The DOI matches its Crossref record.
PIC: Protein Interactions Calculator
Open accessAbstract
Interactions within a protein structure and interactions between proteins in an assembly are essential considerations in understanding molecular basis of stability and functions of proteins and their complexes. There are several weak and strong interactions that render stability to a protein structure or an assembly. Protein Interactions Calculator (PIC) is a server which, given the coordinate set of 3D structure of a protein or an assembly, computes various interactions such as disulphide bonds, interactions between hydrophobic residues, ionic interactions, hydrogen bonds, aromatic-aromatic interactions, aromatic-sulphur interactions and cation-pi interactions within a protein or between proteins in a complex. Interactions are calculated on the basis of standard, published criteria. The identified interactions between residues can be visualized using a RasMol and Jmol interface. The advantage with PIC server is the easy availability of inter-residue interaction calculations in a single site. It also determines the accessible surface area and residue-depth, which is the distance of a residue from the surface of the protein. User can also recognize specific kind of interactions, such as apolar-apolar residue interactions or ionic interactions, that are formed between buried or exposed residues or near the surface or deep inside.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
PRosettaC: Rosetta Based Modeling of PROTAC Mediated Ternary Complexes
Zaidman, D., Prilusky, J., & London, N. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00589 · Cited by 224
2P2Idb: a structural database dedicated to orthosteric modulation of protein–protein interactions
Basse, M. J., Betzi, S., Bourgeas, R., Bouzidi, S., Chetrit, B., Hamon, V., Morelli, X., & Roche, P. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1002 · Cited by 148
Quaternary dynamics of the SecA motor drive translocase catalysis.
Gouridis, G., Karamanou, S., Sardis, M. F., Schärer, M. A., Capitani, G., & Economou, A. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.10.036 · Cited by 57
DLPacker : Deep learning for prediction of amino acid side chain conformations in proteins
Misiura, M., Shroff, R., Thyer, R., & Kolomeisky, A. B. (2022) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26311 · Cited by 51
Dey, D., Nagaraja, V., & Ramakumar, S. (2017) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2016.11.014 · Cited by 46
Discovery of archaeal Fusexins homologous to eukaryotic HAP2/GCS1 gamete fusion proteins
Moi, D., Nishio, S., Li, X., Valansi, C., Langleib, M., Brukman, N. G., Flyak, K., Dessimoz, C., de Sanctis, D., Tunyasuvunakool, K., et al. (2021) · doi:10.1101/2021.10.13.464100 · Cited by 23
Santana, M. J., de Oliveira, A. L., Queiroz Júnior, L. H. K., Mandal, S. M., Matos, C. O., de O. Dias, R., Franco, O. L., & Lião, L. M. (2015) · FEBS Letters · doi:10.1016/j.febslet.2015.01.029 · Cited by 21
The molecular basis for immune dysregulation by the hyperactivated E62K mutant of the GTPase RAC2
Arrington, M. E., Temple, B., Schaefer, A., & Campbell, S. L. (2020) · Journal of Biological Chemistry · doi:10.1074/jbc.ra120.012915 · Cited by 19
García-Ramírez, B., Mares-Mejía, I., Rodríguez-Hernández, A., Cano-Sánchez, P., Torres-Larios, A., Ortega, E., & Rodríguez-Romero, A. (2022) · Communications Biology · doi:10.1038/s42003-022-03718-w · Cited by 16
Shishir, T. A., Jannat, T., & Naser, I. B. (2022) · doi:10.1101/2022.02.21.481269 · Cited by 5
Metadata
- Authors
- Tina, K. G., Bhadra, R., & Srinivasan, N.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-05-08
- Volume
- 35
- Issue
- Web Server
- Pages
- W473-W476
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2110869427
- Cited by
- 867
- References
- 0
- FWCI
- 6.35
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
