Sequence alignment in modeling MCQs With Answer

Sequence alignment in modeling MCQs With Answer

This quiz collection is tailored for M.Pharm students studying Bioinformatics and Computational Biotechnology. It focuses on sequence alignment concepts essential for computational modeling, homology-based structure prediction, and comparative analyses used in drug discovery and pharmacogenomics. Questions cover pairwise and multiple sequence alignment algorithms (Needleman–Wunsch, Smith–Waterman, progressive and iterative methods), scoring systems (PAM, BLOSUM, log-odds, gap penalties), statistical significance (E-value, bit score), and practical implications for homology modeling and structure-based design. Each MCQ includes plausible alternatives and a clear answer to reinforce understanding and prepare students for exams and research applications.

Q1. What is the primary goal of sequence alignment in computational modeling?

• To calculate molecular weight of sequences
• To identify homologous regions that imply evolutionary or functional relationships
• To predict secondary structure from primary sequence
• To determine solubility of a protein

Correct Answer: To identify homologous regions that imply evolutionary or functional relationships

Q2. Which statement best describes the Needleman–Wunsch algorithm?

• It performs local alignment using dynamic programming
• It performs global alignment of two sequences using dynamic programming
• It constructs profile hidden Markov models
• It is an iterative database search method

Correct Answer: It performs global alignment of two sequences using dynamic programming

Q3. Smith–Waterman algorithm is most appropriate when you want to:

• Align whole genomes end-to-end
• Find the best local matching subsequence between two sequences
• Generate phylogenetic trees from whole alignments
• Translate nucleotide to amino acid sequences

Correct Answer: Find the best local matching subsequence between two sequences

Q4. What does BLOSUM62 represent in protein alignment?

• A nucleotide scoring matrix for ribosomal RNA
• A protein substitution matrix derived from conserved blocks clustered at 62% identity
• A gap penalty scheme with 62 as the opening cost
• An algorithm for global alignment optimized for 62 residues

Correct Answer: A protein substitution matrix derived from conserved blocks clustered at 62% identity

Q5. PAM substitution matrices are based on which concept?

• Observed substitutions in distantly related proteins without evolutionary modeling
• An evolutionary model estimating substitutions per 100 residues, extrapolated through Markov processes
• A clustering of local ungapped blocks at fixed identity thresholds
• A nucleotide transition/transversion rate table

Correct Answer: An evolutionary model estimating substitutions per 100 residues, extrapolated through Markov processes

Q6. In alignment scoring, what is the difference between gap opening and gap extension penalties?

• Opening penalizes starting a gap; extension penalizes each additional residue in the gap
• Opening penalizes long gaps; extension penalizes short gaps only
• Opening applies to nucleotides, extension applies to amino acids
• There is no difference; both are applied equally per residue

Correct Answer: Opening penalizes starting a gap; extension penalizes each additional residue in the gap

Q7. PSI-BLAST improves sensitivity by:

• Using a fixed BLOSUM62 matrix for every iteration
• Constructing a position-specific scoring matrix (PSSM) from multiple alignments iteratively
• Performing only global alignments against the database
• Ignoring low complexity regions by default and not updating scores

Correct Answer: Constructing a position-specific scoring matrix (PSSM) from multiple alignments iteratively

Q8. Which approach is commonly used for multiple sequence alignment (MSA) in practical modeling workflows?

• Progressive alignment algorithms like ClustalW or MAFFT that build alignments stepwise
• Exclusive use of pairwise Smith–Waterman for every pair without guide trees
• Random shuffling of sequences followed by consensus selection
• Translation of proteins to nucleotides before aligning

Correct Answer: Progressive alignment algorithms like ClustalW or MAFFT that build alignments stepwise

Q9. A profile hidden Markov model (HMM) is best described as:

• A deterministic method for global alignment without probabilities
• A statistical model that encodes position-specific emission and transition probabilities from an MSA
• A simple pairwise substitution matrix for nucleotides
• A technique for molecular dynamics simulation

Correct Answer: A statistical model that encodes position-specific emission and transition probabilities from an MSA

Q10. In BLAST results, the E-value indicates:

• The exact evolutionary distance between sequences
• The expected number of alignments with a given score that would occur by chance in the database
• The alignment length in codons
• The percent identity divided by alignment length

Correct Answer: The expected number of alignments with a given score that would occur by chance in the database

Q11. Why is bit score used alongside raw alignment scores?

• Because bit scores are affected by database size and cannot be compared across searches
• To normalize raw scores so results from different searches or scoring systems can be compared
• Bit score indicates the number of identical residues directly
• Bit score replaces E-value for significance testing only in nucleotide alignments

Correct Answer: To normalize raw scores so results from different searches or scoring systems can be compared

Q12. A log-odds substitution score is calculated as:

• The log of the product of background frequencies of two residues
• The log of the ratio between the observed substitution probability and the expected background probability
• The sum of gap opening and extension penalties
• The average hydrophobicity difference between residues

Correct Answer: The log of the ratio between the observed substitution probability and the expected background probability

Q13. For reliable homology (comparative) modeling, a commonly cited minimum sequence identity between target and template is:

• Below 10% identity
• Approximately 20% identity or lower
• Above ~30% sequence identity for good model accuracy
• Exactly 100% identity is required

Correct Answer: Above ~30% sequence identity for good model accuracy

Q14. Structural alignment differs from sequence alignment primarily because it:

• Uses only nucleotide sequences to align secondary structures
• Aligns three-dimensional coordinates to maximize structural superposition and similarity
• Is faster and less computationally intensive than sequence alignment
• Relies exclusively on substitution matrices like BLOSUM

Correct Answer: Aligns three-dimensional coordinates to maximize structural superposition and similarity

Q15. In homology modeling, the most critical step that depends on accurate sequence alignment is:

• Energy minimization of the final model
• Selection and placement of template-derived backbone coordinates for conserved regions
• Converting the model into a ligand interaction map
• Running molecular dynamics without initial restraints

Correct Answer: Selection and placement of template-derived backbone coordinates for conserved regions

Q16. What is the purpose of codon-aware or back-translation alignments in comparative studies?

• To align protein sequences ignoring synonymous codon differences
• To convert protein alignments back to nucleotide alignments preserving codon boundaries for evolutionary analysis
• To replace amino acids with stop codons for frame detection
• To simplify alignment by removing introns

Correct Answer: To convert protein alignments back to nucleotide alignments preserving codon boundaries for evolutionary analysis

Q17. How can incorrectly placed gaps in a target–template alignment affect a homology model?

• They only affect ligand binding predictions but not backbone geometry
• They can misplace loops or breaks, causing large structural errors in modeled regions
• Gaps have no effect because modeling ignores indels
• They always improve model quality by reducing steric clashes

Correct Answer: They can misplace loops or breaks, causing large structural errors in modeled regions

Q18. How are BLOSUM matrices derived?

• From a single pairwise alignment of model proteins
• From aligned, ungapped blocks of conserved regions across diverse proteins clustered at a chosen identity threshold
• By simulating evolutionary substitutions using Markov chain Monte Carlo exclusively
• By measuring transition/transversion ratios in nucleotide alignments

Correct Answer: From aligned, ungapped blocks of conserved regions across diverse proteins clustered at a chosen identity threshold

Q19. Which is a common choice for scoring nucleotide alignments compared to proteins?

• Use of BLOSUM62 for nucleotides
• Simple match/mismatch scores often with transition/transversion weighting rather than complex amino-acid substitution matrices
• Applying PAM matrices directly to codons without modification
• Scoring nucleotides by hydrophobicity

Correct Answer: Simple match/mismatch scores often with transition/transversion weighting rather than complex amino-acid substitution matrices

Q20. The theoretical basis used by BLAST to estimate the significance of high-scoring sequence alignments is known as:

• Fisher’s exact test
• Karlin–Altschul statistical theory for local alignment scores
• Bayesian phylogenetic inference
• Principal component analysis of alignment columns

Correct Answer: Karlin–Altschul statistical theory for local alignment scores

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