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Summary Protein Annotation, Homology & Evolution – Bioinformatics Guide with BLAST, GO Terms & Structure Prediction

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Escrito en
2024/2025

This comprehensive and well-structured guide explains how protein function and evolutionary relationships are determined through bioinformatics tools and structural analysis. Ideal for students of biochemistry, bioinformatics, molecular biology, and medical genetics. What’s Included: Homology-Based Annotation – Predicting protein function using sequence similarity (e.g., BLAST) Gene Ontology (GO) – Understanding function, process, and cellular localization UniProt – Using expert-reviewed databases for protein insights BLAST & PSI-BLAST – How to find similar sequences and distant homologs Interpreting Scores – E-values, identity vs. similarity, alignment metrics Functional Prediction Cautions – Orthologs vs. paralogs, domain-based inference Protein Domains & Conservation – Functional modules, conserved sites MSA, Profiles, and HMMs – Multiple sequence alignment, position-specific scoring matrices, hidden Markov models Phylogenetics – Tree construction, distance matrices, and evolutionary insight Structure Determination – Experimental (X-ray, NMR, Cryo-EM) and AI-driven (AlphaFold, RoseTTAFold) Threading & Fold Recognition – Finding functionally relevant structures when sequence similarity is low Why this note is useful: Connects sequence, structure, and function seamlessly Equips you to use top bioinformatics tools (BLAST, Pfam, UniProt, PSI-BLAST) Explains the evolutionary logic behind function prediction Practical and theoretical — excellent for assignments, projects, or exam prep

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Biochemistry
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Institución
Biochemistry
Grado
Biochemistry

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Subido en
24 de julio de 2025
Número de páginas
7
Escrito en
2024/2025
Tipo
Resumen

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🔬 Understanding Protein Annotation, Homology, and Evolution

A Detailed Guide for College Students




1. Annotation by Homology: Predicting Function from Similarity

When scientists discover a novel gene or protein, it’s like finding a mysterious tool — they
don’t know what it does. To figure it out, they compare the sequence to known proteins
using bioinformatics tools.

Key Principle: Sequences that are significantly similar likely share a common ancestor and
may perform similar biological roles. This is called homology-based annotation.

🔧 How It Works:

 Sequence Alignment: Aligns sequences to detect conserved regions.

 High Similarity = Stronger evidence of shared ancestry and function.

 Tools Used: Algorithms like BLAST find similar sequences quickly even in massive
databases.

✨ Real-World Use:

If a bacterial protein aligns closely with a human enzyme, researchers might infer that both
catalyze similar biochemical reactions.




2. Gene Ontology (GO): Universal Language of Gene Function

GO terms are like metadata for genes, organizing them into structured vocabularies across
three categories:

GO Category What It Describes Examples

Biological Process Biological goal or pathway “DNA replication,” “Apoptosis”

Molecular Function Specific activity at molecular level “ATPase activity,” “DNA binding”

, GO Category What It Describes Examples




Cellular Component Where the activity happens “Nucleus,” “Ribosome”

📘 Why It Matters:

 Standardization helps global research.

 Ensures consistency when comparing gene roles across species and studies.




3. UniProt: The Encyclopedia of Proteins

UniProt (Universal Protein Resource) is the go-to resource for protein information,
containing sequences, structures, annotations, domains, and evolutionary relationships.

 Reviewed Entries (Swiss-Prot): Manually annotated by experts.

 Unreviewed Entries (TrEMBL): Automatically annotated.

🔎 Use Case:

When analyzing a new protein, scientists search UniProt to find similar, well-characterized
entries.




4. BLAST: Fast & Efficient Sequence Comparison

BLAST (Basic Local Alignment Search Tool) is a foundational tool in bioinformatics. It
finds regions of similarity quickly.

⚙️
How BLAST Works:

 Detects short exact matches (seeds).

 Extends these to find longer local alignments.

 Returns top hits ranked by alignment scores.
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