1426 17 DECEMBER 2021 • VOL 374 ISSUE 6574 science.org SCIENCEI
n his 1972 Nobel Prize acceptance
speech, American biochemist Christian
Anfinsen laid out a vision: One day it
would be possible, he said, to predict
the 3D structure of any protein merely
from its sequence of amino acid build-
ing blocks. With hundreds of thou-
sands of proteins in the human body
alone, such an advance would have
vast applications, offering insights into basic
biology and revealing promising new drug
targets. Now, after nearly 50 years, research-
ers have shown that artificial intelligence
(AI)-driven software can churn out accurate
protein structures by the thousands—an ad-
vance that realizes Anfinsen’s dream and is
Science’s 2021 Breakthrough of the Year.
Protein structures could once be deter-
mined only through painstaking lab analyses.
But they can now be calculated, quickly, for
tens of thousands of proteins, and for com-
plexes of interacting proteins. “This is a sea
change for structural biology,” says Gaetano
Montelione, a structural biologist at Rens-
selaer Polytechnic Institute. David Baker, a
University of Washington, Seattle, compu-
tational biochemist who led one of the pre-
diction projects, adds that with the bounty
of readily available structures, “All areas of
computational and molecular biology will
be transformed.”
Proteins are biology’s workhorses. Theycontract our muscles, convert food into cel-
lular energy, ferry oxygen in our blood, and
fight microbial invaders. Yet despite their
varied talents, all proteins start out with
the same basic form: a linear chain of up
to 20 different kinds of amino acids, strung
together in a sequence encoded in our DNA.
After being assembled in cellular factories
called ribosomes, each chain folds into
a unique, exquisitely complex 3D shape.
Those shapes, which determine how pro-
teins interact with other molecules, define
their roles in the cell.
Work by Anfinsen and others suggested in-
teractions between amino acids pull proteins
into their final shapes. But given the sheer
number of possible interactions between each
individual link in the chain and all the oth-
ers, even modest-size proteins could assume
an astronomical number of possible shapes.
In 1969, American molecular biologist CyrusLevinthal calculated that it would take longer
than the age of a universe for a protein chain
to cycle through them one by one—even at a
furious pace. But in nature, each protein reli-
ably folds up into just one distinctive shape,
usually in the blink of an eye.
In the 1950s, researchers started to map
proteins’ 3D structures by analyzing how x-
rays ricocheted off the molecules’ atoms. This
technique, known as x-ray crystallography,
soon became the leading approach; today,
the field’s central repository, the Protein Data
Bank, contains some 185,000 experimentally
solved structures. But mapping structures
can take years—and cost hundreds of thou-
sands of dollars per protein. To speed the
process, scientists started to create computer
models in the 1970s to predict how a given
protein would fold.
At first, that was possible only for small
proteins or short segments of larger ones. By
1994, however, computer models had grown
sophisticated enough to launch the biennial
Critical Assessment of protein Structure Pre-
diction (CASP) competition. Organizers gave
modelers the amino acid sequences of dozens
of proteins. At the end of the event, the mod-
elers’ results were compared with the latest
experimental data from x-ray crystallography
and emerging techniques such as nuclear
magnetic resonance spectroscopy and cryo–
electron microscopy (cryo-EM). Scores above
90 were considered on par with experimen-
tally solved structures. CREDITS: (ILLUSTRATION V. ALTOUNIAN/SCIENCE; (DATA I. R. HUMPHREYSET AL., SCIENCE374, 6573, EABM4805 (2021 DOI: 10.1126/SCIENCE.ABM2021
BREAKTHROUGH
OF THE YEARBy Robert F. Service
PROTEIN STRUCTURES
Artificial intelligence predicted how two proteins form
a complex involved in DNA repair in yeast.