Simulations of biological processes

Beck, M.B. "Identification and parameter estimation of biological process models" In "System Simulation in Water Resources", Vansteenkiste, G.C., Ed. North Holland, 1975, 19-44. 

AIMD and Hybrid/AIMD simulations certainly constitute a promising novel tool for an ab initio modeling of biological processes. However, due to the great complexity of the systems, technical and fundamental reasons still limit the domain of applications. 

On the frontier of Car-Parrinello simulations is the application to biological systems. These systems are large and often require the incorporation of solvation structures, and energetics of solvation are generally important. Thus, computations of entire biomolecules would be too expensive. Nevertheless, several recent studies have isolated essential features of biological processes by studying carefully chosen models consisting of a tractable number of atoms. 

Employee for Modeling and Simulation of Biological, Chemical and Physical processes at the Scientific Services of Ciba Geigy (Basel), later Novartis (Basel)... 

The key advantage to top-down simulations of biological systems is that the process begins with the end, the full envelope of functional (phenotypic) behaviors of which an integrated biological system is capable, in mind. Top-down simulations typically begin with simple representations of the dynamics of the system phenotype, because these data are much more prevalent than data on internal states, and therefore, provide a firm foundation for guiding the development of the simulation. 

The field of applications of molecular quantum dynamics covers broad areas of science not only in chemistry but also in physics and biology. Historically, due to the fact that the full quantum-mechanical simulation of molecular processes is limited to small systems, molecular quantum dynamics has given rise mainly to important applications of astrophysical and atmospheric relevance. In the interstellar medium or the Earth atmosphere, molecules are generally in the gas phase. Since many accurate spectroscopic data are available, these media have provided various prototype systems to study quantum effects in molecules and to calibrate the theoretical methods used to simulate these effects. In this context, it is not surprising that much theoretical effort is still directed toward modeling the full quantum-mechanical treatment of small molecules. Among others, one can cite the studies of the spectroscopy of water [159-161], and of the spectroscopy, photodissociation. 

The knowledge of real-phase behaviour of electrolyte solutions provides a basis for the design and the simulation of many processes in biological and chemical engineering. Otherwise, salts are systematically used for the recovery of biomolecules and as auxiliary material in separation units. Thus, technical applications of systems containing electrolytes can be found in waste-water and drinking-water treatment, fertilizer production,... 

Normal mode analysis exists as one of the two main simulation techniques used to probe the large-scale internal dynamics of biological molecules. It has a direct connection to the experimental techniques of infrared and Raman spectroscopy, and the process of comparing these experimental results with the results of normal mode analysis continues. However, these experimental techniques are not yet able to access directly the lowest frequency modes of motion that are thought to relate to the functional motions in proteins or other large biological molecules. It is these modes, with frequencies of the order of 1 cm , that mainly concern this chapter. 

For 25 years, molecular dynamics simulations of proteins have provided detailed insights into the role of dynamics in biological activity and function [1-3]. The earliest simulations of proteins probed fast vibrational dynamics on a picosecond time scale. Fifteen years later, it proved possible to simulate protein dynamics on a nanosecond time scale. At present it is possible to simulate the dynamics of a solvated protein on the microsecond time scale [4]. These gains have been made through a combination of improved computer processing (Moore s law) and clever computational algorithms [5]. 

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