Is it possible to predict how proteins coded from mRNA will be cleaved?

The reason I was interested in this is because I did some initial work to translate the raw Coronavirus RNA sequences, which you can see here: https://github.com/imranq/coronavirus. The background section below has more information on my approach.

With the "naive" approach to translate coronavirus RNA, using AUG as the start codon, I am able to identify 7 out of 24 proteins from Zhang lab sequences. However, I see by string matching that I actually have 21 out of 24 protein sequences coded. It would be nice to get to the final 24 proteins straight from the mRNA strand.

Please help. Thanks!

Background

Here is the series of steps I used to convert coronavirus RNA into proteins.

1. The raw RNA sequences are here (sourced from the NIH):
https://github.com/imranq/coronavirus/blob/main/data/rawrna.json

2. The script to translate the RNA is here (assumes AUG is the start
codon):
https://github.com/imranq/coronavirus/blob/main/scripts/translate.js

The translated protein sequences are here:
https://github.com/imranq/coronavirus/blob/main/data/processed/translatedProteins.json

3. The script used to generate a comparison between the translated
proteins and the known protein sequences is here (using levenshtein
distance as our difference metric):
https://github.com/imranq/coronavirus/blob/main/scripts/compareTranslated.js

The data generated from that script is here
https://github.com/imranq/coronavirus/blob/main/data/processed/translatedComparison.json

4. Then we detect cleavage in proteins by running a sliding window
across RNA segments between the known and translated proteins. The
script to do so is here:
https://github.com/imranq/coronavirus/blob/main/scripts/detectCleavage.js

4. Finally we merge the datasets we generated from translation and
protein complexes into one dataset, translated proteins and protein
complexes matched to known proteins. 

The data generated from this algorithm is located here
https://github.com/imranq/coronavirus/blob/main/data/processed/mergedProteins.json

At the end of this pipeline, we get 21 out of the 24 proteins matched straight from RNA.

References:

Here are the papers / articles I researched to answer this question

Turning Genome Data into Proteins Turning publicly available genome data into proteins

Khan Academy Genetic Code: https://www.khanacademy.org/science/ap-biology/gene-expression-and-regulation/translation/a/the-genetic-code-discovery-and-properties

Zhan Lab - SARS CoV 2 - Nucleotide, Coding Region, and Protein sequences https://zhanglab.ccmb.med.umich.edu/COVID-19/

More in the readme here: https://github.com/imranq/coronavirus/blob/main/README.MD