Matthew K. Oki Individual Journal 9

Week 9 Individual Journal

Purpose

• Our purpose was to incorporate programs and software while we learned more about proteins, the structure, and the sequences.

Methods & Results

1. Convert DNA Sequences to protein sequences in ExPASY Translate tool
   • Below is an example of the output of the DNA to protein sequence conversion. They are separated into six reading frames.

1. • How do you know which of the six frames is the correct reading frame (without looking up the answer)?
     • We knew the correct reading frame was the one that had a sequence with no stop codon in the entire frame.
2. Find out what is already known about the HIV gp120 envelope protein in the UniProt Knowledgebase (UniProt KB).
   • If you search on the keywords "HIV" and "gp120", in the main UniProt search field, how many results do you get?
     • There are 206,278 results
   • Entry P04578 was looked up and observed. What types of information are provided about this protein?
     • Function, taxonomy, location on the subcellular level, pathology, processing, interaction, family and domain, sequence, cross-references, and miscellaneous information are all provided on this protein page.
3. PredictProtein server was used to analyze only the V3 region of the Markham et al. (1998) sequences.
   • An amino acid sequence from Markham et al. (1998) was placed in the database and analyzed.
   • How does this information relate to what is stored in the UniProt database?
     • This was an interesting figure because it described possible binding sites, bond locations, and secondary structure locations. It also links back to the UniProt database for certain target alignments.
4. Protein Structure from Kwong et al. (1998) was downloaded and opened in Cn3D software site. The picture of the result is posted below

• Find the N-terminus and C-terminus of each polypeptide tertiary structure.
  • Each terminus of each polypeptide was found by looking for the ends of each polypeptide. By using the coloring shortcuts, this process of finding the ends was sped up.
• Locate all the secondary structure elements. Does this match the predictions made by the PredictProtein server?
  • The PredictProtein server gave us a prediction of two helices and six beta sheets. This was seen exactly in the Cn3D program rendering of the Kwong et al. (1998) structure.
• Locate the V3 region and figure out the location of the Markham et al. (1998) sequences in the structure.
  • We ran out of time before the Markham et al. (1998) sequences could be compared.

Data & Files

• There were no data and files used in this project.

Scientific Conclusion

The different programs used during this weeks project allowed me to gain a different perspective on protein sequences as a whole. The ExPASY Translate tool allowed us to change DNA sequence into a protein sequence in a matter of seconds. Here, the importance of reading frames was shown in the fact that the only frame without a stop codon was the correct sequence. While searching for a specific protein given to us on UniProt Knowledgebase (UniProt KB), we discovered a database with tons of information on this protein and many others. Structural information was given by Cn3D software site. Given the great variability of the V3 region, programs like these will enable us to attempt to make sense of the variability of one subject's different sequences.

Defining Our Research Project

• Our Question:
  • Will there be a visible protein sequence change that correlates with a decline in CD4-T cell count?
• Our Prediction:
  • Given that the amino acids of the clones of subject 10 are changing simultaneously there will be an observable drop in CD4-T cell count in response to the ongoing changes in the clones' proteins.
• Which subjects, visits, and clones will you use to answer your question?
  • We will use all of subject 10's clones from all of the visits.

Acknowledgments

• I would like to thank my partner, William P. Fuchs, for the assistance on this week's project, both in assistance on the structure program methods in class and completion of the our project idea outside of class.
• I would also like to thank Kam D. Dahlquist, Ph.D. for providing the instructions and information for this assignment both in class and on this document: BIOL368/F16:Week 9.
• Even though I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.
• Matthew K. Oki 21:38, 25 October 2016 (EDT):

References

1. BIOL368/F16:Week 9
2. ExPASY Translate tool
3. UniProt Knowledgebase (UniProt KB)
4. PredictProtein server
5. Cn3D software site
6. Markham, R.B., Wang, W.C., Weisstein, A.E., Wang, Z., Munoz, A., Templeton, A., Margolick, J., Vlahov, D., Quinn, T., Farzadegan, H., & Yu, X.F. (1998). Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell decline. Proc Natl Acad Sci U S A. 95, 12568-12573. doi: 10.1073/pnas.95.21.12568

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