COMPUTATIONAL REDUCTION VACCINE FOR COVID-19 ORIGINATING FROM CIVET SARS, BAT SARS, BETACOV BTRS, BETACOV BTRI, AND NEOROMICIA

Abstract

A system for the rapid development of vaccines or anti-bacterial drugs is required when working with pandemics. The easiest way to formulate these new vaccines is through computational reduction of existing organisms via statistical models. Once vaccine candidates are arrived at through this method, “Super Organisms” containing all of the computationally reducible fragments can then be taken through a Crispr reduction process wherein those computationally reducible fragments are removed. The result is a vaccine candidate which has possible problematic function partially or fully removed. The “neutered” version of the virus can be tested in a lab and in clinical trials for efficacy. This patent covers a vaccine candidate utilizing computationally reducible fragments related to Civet SARS, Bat Sars, and BtRs and BtRI BetaCov; those fragments removed from future Covid-19 Super Organisms either collectively (as in this patent) or individually; as well as the RNA transcripts of those fragments.

Claims

1. The reference fragments herein described from Civet Sars, Bat Sars, BetaCov BtRs, BetaCov BtRI, and Neoromicia, occurring in greater than 90% of the Nov. 18, 2020 Covid-19 database, and which may be computationally removed from 21,467 Covid-19 “Super Organisms” to form potential vaccine candidates without laying claim to the actual fragments as genetic material, only their use, collectively or individually, as the basis for the creation of a new organism or organisms including a “neutered” Covid-19 live or dead virus which may be potentially used safely as a vaccine following Crispr reduction, laboratory testing, and clinical trials.

2. The newly created organism with these fragments removed as shown in the sequence file, which is a vaccine candidate for Covid-19, as well as future refinements wherein those fragments may be removed collectively, or individually, to create an effective Covid-19 vaccine from other Covid-19 samples, and which includes future refinements of the vaccine wherein the removal of only one of these fragments may be required.

3. The RNA transcript of each of the fragments described herein which individually or collectively can be utilized in the same manner as in claim 1 without requiring the subtraction of the fragments from a Super Organism for the creation of a live or dead vaccine but rather can be utilized in a kind of “shotgun” approach wherein all fragments are included en masse in each dose of the vaccine, or future refinements of same wherein after significant laboratory testing only one or two RNA transcripts of the fragments may need to be utilized.

Description

BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS

[0006] FIGS. 1-5 are a series of tables of computational fragment reductions from Covid-19 which are related to Civet Sars (FIG. 1), Bat Sars (FIG. 2), BetaCov RtRs (FIG. 3), BetaCov RtRI (FIG. 4), and Neoromicia (FIG. 5). Column headers are described below.

[0007] FIG. 6 is a SnapGene circular view of Covid-19 sample MW205979.1 from which this vaccine is derived.

[0008] FIG. 7 is the same SnapGene circular view of MW205979.1 with the fragments outlined below removed.

DETAILED DESCRIPTION OF THE INVENTION

[0009] There are several types of vaccines. This invention introduces a new type of vaccine which is a computationally derived reductive vaccine. A computationally derived reductive vaccine utilizes statistical computation to arrive at a list of fragments which can then be removed from live viruses or bacteria via Crispr to arrive at “neutered” versions which can then form the basis for the vaccine.

[0010] Computational reduction in this case may be defined as non-laboratory computational reduction of organisms into fragments, which then can be assessed on the basis of frequency across an entire range of similar organisms as well as computationally tested to confirm that those structures are unique to the virus or bacteria in question. The particulars of the method of discovery for these fragments is proprietary.

[0011] What is not proprietary is the statistical analysis of the fragments which are outlined in FIGS. 1-5 and below. In the case of this particular vaccine candidate, the fragments which are included are related to Civet Sars, Bat Sars, BetaCov RtRs and BetaCov RtRI and appear in the NIH Covid-19 database greater than 90% of the time. The Covid-19 database “snapshot” from which the fragments in this patent were selected was taken on Nov. 18, 2020. That database is available upon request.

[0012] The result of this patent is relatively simple. When a Super Organism or Covid-19 sample which contains all, or most, of the fragments outlined below is found, that Super Organism can then be genetically modified in a laboratory using Crispr to remove those fragments. Once all those fragments are removed from the organism, it can then be tested in a laboratory to see if problematic function remains. “Problematic function” in the case of Covid-19 is two-fold: functions of the virus which have caused high transmissibility rates, and functions of the virus which cause high mortality rates. It may take us years to figure out exactly what those functions are and where they appear exactly on the genetic assay. This patent provides a shortcut by simply removing all of the most likely candidates for those problematic functions by identifying fragments which appear often enough not to be considered mutations (i.e. fragments only appearing in one or two samples).

[0013] A scan of the entire Covid-19 database provides a total of 92 fragments related to Civet Sars, Bat Sars, BetaCov RtRs, BetaCov RtRI, and Neoromicia which appear more than 90% of the time across the entire Nov. 18, 2020 Covid-19 database.

[0014] Those 92 fragments are listed in a series of Excel tables in the Drawings. Each table header contains the following information going from left to right: the Genbank virus file where the match was found (ID); the accession number of the viral sample where the match was found (FileWhereFound); the type of organism (Organism); the “bin” size (Bin #) indicating the size of the fragment matched wherein “Bin25” is any fragment from 25-49 base pairs, “Bin50” is any fragment from 50-74 base pairs, and so on; the accession number of the Covid-19 sample providing the matched fragment (CovidID); the number of appearances across the entire Nov. 18, 2020 Covid-19 database (App #); the percentage appearance expressed as a decimal (App %); the location of the organism in the GenBank file (AppLoc); and finally the fragment that was matched (Strip).

[0015] You will notice that there are some repetitive “nesting doll” types of matches—this is due to the nature of the fragment detection system across each individual sample. All fragments are listed in the drawings. However, it should be noted that in the computational reduction process, because of overlap, some fragments, depending on the Super Organism used as a starting point, will simply be redundant.

[0016] In the creation of a vaccine candidate in this manner, we can also view that vaccine not only as a reductive entity which can be manufactured from a variety of possible starting organisms, but also as a complete organism which has potentially been “neutered” of its destructive features.

[0017] To arrive at that possibility, we must first find a Covid-19 sample which contains all of these structures. Of the 27,632 complete Covid-19 sequences in the Nov. 18, 2020 Covid-19 database, there are 21,467 which contain the fragments, and 17,758 which contain the maximum of 24 of the 92 fragments in non-overlapping configurations.

[0018] So, to create a reductive vaccine, computationally those fragments are removed to create the vaccine candidate as shown in this patent's sequence file. The original reference sequence and can be downloaded from NIH via the reference MW205979.1. As previously stated, there are also 21,467 other potential reference candidates which could be used as Super Organisms for the next generation of vaccines based on these fragments. That list is available upon request.

[0019] This application also seeks to cover the RNA transcript of each of the fragments.

[0020] It may well be that RNA transcript vaccines based on these fragments would be of equal or greater efficacy in triggering a useful immune response.

[0021] It should also be noted that while the majority of these fragments are relatively short (25-49 base pairs) at 25 base pairs, a fragment has only a 1 in 1.12 quadrillion (4.sup.25) chance of occurring—in the entire history of the planet. In other words, at a 90% recurrence rate across the entire Covid-19 genome, these fragments represent viable mathematical targets for vaccines.

[0022] This application identifies 92 such fragments.