Peter G. Wolynes

This chapter reviews one particular class of useful coarse-grained protein models that has been developed over the last 25 years in the laboratories. The contemporary form of the resulting protein energy function is called the associative memory, water mediated, structure and energy model (AWSEM). The chapter elaborates on the details of the AWSEM potential and describes the parameter optimization strategy that follows from energy landscape theory. It discusses a number of applications of AWSEM to predicting the folding of globular proteins, and also to predicting mechanisms of protein association and formation of protein-Deoxyribo Nucleic Acid (DNA) complexes, such as nucleosomes. The chapter briefly reviews protein folding theory, clarifying how various fundamental ideas from the theories of spin glasses and polymer physics underlie the folding process. It discusses a series of coarse-grained protein force fields that have been used for predicting protein structure from amino-acid sequences either with or without knowledge about homologous proteins.

Spontaneous directed motion, a hallmark of cell biology, is unusual in classical statistical physics. Here we study, using both numerical and analytical methods, organized motion in models of the cytoskeleton in which constituents are driven by energy-consuming motors. Although systems driven by small-step motors are described by an effective temperature and are thus quiescent, at higher order in step size, both homogeneous and inhomogeneous, flowing and oscillating behavior emerges. Motors that respond with a negative susceptibility to imposed forces lead to an apparent negative-temperature system in which beautiful structures form resembling the asters seen in cell division.

Proteins have often evolved sequences so as to acquire the ability for regulation via allosteric conformational change. Here we investigate how allosteric dynamics is designed through sequences with nonlinear interaction features. First, for 71 allosteric proteins of which two, open and closed, structures are available, a statistical survey of interactions using an all-atom model with effective solvation shows that those residue contact interactions specific to one of the two states are significantly weaker than are the contact interactions shared by the two states. This interaction feature indicates there is underlying sequence design to facilitate conformational change. Second, based on the energy landscape theory, we implement these interaction features into a new atomic-interaction-based coarse-grained model via a multiscale simulation protocol (AICG). The AICG model outperforms standard coarse-grained models for predictions of the native-state mean fluctuations and of the conformational change direction. Third, using the new model for adenylate kinase, we show that intrinsic fluctuations in one state contain rare and large-amplitude motions nearly reaching the other state. Such large-amplitude motions are realized partly by sequence specificity and partly by the nonlinear nature of contact interactions, leading to cracking. Both features enhance conformational transition rates.

Natural protein domains must be sufficiently stable to fold but often need to be locally unstable to function. Overall, strong energetic conflicts are minimized in native states satisfying the principle of minimal frustration. Local violations of this principle open up possibilities to form the complex multifunnel energy landscapes needed for large-scale conformational changes. We survey the local frustration patterns of allosteric domains and show that the regions that reconfigure are often enriched in patches of highly frustrated interactions, consistent both with the idea that these locally frustrated regions may act as specific hinges or that proteins may “crack” in these locations. On the other hand, the symmetry of multimeric protein assemblies allows near degeneracy by reconfiguring while maintaining minimally frustrated interactions. We also anecdotally examine some specific examples of complex conformational changes and speculate on the role of frustration in the kinetics of allosteric change.

In recent years it has become widely accepted that a dynamical length scale {\xi}_{\alpha} plays an important role in supercooled liquids near the glass transition. We examine the implications of the interplay between the growing {\xi}_{\alpha} and the size of the crystal nucleus, {\xi}_M, which shrinks on cooling. We argue that at low temperatures where {\xi}_{\alpha} > {\xi}_M a new crystallization mechanism emerges enabling rapid development of a large scale web of sparsely connected crystallinity. Though we predict this web percolates the system at too low a temperature to be easily seen in the laboratory, there are noticeable residual effects near the glass transition that can account for several previously observed unexplained phenomena of deeply supercooled liquids including Fischer clusters, and anomalous crystal growth near T_g.

Recent studies suggest that there are many nonfunctional transcription factor binding sites along a genome. Although these “decoy” sites compete with the promoter region for binding of transcription factors, they may also protect these proteins from degradation. We show that in the limit of perfect protection, where bound transcription factors are never degraded, the competitive effect of nonfunctional binding sites is completely canceled out by the stability gained from reduced degradation. We examine the response of an autoregulated gene to the total number of transcription factors to quantify the consequences of competition for transcription factors. We show that intuition about this system can be gained by mathematically constructing a single gene with effective parameters that reproduce the behavior of a gene with added decoy sites. In analogy to dressed particles in many-body systems we term this description a “quasi gene.” We find that protective decoys buffer against noise by reducing correlations between transcription factors, specifically in the case of production of transcription factors in bursts. We show that the addition of protective decoy sites causes the level of gene expression to approach that predicted from deterministic mass action models. Finally, we show that protective decoy sites decrease the size of the region of parameter space that exhibits bistability.

The covalently bound heme cofactor plays a dominant role in the folding of cytochrome c. Because of the complicated inorganic chemistry of the heme, some might consider the folding of cytochrome c to be a special case, following principles different from those used to describe the folding of proteins without cofactors. Recent investigations, however, demonstrate that common models describing folding for many proteins work well for cytochrome c when heme is explicitly introduced, generally providing results that agree with experimental observations. In this Account, we first discuss results from simple native structure-based models. These models include attractive interactions between nonadjacent residues only if they are present in the crystal structure at pH 7. Because attractive nonnative contacts are not included in native structure-based models, their energy landscapes can be described as “perfectly funneled”. In other words, native structure-based models are energetically guided towards the native state and contain no energetic traps that would hinder folding. Energetic traps are denoted sources of “frustration”, which cause specific transient intermediates to be populated. Native structure-based models do, however, include repulsion between residues due to excluded volume. Nonenergetic traps can therefore exist if the chain, which cannot cross over itself, must partially unfold so that folding can proceed. The ability of native structure-based models to capture this kind of motion is partly responsible for their successful predictions of folding pathways for many types of proteins. Models without frustration describe the sequence of folding events for cytochrome c well (as inferred from hydrogen-exchange experiments), thereby justifying their use as a starting point. At low pH, the experimentally observed folding sequence of cytochrome c deviates from that at pH 7 and from models with perfectly funneled energy landscapes. Here, alternate folding pathways are a result of “chemical frustration”. This frustration arises because some regions of the protein are destabilized more than others due to the heterogeneous distribution of titratable residues that are protonated at low pH. Beginning with native structure-based terms, we construct more complex models by adding chemical frustration. These more complex models only modestly perturb the energy landscape, which remains, overall, well funneled. These perturbed models can accurately describe how alternative folding pathways are used at low pH. At alkaline pH, cytochrome c populates distinctly different structural ensembles. For instance, lysine residues are deprotonated and compete for the heme ligation site. The same models that can describe folding at low pH also predict well the structures and relative stabilities of intermediates populated at alkaline pH. The success of models based on funneled energy landscapes suggest that cytochrome c folding is driven primarily by native contacts. The presence of heme appears to add chemical complexity to the folding process, but it does not require fundamental modification of the general principles used to describe folding. Moreover, its added complexity provides a valuable means of probing the folding energy landscape in greater detail than is possible with simpler systems.

Biomolecular folding and function are often coupled. During molecular recognition events, one of the binding partners may transiently or partially unfold, allowing more rapid access to a binding site. We describe a simple model for this fly-casting mechanism based on the capillarity approximation and polymer chain statistics. The model shows that fly casting is most effective when the protein unfolding barrier is small and the part of the chain which extends toward the target is relatively rigid. These features are often seen in known examples of fly casting in protein–DNA binding. Simulations of protein–DNA binding based on well-funneled native-topology models with electrostatic forces confirm the trends of the analytical theory.

Biomolecular folding and function are often coupled. During molecular recognition events, one of the binding partners may transiently or partially unfold, allowing more rapid access to a binding site. We describe a simple model for this flycasting mechanism based on the capillarity approximation and polymer chain statistics. The model shows that flycasting is most effective when the protein unfolding barrier is small and the part of the chain which extends towards the target is relatively rigid. These features are often seen in known examples of flycasting in protein-DNA binding. Simulations of protein-DNA binding based on well-funneled native-topology models with electrostatic forces confirm the trends of the analytical theory.