Protein Sequence Analysis
Protein Sequence Analysis - Related Videos
08:53
Strand-Specific Analysis of Proteins at Replicating DNA Strands by Enrichment and Sequencing of Protein-Associated Nascent DNA Method
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2025
Enrichment and sequencing of protein-associated nascent DNA (eSPAN) was developed to detect the relative abundance of a chromatin-associated protein on two replicating DNA strands, thereby revealing molecular insight into chromatin replication and its coupled processes. This protocol describes eSPAN procedures in yeast and mouse embryonic stem (ES) cells.
09:51
Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
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Cited by 2 •
2017
A protocol for the online investigation of protein sequence-structure-dynamics relationships using Bio3D-web is presented.
08:16
Comparative Lesions Analysis Through a Targeted Sequencing Approach
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2019
This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.
07:33
Nanopore DNA Sequencing for Metagenomic Soil Analysis
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Cited by 8 •
2017
Nanopore technology for sequencing biomolecules has wide applications in the life sciences, including identification of pathogens, food safety monitoring, genomic analysis, metagenomic environmental monitoring, and characterization of bacterial antibiotic resistance. In this article, the procedure for metagenomic soil DNA sequencing for species identification using the nanopore sequencing technology is demonstrated.
08:07
Identification of Plasmodesmal Localization Sequences in Proteins In Planta
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Cited by 6 •
2017
Plant intercellular connections, the plasmodesmata (Pd), play central roles in plant physiology and plant-virus interactions. Critical to Pd transport are sorting signals that direct proteins to Pd. However, our knowledge about these sequences is still in its infancy. We describe a strategy to identify Pd localization signals in Pd-targeted proteins.
FAQs
Sequence alignment arranges amino acid sequences so corresponding positions can be compared across proteins. Repeatedly conserved residues or short regions may indicate motifs that contribute to a shared structural or functional role, while broader conserved segments can support recognition of related domains. This comparison helps researchers evaluate functional hypotheses and identify positions that warrant experimental investigation.
These features provide different clues about a protein. A conserved motif is a short recurring sequence pattern, whereas a domain represents a broader region associated with a structural or functional unit. Hydrophobic regions can indicate transmembrane segments or signal peptides. Examining them together gives a more informative interpretation than relying on residue composition alone.
Predictive algorithms convert sequence patterns into testable structural or functional suggestions. By evaluating features such as hydrophobic regions, conserved motifs, and other sequence characteristics, they can predict possible signal peptides, transmembrane segments, or active sites. These predictions do not replace laboratory work, but they help researchers formulate functional hypotheses and select experiments.
A typical workflow begins with the amino acid sequence, followed by alignment with related sequences and comparison against relevant databases. Researchers then examine conserved motifs, domains, residue composition, and hydrophobic regions, using predictive algorithms to assess possible features. The combined results support annotation, functional interpretation, and decisions about which laboratory experiments should follow.
It is useful when researchers need to assign likely functional information to a gene product or decide which hypotheses deserve laboratory testing. Sequence comparisons can reveal homologous proteins, while predicted active sites, signal peptides, transmembrane segments, and domains suggest experimentally relevant features. This makes the approach valuable for annotating genes and prioritizing targets.
Comparing sequences across proteins can reveal homologous relationships and patterns of conservation that help researchers trace molecular evolution. The same evidence can guide biomedical studies by identifying candidate functional regions and prioritizing proteins for investigation. In drug development, sequence-based interpretation can therefore help focus experimental attention on targets with potentially relevant structural or functional features.