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Ever since scientists discovered that conventional silicon-based computers have an upper limit in terms of speed, they have been searching for alternative media with which to solve computational problems. That search has led them, among other places, to DNA.
Juvenile hormone (JH) activity of one hundred and eighty 2,4-dienoates reported for the larvae/pupae of six insect species was modeled using 915 atom pairs and 258 global molecular descriptors (topological and geometrical). Ridge regression, principal component regression and partial least square regression methods were used to model each of the JH activities. The use of all of the available parameters did not yield any good models, and extensive predictor trimming was necessary to improve the models. Ridge regression was found to give the best results among the three statistical tools used. The top ten molecular descriptors selected based on the t-statistic for each of the six models were found to be mostly atom pairs containing heteroatoms and topochemical descriptors. This suggests the importance of the chemical nature of the ligand rather than mere space-filling as the basis of the JH bioactivity. The residual plots indicate the existence of some non-linear relations, and recursive partitioning was used to capture any nonlinear relation between the bioassays and the molecular descriptors.
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Any mind (man or computer) using Physical laws is a part of physical world, and thus it is necessary to correct physical laws for taking into account influence of the work of real limited computer on the predicted result. If we suppose that univerce was constructed to be supreme regular for mind, then this correction is negligible and on principle there is possibility to calculate relation between fundamental physical and biophysical constants. Two main principle are proposed: 1. The principle of minimum action and uncontrole influence of mind. 2. The maximum asymmetry of elementary particles, which are allowed by first principle. The first principle requires the upper and the lower limits for all physical values, and first of all the upper limit for velocity (c) and the lower limit for action (h). The second principle allows to construct the minimal physical elements for mind.
The task of computing molecular structure from combinations of experimental and theoretical constraints is expensive because of the large number of estimated parameters (the 3D coordinates of each atom) and the rugged landscape of many objective functions. For large molecular ensembles with multiple protein and nucleic acid components, the problem of maintaining tractability in structural computations becomes critical. A well-known strategy for solving difficult problems is divide-and-conquer. For molecular computations, there are two ways in which problems can be divided: (1) using the natural hierarchy within biological macromolecules (taking advantage of primary sequence, secondary structural subunits and tertiary structural motifs, when they are known); and (2) using the hierarchy that results from analyzing the distribution of structural constraints (providing information about which substructures are constrained to one another). In this paper, we show that these two hierarchies can be complementary and can provide information for efficient decomposition of structural computations. We demonstrate five methods for building such hierarchies--two automated heuristics that use both natural and empirical hierarchies, one knowledge-based process using both hierarchies, one method based on the natural hierarchy alone, and for completeness one random hierarchy oblivious to auxiliary information--and apply them to a data set for the procaryotic 30S ribosomal subunit using our probabilistic least squares structure estimation algorithm. We show that the three methods that combine natural hierarchies with empirical hierarchies create decompositions which increase the efficiency of computations by as much as 50-fold. There is only half this gain when using the natural decomposition alone, while the random hierarchy suggests that a speedup of about five can be expected just by virtue of having a decomposition. Although the knowledge-based method performs marginally better, the automatic heuristics are easier to use, scale more reliably to larger problems, and can match the performance of knowledge-based methods if provided with basic structural information.
Molecular dynamics computer simulations are used to determine the self-diffusion coefficients for a Gay-Berne model mesogen GB (4.4,20,1,1) in the isotropic, nematic and smectic A phases along two isobars. The values of the parallel and perpendicular diffusion coefficients, D(parallel) and D(perpendicular), are calculated and compared in the different phases. For the phase sequence isotropic-smectic A, D(perpendicular)*> or =D(parallel)* over the whole smectic A range with the ratio D(parallel)*/D(perpendicular)* decreasing with decreasing temperature. At a higher pressure, a nematic phase is observed between these two phases and we find that D(parallel)*>D(perpendicular)* throughout the nematic region and the inequality D(parallel)*>D(perpendicular)* remains on entering the smectic A phase. However, the ratio D(parallel)*/D(perpendicular)* decreases with decreasing temperature within the smectic A range and eventually this ratio inverts such that D(perpendicular)*>D(parallel)* at low temperatures. The temperature dependence of the parallel diffusion coefficient in the smectic A phase for this model mesogen is compared to that predicted by a theoretical model for diffusion subject to a cosine potential.
In the last quarter of a century silicon-based integrated circuits (ICs) have played a major role in the growth of the economy throughout the world. A number of new technologies, such as quantum computing, molecular computing, DNA molecules for computing, etc., are currently being explored to create a product to replace semiconductor transistor technology. We have examined all of the currently explored options and found that none of these options are suitable as silicon IC's replacements. In this paper we provide fundamental device criteria that must be satisfied for the successful operation of a manufacturable, not yet invented, device. The two fundamental limits are the removal of heat and reliability. The switching speed of any practical man-made computing device will be in the range of 10(-15) to 10(-3) s. Heisenberg's uncertainty principle and the computer architecture set the heat generation limit. The thermal conductivity of the materials used in the fabrication of a nanodimensional device sets the heat removal limit. In current electronic products, redundancy plays a significant part in improving the reliability of parts with macroscopic defects. In the future, microscopic and even nanoscopic defects will play a critical role in the reliability of disruptive nanoelectronics. The lattice vibrations will set the intrinsic reliability of future computing systems. The two critical limits discussed in this paper provide criteria for the selection of materials used in the fabrication of future devices. Our work shows that diamond contains the clue to providing computing devices that will surpass the performance of silicon-based nanoelectronics.
Molecular dynamics simulations have been used to investigate the flexibility and variations in the shape of the binding site of an antibody against human Rhinovirus serotype 2 (HRV2) and its complex with a 15 amino acid oligopeptide, the structure of which has been recently determined by X-ray crystallography. During the simulation of the unbound antibody the binding site, defined in terms of the hypervariable regions or complementarity determining regions (CDRs), shows significant fluctuations in shape. For the complex such variations in the shape of the binding site were reduced. The largest fluctuations in the unbound antibody occurred within the CDR-H3. The largest differences between the bound and unbound crystal structures are also associated with CDR-H3. The relative displacements of the loops have been analysed in terms of internal distortions, rigid body motions of the loops and changes with respect to the framework regions. The degree to which the motions of the loops are correlated and the variation in the volume of the binding pocket during the simulation have also been examined.
Parallel computers offer a solution to improve the lengthy computation time of many conventional, sequential programs used in molecular biology. On a parallel computer, different pieces of the computation are performed simultaneously on different processors. LINKMAP is a sequential program widely used by scientists to perform genetic linkage analysis. We have converted LINKMAP to run on a parallel computer, using the machine-independent parallel programming language, Linda. Using the parallelization of LINKMAP as a case study, the paper outlines an approach to converting existing highly iterative programs to a parallel form. The paper describes the steps involved in converting the sequential program to a parallel program. It presents performance benchmarks comparing the sequential version of LINKMAP with the parallel version running on different parallel machines. The paper also discusses alternative approaches to the problem of "load balancing," making sure the computational load is shared as evenly as possible among the available processors.
The living cell is controlled by a molecular stochastic computer of parallel-successive action. MCC may be equivalent to the universal computer. MCC operates with molecule-words (DNA, RNA, proteins) according to the programme recorded in DNA and RNA. Operations are produced by molecular devices (RNA- and DNA-polymerases, ligases, proteinases and so on). Molecular devices operating with molecule-words are recorded on molecules themselves, and they are read off by ribosomes. Therefore the programme of the reorganization of the programme itself may be recorded on the molecule-words. MCC operates with molecular words having definite addresses. The words and the operators collide by Brownian movement and combine if the molecular surface of address segment is complementary and properly oriented. It is possible to reproduce not only the programmes but also the operators of MCC. The molecular computer operates with word-molecules according to the programme, recorded in DNA, with the aim of predicting an outer situation in the next time-moment and selecting of a correct answer by synthesis of suitable proteins and other substances and also by macroscopic motion. Each step of directed calculation is needed of the consumption of minimally necessary portion of free energy and search is due to the Brownian movement without free energy loss. Cyclic nucleotides are intraneuron membrane potential controlling systems which can be described as molecular diffusional analog computers, well fitted to solve mathematical physics equations if there are high frequency generators and regulators of cyclic nucleotides sources and sinks. It is suggested that molecular proton channels in an electric field are such generators of 10(11)-10(12) Hz. Biophysics cannot use the ordinary laws of physics and must take into account the influence on the phenomena to be studied, not only of a measurement but also of a calculation process in the real device predicting the future.