From Watson-Crick
discovered DNA structure; there are lot researches in several fields of science
about this topic, in special biology. Computer science is not an exception,
Professor Adleman with his research and experimentation about new computation
with DNA, opened new research way with organic DNA strands (which is called DNA
Computing). In this article, we would like to give another point view, with
artificial materials, by this reason, the document relates to an electronic
system for emulating the DNA strand of a chromosome, which is characterised in
that it includes means for the binary coding of the four types of nucleotides
(A, G, C, T) that form the strands, such that the nucleotides that form
complementary links are assigned complementary codes. Furthermore, with one
minimal electronic module to emulate pair of nucleotides, it is possible to
create complex electronic structures to solve NP and NP-Complete problems in
polynomial times.
In 1953, Watson and Crick described structure
of DNA (Watson & Crick, 1953) , this fact is
a revolution in the science, and consequently, several science areas use DNA
structure for their studies. In special, Computer Science and Mathematics have
used this simple structure of DNA to create a complex paradigms or
methodologies to calculate unsolvable problem (Hamiltonian path problem, SAT,
etc.). The new branch of science is called DNA Computing, which is a form of
computing, using DNA strands and biochemistry methods. DNA computing is inside
of Natural Computing (G.Rozenberg, T.Back, & J.Kok, 2012) , is a fast developing interdisciplinary area. Big hit in this area is
in 1994, when Professor Adleman at University of Southern of California
demonstrated using organic DNA can solve seven-point Hamiltonian problem (Adleman, 1994) in polynomial
time.
The Adleman experiments demonstrated to have more advantages of actual machines, based in Von Neumann architecture(Von Neumann, 1945) and Harvard Architecture (Furber, 1989) . Consequently of initial Adleman
experiment, several searchers have developed machines, using Turing machine
models (Turing, 1936) or similar
machines with same power, but using DNA (Boneh, Dunworth, Lipton, & Sgall, 1996) , (Kari, Gloor, & Yu, 2000) .
In 1997, Mitsunori Ogihara and Animesh Ray described an implementation about Boolean Circuits using organic DNA (Ogihara & Ray, 1999) . Later in
2002 at Israel, Professor Ehud Shapiro Yaakov Benenson, Binyamin Gil, Uri
Ben-Dor, and Rivka Adar had constructed a DNA device coupled with an input and
output module, which would theoretically be capable of diagnosing cancerous
activity within a cell, and releasing an anti-cancer drug upon diagnosis. (Benenson, Gil, Ben-Dor, Adar, & Shapiro, 2004) .
Note, all methodologies are based in organic DNA and chemical procedures, thus high knowledge in mathematics. Main idea of DNA Computing to be strong alternative of silicon computing (traditional computers), but DNA computing has several walls to cross, material used dies over time, because it’s organic and perishable and it doesn’t work at industrial environments, by this reason, it is very difficult to move outside of laboratories. Almost, there are several organic devices, which are working as a silicon computer, but only in scientific environments.
This article describes an electronic system emulate DNA structure without chemical reactions, using artificial components as silicon, creating with it an inorganic DNA with electronic circuits, by this reason, the electronic system is called InChroSil (Inorganic CHROmosome based in SILicon). On the other hand, the system can be reused lot times, because it is composed by electronic circuits, there are not ethical or moral implications with cloning DNA (note, some countries are prohibited to manipulate human DNA). Also, this computation is not a pure DNA Computing; it is a mixture between both worlds (silicon and DNA), by this reason, it takes the best parts of one and another.
The Adleman experiments demonstrated to have more advantages of actual machines, based in Von Neumann architecture
In 1997, Mitsunori Ogihara and Animesh Ray described an implementation about Boolean Circuits using organic DNA
In general, DNA
computing is similar to parallel computing, because it’s possible to solve any
logical-mathematical problem in linear time. This is because, DNA structure
consists in two chains of nucleotides (main and its complementary), and in
nature both chain are linked in its nucleotides by hydrogen links. Sometimes by
artificial or natural way, one DNA chain is not linked with complementary (In
future, this chain could be called incomplete chain), first action of this incomplete
chain is to look for its complementary chain, because its natural state of DNA
strand. If in specific moment, there are lot incomplete chains, first action of
theses chains is assembling with their complementary at the same time, due
massive parallelism inherent in DNA reactions, by this reason, if one
mathematical problem is codified with incomplete chains (inputs, variables and
equations), when all these chains are introduced in same place react creating a
full strand, which is final result of mathematical problem. Consequently,
complex problems as NP and NP-complete could be solved in linear times, using
this procedure.
Note, all methodologies are based in organic DNA and chemical procedures, thus high knowledge in mathematics. Main idea of DNA Computing to be strong alternative of silicon computing (traditional computers), but DNA computing has several walls to cross, material used dies over time, because it’s organic and perishable and it doesn’t work at industrial environments, by this reason, it is very difficult to move outside of laboratories. Almost, there are several organic devices, which are working as a silicon computer, but only in scientific environments.
This article describes an electronic system emulate DNA structure without chemical reactions, using artificial components as silicon, creating with it an inorganic DNA with electronic circuits, by this reason, the electronic system is called InChroSil (Inorganic CHROmosome based in SILicon). On the other hand, the system can be reused lot times, because it is composed by electronic circuits, there are not ethical or moral implications with cloning DNA (note, some countries are prohibited to manipulate human DNA). Also, this computation is not a pure DNA Computing; it is a mixture between both worlds (silicon and DNA), by this reason, it takes the best parts of one and another.
Nucleotide code and DNA strand structure.
To understand
the electronic system, it is necessary to make a genetic introduction of
chromosomes, which are formed by DNA, RNA and proteins. In turn, DNA is
composed of two longitudinal fibres joined by centromere. These fibres are
called chromatids and represent two identical chains of the duplicated DNA.
Therefore, DNA
is composed of chains (set of nucleotides), which are differentiated in four
types which are listed below:
- Adenine is represented by the letter A.
- Guanine is represented by the letter G.
- Cytosine is represented by the letter C.
- Thymine is represented by the letter T.
Consequently,
DNA is composed of two linked chains and each chain contains innumerable
nucleotides. There are no complementary nucleotides on the same chain, i.e.
they can join without any restriction. However, on linking the two chains,
there are restrictions of complementarity, so that an Adenine (A) of a single
chain can only join with Thymines (T) of the complementary chain, in the same
way as Guanines (G) can only link with Cytosines (C). All above descriptions in
this section are obvious and incomplete for any Biotechnical, geneticist or
similar technical professional, but it’s necessary for other readers to take a
general idea.
On the other
hand, emulating to nature, the electronic system is characterised in that it
comprises means of binary encoding of the four different types of nucleotides
which compose the strands, so that the nucleotides which form complementary
linkages are assigned complementary codes by the inversion of one of them.
Binary encoding
consists in two bits corresponding to each nucleotide acquire the decimal
quantities of 0 of 3 so that it permits forming a plurality of numerical
presentations determined by the position of the two bits and by the value each
position receives. This encoding permits that any encoding system which has
correspondence with the decimal or binary can be encoded with the numeration
and encoding system of this electronic system. Next list shows codification for
each nucleotide:
- Adenine (A) is assigned the value of “00” or in decimal 0.
- Guanine (G) is assigned the value of “01” or in decimal 1.
- Cytosine (C) is assigned the value of “10” or in decimal 2.
- Thymine (T) is assigned the value of “11” or in decimal 3.
Next figure
shows a circuit represents pair of nucleotides (one nucleotide and its
complementary):
Electronic
schema of Figure consists mainly in four bi-states and logical gates. Note
one bi-stable can be used to store state information, by this reason, each
bi-stable store one bit of nucleotide codified. Also, the two bi-stables
connect with SEL0 signal represent one nucleotide and the two
bi-stables connect with SEL1 signal represents codification of both nucleotides,
so this codification permits to obtain different structures of both
nucleotides, next list shows all possible combinations:
- Both nucleotides are active (state normal in nature).
- Top nucleotide is missing, hole in top of DNA strand.
- Bottom nucleotide (complementary) is missing, hole in bottom of DNA strand.
- Both are missing, not genetic information in place, break point of DNA strand.
All combinations are necessary to do holes in
DNA strands, this skill very important to do DNA computing, because one
mathematical-logical problem could be represented by incomplete chain or chain
with holes.
Furthermore, the
system cans read/write one specific nucleotide or both, depending of R/W signal
and Chip/Select signal. Also, Figure 1 is a conceptual model, by this reason;
it could be developed in several technologies as CMOS, quantum or future
technologies.
So the above
electronic system is the unit to represent two nucleotides of DNA strand (one
nucleotide and its complementary). Connecting these units in serial, it is
possible to obtain full DNA strands, because there are not restrictions to join
between nucleotides in same level, by this reason, the length of DNA strand
depends only of number of units connected, creating with this way, a
three-dimensional DNA database with different access it (by columns, rows and
one simple nucleotide).
References
- Adleman, L. M. (1994). Molecular computation of solutions to combinatorial problems. Science , 1021–1024.
- Benenson, Y., Gil, B., Ben-Dor, U., Adar, R., & Shapiro, E. (2004). An autonomous molecular computer for logical control of gene expression. Nature , 423-429.
- Boneh, D., Dunworth, C., Lipton, R. J., & Sgall, J. I. (1996). On the computational power of DNA. Discrete Applied Mathematics , 79–94.
- F, G., M, F., & C, B. (1996). Making DNA add. Science , 220–223.
- Furber, S. B. (1989). VLSI Risc Architecture and Organization. CRC Press.
- G.Rozenberg, T.Back, & J.Kok. (2012). Handbook of Natural Computing. Springer.
- Kari, L., Gloor, G., & Yu, S. (2000). Using DNA to solve the Bounded Post Correspondence Problem. Theoretical Computer Science , 192–203.
- Knuth, D. (1962). Positional Number Systems. In The Art of Computer Programming (pp. 194–213). Addison–Wesley.
- Ogihara, M., & Ray, A. (1999). Simulating Boolean circuits on a DNA computer. Algorithmica , 239–250.
- Turing, A. (1936). On Computable Numbers, with an Application to the Entscheidungsproblem., (pp. 230–65).
- Von Neumann, J. (1945). First Draft of a Report on the EDVAC.
- Watson, J., & Crick, F. (1953). Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid. Nature , 737–738.
- Wu, G., & Seeman, N. C. (2006). Multiplying with DNA. Natural Computing , 427–441.
Your picture shows shows DNA with the wrong chirality. Your picture shows a "left handed" helix, but DNA (in B form) is right handed.
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