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Prof. Jeong's mRNA Vaccine Design, First Steps II

Twenty fragments,
one protein

Join the twenty epitopes from Part I and you get a single 419-residue protein. This part covers only that joining: what holds the pieces together, what else gets attached, and what shape the result takes.
The paper gives the construct's sequence only as a figure, so we rebuild it ourselves. Three numbers prove the rebuild is right โ€” length 419, mass 44.37 kDa, isoelectric point 9.56, all matching the paper to the last digit.
With that ruler in hand you can catch the 42 residues missing from the text, and the epitope that is one residue short, for yourself.
Python runs right inside this page. There is nothing to install.

๐Ÿ Python๐ŸงŠ construct๐Ÿ”— linkers ๐Ÿ“ cross-checks๐Ÿชค pitfalls๐Ÿ“Š quality metrics๐Ÿ‡ฌ๐Ÿ‡ง English
Start lesson 1 โ†’

How you'll learn

๐ŸงŠBuild it block by block

The paper gives the sequence only as a figure. You rebuild it by hand; hitting 419 means you got it right.

๐Ÿ“Check it with three rulers

Length, mass, isoelectric point. Each measures something different, so when all three agree little room is left for error.

๐ŸชคCatch mismatches with arithmetic

The 42 missing residues and the epitope that is one residue short both show up in the numbers first.

๐Ÿ“ŠAsk what each metric measures

Half-life, solubility, Ramachandran, MolProbity โ€” each measures less than you would expect.

Full curriculum

01
์—ํ”ผํ† ํ”„ ์Šค๋ฌด ๊ฐœ๋ฅผ ํ•œ ์ค„๋กœ ์ž‡๋Š”๋‹ค
Fig 1A ยท Methods 4
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02
๋ง์ปค ๋„ท โ€” AAY ยท GPGPG ยท KK ยท EAAAK
Methods 4 ยท Discussion
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03
ํ”„๋กœํ…Œ์•„์ข€์ด ๋ง์ปค๋ฅผ ์ž๋ฅธ๋‹ค๋Š” ๋ง
Discussion ยท ๋ง์ปค ์„ ํƒ์˜ ๊ทผ๊ฑฐ
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04
ฮฒ-๋””ํŽœ์‹  II โ€” ๋ณด์กฐ์ œ๋ฅผ ์•ž์— ๋ถ™์ด๋Š” ๊นŒ๋‹ญ
Methods 4 ยท Discussion ยท 41์ž”๊ธฐ
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05
๊ตฌ์กฐ๋ฌผ์„ ์†์œผ๋กœ ์ง“๋Š”๋‹ค
Fig 1A ยท Fig 1B ยท Table 4 ๋กœ ๋งž์ถ˜ ๋ณต์›
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06
๋ถ„์ž๋Ÿ‰ 44.37 kDa ์„ ๊ฒ€์‚ฐํ•œ๋‹ค
Results 2 ยท ProtParam
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07
๋ณธ๋ฌธ์— ์—†๋Š” 42์ž”๊ธฐ
Methods 4 vs Fig 1A โ€” ์šฐ๋ฆฌ๊ฐ€ ์„ผ ๊ฒƒ
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08
Table 2 ๋ณด๋‹ค ํ•œ ์ž”๊ธฐ ์งง์€ ์—ํ”ผํ† ํ”„
Table 2 vs Fig 1B ยท ์‚ฐ์ˆ˜๊ฐ€ ๊ฐ€๋ฅธ๋‹ค
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09
๋ฒ”๋ก€๊ฐ€ TAT ๋ผ ๋ถ€๋ฅด๋Š” ๊ผฌ๋ฆฌ
Fig 1A ๋ฒ”๋ก€ ยท 409โ€“419
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10
๋ง์ปค๊ฐ€ ์—ํ”ผํ† ํ”„ ์•ˆ์— ๋“ค์–ด ์žˆ์„ ๋•Œ
Table 1 ยท Table 2 โ€” ์šฐ๋ฆฌ๊ฐ€ ์„ผ ๊ฒƒ
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11
ProtParam ์˜ ์ˆ˜์น˜ ์—ฌ์„ฏ โ€” ๊ณ„์‚ฐ๊ณผ ํ‘œ ์กฐํšŒ
Results 2 ยท ProtParam
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12
๋ฐ˜๊ฐ๊ธฐ 30์‹œ๊ฐ„์€ ์•„๋ฏธ๋…ธ์‚ฐ ํ•œ ๊ฐœ๋ฅผ ๋ณด๊ณ  ์ ์€ ๊ฐ’์ด๋‹ค
Results 2 ยท N-end rule
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13
๋“ฑ์ „์  9.56 ๊ณผ ์šฉํ•ด๋„ 0.515
Results 2 ยท ProtParam ยท Protein-Sol
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14
2์ฐจ ๊ตฌ์กฐ โ€” ๋‚˜์„  31 ยท ๊ฐ€๋‹ฅ 25.5 ยท ๊ณ ๋ฆฌ 43.4
Results 3 ยท Fig 1B ยท PSIPRED 4.0
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15
3์ฐจ ๊ตฌ์กฐ โ€” Robetta ๋Š” ๋ฌด์—‡์„ ํ•˜๋‚˜
Results 3 ยท Fig 2A ยท Robetta / RoseTTAFold
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16
GalaxyRefine ๊ณผ MolProbity 2.006
Results 3 ยท Fig 2B ยท Fig 2C
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17
๋ผ๋งˆ์ฐฌ๋“œ๋ž€ 90.1% ๋Š” ์–ด๋А ์ž๋กœ ์žฌ๋А๋ƒ์— ๋‹ฌ๋ ธ๋‹ค
Results 3 ยท Fig 3B ยท PROCHECK
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18
ProSA โˆ’7.54 ์™€ ERRAT 93.052 โ€” ์…‹์€ ๋‹ค๋ฅธ ๊ฒƒ์„ ์žฐ๋‹ค
Results 3 ยท Fig 3C ยท 3D ยท 3E
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19
์‹ค์Šต ์ข…ํ•ฉ โ€” ์ž…์ฒด B์„ธํฌ ์—ํ”ผํ† ํ”„ ๋„ท์„ ๊ตฌ์กฐ๋ฌผ ์œ„์— ์–น๋Š”๋‹ค
Results 4 ยท Table 4 ยท Fig 4 ยท ElliPro
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20
๋งํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ๊ณผ ๋งํ•  ์ˆ˜ ์—†๋Š” ๊ฒƒ
II ๊ถŒ ์ •๋ฆฌ ยท Limitations
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