Importance of long-range interactions in protein folding

Long-range interactions play an active role in the stability of protein molecules. In this work, we have analyzed the importance of long-range interactions in different structural classes of globular proteins in terms of residue distances. We found that 85% of residues are involved in long-range contacts. The residues occurring in the range of 4-10 residues apart contribute more towards long-range contacts in all-alpha proteins while the range is 11-20 in all-beta proteins. The hydrophobic residues Cys, Ile and Val prefer the 11-20 range and all other residues prefer the 4-10 range. The residues in all-beta proteins have an average of 3-8 long-range contacts whereas the residues in other classes have 1-4 long-range contracts. Furthermore, the preference of residue pairs to the folding and stability will be discussed.     

Study of the electrostatics treatment in molecular dynamics simulations

This article considers the treatment of long-range interactions in molecular dynamics simulations. We investigate the effects of using different cutoff distances, constant versus distance-dependent dielectric, and different smoothing methods. In contrast to findings of earlier studies, we find that increasing the cutoff over 8 A does not significantly improve the accuracy (Arnold and Ornstein, Proteins 1994;18:19-33), and using a distance-dependent dielectric instead of a constant dielectric also does not improve accuracy (Guenot and Kollman, Protein Sci 1992;1:1185-1205). This might depend on differences in simulation protocols or force fields, or both, because we use the CHARMM22 force field with stochastic boundary conditions, whereas earlier studies used other protocols and energy functions. We also note that the stability of the simulations is highly dependent on the starting structure, showing that accurate molecular simulations not only depend on a realistic simulation protocol but also on correct initial conditions.     

Minimalist representations and the importance of nearest neighbor effects in protein folding simulations

In order to investigate the level of representation required to simulate folding and predict structure, we test the ability of a variety of reduced representations to identify native states in decoy libraries and to recover the native structure given the advanced knowledge of the very broad native Ramachandran basin assignments. Simplifications include the removal of the entire side-chain or the retention of only the Cbeta atoms. Scoring functions are derived from an all-atom statistical potential that distinguishes between atoms and different residue types. Structures are obtained by minimizing the scoring function with a computationally rapid simulated annealing algorithm. Results are compared for simulations in which backbone conformations are sampled from a Protein Data Bank-based backbone rotamer library generated by either ignoring or including a dependence on the identity and conformation of the neighboring residues. Only when the Cbeta atoms and nearest neighbor effects are included do the lowest energy structures generally fall within 4 A of the native backbone root-mean square deviation (RMSD), despite the initial configuration being highly expanded with an average RMSD > or = 10 A. The side-chains are reinserted into the Cbeta models with minimal steric clash. Therefore, the detailed, all-atom information lost in descending to a Cbeta-level representation is recaptured to a large measure using backbone dihedral angle sampling that includes nearest neighbor effects and an appropriate scoring function.     

Rapid boundary element solvation electrostatics calculations in folding simulations: successful folding of a 23-residue peptide.

Solvation effects play a profound role in the energetics of protein folding. While a continuum dielectric model of solvation may provide a sufficiently accurate estimate of the solvation effects, until now this model was too computationally expensive and unstable for folding simulations. Here we proposed a fast yet accurate and robust implementation of the boundary element solution of the Poisson equation, the REBEL algorithm. Using our earlier double-energy scheme, we included for the first time the mathematically rigorous continuous REBEL solvation term in our Biased Probability Monte Carlo (BPMC) simulations of the peptide folding. The free energy of a 23-residue beta beta alpha-peptide was then globally optimized with and without the solvation electrostatics contribution. An ensemble of beta beta alpha conformations was found at and near the global minimum of the energy function with the REBEL electrostatic solvation term. Much poorer correspondence to the native solution structure was found in the "control" simulations with a traditional method to account for solvation via a distance-dependent dielectric constant. Each simulation took less than 40 h (21 h without electrostatic solvation calculation) on a single Alpha 677 MHz CPU and involved more than 40,000 solvation energy evaluations. This work demonstrates for the first time that such a simulation can be performed in a realistic time frame. The proposed procedure may eliminate the energy evaluation accuracy bottleneck in folding simulations.     

Confinement effects on the thermodynamics of protein folding: Monte Carlo simulations

The effects of chaperonin-like cage-induced confinement on protein stability have been studied for molecules of varying sizes and topologies. Minimalist models based on Gō-like interactions are employed for the proteins, and density-of-states-based Monte Carlo simulations are performed to accurately characterize the thermodynamic transitions. This method permits efficient sampling of conformational space and yields precise estimates of free energy and entropic changes associated with protein folding. We find that confinement-driven stabilization is not only dependent on protein size and cage radius, but also on the specific topology. The choice of the confining potential is also shown to have an effect on the observed stabilization and the scaling behavior of the stabilization with respect to the cage size.     

Effect of short- and long-range interactions on protein folding

The relative importance of short- and long-range interactions is examined using a Monte Carlo simulation of protein folding on bovine pancreatic trypsin inhibitor. The model of the protein and the interaction energies were parametrized using X-ray structures of 30 native proteins. A nearest neighbor Ising model is used to determine the conformational state at each stage of the Monte Carlo procedure. Long-range interactions are simulated by contact free energies which become effective as two residues, separated by four or more residues along the chain, approach each other, and by disulfide-bond energies. Short-range interactions for residues separated by one, two, or three residues along the chain are also modeled by contact free energies and by -helical hydrogen bonds. A hard-sphere model is used to represent repulsive interactions. The ratios of short- to long-range interactions studied are 1:1, 2:1, 1:2, 0:1, and 1:0; e.g., for the 2:1 ratio, short-range interactions are weighted twice as much as long-range interactions, and for the 1:0 ratio, long-range interactions are omitted. For each ratio of short- to long-range interactions, a native conformation is found by a Monte Carlo procedure, a segment of 11 residues (residue numbers 1–11) is then rotated away from the rest of the molecule [breaking the 5–55 native disulfide bond, and moving this segment so that the distance between the sulfur atoms of the 5 and 55 cystine side chains (averaged for all native conformations) increases from 3.9 to 7.3 Å], and the Monte Carlo simulation is carried out (allowing the conformation of the whole molecule to change) until equilibrium is attained. For each ratio, the refolded conformation is compared to the native one using triangular distance maps and differential geometry distance criteria. With ratios of short- to long-range interaction energies of 1:1 and 0:1, the native disulfide bond could be re-formed; with ratios of 2:1 and 1:2 it did not; and with the 1:0 ratio, even a stable native conformation was not achieved. Therefore, long-range interactions (in addition to short-range ones) are required to bring remote parts of the protein together and to stabilize its native conformation.NIH Postdoctoral Fellow, 1977–1978.     

Atomistic molecular simulations of protein folding

Theory and experiment have provided answers to many of the fundamental questions of protein folding; a remaining challenge is an accurate, high-resolution picture of folding mechanism. Atomistic molecular simulations with explicit solvent are the most promising method for providing this information, by accounting more directly for the physical interactions that stabilize proteins. Although simulations of folding with such force fields are extremely challenging, they have become feasible as a result of recent advances in computational power, accuracy of the energy functions or 'force fields', and methods for improving sampling of folding events. I review the recent progress in these areas, and highlight future challenges and questions that we may hope to address with these methods. I also attempt to place atomistic models into the context of the energy landscape view of protein folding, and coarse-grained simulations.     

Molecular dynamics effects on protein electrostatics

Electrostatic calculations have been carried out on a number of structural conformers of tuna cytochrome c. Conformers were generated using molecular dynamics simulations with a range of solvent simulating, macroscopic dielectric formalisms, and one solvent model that explicitly included solvent water molecules. Structures generated using the lowest dielectric models were relatively tight, with side chains collapsed on the surface, while those from the higher dielectric models had more internal and external fluidity, with surface side chains exploring a fuller range of conformational space. The average structure generated with the explicitly solvated model corresponded most closely with the crystal structure. Individual pK values, overall titration curves, and electrostatic potential surfaces were calculated for average structures and structures along each simulation. Differences between structural conformers within each simulation give rise to substantial changes in calculated local electrostatic interactions, resulting in pK value fluctuations for individual sites in the protein that vary by 0.3-2.0 pK units from the calculated time average. These variations are due to the thermal side chain reorientations that produce fluctuations in charge site separations. Properties like overall titration curves and pH dependent stability are not as sensitive to side chain fluctuations within a simulation, but there are substantial effects between simulations due to marked differences in average side chain behavior. These findings underscore the importance of proper dielectric formalism in molecular dynamics simulations when used to generate alternate solution structures from a crystal structure, and suggest that conformers significantly removed from the average structure have altered electrostatic properties that may prove important in episodic protein properties such as catalysis.     

Potential of genetic algorithms in protein folding and protein engineering simulations.

Genetic algorithms are very efficient search mechanisms which mutate, recombine and select amongst tentative solutions to a problem until a near optimal one is achieved. We introduce them as a new tool to study proteins. The identification and motivation for different fitness functions is discussed. The evolution of the zinc finger sequence motif from a random start is modelled. User specified changes of the lambda repressor structure were simulated and critical sites and exchanges for mutagenesis identified. Vast conformational spaces are efficiently searched as illustrated by the ab initio folding of a model protein of a four beta strand bundle. The genetic algorithm simulation which mimicked important folding constraints as overall hydrophobic packaging and a propensity of the betaphilic residues for trans positions achieved a unique fold. Cooperativity in the beta strand regions and a length of 3-5 for the interconnecting loops was critical. Specific interaction sites were considerably less effective in driving the fold.     

Advances in free-energy-based simulations of protein folding and ligand binding

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All-atom fast protein folding simulations: the villin headpiece

We provide a fast folding simulation using an all-atom solute, implicit solvent method that eliminates the need for treating solvent degrees of freedom. The folding simulations for the 36-residue villin headpiece exhibit close correspondence with the landmark all-atom explicit solvent molecular dynamics simulations by Duan and Kollman (Duan & Kollman, Science 1998;282:740-744; Duan, Wang, & Kollman, Proc Natl Acad Sci USA 1998;95:9897-9902). Our implicit solvent approach uses only an entry-level single CPU PC with comparable throughput ( approximately 4 nsec/day) to the DK supercomputer simulation. The native state is shown to be stable. Our 200-nsec folding trajectory agrees with the DK simulation in displaying a burst phase, a rapid initial shrinkage, a highly native-like binding site structure, and more.     

Computer simulations of membrane protein folding: structure and dynamics

A lattice model of membrane proteins with a composite energy function is proposed to study their folding dynamics and native structures using Monte Carlo simulations. This model successfully predicts the seven helix bundle structure of sensory rhodopsin I by practicing a three-stage folding. Folding dynamics of a transmembrane segment into a helix is further investigated by varying the cooperativity in the formation of alpha helices for both random folding and assisted folding. The chain length dependence of the folding time of a hydrophobic segment to a helical state is studied for both free and anchored chains. An unusual length dependence in the folding time of anchored chains is observed.     

Molecular simulations of cotranslational protein folding: fragment stabilities, folding cooperativity, and trapping in the ribosome

Although molecular simulation methods have yielded valuable insights into mechanistic aspects of protein refolding in vitro, they have up to now not been used to model the folding of proteins as they are actually synthesized by the ribosome. To address this issue, we report here simulation studies of three model proteins: chymotrypsin inhibitor 2 (CI2), barnase, and Semliki forest virus protein (SFVP), and directly compare their folding during ribosome-mediated synthesis with their refolding from random, denatured conformations. To calibrate the methodology, simulations are first compared with in vitro data on the folding stabilities of N-terminal fragments of CI2 and barnase; the simulations reproduce the fact that both the stability and thermal folding cooperativity increase as fragments increase in length. Coupled simulations of synthesis and folding for the same two proteins are then described, showing that both fold essentially post-translationally, with mechanisms effectively identical to those for refolding. In both cases, confinement of the nascent polypeptide chain within the ribosome tunnel does not appear to promote significant formation of native structure during synthesis; there are however clear indications that the formation of structure within the nascent chain is sensitive to location within the ribosome tunnel, being subject to both gain and loss as the chain lengthens. Interestingly, simulations in which CI2 is artificially stabilized show a pronounced tendency to become trapped within the tunnel in partially folded conformations: non-cooperative folding, therefore, appears in the simulations to exert a detrimental effect on the rate at which fully folded conformations are formed. Finally, simulations of the two-domain protease module of SFVP, which experimentally folds cotranslationally, indicate that for multi-domain proteins, ribosome-mediated folding may follow different pathways from those taken during refolding. Taken together, these studies provide a first step toward developing more realistic methods for simulating protein folding as it occurs in vivo.     

Computer simulations of protein folding by targeted molecular dynamics

We have performed 128 folding and 45 unfolding molecular dynamics runs of chymotrypsin inhibitor 2 (CI2) with an implicit solvation model for a total simulation time of 0.4 microseconds. Folding requires that the three-dimensional structure of the native state is known. It was simulated at 300 K by supplementing the force field with a harmonic restraint which acts on the root-mean-square deviation and allows to decrease the distance to the target conformation. High temperature and/or the harmonic restraint were used to induce unfolding. Of the 62 folding simulations started from random conformations, 31 reached the native structure, while the success rate was 83% for the 66 trajectories which began from conformations unfolded by high-temperature dynamics. A funnel-like energy landscape is observed for unfolding at 475 K, while the unfolding runs at 300 K and 375 K as well as most of the folding trajectories have an almost flat energy landscape for conformations with less than about 50% of native contacts formed. The sequence of events, i.e., secondary and tertiary structure formation, is similar in all folding and unfolding simulations, despite the diversity of the pathways. Previous unfolding simulations of CI2 performed with different force fields showed a similar sequence of events. These results suggest that the topology of the native state plays an important role in the folding process.     

Lattice simulations of aggregation funnels for protein folding.

A computer model of protein aggregation competing with productive folding is proposed. Our model adapts techniques from lattice Monte Carlo studies of protein folding to the problem of aggregation. However, rather than starting with a single string of residues, we allow independently folding strings to undergo collisions and consider their interactions in different orientations. We first present some background into the nature and significance of protein aggregation and the use of lattice Monte Carlo simulations in understanding other aspects of protein folding. The results of a series of simulation experiments involving simple versions of the model illustrate the importance of considering aggregation in simulations of protein folding and provide some preliminary understanding of the characteristics of the model. Finally, we discuss the value of the model in general and of our particular design decisions and experiments. We conclude that computer simulation techniques developed to study protein folding can provide insights into protein aggregation, and that a better understanding of aggregation may in turn provide new insights into and constraints on the more general protein folding problem.     

Solvent effects on protein association and protein folding

Solvent effects on the thermodynamics of two processes--folding of proteins and association between proteins--are examined in detail. A complete inventory of the multitude of solvent effects may be obtained by employing the concept of conditional solvation free energy. This theoretical tool allows for the isolation of specific side-chain effects from the entire protein and for the study of its contribution to the overall free energy change in small model compounds. Some numerical examples are presented, and ways of estimating other cases, for which no relevant experimental data are available, are suggested. Our findings lead to the conclusion that the currently used hydrophobicity scales, based on partition coefficients between water and an organic solvent, are inadequate measures of the contribution of side chains being transferred from water to the interior of the protein. We have also tentatively concluded that correlation between hydrophilic functional groups might be more important than correlations between hydrophobic side chains.     

Molecular simulations of mutually exclusive folding in a two-domain protein switch

A major challenge with testing designs of protein conformational switches is the need for experimental probes that can independently monitor their individual protein domains. One way to circumvent this issue is to use a molecular simulation approach in which each domain can be directly observed. Here we report what we believe to be the first molecular simulations of mutually exclusive folding in an engineered two-domain protein switch, providing a direct view of how folding of one protein drives unfolding of the other in a barnase-ubiquitin fusion protein. These simulations successfully capture the experimental effects of interdomain linker length and ligand binding on the extent of unfolding in the less stable domain. In addition, the effect of linker length on the potential for oligomerization, which eliminates switch activity, is in qualitative agreement with analytical ultracentrifugation experiments. We also perform what we believe to be the first study of protein unfolding via progressive localized compression. Finally, we are able to explore the kinetics of mutually exclusive folding by determining the effect of linker length on rates of unfolding and refolding of each protein domain. Our results demonstrate that molecular simulations can provide seemingly novel biological insights on the behavior of individual protein domains, thereby aiding in the rational design of bifunctional switches.     

Accelerating all-atom protein folding simulations through reduced dihedral barriers

Protein folding requires extensive changes of backbone and sidechain dihedral angles, whose energy barriers constitute obstacles for the folding kinetics. Folding of small proteins is furthermore thought to be path-independent. Here, we propose that time-consuming all-atom protein folding simulations may be accelerated through a reduction of the dihedral barriers of the force field. In order to investigate this hypothesis, we performed various folding simulations of two small proteins. We report an acceleration towards smaller root-mean-square deviations from the native protein structure using our proposed method.