How many coincidences...

Before it becomes mathematically impossible?

This is a deep dive into the possibility that similarities in the design of the genetic COVID vaccines that magically appeared overnight in February 2020 were more than coincidental. 

The findings are significant because they imply collusion, not competition, between all the vaccine companies who shared a (yet to be determined) common goal. 

Following the revelations a few weeks ago in the article below (which you really, really should read to understand what is going on)….

The New Eugenics Movement - Part 2

I went on to investigate something that popped out at me during the writing of that article and the investigation of the vaccine genome sequences. You see, I’m a patterns sort of person. Some people are good at recognising faces, others are good at playing music by ear and I’m not bad at recognising patterns in numbers (or at least, recognising when something is up).

And looking at the COVID vaccine sequences there is definitely something “up”… and it’s something that certain people have been suspicious about for over 2 years.

Now, in case you are already lost “#CoptiGate” was all about the fact that the Pfizer and Moderna vaccines completely replicated the original COVID virus spike protein to the exact amino acid of the 1273 amino acid sequence that made up that protein¹, but changed the underlying nucleotide sequence that provided the code for that amino acid sequence.

The reason for that will become clear, hopefully, soon.

“CoptiGate” was short for “Codon optimisation gate” (“gate” being, in this context, a scandal).

Codon? What’s a Codon?

A codon is a triplet of nucleotides (genetic code characters selected from C-A-G-T²) that tell the cell which amino acid to add to a chain of amino acids in making a protein as mentioned long long ago in this article:

How to BLAST your way to the truth about the origins of COVID-19

Proteins are the functional units of the body and without them life on earth would not exist. The “spike protein” of the COVID (SARS-Cov-2) virus is an example and it is made up of 1273 amino acids something like this…

Sample of genomic and amino acid sequence from Pfizer vaccine (top) and Novavax vaccine (bottom). The corresponding amino acids (MVFL..) are labelled above the nucleotides

Now in this diagram the protein sequence is on the top line “MFVFLVLLPL….” and the genome sequence is underneath. The two genome sequences are different yet code for exactly the same amino acids. This is possible because there are 64 combinations of any 3 nucleotides (C-A-G-T, 4^3 = 64) but there are only 20 possible amino acids (M-F-V-L etc³). In the old days we would use a codon wheel to remember which triple of nucleotides coded for which amino acid. It looked something like this:

Codon Wheel. Each triplet of nucleotides are read from the centre of the wheel (marked 5’) outwardly. For instance CAU - bottom left - codes for His (Histidine). U (uracil) is the RNA version of T (thymine) in DNA sequences.

Because there are many more triplet combinations of DNA than there are amino acids that are coded by them, we get redundancy. So for instance the amino acid Alanine can be coded for by GCU, GCC, GCA or GCG - 4 different combinations. Any of those combinations, with some limitations, will produce the exact same amino acid.

So in the example above the Pfizer sequence ATGTTCGT[G]TTC and the Novavax sequence ATGTTCGT[C]TTC code for exactly the same amino acid sequence even though they are different at the nucleotide level. From the point of view of a cell, it probably won’t know the difference.

In fact, the only way that you would notice the difference in most cases is to actually sequence the genetic code - or to perform PCR (because PCR is very, very specific to a genomic sequence).

In a PCR test where the primers are selected for the specific sequence, only one of the two sequences mentioned above would be picked up by PCR (in the case of a PCR test, only one would test positive).

So, why did the vaccine manufacturers change the nucleotide sequence to their own proprietary sequence even though that apparently resulted in the exact same amino acid sequence?

Well, according to them and as specified in this paper from Xia it was “to increase the G-C content to produce more protein”. Except from Xia:

There are two lines of evidence suggesting that CGG is not the optimal codon. The first involves the codon usage of human ribosomal protein genes (“RP” in Table 1) which are known to be highly expressed. These genes prefer CGC codons (Table 1). The second and more direct evidence is from codon usage of genes highly expressed in skeletal muscle cells (which are relevant here because the vaccine mRNA is injected and carried by the lipid nanoparticles into skeletal muscle cells to be translated, although vaccine mRNA could also be carried to some other tissues). …. the CGC codon preferred by ribosomal protein genes are also preferred by highly expressed muscle genes.

These multiple lines of evidence suggest that CGC is a better codon than CGG. The designers of the mRNA vaccines (especially mRNA-1273) chose a wrong codon as the optimal codon.

So let’s just check what the manufacturers actually used for the Arginines in the vaccine sequence, that according to Xia should have been “CGC”. As stated by Xia, Moderna was the worst offender converting nearly all its arginines to CGG. [It is worth noting here that increasing the CG content actually risks the G-quadruplexes that cause prion neurodegenerative disease as noted by Kevin McKernan in 2021].

Here’s the chart (SARSCOV2 is the viral sequence on which the vaccines were supposedly modelled):

Now the very attentive and eagle-eyed of you will notice two things

(1) That Pfizer and Moderna for some reason, not colluding at all, decided to ditch the idea of using a CGC codon for all 42 arginines despite the fact that the CGG that they chose (and AGA for Pfizer) were not the “optimal” codons…

and

(2) That Novavax didn’t use any CGG codons to code for Arginine, thus completely negating my contention from “The new eugenics movement: Part 2”, which was that all three vaccine manufacturers appear to have colluded to increase the number of instances of CGG in their vaccine sequence.

Well, not so fast - because as always, there’s a twist. Here’s the triplet count I posted in the article. Note that I used the word “Triplet” in the table previous article (reposted below) and the word “Codon” above.

That’s because “codon” means that the sequence actually codes for an amino acid and “triplet” means that it just exists in the sequence. So in the full sequence of 3819 nucleotides there are 3817 triplets (counting any 3 letters from the start to the end), but only 1273 codons (counting in threes from the start).

So putting this all together, it seems obvious that Pfizer and Moderna decided for “independent” reasons to change all their arginines to the “wrong” CGG codon and that contributed to both of them maximising the number of CGG triplets in the sequence. Novavax also “independently” decided not to use CGG codons for arginine yet still managed to massively increase the number of CGG triplets in their sequence.

Smart, but why does it matter?

Well, because all these approaches have the impact of dropping PAM sequences into the code under cover of “codon optimisation” with plausible deniability against the idea that dropping PAM sequences into the code was what they were actually trying to do. Now why would they want to do that?

Just as a reminder:

A PAM sequence is a triplet of CGG (preferred), or any other nGG triplet - irrespective of whether it is in a coding location - that enables an anchor for CRISPR-Cas9 gene editing

“It’s all a conspiracy theory”

Of course. There is no chance that three (or four) “independent” corporations would end up at the same point having taken radically different paths. Is there? No, that would be “conspiracy theory” which is almost always explained by coincidence.

Well buckle up because it’s time for some mathematical probability.

And this is the question:

What is the probability that at least three “independent” corporations managed to maintain a specific sequence in their genomic vaccines if they were all performing different codon optimisations in order to create sufficiently diverse gene sequences that they could claim a patent on their own version, without appearing to have colluded⁴?

And for that sequence to be a suitable sequence to be a target for CRISPR (Cas9) by being both long enough to act as an anchor and ending in a CGG (PAM) sequence

Well I’m going to answer this for you.

But first let’s take you through this question

How similar are the vaccine sequences?

This is such an important question that gets very little attention. You see, each of the vaccine manufacturers were apparently creating their vaccines “overnight” once the genome sequence of the COVID virus was released in January 2020.

Well of course, this is not possible. It is possible to design a sequence like this in silico (on a computer) but you have no idea whether it will work when put into cells. That’s because some codon sequences will just go “bleh” when introduced to a cell and others might produce the wrong sequence due to instability of the mRNA ass described here:

Although codon optimization of the target sequence can provide certain benefits, it may also result in reduced mRNA stability in solution, which impairs its functionality. Therefore, it is necessary to experimentally confirm the stability of the structure of optimized nucleic acids.

So it’s not just simply a case of “computer says this so let’s go with it”. There are a myriad of options for codon optimisation and all the products needs to be produced, cultured in cells, the protein tested etc etc. That takes weeks if not months. But Pfizer and Moderna did it in one day. Of course. They must have used the Unicorn protocol.

Putting that claim aside we can actually see the result they came up with, and align all the sequences from all the manufacturers. This requires some work because they are not all readily available. Fortunately we have help from people like Kevin McKernan who was the first to actually sequence the vaccine vials to see what was in them. And the publication from Castriuta documented the vaccine sequence as retrieved 28 days after vaccination (remember they said it only lasted a day or two?).

As stated earlier, all the vaccine sequences produced the same protein apart from the small 3-amino acid change in the Novavax sequence. The AstraZeneca vaccine, which was supposed to be different because it was a declared DNA gene therapy from the outset, had an identical amino acid sequence to the other vaccines apart from the fact that it did not use the 2-proline mutation. Strangely its nucleotide sequence was relatively secret and only published in the patent database in August 2023⁵.

Now if we align all these sequences in Ugene we can get a “dissimilarity matrix” which tells you how different all of these sequences are from each other - and from the original Wuhan viral spike that they are meant to copy - at the nucleotide level:

This table might seem complex but it’s not - it just compares how identical each sequence is from each other, with the following noted:

(1) All the vaccine sequences are only about 70% similar to the original Wuhan viral strain, that is they are all 30% different from the viral sequence.
(2) The Pfizer BNT162b2 (original Pfizer) vaccine and Astrazeneca vaccine are only 1-2% different from each other. That is, Pfizer and AstraZeneca managed to land at essentially the same codon optimisation “by chance” despite aiming for 30% difference from the original.
(3) The Pfizer original and Pfizer bivalent are only 1% different from each other. Likewise the Moderna original and Moderna bivalent are also only 1-2% different from each other. All the differences are accounted for by the amino acid mutations in the viral strains.
(4) The synthetic sequences from the 4 manufacturers are more different from the original virus than they are from each other 🤔

Putting aside Astrazeneca, which took itself out of the vaccine race recently, from this table we can deduce the following:

The 3 vaccine companies each developed - overnight and without apparently needing to test them - a codon optimised sequence that they deemed necessary to be 30% different from the original virus strain, yet when they had a year to develop a new version of the vaccine for a new virus strain, they only changed their sequence by 1% (just where the new strain amino acid changes were).

Well there are two explanations for this

1. They all independently got really lucky with their original codon optimisations and thought it best to keep to those when designing a new vaccine for a new strain, only changing the sequence just where the new strain had changed an amino acid

   - or -

2. The original codon optimisation was planned well in advance of February 2020 and it was too difficult to try do it all again when new strains kept emerging, so they didn’t bother.

Now I know which of those options my money is on but this is just a cold smoking gun which suggests there there may have been a bit of collusion going on between 3 vaccine companies that were supposed to be fighting each other.

Now you might think that these companies fighting each other for a patent for a similar product would be expected. But remember that Moderna and Pfizer produced exactly the same protein product. So how could they be in a patent battle for exactly the same product? Well because they claim to have used a different sequence from each other. From Pfizer’s response to Moderna’s court filings⁶:

While Moderna has not publicly disclosed the complete mRNA sequence that its vaccine uses, Pfizer and BioNTech have. In 2021, a third party reported that it had sequenced the mRNA in Moderna’s vaccine and published the results. As Moderna can confirm based on its own and publicly available information, Comirnaty®’s mRNA sequence is different from Spikevax®’s mRNA sequence

In fact, this defence from Pfizer (that although the protein was identical the genomic sequence was different) is repeated throughout their response⁷. More bizarrely, Pfizer claim that they “didn’t know what Moderna’s sequence” was yet managed to codon optimise their sequence to a point:

1. that was almost the same dissimilarity (difference) - 30% - from the viral sequence as Moderna

2. that had just enough differences (10%) from the Moderna sequence to be able to make a case that their sequence was not the same, as they wrote repeatedly in their court filings. Here’s the comparison table:

This is certainly suspicious of collusion in itself but there is one more part to this puzzle that we need to get our heads round.

That is, how likely is it that in the codon optimisation process - where these companies had nothing to do with each other and all created their own sequence by chance - that any specific long sequence would be retained?

Well it’s actually a trillion dollar question and before we go there here’s a quick summary of where we are up to.

All four of the vaccine companies that produced recombinant vaccines for distribution to Western countries "codon optimised" to produce essentially the same protein but with a different gene sequence.

The magnitude of difference from the original virus that they were supposed to be copying was similar between the companies, and greater than that between them.

These differences suggest collusion between the vaccine companies, despite their claims to have independently and instantaneously discovered their own version of the "perfect" genetic sequence for their products. 

The Great Convergence

Just to go recap where we are going to next, as it might seem on the face of it that in the context of our daily lives “what is the longest consensus sequence between the vaccine companies and why does it matter?” is rather down the list especially when “can I afford to eat this week” is encroaching on the number 1 spot for many people. Of course the two may be related but we’ll come to that…

Here is a snippet of the gene sequences for the 3 main vaccine candidates aligned in Ugene

The grey bars at the top show how many of the characters (nucleotides) at any point in the sequence align - if all 3 are the same the grey bar is full height.

From aligning the 3 sequences we know that the probability of all 3 matching at any point is 81% (conversely the probability of not matching is 19%, roughly 1-in-5).

The question we are then trying to ask is similar in scale to the question “what is the biggest number of times can I throw a five-sided dice and never throw a 5?⁸”

So if we are looking at the grey bars we want to know whether it is likely that there should be any very long runs of full-length grey bars. And if there are any long sequence runs, is there anything special about them?

If you are more of a visual person here’s a clip of Ugene that might help you see the problem. We are looking to see how if there are any very long runs in the long grey bars. To entice you to watch the 98 second clip I’ve added a relevant soundtrack.

Now here is the bit we are interested in, which Jessica Rose alluded to in her recent substack in relation to the clue in the previous article.

It’s a length of 44 nucleotides (nt) that doesn’t exist in the human genome according to BLAST. You can check this for yourself on BLAST using the same techniques explained previously and putting in this sequence as the query, and specifying 9606 (or homo sapiens) as the species:

AAGATCGCCGACTACAACTACAAGCTGCCCGACGACTTCACCGG

And more interestingly, if you forget to restrict your search to humans you will get a whole bunch of synthetic clones and vectors (lab made clones) including this horror chimera created by Ralph Baric, that we just happen to have seen before in the investigation of the vaccine experiment conducted in Samoa in 2019.

Which I talked about here:

The Killing Fields of Samoa

In fact this is such a rare sequence before 2022 that there were only 10 hits on BLAST for the publication years 2020-2021, and all matched clones that were used to develop COVID vaccines including Sputnik (the Russian Astrazeneva equivalent).

In other words, this sequence never existed in humans as far as we can reasonably test. If you have the patience you can check this against multiple human databases on BLAST (around 140 trillion letter sequences to choose from).

And all you’ll get is this. “Computer says no”. It didn’t exist⁹.

And just to put the cherry on the top of the icing on this cake, this unique sequence just happens to end in a CGG PAM sequence, which is the 3-nucleotide sequence you need if you are going to want to edit anybody’s genome (explained in part 2).

As Kevin McKernan (probably the most published genomicist in the world) rightly points out these sequences are pretty common and in coding sequences occur in about 1% of the genome.

So, adding a whole bunch of these CGG sequences into the genome might be a nothing burger because there are already millions in each cell.

Yet what isn’t (or wasn’t) in any cell in the body was the unique sequence attached this particular CGG.

AAGATCGCCGACTACAACTACAAGCTGCCCGACGACTTCACCGG

Now we’re in a totally different league of statistics altogether and we need to try and establish whether that sequence could have happened by chance, or was a one-in-a-million event.

Does it matter?

OK so you’re maybe thinking “what does it matter there is a unique sequence in all these vaccines?”'

Well let’s just put some things together now

1. We know the vaccines are all derived from DNA plasmids and those plasmids were found to contaminate the vaccines at sufficiently high level to get into cell nuclei

2. We know that months following vaccination spike protein is being produced confirming that either genomic integration has occurred or the sequences are semi-permanent

3. We know that all makes of the original vaccines contain the same unique sequence that is not a human gene sequence

4. We know that this unique gene sequence ends in a CGG PAM sequence

And just for clarity what we are really now trying to establish is this:

1. Could the presence of this sequence be used to detect whether someone has ever been vaccinated with the genetic vaccines?

2. Could there be any consequence of having this sequence in the genome that could have commercial value?

In answering (1) that gives us a little segue to break to a clip from our favourite movie at the scene introducing our new dystopia where you can only function in society if you have the right genetic sequences:

And to clarify the question: is it possible using current technology to detect whether someone has had any “valid” gene therapy vaccine, from a rapid blood test?

I bet you know the answer don’t you?

Of course the answer is yes, provided that gene sequence persists for long enough to detect in your blood.

In fact, simple PCR can detect gene sequences for months after vaccination but PCR takes hours and the smallest gene sequence that PCR can detect in practice runs at about 100 bases (nt or nucleotides), and it is very specific. Which means that, because there are no sequences of this length that are identical between the vaccine manufacturers, you would have to know which vaccine you were testing for. That’s great for claiming patent licensing rights of course, as we discussed before:

Who owns who?

But it’s not so useful for the more generic GATTACA-style “is this person valid?”.

For that you need something rapid, highly specific and applicable to a short sequence. For this, you need a CRISPR-based diagnostic test of which there are a number that just happen to be patented by our “let’s use CRISPR to stop cow farts” enthusiasts Jennifer Doudna (IGI, Berkley) and Feng Zhang (Broad Institute, Boston).

You literally can’t make this cowpat up. They even have nice cuddly sounding names like SHERLOCK, HOLMES, HUDSON and the more ominous DETECTR.

So it seems that whichever way you slice this the CRISPR companies stand to make trillions of dollars on the back of the genetic therapy vaccine rollout because, should there happen to have been genomic integration, they now have access to:

1. Targeted gene editing - because a known gene sequence would now exist in your genome that ends in a CGG PAM and is unique enough that targeting it with CRISPR-Cas9 gene editing might not result in fragmenting your whole genome

2. A theoretically simple, quick, diagnostic test for the presence of the vaccine sequence in your blood in case somebody decided that that should be the marker of whether you were considered a “valid” in society, as depicted in GATTACA..

Screenshots from GATTACA. Jerome “Eugene” Morrow is “Valid” based on his genetic signature. Note the symbolism between the eugenics-approved Jerome (infinity loop symbol) and the “God-child” = “In-Valid” Vincent Freeman.

Now obviously nobody would do that would they? I mean, that would require collusion between a bunch of fluffy benevolent corporations who have no intention of providing a means to a digital-ID based on your genomic signature.

So next we shall see how “accidental” this event actually was, in the final section of this unintentionally piece (and if you have survived so far, congratulations).

What ARE the odds?

This is the trillion dollar question (because the trillion dollar CRISPR industry is primed to benefit from it, accidentally of course). So just to clarify what the question actually is, here goes…

What is the probability that 3 competing vaccine companies would each come up with a gene sequence creating the exact same protein, that differed by 30% from the original viral sequence yet shared the same 44nt sequence and that just happened to end in a CGG PAM sequence?

Now to break this down we have to look at the following mathematical properties of this particular product. Here they are:

1. The sequence is 3819 nucleotides (characters from C,G,A,T) long

2. The coding sequence is 1273 triplets (e.g. ATC, GTG) and they all need to produce the same resulting 1273 amino acid sequence.

3. The chance of any single nucleotide matching across 3 sequences is 81%

4. There are 3817 points at which a CGG can occur in the sequence

5. The longest run of any matching characters across the 3 sequences ends when the sequences differ, and the count of the next run starts from the next matching character like this:

Now, it turns out that calculating the probability of our sequence happening in this situation is not that simple. Sure enough, calculating the probability of 44 matching points out of 44 where the probability of a match is 0.81 is easy and can be calculated by any binomial calculator (it’s about 0.1%). But we have more complexity than this because we can have any sequence length and each time a sequence ends we have to recalculate the probability that another sequence of a certain length exists in the remaining characters from our bucket of 3819 balls. It’s even more complex in fact that this related problem discussed on various statistics fora and even the De Moivre formula might not solve the problem (enthusiastic statisticians are invited to prove me wrong on this in the comments).

So when something becomes mathematically complex it can be easier to solve the problem by bootstrapping. That is, you create a simulation of the problem on a computer and get the computer to reproduce it 1000 or 10,000 times and see how many times your event occurs.

And when you do that for our subject of interest you get something like this

Now in this graph the black dots are the actual number of sequences in our 3-vaccine comparison that match a certain length (on the x-axis) before a mismatch. [At this point, a massive hat-tip to

OpenVAET

for his help coding some of the prep work for this, which saved me a huge amount of time].

The orange arrow arrow on the graph is our 44nt sequence of interest and you should note that there are no sequences between 30-40nt in our black dots, and in fact nothing at all over 30nt except for this one magical sequence. Because the simulation (the red line) is scaled to match our actual comparison you can see if you zoom in that this 44nt bump is a bit lucky. Here’s the zoomed in view:

That result (the red line) was based on 10,000 simulations and calculated the probability that any particular length matching sequence would be present. But that’s not all. What we really want to know is “what is the probability that there would be no sequences between length 30-40nt in our comparison, but a sequence over 40nt, and that sequence ending in a CGG”

Well it turns out that we can calculate the probability of this sequence having a CGG at the end as we know how many CGG sequences exist in the consensus sequence (the sequence where all 3 match) - and that is 33. So now, approximating to 3800 characters, we can take a random mix of 33 “1s” and 3767 “0s” and see how often our “1” appears in any sample of 42 numbers (there are 42 positions that a triplet can occupy in a 44nt sequence) and how often it appears at the end.

The model shows that a CGG would be present in around 31% (+/- 2%) of the sequences and would be at the end in around 0.85% (+/- 0.1%)¹⁰

Now we need to multiply that by the probability of having no sequences between 30-40nt and a sequence over 40nt in the same run, which was calculated at 4.3% on our bootstrap (10,000 runs).

That gives us an overall probability of this particular sequence happening by chance in this situation of 0.037% or approximately 4 in 10,000.

And because I know this article is going to be on the desk of all the BigPharma “factcheckers” next week I also knew that the first argument against this would be “oh but that part of the amino acid sequence had fewer codon optimisation options so that is why the sequences are shared between all the manufacturers”. Well I’d already thought of that and reversed engineered the possibilities for codon optimisation for each region of the vaccine sequence.

The coding part of interest is the amino acid sequence KIADYNYKLPDDFTG

And we can check each 45nt (15 amino acid) section along the whole sequences to see how many options there were for codon optimisation. And it turns out that that particular region was well within the normal range (+/-2SD), with quite a few other parts of the sequence having many fewer options for codon change yet not demonstrating the same consensus. So you’ll have to find another excuse.

The second thing that will be claimed is that Novavax “can’t have this problem because it’s a protein vaccine”…

Well that would be true if it wasn’t for the fact that Novavax is susceptible to exactly the same plasmid contamination problem that we were told wouldn’t happen with Pfizer and Moderna, and that turned out to be an absolute lie. As yet, no independent lab has tested Novavax for plasmid contamination but the presence of Saponin-M and a similar lipid nanoparticle formulation¹¹ to the mRNA vaccine creates exactly the same transfection risk seen in the recent #plasmidgate revelations and earning Novavax its own #Novagate hashtag.

Novavax’s own product image shows its plasmid and BCV vector as well as the detergent-based nanoparticles that can act as transfection agents as explained in the Daily Beagle’s substack here

So, now we have an idea of how likely it was for this magical sequence to have happened by chance. There are other features too which will reduce even further the probability of this being an accidental event but that we don’t have enough space for here, like the bizarrely “incompetent” inclusion of nuclear and mitochondrial targeting sequences, and the inexplicable drive to get people to take 3 transfection doses when the UK’s MHRA knew that one dose was enough¹².

So I think I’ll stop there.

4 in 10,000 is a rare event. And with everything related to COVID we will be told that it could not possibly be anything else other than a coincidence.

Just like the plasmids.
Just like the lipid nanoparticles in the ovaries.
Just like the excess deaths.
Just like the myocarditis.
Just like the missing safety data.
Just like the withheld FOI requests.
Just like the dismissed court cases.
Just like the hidden contracts.

All coincidental.

Absolutely nothing to see. Move along now. And don’t forget your digital ID.

Have a great weekend.

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Just an endnote… if you got this far, are still paying attention and just for fun.

---

[UPDATE 9/10/24]

I was asked a few times to compare the J&J vaccine sequence. I didn’t do this earlier because I was happy that there was enough in here to make a case, and the J&J was always thought to be the “same” as the AstraZeneca vaccine.

Turns out that J&J (MQ330767) is more similar to the Pfizer vaccine than the AstraZeneca vaccine, with 90 mismatches to AstraZeneca and only 38 mismatches to Pfizer. Here is the similarity matrix.

I haven’t rerun the probability calculation, but if I get time I will.

Clearly it would be very coincidental if the same sequence matched J&J too.

But of course it does. PAM, warts and all.

Just a coincidence.

1. Actually there was a tiny difference from the original Wuhan Spike protein in that there was a swap of two amino acids to proline in order to “stabilise the spike in the prefusion conformation”. There was no logic to this but the person that invented it, Jason McLellan, was handsomely rewarded. His original paper was published in 2017 in relation to a putative vaccine for MERS, which was never used in clinical practice.

https://www.pnas.org/doi/10.1073/pnas.1707304114

2. T = Thymine is a nucleotide only seen in DNA. The RNA equivalent is U = Uracil. Therefore a code sequence CAGTTC in DNA is the same as CAGUUC in RNA.

3. The single letter code is used for convenience for the representation of amino acids with examples A=Alanine, R=Arginine, K=Lysine. A three letter code can also be used.

4. Collusion could invalidate their patent claim
https://henry.law/blog/prior-art-invalidate-issued-patent/ and https://www.unemed.com/blog/collaborations-and-their-impact-on-inventions-and-patents are just examples in this highly complex legal space.

5. OCR searchable version of the full AstraZeneca sequence publication (retrieved May 2022)

Az Nomenclature Annotated Genome Sequence Cleaned

6.7MB ∙ PDF file

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6. Moderna patent complaint against Pfizer

Moderna Patent Filing

294KB ∙ PDF file

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7. Pfizer response to Moderna complaint

Pfizer Reply Moderna

640KB ∙ PDF file

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8. For the probability buffs it is more complex than this and is actually: “What is the maximum number of consecutive throws of the 5-sided dice I can make without throwing a 5, whereby if I throw a 5 I start counting again and the maximum number of throws that I’m allowed is 3819 (the length of the vaccine spike genome sequence)?”

9. If you want to look into this more you will be swamped by BLAST hits from copycat vaccines from 2021-2024. Just include the line “not 2021:2024[PDAT]” in the Entrez search box

10. The ratio here should be 42 but ends up at 36, which is close enough.

11. The full sequence of Novavax’s plasmid has not been released publicly. The sequence described is that which is available on genbank that matches the amino acid sequence in the Novavax patent copied here.

Novavax Patent Us20210228709a1

13.2MB ∙ PDF file

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12. MHRA committee on human medicines meeting minutes 24/12/20 obtained under FOI

Phe 913 Foi Documents Relating To The Independent Analysis By Phe Of The Full Pfizer Data Set Redacted

129KB ∙ PDF file

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Chm 24 December 2020 Final Summary Minutes Copy

169KB ∙ PDF file

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