ArticlePloS one2017
Identification of metal ion binding sites based on amino acid sequences.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 61 citations in OpenAlex.
- Recent advances in structural and functional diversities of cancer lncRNA-encoded peptides: current opportunities and challenges for enhancing cancer diagnosis and treatment.Cancer cell international · 2026Review
- In silico approach on structural and functional characterization of heat shock protein from Sulfobacillus acidophilus.Journal of applied genetics · 2025Article
- Compatibility of intracellular binding: Evolutionary design principles for metal sensors.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Characterization of Tetrathionate Hydrolase from Acidothermophilic Sulfur-Oxidizing ArchaeonInternational journal of molecular sciences · 2025Article
- Article
- M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings.Bioinformatics (Oxford, England) · 2024Article
- Prediction of Protein Ion-Ligand Binding Sites with ELECTRA.Molecules (Basel, Switzerland) · 2023Article
- Differences in pork myosin solubility and structure with various chloride salts and their property of pork gel.Journal of animal science and technology · 2023Article
- A systematicFrontiers in plant science · 2023Article
- In Silico Characterization of the Physicochemical and Biological Properties of the Pink (Bioinformatics and biology insights · 2023Article
- Unveiling the Metal-Dependent Aggregation Properties of the C-terminal Region of Amyloidogenic Intrinsically Disordered Protein Isoforms DPF3b and DPF3a.International journal of molecular sciences · 2022Article
- mebipred: identifying metal-binding potential in protein sequence.Bioinformatics (Oxford, England) · 2022Article
- Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble.Scientific reports · 2022Article
- Development of Cobalt-Binding Peptide Chelate from Human Serum Albumin: Cobalt-Binding Properties and Stability.International journal of molecular sciences · 2022Article
- Prediction of metal ion ligand binding residues by adding disorder value and propensity factors based on deep learning algorithm.Frontiers in genetics · 2022Article
- A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level.BioMed research international · 2022Review
- Ambient Availability of Amino Acids, Proteins, and Iron Impacts Copper Resistance ofFrontiers in cellular and infection microbiology · 2022Article
- Forced Biomineralization: A Review.Biomimetics (Basel, Switzerland) · 2021Review
- Prediction of Metal Ion Binding Sites of Transmembrane Proteins.Computational and mathematical methods in medicine · 2021Article
- Recognition of Metal Ion Ligand-Binding Residues by Adding Correlation Features and Propensity Factors.Frontiers in genetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. Ten metal ions were extracted from the BioLip database: Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+. The analysis showed that Zn2+, Cu2+, Fe2+, Fe3+, and Co2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca2+ was insensitive to hydrophobicity and hydrophilicity information and Mn2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at http://60.31.198.140:8081/metal/HomePage/HomePage.html.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.