Inference of macromolecular assemblies from crystalline state.

By Eugene Krissinel, K. Henrick. 2007

9,916 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Computational Biology & Bioinformatics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Torsten Schwede
2. Petras J. Kundrotas
3. Ivan V. Anishchenko
4. Jeffrey J. Gray
5. David T. Jones
6. Ilya A. Vakser
7. Dima Kozakov
8. Chaok Seok

In Materials Chemistry

1. Randy J. Read
2. Torsten Schwede
3. G. Murshudov
4. A. McCoy
5. Yang Zhang
6. Martyn D. Winn
7. Björn Wallner
8. Arne Elofsson

In Molecular Biology

1. Randy J. Read
2. Torsten Schwede
3. Yang Zhang
4. Arne Elofsson
5. Björn Wallner
6. Jeffrey J. Gray
7. G. Murshudov
8. Andriy Kryshtafovych

In Computational Biology & Bioinformatics

1. Randy J. Read
2. Torsten Schwede
3. Yang Zhang
4. G. Murshudov
5. Arne Elofsson
6. A. McCoy
7. David T. Jones
8. Robbie P. Joosten

Citations in the corpus

• Toward the estimation of the absolute quality of individual protein structure models (2010, methodology): “The authors thank Florian Kiefer for his support with generating the oligomeric assemblies from PISA and all members of the group for fruitful discussions.”
• Overview of the CCP4 suite and current developments (2011, methodology): “The quaternary structure of the protein can be analysed with PISA (Krissinel & Henrick, 2007).”
• Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein (2013, methodology): “(Krissinel and Henrick 2007).”
• Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns (2014, background): “Part of complex is the fraction of proteins that are part of a complex according to PISA [49].”
• Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment (2019, neutral): “Indeed, PISA predicts neither interfaces of T138 as stable, whereas EPPIC classifies both interfaces as stable.”
• The challenge of modeling protein assemblies: the CASP12‐CAPRI experiment (2018, background): “33,34 Nonetheless an additional target offered to this prediction Round (T115/T0877) was cancelled after it had been established that the corresponding protein was a monomer.”
• De Novo Structure Prediction of Globular Proteins Aided by Sequence Variation-Derived Contacts (2014, background): “All of the proteins have high quality resolved crystal structures (resolution #1.9 Å), are monomeric according to PISA [41], and both short (,50 residues) and very long (.270 residues) chains were excluded.”
• Applications of sequence coevolution in membrane protein biochemistry (2017, positive): “We find it to be as useful as – and complementary to – other commonly used computational methods such as homology modeling, sequence conservation mapping onto structure using Consurf [146], protein interface analysis using PISA [147], and”
• Exploring Structural Diversity among Adhesion Devices Encoded by Lactococcal P335 Phages with AlphaFold2 (2022, methodology): “Analyses of protein–protein interfaces were performed using the PDBePISA server [46].”
• OPM database and PPM web server: resources for positioning of proteins in membranes (2011, methodology): “Oligomeric states are taken from the PDBe (29) or generated by PISA (30), excluding a number of cases in which biological units were chosen in accordance with publications.”
• Structural insights into Cullin4-RING ubiquitin ligase remodelling by Vpr from simian immunodeficiency viruses (2021, methodology): “Molecular interfaces 623 were analysed using the EBI PDBePISA server [87] (https://www.”