Side chain burial and hydrophobic core packing in protein folding transition states

A critical step in the folding pathway of globular proteins is the formation of a tightly packed hydrophobic core. Several mutational studies have addressed the question of whether tight packing interactions are present during the rate-limiting step of folding. In some of these investigations, substituted side chains have been assumed to form native-like interactions in the transition state when the folding rates of mutant proteins correlate with their native-state stabilities. Alternatively, it has been argued that side chains participate in nonspecific hydrophobic collapse when the folding rates of mutant proteins correlate with side-chain hydrophobicity. In a reanalysis of published data, we have found that folding rates often correlate similarly well, or poorly, with both native-state stability and side-chain hydrophobicity, and it is therefore not possible to select an appropriate transition state model based on these one-parameter correlations. We show that this ambiguity can be resolved using a two-parameter model in which side chain burial and the formation of all other native-like interactions can occur asynchronously. Notably, the model agrees well with experimental data, even for positions where the one-parameter correlations are poor. We find that many side chains experience a previously unrecognized type of transition state environment in which specific, native-like interactions are formed, but hydrophobic burial dominates. Implications of these results to the design and analysis of protein folding studies are discussed.     

How do side chains orient globally in protein structures?

An angle Omega is defined to serve as a metric for global side-chain orientations, which reflects the orientation of the side chain relative to the radial vector from the center of the protein to an amino acid. The side-chain orientations of buried residues exhibit characteristically different orientations than do exposed residues, in both monomeric and dimeric structures. Overall, buried side chains point mostly inward, whereas surface side chains tend to point outward from the surface. This difference in behavior also correlates well with the residue hydrophobicity; so a global side-chain orientation can be viewed as a direct structural manifestation of hydrophobicity. When various solvent-accessible layers are considered, the behavior is relatively continuous between centrally located and exposed residues. In the case of interfacial residues between subunits, there are statistically significant differences between exposed residues and interface residues for ALA, ARG, ASN, ASP, GLU, HIS, LYS, THR, VAL, MET, PRO, and overall the interface residues have an increased tendency to point inward. Presumably, these substantial differences in orientations of side chains may be a manifestation of hydrophobic forces.     

An all-atom structure-based potential for proteins: bridging minimal models with all-atom empirical forcefields

Protein dynamics take place on many time and length scales. Coarse-grained structure-based (Go) models utilize the funneled energy landscape theory of protein folding to provide an understanding of both long time and long length scale dynamics. All-atom empirical forcefields with explicit solvent can elucidate our understanding of short time dynamics with high energetic and structural resolution. Thus, structure-based models with atomic details included can be used to bridge our understanding between these two approaches. We report on the robustness of folding mechanisms in one such all-atom model. Results for the B domain of Protein A, the SH3 domain of C-Src Kinase, and Chymotrypsin Inhibitor 2 are reported. The interplay between side chain packing and backbone folding is explored. We also compare this model to a C(alpha) structure-based model and an all-atom empirical forcefield. Key findings include: (1) backbone collapse is accompanied by partial side chain packing in a cooperative transition and residual side chain packing occurs gradually with decreasing temperature, (2) folding mechanisms are robust to variations of the energetic parameters, (3) protein folding free-energy barriers can be manipulated through parametric modifications, (4) the global folding mechanisms in a C(alpha) model and the all-atom model agree, although differences can be attributed to energetic heterogeneity in the all-atom model, and (5) proline residues have significant effects on folding mechanisms, independent of isomerization effects. Because this structure-based model has atomic resolution, this work lays the foundation for future studies to probe the contributions of specific energetic factors on protein folding and function.     

Sequence determinants of thermodynamic stability in a WW domain—An all‐β‐sheet protein

The stabilities of 66 sequence variants of the human Pin1 WW domain have been determined by equilibrium thermal denaturation experiments. All 34 residues composing the hPin1 WW three‐stranded β‐sheet structure could be replaced one at a time with at least one different natural or non‐natural amino acid residue without leading to an unfolded protein. Alanine substitutions at only four positions within the hPin1 WW domain lead to a partially or completely unfolded protein—in the absence of a physiological ligand. The side chains of these four residues form a conserved, partially solvent‐inaccessible, continuous hydrophobic minicore comprising the N‐ and C‐termini. Ala mutations at five other residues, three of which constitute the ligand binding patch on the concave side of the β‐sheet, significantly destabilize the hPin1 WW domain without leading to an unfolded protein. The remaining mutations affect protein stability only slightly, suggesting that only a small subset of side chain interactions within the hPin1 WW domain are mandatory for acquiring and maintaining a stable, cooperatively folded β‐sheet structure.     

Designing cooperativity into the designed protein Top7

The topology of the designed protein Top7 is not found in natural proteins. Top7 shows signatures of non‐cooperative folding in both experimental studies and computer simulations. In particular, molecular dynamics of coarse‐grained structure‐based models of Top7 show a well‐populated C‐terminal folding‐intermediate. Since most similarly sized globular proteins are cooperative folders, the non‐natural topology of Top7 has been suggested as a reason for its non‐cooperative folding. Here, we computationally examine the folding of Top7 with the intent of making it cooperative. We find that its folding cooperativity can be increased in two ways: (a) Optimization of packing interactions in the N‐terminal half of the protein enables further folding of the C‐terminal intermediate. (b) Reduction in the packing density of the C‐terminal region destabilizes the intermediate. In practice, these strategies are implemented in our Top7 model through modifications to the contact‐map. These modifications do not alter the topology of Top7 but result in cooperative folding. Amino‐acid mutations that mimic these modifications also lead to a significant increase in folding cooperativity. Finally, we devise a method to randomize the sizes of amino‐acids within the same topology, and confirm that the structure of Top7 makes its folding sensitive to packing interactions. In contrast, the ribosomal protein S6, which has secondary structure similar to Top7, has folding which is much less sensitive to packing perturbations. Thus, it should be possible to make a sequence fold cooperatively to the structure of Top7, but to do so its side‐chain packing needs to be carefully designed. Proteins 2014; 82:364–374. © 2013 Wiley Periodicals, Inc.     

Assessment of protein side‐chain conformation prediction methods in different residue environments

Computational prediction of side‐chain conformation is an important component of protein structure prediction. Accurate side‐chain prediction is crucial for practical applications of protein structure models that need atomic‐detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side‐chain prediction methods in reproducing the side‐chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane‐spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side‐chains at protein interfaces and membrane‐spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane‐spanning regions as for modeling monomers. Proteins 2014; 82:1971–1984. © 2014 Wiley Periodicals, Inc.     

Automated electron-density sampling reveals widespread conformational polymorphism in proteins

Although proteins populate large structural ensembles, X-ray diffraction data are traditionally interpreted using a single model. To search for evidence of alternate conformers, we developed a program, Ringer, which systematically samples electron density around the dihedral angles of protein side chains. In a diverse set of 402 structures, Ringer identified weak, nonrandom electron-density features that suggest of the presence of hidden, lowly populated conformations for >18% of uniquely modeled residues. Although these peaks occur at electron-density levels traditionally regarded as noise, statistically significant (P < 10⁻⁵) enrichment of peaks at successive rotameric χ angles validates the assignment of these features as unmodeled conformations. Weak electron density corresponding to alternate rotamers also was detected in an accurate electron density map free of model bias. Ringer analysis of the high-resolution structures of free and peptide-bound calmodulin identified shifts in ensembles and connected the alternate conformations to ligand recognition. These results show that the signal in high-resolution electron density maps extends below the traditional 1 σ cutoff, and crystalline proteins are more polymorphic than current crystallographic models. Ringer provides an objective, systematic method to identify previously undiscovered alternate conformations that can mediate protein folding and function.     

Implications of aromatic–aromatic interactions: From protein structures to peptide models

With increasing structural information on proteins, the opportunity to understand physical forces governing protein folding is also expanding. One of the significant non‐covalent forces between the protein side chains is aromatic–aromatic interactions. Aromatic interactions have been widely exploited and thoroughly investigated in the context of folding, stability, molecular recognition, and self‐assembly processes. Through this review, we discuss the contribution of aromatic interactions to the activity and stability of thermophilic, mesophilic, and psychrophilic proteins. Being hydrophobic, aromatic amino acids tend to reside in the protein hydrophobic interior or transmembrane segments of proteins. In such positions, it can play a diverse role in soluble and membrane proteins, and in α‐helix and β‐sheet stabilization. We also highlight here some excellent investigations made using peptide models and several approaches involving aryl–aryl interactions, as an increasingly popular strategy in protein and peptide engineering. A recent survey described the existence of aromatic clusters (trimer, tetramer, pentamer, and higher order assemblies), revealing the self‐associating property of aryl groups, even in folded protein structures. The application of this self‐assembly of aromatics in the generation of modern bionanomaterials is also discussed.     

Side-chain conformational entropy in protein folding.

An important, but often neglected, contribution to the thermodynamics of protein folding is the loss of entropy that results from restricting the number of accessible side-chain conformers in the native structure. Conformational entropy changes can be found by comparing the number of accessible rotamers in the unfolded and folded states, or by estimating fusion entropies. Comparison of several sets of results using different techniques shows that the mean conformational free energy change (T delta S) is 1 kcal.mol-1 per side chain or 0.5 kcal.mol-1 per bond. Changes in vibrational entropy appear to be negligible compared to the entropy change resulting from the loss of accessible rotamers. Side-chain entropies can help rationalize alpha-helix propensities, predict protein/inhibitor complex structures, and account for the distribution of side chains on the protein surface or interior.     

An analysis of side chain interactions and pair correlations within antiparallel β-sheets: The differences between backbone hydrogen-bonded and non-hydrogen-bonded residue pairs

Cross-strand pair correlations are calculated for residue pairs in antiparallel β-sheet for two cases: pairs whose backbone atoms are hydrogen bonded together (H-bonded site) and pairs which are not (non-H-bonded site). The statistics show that this distinction is important. When glycine is located on the edge of a sheet, it shows a 3:1 preference for the H-bonded site. Thestrongest observed correlations are for pairs of disulfide-bonded cystines, many of which adopt a close-packed conformation with each cystine in a spiral conformation of opposite chirality to its partner. It is likely that these pairs are a signature for the family of small, cystine-rich proteins. Most other strong positive and negative correlations involve charged and polar residues. It appears that electrostatic compatibility is the strongest factor affecting pair correlation. Significant correlations are observed for β- and γ-branched residues inthe non-H-bonded site. An examination of the structures showsa directionality in side chain packing. There is a correlation between (1) the directionality in the packing interactions of non-H-bonded β- and γ-branched residue pairs, (2) the handedness of the observed enantiomers of chiral β-branched side chains, and (3) the handedness of the twist of β-sheet. These findings have implications for the formation of β-sheets during protein folding and the mechanism by which the sheet becomes twisted. © 1995 Wiley-Liss, Inc.     

Prediction and evaluation of side-chain conformations for protein backbone structures

A common approach to protein modeling is to propose a backbone structure based on homology or threading and then to attempt to build side chains onto this backbone. A fast algorithm using the simple criteria of atomic overlap and overall rotamer probability is proposed for this purpose. The method was first tested in the context of exhaustive searches of side chain configuration space in protein cores and was then applied to all side chains in 49 proteins of known structure, using simulated annealing to sample space. The latter procedure obtains the correct rotamer for 57% and the correct χ₁ value for 74% of the 6751 residues in the sample. When low-temperature Monte-Carlo simulations are initiated from the results of the simulated-annealing processes, consensus configurations are obtained which exhibit slightly more accurate predictions. The Monte-Carlo procedure also allows converged side chain entropies to be calculated for all residues. These prove to be accurate indicators of prediction reliability. For example, the correct rotamer is obtained for 79% and the correct χ₁ value is obtained for 84% of the half of the sample residues exhibiting the lowest entropies. Side chain entropy and predictability are nearly completely uncorrelated with solvent-accessible area. Some precedents for and implications of this observation are discussed. © 1996 Wiley-Liss, Inc.     

Protein side chain conformation predictions with an MMGBSA energy function

The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an “MMGBSA” energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803–819. © 2016 Wiley Periodicals, Inc.     

Statistical and conformational analysis of the electron density of protein side chains

Protein side chains make most of the specific contacts between proteins and other molecules, and their conformational properties have been studied for many years. These properties have been analyzed primarily in the form of rotamer libraries, which cluster the observed conformations into groups and provide frequencies and average dihedral angles for these groups. In recent years, these libraries have improved with higher resolution structures and using various criteria such as high thermal factors to eliminate side chains that may be misplaced within the crystallographic model coordinates. Many of these side chains have highly non-rotameric dihedral angles. The origin of side chains with high B-factors and/or with non-rotameric dihedral angles is of interest in the determination of protein structures and in assessing the prediction of side chain conformations. In this paper, using a statistical analysis of the electron density of a large set of proteins, it is shown that: (1) most non-rotameric side chains have low electron density compared to rotameric side chains; (2) up to 15% of chi1 non-rotameric side chains in PDB models can clearly be fit to density at a single rotameric conformation and in some cases multiple rotameric conformations; (3) a further 47% of non-rotameric side chains have highly dispersed electron density, indicating potentially interconverting rotameric conformations; (4) the entropy of these side chains is close to that of side chains annotated as having more than one chi(1) rotamer in the crystallographic model; (5) many rotameric side chains with high entropy clearly show multiple conformations that are not annotated in the crystallographic model. These results indicate that modeling of side chains alternating between rotamers in the electron density is important and needs further improvement, both in structure determination and in structure prediction.     

Backbone dependency further improves side chain prediction efficiency in the Energy‐based Conformer Library (bEBL)

Side chain optimization is an integral component of many protein modeling applications. In these applications, the conformational freedom of the side chains is often explored using libraries of discrete, frequently occurring conformations. Because side chain optimization can pose a computationally intensive combinatorial problem, the nature of these conformer libraries is important for ensuring efficiency and accuracy in side chain prediction. We have previously developed an innovative method to create a conformer library with enhanced performance. The Energy‐based Library (EBL) was obtained by analyzing the energetic interactions between conformers and a large number of natural protein environments from crystal structures. This process guided the selection of conformers with the highest propensity to fit into spaces that should accommodate a side chain. Because the method requires a large crystallographic data‐set, the EBL was created in a backbone‐independent fashion. However, it is well established that side chain conformation is strongly dependent on the local backbone geometry, and that backbone‐dependent libraries are more efficient in side chain optimization. Here we present the backbone‐dependent EBL (bEBL), whose conformers are independently sorted for each populated region of Ramachandran space. The resulting library closely mirrors the local backbone‐dependent distribution of side chain conformation. Compared to the EBL, we demonstrate that the bEBL uses fewer conformers to produce similar side chain prediction outcomes, thus further improving performance with respect to the already efficient backbone‐independent version of the library. Proteins 2014; 82:3177–3187. © 2014 Wiley Periodicals, Inc.     

Sequence–function relationships in folding upon binding

Folding coupled to binding is ubiquitous in biology. Nevertheless, the relationship of sequence to function for protein segments that undergo coupled binding and folding remains to be determined. Specifically, it is not known if the well-established rules that govern protein folding and stability are relevant to ligand-linked folding transitions. Upon small ligand biotinoyl-5′-AMP (bio-5′-AMP) binding the Escherichia coli protein BirA undergoes a disorder-to-order transition that results in formation of a network of packed hydrophobic side chains. Ligand binding is also allosterically coupled to protein association, with bio-5′-AMP binding enhancing the dimerization free energy by −4.0 kcal/mol. Previous studies indicated that single alanine replacements in a three residue hydrophobic cluster that contributes to the larger network disrupt cluster formation, ligand binding, and allosteric activation of protein association. In this work, combined equilibrium and kinetic measurements of BirA variants with alanine substitutions in the entire hydrophobic network reveal large functional perturbations resulting from any single substitution and highly non-additive effects of multiple substitutions. These substitutions also disrupt ligand-linked folding. The combined results suggest that, analogous to protein folding, functional disorder-to-order linked to binding requires optimal packing of the relevant hydrophobic side chains that contribute to the transition. The potential for many combinations of residues to satisfy this requirement implies that, although functionally important, segments of homologous proteins that undergo folding linked to binding can exhibit sequence divergence.     

Side‐Chain Engineering for Fine‐Tuning of Energy Levels and Nanoscale Morphology in Polymer Solar Cells

A series of four polymers containing benzo[1,2‐b:4,5‐b′]dithiophene (BDT) and 5,6‐difluoro‐4,7‐diiodobenzo[c][1,2,5]thiadiazole (2FBT), PBDT2FBT, PBDT2FBT‐O, PBDT2FBT‐T, and PBDT2FBT‐T‐O, are synthesized with their four different side chains, alkyl‐, alkoxy‐, alkylthienyl‐, and alkoxythienyl. Experimental results and theoretical calculations show that the molecular tuning of the side chains simultaneously influences the solubilities, energy levels, light absorption, surface tension, and intermolecular packing of the resulting polymers by altering their molecular coplanarity and electron affinity. The polymer solar cell (PSC) based on a blend of PBDT2FBT‐T/[6,6]‐phenyl‐C₇₁‐butyric acid methyl ester (PC₇₁BM) exhibits the best photovoltaic performance of the four PBDT2FBT derivatives, with a high open‐circuit voltage of 0.98 V and a power conversion efficiency of 6.37%, without any processing additives, post‐treatments, or optical spacers. Furthermore, PBDT2FBT‐T‐O, which has a novel side chain alkoxythienyl, showed promising properties with the most red‐shifted absorption and strong intermolecular packing property in solid state. This study provides insight into molecular design and fabrication strategies via structural tuning of the side chains of conjugated polymers for achieving highly efficient PSCs.     

Minimal ensembles of side chain conformers for modeling protein–protein interactions

The goal of this article is to reduce the complexity of the side chain search within docking problems. We apply six methods of generating side chain conformers to unbound protein structures and determine their ability of obtaining the bound conformation in small ensembles of conformers. Methods are evaluated in terms of the positions of side chain end groups. Results for 68 protein complexes yield two important observations. First, the end‐group positions change less than 1 Å on association for over 60% of interface side chains. Thus, the unbound protein structure carries substantial information about the side chains in the bound state, and the inclusion of the unbound conformation into the ensemble of conformers is very beneficial. Second, considering each surface side chain separately in its protein environment, small ensembles of low‐energy states include the bound conformation for a large fraction of side chains. In particular, the ensemble consisting of the unbound conformation and the two highest probability predicted conformers includes the bound conformer with an accuracy of 1 Å for 78% of interface side chains. As more than 60% of the interface side chains have only one conformer and many others only a few, these ensembles of low‐energy states substantially reduce the complexity of side chain search in docking problems. This approach was already used for finding pockets in protein–protein interfaces that can bind small molecules to potentially disrupt protein–protein interactions. Side‐chain search with the reduced search space will also be incorporated into protein docking algorithms. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Glycoprotein folding in the endoplasmic reticulum: a tale of three chaperones?

The endoplasmic reticulum (ER) is a major site of protein synthesis and its inside, or lumen, is a major site of protein folding. The lumen of the ER contains many folding factors and molecular chaperones, which facilitate protein folding by increasing both the rate and the efficiency of this process. Amongst the many ER folding factors, there are three components that specifically modulate the folding glycoproteins bearing N-linked carbohydrate side chains. These components are calnexin, calreticulin and ERp57, and this review focuses on the molecular basis for their capacity to influence glycoprotein folding.     

Molprobity's ultimate rotamer‐library distributions for model validation

Here we describe the updated MolProbity rotamer‐library distributions derived from an order‐of‐magnitude larger and more stringently quality‐filtered dataset of about 8000 (vs. 500) protein chains, and we explain the resulting changes and improvements to model validation as seen by users. To include only side‐chains with satisfactory justification for their given conformation, we added residue‐specific filters for electron‐density value and model‐to‐density fit. The combined new protocol retains a million residues of data, while cleaning up false‐positive noise in the multi‐ datapoint distributions. It enables unambiguous characterization of conformational clusters nearly 1000‐fold less frequent than the most common ones. We describe examples of local interactions that favor these rare conformations, including the role of authentic covalent bond‐angle deviations in enabling presumably strained side‐chain conformations. Further, along with favored and outlier, an allowed category (0.3–2.0% occurrence in reference data) has been added, analogous to Ramachandran validation categories. The new rotamer distributions are used for current rotamer validation in MolProbity and PHENIX, and for rotamer choice in PHENIX model‐building and refinement. The multi‐dimensional distributions and Top8000 reference dataset are freely available on GitHub. These rotamers are termed “ultimate” because data sampling and quality are now fully adequate for this task, and also because we believe the future of conformational validation should integrate side‐chain with backbone criteria. Proteins 2016; 84:1177–1189. © 2016 Wiley Periodicals, Inc.