NOR Logic Gates with Modular Design - ACS Publications

Nov 10, 2009 - The logic gates NAND/NOR were mimicked by enzyme ... The subunits performing AND/OR Boolean logic operations were designed using ...
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J. Phys. Chem. B 2009, 113, 16065–16070

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Enzyme-Based NAND and NOR Logic Gates with Modular Design Jian Zhou, Mary A. Arugula, Jan Hala´mek, Marcos Pita, and Evgeny Katz* Department of Chemistry and Biomolecular Science, and NanoBio Laboratory (NABLAB), Clarkson UniVersity, Potsdam New York 13699-5810 ReceiVed: August 15, 2009; ReVised Manuscript ReceiVed: October 6, 2009

The logic gates NAND/NOR were mimicked by enzyme biocatalyzed reactions activated by sucrose, maltose and phosphate. The subunits performing AND/OR Boolean logic operations were designed using maltose phosphorylase and cooperative work of invertase/amyloglucosidase, respectively. Glucose produced as the output signal from the AND/OR subunits was applied as the input signal for the INVERTER gate composed of alcohol dehydrogenase, glucose oxidase, microperoxidase-11, ethanol and NAD+, which generated the final output in the form of NADH inverting the logic signal from 0 to 1 or from 1 to 0. The final output signal was amplified by a self-promoting biocatalytic system. In order to fulfill the Boolean properties of associativity and commutativity in logic networks, the final NADH output signal was converted to the initial signals of maltose and phosphate, thus allowing assembling of the same standard units in concatenated sequences. The designed modular approach, signal amplification and conversion processes open the way toward complex logic networks composed of standard elements resembling electronic integrated circuitries. Introduction Rapid development of molecular1 and biomolecular2 computing systems, mimicking electronic counterparts,3 resulted in the development of novel chemical processes performing Boolean logic operations. On the basis of molecular switchable systems, various Boolean logic operations such as AND,4 OR,5 XOR,6 NOR,7 NAND,8 INHIB,9 XNOR,10 etc., were realized. In addition to sophisticated synthetic molecular1 and supramolecular switchable systems,11 different biomolecular tools, including proteins/enzymes,12 DNA,13 RNA,14 and whole cells,15 were used to assemble biochemical information processing systems. The major challenge in further development of chemical information processing systems is scaling up their complexity assembling individual logic gates in logic networks.16 Impressive results were recently achieved in this direction.1 Combination of chemical logic gates in groups or networks resulted in simple computing devices performing basic arithmetic operations17 such as half-adder/half-subtracter18 or fulladder/full-subtracter.19 Integration of several functional units in a molecular structure resulted in multisignal responses to stimuli of various chemical or physical natures, thus allowing different logic operations or even simple arithmetic functions to be performed within a single multifunctional molecule.20 Molecular automation based on networked logic operations performed by DNA was developed,21 further scaled up to integrated molecular circuits composed of 128 deoxyribozyme-based logic gates with 32 input DNA molecules and 8 two-channel fluorescent outputs across 8 wells.22 Recently, pioneered enzyme-based logic gates23 were networked in the information processing systems composed up to 3-4 concatenated gates,24 while their theoretical analysis predicted that their networks up to 10 gates can operate with the acceptable level of noise.25 Even higher complexity logic networks can be achieved if enzyme logic gates with a sigmoidresponse function are used.26 * Corresponding author. E-mail: [email protected]. Phone: +1-315268-4421. Fax: +1-315-268-6610.

One of the most important goals in the development of molecular computing systems with an increased complexity is the reproduction of basic concepts of digital logic, such as modularity27 and Boolean properties (associativity, distributivity, commutativity, etc).28 The present paper is addressing these challenging goals for enzyme-based logic gates. We assembled logic gates NAND and NOR using a modular approach and attempted to design systems for the output-input signal conversion and amplification for future assembling logic networks, fulfilling Boolean properties of associativity and commutativity. Experimental Section Chemicals and Materials. The enzymes for the biochemical systems were obtained from Sigma-Aldrich and used without further purification: glucose oxidase (GOx) from Aspergillus niger type X-S (E.C. 1.1.3.4), glucose dehydrogenase (GDH) from Pseudomonas sp. (E.C. 1.1.1.47), amyloglucosidase (AGS) from Aspergillus niger (E.C. 3.2.1.3), invertase (Inv) from baker’s yeast, grade VII (E.C. 3.2.1.26), alcohol dehydrogenase (ADH) from Saccharomyces cereVisiae (E.C. 1.1.1.1), maltose phosphorylase (MPh) from Enterococcus sp. recombinant expressed in E. coli (E.C. 2.4.1.8), and glutathione reductase (GR) from baker’s yeast (E.C. 1.6.4.2). Other chemicals from Sigma-Aldrich included microperoxidase-11 (MP-11), β-nicotinamide adenine dinucleotide reduced sodium salt (NADH) (98%), β-D-(+)-glucose (99.5% GC), D-(+)-maltose monohydrate (99%), sucrose (ACS reagent), 4-(2-hydroxyethyl)-1piperazineethanesulfonic acid (HEPES) (99.5%), tetraethylthiuram disulfide (disulfiram) (>97%), glutathione oxidized disodium salt (GSSG) (>99%), potassium antimonyl-tartrate (ACS reagent >99%), and L-ascorbic acid. β-Nicotinamide adenine dinucleotide disodium salt (NAD+) (97%) and Splittgerber’s reagent were purchased from Fluka. All of the chemicals were used as supplied. Ultrapure water (18.2 MΩ cm) from NANOpure Diamond (Barnstead) source was used in all of the experiments. Composition of the NAND and NOR Logic Gates. Two enzymatic logic gates AND/OR were designed for generating

10.1021/jp9079052 CCC: $40.75  2009 American Chemical Society Published on Web 11/10/2009

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glucose, and then, each of them was connected to the Inverter (INV) gate to assemble the NAND/NOR gates. The “machinery” for the AND gate included maltose phosphorylase (MPh, 2 units mL-1) in 50 mM, pH 7.2, HEPES buffer. The input signals were maltose (input A) and phosphate (input B), of which concentrations of 15 and 10 mM were defined as input value 1, respectively. The absence of the respective chemicals was defined as input 0 for the AND gate. The OR gate “machinery” included invertase (Inv, 20 units mL-1) and amyloglucosidase (AGS, 20 units mL-1) in 50 mM, pH 7.2, phosphate buffer. Sucrose (input A, 20 mM) and maltose (input B, 15 mM) were applied as the input signals 1 for the OR gate. The absence of the respective chemicals was defined as the input 0 for the OR gate. The Inverter (INV) gate was composed of alcohol dehydrogenase (ADH, 5 units mL-1), glucose oxidase (GOx, 20 units mL-1), NAD+ (0.2 mM), and microperoxidase11 (MP-11, 0.1 mM) as the “machinery”. Ethanol (10 mM) was always applied as a part of the INV “machinery” to produce NADH defined as the digital output 1. The input signals for the INV gate were produced in situ by the AND/OR gates to yield the NAND/NOR gates, respectively. Composition of the Signal Amplification System. The amplification system aimed at the increase of the NADH concentration being the final output signal from the NAND/ NOR gates. The NADH amplifying enzyme alcohol dehydrogenase (ADH, 0.6 units mL-1) was incubated overnight at 23 ( 2 °C in the presence of disulfiram (0.8 mM) to inhibit the enzyme activity. The excess of the inhibitor was removed from the solution using ultrafiltration tubes (NANOSEP 30 kDaltons, OMEGA). NAD+ (1 mM) and ethanol (1.7 M) were added to the solution of the inhibited enzyme. The enzyme-bound inhibitor was removed, and the enzyme was reactivated in situ by the addition of glutathione reductase (GR, 2 units mL-1), oxidized glutathione (GSSG, 3 µM), and NADH (50 µM). The reactivated enzyme started the biocatalytic production of NADH upon the reduction of NAD+, using ethanol as the reducer, thus amplifying the NADH concentration. Composition of the Signal Converting Systems. The converting systems aimed at the conversion of NADH being the final output signal generated by the NAND/NOR gates to the original inputs (maltose, phosphate) consumed by the next NAND gate in a chain network. The conversions were performed in two steps: the first conversion step resulted in the production of glucose activated by the NADH signal, while the second step yielded maltose and phosphate upon activation with the glucose input. The first converter (NADH signal to glucose signal) was composed of glucose dehydrogenase (GDH, 10 units mL-1) and gluconic acid (10 mM) in 50 mM, pH 7.2, phosphate buffer. It was activated by the NADH input (0.4 mM) to yield glucose (monitored spectrophotometrically by the decrease in the NADH absorption at λmax ) 340 nm). The next converter (glucose signal to maltose and phosphate signals) was composed of maltose phosphorylase (MPh, 40 units mL-1) and glucose1-phosphate (50 mM) in 50 mM, pH 7.2, phosphate buffer. The converter was activated by the addition of glucose produced in the previous converter to yield maltose (analyzed by HPLC) and phosphate (analyzed spectrophotometrically through free inorganic phosphate’s reaction with Splittgerber’s reagent;29 see details in the Supporting Information). All reactions were performed at ambient temperature, 23 ( 2 °C. Instruments and Methods. All optical measurements were performed using a UV-2401PC/2501PC UV-vis spectrophotometer (Shimadzu, Tokyo, Japan). The HPLC measurements were conducted on an HP Hewlett-Packard Series 1050 system

Zhou et al. SCHEME 1: Modular Design of the Enzyme-Based NAND and NOR Gates

equipped with an HPLC column Shodex SUGAR SP0810 and a RI (refraction index) detector Varian Star 9040. Results and Discussion At present, all kinds of chemical logic gates, organic1,4-10 or bioorganic,2,23,24 mimicking various Boolean operations are based on completely different chemical compositions and reactions. This makes the chemical/biochemical computing systems very complicated and different from their electronic counterparts,30 where a standard modular approach is always used. It is known that in electronic systems NAND and NOR logic gates are universal and all other Boolean functions can be derived from their compositions.3 Standard NAND/NOR gates are used in electronic integrated circuitries to perform all needed digital functions.30 It would be an advantage for chemical computing systems to use this standard modular approach. Thus, we developed the NAND and NOR logic gates with modular exchangeable subunits composed of enzymes performing biocatalytic reactions interconnected in cascades mimicking the logic operations. It should be noted that all previously designed chemical NAND/NOR gates used unique designs without the modularity concept.7,8 We need to note that at the present stage the developed NAND/NOR gates do not pretend to mimic all possible Boolean operations because of the complexity of the required networks. Still, one should keep in mind that their potential use as universal gates might be possible in the future. In our design, we developed AND/OR gate subunits producing glucose as the output signals connected to an Inverter (INV) gate subunit accepting glucose as the input and converting it to NADH being the final output, Scheme 1. The AND/OR subunits were interchangeable and connectable to the INV unit. The AND gate subunit was composed of maltose phosphorylase (MPh, 2 units mL-1), biocatalyzing reaction of maltose and phosphate (defined as the input signals A and B, respectively) to yield glucose and glucose-1-phosphate as a byproduct. The optimized concentrations of maltose (15 mM) and phosphate (10 mM) were considered as logic 1 values, while their absence was defined as logic 0 inputs. The optimization of the input concentrations aimed at the production of the output signals (glucose concentrations) comparable with those generated by another interchangeable OR logic subunit described later. The glucose production was activated only in the presence of both input signals (1,1), while it was inhibited in the absence of either of them or both (0,1; 1,0; 0,0), thus resembling the Boolean

Enzyme-Based NAND and NOR Logic Gates

Figure 1. Absorbance spectra corresponding to the output signal of NADH generated by the enzyme-based NAND logic gate upon different combination of the input signals of maltose and phosphate: (a) 0,0; (b) 0,1; (c) 1,0; (d) 1,1. Inset: The output signal values measured at λmax ) 340 nm corresponding to the logic 1 when higher than 0.2 and 0 when lower than 0.15. The definition of the logic gate “machinery” and input signals is given in the Experimental Section.

AND logic operation. The OR gate subunit was composed of amyloglucosidase (AGS, 20 units mL-1) and invertase (Inv, 20 units mL-1), biocatalyzing conversion of maltose and sucrose (defined as the input signals A and B, respectively) to glucose. Similar to the AND gate subunit, the optimized concentrations of maltose (15 mM) and sucrose (20 mM) were considered as logic 1 values, while their absence was defined as logic 0 inputs. The glucose production was activated by any of the parallel biocatalytic reactions or by both of them in the presence of either or both input signals (0,1; 1,0; 1,1), while it was inhibited in the absence of both inputs (0,0), thus resembling the Boolean OR logic operation. The INV subunit included alcohol dehydrogenase (ADH, 5 units mL-1), to produce constantly NADH upon the reaction of the NAD+ (0.2 mM) and ethanol (10 mM), being the parts of the system “machinery”. Another biocatalytic entity, MP-11 (0.1 mM), was included to reverse the NADH production, returning it to the initial oxidized state NAD+ in the presence of H2O2 produced in situ by glucose oxidase (GOx, 20 units mL-1) in the presence of glucose coming from the connected AND/OR gate subunits. It should be noted that the catalytic activity of MP-11 was high enough to overwhelm the biocatalytic reduction process resulting in the production of NADH. The optimization of the MP-11 concentration was performed for the specific H2O2 concentrations produced in situ by the preceding biocatalytic cascade. Finally, the NADH output signal was generated only in the absence of glucose incoming from the AND/OR logic subunits, thus inverting the 1 signal of glucose to the 0 signal of NADH and resembling the NAND/ NOR logic when the INV is connected to the AND/OR subunits, respectively. Figure 1 shows the output signals of the NAND gate composed of the AND-INV subunits for different combinations of the primary input signals (maltose and phosphate): 0,0; 0,1; 1,0; and 1,1. The output signals were recorded as the absorbance spectra of NADH being the final output signal of the gate. It should be noted that similar output signals could be derived from the electrochemical detection of NADH in the presence of a multienzyme logic system.31 The large absorbance, λmax ) 340 nm, corresponding to the in situ generated NADH was observed in the absence of either input or in the absence of both primary input signals (0,1; 1,0; 0,0), Figure 1, curves a-c.

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Figure 2. Absorbance spectra corresponding to the output signal of NADH generated by the enzyme-based NOR logic gate upon different combination of the input signals of maltose and sucrose: (a) 0,0; (b) 0,1; (c) 1,0; (d) 1,1. Inset: The output signal values measured at λmax ) 340 nm corresponding to the logic 1 when higher than 0.2 and 0 when lower than 0.15. The definition of the logic gate “machinery” and input signals is given in the Experimental Section.

The presence of both input signals (1,1) inhibited the absorbance formation characteristic of NADH, Figure 1, curve d, thus resembling the NAND features. The absorbance values below 0.15 at λmax ) 340 nm were considered as digital 0 values, while the absorbance above 0.2 was defined as digital 1 output, Figure 1, inset. Similar to the paradigm used in electronics,30 we considered the absorbance values between two thresholds as digitally undefined. Figure 2 shows the output signals of the NOR gate composed of the OR-INV subunits for different combinations of the primary input signals (maltose and sucrose): 0,0; 0,1; 1,0; and 1,1. The output signals were recorded as the absorbance spectra of NADH being the final output signal of the gate. The large absorbance, λmax ) 340 nm, corresponding to the in situ generated NADH was observed only in the absence of both primary input signals (0,0), Figure 2, curve a, while the presence of either or both input signals (0,1; 1,0; and 1,1) inhibited the absorbance formation characteristic of NADH, Figure 2, curves b-d. The absorbance values below 0.15 at λmax ) 340 nm were considered as digital 0 values, while the absorbance above 0.2 was defined as digital 1 output, Figure 2, inset. The response pattern generated by the system was characteristic of the Boolean NOR logic gate, Figure 2, inset. When concatenated logic gates operating in a complex network are aimed, the issue of the signal amplification between the gates should be addressed. Many natural biochemical pathways, particularly responsible for signal transduction, include amplification steps sometimes reaching 1000-fold increasing signals.32 The electronic counterparts in integrated schemes also include amplification steps for the processed signals.30 However, the electronic systems always operate with electrical signals, while biochemical systems use various chemicals through all biocatalytic steps. Different methods should be applied for the amplification of these chemical signals depending on their nature. In order to illustrate this approach, applied specifically to the presently developed NAND/NOR gates, we designed a biocatalytic system amplifying the NADH output signal produced by the gates. We selected alcohol dehydrogenase (ADH) as the biocatalyst producing NADH in the presence of NAD+ and ethanol.33 The tricky part of the process was activation of this biocatalytic reaction by the NADH

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SCHEME 2: The Self-Promoted Biocatalytic System for the Amplification of the NADH Signal

signal, in other words aiming the amplified production of NADH activated by the NADH signal, Scheme 2. To achieve this goal, we use disulfiram (DS) to cause a reversible inhibition of ADH and further reactivation of the enzyme upon biocatalytic removal of the inhibitor initiated by NADH. It is known that disulfiram inhibits ADH only when it is in the disulfide state, and the enzyme can be reactivated when the disulfide bond in the inhibitor is reduced.34 Glutathione reductase (GR) can be used to reduce disulfide bonds in the oxidized state of glutathione (GSSG) using NADH as the reductive agent;35 however, GR is not efficient for the direct reduction of disulfiram.36 Thus, we applied GR to reduce oxidized glutathione (GSSG) in the presence of NADH; then, the biocatalytically reduced glutathione (GSH) induced the reduction of disulfiram to yield diethyldithiocarbamate (DDC) due to the thiol-disulfide exchange.37 This resulted in the removal of the inhibitor, reactivation of ADH, and production of NADH, thus amplifying the initial NADH input, Scheme 2. The following experiment was performed to demonstrate the amplification process. First, ADH (0.6 units mL-1) was inhibited by the addition of the optimized concentration of disulfiram (0.8 mM) upon overnight incubation. The optimum disulfiram concentration implied significant inhibition of ADH, which still could be reactivated by the thiol-disulfide exchange with the reduced glutathione produced in situ by the GR reaction. A lower disulfiram concentration did not result in substantial inhibition of ADH, while a higher concentration did not allow the enzyme reactivation. The inhibited ADH was tested for the production of NADH in the presence of NAD+ (1 mM) and ethanol (1.7 M). Despite its inhibition, the enzyme ADH demonstrated some residual activity producing NADH, Figure 3, curve a. The addition of NADH input (50 µM) to the solution in the absence of the disulfide reducing system (GR and GSSG) did not affect the rate of the biocatalytic production of NADH, Figure 3, curve b. The same experiment performed in the presence of GR (2 units mL-1), GSSG (3 µM), and NADH (50 µM) resulted in the enhanced production of NADH, witnessing the inhibitor reductive removal and the ADH reactivation, Figure 3, curve c. The rate of the NADH production was increased by 2-fold, thus demonstrating the NADH signal amplification, Figure 3, inset. All chemical1 and biochemical2 networks composed of concatenated logic gates (particularly including enzyme-based networks)24 reported until now do not fulfill Boolean properties of associativity, distributivity, and commutativity.28 Indeed, each chemical step consumes chemicals and produces other chemicals

Figure 3. Absorbance changes (λmax ) 340 nm) corresponding to the NADH production in the signal amplification system: (a) with the inhibited ADH enzyme, (b) upon addition of NADH (50 µM) in the absence of the inhibitor reducing system (GR and GSSG), (c) in the presence of the activation system and NADH signal. Inset: the absorbance values after 20 min of the reaction. The definition of the amplification system and input signals is given in the Experimental Section.

SCHEME 3: The Two-Step Biocatalytic System Converting the Final Output Signal of NADH to the Initial Input Signals of Maltose and Phosphate

different from the original inputs. Individual chemical reactions can mimic Boolean logic operations and even their sequences, but they cannot be exchanged in their order because of the chemical difference between the input and output signals at each step. This difference might be used in some specific applications, for example, to realize the IMPLICATION logic operation, when the final result depends not only on the logic values but also on the order of the input signals.24b,38 However, to mimic the electronic networks, meeting the requirements of Boolean properties, chemical/biochemical logic gates should be exchangeable regardless of the chemical nature of the input/output signals. To achieve this goal, at least partially, we developed methods for converting the output signals to the initial input signals, thus potentially allowing the sequential operation of the logic gates with the same inputs at each individual logic step. To illustrate the concept, we designed biochemical systems transforming the final NADH output signal generated by the NAND/NOR gates to some of the initial input signals consumed by the gates: maltose and phosphate. A two-step conversion method of the NADH signal was designed, Scheme 3. First, the NADH signal was used to activate a biocatalytic system composed of glucose dehydrogenase (GDH, 10 units mL-1) and gluconic acid (10 mM), able to generate glucose. Using the reversibility of the reaction biocatalyzed by GDH, gluconic acid was reduced to glucose in the presence of NADH. The reaction was followed by the decrease of the NADH optical absorbance, Figure 4A. Then,

Enzyme-Based NAND and NOR Logic Gates

J. Phys. Chem. B, Vol. 113, No. 49, 2009 16069 sembling of the same gates in their various combinations and fulfilling the Boolean network properties. Conclusions and Perspectives The NAND/NOR logic gates were assembled from the standard exchangeable subunits, allowing their modular design. Two challenging issues in the chemical gates networking were addressed: amplification of the output signals and conversion of them to the initial input signals. The former is important for keeping the standard level of the signals between the concatenated chemical gates, while the latter is critical for fulfilling Boolean network properties, allowing exchange in the gates positioning in the network. The present work for the first time emphasized the need of the chemical output-to-input conversion as the immanent requirement for the Boolean properties in chemical networks. It should be noted that the enzymes used in the signal amplifying and converting systems are mostly the same as in the NAND/NOR logic gates, thus simplifying the future design of the integrated logic circuitries. The designed systems and performed experiments demonstrated the concepts and illustrated possible approaches, still keeping many problems for the future work. For any practical applications (mostly aiming at biosensing systems rather than competing with electronic computers), the enzymes should be immobilized in microfluidic devices and their modular units should be integrated with amplifying and signal-converting systems. The present work demonstrated the operation of these important networking elements separately; still, a lot of work will be needed to assemble them in real operating devices. Acknowledgment. This research was supported by the National Science Foundation (grants CCF-0726698, DMR0706209), by Office of Naval Research (award #N00014-081-1202), and by the Semiconductor Research Corporation (award 2008-RJ-1839G). M.A.A. and J.Z. acknowledge Wallace H. Coulter scholarships from Clarkson University. The technical help of Prof. Roshan Jachuck and Hariprasad Amanapu in the HPLC experiments is gratefully acknowledged. Supporting Information Available: Spectrophotometric analysis of phosphate. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes

Figure 4. Conversion of the final output signal of NADH produced by the NAND gate to the intermediate signal of glucose and to the initial signals of maltose and phosphate. (A) Absorbance spectra of NADH in the converter system: (a) before and (b) after 10 min of the reaction. (B) HPLC analysis of maltose in the converter system: (a) before and (b) after the reaction for 2 h (mAU ) milliarbitrary units). (C) Spectrophotometric analysis of phosphate using Splittgerber’s reagent: (a) before and (b) after 5 min of the reaction. The composition and operation of the converter system is detailed in the Experimental Section.

another reversible reaction biocatalyzed by maltose phosphorylase (MPh, 40 units mL-1) resulted in the conversion of glucose-1-phosphate (50 mM) and in situ generated glucose to maltose and phosphate, where maltose formation was analyzed by HPLC, Figure 4B, and the phosphate production was proved by a colorimetric test,29 Figure 4C. The present system allowed the digital conversion (in terms of YES/NO; 1/0) of the final output signal NADH to the initial signals maltose and phosphate consumed by the logic gates, thus potentially allowing as-

(1) (a) De Silva, A. P.; Uchiyama, S.; Vance, T. P.; Wannalerse, B. Coord. Chem. ReV. 2007, 251, 1623–1632. (b) De Silva, A. P.; Uchiyama, S. Nat. Nanotechnol. 2007, 2, 399–410. (c) Szacilowski, K. Chem. ReV. 2008, 108, 3481–3548. (d) Credi, A. Angew. Chem., Int. Ed. 2007, 46, 5472– 5475. (2) (a) Shao, X. G.; Jiang, H. Y.; Cai, W. S. Prog. Chem. 2002, 14, 37–46. (b) Saghatelian, A.; Volcker, N. H.; Guckian, K. M.; Lin, V. S. Y.; Ghadiri, M. R. J. Am. Chem. Soc. 2003, 125, 346–347. (c) Ashkenasy, G.; Ghadiri, M. R. J. Am. Chem. Soc. 2004, 126, 11140–11141. (3) Shiva, S. G. Introduction to Logic Design, 2nd ed.; Marcel Dekker: New York, 1998. (4) (a) De Silva, A. P.; Gunaratne, H. Q. N.; McCoy, C. P. Nature 1993, 364, 42–44. (b) De Silva, A. P.; Gunaratne, H. Q. N.; McCoy, C. P. J. Am. Chem. Soc. 1997, 119, 7891–7892. (5) De Silva, A. P.; Gunaratne, H. Q. N.; Maguire, G. E. M. J. Chem. Soc., Chem. Commun. 1994, 1213–1214. (6) (a) Credi, A.; Balzani, V.; Langford, S. J.; Stoddart, J. F. J. Am. Chem. Soc. 1997, 119, 2679–2681. (b) De Silva, A. P.; McClenaghan, N. D. Chem.sEur. J. 2002, 8, 4935–4945. (7) (a) De Silva, A. P.; Dixon, I. M.; Gunaratne, H. Q. N.; Gunnlaugsson, T.; Maxwell, P. R. S.; Rice, T. E. J. Am. Chem. Soc. 1999, 121, 1393– 1394. (b) Straight, S. D.; Liddell, P. A.; Terazono, Y.; Moore, T. A.; Moore, A. L.; Gust, D. AdV. Funct. Mater. 2007, 17, 777–785. (c) Turfan, B.; Akkaya, E. U. Org. Lett. 2002, 4, 2857–2859. (d) Wang, Z.; Zheng, G.; Lu, P. Org. Lett. 2005, 7, 3669–3672.

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(8) (a) Baytekin, H. T.; Akkaya, E. U. Org. Lett. 2000, 2, 1725–1727. (b) Zong, G.; Xiana, L.; Lua, G. Tetrahedron Lett. 2007, 48, 3891–3894. (9) (a) Gunnlaugsson, T.; MacDo´naill, D. A.; Parker, D. J. Am. Chem. Soc. 2001, 123, 12866–12876. (b) Gunnlaugsson, T.; MacDo´naill, D. A.; Parker, D. Chem. Commun. 2000, 93–94. (c) Gunnlaugsson, T.; MacDo´naill, D. A.; Parker, D. Chem. Commun. 2000, 93–94. (d) De Sousa, M.; De Castro, B.; Abad, S.; Miranda, M. A.; Pischel, U. Chem. Commun. 2006, 2051–2053. (e) Li, L.; Yu, M.-X.; Li, F. Y.; Yi, T.; Huang, C. H. Colloids Surf., A 2007, 304, 49–53. (f) Gunnlaugsson, T.; MacDo´nail, D. A.; Parker, D. Chem. Commun. 2000, 93–94. (10) (a) Luxami, V.; Kumar, S. New J. Chem. 2008, 32, 2074–2079. (b) Qian, J. H.; Qian, X. H.; Xu, Y. F.; Zhang, S. Y. Chem. Commun. 2008, 4141–4143. (11) (a) Credi, A.; Balzani, V.; Langford, S. J.; Stoddart, J. F. J. Am. Chem. Soc. 1997, 119, 2679–2681. (b) Flood, A. H.; Ramirez, R. J. A.; Deng, W. Q.; Muller, R. P.; Goddard, W.A.; J.; Stoddart, J. F. Aust. J. Chem. 2004, 57, 301–322. (12) (a) Sivan, S.; Lotan, N. Biotechnol. Prog. 1999, 15, 964–970. (b) Sivan, S.; Tuchman, S.; Lotan, N. Biosystems 2003, 70, 21–33. (c) Deonarine, A. S.; Clark, S. M.; Konermann, L. Future Generation Comput. Syst. 2003, 19, 87–97. (d) Ashkenazi, G.; Ripoll, D. R.; Lotan, N.; Scheraga, H. A. Biosens. Bioelectron. 1997, 12, 85–95. (e) Unger, R.; Moult, J. Proteins 2006, 63, 53–64. (13) (a) Stojanovic, M. N.; Stefanovic, D.; LaBean, T.; Yan, H. In Bioelectronics: From Theory to Applications; Willner, I., Katz, E., Eds.; Wiley-VCH: Weinheim, Germany, 2005; pp 427-455. (b) Saghatelian, A.; Volcker, N. H.; Guckian, K. M.; Lin, V. S. Y.; Ghadiri, M. R. J. Am. Chem. Soc. 2003, 125, 346–347. (c) Ashkenasy, G.; Ghadiri, M. R. J. Am. Chem. Soc. 2004, 126, 11140–11141. (14) Win, M. N.; Smolke, C. D. Science 2008, 322, 456–460. (15) Simpson, M. L.; Sayler, G. S.; Fleming, J. T.; Applegate, B. Trends Biotechnol. 2001, 19, 317–323. (16) Wagner, N.; Ashkenasy, G. Chem.sEur. J. 2009, 15, 1765–1775. (17) (a) Pischel, U. Angew. Chem., Int. Ed. 2007, 46, 4026–4040. (b) Brown, G. J. A. P.; De Silva, A. P.; Pagliari, S. Chem. Commun. 2002, 2461–2463. (18) (a) Qu, D.-H.; Wang, Q.-C.; Tian, H. Angew. Chem., Int. Ed. 2005, 44, 5296–5299. (b) Andre´asson, J.; Straight, S. D.; Kodis, G.; Park, C.-D.; Hambourger, M.; Gervaldo, M.; Albinsson, B.; Moore, T. A.; Moore, A. L.; Gust, D. J. Am. Chem. Soc. 2006, 128, 16259–16265. (c) Andre´asson, J.; Kodis, G.; Terazono, Y.; Liddell, P. A.; Bandyopadhyay, S.; Mitchell, R. H.; Moore, T. A.; Moore, A. L.; Gust, D. J. Am. Chem. Soc. 2004, 126, 15926– 15927. (d) Lopez, M. V.; Vazquez, M. E.; Gomez-Reino, C.; Pedrido, R.; Bermejo, M. R. New J. Chem. 2008, 32, 1473–1477. (19) (a) Margulies, D.; Melman, G.; Shanzer, A. J. Am. Chem. Soc. 2006, 128, 4865–4871. (b) Kuznetz, O.; Salman, H.; Shakkour, N.; Eichen, Y.; Speiser, S. Chem. Phys. Lett. 2008, 451, 63–67. (20) (a) Liu, Y.; Jiang, W.; Zhang, H.-Y.; Li, C.-J. J. Phys. Chem. B 2006, 110, 14231–14235. (b) Guo, X.; Zhang, D.; Zhang, G.; Zhu, D. J. Phys. Chem. B 2004, 108, 11942–11945.

Zhou et al. (21) Stojanovic, M. N.; Stefanovic, D. Nat. Biotechnol. 2003, 21, 1069– 1074. (22) Macdonald, J.; Li, Y.; Sutovic, M.; Lederman, H.; Pendri, K.; Lu, W. H.; Andrews, B. L.; Stefanovic, D.; Stojanovic, M. N. Nano Lett. 2006, 6, 2598–2603. (23) (a) Strack, G.; Pita, M.; Ornatska, M.; Katz, E. ChemBioChem 2008, 9, 1260–1266. (b) Baron, R.; Lioubashevski, O.; Katz, E.; Niazov, T.; Willner, I. J. Phys. Chem. A 2006, 110, 8548–8553. (c) Baron, R.; Lioubashevski, O.; Katz, E.; Niazov, T.; Willner, T. Angew. Chem., Int. Ed. 2006, 45, 1572–1576. (24) (a) Privman, M; Tam, T. K.; Pita, M.; Katz, E. J. Am. Chem. Soc. 2009, 131, 1314–1321. (b) Strack, G.; Ornatska, M.; Pita, M.; Katz, E J. Am. Chem. Soc. 2008, 130, 4234–4235. (c) Niazov, T.; Baron, R.; Katz, E.; Lioubashevski, O.; Willner, I. Proc. Natl. Acad. U.S.A. 2006, 103, 17160– 17163. (25) (a) Melnikov, D.; Strack, G.; Pita, M.; Privman, V.; Katz, E. J. Phys. Chem. B 2009, 113, 10472–10479. (b) Privman, V.; Arugula, M. A.; Hala´mek, J.; Pita, M.; Katz, E. J. Phys. Chem. B 2009, 113, 5301–5310. (c) Privman, V.; Strack, G.; Solenov, D.; Pita, M.; Katz, E. J. Phys. Chem. B 2008, 112, 11777–11784. (26) Privman, V.; Pedrosa, V.; Melnikov, D.; Pita, M.; Simonian, A.; Katz, E. Biosens. Bioelectron. 2009, 25, 695–701. (27) Frezza, B. M.; Cockroft, S. L.; Ghadiri, M. R. J. Am. Chem. Soc. 2007, 129, 14875–14879. (28) Whitesitt, J. E. Boolean Algebra and Its Applications; Dover Publications: New York, 1995. (29) Parsons, T. R.; Maita, Y.; Lalli, C. M. A Manual of Chemical and Biological Methods for Seawater Analysis; Pergamon Press: New York, 1984. (30) Bostock, G. Programmable Logic DeVices. Technology and Applications; McGraw-Hill: New York, 1988. (31) Manesh, K. M.; Hala´mek, J.; Pita, M.; Zhou, J.; Tam, T. K.; Santhosh, P.; Chuang, M.-C.; Windmiller, J. R.; Abidin, D.; Katz, E.; Wang, J. Biosens. Bioelectron. 2009, 24, 3569–3574. (32) Principles and Techniques of Biochemistry and Molecular Biology; Wilson, K., Walker, J., Eds.; Cambridge University Press: New York, 2005. (33) De Smidt, O.; Du Preez, J. C.; Albertyn, J. FEMS Yeast Res. 2008, 8, 967–978. (34) Carper, W. R.; Dorey, R. C.; Beber, J. H. Clin. Chem. 1987, 33, 1906–1908. (35) (a) Rietveld, P.; Arscott, L. D.; Berry, A.; Scrutton, N. S.; Deonarain, M. P.; Perham, R. N.; Williams, C. H. Biochemistry 1994, 33, 13888–13895. (b) Chung, Y. C.; Hurlbert, R. E. J. Bacteriol. 1975, 123, 203–211. (36) Nagendra, S. N.; Shetty, K. T.; Subhash, M. N.; Guru, S. C. Life Sci. 1991, 49, 23–28. (37) Gilbert, H. F. Methods Enzymol. 1995, 251, 8–28. (38) Margulies, D.; Felder, C. E.; Melman, G.; Shanzer, A. J. Am. Chem. Soc. 2007, 129, 347–354.

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