Multiple sequence alignment MCQs With Answer

Multiple sequence alignment MCQs With Answer

This quiz collection on Multiple Sequence Alignment (MSA) is tailored for M.Pharm students studying Bioinformatics and Computational Biotechnology. It provides focused, exam-oriented multiple-choice questions that cover fundamental concepts (algorithms, scoring matrices, gap penalties), advanced topics (consistency methods, HMMs, profile–profile alignment), practical considerations (sequence weighting, structural constraints) and evaluation metrics (sum‑of‑pairs, column score). Each question is followed by four thoughtfully chosen options and the exact correct answer. Use these MCQs to strengthen conceptual understanding and to prepare for viva, internal exams and competitive tests where MSA knowledge is applied to drug target analysis, homology modeling and comparative genomics.

Q1. What is the primary definition of multiple sequence alignment (MSA)?

• Aligning two sequences to find the best pairwise match
• Aligning three or more biological sequences to identify conserved regions
• Predicting tertiary structure from a single protein sequence
• Calculating phylogenetic trees without sequence alignment

Correct Answer: Aligning three or more biological sequences to identify conserved regions

Q2. Which of the following is the most common biological purpose for performing an MSA in pharmaceutical research?

• To determine the GC content of a single sequence
• To identify conserved residues and motifs that may indicate functional or active sites
• To compute molecular dynamics simulations
• To estimate protein solubility directly from raw reads

Correct Answer: To identify conserved residues and motifs that may indicate functional or active sites

Q3. Which statement best describes the progressive alignment strategy used by tools like ClustalW?

• It simultaneously optimizes alignment for all sequences using exact dynamic programming
• It builds an alignment by iteratively refining from a random start without using a guide tree
• It aligns sequences stepwise following a guide tree, and early alignment errors can propagate without revision
• It uses only structural information and ignores sequence similarity

Correct Answer: It aligns sequences stepwise following a guide tree, and early alignment errors can propagate without revision

Q4. Which of the following algorithms is primarily a progressive MSA method?

• ClustalW
• ProbCons (probabilistic consistency)
• MUSCLE with iterative refinement
• T-Coffee with consistency scoring

Correct Answer: ClustalW

Q5. An affine gap penalty in alignment scoring consists of which two components?

• Match score and mismatch score
• Gap opening penalty and gap extension penalty
• Substitution matrix and phylogenetic weight
• Sequence identity and alignment length

Correct Answer: Gap opening penalty and gap extension penalty

Q6. The sum-of-pairs (SP) score for evaluating an MSA is defined as:

• The number of fully conserved columns only
• The average pairwise identity across the entire alignment length
• The sum of scores of all pairwise residue comparisons across all columns
• The score of the best single pairwise alignment among all pairs

Correct Answer: The sum of scores of all pairwise residue comparisons across all columns

Q7. Consistency-based MSA methods (e.g., T-Coffee, ProbCons) improve alignment accuracy by:

• Using only global alignment without pairwise information
• Enforcing that pairwise alignments are consistent with each other via a library or probabilistic model
• Relying solely on gap penalties and ignoring substitution scores
• Aligning sequences based purely on GC content

Correct Answer: Enforcing that pairwise alignments are consistent with each other via a library or probabilistic model

Q8. What is the usual role of a guide tree in progressive MSA?

• To predict secondary structure for each sequence
• To determine the order in which sequences (or profiles) are aligned based on pairwise distances
• To compute exact global optimum alignment across all sequences
• To remove low complexity regions before alignment

Correct Answer: To determine the order in which sequences (or profiles) are aligned based on pairwise distances

Q9. Which substitution matrix is more appropriate for aligning closely related protein sequences?

• BLOSUM45
• BLOSUM62
• BLOSUM80
• PAM250

Correct Answer: BLOSUM80

Q10. When aligning two previously computed multiple sequence alignments, which alignment type is most appropriate?

• Pairwise sequence-to-sequence alignment
• Profile–profile alignment
• Local alignment optimized for short motifs only
• Dot-plot comparison without scoring

Correct Answer: Profile–profile alignment

Q11. Which bioinformatics tool or method is based fundamentally on Hidden Markov Models (HMMs)?

• ClustalW
• MUSCLE
• HMMER
• BLAST

Correct Answer: HMMER

Q12. PAM substitution matrices are characterized by which origin or principle?

• Derived from structure-based superpositions and not from sequence evolution
• Derived from local alignments of viral sequences only
• Built from global alignments of closely related proteins and extrapolated to higher evolutionary distances
• Constructed from randomly mutated synthetic proteins

Correct Answer: Built from global alignments of closely related proteins and extrapolated to higher evolutionary distances

Q13. Why is exact multiple sequence alignment computationally infeasible for many sequences?

• Because dynamic programming cannot handle protein alphabets larger than 4
• Because the search space grows exponentially with the number of sequences and alignment length
• Because substitution matrices cannot be applied to more than two sequences
• Because gap penalties are undefined for more than three sequences

Correct Answer: Because the search space grows exponentially with the number of sequences and alignment length

Q14. Which strategy is commonly used to overcome the error propagation problem of progressive alignment?

• Using only pairwise Smith–Waterman alignments without building an MSA
• Iterative refinement where the alignment is repeatedly re-optimized
• Eliminating gap penalties entirely
• Converting proteins to nucleotides before aligning

Correct Answer: Iterative refinement where the alignment is repeatedly re-optimized

Q15. Incorporating structural (3D) information into MSA is most beneficial when:

• All sequences are nearly identical and structure is irrelevant
• Sequences are distantly related but structures are available to guide alignment of conserved cores
• Only nucleotide sequences are used
• One wants to avoid using substitution matrices

Correct Answer: Sequences are distantly related but structures are available to guide alignment of conserved cores

Q16. What is the purpose of sequence weighting in progressive MSA?

• To prioritize longer sequences regardless of redundancy
• To reduce bias from overrepresented, closely related sequences so conserved positions are not dominated by duplicates
• To convert protein scores to nucleotide scores
• To make gap penalties equal for all sequences

Correct Answer: To reduce bias from overrepresented, closely related sequences so conserved positions are not dominated by duplicates

Q17. T-Coffee improves alignment reliability by creating a library of pairwise alignments. This library is then used to:

• Generate random guide trees for bootstrapping
• Score candidate residue pairings for consistency during progressive alignment
• Remove all gaps before final alignment
• Estimate secondary structure exclusively

Correct Answer: Score candidate residue pairings for consistency during progressive alignment

Q18. The total column (TC) score for an MSA measures:

• The sum of all pairwise substitution scores
• The fraction or number of alignment columns that are exactly identical to a reference alignment
• The average gap length across the alignment
• The GC content of aligned nucleotide columns

Correct Answer: The fraction or number of alignment columns that are exactly identical to a reference alignment

Q19. Which evaluation metric counts correctly aligned residue pairs across all sequence pairs when comparing to a reference alignment?

• Column score (TC)
• Sum-of-pairs (SP) score
• Bootstrap support value
• Root mean square deviation (RMSD)

Correct Answer: Sum-of-pairs (SP) score

Q20. In the context of M.Pharm applications, how is MSA most directly useful for drug discovery?

• Sequencing genomes faster than next-generation sequencing
• Identifying conserved residues and motifs across homologous proteins to guide target validation and structure‑based drug design
• Measuring pharmacokinetic parameters directly from sequence data
• Predicting solubility of small molecules

Correct Answer: Identifying conserved residues and motifs across homologous proteins to guide target validation and structure‑based drug design

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