This set of Bioinformatics Multiple Choice Questions & Answers (MCQs) focuses on “Post translational Modification”.
1. Which of the following is a wrong statement?
a) To assume biological activity, many nascent polypeptides have to be covalently modified before or after the folding process
b) In eukaryotic cells most modifications take place in the endoplasmic reticulum and the Golgi apparatus
c) The modifications in eukaryotic cells include proteolytic cleavage; formation of disulfide bonds; addition of phosphoryl, methyl, acetyl, or other groups onto certain amino acid residues
d) The modifications in eukaryotic cells doesn’t include attachment of oligosaccharides or prosthetic groups to create mature proteins
Explanation: Post translational modifications have a great impact on protein function by altering the size, hydrophobicity and overall conformation of the proteins. The modifications can directly influence protein–protein interactions and distribution of proteins to different subcellular locations.
2. Which of the following is a wrong about AutoMotif?
a) It is a web server predicting protein sequence motifs
b) It doesn’t use SVM approach
c) In this process, the query sequence is chopped up into a number of overlapping fragments
d) The overlapping fragments from are query sequence are fed into different kernels (similar to nodes)
Explanation: Hyperplane, which has been trained to recognize known protein sequence motifs, separates the kernels into different classes. Each separation is compared with known motif classes, most of which are related to posttranslational modification. The best match with a known class defines the functional motif.
3. It is important to use bioinformatics tools to predict sites for posttranslational modifications based on specific protein sequences. However, prediction of such modifications can often be difficult because the short lengths of the sequence motifs associated with certain modifications.
Explanation: This often leads to many false-positive identifications. One such example is the known consensus motif for protein phosphorylation, [ST]-x-[RK]. Such a short motif can be found multiple times in almost every protein sequence. Most of the predictions based on this sequence motif alone are likely to be wrong, producing very high rates of false-positives.
4. To minimize false-positive results, a statistical learning process called support vector machine (SVM) can be used to increase the specificity of prediction.
Explanation: This is a data classification method similar to the linear or quadratic discriminant analysis. In this method, the data are projected in a three-dimensional space or even a multidimensional space.
5. In a statistical learning process called support vector machine (SVM), a hyperplane is _____
a) a linear or nonlinear mathematical function
b) nonlinear mathematical function
c) linear mathematical function
d) exponential mathematical function
Explanation: It is used to best separate true signals from noise. The algorithm has more environmental variables included that may be required for the enzyme modification. After training the algorithm with sufficient structural features, it is able to correctly recognize many posttranslational modification patterns.
6. A disulfide bridge is a unique type of _____ modification in which _____ bonds are formed between cysteine residues.
a) posttranslational, covalent
b) translational, covalent
c) translational, ionic
d) posttranslational, ionic
Explanation: Disulfide bonds are important for maintaining the stability of certain types of proteins. The disulfide prediction is the prediction of paring potential or bonding states of cysteines in a protein.
7. Accurate prediction of _____ bonds may also help to predict the _____ dimensional structure of the protein of interest.
a) nitrogen, two
b) nitrogen, three
c) disulfide, three
d) oxygen, three
Explanation: This problem can be tackled by using profiles constructed from multiple sequence alignment. It can also be tackled by using residue contact potentials calculated based on the local sequence environment.
8. Only Advanced neural networks are used to discern long-distance pairwise interactions among cysteine residues.
Explanation: Advanced neural networks or SVM or hidden Markov model (HMM) algorithms are often used to discern long-distance pairwise interactions among cysteine residues. Cysteine is one of the publicly available programs specialized in disulfide prediction.
9. Cysteine doesn’t make predictions by building profiles.
Explanation: Is a web server that predicts the disulfide bonding states of cysteine residues in a protein sequence by building profiles based on multiple sequence alignment information. A recursive neural network ranks the candidate residues for disulfide formation.
10. ExPASY contains a number of programs to determine posttranslational modifications based on MS molecular mass data.
Explanation: Find Mod is a subprogram that uses experimentally determined peptide fingerprint information to compare the masses of the peptide fragments with those of theoretical peptides. If a difference is found, it predicts a particular type of modification basedona set of predefined rules. It can predict twenty-eight types of modifications, including methylation, phosphorylation, lipidation, and sulfation.
Sanfoundry Global Education & Learning Series – Bioinformatics.
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