Protein Folding: Past and Future: Fifty years ago the Nobel Prize in chemistry was awarded to Max Perutz and John Kendrew for determining the structure of globular proteins. Since first viewing their structure of myoglobin, scientists have sought to understand protein folding. Dill and MacCallum (p. 1042 ) review the progress that has been made on three central questions: What is the code that relates sequence to structure? How do proteins fold so fast? Can protein structure be computationally predicted? While we have come some way toward answering these questions, new questions have been gene rated. It is no longer useful to talk about “solving the protein-folding problem”—protein folding has grown into a field of research where the next 50 years promise to be as exciting as the last.

How are water’s material properties encoded within the structure of the water molecule? This is pertinent to understanding Earth’s living systems, its materials, its geochemistry and geophysics, and a broad spectrum of its industrial chemistry. Water has distinctive liquid and solid properties: It is highly cohesive. It has volumetric anomalies—water’s solid (ice) floats on its liquid; pressure can melt the solid rather than freezing the liquid; heating can shrink the liquid. It has more solid phases than other materials. Its supercooled liquid has divergent thermodynamic response functions. Its glassy state is neither fragile nor strong. Its component ions—hydroxide and protons—diffuse much faster than other ions. Aqueous solvation of ions or oils entails large entropies and heat capacities. We review how these properties are encoded within water’s molecular structure and energies, as understood from theories, simulations, and experiments. Like simpler liquids, water molecules are nearly spherical and interact with each other through van der Waals forces. Unlike simpler liquids, water’s orientation-dependent hydrogen bonding leads to open tetrahedral cage-like structuring that contributes to its remarkable volumetric and thermal properties.

What are the physical limits to cell behavior? Often, the physical limitations can be dominated by the proteome, the cell’s complement of proteins. We combine known protein sizes, stabilities, and rates of folding and diffusion, with the known protein-length distributions P ( N ) of proteomes ( Escherichia coli , yeast, and worm), to formulate distributions and scaling relationships in order to address questions of cell physics. Why do mesophilic cells die around 50 °C? How can the maximal growth-rate temperature (around 37 °C) occur so close to the cell-death temperature? The model shows that the cell’s death temperature coincides with a denaturation catastrophe of its proteome. The reason cells can function so well just a few degrees below their death temperature is because proteome denaturation is so cooperative. Why are cells so dense-packed with protein molecules (about 20% by volume)? Cells are packed at a density that maximizes biochemical reaction rates. At lower densities, proteins collide too rarely. At higher densities, proteins diffuse too slowly through the crowded cell. What limits cell sizes and growth rates? Cell growth is limited by rates of protein synthesis, by the folding rates of its slowest proteins, and—for large cells—by the rates of its protein diffusion. Useful insights into cell physics may be obtainable from scaling laws that encapsulate information from protein knowledge bases.

Significance: mAbs are increasingly being used for treatment of chronic diseases wherein the subcutaneous delivery route is preferred to enable self-administration and at-home use. To deliver high doses (several hundred milligrams) through a small volume (∼1 mL) into the subcutaneous space, mAb solutions need to have low viscosity. Concomitantly, acceptable chemical stability is required for adequate shelf life, and normal in vivo clearance is needed for less frequent dosing. We propose in silico tools that provide rapid assessment of atypical behavior of mAbs (high viscosity, chemical degradation, and fast plasma clearance), which are simply predicted from sequence and/or structure-derived parameters. Such analysis will greatly improve the probability of success to move mAb-based therapeutics efficiently into clinical development and ultimately benefit patients.

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell’s fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions. Significance Bacterial cells are remarkable machines. When food is present, bacteria shift gears into a fast-growth mode, whereby they duplicate all their proteins quickly. Cells do this by producing proportionately more ribosomes relative to other proteins. Ribosomes are the 55-protein complexes that a cell makes to synthesize all the cells proteins. Here, we develop a mathematical model of the mechanism of the cell’s gear-shifting and energy utilization under different growth conditions. A major conclusion from this modeling is that we can understand an evolutionary choice made by bacteria. We find that fast growing cells operate close to their optimal energy efficiency, which is a balance between the rates of translation and turnover of proteins and ribosomal assembly.

Significance: Cells and organisms grow old and die. We develop a biophysical model of the mechanism. Young cells are kept healthy by the positive processes of protein synthesis, degradation, and chaperoning (the activity of keeping proteins properly folded). But, with age, negative processes increase: Oxidative damage accumulates randomly in the cell’s proteins, healthy synthesis and degradation slow down, and—like overfilled garbage cans—chaperone capacity is exceeded. The chaperones are distracted trying to fold irreversibly damaged proteins, leading to accumulating misfolded and aggregated proteins in the cell. The tipping point to death happens when the negative overwhelms the positive. The model makes several quantitative predictions of the life span of the worm Caenorhabditis elegans .