Target identification and drug discovery MCQs With Answer

Target identification and drug discovery MCQs With Answer is a focused quiz resource designed for M.Pharm students studying Bioinformatics and Computational Biotechnology. This set covers core concepts such as target validation, genomic and proteomic approaches, computational target prediction, structural biology, virtual screening, docking, QSAR, ADMET prediction, systems pharmacology, and modern experimental techniques used to prioritize drug targets. Questions emphasize practical understanding of algorithms, databases, experimental validation methods, and decision-making in lead identification and optimization. Use these MCQs to test comprehension, prepare for exams, and reinforce strategies for integrating computational tools with laboratory workflows in contemporary drug discovery.

Q1. Which criterion best describes a ‘druggable’ target in the context of small-molecule drug discovery?

• The target is essential for cell survival but has no known binding pockets
• The target has a well-defined binding pocket suitable for small-molecule interactions
• The target is only expressed in inaccessible tissues
• The target is highly conserved with toxic homologs in humans

Correct Answer: The target has a well-defined binding pocket suitable for small-molecule interactions

Q2. In target identification, which high-throughput experimental approach directly links gene perturbation to phenotype to validate targets?

• Chromatin immunoprecipitation sequencing (ChIP-seq)
• Genome-wide CRISPR knockout/knockdown screening
• Mass spectrometry-based proteomics without perturbation
• In silico homology modeling

Correct Answer: Genome-wide CRISPR knockout/knockdown screening

Q3. Which computational method is most appropriate for predicting potential binding sites on a protein with known 3D structure?

• RNA-Seq differential expression analysis
• Binding site prediction using pocket detection algorithms (e.g., CASTp)
• Phylogenetic tree reconstruction
• BLAST sequence alignment

Correct Answer: Binding site prediction using pocket detection algorithms (e.g., CASTp)

Q4. In ligand-based virtual screening, which model relies on physicochemical descriptors of known actives to predict new actives?

• Homology modeling
• Pharmacophore modeling and QSAR
• Ab initio folding
• Sequence motif search

Correct Answer: Pharmacophore modeling and QSAR

Q5. Which database is commonly used to retrieve protein target sequences and functional annotations for drug discovery?

• PubChem Compound Database
• UniProt Knowledgebase
• KEGG Ligand-only
• GenBank short reads

Correct Answer: UniProt Knowledgebase

Q6. What is the primary advantage of structure-based drug design (SBDD) over purely ligand-based approaches?

• SBDD requires no structural information
• SBDD can exploit 3D protein-ligand interactions to design novel scaffolds
• SBDD ignores protein flexibility completely
• SBDD is always faster than high-throughput screening

Correct Answer: SBDD can exploit 3D protein-ligand interactions to design novel scaffolds

Q7. Molecular docking scoring functions are intended to estimate which property of a ligand-protein complex?

• mRNA expression level
• Binding affinity or binding free energy approximation
• Gene essentiality
• Protein secondary structure

Correct Answer: Binding affinity or binding free energy approximation

Q8. Which of the following best describes ‘polypharmacology’ in drug discovery?

• A drug acting on a single, highly specific target only
• A drug interacting with multiple targets, potentially beneficial or off-target
• Exclusive focus on protein kinases as targets
• Use of only natural products as leads

Correct Answer: A drug interacting with multiple targets, potentially beneficial or off-target

Q9. When using machine learning for target prediction, what is a critical requirement to avoid overfitting and ensure model generalization?

• Using the same dataset for training and testing
• Large, balanced, and well-annotated training datasets with external validation
• Ignoring feature selection entirely
• Maximizing model complexity without cross-validation

Correct Answer: Large, balanced, and well-annotated training datasets with external validation

Q10. In systems biology approaches to target identification, which concept helps identify essential nodes whose perturbation yields desired phenotypic changes?

• Protein crystallography
• Network centrality and pathway analysis
• Simple BLAST homology
• Single-protein enzymology only

Correct Answer: Network centrality and pathway analysis

Q11. Which experimental validation method assesses direct physical interaction between a small molecule and a protein target?

• Surface plasmon resonance (SPR)
• RNA-Seq differential expression
• In silico docking only
• Phylogenetic footprinting

Correct Answer: Surface plasmon resonance (SPR)

Q12. Which property is evaluated during ADMET profiling to reduce late-stage drug attrition?

• Only synthetic accessibility
• Absorption, distribution, metabolism, excretion, and toxicity characteristics
• Chromatographic retention time exclusively
• Sequence alignment score

Correct Answer: Absorption, distribution, metabolism, excretion, and toxicity characteristics

Q13. Homology modeling is most reliable when the template protein has what level of sequence identity to the target?

• Less than 20% sequence identity
• Greater than ~30% sequence identity, ideally above 50%
• Exactly 0% identity
• Only in non-homologous proteins

Correct Answer: Greater than ~30% sequence identity, ideally above 50%

Q14. Which in silico technique uses fragment libraries and iterative assembly to propose novel chemical entities for a given binding site?

• Fragment-based drug design (FBDD)
• RNA interference screening
• Protein microarray hybridization
• Phylogenetic clustering

Correct Answer: Fragment-based drug design (FBDD)

Q15. A high-throughput screening (HTS) campaign primarily aims to:

• Validate a single compound in clinical trials
• Rapidly test thousands to millions of compounds to identify initial hits
• Sequence genomes of patients
• Perform detailed ADME studies on one compound

Correct Answer: Rapidly test thousands to millions of compounds to identify initial hits

Q16. Which metric assesses a gene’s likelihood of being essential for organism survival and thus a potential therapeutic target?

• Hydropathy index
• Gene essentiality scores from genetic screens or databases
• Chromatography peak area
• pI of the encoded protein exclusively

Correct Answer: Gene essentiality scores from genetic screens or databases

Q17. Pharmacophore modeling defines which aspects crucial for ligand binding?

• Spatial arrangement of essential chemical features like H-bond donors/acceptors, hydrophobic centers, and aromatic rings
• Only the primary sequence of the target protein
• Chromosomal location of the gene
• Mass spectrometry fragmentation patterns

Correct Answer: Spatial arrangement of essential chemical features like H-bond donors/acceptors, hydrophobic centers, and aromatic rings

Q18. Which approach is best when no experimental 3D structure of the target is available but multiple ligands are known?

• Ligand-based virtual screening using QSAR and pharmacophore methods
• Direct X-ray crystallography without protein
• Rely solely on metabolic profiling
• Constructing a phylogenetic tree

Correct Answer: Ligand-based virtual screening using QSAR and pharmacophore methods

Q19. In lead optimization, which property is commonly modified to improve a compound’s selectivity and reduce off-target effects?

• Adjusting substituents to modulate steric and electronic interactions with the target binding site
• Changing the gene sequence of the target
• Increasing the compound’s molecular weight indiscriminately
• Removing all polar groups to maximize lipophilicity

Correct Answer: Adjusting substituents to modulate steric and electronic interactions with the target binding site

Q20. Which combined strategy helps prioritize targets by integrating omics data, literature, and druggability assessments?

• Random single-gene selection
• Integrated computational pipeline using genomics, proteomics, network analysis, and druggability scoring
• Only relying on ancient herbal texts
• Exclusive use of one experimental assay without computational input

Correct Answer: Integrated computational pipeline using genomics, proteomics, network analysis, and druggability scoring

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