Latest developments in experimental and computational approaches to characterize protein–lipid interactions

Understanding the functional roles of all the molecules in cells is an ultimate goal of modern biology. An important facet is to understand the functional contributions from intermolecular interactions, both within a class of molecules (e.g. protein–protein) or between classes (e.g. protein‐DNA). While the technologies for analyzing protein–protein and protein–DNA interactions are well established, the field of protein–lipid interactions is still relatively nascent. Here, we review the current status of the experimental and computational approaches for detecting and analyzing protein–lipid interactions. Experimental technologies fall into two principal categories, namely solution‐based and array‐based methods. Computational methods include large–scale data‐driven analyses and predictions/dynamic simulations based on prior knowledge of experimentally identified interactions. Advances in the experimental technologies have led to improved computational analyses and vice versa, thereby furthering our understanding of protein–lipid interactions and their importance in biological systems.     

The label free DNA sensor using a silicon nanowire array

Biosensors based on silicon nanowire (Si-NW) promise highly sensitive dynamic label free electrical detection of various biological molecules. Here we report Si-NW array electronic devices that function as sensitive and selective detectors of as synthesized 2D DNA lattices with biotins. The Si-NW array was fabricated using top-down approach consists of 250 nanowires of 20 μm in length, equally spaced with an interval of 3.2 μm. Measurements of photoresistivity of the Si-NW array device with streptavidin (SA) attached on biotinylated DNA lattices at different concentration were observed and analyzed.. The conductivity in the DNA lattices with protein SA shows significant change in the photoresistivity of Si-NW array device. This Si-NW based DNA sensor would be one of very efficient devices for direct, label free DNA detection and could provide a pathway to immunological assays, DNA forensics and toxin detection in modern biotechnology.     

Fractal construction of constrained code words for DNA storage systems

The use of complex biological molecules to solve computational problems is an emerging field at the interface between biology and computer science. There are two main categories in which biological molecules, especially DNA, are investigated as alternatives to silicon-based computer technologies. One is to use DNA as a storage medium, and the other is to use DNA for computing. Both strategies come with certain constraints. In the current study, we present a novel approach derived from chaos game representation for DNA to generate DNA code words that fulfill user-defined constraints, namely GC content, homopolymers, and undesired motifs, and thus, can be used to build codes for reliable DNA storage systems.     

Biochemistry and structural DNA nanotechnology: an evolving symbiotic relationship

Structural DNA nanotechnology is derived from naturally occurring structures and phenomena in cellular biochemistry. Motifs based on branched DNA molecules are linked together by sticky ends to produce objects, periodic arrays, and nanomechanical devices. The motifs include Holliday junction analogues, double and triple crossover molecules, knots, and parallelograms. Polyhedral catenanes, such as a cube or a truncated octahedron, have been assembled from branched junctions. Stiff motifs have been used to produce periodic arrays, containing topographic features visible in atomic force microscopy; these include deliberately striped patterns and cavities whose sizes can be tuned by design. Deliberately knotted molecules have been assembled. Aperiodic arrangements of DNA tiles can be used to produce assemblies corresponding to logical computation. Both DNA structural transitions and branch migration have been used as the basis for the operation of DNA nanomechanical devices. Structural DNA nanotechnology has been used in a number of applications in biochemistry. An RNA knot has been used to establish the existence of RNA topoisomerase activity. The sequence dependence of crossover isomerization and branch migration at symmetric sites has been established through the use of symmetric immobile junctions. DNA parallelogram arrays have been used to determine the interhelical angles for a variety of DNA branched junctions. The relationship between biochemistry and structural DNA nanotechnology continues to grow.     

Nanomaterials in biological environment: a review of computer modelling studies

Nanotechnology is set to impact a vast range of fields, including computer science, materials technology, engineering/manufacturing and medicine. As nanotechnology grows so does exposure to nanostructured materials, thus investigation of the effects of nanomaterials on biological systems is paramount. Computational techniques can allow investigation of these systems at the nanoscale, providing insight into otherwise unexaminable properties, related to both the intentional and unintentional effects of nanomaterials. Herein, we review the current literature involving computational modelling of nanoparticles and biological systems. This literature has highlighted the common modes in which nanostructured materials interact with biological molecules such as membranes, peptides/proteins and DNA. Hydrophobic interactions are the most favoured, with π-stacking of the aromatic side-chains common when binding to a carbonaceous nanoparticle or surface. van der Waals forces are found to dominate in the insertion process of DNA molecules into carbon nanotubes. Generally, nanoparticles have been observed to disrupt the tertiary structure of proteins due to the curvature and atomic arrangement of the particle surface. Many hydrophobic nanoparticles are found to be able to transverse a lipid membrane, with some nanoparticles even causing mechanical damage to the membrane, thus potentially leading to cytotoxic effects. Current computational techniques have revealed how some nanoparticles interact with biological systems. However, further research is required to determine both useful applications and possible cytotoxic effects that nanoparticles may have on DNA, protein and membrane structure and function within biosystems.     

Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined.     

Visualization of dynamic simulations of muscle thin filaments

Following a novel computational formalism, the thin filament of muscle can be modeled by a computational machine containing a large number of finite automata that have one-to-one correspondence with the constituent protein molecules.¹ Computer graphics can be used to visualize the correspondence between the states of finite automata and the configurations of protein molecules according to the structural data. The dynamic simulation of the muscle filament that corresponds to the concurrent state transitions of finite automata can be represented as a sequence of video images. The kinetic and structural knowledge of individual protein molecules is, therefore, integrated into a coherent and functional system. This type of computation and visualization can also be useful for the investigation of molecular structure, function, and interaction in various complex biological systems.     

Logic Gate Operation by DNA Translocation through Biological Nanopores

Logical operations using biological molecules, such as DNA computing or programmable diagnosis using DNA, have recently received attention. Challenges remain with respect to the development of such systems, including label-free output detection and the rapidity of operation. Here, we propose integration of biological nanopores with DNA molecules for development of a logical operating system. We configured outputs “1” and “0” as single-stranded DNA (ssDNA) that is or is not translocated through a nanopore; unlabeled DNA was detected electrically. A negative-AND (NAND) operation was successfully conducted within approximately 10 min, which is rapid compared with previous studies using unlabeled DNA. In addition, this operation was executed in a four-droplet network. DNA molecules and associated information were transferred among droplets via biological nanopores. This system would facilitate linking of molecules and electronic interfaces. Thus, it could be applied to molecular robotics, genetic engineering, and even medical diagnosis and treatment.     

DNA enables nanoscale control of the structure of matter

Structural DNA nanotechnology consists of constructing objects, lattices and devices from branched DNA molecules. Branched DNA molecules open the way for the construction of a variety of N-connected motifs. These motifs can be joined by cohesive interactions to produce larger constructs in a bottom-up approach to nanoconstruction. The first objects produced by this approach were stick polyhedra and topological targets, such as knots and Borromean rings. These were followed by periodic arrays with programmable patterns. It is possible to exploit DNA structural transitions and sequence-specific binding to produce a variety of DNA nanomechanical devices, which include a bipedal walker and a machine that emulates the translational capabilities of the ribosome. Much of the promise of this methodology involves the use of DNA to scaffold other materials, such as biological macromolecules, nanoelectronic components, and polymers. These systems are designed to lead to improvements in crystallography, computation and the production of diverse and exotic materials.     

A CDC6 protein-binding peptide selected using a bacterial two-hybrid-like system is a cell cycle inhibitor

Peptides or small molecules able to modulate protein-protein interactions hold promise as tools with which to probe and manipulate biological pathways. An important issue in this nascent field is to evaluate different methods with which to search libraries for molecules that modulate the function of specific target proteins. One strategy is to screen libraries for molecules that bind specifically to a protein known to be critical in the pathway of interest, with the expectation that the molecules isolated will recognize regions of the target protein important for its function and thereby exhibit biological activity. Here, a peptide library was screened using a two-hybrid-like system for molecules able to bind human CDC6 protein (CDC6p), required for the initiation of DNA replication in eukaryotic cells. From a collection of over a million peptides, a single species that exhibited good affinity and specificity for binding CDC6p was obtained. When expressed in human cells, the peptide inhibited cell cycle progression and exhibited other properties expected of a CDC6p inhibitor. This approach, which does not require detailed knowledge of the mechanism of action of a protein target, may be generally useful for isolating peptides capable of manipulating biological pathways.     

Designed DNA molecules: principles and applications of molecular nanotechnology

Long admired for its informational role in the cell, DNA is now emerging as an ideal molecule for molecular nanotechnology. Biologists and biochemists have discovered DNA sequences and structures with new functional properties, which are able to prevent the expression of harmful genes or detect macromolecules at low concentrations. Physical and computational scientists can design rigid DNA structures that serve as scaffolds for the organization of matter at the molecular scale, and can build simple DNA-computing devices, diagnostic machines and DNA motors. The integration of biological and engineering advances offers great potential for therapeutic and diagnostic applications, and for nanoscale electronic engineering.     

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/ .     

DNA计算机的分子生物学研究进展

DNA(脱氧核糖核酸)计算机研究是一个新领域。从字面上看,它既包含DNA研究也包含计算机的研究,因而也包含DNA技术与计算机技术如何交融的研究。1994年,Adleman在Science上报道了首例DNA计算的研究结果;2001年,Benenson等在Nature报道了一种由DNA分子和相应的酶分子构成的、有图灵机功能的可程序试管型DNA计算机,标志着DNA计算机研究的重大进展。DNA计算机最大的特点是超大规模的并行运算能力和潜在的巨大的数据储存能力。目前DNA计算机研究已涉及许多领域,包括生物学、数学、物理、化学、计算机科学和自动化工程等具体应用,是计算概念上的一次革命。DNA计算机的研究大大促进了DNA分子操作技术尤其是在纳米尺度下操作DNA分子的研究速度。从DNA计算机的基本原理、应用形式、与基因组学研究的重要关系等方面总结和评述了相关研究进展。     

Strategy for surveying the proteome using affinity proteomics and mass spectrometry

Antibody‐based microarrays is a rapidly evolving technology that has gone from the first proof‐of‐concept studies to more demanding proteome profiling applications, during the last years. Miniaturized microarrays can be printed with large number of antibodies harbouring predetermined specificities, capable of targeting high‐ as well as low‐abundant analytes in complex, nonfractionated proteomes. Consequently, the resolution of such proteome profiling efforts correlate directly to the number of antibodies included, which today is a key limiting factor. To overcome this bottleneck and to be able to perform in‐depth global proteome surveys, we propose to interface affinity proteomics with MS‐based read‐out, as outlined in this technical perspective. Briefly, we have defined a range of peptide motifs, each motif being present in 5–100 different proteins. In this manner, 100 antibodies, binding 100 different motifs commonly distributed among different proteins, would potentially target a protein cluster of 10⁴ individual molecules, i.e. around 50% of the nonredundant human proteome. Notably, these motif‐specific antibodies would be directly applicable to any proteome in a specie independent manner and not biased towards abundant proteins or certain protein classes. The biological sample is digested, exposed to these immobilized antibodies, whereby motif‐containing peptides are specifically captured, enriched and subsequently detected and identified using MS.     

Target-responsive DNA-capped nanocontainer used for fabricating universal detector and performing logic operations

Nucleic acids have become a powerful tool in nanotechnology because of their controllable diverse conformational transitions and adaptable higher-order nanostructure. Using single-stranded DNA probes as the pore-caps for various target recognition, here we present an ultrasensitive universal electrochemical detection system based on graphene and mesoporous silica, and achieve sensitivity with all of the major classes of analytes and simultaneously realize DNA logic gate operations. The concept is based on the locking of the pores and preventing the signal-reporter molecules from escape by target-induced the conformational change of the tailored DNA caps. The coupling of ‘waking up’ gatekeeper with highly specific biochemical recognition is an innovative strategy for the detection of various targets, able to compete with classical methods which need expensive instrumentation and sophisticated experimental operations. The present study has introduced a new electrochemical signal amplification concept and also adds a new dimension to the function of graphene-mesoporous materials hybrids as multifunctional nanoscale logic devices. More importantly, the development of this approach would spur further advances in important areas, such as point-of-care diagnostics or detection of specific biological contaminations, and hold promise for use in field analysis.     

Microarrays: The Technology,Analysis and Application

DNA microarray analysis represents one of the major advances leading to the development of functional genomics and proteomics. It involves the fabrication of DNA either by in situ or on‐chip photolithographic synthesis or by inkjet or microjet deposition, as microspots immobilized on the surface of miniaturized substrates like glass or membranes. The immobilized DNA molecules are then allowed to hybridize with labeled complementary DNA. The hybrid DNA so formed is read through scanning devices, such as fluorescence and radioactivity. Further, computational approaches, for example, normalization and clustering allow thousands of genetic parameters in a single experiment to be simultaneously analyzed. This review discusses the fundamental principles and data analysis of the microarray technology, while focusing on its application in gene expression analysis, genotyping for point mutation and diseases diagnostics.     

Recursive construction of perfect DNA molecules from imperfect oligonucleotides

Making faultless complex objects from potentially faulty building blocks is a fundamental challenge in computer engineering, nanotechnology and synthetic biology. Here, we show for the first time how recursion can be used to address this challenge and demonstrate a recursive procedure that constructs error‐free DNA molecules and their libraries from error‐prone oligonucleotides. Divide and Conquer (D&C), the quintessential recursive problem‐solving technique, is applied in silico to divide the target DNA sequence into overlapping oligonucleotides short enough to be synthesized directly, albeit with errors; error‐prone oligonucleotides are recursively combined in vitro, forming error‐prone DNA molecules; error‐free fragments of these molecules are then identified, extracted and used as new, typically longer and more accurate, inputs to another iteration of the recursive construction procedure; the entire process repeats until an error‐free target molecule is formed. Our recursive construction procedure surpasses existing methods for de novo DNA synthesis in speed, precision, amenability to automation, ease of combining synthetic and natural DNA fragments, and ability to construct designer DNA libraries. It thus provides a novel and robust foundation for the design and construction of synthetic biological molecules and organisms.     

Towards a theoretical foundation for morphological computation with compliant bodies

The control of compliant robots is, due to their often nonlinear and complex dynamics, inherently difficult. The vision of morphological computation proposes to view these aspects not only as problems, but rather also as parts of the solution. Non-rigid body parts are not seen anymore as imperfect realizations of rigid body parts, but rather as potential computational resources. The applicability of this vision has already been demonstrated for a variety of complex robot control problems. Nevertheless, a theoretical basis for understanding the capabilities and limitations of morphological computation has been missing so far. We present a model for morphological computation with compliant bodies, where a precise mathematical characterization of the potential computational contribution of a complex physical body is feasible. The theory suggests that complexity and nonlinearity, typically unwanted properties of robots, are desired features in order to provide computational power. We demonstrate that simple generic models of physical bodies, based on mass-spring systems, can be used to implement complex nonlinear operators. By adding a simple readout (which is static and linear) to the morphology such devices are able to emulate complex mappings of input to output streams in continuous time. Hence, by outsourcing parts of the computation to the physical body, the difficult problem of learning to control a complex body, could be reduced to a simple and perspicuous learning task, which can not get stuck in local minima of an error function.