Podcast
Questions and Answers
What are the three important features that Gene Ontology captures about function?
What are the three important features that Gene Ontology captures about function?
- Molecular Function, Biological Process, Cellular Component (correct)
- Intrinsic Function, External Factor, Gene Family
- Molecular Interaction, Biological Pathway, Cellular Environment
- Enzyme Activity, Cellular Structure, Protein Family
Molecular function refers to the broad biological goals achieved by gene products.
Molecular function refers to the broad biological goals achieved by gene products.
False (B)
What evidence codes in Gene Ontology signify?
What evidence codes in Gene Ontology signify?
The reliability and confidence level of the annotations.
The subcellular structures where a gene product acts are termed __________.
The subcellular structures where a gene product acts are termed __________.
Match the following Gene Ontology terms with their corresponding descriptions:
Match the following Gene Ontology terms with their corresponding descriptions:
Which sources are considered the most reliable for Gene Ontology annotations?
Which sources are considered the most reliable for Gene Ontology annotations?
RNA-seq can be used to identify whether a set of highly expressed genes belongs to a similar GO term.
RNA-seq can be used to identify whether a set of highly expressed genes belongs to a similar GO term.
What is the main risk associated with late patenting in drug development?
What is the main risk associated with late patenting in drug development?
QSAR stands for Quantitative Structure Activity Relationship.
QSAR stands for Quantitative Structure Activity Relationship.
What are the three types of modeling in computer-based drug design?
What are the three types of modeling in computer-based drug design?
The first step in ligand screening is to derive a _____.
The first step in ligand screening is to derive a _____.
Match the following docking methods with their descriptions:
Match the following docking methods with their descriptions:
Which database is known for identifying proteins that interact with a query protein?
Which database is known for identifying proteins that interact with a query protein?
Prosite motifs are useful for identifying patterns in enzyme active sites.
Prosite motifs are useful for identifying patterns in enzyme active sites.
What is the main focus of NetGo2.0 in function prediction?
What is the main focus of NetGo2.0 in function prediction?
The gene ontology prediction challenge is known as _____ which tests function prediction accuracy.
The gene ontology prediction challenge is known as _____ which tests function prediction accuracy.
Match the following databases/tools with their primary function:
Match the following databases/tools with their primary function:
Which approach integrates multiple sources of information for function prediction?
Which approach integrates multiple sources of information for function prediction?
Structure-based approaches may occasionally reveal relationships that are not discernible by sequence alone.
Structure-based approaches may occasionally reveal relationships that are not discernible by sequence alone.
What is the main advantage of structure-based approaches in functional annotation?
What is the main advantage of structure-based approaches in functional annotation?
Pfam uses _____ models to categorize protein domains.
Pfam uses _____ models to categorize protein domains.
What was the major advancement introduced in NetGo3.0?
What was the major advancement introduced in NetGo3.0?
Which scale is NOT mentioned for assessing hydrophobicity?
Which scale is NOT mentioned for assessing hydrophobicity?
Signal peptides are typically cleaved off after directing the protein to its cellular location.
Signal peptides are typically cleaved off after directing the protein to its cellular location.
What does DeepTMHMM use to predict transmembrane structures?
What does DeepTMHMM use to predict transmembrane structures?
Low complexity regions in protein sequences are often replaced with ______ in BLAST searches.
Low complexity regions in protein sequences are often replaced with ______ in BLAST searches.
Match the following terms with their descriptions:
Match the following terms with their descriptions:
What does PONDR-FIT and DISOPRED2 use to predict disorder in proteins?
What does PONDR-FIT and DISOPRED2 use to predict disorder in proteins?
The pLDDT value under 70% indicates a high confidence in AlphaFold predictions.
The pLDDT value under 70% indicates a high confidence in AlphaFold predictions.
What alters the statistical significance scores of sequence alignments?
What alters the statistical significance scores of sequence alignments?
DeepTMHMM predicts how the sequence maps from the N- to the _____ terminus.
DeepTMHMM predicts how the sequence maps from the N- to the _____ terminus.
Regions with low amino acid diversity are informative for protein structure prediction.
Regions with low amino acid diversity are informative for protein structure prediction.
Which of the following statements about fIDPnn is true?
Which of the following statements about fIDPnn is true?
DisProt is considered the gold standard database for intrinsically disordered proteins.
DisProt is considered the gold standard database for intrinsically disordered proteins.
What is the purpose of Clinical Phase I in drug development?
What is the purpose of Clinical Phase I in drug development?
A __________ is a chemically optimized version of a hit designed to enhance therapeutic efficacy.
A __________ is a chemically optimized version of a hit designed to enhance therapeutic efficacy.
Match the clinical development phases with their primary focus:
Match the clinical development phases with their primary focus:
What does the term 'Hit' refer to in drug discovery?
What does the term 'Hit' refer to in drug discovery?
Participants in Clinical Phase III trials are usually healthy volunteers.
Participants in Clinical Phase III trials are usually healthy volunteers.
What is the goal of the Regulatory Phase in drug development?
What is the goal of the Regulatory Phase in drug development?
The database that correlates strongly with disorder predictions from AlphaFold2 pLDDT is called __________.
The database that correlates strongly with disorder predictions from AlphaFold2 pLDDT is called __________.
What are the common functions annotated in fIDPnn predictions?
What are the common functions annotated in fIDPnn predictions?
Flashcards
Gene Ontology (GO)
Gene Ontology (GO)
A controlled vocabulary system used to describe the functions of genes and gene products (proteins and RNA) across all organisms.
Molecular Function
Molecular Function
The specific tasks performed by individual gene products, like binding to a molecule or catalyzing a reaction.
Biological Process
Biological Process
The overall biological objective or goal that a gene product contributes to, such as cell division or metabolism.
Cellular Component
Cellular Component
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Evidence Code
Evidence Code
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Function Prediction
Function Prediction
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GO Term Clustering
GO Term Clustering
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Specific Domain Libraries
Specific Domain Libraries
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Prosite Motifs
Prosite Motifs
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Prosite Profiles
Prosite Profiles
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Interactome Databases
Interactome Databases
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STRING Database
STRING Database
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NetGo2.0
NetGo2.0
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Structure-Based Approach
Structure-Based Approach
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Structural Search
Structural Search
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Similar Fold Search
Similar Fold Search
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QSAR
QSAR
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Redocking
Redocking
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Lock-and-key approach
Lock-and-key approach
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Training on one protein, testing on a homologous protein
Training on one protein, testing on a homologous protein
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DiffDock
DiffDock
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Signal Peptide
Signal Peptide
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Hydrophobic Plot
Hydrophobic Plot
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Low Complexity Region
Low Complexity Region
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Coiled-Coil
Coiled-Coil
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Disordered Protein
Disordered Protein
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Disordered Regions
Disordered Regions
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DeepTMHMM
DeepTMHMM
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SEG Program
SEG Program
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COILS
COILS
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PONDR-FIT and DISOPRED2
PONDR-FIT and DISOPRED2
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Target
Target
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Hit
Hit
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Lead
Lead
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IC50
IC50
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Clinical Phase I
Clinical Phase I
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Clinical Phase II
Clinical Phase II
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Clinical Phase III
Clinical Phase III
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Regulatory Phase
Regulatory Phase
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Sales and Monitoring Phase (Phase IV)
Sales and Monitoring Phase (Phase IV)
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DisProt
DisProt
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Study Notes
Protein Function and Gene Ontology
- Gene ontology (GO) classifies gene products (proteins and RNA) based on their functions.
- GO provides a controlled vocabulary applicable to all organisms, documenting functions beyond what enzyme classification systems offer.
- GO captures three key functional aspects: molecular function, biological process, and cellular component.
- Molecular function defines the tasks performed by a gene product (e.g., GTPase activity).
- Biological process outlines the broader biological goals fulfilled by the gene product (e.g., mitosis).
- Cellular component describes the location or active location of a gene product (e.g., nucleus).
- Evidence codes (e.g., experimental or computational analysis) associated with annotations indicate their reliability.
Function Prediction Approaches
- Protein function prediction uses homology and protein families.
- General homology searches (using BLAST, PSIBLAST, HMMs) compare a query sequence to a database to identify similar sequences.
- Orthologs share function and high sequence identity (often >85%) across species.
- Paralogs, arising from gene duplication, have related but not identical functions within a species, exhibiting lower sequence identity than orthologs.
Homology-Based Predictions and Domain Libraries
- Homology searches identify local similarities (shared domains) between sequences.
- Domains with similar structures may share function, even if the overall protein functions differ.
- Specific Domain Libraries: like InterPro, Prosite, Pfam are used to search for function based on specific motifs/patterns not just overall sequence similarity.
Structure-Based Predictions
- Matching 3D structures (superposition/alignment).
- Comparing functional residues to imply function transfer
- Structural searching helps find similar folds (using tools like DALI, CATH, and Foldseek to determine similar 3D structures).
Advanced Sequence-Based Approaches
- Different prediction approaches combine data sources to make predictions based on interactions or related functions in databases.
- STRING Database: used to identify proteins that interact with a query proteins
- NetGo: machine learning approach
- Combining multiple data sources often improves predictive accuracy and provides a more holistic view.
Transmembrane Region Prediction
- Early methods to predict transmembrane regions: relied on hydrophobic residue runs.
- More advanced methods: utilize hydrophobicity scales, and often combine these methods with machine learning.
Prediction of Disorder
- Some proteins contain unstructured or disordered regions not well represented by typical 3D structures.
- Deep learning algorithms (e.g., DISOPRED2, PONDR-FIT, pIDPnn) are now used to predict disordered regions and functions like binding activities.
- DisProt is a valuable database for intrinsically disordered proteins and regions.
Drug Discovery Pipeline
- Target: A protein or molecule whose activity is modified to achieve therapeutic effects.
- Hit: A compound with a desirable effect (like IC50 ≤ 1 µM).
- Lead: Modified hits to optimize efficacy, reduce toxicity.
- Clinical trials (Phase I-III) evaluate safety, efficacy, and dosage.
- Regulatory approval & sales/monitoring phase follow clinical trials.
Computer-Based Drug Design
- Ligand Screening: Use Quantitative Structure-Activity Relationships (QSAR) and virtual screening to identify potential drug candidates through docking to target protein.
- Docking Methods: Traditional methods use atom-atom interactions to score docking outcomes; advanced methods (like deep learning) offer improved accuracy and incorporate better modeling of conformational changes.
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