Nicholas, additional, Pereira, Joana, additional, Perrakis, Anastassis, additional, Powell, Harold R., additional, Read, Randy J., additional, Rigden, Daniel J., additional, Rochira, William, additional, Sammito, Massimo, additional, Sánchez Rodríguez, Filomeno, additional, Sheldrick, George M., additional, Shelley, Kathryn L., additional, Simkovic, Felix, additional, Simpkin, Adam J., additional, Skubak, Pavol, additional, Sobolev, Egor, additional, Steiner, Roberto A., additional, Stevenson, Kyle, additional, Tews, Ivo, additional, Thomas, Jens M. H., additional, Thorn, Andrea, additional, Valls, Josep Triviño, additional, Uski, Ville, additional, Usón, Isabel, additional, Vagin, Alexei, additional, Velankar, Sameer, additional, Vollmar, Melanie, additional, Walden, Helen, additional, Waterman, David, additional, Wilson, Keith S., additional, Winn, Martyn D., additional, Winter, Graeme, additional, Wojdyr, Marcin, additional, and Yamashita, Keitaro, additional

Published
2023
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11. Detection of translational noncrystallographic symmetry in Patterson functions

Author

Ministerio de Economía y Competitividad (España), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Generalitat de Catalunya, Department of Energy (US), Wellcome Trust, National Institutes of Health (US), European Commission, Caballero, Iracema, Sammito, Massimo, Afonine, Pavel V., Usón, Isabel, Read, Randy J., McCoy, Airlie J., Ministerio de Economía y Competitividad (España), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Generalitat de Catalunya, Department of Energy (US), Wellcome Trust, National Institutes of Health (US), European Commission, Caballero, Iracema, Sammito, Massimo, Afonine, Pavel V., Usón, Isabel, Read, Randy J., and McCoy, Airlie J.

Abstract

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution.

Published
2021

14. A conserved filamentous assembly underlies the structure of the meiotic chromosome axis

Author

National Institutes of Health (US), National Science Foundation (US), Ministerio de Ciencia e Innovación (España), Ministerio de Economía y Competitividad (España), Ludwig Institute for Cancer Research (US), West, Alan MV, Rosenberg, Scott C., Ur, Sarah N., LehmeR, Madison K., Ye, Qiaozhen, Götz, Hagemann, Caballero, Iracema, Usón, Isabel, MacQueen, Amy J., Herzog, Franz, Corbett, Kevin D., National Institutes of Health (US), National Science Foundation (US), Ministerio de Ciencia e Innovación (España), Ministerio de Economía y Competitividad (España), Ludwig Institute for Cancer Research (US), West, Alan MV, Rosenberg, Scott C., Ur, Sarah N., LehmeR, Madison K., Ye, Qiaozhen, Götz, Hagemann, Caballero, Iracema, Usón, Isabel, MacQueen, Amy J., Herzog, Franz, and Corbett, Kevin D.

Abstract

The meiotic chromosome axis plays key roles in meiotic chromosome organization and recombination, yet the underlying protein components of this structure are highly diverged. Here, we show that 'axis core proteins' from budding yeast (Red1), mammals (SYCP2/SYCP3), and plants (ASY3/ASY4) are evolutionarily related and play equivalent roles in chromosome axis assembly. We first identify 'closure motifs' in each complex that recruit meiotic HORMADs, the master regulators of meiotic recombination. We next find that axis core proteins form homotetrameric (Red1) or heterotetrameric (SYCP2:SYCP3 and ASY3:ASY4) coiled-coil assemblies that further oligomerize into micron-length filaments. Thus, the meiotic chromosome axis core in fungi, mammals, and plants shares a common molecular architecture, and likely also plays conserved roles in meiotic chromosome axis assembly and recombination control.

Published
2019

20. ARCIMBOLDOon coiled coils

Author

Caballero, Iracema, primary, Sammito, Massimo, additional, Millán, Claudia, additional, Lebedev, Andrey, additional, Soler, Nicolas, additional, and Usón, Isabel, additional

Published
2018
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21. ARCIMBOLDO on coiled coils

Author

Ministerio de Economía y Competitividad (España), Generalitat de Catalunya, Science and Technology Facilities Council (UK), Soler, Nicolas [0000-0003-1137-1213], Caballero, Iracema, Sammito, Massimo, Millán, Claudia, Lebedev, Andrey, Soler, Nicolas, Usón, Isabel, Ministerio de Economía y Competitividad (España), Generalitat de Catalunya, Science and Technology Facilities Council (UK), Soler, Nicolas [0000-0003-1137-1213], Caballero, Iracema, Sammito, Massimo, Millán, Claudia, Lebedev, Andrey, Soler, Nicolas, and Usón, Isabel

Abstract

ARCIMBOLDO solves the phase problem by combining the location of small model fragments using Phaser with density modification and autotracing using SHELXE. Mainly helical structures constitute favourable cases, which can be solved using polyalanine helical fragments as search models. Nevertheless, the solution of coiled-coil structures is often complicated by their anisotropic diffraction and apparent translational noncrystallographic symmetry. Long, straight helices have internal translational symmetry and their alignment in preferential directions gives rise to systematic overlap of Patterson vectors. This situation has to be differentiated from the translational symmetry relating different monomers. ARCIMBOLDO_LITE has been run on single workstations on a test pool of 150 coiled-coil structures with 15–635 amino acids per asymmetric unit and with diffraction data resolutions of between 0.9 and 3.0 Å. The results have been used to identify and address specific issues when solving this class of structures using ARCIMBOLDO. Features from Phaser v.2.7 onwards are essential to correct anisotropy and produce translation solutions that will pass the packing filters. As the resolution becomes worse than 2.3 Å, the helix direction may be reversed in the placed fragments. Differentiation between true solutions and pseudo-solutions, in which helix fragments were correctly positioned but in a reverse orientation, was found to be problematic at resolutions worse than 2.3 Å. Therefore, after every new fragment-placement round, complete or sparse combinations of helices in alternative directions are generated and evaluated. The final solution is once again probed by helix reversal, refinement and extension. To conclude, density modification and SHELXE autotracing incorporating helical constraints is also exploited to extend the resolution limit in the case of coiled coils and to enhance the identification of correct solutions. This study resulted in a specialized mode within AR

Published
2018

23. <italic>ARCIMBOLDO</italic> on coiled coils.

Author

Caballero, Iracema, Sammito, Massimo, Millán, Claudia, Lebedev, Andrey, Soler, Nicolas, and Usón, Isabel

Subjects
*POLYALANINE, *AMINO acids, *ANISOTROPY
Abstract

ARCIMBOLDO solves the phase problem by combining the location of small model fragments using Phaser with density modification and autotracing using SHELXE. Mainly helical structures constitute favourable cases, which can be solved using polyalanine helical fragments as search models. Nevertheless, the solution of coiled‐coil structures is often complicated by their anisotropic diffraction and apparent translational noncrystallographic symmetry. Long, straight helices have internal translational symmetry and their alignment in preferential directions gives rise to systematic overlap of Patterson vectors. This situation has to be differentiated from the translational symmetry relating different monomers. ARCIMBOLDO_LITE has been run on single workstations on a test pool of 150 coiled‐coil structures with 15–635 amino acids per asymmetric unit and with diffraction data resolutions of between 0.9 and 3.0 Å. The results have been used to identify and address specific issues when solving this class of structures using ARCIMBOLDO. Features from Phaser v.2.7 onwards are essential to correct anisotropy and produce translation solutions that will pass the packing filters. As the resolution becomes worse than 2.3 Å, the helix direction may be reversed in the placed fragments. Differentiation between true solutions and pseudo‐solutions, in which helix fragments were correctly positioned but in a reverse orientation, was found to be problematic at resolutions worse than 2.3 Å. Therefore, after every new fragment‐placement round, complete or sparse combinations of helices in alternative directions are generated and evaluated. The final solution is once again probed by helix reversal, refinement and extension. To conclude, density modification and SHELXE autotracing incorporating helical constraints is also exploited to extend the resolution limit in the case of coiled coils and to enhance the identification of correct solutions. This study resulted in a specialized mode within ARCIMBOLDO for the solution of coiled‐coil structures, which overrides the resolution limit and can be invoked from the command line (keyword coiled_coil) or ARCIMBOLDO_LITE task interface in CCP4i. [ABSTRACT FROM AUTHOR]

Published
2018
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24. The CCP 4 suite: integrative software for macromolecular crystallography

Author

Agirre, Jon, Atanasova, Mihaela, Bagdonas, Haroldas, Ballard, Charles B., Baslé, Arnaud, Beilsten-Edmands, James, Borges, Rafael J., Brown, David G., Burgos-Mármol, J. Javier, Berrisford, John M., Bond, Paul S., Caballero, Iracema, Catapano, Lucrezia, Chojnowski, Grzegorz, Cook, Atlanta G., Cowtan, Kevin D., Croll, Tristan I., Debreczeni, Judit É., Devenish, Nicholas E., Dodson, Eleanor J., Drevon, Tarik R., Emsley, Paul, Evans, Gwyndaf, Evans, Phil R., Fando, Maria, Foadi, James, Fuentes-Montero, Luis, Garman, Elspeth F., Gerstel, Markus, Gildea, Richard J., Hatti, Kaushik, Hekkelman, Maarten L., Heuser, Philipp, Hoh, Soon Wen, Hough, Michael A., Jenkins, Huw T., Jiménez, Elisabet, Joosten, Robbie P., Keegan, Ronan M., Keep, Nicholas, Krissinel, Eugene B., Kolenko, Petr, Kovalevskiy, Oleg, Lamzin, Victor S., Lawson, David M., Lebedev, Andrey A., Leslie, Andrew G. W., Lohkamp, Bernhard, Long, Fei, Malý, Martin, McCoy, Airlie J., McNicholas, Stuart J., Medina, Ana, Millán, Claudia, Murray, James W., Murshudov, Garib N., Nicholls, Robert A., Noble, Martin E. M., Oeffner, Robert, Pannu, Navraj S., Parkhurst, James M., Pearce, Nicholas, Pereira, Joana, Perrakis, Anastassis, Powell, Harold R., Read, Randy J., Rigden, Daniel J., Rochira, William, Sammito, Massimo, Sánchez Rodríguez, Filomeno, Sheldrick, George M., Shelley, Kathryn L., Simkovic, Felix, Simpkin, Adam J., Skubak, Pavol, Sobolev, Egor, Steiner, Roberto A., Stevenson, Kyle, Tews, Ivo, Thomas, Jens M. H., Thorn, Andrea, Valls, Josep Triviño, Uski, Ville, Usón, Isabel, Vagin, Alexei, Velankar, Sameer, Vollmar, Melanie, Walden, Helen, Waterman, David, Wilson, Keith S., Winn, Martyn D., Winter, Graeme, Wojdyr, Marcin, and Yamashita, Keitaro

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25. Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER

Author

Ana Medina, Elisabet Jiménez, Iracema Caballero, Albert Castellví, Josep Triviño Valls, Martin Alcorlo, Rafael Molina, Juan A. Hermoso, Massimo D. Sammito, Rafael Borges, Isabel Usón, Ministerio de Ciencia e Innovación (España), Science and Technology Facilities Council (UK), Medina, Ana, Jiménez, Elisabet, Caballero, Iracema, and Sammito, Massimo D.

Subjects
Models, Molecular, Predictions, ARCIMBOLDO, Structural Biology, RoseTTAFold, Phasing, Verification, ARCIMBOLDO_SHREDDER, AlphaFold, Fragment-based molecular replacement, Crystallography, X-Ray, Peptides, Model bias
Abstract

11 pags., 5 figs., 3 tabs, Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios., We are grateful to the Spanish MICINN/AEI/FEDER/UE for support through the PGC2018-101370-B-100 project to IU, PID2020-115331GB-I00 to JH, a scholarship (PRE2019-087953) to EJ and a scholarship (BES-2017-080368) associated with the Structural Biology Maria de Maeztu Unit of Excellence (MDM2014-0435-01) to AM. Support from STFC-UK/ CCP4 ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ is gratefully acknowledged.

Published
2022
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26. ARCIMBOLDO at low resolution: Verification for coiled coils and globular proteins.

Author

Caballero I, Castellví A, Triviño J, Jiménez E, Soler N, Borges R, and Usón I

Subjects
Crystallography, X-Ray, Protein Conformation, Software, Proteins chemistry, Models, Molecular
Abstract

Crystallography at low resolution must determine the atomic model from less experimental observations, which is challenging in the absence of a model. In addition, model bias is more severe when independent experimental data are scarce. Our methods solve the phase problem by combining the location of accurate model fragments using Phaser with density modification and interpretation of the resulting maps using SHELXE. From a partial, correct structure, the density modification process and the stereochemical constraints draw the rest of the structure, validating the result. This same principle is now exploited at low resolution. Coiled coils are important, ubiquitous structures but notoriously difficult to phase and to predict. Both correct solutions and incorrect ones are poorly discriminated by the crystallographic figures of merit as long as helices are correctly oriented. We incorporate coiled-coil verification, designed to set up competing, incompatible structural hypotheses to probe both the results and establish the power of the data to discriminate them. Efficiency of coiled-coil phasing and validation in test cases from 3 to 4 Å is demonstrated in ARCIMBOLDO&#95;LITE, placing single helices, and in ARCIMBOLDO&#95;SHREDDER, with fragments derived from AlphaFold models. SHELXE tracing at low resolution has been enhanced, maintaining its local character but extending the environment assessment. For non-helical structures, verification is demonstrated in the fragment location process. Its use is exemplified with the solution of the VSR1 structure at 3.5 Å, depending on LLG optimization and the emergence of new features in the electron density. Relying on verification, we have extended the use of the ARCIMBOLDO software to low resolution., (© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Published
2024
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