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Adapted from
“Mechanical Control of Spin States
in Spin-1 Molecules and the Underscreened Kondo Effect”
J. J. Parks et al., Science, 328:1370–1373 (2010).

Pulling on the ends of a cobalt complex that bridges an electrical junction (as illustrated) changes the geometry of the coordinating ligands, hence the energies of electronic spin states, hence (as it turns out) the low-temperature electrical resistance of the junction. The authors of the paper cited here look toward potential applications for devices that manipulate spin states mechanically:

…Our work further demonstrates that mechanical control can be a realistic strategy for manipulating molecular spin states to supplement or replace the use of magnetic fields in proposed applications such as quantum manipulation or information storage.
(Science,June 2010)

Whether or not their approach is practical, this paper is a reminder that almost all molecular properties are sensitive to mechanical effects, and sometimes in important ways. Modulating chemical reactivity and selecting among reaction sites are basic and obvious examples of molecular mechanical effects, but the general class can be anticipated to be as broad as the effects of temperature or pressure.

• Mechanochemistry, Mechanosynthesis, and Molecular Machinery
• The Physical Basis of Atomically Precise Manufacturing
• Productive nanosystems: the physics of molecular fabrication [pdf]
  (from the Institute of Physics journal, Physics Education)
• Molecular Nanomachines: Physical Principles and Implementation Strategies (from the Annual Review of Biophysics and Biomolecular Structure)

As regular readers know, I see foldamer engineering as a key to next-generation atomically precise nanosystems. Valuable in themselves, foldamers can also serve as components of composite systems that exploit diverse materials and nanotechnologies of qualitatively different kinds.

“Foldamers: Accomplishments and Goals”, by Samuel Gellman, heads a collection of 59 abstracts from a recent international conference on foldamers held in Bordeaux-Pessac, France. (Note that Gellman also authored the classic 1998 paper, “Foldamers: A Manifesto”.)

This set of abstracts offers a good window into the state of a broad, dynamic, and important field.

Zinc fingers & DNA

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From “Toward Modular Molecular
Composite Nanosystems”
[talk slides, pdf]

Zinc finger technology has great promise in genetic engineering and therapeutics, with potential applications in structural DNA nanotechnology, too.

Zinc finger proteins (ZFPs) are often called “game changing” because of the unprecedented way they precisely modify genes. Excitement about them is mirrored in the number of related scientific publications, which have climbed from hardly any 20 years ago to more than 360 in 2009.

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Chemical & Engineering News

A ZFP is a sequence of small protein structures (the fingers) that, taken together, bind to a specific DNA sequence. Unlike oligonucleotides, which bind to the Watson-Crick interface of single-stranded DNA, ZFPs bind in the major groove of double-stranded DNA (dsDNA), recognizing DNA base pairs from the side. They’re modular and can be engineered to target sequences chosen by a designer.

This mode of binding enables sequence-specific interactions without prying DNA strands apart, a fundamental advantage in a biological context. Binding dsDNA also opens a range of potential applications in structural DNA nanotechnology because it provides a way to bind protein structures to a dsDNA scaffold at specific sites, and with relatively high rigidity. This is an enabler for the DNA/protein/special-structure approach to modular molecular composite nanosystems.

Each finger binds with a degree of specificity and affinity, but multiple fingers must be stitched together to achieve tight, high-affinity binding to unique sequences. This engineering problem is tractable. There’s an open-source Zinc Finger Consortium (and a zinc-finger design server), as well as a thriving biotechnology company with a fat patent portfolio, Sangamo BioSciences. Sangamo aims to to produce products for medicine.

ZFPs enable a clever trick for editing DNA: A nuclease that cuts dsDNA can be inactivated by splitting into domains that regain activity when brought together. The complementary domains are linked to ZFPs that bind DNA sequences flanking a target site. Where these sequences are found together, both ZFPs bind, bringing the nuclease domains together; these bind, regain function, and cut, leaving the rest of the genome untouched.

This synergistic, cleanly targeted operation can be leveraged to inactivate or edit a selected genetic component with unmatched reliability and specificity. Powerful applications follow.

华大基因
BGI

In a decade, the global Human Genome Project sequenced 3 billion DNA base pairs. Today, a single machine (the Illumina HiSeq™ 2000) can sequence 25 billion base pairs per day, and BGI (the Shenzhen company formerly known as the Beijing Genomics Institute) has purchased 128 of them. This puts BGI “on track to surpass the entire sequencing output of the United States”.

These statistics are from a news article in Nature, “The Sequence Factory”, that also discusses controversies about the scientific status of the work, and mentions “the charge that the BGI has reduced science to brute mechanization”.

This is absurd, because this aspect of BGI’s work isn’t science to begin with: BGI is (merely!) providing data of enormous scientific value, enabled by state-of-the art instruments. This requires smart problem-solving by scientifically trained staff, some of whom participate in the science side of BGI’s work, but these connections are beside the point. Having science-based input and science-enabling output doesn’t change the nature of the task itself.

Wang Jun, executive director of BGI, jokes that “We are the muscle, we have no brain”. If engineering and production were brainless, and if that were all BGI did, this might be an accurate metaphor.

Comprehensive data is nature on display

Data-intensive science includes what looks like traditional scientific work writ large (collecting gigabytes of genome sequence, petabytes of sky-wide telescopic images) but collecting these comprehensive datasets lacks the hypothesis-testing aspect of science.

Rather than trying to force comprehensive data-collection projects into the mold of science, I think it’s better to view them as providing instruments that make nature more visible.

Genomic data can replace slow and costly gene-reading with fast and cheap database-reading. Within instrumental limits, synoptic sky surveys can replace scarce telescope time with unlimited data access. If reading from database isn’t a way to read nature, then reading any instrument, viewing any image, fails the same test.

Making new instruments isn’t science. It is merely a process of technology development that sets the pace of scientific progress and makes new sciences possible.

• Science and Engineering: A Layer-Cake of Inquiry and Design
• The Data Explosion and the Scientific Method
• Learning Bioinformatics

Bioinformatics is huge, growing, fast, and has a surprising range of applications to molecular systems engineering. Here’s a PLoS article: “A Quick Guide for Developing Effective Bioinformatics Programming Skills”. From the abstract:

Successful adoption of these principals will serve both beginner and experienced bioinformaticians alike in career development and pursuit of professional and scientific goals.

See also:

• How to study for a career in nanotechnology
• Macromolecular Modeling for Molecular Systems Engineering
• How to Learn About Everything

Students often ask me for advice on how to study for a career in nanotechnology, and as you might imagine, providing a good answer is challenging. “Nanotechnology” refers to a notoriously broad range of areas of science and technology, and progress during a student’s career will open new areas, and some are yet to be imagined. Choices within this complex and changing field should reflect a student’s areas of interest and ability, current background, level of ambition, and willingness to to accept risk — there is a trade-off between pioneering new directions and seeking a secure career path.

Here is an attempt to give a useful answer that takes account of these unknowns. My advice centers on fundamentals, outlining areas of knowledge are are universally important, and offering suggestions for how to approach both specialized choices and learning in general. It includes observations about the future of nanotechnology, the context for future careers.

Learn the fundamentals, and not just in science

The most basic requirement for competence in any physical technology is a broad and solid understanding of the underlying physical sciences. Mathematics is the foundation of this foundation, and basic physics is the next layer. Classical mechanics and electromagnetics are universally important, and the concerns of nanotechnology elevate the importance of thermodynamics, statistical mechanics, and molecular quantum mechanics. A flexible competence in nanotechnology also requires a sound understanding of chemistry and chemical synthesis, of biomolecular structure and function, of intermolecular forces, and of solids and surfaces.

These are important areas of science, but science is not technology. As I’ve discussed in “The Antiparallel Structures of Science and Engineering”, science and engineering are in a deep sense opposites, and must not be confused. Nanotechnology today is a science-intensive area of engineering, largely because the problem of designing a nanostructure is often overshadowed by the problem of finding, by experiment, a way to make it.

This has implications for choosing a course of study.

Engineering and progress in nanotechnology

A measure of progress in nanotechnology is growth of the range of physical systems that can be designed and debugged without extensive experimentation. As a basis for implementing nanoscale digital systems, commercial semiconductor fabrication provides a predictable design domain of this sort, and some areas of structural DNA nanotechnology have become almost as predictable as carpentry.

Computational tools are in a class of their own, an area of immaterial technology that applies to every area of material technology. It’s important to understand the capabilities and limitations of these tools, and extending them makes a strategic contribution to progress. Computational tools tools are often the key to transforming reproducible processes and stable structures into reliable operations and building blocks for engineering. Today, better design tools are the key to unlocking the enormous potential of foldamers and self assembly as a basis for implementing complex nanosystems.

Competence in engineering — and understanding how science can support it — requires study of design principles and experience in solving design problems. As with physics, some lessons apply across many domains. Because nanotechnology relies on innovations in macro- and micro-scale equipment, engineering education has immediate and strong relevance. Looking forward, the growth of nanosystems engineering will open increasing opportunities for researchers with backgrounds that provide both the scientific knowledge necessary to understand new nanotechnologies and the engineering problem-solving abilities necessary to exploit them.

Students aiming to pioneer in directions that can open new worlds of nanotechnology should learn enough of both science and engineering to solve crucial problems at the interface between them. The most important of these is the problem of recognizing and developing the means for systematic engineering in new domains, extracting solid toolsets from the flood of novelty-oriented nanoscience.

In considering all of the above, keep in mind that the general direction of nanotechnology leads toward greater precision at the level of nanoscale components, making products of increasing complexity and size, implemented in an increasing range of materials. Molecular-level atomic precision has widespread applications in nanotechnology today, and already provides components with the ultimate precision at the smallest possible length scale. I expect that the road forward will increasingly focus on extending these atomically precise technologies toward greater scale, complexity, and materials quality. I recommend courses of study that prepare for this.

Choosing topics and ways to study them

In both science and engineering, a good methodology for selecting an ideal course of study would be to survey a course catalog and note which classes appear in lists of prerequisites for advanced classes in relevant areas of science and engineering. This indicates areas where it is important to study and master the content.

Courses toward the periphery of this network of prerequisites are good candidates for a different mode of study, a mode aimed at understanding the problems an area addresses, the methods used to solve them, and how those problems and methods fit in with the rest of science and technology. I discuss this mode of study in “How to Learn About Everything”. It builds knowledge of a kind that can help a student choose topics that call for deeper, focused learning, and it can later help greatly in practical work — scientists and engineers with broader knowledge will see more opportunities and encounter fewer unanticipated problems. These advantages mean fewer days (months, years) lost and greater strides forward.

Choosing institutions

Beyond topics of study, I’m also asked to recommend universities and programs. It’s difficult to give a specific answer, because a good choice depends on all of the above, and because for each of many areas of science and technology, there are many possible institutions, programs, and research groups. I can only advise that students facing this decision first consider their objectives, and then to look for institutions and people able to help them get there. In particular, universities must either offer a degree program that fits, or provide the flexibility to make one. I found a home in MIT’s Interdisciplinary Science Program (which I can’t recommend, because it no longer exists).

In undergraduate studies, the general breadth, orientation, and quality of a school is more important than any focused undergraduate program that it is likely to have.

Early involvement in research of almost any kind has a special value: It can provide knowledge of kinds that can’t be learned from reading, from classes, or even from lab courses. Pay special attention to research that studies atomically precise structures of significant size and complexity. If that research has an engineering component — designing and making things — so much the better.

• How to Learn About Everything
• How to Understand Everything (and Why)
• The Antiparallel Structures of Science and Engineering

Johann Josef Loschmidt
Chemist, atomic scientist

Chemists understood the atomic structure of molecules in the 1800s, yet many say that Einstein established the existence of atoms in a paper on Brownian motion, “Die von der Molekularkinetischen Theorie der Wärme Gefordete Bewegung von in ruhenden Flüssigkeiten Suspendierten Teilchen”, published in 1905.

This is perverse, and has seemed strange to me ever since I began reading the history of organic chemistry. Chemists often don’t get the credit they deserve, and this provides an outstanding example.

For years, I’ve read statements like this:

[Einstein] offered an experimental test for the theory of heat and proof of the existence of atoms….
[“The Hundredth Anniversary of Einstein’s Annus Mirabilis”]

Perhaps this was so for physicists in thrall (or opposition) to the philosophical ideas of another physicist, Ernst Mach; he had odd convictions about the relationship between primate eyes and physical reality, and denied the reality of invisible atoms.

Confusion among physicists, however, gives reason for more (not less!) respect for the chemists who had gotten the facts right long before, and in more detail: that matter consists of atoms of distinct chemical elements, that the atoms of different elements have specific ratios of mass, and that molecules consist not only of groups of atoms, but of atoms linked by bonds (“Verwandtschaftseinheiten”) to form specific structures.

When say “more detail”, I mean a lot more detail than merely inferring that atoms exist. For example, organic chemists had deduced that carbon atoms form four bonds, typically (but not always) directed tetrahedrally, and that the resulting molecules can as a consequence have left- and right-handed forms.

The chemists’ understanding of bonding had many non-trivial consequences. For example, it made the atomic structure of benzene a problem, and made a six-membered ring of atoms with alternating single and double bonds a solution to that problem. Data regarding chemical derivatives of benzene indicated a further problem, leading to the inference that the six bonds are equivalent. Decades later, quantum mechanics provided the explanation.

The evidence for these detailed and interwoven facts about atoms included a range of properties of gases, the compositions of compounds, the symmetric and asymmetric shapes of crystals, the rotation of polarized light, and the specific numbers of chemically distinct forms of molecules with related structures and identical numbers of atoms.

And chemists not only understood many facts about atoms, they understood how to make new molecular structures, pioneering the subtle methods of organic synthesis that are today an integral part of the leading edge of atomically precise nanotechnology.

All this atom-based knowledge and capability was in place, as I said, before 1900, courtesy of chemical research by scientists including Dalton, van ’t Hoff, Kekulé, and Pasteur.

But was it really knowledge?

By “knowledge”, I don’t mean to imply that universal consensus had been achieved at the time, or that knowledge can ever be philosphically and absolutely certain, but I think the term fits:

A substantial community of scientists had a body of theory that explained a wide range of phenomena, including the many facets of the kinetic theory of gases and a host of chemical transformations, and more. That community of scientists grew, and progressively elaborated this body of atom-based theory and technology to up to the present day, and it was confirmed, explained, and extended by physics along the way.

Should we deny that this constituted knowledge, brush it all aside, and credit 20th century physics with establishing that atoms even exist? As I said: perverse.

But what about quantitative knowledge?

There is a more modest claim for Einstein’s 1905 paper:

…the bridge between the microscopic and macroscopic world was built
by A. Einstein: his fundamental result expresses a macroscopic quantity — the coefficient of diffusion — in terms of microscopic data (elementary jumps of atoms or molecules).
[“One and a Half Centuries of Diffusion: Fick, Einstein, Before and Beyond”]

This claim for the primacy of physics also seem dubious. A German chemist, Johann Josef Loschmidt, had already used macroscopic data to deduce the size of molecules in a gas. He built this quantitative bridge in a paper, “Zur Grösse der Luftmoleküle”, published in 1865.

• A Map of Science
• How to Learn About Everything

Diverse components

This post is prompted by a set of interrelated advances in chemistry that hold great promise for advancing the art of atomically precise fabrication. In this post, I’ll describe an emerging class of modular synthesis methods for making a diverse set of small, complex molecular building blocks.

The road to complex self-assembled nanosystems starts with stable molecular building blocks, and the more choices, the better. Self-assembly and the folding of foldamers are similar processes: They work when parts fit together well, and in just one way. Having building blocks to choose from at the design stage will typically make possible a better fit, resulting in a denser, more stable structure.

Building blocks for building blocks for building blocks

I often think in terms of four levels of molecular assembly:

• Specialized covalent chemistry to synthesize monomers
  (~1 nm)
• Modular covalent chemistry to link monomers to make oligomers
  (~10 nm length)
• Intramolecular self-assembly (folding) to make 3D objects
  (< 10 nm diameter)
• Intermolecular self-assembly to make functional systems
  (~10–1000 nm)

Recent developments are blurring the first level into the second, however, because new modular chemistries can make complex structures that can serve a monomers at the next level of assembly. Perhaps the most outstanding example comes from Marty Burke’s lab, which has pioneered a new, combinatorial methodology for piecing together small molecules of enormous diversity. From the lab website:

To most effectively harness the potential impact of complex small molecules on both science and medicine, it is critical to maximize the simplicity, efficiency, and flexibility with which these types of compounds can be synthesized in the laboratory.

…the process of peptide synthesis is routinely automated. As a result, this highly enabling methodology is accessible to a broad range of scientists. In sharp contrast, the laboratory synthesis of small molecules remains a relatively complex and non-systematized process. We are currently developing a simple and highly modular strategy for making small molecules which is analogous to peptide synthesis…

Our long term goal is to create a general and automated process for the simple and flexible construction of a broad range of complex small molecules, thereby making this powerful discovery engine widely accessible, even to the non-chemist.

In outline, the Burke group’s method exploits iterative Suzuki-Miyaura coupling, a mild and increasingly general technique in which (in Burke’s approach) carbon-carbon bond formation plays the role of amide bond formation in making peptides. In peptide synthesis, suitably-protected amino acids are iteratively coupled, deprotecting the terminal amine at each step. In Burke’s method, suitably-protected boronic acids play the analogous role.

The key advance is the N-methyliminodiacetic acid (MIDA) protecting group, a trivalent ligand that rehybridizes the boron center from sp² to sp³, thereby filling and blocking access to the open p orbital that makes trivalent boron compounds so wonderfully, gently reactive. The resulting complex is stable to a wide range of aggressive conditions, including powerful oxidants and strong acids. It can be removed, however, by an aqueous base (e.g., sodium bicarbonate in water).

For more information, good places to start are the Burke lab’s research overview page, and the MIDA boronate technology spotlight page at Sigma-Aldrich, which also provides off-the-shelf MIDA-protected building blocks. Sigma-Aldrich offers a larger universe of boronic acids and boronic esters, as does CombiPhos Catalysts. It’s worth looking through one of these documents to get a gut sense of what’s now available. Impressive diversity, compared to the 20 standard amino acid side chains.

(For a general perspective on this direction of development, see “Controlled Iterative Cross-Coupling: On the Way to the Automation of Organic Synthesis”, Angew. Chem. Int. Ed. 2009.)

More than a protecting group

The MIDA boronate ester is an example of a broader class of structures that are important in their own right. The demands of organic synthesis have brought forth a vast range of commercially available boronate esters (see links above), and this investment gives a free ride to scientists aiming to exploit them as building blocks. As linkers for self-assembled structures, boronate esters are both extraordinary and underexploited.

Relying a little less on hydrogen bonds, and a little more on bonds that can hold a self-assembled solid together at 600°C — dull red heat — could increase the robustness of self-assembled products. A fast, reversible, aqueous, biocompatible boron chemistry opens a door.

More later.

See also:

• Modular Molecular Composite Nanosystems
• A High-Performance Polymer for Nanosytems Engineering
• CAD for Nanoengineering: DNA, proteins, and search-intensive design