Biomolecules as Paradigms of Complex
Matter
Hans Frauenfelder
Los Alamos National Laboratory
Center for Nonlinear Studies, MS B258
Los Alamos, NM 87545
(505) 677-2547
(505) 665-2659
"Ask not what physics can do for biology, ask what biology can do for physics." Stan Ulam, to HF.
Nature invented and perfected complex matter long before physicists became interested in CAM. Biology can teach us concepts and laws of complexity, if we select the proper systems and learn to study and read the message. At one end of biological complexity are brains, at the other biomolecules. Here I focus on biomolecules, in particular proteins. They have gone through four Gigayears of R&D, and can be characterized as SECAM, or self-organizing evolutionary complex adaptive matter. Coordinated studies involving biologists, chemists, computer scientists, mathematicians, and physicists may lead to insight into CAM that may be difficult to obtain by using more traditional materials. Here I sketch three areas where systematic studies of biomolecules have already contributed to an understanding of complexity and where important concepts have emerged:
1.Energy landscapes. A protein does not have a unique structure and ground state energy; it can assume a very large number of different conformations or conformational substates. The substates can be described by a rough energy landscape in 3 N dimensions, where N is the number of atoms in the protein. The exploration of the energy landscape is still at a beginning, but it is already clear that it is arranged in a hierarchy and that its organization is crucial for the dynamics and function of biomolecules.
2. Reactions in complex systems. Biomolecules are dynamic systems and a proper description of transitions among the states and substates requires an understanding of the relevant theory, covering phenomena from the influence of friction to quantum-mechanical tunneling and the effect of collective motions. A close interaction between theory and experiment can lead to progress in this area.
3. Connections among structure, energy landscape, dynamics, and function. The exploration and understanding of these connections are still rudimentary, but progress would be important for fields from medicine to materials science.