Backrub-like backbone simulation recapitulates natural protein conformational variability and improves mutant side-chain prediction

Incorporation of effective backbone sampling into protein simulation and design is an important step in increasing the accuracy of computational protein modeling. Recent analysis of high-resolution crystal structures has suggested a new model, termed backrub, to describe localized, hinge-like alternative backbone and side-chain conformations observed in the crystal lattice. The model involves internal backbone rotations about axes between C-alpha atoms. Based on this observation, we have implemented a backrub-inspired sampling method in the Rosetta structure prediction and design program. We evaluate this model of backbone flexibility using three different tests. First, we show that Rosetta backrub simulations recapitulate the correlation between backbone and side-chain conformations in the high-resolution crystal structures upon which the model was based. As a second test of backrub sampling, we show that backbone flexibility improves the accuracy of predicting point-mutant side-chain conformations over fixed backbone rotameric sampling alone. Finally, we show that backrub sampling of triosephosphate isomerase loop 6 can capture the millisecond/microsecond oscillation between the open and closed states observed in solution. Our results suggest that backrub sampling captures a sizable fraction of localized conformational changes that occur in natural proteins. Application of this simple model of backbone motions may significantly improve both protein design and atomistic simulations of localized protein flexibility.     

RASP: rapid and robust backbone chemical shift assignments from protein structure

Chemical shift prediction has an unappreciated power to guide backbone resonance assignment in cases where protein structure is known. Here we describe Resonance Assignment by chemical Shift Prediction (RASP), a method that exploits this power to derive protein backbone resonance assignments from chemical shift predictions. Robust assignments can be obtained from a minimal set of only the most sensitive triple-resonance experiments, even for spectroscopically challenging proteins. Over a test set of 154 proteins RASP assigns 88 % of residues with an accuracy of 99.7 %, using only information available from HNCO and HNCA spectra. Applied to experimental data from a challenging 34 kDa protein, RASP assigns 90 % of manually assigned residues using only 40 % of the experimental data required for the manual assignment. RASP has the potential to significantly accelerate the backbone assignment process for a wide range of proteins for which structural information is available, including those for which conventional assignment strategies are not feasible.     

1H, 13C and 15N backbone and side-chain chemical shift assignments for oxidized and reduced desulfothioredoxin

Based on sequence homology, desulfothioredoxin (DTrx) from Desulfovibrio vulgaris Hildenborough has been identified as a new member of the thioredoxin superfamily. Desulfothioredoxin (104 amino acids) contains a particular active site consensus sequence, CPHC probably correlated to the anaerobic metabolism of these bacteria. We report the full ¹H, ¹³C and ¹⁵N resonance assignments of the reduced and the oxidized form of desulfothioredoxin (DTrx). 2D and 3D heteronuclear NMR experiments were performed using uniformly ¹⁵N-, ¹³C-labelled DTrx. More than 98% backbone and 96% side-chain ¹H, ¹³C and ¹⁵N resonance assignments were obtained. (BMRB deposits with accession number 16712 and 16713).     

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.     

A simple model of backbone flexibility improves modeling of side-chain conformational variability

The considerable flexibility of side-chains in folded proteins is important for protein stability and function, and may have a role in mediating allosteric interactions. While sampling side-chain degrees of freedom has been an integral part of several successful computational protein design methods, the predictions of these approaches have not been directly compared to experimental measurements of side-chain motional amplitudes. In addition, protein design methods frequently keep the backbone fixed, an approximation that may substantially limit the ability to accurately model side-chain flexibility. Here, we describe a Monte Carlo approach to modeling side-chain conformational variability and validate our method against a large dataset of methyl relaxation order parameters derived from nuclear magnetic resonance (NMR) experiments (17 proteins and a total of 530 data points). We also evaluate a model of backbone flexibility based on Backrub motions, a type of conformational change frequently observed in ultra-high-resolution X-ray structures that accounts for correlated side-chain backbone movements. The fixed-backbone model performs reasonably well with an overall rmsd between computed and predicted side-chain order parameters of 0.26. Notably, including backbone flexibility leads to significant improvements in modeling side-chain order parameters for ten of the 17 proteins in the set. Greater accuracy of the flexible backbone model results from both increases and decreases in side-chain flexibility relative to the fixed-backbone model. This simple flexible-backbone model should be useful for a variety of protein design applications, including improved modeling of protein-protein interactions, design of proteins with desired flexibility or rigidity, and prediction of correlated motions within proteins.     

1H, 13C, and 15N backbone and side-chain chemical shift assignment of the staphylococcal MazF mRNA interferase

MazF proteins are ribonucleases that cleave mRNA with high sequence-specificity as part of bacterial stress response and that are neutralized by the action of the corresponding antitoxin MazE. Prolonged activation of the toxin MazF leads to cell death. Several mazEF modules from Gram-negative bacteria have been characterized in terms of catalytic activity, auto-regulation mechanism and structure, but less is known about their distant relatives found in Gram-positive organisms. Currently, no solution NMR structure is available for any wild-type MazF toxin. Here we report the ¹H, ¹⁵N and ¹³C backbone and side-chain chemical shift assignments of this toxin from the pathogen bacterium Staphylococcus aureus. The BMRB accession number is 17288.     

Assessing side-chain perturbations of the protein backbone: a knowledge-based classification of residue Ramachandran space

Grouping the 20 residues is a classic strategy to discover ordered patterns and insights about the fundamental nature of proteins, their structure, and how they fold. Usually, this categorization is based on the biophysical and/or structural properties of a residue's side-chain group. We extend this approach to understand the effects of side chains on backbone conformation and to perform a knowledge-based classification of amino acids by comparing their backbone phi, psi distributions in different types of secondary structure. At this finer, more specific resolution, torsion angle data are often sparse and discontinuous (especially for nonhelical classes) even though a comprehensive set of protein structures is used. To ensure the precision of Ramachandran plot comparisons, we applied a rigorous Bayesian density estimation method that produces continuous estimates of the backbone phi, psi distributions. Based on this statistical modeling, a robust hierarchical clustering was performed using a divergence score to measure the similarity between plots. There were seven general groups based on the clusters from the complete Ramachandran data: nonpolar/beta-branched (Ile and Val), AsX (Asn and Asp), long (Met, Gln, Arg, Glu, Lys, and Leu), aromatic (Phe, Tyr, His, and Cys), small (Ala and Ser), bulky (Thr and Trp), and, lastly, the singletons of Gly and Pro. At the level of secondary structure (helix, sheet, turn, and coil), these groups remain somewhat consistent, although there are a few significant variations. Besides the expected uniqueness of the Gly and Pro distributions, the nonpolar/beta-branched and AsX clusters were very consistent across all types of secondary structure. Effectively, this consistency across the secondary structure classes implies that side-chain steric effects strongly influence a residue's backbone torsion angle conformation. These results help to explain the plasticity of amino acid substitutions on protein structure and should help in protein design and structure evaluation.     

IRECS: a new algorithm for the selection of most probable ensembles of side-chain conformations in protein models

We introduce a new algorithm, IRECS (Iterative REduction of Conformational Space), for identifying ensembles of most probable side-chain conformations for homology modeling. On the basis of a given rotamer library, IRECS ranks all side-chain rotamers of a protein according to the probability with which each side chain adopts the respective rotamer conformation. This ranking enables the user to select small rotamer sets that are most likely to contain a near-native rotamer for each side chain. IRECS can therefore act as a fast heuristic alternative to the Dead-End-Elimination algorithm (DEE). In contrast to DEE, IRECS allows for the selection of rotamer subsets of arbitrary size, thus being able to define structure ensembles for a protein. We show that the selection of more than one rotamer per side chain is generally meaningful, since the selected rotamers represent the conformational space of flexible side chains. A knowledge-based statistical potential ROTA was constructed for the IRECS algorithm. The potential was optimized to discriminate between side-chain conformations of native and rotameric decoys of protein structures. By restricting the number of rotamers per side chain to one, IRECS can optimize side chains for a single conformation model. The average accuracy of IRECS for the chi1 and chi1+2 dihedral angles amounts to 84.7% and 71.6%, respectively, using a 40 degrees cutoff. When we compared IRECS with SCWRL and SCAP, the performance of IRECS was comparable to that of both methods. IRECS and the ROTA potential are available for download from the URL http://irecs.bioinf.mpi-inf.mpg.de.     

1H, 13C and 15N backbone and side-chain chemical shift assignments for reduced unusual thioredoxin Patrx2 of Pseudomonas aeruginosa

The gram-negative organism Pseudomonas aeruginosa is an opportunistic human pathogen and a leading cause of hospital-acquired infections. In P. aeruginosa PAO1, three cytoplasmic thioredoxins have been identified. An unusual thioredoxin (Patrx2) (108 amino acids) encoded by the PA2694 gene, is identified as a new thioredoxin-like protein based on sequence homology. Thioredoxin is a ubiquitous protein, which serves as a general protein disulfide oxidoreductase. Patrx2 present an atypical active site CGHC. We report the nearly complete ¹H, ¹³C and ¹⁵N resonance assignments of reduced Patrx2. 2D and 3D heteronuclear NMR experiments were performed with uniformly ¹⁵N-, ¹³C-labelled Patrx2, resulting in 97.2 % backbone and 92.5 % side-chain ¹H, ¹³C and ¹⁵N resonance assignments for the reduced form. (BMRB deposits with accession number 18130).     

Site-specific protein backbone and side-chain NMR chemical shift and relaxation analysis of human vinexin SH3 domain using a genetically encoded 15N/19F-labeled unnatural amino acid

SH3 is a ubiquitous domain mediating protein-protein interactions. Recent solution NMR structural studies have shown that a proline-rich peptide is capable of binding to the human vinexin SH3 domain. Here, an orthogonal amber tRNA/tRNA synthetase pair for ¹⁵N/¹⁹F-trifluoromethyl-phenylalanine (¹⁵N/¹⁹F-tfmF) has been applied to achieve site-specific labeling of SH3 at three different sites. One-dimensional solution NMR spectra of backbone amide (¹⁵N)¹H and side-chain ¹⁹F were obtained for SH3 with three different site-specific labels. Site-specific backbone amide (¹⁵N)¹H and side-chain ¹⁹F chemical shift and relaxation analysis of SH3 in the absence or presence of a peptide ligand demonstrated different internal motions upon ligand binding at the three different sites. This site-specific NMR analysis might be very useful for studying large-sized proteins or protein complexes.     

pH dependence of conformational fluctuations of the protein backbone

Proton binding equilibria (pK_a values) of ionizable groups in proteins are exquisitely sensitive to their microenvironments. Apparent pK_a values measured for individual ionizable residues with NMR spectroscopy are actually population‐weighted averages of the pK_a in different conformational microstates. NMR spectroscopy experiments with staphylococcal nuclease were used to test the hypothesis that pK_a values of surface Glu and Asp residues are affected by pH‐sensitive fluctuations of the backbone between folded and locally unfolded conformations. ¹⁵N spin relaxation studies showed that as the pH decreases from the neutral into the acidic range the amplitudes of backbone fluctuations in the ps‐ns timescale increase near carboxylic residues. Hydrogen exchange experiments suggested that backbone conformational fluctuations promoted by decreasing pH also reflect slower local or sub‐global unfolding near carboxylic groups. This study has implications for structure‐based pK_a calculations: (1) The timescale of the backbone's response to ionization events in proteins can range from ps to ms, and even longer; (2) pH‐sensitive fluctuations of the backbone can be localized to both the segment the ionizable residue is attached to or the one that occludes the ionizable group; (3) Structural perturbations are not necessarily propagated through Coulomb interactions; instead, local fluctuations appear to be coupled through the co‐operativity inherent to elements of secondary structure and to networks of hydrogen bonds. These results are consistent with the idea that local conformational fluctuations and stabilities are important determinants of apparent pK_a values of ionizable residues in proteins. Proteins 2014; 82:3132–3143. © 2014 Wiley Periodicals, Inc.     

SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2

The unprecedented performance of Deepmind’s Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes and protein sequence repositories is reshaping structural biology. However, because this database returns a single structure, it brought into question Alphafold’s ability to capture the intrinsic conformational flexibility of proteins. Here we present a general approach to drive Alphafold2 to model alternate protein conformations through simple manipulation of the multiple sequence alignment via in silico mutagenesis. The approach is grounded in the hypothesis that the multiple sequence alignment must also encode for protein structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations. A systematic modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design.     

Protein backbone angle restraints from searching a database for chemical shift and sequence homology

Chemical shifts of backbone atoms in proteins are exquisitely sensitive to local conformation, and homologous proteins show quite similar patterns of secondary chemical shifts. The inverse of this relation is used to search a database for triplets of adjacent residues with secondary chemical shifts and sequence similarity which provide the best match to the query triplet of interest. The database contains 13C, 13C, 13C, 1H and 15N chemical shifts for 20 proteins for which a high resolution X-ray structure is available. The computer program TALOS was developed to search this database for strings of residues with chemical shift and residue type homology. The relative importance of the weighting factors attached to the secondary chemical shifts of the five types of resonances relative to that of sequence similarity was optimized empirically. TALOS yields the 10 triplets which have the closest similarity in secondary chemical shift and amino acid sequence to those of the query sequence. If the central residues in these 10 triplets exhibit similar and backbone angles, their averages can reliably be used as angular restraints for the protein whose structure is being studied. Tests carried out for proteins of known structure indicate that the root-mean-square difference (rmsd) between the output of TALOS and the X-ray derived backbone angles is about 15°. Approximately 3% of the predictions made by TALOS are found to be in error.     

PRODECOMPv3: decompositions of NMR projections for protein backbone and side-chain assignments and structural studies

PRODECOMP (projection decomposition) is an implementation of a multi-way decomposition algorithm for the analysis of two-dimensional projections of high-dimensional nuclear magnetic resonance spectra. The newest version, PRODECOMPv3, features a dramatic speedup, more reliable decompositions, a substantial reduction in memory demands, a new graphical user interface and integration into third-party software. These improvements extend the applicability of decompositions to novel types of NMR data on proteins, yielding backbone and side-chain assignments as well as structural information, and therewith enabling complete characterizations of proteins. AVAILABILITY: Program, short manual and an example calculation are freely available at www2.chem.gu.se/bcbp/nmr/prodecomp.html.     

1H, 13C and 15N backbone and side-chain chemical shift assignment of the Fyn SH2 domain and its complex with a phosphotyrosine peptide

SH2 domains are interaction modules uniquely dedicated to recognize phosphotyrosine sites, playing a central role in for instance the activation of tyrosine kinases or phosphatases. Here we report the ¹H, ¹⁵N and ¹³C backbone and side-chain chemical shift assignments of the SH2 domain of the human protein tyrosine kinase Fyn, both in its free state and bound to a high-affinity phosphotyrosine peptide corresponding to a specific sequence in the hamster middle-T antigen. The BMRB accession numbers are 17,368 and 17,369, respectively.     

The dominant role of side-chain backbone interactions in structural realization of amino acid code. ChiRotor: a side-chain prediction algorithm based on side-chain backbone interactions

The basic differences between the 20 natural amino acid residues are due to differences in their side-chain structures. This characteristic design of protein building blocks implies that side-chain-side-chain interactions play an important, even dominant role in 3D-structural realization of amino acid codes. Here we present the results of a comparative analysis of the contributions of side-chain-side-chain (s-s) and side-chain-backbone (s-b) interactions to the stabilization of folded protein structures within the framework of the CHARMm molecular data model. Contrary to intuition, our results suggest that side-chain-backbone interactions play the major role in side-chain packing, in stabilizing the folded structures, and in differentiating the folded structures from the unfolded or misfolded structures, while the interactions between side chains have a secondary effect. An additional analysis of electrostatic energies suggests that combinatorial dominance of the interactions between opposite charges makes the electrostatic interactions act as an unspecific folding force that stabilizes not only native structure, but also compact random conformations. This observation is in agreement with experimental findings that, in the denatured state, the charge-charge interactions stabilize more compact conformations. Taking advantage of the dominant role of side-chain-backbone interactions in side-chain packing to reduce the combinatorial problem, we developed a new algorithm, ChiRotor, for rapid prediction of side-chain conformations. We present the results of a validation study of the method based on a set of high resolution X-ray structures.     

Molecular dynamics simulations of a beta-hairpin fragment of protein G: balance between side-chain and backbone forces

How is the native structure encoded in the amino acid sequence? For the traditional backbone centric view, the dominant forces are hydrogen bonds (backbone) and phi-psi propensity. The role of hydrophobicity is non-specific. For the side-chain centric view, the dominant force of protein folding is hydrophobicity. In order to understand the balance between backbone and side-chain forces, we have studied the contributions of three components of a beta-hairpin peptide: turn, backbone hydrogen bonding and side-chain interactions, of a 16-residue fragment of protein G. The peptide folds rapidly and cooperatively to a conformation with a defined secondary structure and a packed hydrophobic cluster of aromatic side-chains. Our strategy is to observe the structural stability of the beta-hairpin under systematic perturbations of the turn region, backbone hydrogen bonds and the hydrophobic core formed by the side-chains, respectively. In our molecular dynamics simulations, the peptides are solvated. with explicit water molecules, and an all-atom force field (CFF91) is used. Starting from the original peptide (G41EWTYDDATKTFTVTE56), we carried out the following MD simulations. (1) unfolding at 350 K; (2) forcing the distance between the C(alpha) atoms of ASP47 and LYS50 to be 8 A; (3) deleting two turn residues (Ala48 and Thr49) to form a beta-sheet complex of two short peptides, GEWTYDD and KTFTVTE; (4) four hydrophobic residues (W43, Y45, F52 and T53) are replaced by a glycine residue step-by-step; and (5) most importantly, four amide hydrogen atoms (T44, D46, T53, and T55, which are crucial for backbone hydrogen bonding), are substituted by fluorine atoms. The fluorination not only makes it impossible to form attractive hydrogen bonding between the two beta-hairpin strands, but also introduces a repulsive force between the two strands due to the negative charges on the fluorine and oxygen atoms. Throughout all simulations, we observe that backbone hydrogen bonds are very sensitive to the perturbations and are easily broken. In contrast, the hydrophobic core survives most perturbations. In the decisive test of fluorination, the fluorinated peptide remains folded under our simulation conditions (5 ns, 278 K). Hydrophobic interactions keep the peptide folded, even with a repulsive force between the beta-strands. Thus, our results strongly support a side-chain centric view for protein folding.