A cellular automata model of diffusion in aqueous systems

Computational Systems Biology in Cancer: Modeling Methods and Applications

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy.

Water chreodes and the mechanisms of ligand diffusion, general anesthesia, and sleep

The concept of the presence of passageways, chreodes, created by the influence of the hydropathic states of amino acid side chains on the surface water of proteins, has been proposed. These chreodes facilitate and direct the diffusion of neurotransmitters through surface water, to the receptor or active site on a protein. This system of chreodes is vulnerable to the presence of some other molecules that may encounter the chreode system. This encounter and disruption has been proposed to explain the mechanism of general anesthesia. Based on much recent evidence of the similarities between anesthesia from volatile anesthetic agents and sleep, a comparable mechanism has been proposed for sleep. Since this must be an exogenous substance to be comparable to a general anesthetic agent, it was proposed that this exogenous, sleep-producing substance is elemental nitrogen. Recent evidence supports these hypotheses.

Cellular-automata models of solid-liquid interfaces

A series of cellular-automata (CA) models have been created, simulating relationships between water (or aqueous solutions) and solid surfaces of differing hydropathic (i.e., hydrophilic or hydrophobic) nature. Both equilibrium- and dynamic-flow models were examined, employing simple breaking and joining rules to simulate the hydropathic interactions. The CA simulations show that water accumulates near hydrophilic surfaces and avoids hydrophobic surfaces, forming concave-up and concave-down meniscuses, resp., under equilibrium conditions. In the dynamic-flow simulations, the flow rate of water was found to increase past a wall surface as the surface became less hydrophilic, reaching a maximum rate when the solid surface was of intermediate hydropathic state, and then declining with further increase in the hydrophobicity of the surface. Solution simulations show that non-polar solutes tend to achieve higher concentrations near hydrophobic-wall surfaces, whereas other hydrophobic/hydrophilic combinations of solutes and surfaces do not show such accumulations. Physical interpretations of the results are presented, as are some possible biological consequences.

Water as a complex system: its role in ligand diffusion, general anesthesia, and sleep

The work and inspiration of Robert Rosen is stated and expressed in personal tones. The concept of passages through water (H2O) near protein surfaces is reviewed in terms of its influence on ligand diffusion to an effector. This is offered as a target for interference by a non-specific general anesthetic agent. In view of the similarities between this anesthetic state and sleep, this mechanism is proposed to be operative for the sleep/wake states. Based on this mechanism and other factors, nitrogen (N2) is proposed as an exogenous sleep factor.

Computational systems biology in drug discovery and development: methods and applications

Computational systems biology is an emerging field in biological simulation that attempts to model or simulate intra- and intercellular events using data gathered from genomic, proteomic or metabolomic experiments. The need to model complex temporal and spatiotemporal processes at many different scales has led to the emergence of numerous techniques, including systems of differential equations, Petri nets, cellular automata simulators, agent-based models and pi calculus. This review provides a brief summary and an assessment of most of these approaches. It also provides examples of how these methods are being used to facilitate drug discovery and development.

A cellular automata model of ligand passage over a protein hydrodynamic landscape

The subject of ligand passage to an active site on a protein is addressed. Current views on the mechanism and the possible role of surface water are discussed. A theory is presented in which the pattern of hydropathic states of protein surface amino acid side chains is invoked as the influence on the relative hydrophobic effects of nearby water. The theory describes a ligand passage through the hydrodynamic near-surface water which exhibits temporary organized cavities resembling the chreodes introduced by Waddington. The passage of the ligand to the active site is facilitated by this dynamic mechanism. Cellular automata models of preferential directional diffusion through these chreodes support the theory. The theory may be invoked to explain a number of ligand-active site observations and serves as an idea for further studies.

Cellular automata models of chemical systems

This paper describes the use of kinematic, asynchronous, stochastic cellular automata to model liquid properties, solution phenomena and kinetic phenomena encountered in complex biological systems. Cellular automata models of dynamic phenomena represent in silico experiments designed to assess the effects of competing factors on the physical and chemical properties of solutions and other complex systems. Specific applications include solution behavior, separation of immiscible liquids, micelle formation, diffusion, membrane passage, first- and second-order chemical kinetics, enzyme activity and acid dissociation. Cellular automata is thus considered as providing an exploratory method for the analysis of dynamic phenomena and the discovery and understanding of new, unexpected phenomena.