Towards a biomolecular computer.

A new version of computing and information processing devices may result from major principles of information processing at molecular level. Non-discrete biomolecular computers based on these principles seems to be capable of solving problems of high computational complexity. One of the possible ways to implement these devices is based on biochemical non-linear dynamical systems. Means and ways to materialize biomolecular computers are discussed.     

Imaging biochemistry inside cells

Proteins provide the building blocks for multicomponent molecular units, or pathways, from which higher cellular functions emerge. These units consist of either assemblies of physically interacting proteins or dispersed biochemical activities connected by rapidly diffusing second messengers, metabolic intermediates, ions or other proteins. It will probably remain within the realm of genetics to identify the ensemble of proteins that constitute these functional units and to establish the first-order connectivity. The dynamics of interactions within these protein machines can be assessed in living cells by the application of fluorescence spectroscopy on a microscopic level, using fluorescent proteins that are introduced within these functional units. Fluorescence is sensitive, specific and non-invasive, and the spectroscopic properties of a fluorescent probe can be analysed to obtain information on its molecular environment. The development and use of sensors based on the genetically encoded variants of green-fluorescent proteins has facilitated the observation of 'live' biochemistry on a microscopic level, with the advantage of preserving the cellular context of biochemical connectivity, compartmentalization and spatial organization. Protein activities and interactions can be imaged and localized within a single cell, allowing correlation with phenomena such as the cell cycle, migration and morphogenesis.     

The bhopalator: a molecular model of the living cell based on the concepts of conformons and dissipative structures

A molecular model of the living cell has been formulated based on a new theory of enzymic catalysis which takes into account the complementary roles of free energy and genetic information. The elementary units of free energy and genetic information that are necessary and sufficient for effectuating molecular mechanisms responsible for the life of the cell are called conformons. Conformons are visualized as a collection of a small number of catalytic residues of enzymes or segments of nucleic acids that are arranged in space and time with appropriate force vectors so as to cause chemical transformations or physical changes of a substrate or a bound ligand. So defined, conformons provide a plausible molecular means to link the genetic information stored in DNA and its ultimate expression, namely networks of coupled intracellular biochemical reactions and physical processes maintained by a continuous dissipation of free energy--dissipative structures of Prigogine. The proposed model of the living cell appears to possess the potential for bridging the gap between molecular biology and the biology of multicellular systems.     

Bacteria as computers making computers

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments.     

Hierarchy measure for complex networks

Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks and, as we demonstrate, is capable of capturing the essential features of the structure and the degree of hierarchy in a complex network. The measure we introduce is based on a generalization of the m-reach centrality, which we first extend to directed/partially directed graphs. Then, we define the global reaching centrality (GRC), which is the difference between the maximum and the average value of the generalized reach centralities over the network. We investigate the behavior of the GRC considering both a synthetic model with an adjustable level of hierarchy and real networks. Results for real networks show that our hierarchy measure is related to the controllability of the given system. We also propose a visualization procedure for large complex networks that can be used to obtain an overall qualitative picture about the nature of their hierarchical structure.     

A crystallographic molecular lattice builder applied to model lipid bilayers

It is often desirable for noncrystallographers to generate graphical models of three-dimensional crystal structures based on published coordinates of the atoms that make up the crystallographic unit cells. This type of visualization is particularly important for small-molecule crystals, such as lipid crystals, where one may be interested in investigating interactions between the individual molecules in addition to their conformations. BILAYER BUILDER is a program that generates a portion of the entire crystal structure from the coordinates of the molecules in a single unit cell. It gives users of small desktop computers, such as the Apple Macintosh, the capability to generate and examine model crystal structures with a molecular graphics display program. BILAYER BUILDER stores the crystal coordinates in a Brookhaven Protein Data Bank file format for possible use in a variety of applications on many different computers. Initially, it was written for use with lipid crystals and bilayers but may be used for building an assortment of molecular crystals.     

Transient state kinetics tutorial using the kinetics simulation program, KINSIM.

This article provides an introduction to a computer tutorial on transient state kinetics. The tutorial uses our Macintosh version of the computer program, KINSIM, that calculates the time course of reactions. KINSIM is also available for other popular computers. This program allows even those investigators not mathematically inclined to evaluate the rate constants for the transitions between the intermediates in any reaction mechanism. These rate constants are one of the insights that are essential for understanding how biochemical processes work at the molecular level. The approach is applicable not only to enzyme reactions but also to any other type of process of interest to biophysicists, cell biologists, and molecular biologists in which concentrations change with time. In principle, the same methods could be used to characterize time-dependent, large-scale processes in ecology and evolution. Completion of the tutorial takes students 6-10 h. This investment is rewarded by a deep understanding of the principles of chemical kinetics and familiarity with the tools of kinetics simulation as an approach to solve everyday problems in the laboratory.     

Nonlinear dynamics of the distributed biochemical systems functioning in the dissipative structure formation mode

Nonlinear dynamical biomolecular systems can evidently be considered as prototypes of information processing devices at molecular level capable to solve problems of high computational complexity. Keeping in mind this goal the dynamics of biochemical system based on enzymatic oxidation of uric acid was considered. The system was studied in the version of distributed biomolecular structure having predetermined geometry of enzyme distribution on a porous planar medium. Being in the regime of stepwise dissipative structure formation this system demonstrated complicated modes of behaviour.     

A phenomenological approach to the simulation of metabolism and proliferation dynamics of large tumour cell populations

A major goal of modern computational biology is to simulate the collective behaviour of large cell populations starting from the intricate web of molecular interactions occurring at the microscopic level. In this paper we describe a simplified model of cell metabolism, growth and proliferation, suitable for inclusion in a multicell simulator, now under development (Chignola R and Milotti E 2004 Physica A 338 261-6). Nutrients regulate the proliferation dynamics of tumour cells which adapt their behaviour to respond to changes in the biochemical composition of the environment. This modelling of nutrient metabolism and cell cycle at a mesoscopic scale level leads to a continuous flow of information between the two disparate spatiotemporal scales of molecular and cellular dynamics that can be simulated with modern computers and tested experimentally.     

Iterative cluster analysis of protein interaction data

MOTIVATION: Generation of fast tools of hierarchical clustering to be applied when distances among elements of a set are constrained, causing frequent distance ties, as happens in protein interaction data. RESULTS: We present in this work the program UVCLUSTER, that iteratively explores distance datasets using hierarchical clustering. Once the user selects a group of proteins, UVCLUSTER converts the set of primary distances among them (i.e. the minimum number of steps, or interactions, required to connect two proteins) into secondary distances that measure the strength of the connection between each pair of proteins when the interactions for all the proteins in the group are considered. We show that this novel strategy has advantages over conventional clustering methods to explore protein-protein interaction data. UVCLUSTER easily incorporates the information of the largest available interaction datasets to generate comprehensive primary distance tables. The versatility, simplicity of use and high speed of UVCLUSTER on standard personal computers suggest that it can be a benchmark analytical tool for interactome data analysis. AVAILABILITY: The program is available upon request from the authors, free for academic users. Additional information available at http://www.uv.es/genomica/UVCLUSTER.     

Improved resolution on the phylogenetic relationships among Pseudomonas by the combined analysis of atpD, carA, recA and 16S rDNA

A study of representatives of the bacterial genus Pseudomonas, analysing a combined data set of four molecular sequences with completely different properties and evolutionary constraints, is reported. The best evolutionary model was obtained with a hierarchical hypothesis testing program to describe each data set and the combined data set is presented and analysed under the likelihood criterion. The resolution among Pseudomonas taxa based on the combined data set analysis of the different lineages increased due to a synergistic effect of the individual data sets. The unresolved fluorescens lineage, as well as other weakly supported lineages in the single data set trees, should be revised in detail at the biochemical and molecular level. The taxonomic status of biovars of P. putida is discussed.     

Signal transduction networks: topology, response and biochemical processes

Conventionally, biological signal transduction networks are analysed using experimental and theoretical methods to describe specific protein components, interactions, and biochemical processes and to model network behavior under various conditions. While these studies provide crucial information on specific networks, this information is not easily converted to a broader understanding of signal transduction systems. Here, using a specific model of protein interaction we analyse small network topologies to understand their response and general properties. In particular, we catalogue the response for all possible topologies of a given network size to generate a response distribution, analyse the effects of specific biochemical processes on this distribution, and analyse the robustness and diversity of responses with respect to internal fluctuations or mutations in the network. The results show that even three- and four-protein networks are capable of creating diverse and biologically relevant responses, that the distribution of response types changes drastically as a function of biochemical processes at protein level, and that certain topologies strongly pre-dispose a specific response type while others allow for diverse types of responses. This study sheds light on the response types and properties that could be expected from signal transduction networks, provides possible explanations for the role of certain biochemical processes in signal transduction and suggests novel approaches to interfere with signaling pathways at the molecular level. Furthermore it shows that network topology plays a key role on determining response type and properties and that proper representation of network topology is crucial to discover and understand so-called building blocks of large networks.     

Toward the assembly of a minimal divisome

The construction of an irreducible minimal cell having all essential attributes of a living system is one of the biggest challenges facing synthetic biology. One ubiquitous task accomplished by any living systems is the division of the cell envelope. Hence, the assembly of an elementary, albeit sufficient, molecular machinery that supports compartment division, is a crucial step towards the realization of self-reproducing artificial cells. Looking backward to the molecular nature of possible ancestral, supposedly more rudimentary, cell division systems may help to identify a minimal divisome. In light of a possible evolutionary pathway of division mechanisms from simple lipid vesicles toward modern life, we define two approaches for recapitulating division in primitive cells: the membrane deforming protein route and the lipid biosynthesis route. Having identified possible proteins and working mechanisms participating in membrane shape alteration, we then discuss how they could be integrated into the construction framework of a programmable minimal cell relying on gene expression inside liposomes. The protein synthesis using recombinant elements (PURE) system, a reconstituted minimal gene expression system, is conceivably the most versatile synthesis platform. As a first step towards the de novo synthesis of a divisome, we showed that the N-BAR domain protein produced from its gene could assemble onto the outer surface of liposomes and sculpt the membrane into tubular structures. We finally discuss the remaining challenges for building up a self-reproducing minimal cell, in particular the coupling of the division machinery with volume expansion and genome replication.     

Systems genetics in “-omics” era: current and future development

The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP–SNP genetic interactions, LD block–block interactions, miRNA–mRNA interactions, DNA–protein interactions, protein–protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate “-omics” datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.     

Design of dihydrofolate reductase inhibitors from X-ray crystal structures

Dihydrofolate reductase (DHFR) is an important therapeutic target for treatment of cancer and microbial disease. Its species specificity has resulted in the sequencing of a number of vertebrate and bacterial DHFRs, and the three-dimensional structure of isozymes from Escherichia coli, Lactobacillus casei, and chicken liver has been elucidated, in the presence of the coenzyme NADPH and of a number of inhibitors. This information has enabled scientists to try to design improved and more selective inhibitors, based on the known coordinates of the enzyme features. Simple use of computer graphics or wire models has resulted in the design of inhibitors with 50 times the activity of trimethoprim, an antibacterial DHFR inhibitor, by making use of an unused ionic binding site. However, in a number of instances this approach was completely unsuccessful because hydrophobic sites of interaction were preferred. More sophisticated techniques involve energy minimization of the small molecule-macromolecule interactions to optimize the geometry. In this paper I describe the use of a molecular mechanics program, AMBER, for predicting the geometry and relative energetics of binding. Very encouraging results have been obtained for a closely related series of compounds. Where differing entropic and solvent effects are involved, predictions may be poor. The use of super computers and molecular dynamics methods should increase this capability in the near future.     

HAMOG: Molecular graphics program for chemistry 5 biochemistry 5 molecular biology and enzyme research

HAMOG is a computer graphics program written in C for personal computers. Clear menus and a contextsensitive help option make the program easy to operate for occasional users. HAMOG provides a flexible environment for displaying and manipulating molecules and molecular systems. Special functions allow the investigation of structure-activity relationships of biologically active molecules. These include the calculation of molecular electrostatic potentials and fields, the superposition of molecules and the calculation of steric accessibilities. The visualization and manipulation of protein structures immediately readable from the Brookhaven Protein Data Bank files are also possible using HAMOG. The construction of any peptide or protein structure is very simple.