The DOI matches its Crossref record, with a small difference in title or year; 1 of the 1 references it cites were found in a registry or an index.
Identification of sequence determinants for the ABHD14 enzymes
Open accessPublished version of a preprint
Abstract
Over the course of evolution, enzymes have developed remarkable functional diversity in catalyzing important chemical reactions across various organisms, and understanding how new enzyme functions might have evolved remains an important question in modern enzymology. To systematically annotate functions, based on their protein sequences and available biochemical studies, enzymes with similar catalytic mechanisms have been clustered together into an enzyme superfamily. Typically, enzymes within a superfamily have similar overall three‐dimensional structures, conserved catalytic residues, but large variations in substrate recognition sites and residues to accommodate the diverse biochemical reactions that are catalyzed within the superfamily. The serine hydrolases are an excellent example of such an enzyme superfamily. Based on known enzymatic activities and protein sequences, they are split almost equally into the serine proteases and metabolic serine hydrolases. Within the metabolic serine hydrolases, there are two outlying members, ABHD14A and ABHD14B, that have high sequence similarity, but their biological functions remained cryptic till recently. While ABHD14A still lacks any functional annotation to date, we recently showed that ABHD14B functions as a lysine deacetylase in mammals. Given their high sequence similarity, automated databases often wrongly assign ABHD14A and ABHD14B as the same enzyme, and therefore, annotating functions to them in various organisms has been problematic. In this article, we present a bioinformatics study coupled with biochemical experiments, which identifies key sequence determinants for both ABHD14A and ABHD14B, and enable better classification for them. In addition, we map these enzymes on an evolutionary timescale and provide a much‐wanted resource for studying these interesting enzymes in different organisms.
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
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Flagged first, then by citations
Research works printed but not linked: 51
- 10.1021/ar000058i · DOI
- 10.1146/annurev.bb.05.060176.001415 · DOI
- 10.1016/j.cbpa.2009.01.014 · DOI
- 10.1146/annurev.biochem.70.1.209 · DOI
- 10.1016/S0065-3233(01)55001-9 · DOI
- 10.1074/jbc.272.49.30591 · DOI
- 10.1016/j.cbpa.2006.08.012 · DOI
- Glasner ME, 2007, Mechanisms of protein evolution and their application to protein engineering, Adv Enzymol Relat Areas Mol Biol, 75, 193
- 10.1038/83048 · DOI
- 10.1186/gb-2000-1-5-reviews0005 · DOI
- 10.1021/bi201312u · DOI
- 10.1021/cr200075y · DOI
- 10.1038/nrd3620 · DOI
- 10.1016/j.sbi.2007.08.003 · DOI
- 10.1016/j.bbalip.2013.01.002 · DOI
- 10.2174/1389203003381405 · DOI
- 10.1016/S0959-440X(99)00037-8 · DOI
- 10.1093/protein/5.3.197 · DOI
- 10.1074/jbc.R109.097600 · DOI
- 10.1016/j.molbrainres.2003.10.004 · DOI · Paper page
- 10.1074/jbc.M312165200 · DOI
- 10.1021/acs.biochem.9b00703 · DOI
- 10.1016/j.jbc.2022.102128 · DOI
- 10.1093/nar/25.17.3389 · DOI · Paper page
- 10.1093/nar/gkv451 · DOI
- 10.1093/bioinformatics/17.7.646 · DOI
- 10.1016/0022-2836(70)90057-4 · DOI · Paper page
- 10.1093/nar/gkf436 · DOI · Paper page
- 10.1093/molbev/msy096 · DOI
- 10.1093/bioinformatics/btl529 · DOI
- 10.1021/acs.biochem.1c00171 · DOI
- 10.1038/s41589-018-0195-0 · DOI
- 10.1073/pnas.96.26.14694 · DOI
- 10.1186/s13068-023-02343-x · DOI
- 10.1093/nar/gkab1061 · DOI · Paper page
- 10.1016/j.bbapap.2015.04.015 · DOI
- 10.1093/gerona/glac105 · DOI
- 10.1093/ejendo/lvad046 · DOI
- 10.1530/ERC-19-0357 · DOI
- 10.1007/s10585-011-9397-5 · DOI
- 10.1007/s10585-014-9672-3 · DOI
- 10.18632/oncotarget.19349 · DOI
- 10.1007/s00439-011-1094-6 · DOI · Paper page
- 10.18632/aging.102399 · DOI
- 10.1186/2040-2392-5-1 · DOI
- 10.3389/fgene.2014.00082 · DOI
- 10.1371/journal.pcbi.1001054 · DOI
- 10.1038/s41598-021-04664-z · DOI
- 10.1186/s12885-019-5554-z · DOI
- 10.1093/pcmedi/pbac017 · DOI
- Chang YS, 2020, Genome‐wide analysis of prognostic alternative splicing signature and splicing factors in lung adenocarcinoma, Genes, 11, 10.3390/genes11111300 · DOI
Metadata
- Authors
- Vaidya, K., Rodrigues, G., Gupta, S., Devarajan, A., Yeolekar, M., Madhusudhan, M. S., & Kamat, S. S.
- Affiliations
- Indian Institute of Science Education and Research Pune (IN)
- Indian Institute of Science Education and Research, Bhopal (IN)
- Corresponding author
- Madhusudhan, M. S.
- Kamat, Siddhesh S.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2023-11-16
- Volume
- 93
- Issue
- 1
- Pages
- 255-266
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W4388768335
- Cited by
- 9
- References
- 1
- Citations by year
- 2026: 5 · 2025: 4
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Funders
- Department of Biotechnology, Ministry of Science and Technology, India
- European Molecular Biology Organization
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- serine hydrolases, enzyme superfamilies, sequence determinants, lysine deacetylases, enzyme evolution, substrate recognition, enzyme classification
- MeSH terms
- Amino Acid Sequence, Animals, Humans, Models, Molecular, Phylogeny, Substrate Specificity, Sequence Alignment, Conserved Sequence, Catalytic Domain, Protein Interaction Domains and Motifs
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