Synthetic molecular machines for active self-assembly : prototype algorithms, designs, and experimental study

Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of “active self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

Protein structure refinement algorithms

Protein structure prediction has remained a major challenge in structural biology for more than half a century. Accelerated and cost efficient sequencing technologies have allowed researchers to sequence new organisms and discover new protein sequences. Novel protein structure prediction technologies will allow researchers to study the structure of proteins and to determine their roles in the underlying biology processes and develop novel therapeutics.

Difficulty of the problem stems from two folds: (a) describing the energy landscape that corresponds to the protein structure, commonly referred to as force field problem; and (b) sampling of the energy landscape, trying to find the lowest energy configuration that is hypothesized to be the native state of the structure in solution. The two problems are interweaved and they have to be solved simultaneously. This thesis is composed of three major contributions. In the first chapter we describe a novel high-resolution protein structure refinement algorithm called GRID. In the second chapter we present REMCGRID, an algorithm for generation of low energy decoy sets. In the third chapter, we present a machine learning approach to ranking decoys by incorporating coarse-grain features of protein structures.

Kinetic investigations of heterogeneously catalyzed reactions on the Ru(001) and Pt(110)-(1x2) surfaces

The initial probabilities of activated, dissociative chemisorption of methane and ethane on Pt(110)-(1 x 2) have been measured. The surface temperature was varied from 450 to 900 K with the reactant gas temperature constant at 300 K. Under these conditions, we probe the kinetics of dissociation via trapping-mediated (as opposed to 'direct') mechanism. It was found that the probabilities of dissociation of both methane and ethane were strong functions of the surface temperature with an apparent activation energies of 14.4 kcal/mol for methane and 2.8 kcal/mol for ethane, which implys that the methane and ethane molecules have fully accommodated to the surface temperature. Kinetic isotope effects were observed for both reactions, indicating that the C-H bond cleavage was involved in the rate-limiting step. A mechanistic model based on the trapping-mediated mechanism is used to explain the observed kinetic behavior. The activation energies for C-H bond dissociation of the thermally accommodated methane and ethane on the surface extracted from the model are 18.4 and 10.3 kcal/mol, respectively.

The studies of the catalytic decomposition of formic acid on the Ru(001) surface with thermal desorption mass spectrometry following the adsorption of DCOOH and HCOOH on the surface at 130 and 310 K are described. Formic acid (DCOOH) chemisorbs dissociatively on the surface via both the cleavage of its O-H bond to form a formate and a hydrogen adatom, and the cleavage of its C-O bond to form a carbon monoxide, a deuterium adatom and an hydroxyl (OH). The former is the predominant reaction. The rate of desorption of carbon dioxide is a direct measure of the kinetics of decomposition of the surface formate. It is characterized by a kinetic isotope effect, an increasingly narrow FWHM, and an upward shift in peak temperature with Ɵ_T, the coverage of the dissociatively adsorbed formic acid. The FWHM and the peak temperature change from 18 K and 326 K at Ɵ_T = 0.04 to 8 K and 395 K at Ɵ_T = 0.89. The increase in the apparent activation energy of the C-D bond cleavage is largely a result of self-poisoning by the formate, the presence of which on the surface alters the electronic properties of the surface such that the activation energy of the decomposition of formate is increased. The variation of the activation energy for carbon dioxide formation with Ɵ_T accounts for the observed sharp carbon dioxide peak. The coverage of surface formate can be adjusted over a relatively wide range so that the activation energy for C-D bond cleavage in the case of DCOOH can be adjusted to be below, approximately equal to, or well above the activation energy for the recombinative desorption of the deuterium adatoms. Accordingly, the desorption of deuterium was observed to be governed completely by the desorption kinetics of the deuterium adatoms at low Ɵ_T, jointly by the kinetics of deuterium desorption and C-D bond cleavage at intermediate Ɵ_T, and solely by the kinetics of C-D bond cleavage at high Ɵ_T. The overall branching ratio of the formate to carbon dioxide and carbon monoxide is approximately unity, regardless the initial coverage Ɵ_T, even though the activation energy for the production of carbon dioxide varies with Ɵ_T. The desorption of water, which implies C-O bond cleavage of the formate, appears at approximately the same temperature as that of carbon dioxide. These observations suggest that the cleavage of the C-D bond and that of the C-O bond of two surface formates are coupled, possibly via the formation of a short-lived surface complex that is the precursor to to the decomposition.

The measurement of steady-state rate is demonstrated here to be valuable in determining kinetics associated with short-lived, molecularly adsorbed precursor to further reactions on the surface, by determining the kinetic parameters of the molecular precursor of formaldehyde to its dissociation on the Pt(110)-(1 x 2) surface.

Overlayers of nitrogen adatoms on Ru(001) have been characterized both by thermal desorption mass spectrometry and low-energy electron diffraction, as well as chemically via the postadsorption and desorption of ammonia and carbon monoxide.

The nitrogen-adatom overlayer was prepared by decomposing ammonia thermally on the surface at a pressure of 2.8 x 10^(-6) Torr and a temperature of 480 K. The saturated overlayer prepared under these conditions has associated with it a (√247/10 x √247/10)R22.7° LEED pattern, has two peaks in its thermal desorption spectrum, and has a fractional surface coverage of 0.40. Annealing the overlayer to approximately 535 K results in a rather sharp (√3 x √3)R30° LEED pattern with an associated fractional surface coverage of one-third. Annealing the overlayer further to 620 K results in the disappearance of the low-temperature thermal desorption peak and the appearance of a rather fuzzy p(2x2) LEED pattern with an associated fractional surface coverage of approximately one-fourth. In the low coverage limit, the presence of the (√3 x √3)R30° N overlayer alters the surface in such a way that the binding energy of ammonia is increased by 20% relative to the clean surface, whereas that of carbon monoxide is reduced by 15%.

A general methodology for the indirect relative determination of the absolute fractional surface coverages has been developed and was utilized to determine the saturation fractional coverage of hydrogen on Ru(001). Formaldehyde was employed as a bridge to lead us from the known reference point of the saturation fractional coverage of carbon monoxide to unknown reference point of the fractional coverage of hydrogen on Ru(001), which is then used to determine accurately the saturation fractional coverage of hydrogen. We find that ƟSAT/H = 1.02 (±0.05), i.e., the surface stoichiometry is Ru : H = 1 : 1. The relative nature of the method, which cancels systematic errors, together with the utilization of a glass envelope around the mass spectrometer, which reduces spurious contributions in the thermal desorption spectra, results in high accuracy in the determination of absolute fractional coverages.