The Associative memory, Water mediated, Structure and Energy Model (AWSEM) is a coarse-grained protein force field. AWSEM contains physically motivated terms, such as hydrogen bonding, as well as a bioinformatically based local structure biasing term, which efficiently takes into account many-body effects that are modulated by the local sequence. When combined with appropriate local or global alignments to choose memories, AWSEM can be used to perform de novo protein structure prediction. Herein we present structure prediction results for a particular choice of local sequence alignment method based on short residue sequences called fragments. We demonstrate the model’s structure prediction capabilities for three levels of global homology between the target sequence and those proteins used for local structure biasing, all of which assume that the structure of the target sequence is not known. When there are no homologs in the database of structures used for local structure biasing, AWSEM calculations produce structural predictions that are somewhat improved compared with prior works using related approaches. The inclusion of a small number of structures from homologous sequences improves structure prediction only marginally but when the fragment search is restricted to only homologous sequences, AWSEM can perform high resolution structure prediction and can be used for kinetics and dynamics studies.

A predictive coarse-grained protein force field [associative memory, water-mediated, structure, and energy model for molecular dynamics (AWSEM)-MD] is used to study the energy landscapes and relative stabilities of amyloid-β protein in the monomer and all of its oligomeric forms up to an octamer. We find that an isolated monomer is mainly disordered with a short α-helix formed at the central hydrophobic core region (L17-D23). A less stable hairpin structure, however, becomes increasingly more stable in oligomers, where hydrogen bonds can form between neighboring monomers. We explore the structure and stability of both prefibrillar oligomers that consist of mainly antiparallel β-sheets and fibrillar oligomers with only parallel β-sheets. Prefibrillar oligomers are polymorphic but typically take on a cylindrin-like shape composed of mostly antiparallel β-strands. At the concentration of the simulation, the aggregation free energy landscape is nearly downhill. We use umbrella sampling along a structural progress coordinate for interconversion between prefibrillar and fibrillar forms to identify a conversion pathway between these forms. The fibrillar oligomer only becomes favored over its prefibrillar counterpart in the pentamer where an interconversion bottleneck appears. The structural characterization of the pathway along with statistical mechanical perturbation theory allow us to evaluate the effects of concentration on the free energy landscape of aggregation as well as the effects of the Dutch and Arctic mutations associated with early onset of Alzheimer's disease.misfolding | amyloid funnel | nucleation A lzheimer's disease is associated with the deposition of amyloid-β (Aβ) protein aggregates in the brain (1). Soluble Aβ oligomers, intermediates formed early in the aggregation process, can cause synaptic dysfunction, whereas the later-formed insoluble fibrils may function as reservoirs of the toxic oligomers (2). Owing to their stoichiometric complexity and transience, the early oligomeric forms are difficult to study in the laboratory. Nevertheless, distinct forms of oligomers, described as prefibrillar and fibrillar, have been found to bind differently to conformation-dependent antibodies (3): the fibrillar oligomers and mature fibrils both display a common epitope that is absent from the prefibrillar oligomers. The study of the secondary structure of Aβ species using Fourier transform infrared spectroscopy suggests that fibrillar forms of Aβ are organized in a parallel β-sheet conformation, much like in the complete fibril structure constructed from solid-state NMR data by Petkova et al. (4), whereas the prefibrillar oligomers contain mainly antiparallel β-sheets (5). Numerous computer simulation studies of both the monomer and higher aggregates using models ranging in complexity from fully atomistic simulations in solvent to lattice models have been undertaken to fill the knowledge gap (6-8). It remains, however, unclear what the exact tertiary arrangements of the β-sheets in the Aβ prefibrillar oligome...

The Nuclear Pore Complex (NPC, ~50 MDa) is the sole passageway for the transport of macromolecules across the nuclear envelope. The NPC plays a key role in numerous critical cellular processes such as transcription, and many of its components are implicated in human diseases such as cancer. Previous work (ref 1, 2) defined the relative positions of its 456 constituent proteins (nucleoporin or Nups), based on spatial restraints derived from biophysical, electron microscopy, and proteomic data. Further elucidation of the evolutionary origin, transport mechanism, and assembly of the NPC will require higher resolution information. As part of an effort to improve upon the resolution and accuracy of the NPC structure, we set out to determine the atomic structures of the NPC components. Because it proved difficult to determine the atomic structures of whole Nups by X-ray crystallography alone, we are relying on multiple datasets that are combined computationally by our Integrative Modeling Platform (IMP) package (http://salilab.org/imp). In particular, we developed an integrative modeling approach that benefits from crystallographic structures of fragments of the protein or its homologs, Solution Small Angle X-ray Scattering (SAXS) profiles of the protein and its fragments (ref 3), NMR, and negative stain Electron Microscopy (EM) micrographs of the protein. Each dataset is converted into a set of spatial restraints on the protein structure, followed by finding a model that satisfies the restraints as well as possible using a Monte Carlo / molecular dynamics optimization procedure. The approach will be illustrated by its application to yeast Nup133.

Replica exchange (RE) is a generalized ensemble simulation method for accelerating the exploration of free-energy landscapes, which define many challenging problems in computational biophysics, including protein folding and binding. Although temperature RE (T-RE) is a parallel simulation technique whose implementation is relatively straightforward, kinetics and the approach to equilibrium in the T-RE ensemble are very complicated; there is much to learn about how to best employ T-RE to protein folding and binding problems. We have constructed a kinetic network model for RE studies of protein folding and used this reduced model to carry out ''simulations of simulations'' to analyze how the underlying temperature dependence of the conformational kinetics and the basic parameters of RE (e.g., the number of replicas, the RE rate, and the temperature spacing) all interact to affect the number of folding transitions observed. When protein folding follows anti-Arrhenius kinetics, we observe a speed limit for the number of folding transitions observed at the low temperature of interest, which depends on the maximum of the harmonic mean of the folding and unfolding transition rates at high temperature. The results shown here for the network RE model suggest ways to improve atomic-level RE simulations such as the use of ''training'' simulations to explore some aspects of the temperature dependence for folding of the atomic-level models before performing RE studies.anti-Arrhenius ͉ Markov process ͉ parallel tempering O ne of the key challenges in the computer simulation of proteins at the atomic level is the sampling of conformational space. The efficiency of many common sampling protocols, such as Monte Carlo (MC) and molecular dynamics (MD), is limited by the need to cross high free-energy barriers between conformational states and rugged energy landscapes. One class of methods for studying equilibrium properties of quasi-ergodic systems that has received a great deal of recent attention is based on the replica exchange (RE) algorithm (1, 2) (also known as parallel tempering). To accomplish barrier crossings, RE methods simulate a series of replicas over a range of temperatures. Periodically, coordinates are exchanged by using a Metropolis criterion (3) that ensures that at any given temperature a canonical distribution is realized. RE methods, particularly REMD (4), have become very popular for the study of protein biophysics, including peptide and protein folding (5, 6), aggregation (7-9), and protein-ligand interactions (10, 11). Previous studies of protein folding appear to show a significant increase in the number of reversible folding events in REMD simulations versus conventional MD (12,13). Given the wide use of REMD, a better understanding of the RE algorithm and how it can be used most effectively for the study of protein folding and binding is of considerable interest.The effectiveness of RE methods is determined by the number of temperatures (replicas) that are simulated, their range and spacing, the rate at ...

We investigate protein-protein association using the associativememory, water-mediated, structure, and energy model (AWSEM), a coarse-grained protein folding model that has been optimized using energy-landscape theory. The potential was originally parameterized by enforcing a funneled nature for a database of dimeric interfaces but was later further optimized to create funneled folding landscapes for individual monomeric proteins. The ability of the model to predict interfaces was not tested previously. The present results show that simulated annealing of the model indeed is able to predict successfully the native interfaces of eight homodimers and four heterodimers, thus amounting to a flexible docking algorithm. We go on to address the relative importance of monomer geometry, flexibility, and nonnative intermonomeric contacts in the association process for the homodimers. Monomer surface geometry is found to be important in determining the binding interface, but it is insufficient. Using a uniform binding potential rather than the water-mediated potential results in sampling of misbound structures that are geometrically preferred but are nonetheless energetically disfavored by AWSEM, as well as in nature. Depending on the stability of the unbound monomers, nonnative contacts play different roles in the association process. For unstable monomers, thermodynamic states stabilized by nonnative interactions correspond to productive, on-pathway intermediates and can, therefore, catalyze binding through a fly-casting mechanism. For stable monomers, in contrast, states stabilized by nonnative interactions generally correspond to traps that impede binding.binding interface prediction | swapped contacts P rotein-protein interfaces encode information that is key to a molecular understanding of biological functions. The folding of proteins is well understood in the framework of energy landscape theory and its principle of minimal frustration. Are binding landscapes also funneled? Mechanistic consequences of funneled binding landscapes have been investigated using structure-based models (1-5). The agreement of these mechanisms with observation suggests that binding landscapes are generally funneled, explaining why topology is indeed a major factor in determining binding mechanisms (1). A statistical analysis of a large database of protein complexes revealed that for many of the complexes, the binding energy gap is indeed larger than expected knowing the variance of the binding energy (6), the hallmark feature of a funneled landscape (7). When further testing this idea, Papoian et al. discovered that for other complexes, to have a funneled landscape for binding, unanticipated water-mediated interactions were required. They developed a water-mediated potential encoding these interactions (8). This transferable potential was later optimized to create funneled folding landscapes that successfully predict the structure of monomeric proteins (9, 10). Therefore, there is considerable support for the idea that, like folding landsc...

Frustration from strong interdomain interactions can make misfolding a more severe problem in multidomain proteins than in singledomain proteins. On the basis of bioinformatic surveys, it has been suggested that lowering the sequence identity between neighboring domains is one of nature's solutions to the multidomain misfolding problem. We investigate folding of multidomain proteins using the associative-memory, water-mediated, structure and energy model (AWSEM), a predictive coarse-grained protein force field. We find that reducing sequence identity not only decreases the formation of domain-swapped contacts but also decreases the formation of strong self-recognition contacts between β-strands with high hydrophobic content. The ensembles of misfolded structures that result from forming these amyloid-like interactions are energetically disfavored compared with the native state, but entropically favored. Therefore, these ensembles are more stable than the native ensemble under denaturing conditions, such as high temperature. Domainswapped contacts compete with self-recognition contacts in forming various trapped states, and point mutations can shift the balance between the two types of interaction. We predict that multidomain proteins that lack these specific strong interdomain interactions should fold reliably.aggregation | funnel P rotein misfolding and productive protein folding bear a yinyang relationship in the energy landscape theory of biomolecular self-organization (1). Only by comparing the strengths of the forces leading to proper structure to those that might, by chance, stabilize alternative structure can we quantitatively understand how proteins kinetically access their thermodynamically stable ordered states (1). In vivo and at low concentrations in vitro, unfolded small proteins avoid kinetic traps and generally find their way easily to their native state. Nevertheless, diseases caused by the misfolding of several specific proteins plague mankind (2, 3). Despite much effort, the patterns of interactions that allow pathological misfolding remain incompletely understood. Known pathological misfolding entails aggregation of specific proteins and thus the interactions of protein molecules with other copies of themselves. Energy landscape theory provides one natural explanation of this specificity in misfolding through the funneled nature of the monomeric protein energy landscape: Native-like interactions between different protein molecules like those found within a single protein are stronger than alternate nonnative interactions in the same molecule or interactions between peptide sequences chosen at random in the two molecules. Because of this intrinsic self-stickiness of foldable molecules, runaway domain swapping, in which native-like interactions are made between different copies of the same protein, provides a natural mechanism for aggregation (4-7). Indeed, transient protein aggregation during refolding at moderately high concentration does appear to be universal (8). Nevertheless this aggregati...

Genetic switches based on the NF-κB/ IκB/ DNA system are master regulators of an array of cellular responses. Recent kinetic experiments have shown that IκB can actively remove NF-κB bound to its genetic sites via a process called "molecular stripping." This allows the NF-κB/ IκB/ DNA switch to function under kinetic control rather than the thermodynamic control contemplated in the traditional models of gene switches. Using molecular dynamics simulations of coarse-grained predictive energy landscape models for the constituent proteins by themselves and interacting with the DNA we explore the functional motions of the transcription factor NF-κB and its various binary and ternary complexes with DNA and the inhibitor IκB. These studies show that the function of the NF-κB/ IκB/ DNA genetic switch is realized via an allosteric mechanism. Molecular stripping occurs through the activation of a domain twist mode by the binding of IκB that occurs through conformational selection. Free energy calculations for DNA binding show that the binding of IκB not only results in a significant decrease of the affinity of the transcription factor for the DNA but also kinetically speeds DNA release. Projections of the free energy onto various reaction coordinates reveal the structural details of the stripping pathways. T he binding and release of protein transcription factors from DNA are fundamental molecular processes by which genes are regulated in the cell. The pioneering studies of Jacob, Monod, Ptashne, and Gilbert explained how these two processes, seeming inverses of each other, while being maintained in local chemical equilibrium, could still lead to robust genetic switches by coupling to protein synthesis and degradation, which are kinetically controlled far from equilibrium processes (1-4). This classic picture, with the law of mass action at its core (5, 6), suggests that understanding the molecular mechanism of the binding and release of transcription factors is of secondary interest compared with understanding the thermodynamics of protein-DNA recognition. The recent discovery of proteininduced release of a DNA-bound transcription factor in the NF-κB=IκB=DNA genetic switch changes this picture (7). The induced process, called "molecular stripping," opens up the possibility of molecular kinetic control of binding and release, thus overturning the classic paradigm based only on thermodynamic control. In this paper, we use molecular dynamics simulations of coarse-grained but predictive energy landscape models of the proteins along with their interacting DNA to explore first how the NF-κB transcription factor binds individually both to DNA and to its inhibitor IκB and then to study how an approaching IκB can strip the NF-κB from a DNA molecule to which it has already been bound, by forming an intermediate ternary complex. These simulations show that each of the binary binding events involves conformational selection of different NF-κB global conformations. Molecular stripping then occurs that is induced by forming the ternar...

Using a predictive coarse-grained protein force field, we compute and compare the free energy landscapes and relative stabilities of amyloid-β protein (1-42) and amyloid-β protein (1-40) in their monomeric and oligomeric forms up to the octamer. At the same concentration, the aggregation free energy profile of Aβ42 is more downhill, with a computed solubility that is about ten times smaller than that of Aβ40. At a concentration of 40 μM, the clear free energy barrier between the prefibrillar tetramer form and the fibrillar pentamer in the Aβ40 aggregation landscape disappears for Aβ42, suggesting that the Aβ42 tetramer has a more diverse structural range. To further compare the landcapes, we develop a cluster analysis based on the structural similarity between configurations and use it to construct an oligomerization map that captures the paths of easy interconversion between different but structurally similar states of oligomers for both species. A taxonomy of the oligomer species based on β-sheet stacking topologies is proposed. The comparison of the two oligomerization maps highlights several key differences in the landscapes that can be attributed to the two additional C-terminal residues that Aβ40 lacks. In general, the two terminal residues strongly stabilize the oligomeric structures for Aβ42 relative to Aβ40, and greatly facilitate the conversion from prefibrillar trimers to fibrillar tetramers.