Introduction to Biochemistry

Under scientific review

This introductory page is under scientific review. Use it for orientation, not clinical decision-making.

Biochemistry is the study of chemical processes within and related to living organisms. It is a subdiscipline of biology and chemistry and can be divided into three fields: structural biology, enzymology, and metabolism.

The Data Structures of Life (Macromolecules)

For a developer, the human body processes 3 major "primitive types" of molecular structures:

1. Nucleic Acids (DNA/RNA): The database. They are polymers formed by a "String" of only 4 characters (A, T, C, G or A, U, C, G). The computational focus here is Sequence Bioinformatics (String alignment, Graph algorithms).
2. Proteins: The physical machines. Formed by 20 different "characters" (Amino Acids). The challenge here is not just reading the string, but understanding the physics of how this string "folds" into 3D.
3. Lipids and Carbohydrates (Metabolites): The fuels and cell walls. They are molecules of heterogeneous chemistry. The computational focus here is Network Theory and Metabolic Graphs (e.g., databases like KEGG).

Cancer often subverts metabolism (Warburg Effect), changing the routing of the carbohydrate network to prioritize rapid cell division.

Cancer Enzymology

Enzymes are proteins that catalyze chemical reactions:

• Kinases: Often hyperactive in cancer
• Therapeutic Targets: Specific inhibitors for treatment
• Regulation: Control of enzymatic activity

The Computational Challenge of Protein Folding

For 50 years, biochemistry had a massive computational problem: How to predict the 3D (physical) structure of a protein knowing only its 1D string of amino acids?

Protein folding determines whether a drug can bind to it or not (Molecular docking). In cancer, mutations change a single amino acid in the string, which can completely change the 3D shape of the protein, rendering a drug useless (Acquired Resistance).

For decades, the only way to discover the 3D structure was using X-ray crystallography (which takes months or years per protein). The computational search space was so infinite (Levinthal's Paradox) that no supercomputer could simulate the physics of folding by brute force.

The AI Revolution (AlphaFold)

The problem shifted from Computational Physics to Deep Learning. Tools based on Transformers, notably AlphaFold (Google DeepMind) and ESMFold (Meta), learned to map the text string to 3D coordinates $(x,y,z)$ in minutes. Today, developers in Computer-Aided Drug Design (CADD) use these predicted structures to simulate (via graph neural networks) where small molecules (cancer drugs) can fit into the damaged cellular machinery.

Learning Resources

• Books: Lehninger Principles of Biochemistry
• Courses: Khan Academy: cellular respiration and metabolism, Coursera biochemistry courses
• Tools: KEGG, Reactome, MetaCyc

---

Cancer biochemistry is the study of alterations in biochemical processes that occur in cancer cells.