For more than a decade, molecular biologist Martin Beck and his colleagues have been trying to piece together one of the world’s hardest jigsaw puzzles: a detailed model of the largest molecular machine in human cells.
This behemoth, called the nuclear pore complex, controls the flow of molecules in and out of the nucleus of the cell, where the genome sits. Hundreds of these complexes exist in every cell. Each is made up of more than 1,000 proteins that together form rings around a hole through the nuclear membrane.
These 1,000 puzzle pieces are drawn from more than 30 protein building blocks that interlace in myriad ways. Making the puzzle even harder, the experimentally determined 3D shapes of these building blocks are a potpourri of structures gathered from many species, so don’t always mesh together well. And the picture on the puzzle’s box — a low-resolution 3D view of the nuclear pore complex — lacks sufficient detail to know how many of the pieces precisely fit together.
In 2016, a team led by Beck, who is based at the Max Planck Institute of Biophysics (MPIB) in Frankfurt, Germany, reported a model1 that covered about 30% of the nuclear pore complex and around half of the 30 building blocks, called Nup proteins.
Then, last July, London-based firm DeepMind, part of Alphabet — Google’s parent company — made public an artificial intelligence (AI) tool called AlphaFold2. The software could predict the 3D shape of proteins from their genetic sequence with, for the most part, pinpoint accuracy. This transformed Beck’s task, and the studies of thousands of other biologists (see ‘AlphaFold mania’).
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