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YOUR BODY is teeming with quantum computers. Marching along your DNA and
floating around your cells, several hundred million of these minuscule devices
are rearranging your molecules in super-efficient quantum fashion.

So, at any rate, says Apoorva Patel, a physicist at the Indian Institute of
Science in Bangalore. According to Patel, these weird machines are essential to
life. Every living thing from the greatest whale to the lowliest bacterium
depends on an army of quantum computers to copy its DNA and put together its
proteins.

To many biologists this seems like a bad joke. Received wisdom is that
quantum physics, aside from a few minor details, has nothing to do with biology.
Sure, it underlies the chemistry of all molecules, including biological ones,
but the quantum weirdness is kept well out of sight.

Even physicists have reason to be scornful. For 15 years, they have struggled
to build a quantum computer, a device that could exploit the peculiar properties
of the quantum world to do calculations with a style and speed to put any
ordinary computer to shame. Physicists generally concede that the task is so
formidable that a practical quantum computer won鈥檛 exist for decades.

So Patel鈥檚 proposal, which he unveiled in an electronic preprint in February
(http://xxx.lanl.gov/abs/quant-ph/0002037), is a radical one by anyone鈥檚
standards. The forces of evolution, he claims, may have solved the problem of
quantum computing several billion years ago. It鈥檚 a startling idea鈥攂ut if
true, it could explain a puzzle at the core of biology.

Biologists have known for half a century that the sequence of bases along
each strand of DNA encodes biological recipes for making proteins. Each base is
one of four possible kinds鈥攃ytosine (C), guanine (G), adenine (A) and
thymine (T). So there is a fundamental difference between the four-letter code
of DNA and the strings of 0s and 1s in any computer, where there are only two
alternatives. This is where the mystery begins: why four rather than just
two?

A binary code ought to be better. Modern computers use only two characters so
they can store information using very simple components. To store a 0 or 1, the
transistors inside a microchip only need two states, 鈥渙n鈥� and 鈥渙ff鈥�. More
characters in the code would demand more complicated and costly devices.

Binary logic also cuts down on mistakes. Imagine walking to a distant hilltop
and then trying to transmit a message back to a friend. You might carry 26
flags, one for each letter, and try to spell out messages that way. But on a
breezy day an E might look like an F, and a P like an R. You鈥檇 be better off
using just two flags, one black, one white, and expressing letters as strings of
the two. Then your friend would face nothing but simple black-white decisions,
and you could be more confident in your communications. When it comes to
handling information, computer scientists agree that binary is best.

So why doesn鈥檛 biology use it? Several billion years ago, when the first
self-replicating molecules were evolving, this simplest of all codes ought to
have been the first to arise, and should have defeated other, more error-prone
codes in the evolutionary race. Or might there be something mysteriously
efficient about the number 4?

Patel thinks there is. To see why, we need to think in terms of computation.
鈥淐omputation is nothing but the processing of information,鈥� he says, 鈥渟o we can
study what DNA does from the viewpoint of computer science.鈥�

A biological computation happens every time a cell divides: the data stored
in one set of DNA molecules gets copied into another set. In a stretch of
double-stranded DNA, bonds link the bases along one strand to those on the
other, with every C bound to a complementary G, and every A to a T. Just before
cell division, enzymes unzip the strands, exposing the bases to the cell鈥檚
internal soup of raw materials. Another enzyme known as a DNA polymerase then
marches along each of the two strands, triggering each base to pair up with a
complementary base from the soup. Step by step, the polymerase copies the
genetic information and creates two new double-stranded DNA molecules identical
to the original.

But there鈥檚 more to this than the simple copying of data. As Patel sees it,
the soup of bases is like a disorganised database containing four kinds of
entry. The polymerase鈥檚 task is to find an entry of one particular kind. As the
polymerase repeatedly searches for the right base in the alphabet soup, it is
doing computations. And here lies the nub of Patel鈥檚 idea: we would expect the
polymerase to search in the best way possible. So what is the best of all
possible ways to search a database?

In conventional computing, the best you can do is trial and error. To search
for one kind of object in a jumble of N different kinds, you try one
after another until you get lucky. This way you will find the right thing after
an average of N attempts. For instance, it takes four tries on average
to find a heart by cutting a shuffled pack of cards. This is just like the soup
of bases, which would get shuffled by thermal motions after each attempt.

So molecular biologists assume that DNA polymerase works in the same way.
Every so often, a base of some random kind wanders past the polymerase. It
becomes attached to the growing chain if it happens to be the correct base, and
wanders off again if it isn鈥檛. In that case, a polymerase would need to test an
average of four bases before finding the right one. Normally, this is the best
that can possibly be done. But, says Patel, it is possible to do better by
exploiting one of the weirder consequences of quantum mechanics.

In an ordinary computer, a transistor can be either on or off, so a bit is
always either 1 or 0. An alternative is to exploit quantum physics, and to store
information using single quantum particles such as electrons. One might store
bits in an electron鈥檚 spin, for example, which can be either 鈥渦p鈥� or 鈥渄own鈥�. The
key is that the quantum world also allows other seemingly nonsensical
possibilities: an electron鈥檚 spin can be neither up nor down, but in a
superposition of both. So a string of electrons can hold not just one distinct
string of 0s and 1s, but every conceivable string all at once.

As a consequence, a computer handling information in quantum fashion could do
parallel processing on an outrageous scale, testing many possibilities at the
same time. In 1997 mathematician Lov Grover of the IBM Research Division showed
that a quantum computer can search a database far faster than any classical
device. It starts with a superposition of all the different items in a database,
and alters this quantum state to amplify the desired item and make the others
fade away. For a huge database, the time savings are huge, and even for smaller
values of N the quantum procedure is faster.

Coincidentally, Patel and Grover were graduate students together at Caltech
in the early 1980s. 鈥淲e met again last year,鈥� says Grover, 鈥渢hrough a mutual
interest in quantum computing.鈥� To Patel, Grover鈥檚 algorithm suggested an
intriguing question: might biochemistry pull off a quantum computation?

Grover鈥檚 mathematics gives an exact formula for the number of quantum
attempts, Q, needed to find one specific element in a database of
N things. It turns out that if N = 4, then Q = 1. In
other words, a quantum computer can distinguish between four distinct
possibilities with just one attempt.

Of course, it would also take a single quantum step to distinguish between
two possibilities. But with a four-base code, DNA only needs to be half the
length. So biology might have decided to use four bases instead of two so that
replication of the molecule can happen twice as quickly.

For Patel鈥檚 idea to work, the DNA polymerase would have to be able to
manipulate the biochemical soup around it, watching over the base-pair bonding
process to ensure that it occurs in a coherent, quantum-mechanical way. Each
time the enzyme moves to a new base on the strand of DNA it is copying, it sets
up a quantum superposition of the four bases that lie somewhere in its vicinity,
with one ghostly component corresponding to each. According to quantum theory,
such ghosts act like independent waves that move towards the exposed base on the
DNA strand.

Next, Patel believes, the superposition of the four 鈥渋ncoming鈥� waves starts
to interact with the exposed base. This should alter the four waves in different
ways, he says, making them interfere with one another in such a way that the
ghosts for each incorrect base cancel out, while those for the correct base
reinforce. At this point, the C-G-A-T superposition collapses, leaving the
correct base bound to the DNA chain with a hydrogen bond. In other words, the
enzyme should act like a sort of waveguide, ushering the component wave for the
correct base into its proper resting place, while rejecting the
others鈥攃arrying out Grover鈥檚 quantum search in the process.

鈥淭he quantum search scheme he shows is very nice,鈥� says Grover, 鈥渁lthough a
few of the details are somewhat speculative. If true, it is another instance
where nature first figured out how to do things better than us.鈥�

Perhaps the biggest 鈥渋f鈥� is whether the noisy environment within the cell
would permit all this quantum business. The greatest obstacle to building a
quantum computer in the lab is the need to isolate all its working parts from
external disturbances, as almost any interference will destroy the fragile
quantum dynamics. In all their attempts so far, physicists have tried to do this
by cooling their apparatus down to near absolute zero. At the temperature inside
a living cell, the enzyme and the four bases ought to suffer an annihilating
storm of abuse, which should wipe out any possibility of quantum behaviour.

So DNA polymerase would somehow have to protect the environment around the
growing DNA strand, permitting the quantum computation to go forward
undisturbed. Patel points out that the configuration of electrons around atomic
nuclei helps to shield some nuclear properties from their environment. Nuclear
spins remain in quantum superpositions for several seconds. He suggests that
something similar happens in biochemistry.

No one knows whether DNA polymerases really have all these properties, and
yet the idea may not be so ludicrous: quantum physics is not as foreign to
biology as one might think. In photosynthesis, biology exploits quantum
possibilities at a scale above that of single molecules. When a photon is
absorbed by a photosynthesising cell, its energy excites an electron into a
delocalised state spread out over tens of molecules.

Patel鈥檚 proposal is more radical, in that it involves quantum superpositions
of whole molecules. The more massive the object, the less obvious its quantum
nature should be: lightweight electrons flaunt their quantum properties, while
whole molecules are usually more coy. But some researchers have begun to suspect
that all enzymes may depend on a quantum process involving protons鈥攕till
150 times lighter than bases, but 2000 times heavier than electrons. Last year,
biochemist Judith Klinsman and colleagues from the University of California at
Berkeley demonstrated that to speed up crucial cellular chemical reactions, some
bacterial enzymes rely on the tunnelling of protons鈥攁 quantum process that
allows a particle to pass through a barrier even if it hasn鈥檛 got enough energy
to climb over. What鈥檚 more, they manage the feat even at room temperature.

Finding out whether DNA polymerases perform even more daring quantum tricks
will require careful experiments. In the meantime, Patel is trying to see where
else the quantum connection leads. Every protein in the human body is a string
made from 20 different kinds of amino acid. Why 20? Here again, Patel thinks,
the signs point to quantum computing.

To set the stage for the making of proteins, a strand of messenger RNA copies
the genetic information from DNA and carries it out to a ribosome, one of the
cell鈥檚 protein manufacturing plants. The ribosome steps along the messenger RNA,
and to each set of three base pairs attaches a tRNA, a stringy molecule with
three base pairs at one end and an amino acid at the other. Once again, the
ribosome faces a search: to build the right protein, it has to repeatedly find a
tRNA corresponding to just one of the 20 kinds of amino acid in the soup.

The number 20 would seem to have little connection to anything. Patel points
out, however, that this is just the right number to set up another
super-efficient quantum search: for according to Grover鈥檚 algorithm, a
three-step quantum search can find an object in a database containing up to 20
kinds of entry. Like the number of bases, then, the number of amino acids seems
to be just right if biology has set things up so that the protein manufacturing
process is, in a quantum sense, as efficient as it can be.

鈥淭he numbers are certainly very provocative,鈥� says Grover. As Patel puts it,
鈥淭his is the first time they have come out of an algorithm that performs the
actual task accomplished by DNA.鈥� But do these numbers really point to quantum
computers at the heart of life?

Evolutionary biologists are not convinced. 鈥淭his field is rife with premature
speculation,鈥� says Laurence Hurst of the University of Bath. 鈥淭he history of the
20 amino acids problem has seen some of the most ingenious explanations, which
at first looked even better than this one.鈥� They were all shot down in flames,
he adds, when the biochemistry of the code was finally unravelled. With regard
to the number of amino acids, Hurst points to one specific issue that Patel
concedes is rather troubling: that the correspondence between tRNAs and amino
acids isn鈥檛 one-to-one. 鈥淭here may be 20 amino acids,鈥� says Hurst, 鈥渂ut the same
amino acid can get put onto different tRNAs, and the tRNA does the interacting.
So it seems to me that there are more than 20 types to be found.鈥�

Even if Patel鈥檚 idea won鈥檛 stretch this far, it may still explain why there
are four bases in the basic structure of DNA. 鈥淎poorva generates a lot of
ideas,鈥� says Grover, 鈥渁nd I think irrespective of how the biological and
chemical aspects turn out, this one will make an impact.鈥� And after all, why
wouldn鈥檛 evolution exploit any quantum avenues open to it? If the cell spurns
quantum tricks, wouldn鈥檛 that need some explaining of its own?