Towards proteinoid computers. Hypothesis paper.

Proteinoids - thermal proteins - are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. Proteinoids swell in aqueous solution into hollow microspheres. The proteinoid microspheres produce endogenous burst of electrical potential spikes and change patterns of their electrical activity in response to illumination. The microspheres can interconnect by pores and tubes and form networks with a programmable growth. We speculate on how ensembles of the proteinoid microspheres can be developed into unconventional computing devices.

A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model.

A DNA (DeoxyriboNucleic Acid) algorithm is proposed to solve the job shop scheduling problem. An encoding scheme for the problem is developed and DNA computing operations are proposed for the algorithm. After an initial solution is constructed, all possible solutions are generated. DNA computing operations are then used to find an optimal schedule. The DNA algorithm is proved to have an O(n2) complexity and the length of the final strand of the optimal schedule is within appropriate range. Experiment with 58 benchmark instances show that the proposed DNA algorithm outperforms other comparative heuristics.

A mixed culture of bacterial cells enables an economic DNA storage on a large scale.

DNA emerged as a novel potential material for mass data storage, offering the possibility to cheaply solve a great data storage problem. Large oligonucleotide pools demonstrated high potential of large-scale data storage in test tube, meanwhile, living cell with high fidelity in information replication. Here we show a mixed culture of bacterial cells carrying a large oligo pool that was assembled in a high-copy-number plasmid was presented as a stable material for large-scale data storage. The underlying principle was explored by deep bioinformatic analysis. Although homology assembly showed sequence context dependent bias, the large oligonucleotide pools in the mixed culture were constant over multiple successive passages. Finally, over ten thousand distinct oligos encompassing 2304 Kbps encoding 445 KB digital data, were stored in cells, the largest storage in living cells reported so far and present a previously unreported approach for bridging the gap between in vitro and in vivo systems.

Trends to store digital data in DNA: an overview.

There has been an ascending growth in the capacity of information being generated. The increased production of data in turn has put forward other challenges as well thus, and there is the need to store this information and not only to store it but also to retain it for a prolonged time period. The reliance on DNA as a dense storage medium with high storage capacity and its ability to withstand extreme environmental conditions has increased over the past few years. There have been developments in reading and writing different forms of data on DNA, codes for encrypting data and using DNA as a way of secret writing leading towards new styles like stenography and cryptography. The article outlines different methods adopted for storing digital data on DNA with pros and cons of each method that has been applied plus the advantages and limitations of using DNA as a storage medium.

DNA-Based Dynamic Reaction Networks.

Deriving from logical and mechanical interactions between DNA strands and complexes, DNA-based artificial reaction networks (RNs) are attractive for their high programmability, as well as cascading and fan-out ability, which are similar to the basic principles of electronic logic gates. Arising from the dream of creating novel computing mechanisms, researchers have placed high hopes on the development of DNA-based dynamic RNs and have strived to establish the basic theories and operative strategies of these networks. This review starts by looking back on the evolution of DNA dynamic RNs; in particular' the most significant applications in biochemistry occurring in recent years. Finally, we discuss the perspectives of DNA dynamic RNs and give a possible direction for the development of DNA circuits.

Molecular logic gates: the past, present and future.

The field of molecular logic gates originated 25 years ago, when A. P. de Silva published a seminal article in Nature. Stimulated by this ground breaking research, scientists were inspired to join the race to simulate the workings of the fundamental components of integrated circuits using molecules. The rules of this game of mimicry were flexible, and have evolved and morphed over the years. This tutorial review takes a look back on and provides an overview of the birth and growth of the field of molecular logics. Spinning-off from chemosensor research, molecular logic gates quickly proved themselves to be more than intellectual exercises and are now poised for many potential practical applications. The ultimate goal of this vein of research became clearer only recently - to "boldly go where no silicon-based logic gate has gone before" and seek out a new deeper understanding of life inside tissues and cells.

Poly-glutamic dendrimer-based conjugates for cancer vaccination - a computational design for targeted delivery of antigens.

Computational techniques are useful to predict interaction models and molecular properties for the design of drug delivery systems, such as dendrimers. This work evaluated the impact of surface modifications of mannosamine-conjugated multifunctional poly(glutamic acid) (PG)-dendrimers as nanocarriers of the tumour associated antigens (TAA) MART-1, gp100:44 and gp100:209. Molecular dynamics simulations and docking studies were performed. Nitrobenzoxadiazole (NBD)-PG-G4-dendrimer displayed 64 carboxylic groups, however, the Frontier Molecular Orbital Theory study evidenced that only 32 of those were available to form covalent bonds. When the number of mannosamines conjugated to dendrimer was increased from 16 to 32, the dendrimer interacted with the receptor with higher affinity. However, 16 mannosamines-NBD-PG-G4-dendrimer was chosen to conjugate TAA for added functionality as no carboxylic end groups were available for further conjugation in the 32 mannosamines-dendrimer. Docking results showed that the majority of TAA-conjugated NBD-PG-G4-dendrimer demonstrated a favourable interaction with mannosamine binding site on mannose receptor, thus constituting a promising tool for TAA targeted delivery. Our in silico approach effectively narrows down the selection of the best candidates for the synthesis of functionalised PG-dendrimers with desired functionalities. These results will significantly reduce the time and efforts required to experimentally synthesise modified dendrimers for optimal antigen delivery.

A general resolution of intractable problems in polynomial time through DNA Computing.

Based on a set of known biological operations, a general resolution of intractable problems in polynomial time through DNA Computing is presented. This scheme has been applied to solve two NP-Hard problems (Minimization of Open Stacks Problem and Matrix Bandwidth Minimization Problem) and three co-NP-Complete problems (associated with Hamiltonian Path, Traveling Salesman and Hamiltonian Circuit), which have not been solved with this model. Conclusions and open questions concerning the computational capacity of this model are presented, and research topics are suggested.

DNA-based cryptographic methods for data hiding in DNA media.

Information security can be achieved using cryptography, steganography or a combination of them, where data is firstly encrypted using any of the available cryptography techniques and then hid into any hiding medium. Recently, the famous genomic DNA has been introduced as a hiding medium, known as DNA steganography, due to its notable ability to hide huge data sets with a high level of randomness and hence security. Despite the numerous cryptography techniques, to our knowledge only the vigenere cipher and the DNA-based playfair cipher have been combined with the DNA steganography, which keeps space for investigation of other techniques and coming up with new improvements. This paper presents a comprehensive analysis between the DNA-based playfair, vigenere, RSA and the AES ciphers, each combined with a DNA hiding technique. The conducted analysis reports the performance diversity of each combined technique in terms of security, speed, hiding capacity in addition to both key size and data size. Moreover, this paper proposes a modification of the current combined DNA-based playfair cipher technique, which makes it not only simple and fast but also provides a significantly higher hiding capacity and security. The conducted extensive experimental studies confirm such outstanding performance in comparison with all the discussed combined techniques.

Approaching mathematical model of the immune network based DNA Strand Displacement system.

One biggest obstacle in molecular programming is that there is still no direct method to compile any existed mathematical model into biochemical reaction in order to solve a computational problem. In this paper, the implementation of DNA Strand Displacement system based on nature-inspired computation is observed. By using the Immune Network Theory and Chemical Reaction Network, the compilation of DNA-based operation is defined and the formulation of its mathematical model is derived. Furthermore, the implementation on this system is compared with the conventional implementation by using silicon-based programming. From the obtained results, we can see a positive correlation between both. One possible application from this DNA-based model is for a decision making scheme of intelligent computer or molecular robot.

Converting differential-equation models of biological systems to membrane computing.

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-ß is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular.

RNA nanotechnology for computer design and in vivo computation.

Molecular-scale computing has been explored since 1989 owing to the foreseeable limitation of Moore's law for silicon-based computation devices. With the potential of massive parallelism, low energy consumption and capability of working in vivo, molecular-scale computing promises a new computational paradigm. Inspired by the concepts from the electronic computer, DNA computing has realized basic Boolean functions and has progressed into multi-layered circuits. Recently, RNA nanotechnology has emerged as an alternative approach. Owing to the newly discovered thermodynamic stability of a special RNA motif (Shu et al. 2011 Nat. Nanotechnol. 6, 658-667 (doi:10.1038/nnano.2011.105)), RNA nanoparticles are emerging as another promising medium for nanodevice and nanomedicine as well as molecular-scale computing. Like DNA, RNA sequences can be designed to form desired secondary structures in a straightforward manner, but RNA is structurally more versatile and more thermodynamically stable owing to its non-canonical base-pairing, tertiary interactions and base-stacking property. A 90-nucleotide RNA can exhibit 49° nanostructures, and its loops and tertiary architecture can serve as a mounting dovetail that eliminates the need for external linking dowels. Its enzymatic and fluorogenic activity creates diversity in computational design. Varieties of small RNA can work cooperatively, synergistically or antagonistically to carry out computational logic circuits. The riboswitch and enzymatic ribozyme activities and its special in vivo attributes offer a great potential for in vivo computation. Unique features in transcription, termination, self-assembly, self-processing and acid resistance enable in vivo production of RNA nanoparticles that harbour various regulators for intracellular manipulation. With all these advantages, RNA computation is promising, but it is still in its infancy. Many challenges still exist. Collaborations between RNA nanotechnologists and computer scientists are necessary to advance this nascent technology.

Non-linear molecular pattern classification using molecular beacons with multiple targets.

In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns.

Single-molecule junctions beyond electronic transport.

The idea of using individual molecules as active electronic components provided the impetus to develop a variety of experimental platforms to probe their electronic transport properties. Among these, single-molecule junctions in a metal-molecule-metal motif have contributed significantly to our fundamental understanding of the principles required to realize molecular-scale electronic components from resistive wires to reversible switches. The success of these techniques and the growing interest of other disciplines in single-molecule-level characterization are prompting new approaches to investigate metal-molecule-metal junctions with multiple probes. Going beyond electronic transport characterization, these new studies are highlighting both the fundamental and applied aspects of mechanical, optical and thermoelectric properties at the atomic and molecular scales. Furthermore, experimental demonstrations of quantum interference and manipulation of electronic and nuclear spins in single-molecule circuits are heralding new device concepts with no classical analogues. In this Review, we present the emerging methods being used to interrogate multiple properties in single molecule-based devices, detail how these measurements have advanced our understanding of the structure-function relationships in molecular junctions, and discuss the potential for future research and applications.

Recent advances in nuclear magnetic resonance quantum information processing.

Quantum information processors have the potential to drastically change the way we communicate and process information. Nuclear magnetic resonance (NMR) has been one of the first experimental implementations of quantum information processing (QIP) and continues to be an excellent testbed to develop new QIP techniques. We review the recent progress made in NMR QIP, focusing on decoupling, pulse engineering and indirect nuclear control. These advances have enhanced the capabilities of NMR QIP, and have useful applications in both traditional NMR and other QIP architectures.

Implementing quantum logic gates with gradient ascent pulse engineering: principles and practicalities.

We briefly describe the use of gradient ascent pulse engineering (GRAPE) pulses to implement quantum logic gates in nuclear magnetic resonance quantum computers, and discuss a range of simple extensions to the core technique. We then consider a range of difficulties that can arise in practical implementations of GRAPE sequences, reflecting non-idealities in the experimental systems used.

Control aspects of quantum computing using pure and mixed states.

Steering quantum dynamics such that the target states solve classically hard problems is paramount to quantum simulation and computation. And beyond, quantum control is also essential to pave the way to quantum technologies. Here, important control techniques are reviewed and presented in a unified frame covering quantum computational gate synthesis and spectroscopic state transfer alike. We emphasize that it does not matter whether the quantum states of interest are pure or not. While pure states underly the design of quantum circuits, ensemble mixtures of quantum states can be exploited in a more recent class of algorithms: it is illustrated by characterizing the Jones polynomial in order to distinguish between different (classes of) knots. Further applications include Josephson elements, cavity grids, ion traps and nitrogen vacancy centres in scenarios of closed as well as open quantum systems.