Physics in Molecular Biology
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Tools developed by statistical physicists are of increasing importance in the analysis of complex biological systems. Physics in Molecular Biology, first published in 2005, discusses how physics can be used in modeling life. It begins by summarizing important biological concepts, emphasizing how they differ from the systems normally studied in physics. A variety of topics, ranging from the properties of single molecules to the dynamics of macro-evolution, are studied in terms of simple mathematical models. The main focus of the book is on genes and proteins and how they build systems that compute and respond. The discussion develops from simple to complex systems, and from small-scale to large-scale phenomena. This book will inspire advanced undergraduates and graduate students in physics to approach biological subjects from a physicist's point of view. It is self-contained, requiring no background knowledge of biology, and only familiarity with basic concepts from physics, such as forces, energy, and entropy.
information at the DNA level has a mass of 600 kg/mol. The peculiar structure of biological macromolecules represents the existence of two distinct energy scales. The polymer backbone is held together by covalent (strong) bonds, i.e. energies of order ∼ 200 kcal/mol (∼ 10 eV). The secondary and tertiary structure, i.e. the DNA double helix (see Fig. 3.1), the folded form of a 44 DNA 45 Table 3.1. The genetic code 5 end U U U U C C C C A A A A G G G G U C A G 3 end Phe (F) Phe (F) Leu
(5.13) One now obtains a characteristic V-shaped curve, which is usually called a chevron plot; see Fig. 5.7. The straight-line extrapolations shown with dotted lines can be used to extrapolate ku , kf to zero and high denaturant concentration. Thus one can infer folding times that are faster than the inherent mixing time limit of 2–5 ms. The ratio of forward and backward rates must give the equilibrium constant for any denaturant concentration [N] kf = K (D) = ku [U] which can be measured by
− kB T ln kB T δ (5.37) which has the same non-monotonous form (T − T ln(T )) as the one obtained from assuming4 a constant Cp in the Questions on p. 101. In Fig. 5.21 we show G, to be compared with Fig. 5.4 (left-hand panel). If µ < −E0 then the unfolded state (ﬁrst term, exposed residue) wins at low temperature. As T increases, the water entropy term g can dominate sufﬁciently over the few lower-energy terms in the water ladder, and this leads to folding (burial of residues in a hydrophobic
motor works is not obvious. Thermal noise and diffusion certainly play a role, making this “soft” machine qualitatively different from a macroscopic motor. In the next section we elaborate on these ideas through some models. The most studied motors include myosin and kinesin, which move along the polymers that deﬁne the cytoskeleton. Kinesin walks on microtubules (Fig. 6.1), whereas myosin walks on polymerized actin. Microtubules and actin ﬁbers are long (µm) polymers where the monomer units are
number of bacteria per mL. To count phages we remove the E. coli from the solution, and we are left with a solution containing the released phages. An appropriate dilution of this solution is poured over a detector strain of E. coli that has receptors for the λ. This plate is grown overnight. Each phage will then initiate a local plaque. The reason is as follows. The phage will infect a bacterium and in most cases (∼99%) it enters lysis. Then new phages are produced and they infect and kill the