Foresight Update 4 (page 3)

A publication of the Foresight Institute

Table of Contents - Foresight Update 4

Recent Progresss: The Materials of Nanotechnology

by Russell Mills

The road to nanotechnology consists of several converging paths, each leading independently to the Assembler Breakthrough--the building of the first general molecular fabricators. Biotechnology is one of these paths, but not necessarily the shortest one.

Biotechnology seeks to understand and manipulate the molecules we have inherited through traditional evolutionary processes, focusing particularly on two chainlike molecules: proteins (chains of amino acids) and nucleic acids (chains of sugar and phosphate molecules with pyrimidine and purine bases attachments).

Nanotechnology, by contrast, deals with any material, chainlike or not, that can be designed and assembled atom-by-atom. In this sense nanotechnology is broader than biotechnology.

What materials will form the basis of the Assembler Breakthrough? One could argue that proteins and nucleic acids have the best (in fact, the only) "track record" as substrates for nanomachinery, and that these are therefore the materials of choice for building nanomachinery. But the qualities that made nucleic acids and proteins good choices as biological materials on the Earth several billion years ago are less relevant to nanotechnology today. Evolution selected them because of their chainlike structure and the ready availability of their component parts on prebiotic Earth. Molecular chains are favored over other structures because they can be copied and repaired by relatively simple molecular machines; Earth's evolutionary process places a premium on simplicity by emphasizing individual self-reliance--each individual organism is forced to contain most of the machinery needed for its own maintenance and replication.

Nanotechnology presents a very different situation: we do not want self-reliant assemblers. We will build assemblers that rely on us for support, and cannot function without externally supplied information, energy, or assistance in replication. This freedom from traditional evolutionary constraints opens up design possibilities that have never been exploited biologically. Even if, for historical reasons, the easiest route to nanotechnology turns out to lead through protein-based assemblers programmed with information conveyed by nucleic acid molecules, we should expect a rapid transition to better materials.

Let's look at where we stand in understanding and using traditional nanomachinery, then look at some developments in less traditional areas.

Protein structure & applications

The ability to redesign existing proteins (e.g., enzymes, regulatory proteins, receptor proteins), or to design new ones, depends on understanding the detailed relationship between function and configuration.

The amino acid sequences making up proteins are determined by direct analysis or from translation of the DNA or RNA sequences that encode them. These methods generate data rapidly.

On the other hand, 3D maps of proteins in their functional configurations are obtained by X-ray crystallography, sometimes with the aid of nuclear magnetic resonance (NMR). These are time-consuming methods.

The different rates at which these techniques can be used has given rise to a growing gap between the availability of sequence data and its interpretation and application:

Sequence data is available for more than 8000 proteins and is accumulating at an exponential rate (doubling time about 2 years) [1].
Only about 400 proteins have been spatially mapped. The number of these maps increases linearly (about 40 proteins per year). [1, 4]

Sequence data alone gives little indication of function. Progress in understanding protein function requires spatial maps, but proteins are difficult to crystallize in forms suitable for X-ray crystallography. This obstacle is now being surmounted by growing protein crystals on a mineral substrate, such as magnetite. The atomic spacing in the mineral surface seems to affect the pattern of deposition of protein molecules; the result has been the ability to grow some protein crystals with unprecedented ease, and in forms never before seen [5].

THE FOLDING PROBLEM

Proteins fold up into their functional conformations with little or no outside help; this implies that the amino acid chain itself contains the information needed to specify the folding pattern. A fast way to acquire useful data on protein function might therefore be to compute the most stable spatial configuration of protein chains from energy considerations and sequence data alone. This approach, known as "the folding problem", has slowly been yielding to efforts to solve it [7]. The general case has proved too difficult to carry out with present-day computers, but the problem size can be reduced in several ways [1, 4]:

For proteins with sequences similar to proteins of known structure, take parts of the known structure as givens.
Statistical properties of a sequence can identify segments that lie inside or outside the folded protein, or segments that make contact with a lipid matrix (suggesting a protein destined for a cell membrane).
NMR data can put constraints on distances between specific amino acids residues in the folded protein.
Exon shuffling (the swapping of DNA segments within the genome that is known to occur in genes associated with the immune system, and may turn out to be a much more general phenomenon) suggests that proteins are actually composed of a relatively small number of modular units. A number of such modules have already been identified, but it is not known to what extent all proteins are modular in this sense. To the extent that they are, the folding problem would reduce to a calculation of the packing configuration of a given set of prefolded modules.

THE ACTIVITY PROBLEM

Some investigators, ignoring spatial conformation, are trying to determine the functions of proteins from statistical properties of their sequences. They have determined, for example, that antigenic activity correlates with certain periodic variation of hydrophobic residues along a sequence. [4]

THE DESIGN PROBLEM

Despite difficulties with the folding problem and the activity problem, progress has been made (as predicted in 1981 [17]) in solving the design problem: to design a protein sequence that will give rise to a given activity. Several approaches are being pursued:

Limit the design to include only those aspects of protein folding which are already understood. For example, W. DeGrado at duPont has designed and built a protein that self-folds into a 4-helix bundle. It might be modified to incorporate biological functions [7].
Design a protein from native components. T. A. Jones of Univ. of Uppsala has used this approach to build retinol-binding protein by fitting together 22 fragments from other proteins. The resulting protein has a different amino-acid sequence than the protein it mimics, but has the same shape [1]. Similar modeling of triose phosphate isomerase and lactate dehydrogenase has been done by S. Wodak of l'Universite Libre de Bruxelles.
Modify existing proteins.

One recent effort at protein modification involves a redesign of the antimicrobial drug trimethoprim (TMP) to make it less toxic. Toxicity results from TMP attacking human dihydrofolate reductase (dHFR) in addition to bacterial dHFR, its intended target. The strategy being taken is to reduce the floppiness of the TMP molecule, so that it fits only its target and not human dHFR. [1]

Another example is a redesign of glucose isomerase (commercially important in corn syrup production) to improve its efficiency, by taking cues from the structure of triose phosphate isomerase, an enzyme that catalyzes a different reaction but does so 10,000 times faster. [1]

Genex has developed a technique for redesigning antibody molecules. The result is a much smaller antibody that consists of a single chain instead of four chains, is much easier to produce in quantity, elicits fewer side effects when used in patients, is more stable, and binds better to the target molecules. The trick is to use computer-designed sequences of amino-acids to link together binding sites which formerly were located on separate protein chains. The technique may lend itself to the redesign of many other useful protein molecules besides antibodies. [15]

Table of Contents - Foresight Update 4

Nucleic acid structure

Nucleic acids are sequenced either by chopping them into pieces of all possible lengths, or by causing them to grow into such a set of pieces in the first place, and then separating the pieces by electrophoresis. The sequencing procedure is even easier than that of proteins, and some of the steps have been automated.

About 20 million nucleotides from hundreds of organisms have been sequenced and the number is increasing exponentially. The doubling time, currently 2 to 3 years, is expected to decrease sharply soon. A sequencing rate of one million bases per day is anticipated by 1996. [4]

As with proteins, to know the sequence is not to know the function. Some of the most interesting and useful biological information resides in the local geometry of nucleic acids: information about gene boundaries, regulatory binding sites, polymerase binding sites, ribosomal sites, posttranslational modification sites, etc. While the average spatial architecture of nucleic acids is known in detail, local variations in this architecture are hard to study and data is sparse [4].

The number of nucleic acid structures known from crystallographic studies is less than 40.
Statistical analysis of nucleic acid sequences can identify some of these structures in DNA, and can be done by computer. Reliability varies greatly, but is as high as 90% in some cases.

Table of Contents - Foresight Update 4

Nontraditional materials

SELF-ASSEMBLING MEMBRANES

A traditional cell membrane is like a sea of inert material with, here and there, a floating island of protein machinery. The sea is a mixture of fatty molecules (phospholipids, like lecithin) and cholesterol molecules, the relative proportions of which determine how wavy and flexible the surface is. Typically the protein machines extend all the way through the cell membrane, providing specialized communications links (or in some cases pores) between the inside and outside of the cell.

By determining what goes in and comes out of a cell, the cell membrane defines the relations a cell has with the external world. It is therefore intriguing to think of what might be possible if such membranes could be deliberately altered, or if entirely different kinds of active membranes could be designed and synthesized.

At the Weizmann Institute of Science a group led by Israel Rubinstein is making membranes from molecules chosen for their ability to mimic one function of biological membranes: the ability to recognize ions in the solution surrounding the cell. These investigators have found that a mixture of 2,2'-thiobisethyl acetoacetate (TBEA) and n-octadecyl mercaptan (OM) will spontaneously assemble into a layer one molecule thick on a gold electrode. TBEA is the active element; OM plugs gaps between TBEA molecules preventing direct access to the gold substrate. When the coated electrode is put in a solution with copper and iron ions, it is found that copper ions are reduced to elemental copper, whereas iron ions are unaffected. The mechanism depends on the fact that TBEA molecules have two arms that open just wide enough for a copper ion to slip in and bind to four oxygens projecting from the arms. This brings the copper ion to within 7 angstroms (.7 nm) of the gold substrate--close enough for electrons to pass by quantum-mechanical tunneling from the substrate to the copper. Because of their geometry, iron atoms are not accepted into the arms of TBEA. [13, 14]

SYNTHETIC NANO-EFFECTORS

A group at UCLA led by Donald J. Cram has launched a full-scale attack on the problem of nano-effector design [16]. Working entirely away from the protein/nucleic acid path blazed by terrestrial evolution over the past several billion years, this group has designed hundreds of molecules of varying shapes, hoping to learn how to make molecules with desired catalytic properties. Cram's co-workers synthesized more than 75 of these designed molecules and subjected them to X-ray crystallography to check the correspondence between design and actual structure. A series of compounds of gradually increasing complexity was then tested for the intended activity: in one case the ability to selectively bind certain ions (lithium, sodium, potassium, and others). The compounds performed extremely well.

In another set of experiments, the aim was to build molecules able to discriminate between D-and L-amino acids and ester salts--a task that seemed intractable earlier in this century. So successful were their efforts that the investigators were able to build a machine based on the designed molecules; when a 50-50 D-L mixture was poured into the machine, the machine delivered two solutions with 86 to 90% separation of the two substances.

In yet another branch of their work, Cram's group is designing molecules that mimic the actions of enzymes. Free of the requirement to build everything out of amino acids, they have been able to come up with molecules far smaller (though not easier to make) than the enzymes being imitated. Their mimic for the enzyme chymotrypsin has been synthesized and tested; it proved to have some, but not all, of the functionality of chymotrypsin itself.

DIAMOND

Diamond is in the news, and this is good news for nanotechnology. Diamond is a prime candidate material for building nanomachines for several reasons: the tetrahedral geometry of its bonds lets it be shaped in three dimensions without becoming floppy; it is made of carbon, the chemistry of which is well understood; and carbon atoms make a variety of useful bonds with other types of atoms. Diamond research may therefore advance nanotechnology even when it is pursued for its short-term commercial potential. Progress in understanding and making diamonds has been driven mainly by work done in the Soviet Union [8, 9]:

In the 1930s Soviet scientists calculated a phase diagram for diamond and began looking for easy ways to synthesize diamond.
In the 1950s, while American industry started manufacturing diamonds at 2,000 degrees C and 55,000 atmospheres pressure, Soviet scientists developed a vapor deposition method for growing diamond fibers at 1,000 degrees C and low pressures.
During the 1960s and 1970s, the Soviet group improved on this process, aiming to produce diamond films.

The technological implications of diamond films have recently been realized in Japan and the U.S., and so a race has begun to develop this technology. Dramatic discoveries are being made:

At the University of Texas 10-nanosecond laser pulses are being used to vaporize graphite, which then deposits as a film 20 nm thick over areas as large as 10 square centimeters. The film is diamond-like, but may turn out to be something new. [3]
Soviet researchers report the discovery of a new form of carbon much harder than diamond, called C₈. They use an ion beam of low energy to produce thin films of the substance. Carbon atoms in C₈ appear to have tetrahedral bonds, but the lattice is somehow different than in diamond--it may simply be somewhat random, resembling a glass rather than a crystal. [8]

Much of the new interest in diamond is motivated by near-term commercial applications like diamond-coated razor blades, scratch-resistant windows and radiation-resistant semiconductors for nuclear missiles. The C₈ results, however, are of special relevance to nanotechnology, showing us that diamond is just the default form of more general tetrahedral bonding patterns for carbon. Choosing from among the many possible departures from crystalline regularity may turn out to be an important of nanomachine design.

Speaking of crystallinity ... a "new state of matter" has been announced, called the nanocrystal [6]. The nanocrystalline state is one in which roughly half the atoms occupy sites in crystal grains, while the other half are free to move between and around the grains. Both populations of atoms have the same chemical composition (titanium oxide, for example), and atoms are easily exchanged between the grains and the matrix. The response of such a material to strain is plastic rather than brittle, because grains can change shape quickly instead of hammering against each other or being forced apart (cracking). This flow of atoms and restructuring of grains does not turn the material into a liquid or a putty; at macro scales, nanocrystalline materials are as solid as their ordinary counterparts.

Nanocrystallinity is a function of grain size. In nanocrystals the grains are about 10 nanometers across--1000 times smaller than in ordinary materials. Small grain size implies large surface-to-volume ratio and short diffusion "circuits" around the grains--hence, rapid response to strain. In the case of nanocrystalline copper, self-diffusion at 20-120 degrees C is increased by 19 orders of magnitude over ordinary copper!

J. Israelachvili and collaborators are studying the properties of bulk materials as one or more dimensions of a system is reduced to the size of a few molecules or less [10, 11]. Previous work has shown that some properties remain similar to bulk properties: e.g., refractive index, dielectric constant, and surface energy. Now they have undertaken to measure viscosity in thin films trapped between two solid surfaces. They report that as the liquid layer thins to less than 10 molecular diameters the liquid stops acting like a continuum and comes to resemble a series of layers; the principles of viscosity no longer describe the relationship between shear forces and sliding motion.

Sliding parts in a mechanical nanocomputer require no special lubrication.

Above: Mechanism for two nanocomputer gates, initial position. One control rod with two gate knobs is seen laterally; two more more rods with knobs are seen end on. Each rod with associated knobs is a single molecule.

Below: The lateral rod has been pulled to the left during computation. Notice that one of the end-on rods has now been blocked and the other one unblocked in mechanical mimicry of the transistor action.

The amount of force required to initiate sliding (the critical shear stress) is much greater in such systems than that predicted by extrapolating from bulk properties. Taken at face value this suggests that nanomachines with moving parts would get stuck unless the parts remained in continuous motion, even when lubricants are present. But a better interpretation is that the concept of liquid lubrication becomes meaningless at the nanometer scale.

Liquids, the atoms of which are not tied down, evade part of the design process. This is acceptable in a bulk machine, but not in a nanomachine, the design of which must specify the behavior of every atom. "Lubrication" in a nanomachine would consist of an optimization of the chemical type, location, and orientation of each atom in the machine; it would inhere in the design of the solid parts themselves rather than in a separate liquid substance [18].

Dr. Mills has a degree in biophysics and runs a business in Palo Alto. He also assists with the production of Foresight Update.

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References

Barbara Jasny, Science 240:722-723 (6May88)
Science News 134:116 (6Aug88)
Science News 134:94 (6Aug88)
Charles DeLisi, Science 240:47-52 (1Apr88)
Ivars Peterson, Science News 133:154-155 (5Mar88)
Robert W. Cahn, Nature 332:112-113 (10Mar88)
Thomas E. Creighton, Science 240:267 (15Apr88)
Mike Simpson, New Scientist:50-53 (10Mar88)
The Economist: 92 (23Apr88)
Jacob N. Israelachvili, et al., Science 240:189-191 (8Apr88)
Ivars Peterson, Science News 133:283 (30Apr88)
Nature 332:374-376 (24Mar88)
R.J.P. Williams, Nature 332:393 (31Mar88)
Israel Rubenstein, et al., Nature 332:426-429 (31Mar88)
The Economist: 75 (27Feb88)
Donald J. Cram, Science 240:760-767 (6May88)
K. Eric Drexler, Proc. Nat. Acad. Sci. USA 78:5275-5278 (1981)
K. Eric Drexler, in Proceedings of the IEEE Micro Robots and Teleoperators Workshop, IEEE87TH0204-8 (1987)

Table of Contents - Foresight Update 4

Foresight thanks Dave Kilbridge for converting Update 4 to html for this web page.

From Foresight Update 4, originally published 15 October 1988.
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