Tag Archives: oncogene

The incredible combinatorial complexity of cellular biochemistry

K8, K14, K20, T92, P125, S129, S137, Y176, T195, K276, T305, T308, T312, P313, T315, T326, S378, T450, S473, S477, S479. No, this is not some game of cosmic bingo. They represent amino acid positions in Protein Kinase B (AKT).

In the 1 letter amino acid code K is lysine T, threonine, S serine, P proline, Y tyrosine.

All 21 amino acids are modified (or not) one of them in 3 ways. This gives 4 * 2^20 = 4,194,304 possible post-translational modifications. Will we study all of them? It’s pretty easy to substitute alanine for serine or threonine making an unmodifiable position, or to substitute aspartic acid for threonine or serine making a phosphorylation mimic which is pretty close to phosphoserine or phosphothreonine, creating even more possibilities for study.

Most of the serines, threonines, tyrosines listed are phosphorylated, but two of the threonines are Nacetyl glucosylated. The two prolines are hydroxylated in the ring. The lysines can be methylated, acetylated, ubiquitinated, sumoylated. I did take the trouble to count the number of serines in the complete amino acid sequence and there are 24, of which only 6 are phosphorylated — so the phosphorylation pattern is likely to be specific and selected for. Too lazy do the same for lysine, threonine, tyrosine and proline. Here’s a link to the full sequence if you want to do it — http://www.uniprot.org/uniprot/P31749

The phosphorylations at each serine/threonine/tyrosine are carried out by not more than one of the following 8 kinases (CK2, IKKepsilon, ACK1,TBK1, PDK1, GSK3alpha, mTORC2 and CDK2)

AKT contains some 481 amino acids, divided (by humans for the purposes of comprehension) into 4 regions Pleckstrin Homology (#1 – #108), linker (#108 – #152) catalytic –e.g. kinase (#152 – #409),regulatory (#409 – #481).

This is from an excellent review of the functions of AKT in Cell vol. 169 pp. 381 – 3405 ’17. It only takes up the first two pages of the review before the functionality of AKT is even discussed.

This raises the larger issue of the possibility of human minds comprehending cellular biochemistry.

This is just one protein, although a very important one. Do you think we’ll ever be able to conduct enough experiments, to figure out what each modification (along or in combination) does to the many functions of AKT (and there are many)?

Now design a drug to affect one of the actions of AKT (particularly since AKT is the cellular homolog of a viral oncogene). Quite a homework assignment.

The death of the synonymous codon – IV

The coding capacity of our genome continues to amaze. The redundancy of the genetic code has been put to yet another use. Depending on how much you know, skip the following three links and read on. Otherwise all the background to understand the following is in them.




There really was no way around it. If you want to code for 20 different amino acids with only four choices at each position, two positions (4^2) won’t do. You need three positions, which gives you 64 possibilities (61 after the three stop codons are taken into account) and the redundancy that comes with it. The previous links show how the redundant codons for some amino acids aren’t redundant at all but used to code for the speed of translation, or for exonic splicing enhancers and inhibitors. Different codons for the same amino acid can produce wildly different effects leaving the amino acid sequence of a given protein alone.

If anything will figure out a way to use synonymous codons for its own ends, it’s cancer. [ Cell vol. 156 pp. 1129 – 1131, 1324 – 1335 ’14 ] analyzed protein coding genes in cancer. Not just a few cases, but the parts of the genome coding for the exons of a mere 3,851 cases of cancer. In addition they did whole genome sequencing in 400 cases of 19 different tumor types.

There are genes which suppress cancer (which cancer often knocks out — such as the retinoblastoma or the ubiquitous p53), and genes which when mutated promote it (oncogenes like ras). They found a 1.3 fold enrichment of synonymous mutations in oncogenes (which would tend to activate them) than in the tumor suppressors. The synonymous mutations accounted for 20 – 40 % of somatic mutations found in cancer exomes.

Unfortunately, synonymous mutations have been used to estimate the background mutation frequency for evolutionary analysis, on the theory that they are neutral (e.g. because they don’t change protein structure, they are assumed not to change how the gene for the protein functions). Wrong. Wrong. They can change how much, or where, or what exons of a protein are included in the final product.