Chapter 1 — Further Reading

Sources are grouped by this book's three honesty tiers. Tier 1 is verified canonical — things we are confident exist and can stand behind. Tier 2 is attributed but with specifics unverified, given as ranges rather than false precision. Tier 3 is illustrative and constructed for teaching.

Tier 1 — Verified canonical

The chemistry itself. Any standard biochemistry textbook covers amino acids, the peptide bond, and protein structure to a depth well beyond this chapter. Lehninger's Principles of Biochemistry (Nelson and Cox) and Berg, Tymoczko, and Stryer's Biochemistry are the two most widely used, and both have chapters on amino acids and protein structure that are more rigorous than anything here. Berg et al. is freely readable in older editions through the NCBI Bookshelf, which makes it the most accessible serious reference available.

Sanger's insulin work. Frederick Sanger determined the amino acid sequence of insulin over roughly a decade ending in 1955, and received the Nobel Prize in Chemistry in 1958 for it — and a second in 1980 for DNA sequencing methods. The Nobel Prize organization publishes the lectures and biographical material for both prizes free online, and the 1958 lecture is unusually readable for a primary source.

Vincent du Vigneaud determined the structure of oxytocin and then synthesized it, receiving the Nobel Prize in Chemistry in 1955. The same archive covers it. This is the origin point for the idea that a hormone is something you can build rather than only something you can extract.

Protein and peptide structure databases. The Protein Data Bank (PDB, rcsb.org) holds experimentally determined three-dimensional structures and is free. UniProt (uniprot.org) is the reference database for protein and peptide sequences, and is where to go if you want to check what a molecule's actual sequence is rather than what a product page says it is. Both are searchable by name.

Drug nomenclature. The World Health Organization's International Nonproprietary Names (INN) program assigns generic drug names and publishes the stem list — the reference behind §1.8. The USAN Council (United States Adopted Names, administered by the American Medical Association) does the equivalent for the United States. Both publish their stem conventions publicly. If you want to know what a suffix means, these are the authorities rather than a secondary source.

Approved drug labels. The FDA's Drugs@FDA database and DailyMed (from the National Library of Medicine) hold the complete approved labeling for every drug approved in the United States, free. This is the single most underused research resource available to a non-specialist, and Chapter 27 makes a case for reading labels directly. Start with insulin's, which is unusually clear.

Tier 2 — Attributed, specifics unverified

On the number of approved peptide drugs. Review articles on peptide therapeutics generally place the count of approved peptide drugs worldwide at more than eighty, with several dozen more in active clinical development. Counts vary by how the boundary with proteins is drawn — which is exactly the §1.5 problem, appearing in the literature rather than in marketing. Treat any precise figure with suspicion, including a precise figure that agrees with you.

On the amino acid alphabet. The proposition that the twenty proteinogenic amino acids represent a "frozen accident" — an early biochemical commitment that became unrevisable — is a widely held and seriously argued position rather than an established finding. Alternative accounts emphasize selection for chemical diversity or for availability in prebiotic conditions. The literature on this is genuinely unsettled, and sources that state one account as fact are overreaching.

On collagen peptide absorption. That di- and tripeptides including proline-hydroxyproline are detectable in blood after oral collagen ingestion has been reported in multiple studies. Whether those fragments produce clinically meaningful effects is not established, and the trial literature on clinical outcomes is characteristically small, short, and frequently industry-funded. See Case Study 2, and revisit after Chapter 5.

On peptide drug half-lives and molecular weights. Figures given in this chapter are approximate and drawn from standard references. Where a molecular weight matters (semaglutide at approximately 4,100 Da, insulin at approximately 5,800 Da), the approximation is deliberate — see the precision rule in this book's editorial standards.

Tier 3 — Illustrative and constructed

• The reader-question framings in §1.1 (the sister on Ozempic, the training partner, the \$90 serum, the clinic email) are constructed composites representing common real situations. No individual is described.
• The worked Field 1 dossier entries for insulin and BPC-157 in the chapter checkpoint are demonstrations built for this book, using publicly available identity information.
• All ASCII diagrams in this chapter are schematic teaching devices and are explicitly not to scale.

If you only read one thing

Look up a peptide on UniProt. Pick one from your dossier. Type the name, find the entry, and look at the sequence.

It takes two minutes and it changes something. A molecule you have only encountered as a word on a product page becomes a specific string of letters with a specific length, deposited in a public database, checkable by anyone. That is what the rest of this book means by identity — and, as Chapter 34 will make uncomfortably clear, it is entirely separate from the question of what is in any particular vial.

Looking ahead

Chapter 2's further reading covers receptor pharmacology and signal transduction. If you want to get ahead, the relevant background is G-protein-coupled receptors — the receptor family that most peptide drugs target, and the subject of the 2012 Nobel Prize in Chemistry (Lefkowitz and Kobilka), whose lectures are, again, free.