092526 Lecture Video

Overview

Tim Johann explains how pH relative to pKa predicts amino acid protonation, then demonstrates Henderson–Hasselbalch calculations for a group with pKa 3.0 at pH 4.5, yielding about 3% protonated and 97% deprotonated forms. He connects protein isoelectric points to insulin glargine’s altered solubility and isoelectric focusing, then describes how X-ray crystallography, NMR, and cryo-electron microscopy produce protein structures.

Key takeaways

For a titratable group more than about two pH units from its pKa, its dominant protonation state is usually sufficient for a fast estimate without Henderson–Hasselbalch calculations.
At pH 4.5 for a carboxyl group with pKa 3.0, the A−/HA ratio is about 31.6, corresponding to approximately 97% deprotonated and 3% protonated forms.
A protein’s pI is the pH at which its total net charge is zero; individual charged groups can still remain within the protein.
Isoelectric focusing separates proteins by pI, and pairing it with molecular-weight electrophoresis provides a second dimension of separation.
X-ray crystallography derives protein models by fitting an amino acid sequence into an electron-density map calculated from diffraction by a protein crystal.
NMR structure calculations use measured proton relationships as distance restraints, often producing an ensemble of structures rather than a single uniquely determined conformation.

Chapters

0:00 Using pH and pKa to Predict Amino Acid Protonation

Groups are predominantly protonated below their pKa and deprotonated above it.
At pH 7, a carboxyl group with pKa 2 to 3 is deprotonated, while an amine with pKa 9 to 10 remains protonated.
When pH is more than about two units from a pKa, Johann treats the dominant form as effectively 100% for quick estimates.

3:00 Henderson–Hasselbalch Fractions for Alanine at pH 4.5

For the carboxyl group with pKa 3.0, pH 4.5 gives a pH–pKa difference of 1.5.
Henderson–Hasselbalch gives A−/HA = 10^1.5, or approximately 31.6.
Combining that ratio with a total of 100% gives about 3% HA and 97% A−; the amine group is treated as essentially fully protonated.

9:00 Protein Isoelectric Point and Insulin Glargine

The isoelectric point, or pI, is the pH where a protein’s net charge is zero, even though positive and negative groups remain present.
Johann uses insulin glargine to show how amino acid changes can raise insulin’s pI from about 5.4 to 6.7.
Glargine is injected in an acidic solution around pH 4 and becomes less soluble near physiological pH, forming a depot that dissolves gradually.

17:25 Separating Proteins with Isoelectric Focusing

An isoelectric focusing strip maintains a spatial pH gradient from low pH to high pH.
Proteins migrate under an electric field toward the position matching their pI, where their net charge is zero and movement stops.
Two-dimensional electrophoresis can combine pI separation with a second separation by molecular weight, spreading complex protein mixtures across a gel.

22:00 Protein Data Bank Structures and X-Ray Diffraction

Johann demonstrates a protein structure and bound ligand using the Protein Data Bank, including an example structure identified as 4G.
X-ray crystallography is presented as a major source of protein structures, alongside NMR and cryo-electron microscopy.
The diffraction principle is illustrated with light passing through two slits: constructive and destructive interference create a pattern related to spacing.

28:58 From Protein Crystal Diffraction to an Atomic Model

A regularly ordered protein crystal scatters X-rays, producing a three-dimensional diffraction pattern that is collected by a detector.
A computer converts the diffraction data into an electron-density map, and another program fits the known amino acid sequence into that map.
Atomic positions are estimates rather than exact locations; Johann describes an error around 2 angstroms as good for a crystal structure.

34:05 How 2D NMR Restraints Reveal Protein Folds

NMR structure determination uses signals from a protein’s many protons and 2D NMR measurements to identify proton relationships.
Spatially close protons can belong to amino acids far apart in the primary sequence, providing evidence about the protein’s three-dimensional fold.
A computer uses many distance restraints, such as a limit of roughly 4 angstroms, to generate an ensemble of structures consistent with the measurements.

38:50 Comparing NMR Ensembles with Cryo-EM Models

NMR results are often represented as a set of plausible structures that satisfy the experimental restraints, rather than one perfectly fixed model.
Cryo-electron microscopy also uses computational fitting to build a model from an experimental map or shape.
Johann contrasts typical cryo-EM resolutions of roughly 4 to 5 angstroms in the examples discussed with crystal structures around 2 angstroms or better.

Summary, takeaways, and chapters were generated by AI from the video's transcript and may contain errors. The video belongs to its creator, Tim Johann.