The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Ligand Specificity of Brain Lipid-binding Protein
Open accessAbstract
Brain lipid-binding protein (BLBP) is a member of the fatty acid-binding protein (FABP) family. Although BLBP expression in the developing central nervous system is complex, a close correlation between its expression and radial glial differentiation has been observed. Furthermore, antibodies to BLBP can block glial cell differentiation in mixed primary cell cultures. Here we describe the ligand binding properties of BLBP. The binding affinities of BLBP for oleic acid (Kd approximately 0.44 microM) and arachidonic acid (Kd approximately 0.25 microM) are similar to those reported for other FABPs, but BLBP does not bind to palmitic acid or arachidinic acid. These and other experiments establish that BLBP has a strong preference for binding long chain polyunsaturated fatty acids. A probable in vivo ligand for BLBP is docosahexaenoic acid (DHA), since its binding affinity (Kd approximately 10 nM) is the highest yet reported for an FABP/ligand interaction, exceeding even the affinity of retinoic acid for its binding proteins. Furthermore, the requirement of DHA for nervous system development and the coincident expression of BLBP during these developmental stages suggest that the physiologic role of BLBP may involve DHA utilization. Finally, we present a structural model of BLBP/DHA interaction that provides insight into both the structural characteristics important for ligand binding and the effects of specific mutations upon BLBP/ligand interactions.
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
Cites
PROCHECK: a program to check the stereochemical quality of protein structures
Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993) · Journal of Applied Crystallography · doi:10.1107/s0021889892009944 · Cited by 24,581
Primer-Directed Enzymatic Amplification of DNA with a Thermostable DNA Polymerase
Saiki, R. K., Gelfand, D. H., Stoffel, S., Scharf, S. J., Higuchi, R., Horn, G. T., Mullis, K. B., & Erlich, H. A. (1988) · Science · doi:10.1126/science.2448875 · Cited by 17,719
The relation between the divergence of sequence and structure in proteins.
Chothia, C., & Lesk, A. M. (1986) · The EMBO Journal · doi:10.1002/j.1460-2075.1986.tb04288.x · Cited by 2,458
Cited by
Comparative Protein Structure Modeling of Genes and Genomes
Martí-Renom, M. A., Stuart, A. C., Fiser, A., Sánchez, R., Melo, F., & Šali, A. (2000) · Annual Review of Biophysics and Biomolecular Structure · doi:10.1146/annurev.biophys.29.1.291 · Cited by 3,169
Self-citationModeling of loops in protein structures
Fiser, A., Do, R. K. G., & Šali, A. (2000) · Protein Science · doi:10.1110/ps.9.9.1753 · Cited by 2,116
Protein Structure Prediction and Structural Genomics
Baker, D., & Sali, A. (2001) · Science · doi:10.1126/science.1065659 · Cited by 1,587
Self-citationComparative protein structure modeling using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Protein Science · doi:10.1002/cpps.20 · Cited by 730
“…a given binding site (Ring et al., 1993; Li et al., 1996; Selzer et al., 1997; Enyedy et al., 2001; Que et al., 2002); modeling substrate specificity (Xu et al., 1996); in predicting antigenic epitopes (Sali and Blundell, 1993); in simulating protein-protein docking (Vakser, 1995); in inferring…”
BackgroundThe Emerging Functions and Mechanisms of Mammalian Fatty Acid–Binding Proteins
Storch, J., & Corsico, B. (2008) · Annual Review of Nutrition · doi:10.1146/annurev.nutr.27.061406.093710 · Cited by 470
Metadata
- Authors
- Zhong Xu, L., Sánchez, R., Sali, A., & Heintz, N.
- Venue
- Journal of Biological Chemistry
- Publisher
- Elsevier BV
- Published
- 1996-10
- Volume
- 271
- Issue
- 40
- Pages
- 24711-24719
- ISSN
- 0021-9258 (ISSN-L)
- OpenAlex
- W2047444442
- Cited by
- 207
- References
- 3
- FWCI
- 7.03
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Ligand Specificity of Brain Lipid-binding Protein. https://app.cochat.ai/papers/10.1074/jbc.271.40.24711
- The paper
- Zhong Xu, L., Sánchez, R., Sali, A., & Heintz, N. (1996). Ligand Specificity of Brain Lipid-binding Protein. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.271.40.24711
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.