Haemoglobin and Oxygen Dissociation

Haemoglobin is a globular protein with quaternary structure. Its subunits contain haem groups with iron ions involved in reversible oxygen binding. Red blood cells provide a high concentration of haemoglobin; their biconcave shape gives a large surface relative to volume and a short diffusion path.

Reversible binding allows loading at high oxygen partial pressure and unloading at lower partial pressure. Oxygenated haemoglobin is not permanently bonded to oxygen as an irreversible end product. The first oxygen bindings alter haemoglobin’s conformation in ways that facilitate further binding, producing cooperative behaviour and a sigmoid dissociation curve.

The steep region allows a relatively small fall in tissue oxygen partial pressure to produce a substantial fall in saturation and release of oxygen. At higher pressures the plateau helps maintain substantial loading even if lung oxygen pressure varies moderately.

To compare affinity, choose the same oxygen partial pressure on both curves. A higher saturation at that pressure indicates greater affinity under the stated conditions. A left-shifted curve generally indicates higher affinity; it can help loading in low-oxygen conditions but may make unloading less easy. Do not compare unrelated points at different pressures and call the difference affinity.

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Higher carbon dioxide concentration can reduce haemoglobin’s oxygen affinity, shifting the curve to the right: the Bohr effect. Metabolically active tissues produce more carbon dioxide and use oxygen, so this shift promotes oxygen unloading where demand is high. Link the changed environment to the changed binding behaviour.

Different organisms can possess haemoglobins with different affinities suited to their environments and demands. An adaptation should be evaluated through both loading and unloading. “More affinity is always better” ignores the requirement to deliver oxygen to tissues after it has been loaded.

Try each question before opening the worked response. Use precise biological terms, connect each cause to its effect, and check units and assumptions when interpreting data.