The phase diagram of globular protein solutions : the role of the range of interaction

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1998.Vita.Includes bibliographical references (p. 139-145).by Neer Ruben Asherie.Ph.D

Plasma Dynamics

Contains table of contents for Section 2 and reports on three research projects.National Science Foundation Grant ECS 89-02990U.S. Air Force - Office of Scientific Research Grant F49620-93-1-0108U.S. Army - Harry Diamond Laboratories Contract DAAL02-92-K-0037U.S. Department of Energy Grant DE-FG02-91-ER-40648U.S. Navy - Office of Naval Research Grant N00014-90-J-4130National Aeronautics and Space Administration Grant NAGW-2048National Science Foundation Grant ECS 88-22475U.S. Department of Energy Grant DE-FG02-91-ER-54109Magnetic Fusion Science Fellowship Progra

Plasma Dynamics

Contains table of contents for Section 2 and reports on four research projects.National Science Foundation Grant ECS-89-02990U.S. Air Force - Office of Scientific Research Grant AFOSR 89-0082-CU.S. Army - Harry Diamond Laboratories Contract DAAL02-89-K-0084U.S. Army - Harry Diamond Laboratories Contract DAAL02-92-K-0037U.S. Department of Energy Contract DE-AC02-90ER-40591U.S. Navy - Office of Naval Research Grant N00014-90-J-4130Lawrence Livermore National Laboratories Subcontract B-160456National Aeronautics and Space Administration Grant NAGW-2048National Science Foundation Grant ECS-88-22475U.S. Department of Energy Grant DE-FG02-91-ER-5410

An analytical model for the formation of economic clusters

A simple spatial economy derived from microeconomic foundations is presented to gain insight into the formation of economic clusters. In this model, the formation of economic clusters is a consequence of the competition between economic forces that are consistent with atomistic agents maximizing their utility. An analytic approach is used to obtain the evolution of economic clusters. With this approach, the number of clusters which will grow can be predicted. These results are derived in the traditional one-dimensional geometry and extended to the more realistic two-dimensional landscape.

Monte Carlo study of phase separation in aqueous protein solutions

The binary liquid phase separation of aqueous solutions of ␥-crystallins is utilized to gain insight into the microscopic interactions between these proteins. The interactions are modeled by a square-well potential with reduced range and depth ⑀. A comparison is made between the experimentally determined phase diagram and the results of a modified Monte Carlo procedure which combines simulations with analytic techniques. The simplicity and economy of the procedure make it practical to investigate the effect on the phase diagram of an essentially continuous variation of in the domain 1.05рр2.40. The coexistence curves are calculated and are in good agreement with the information available from previous standard Monte Carlo simulations conducted at a few specific values of . Analysis of the experimental data for the critical volume fractions of the ␥-crystallins permits the determination of the actual range of interaction appropriate for these proteins. A comparison of the experimental and calculated widths of the coexistence curves suggests a significant contribution from anisotropy in the real interaction potential of the ␥-crystallins. The dependence of the critical volume fraction c and the reduced critical energy ⑀ c upon the reduced range is also analyzed in the context of two ''limiting'' cases; mean field theory (→ϱ) and the Baxter adhesive sphere model (→1). Mean field theory fails to describe both the value of c and the width of the coexistence curve of the ␥-crystallins. This is consistent with the observation that mean field is no longer applicable when р1.65. In the opposite case, →1, the critical parameters are obtained for ranges much shorter than those investigated in the literature. This allows a reliable determination of the critical volume fraction in the adhesive sphere limit, c (ϭ1)ϭ0.266Ϯ0.009

The physics of protein self-assembly

Understanding protein self-assembly is important formany biological and industrial processes. Proteins can selfassemble into crystals, filaments, gels, and other amorphous aggregates. The final forms include virus capsids and condensed phases associated with diseases such as amyloid fibrils. Although seemingly different, these assemblies all originate from fundamental protein interactions and are driven by similar thermodynamic and kinetic factors. Herewe reviewrecent advances in understanding protein self-assembly through a soft condensed matter perspective with an emphasis on three specific systems: globular proteins, viruses, and amyloid fibrils. We conclude with a discussion of unanswered questions in the field