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Proteins: Paradigms of complexity
Center for Nonlinear Studies, MS B258, Los Alamos National Laboratory, Los Alamos, NM 87545
| Abstract |
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Proteins are the working machines of living systems. Directed by the DNA, of the order of a few hundred building blocks, selected from 20 different amino acids, are covalently linked into a linear polypeptide chain. In the proper environment, the chain folds into the working protein, often a globule of linear dimensions of a few nanometers. The biologist considers proteins units from which living systems are built. Many physical scientists look at them as systems in which the laws of complexity can be studied better than anywhere else. Some of the results of such studies will be sketched.
"The history of physics is also a history of concepts. For an understanding of the phenomena, the first condition is the introduction of adequate concepts."
Pauli to Heisenberg
During the past few decades, the general attitude of many physicists has undergone a sea change. It used to be that physicists loved simple systems, tried to understand them in the simplest terms, and often looked down on fields like chemistry and biology, where complexity reigned. No longer. Now many physicists are studying complex nonlinear systems and discover to their surprise how beautiful the problems are and how rewarding the interaction with biologists and chemists can be. Here I try to give a brief description of what proteins are, what they do, how complex they are, and why they are nearly ideal systems for the study of complexity. Whether this complexity can be called "self-organized" is a question of semantics.
| Complexity |
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A system can be called complex if it can assume a large number of
states or conformations and if it can carry information. One often
hears even biologists talk about "astronomically large numbers."
Astronomically large numbers are actually very small compared with
biological numbers. They are of the order of
10200 or log
nastro
200. Consider now DNA. It
is built from four different units (bases) and may contain
109 bases. The number of conceivable DNA is
therefore log nbio
108 >> log
nastro. The number of possible protein
is of the order of log nprot >> 200.
Even the number of states that an individual protein can assume is very
large. Biological systems clearly also carry information. Hence
proteins, and in general biological systems, are complex.
| Proteins |
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The textbook picture of a protein is clear: The folded structure is unique; each atom is in its proper place. The pictures obtained by x-ray diffraction techniques appear to support thisat first sightappealing situation. Such proteins would be aptly characterized by Schrödinger's words, "aperiodic crystals" (3). Reality, however, is different. Proteins are dynamic and not static systems (4), and they must perform motions to execute their functions. Motions are possible only if a given protein can assume a large number of somewhat different conformations, for instance with open and closed channels. Actually, the motions involve the atoms not just of the protein itself but also of the hydration shell, a layer of water surrounding the protein. The structure and dynamics of the protein and the hydration shell can be characterized by the energy or conformation landscape.
| The Energy Landscape |
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One goal of the physics approach to proteins is the exploration of the energy landscape. In no protein is the entire landscape known. This state is not surprising if one contemplates how many years it took to determine the energy levels of complex nuclei or atomssystems that are far simpler than proteins. Nevertheless, a number of features have emerged, mainly from studies of myoglobin (5, 7). One important feature is that the energy landscape is organized in a hierarchy, with valleys within valleys within valleys. In other words, the substates are organized in a series of tiers. The different tiers are distinguished by the (average) size of the barriers separating them. At the top of the hierarchy, in tier 0, are the taxonomic substates. They are small in number and are different enough that their properties can be studied individually. Myoglobin, for instance, has three taxonomic substates, called A0, A1, and A3. At physiological temperatures, the three substates interconvert rapidly and are in thermal equilibrium. The equilibrium can be shifted by external agents, for instance pH, lactate, or pressure. Each taxonomic substate contains a very large number of substates of tier 1, or statistical substates. Different statistical substates have, in general, different rates for a particular reaction and slightly different wavelengths of some transitions. At high temperatures, transitions among substates of tiers 0 and 1 are faster than, say, micro- or nanoseconds. At low temperatures, say below 100 K, transitions among the substates of tier 0 and 1 are essentially absent, and the existence of substates can be recognized, for instance, by the facts that reactions become nonexponential in time (8) and that "holes" can be burned into inhomogeneous spectral lines (9). Each statistical substate contains substates with lower barriers. They are small in number, can be called "few-level substates," and may be similar to such levels in glasses. Transitions between such substates can occur even in the millikelvin region.
Some features of the energy landscape of myoglobin are thus clear, but the details are far from being known. Moreover, the connections among substates, structure, and dynamics are far from understood.
| The Energy Landscape and Function |
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| Final Remark |
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| Footnotes |
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This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sciences, "Self-Organized Complexity in the Physical, Biological, and Social Sciences," held March 2324, 2001, at the Arnold and Mabel Beckman Center of the National Academies of Science and Engineering in Irvine, CA.
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