Question

Alignment tools and methods HIV virions wrap themselves with a lipid bilayer membrane as they bud off from infected cells; in this viral membrane envelope are "spikes" composed of two different proteins (actually glycoproteins), gp41 and gp120. The gp denotes glycoprotein, and the number indicates their molecular weight in kilodaltons. gp 120 and \(8 p 41\) together form the trimeric envelope spike on the surface of HIV that functions in viral entry into a host cell. The primary receptor for \(g p 120\) is \(\mathrm{CD} 4,\) a protein found mainly on the white blood cells known as T-lymphocytes. gp120 avoids detection by the host immune system through a number of strategies, including rapid changes in sequence due to mutations. In this exercise, you will grab a sequence for gp 120 and -blast" it to find related proteins. Use the "Search database" on the LANL HIV Sequence Database site (www.hiv.lanl.gov/) to find a sequence for \(\mathrm{gp} 120\); the complete gp120 molecule has about 500 amino acids, so a complete DNA sequence will have roughly 1500 base pairs. With the BLAST website (www.ncbi.nlm.nih.gov/ blast), open a new window and select "blastx" under the "Basic BLAST" heading. Copy and paste your approximately 1500 nucleotide sequence of gp 120 into the top box under "Enter Query Sequence." For the database, select "Protein Data Bank proteins (pdb)." What we are doing is having BLAST translate the \(g\) p 120 nucleotide sequence into an amino acid sequence and then compare it with amino acid sequences of proteins in the PDB. Note that there are some proteins that appear multiple times in the PDB because their structures have been analyzed and determined more than once or in different contexts. Finally, push the "BLAST" button and wait for your results to appear on a new page. (a) How does BLAST determine the ranking of the results from your search? (b) For your top search result, identify the percentage of sequence identity with your query sequence. Explain how this number is determined. (c) You will notice that BLAST has used gaps in many of your alignments. What is the evolutionary significance of these gaps? (d) For your top hit, how many alignments with this high a score or better would have been expected by chance? (e) Looking at your ranked list of results and using only the "E-value," which hits do you expect to (possibly) have a genuine evolutionary relationship with your gp 120 sequence and why?

Short answer

To solve this exercise, gp120 sequence would be searched from LANL HIV Sequence Database and the obtained sequence would be used in the blastx function of BLAST to compare with amino acids sequences in Protein Data Bank. The results would be determined with focus on match scores, E-value, percentage identity, gaps and assessed if the sequence has a potential evolutionary relationship. Top results would have higher scores, lower E-values, higher percentage identities, and provide insights into evolutionary changes over time.

Step-by-step solution

Searching gp120 sequence

Go to the LANL HIV Sequence Database site (www.hiv.lanl.gov/) and use the 'Search database' function to find a sequence for gp 120. A complete gp120 molecule has about 500 amino acids, so a complete DNA sequence will have roughly 1500 base pairs.

Applying blastx using BLAST

Visit the BLAST website (www.ncbi.nlm.nih.gov/ blast) and select 'blastx' under the 'Basic BLAST' heading. Copy and paste your approximately 1500 nucleotide sequence of gp 120 into the top box under 'Enter Query Sequence.' Set the database to 'Protein Data Bank proteins (pdb)' and click the 'BLAST' button.

Understanding the ranking system of BLAST

BLAST determines the ranking of the results from your search based on the matching scores, E-value (Expect value) and percentage of identity. Higher scores, lower E-values, and high percentage of identity rank sequences higher.

Identify the Percentage of Sequence Identity

The percentage of sequence identity is determined by dividing the number of identical residues by the total number of residues in the alignment, and multiplying the result by 100.

Understand the evolutionary significance of the gaps

Gaps in many of the alignments indicate evolutionary changes, such as insertions, deletions, or mutations that have occurred over time. They help in tracing the evolutionary history of the species.

Calculate the number of alignments

The number of alignments with this high a score or better that would have been expected by chance are shown under the column 'Max score'. Lower scores are more statistically significant.

Evaluate the evolutionary relationship based on E-value

The 'E-value' represents the number of random hits one can 'expect' to see just by chance. Lower E-values indicate a higher likelihood of genuine evolutionary relationship. Those proteins with low E-values (ideally less than 0.001) could have a potential evolutionary relationship with your gp 120 sequence.

Key concepts

HIV gp120 Protein

The HIV gp120 protein is a crucial component of the HIV virus's structure, found on the surface of the virus itself. It plays a fundamental role in the process of viral entry into host cells. This protein is part of the viral envelope spikes, formed alongside another glycoprotein, gp41. Together, they facilitate the attachment and fusion of the virus with the host cell, specifically by interacting with the CD4 receptor on T-lymphocytes.
gp120 is a glycoprotein, which means it is a protein that has sugar molecules attached to it. The '120' refers to its molecular weight in kilodaltons. Due to these sugars and its continuously changing sequence, gp120 can effectively evade immune detection, making it a challenging target for the immune system. Constant mutation of its genetic sequence allows HIV to persist in the host, leading to difficulties in vaccine development as the protein has a high degree of variability across different viral strains.

Sequence Identity

Sequence identity refers to the measure of how similar two sequences are, which can be a string of DNA, RNA, or protein, when aligned together. It is expressed as a percentage and can be crucial for understanding the evolutionary relationship between the sequences.
When executing a BLAST alignment, sequence identity is calculated by dividing the number of identical bases or amino acids by the total number of bases or amino acids in the alignment. This is then multiplied by 100 to get a percentage. This percentage provides insight into how closely related the query sequence is to the target sequence found in the database.

• A high percentage typically indicates that the two sequences are highly similar or even homologous, meaning they share a common ancestor.
• Lower percentages might suggest distant evolutionary relationships or unrelated sequences affected by convergent evolution.

Understanding this concept is essential for inferring biological functions and evolutionary histories.

Evolutionary Significance

In sequence alignment, observing gaps is of great evolutionary importance. Gaps are introduced to account for the insertions or deletions (indels) in one sequence compared to another. These gaps indicate evolutionary events that may have taken place over millions of years.
These evolutionary changes can provide insights into how different species have evolved from common ancestors. When aligning the sequences of gp120, these gaps can reveal details about the adaptations and mutations the virus has undergone. They demonstrate how the protein has evolved strategies to resist immune system detection and remain effective in invading host cells.
By studying these gaps and the alignments as a whole, researchers can better understand how viruses evolve, which in turn aids in the development of vaccines and antiviral therapies. This knowledge is vital in the fight against fast-evolving pathogens like HIV.

E-value in BLAST

The E-value, or Expect value, in the context of a BLAST search, is a critical measure. It indicates the number of expected hits found by chance when searching a database for sequences similar to the query. Essentially, it helps assess the significance of the match.
Lower E-values represent a higher probability that the match between the query sequence and the database entry is genuine and not due to random chance. An E-value of less than 0.001 is often used as a threshold when determining whether the match might indicate a genuine evolutionary relationship.

• An E-value close to zero means a high level of significance in the match, implying that the sequences may be related!
• E-values are useful in confirming the validity of alignments, assisting researchers in determining which sequences to investigate further for biological relevance.

Thus, understanding how E-values work can be indispensable for researchers and students trying to unravel the complex evolutionary relationships within large sets of genetic data.