Role of conformational sampling in computing mutation-induced changes in protein structure and stability

The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling.     

Progress of 1D protein structure prediction at last

Accuracy of predicting protein secondary structure and solvent accessibility from sequence information has been improved significantly by using information contained in multiple sequence alignments as input to a neural 'network system. For the Asilomar meeting, predictions for 13 proteins were generated automatically using the publicly available prediction method PHD. The results confirm the estimate of 72% three-state prediction accuracy. The fairly accurate predictions of secondary structure segments made the tool useful as a starting point for modeling of higher dimensional aspects of protein structure. © 1995 Wiley-Liss, Inc.     

The linear interaction energy method for the prediction of protein stability changes upon mutation

The coupling of protein energetics and sequence changes is a critical aspect of computational protein design, as well as for the understanding of protein evolution, human disease, and drug resistance. To study the molecular basis for this coupling, computational tools must be sufficiently accurate and computationally inexpensive enough to handle large amounts of sequence data. We have developed a computational approach based on the linear interaction energy (LIE) approximation to predict the changes in the free-energy of the native state induced by a single mutation. This approach was applied to a set of 822 mutations in 10 proteins which resulted in an average unsigned error of 0.82 kcal/mol and a correlation coefficient of 0.72 between the calculated and experimental ΔΔG values. The method is able to accurately identify destabilizing hot spot mutations; however, it has difficulty in distinguishing between stabilizing and destabilizing mutations because of the distribution of stability changes for the set of mutations used to parameterize the model. In addition, the model also performs quite well in initial tests on a small set of double mutations. On the basis of these promising results, we can begin to examine the relationship between protein stability and fitness, correlated mutations, and drug resistance.     

神经网络在蛋白质二级结构预测中的应用

介绍了蛋白质二级结构预测的研究意义,讨论了用在蛋白质二级结构预测方面的神经网络设计问题,并且较详尽地评述了近些年来用神经网络方法在蛋白质二级结构预测中的主要工作进展情况,展望了蛋白质结构预测的前景。     

Improvement of protein secondary structure prediction using binary word encoding

We propose a binary word encoding to improve the protein secondary structure prediction. A binary word encoding encodes a local amino acid sequence to a binary word, which consists of 0 or 1. We use an encoding function to map an amino acid to 0 or 1. Using the binary word encoding, we can statistically extract the multiresidue information, which depends on more than one residue. We combine the binary word encoding with the GOR method, its modified version, which shows better accuracy, and the neural network method. The binary word encoding improves the accuracy of GOR by 2.8%. We obtain similar improvement when we combine this with the modified GOR method and the neural network method. When we use multiple sequence alignment data, the binary word encoding similarly improves the accuracy. The accuracy of our best combined method is 68.2%. In this paper, we only show improvement of the GOR and neural network method, we cannot say that the encoding improves the other methods. But the improvement by the encoding suggests that the multiresidue interaction affects the formation of secondary structure. In addition, we find that the optimal encoding function obtained by the simulated annealing method relates to non-polarity. This means that nonpolarity is important to the multiresidue interaction. Proteins 27:36–46 © 1997 Wiley-Liss, Inc.     

具时滞的Hopfield型神经网络模型的全局渐近稳定性

本文研究了具时滞的Hopfield型神经网络模型平衡点的全局渐近稳定性,获得了一系列充分条件。     

Effect of the N1 residue on the stability of the alpha-helix for all 20 amino acids

N1 is the first residue in an alpha-helix. We have measured the contribution of all 20 amino acids to the stability of a small helical peptide CH(3)CO-XAAAAQAAAAQAAGY-NH(2) at the N1 position. By substituting every residue into the N1 position, we were able to investigate the stabilizing role of each amino acid in an isolated context. The helix content of each of the 20 peptides was measured by circular dichroism (CD) spectroscopy. The data were analyzed by our modified Lifson-Roig helix-coil theory, which includes the n1 parameter, to find free energies for placing a residue into the N1 position. The rank order for free energies is Asp(-), Ala > Glu(-) > Glu(0) > Trp, Leu, Ser > Asp(0), Thr, Gln, Met, Ile > Val, Pro > Lys(+), Arg, His(0) > Cys, Gly > Phe > Asn, Tyr, His(+). N1 preferences are clearly distinct from preferences for the preceding N-cap and alpha-helix interior. pK(a) values were measured for Asp, Glu, and His, and protonation-free energies were calculated for Asp and Glu. The dissociation of the Asp proton is less favorable than that of Glu, and this reflects its involvement in a stronger stabilizing interaction at the N terminus. Proline is not energetically favored at the alpha-helix N terminus despite having a high propensity for this position in crystal structures. The data presented are of value both in rationalizing mutations at N1 alpha-helix sites in proteins and in predicting the helix contents of peptides.     

Opposing structural changes in two symmetrical polypeptides bring about opposing changes to the thermal stability of a complex integral membrane protein

The relationship between membrane protein structure and thermal stability has been examined in the reaction centre from the bacterium Rhodobacter sphaeroides, a complex membrane protein comprising three polypeptide chains and 10 cofactors. The core of this protein exhibits an approximate twofold symmetry, the cofactors being held in two membrane-spanning branches by two polypeptides, termed L and M, that have very similar folds. In assays of the thermal stability of wild-type and mutant reaction centres embedded in the native bilayer membrane, replacement of a Phe at position 197 of the M polypeptide by His produced an increase in stability, whereas an opposing replacement of His by Phe at the symmetrical position 168 of the L-polypeptide produced a decrease in stability. In light of the known X-ray crystal structures of wild-type and mutant variants of this protein, and further mutagenesis, it is concluded that these stability changes result from the introduction or removal, respectively, of a hydrogen bond between the side-chain of the His and that of an Asn located two positions along the M or L polypeptide chain, in addition to a hydrogen bond between the His side-chain and an adjacent bacteriochlorophyll cofactor.     

Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network

This article attempts to increase the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins through improved learning. Most methods developed for improving the backpropagation algorithm of artificial neural networks are limited to small neural networks. Here, we introduce a guided-learning method suitable for networks of any size. The method employs a part of the weights for guiding and the other part for training and optimization. We demonstrate this technique by predicting residue solvent accessibility and real-value backbone torsion angles of proteins. In this application, the guiding factor is designed to satisfy the intuitive condition that for most residues, the contribution of a residue to the structural properties of another residue is smaller for greater separation in the protein-sequence distance between the two residues. We show that the guided-learning method makes a 2-4% reduction in 10-fold cross-validated mean absolute errors (MAE) for predicting residue solvent accessibility and backbone torsion angles, regardless of the size of database, the number of hidden layers and the size of input windows. This together with introduction of two-layer neural network with a bipolar activation function leads to a new method that has a MAE of 0.11 for residue solvent accessibility, 36 degrees for psi, and 22 degrees for phi. The method is available as a Real-SPINE 3.0 server in http://sparks.informatics.iupui.edu.     

MUFOLD‐SS: New deep inception‐inside‐inception networks for protein secondary structure prediction

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception‐inside‐inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD‐SS. The input to MUFOLD‐SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio‐chemical properties of amino acids, PSI‐BLAST profile, and HHBlits profile. MUFOLD‐SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD‐SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD‐SS outperformed the best existing methods and other deep neural networks significantly. MUFold‐SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html .     

Deep-learning contact-map guided protein structure prediction in CASP13

We report the results of two fully automated structure prediction pipelines, “Zhang-Server” and “QUARK”, in CASP13. The pipelines were built upon the C-I-TASSER and C-QUARK programs, which in turn are based on I-TASSER and QUARK but with three new modules: (a) a novel multiple sequence alignment (MSA) generation protocol to construct deep sequence-profiles for contact prediction; (b) an improved meta-method, NeBcon, which combines multiple contact predictors, including ResPRE that predicts contact-maps by coupling precision-matrices with deep residual convolutional neural-networks; and (c) an optimized contact potential to guide structure assembly simulations. For 50 CASP13 FM domains that lacked homologous templates, average TM-scores of the first models produced by C-I-TASSER and C-QUARK were 28% and 56% higher than those constructed by I-TASSER and QUARK, respectively. For the first time, contact-map predictions demonstrated usefulness on TBM domains with close homologous templates, where TM-scores of C-I-TASSER models were significantly higher than those of I-TASSER models with a P-value <.05. Detailed data analyses showed that the success of C-I-TASSER and C-QUARK was mainly due to the increased accuracy of deep-learning-based contact-maps, as well as the careful balance between sequence-based contact restraints, threading templates, and generic knowledge-based potentials. Nevertheless, challenges still remain for predicting quaternary structure of multi-domain proteins, due to the difficulties in domain partitioning and domain reassembly. In addition, contact prediction in terminal regions was often unsatisfactory due to the sparsity of MSAs. Development of new contact-based domain partitioning and assembly methods and training contact models on sparse MSAs may help address these issues.     

Contribution of surface salt bridges to protein stability: guidelines for protein engineering

The small globular protein, ubiquitin, contains a pair of oppositely charged residues, K11 and E34, that according to the three-dimensional structure are located on the surface of this protein with a spatial orientation characteristic of a salt bridge. We investigated the strength of this salt bridge and its contribution to the global stability of the ubiquitin molecule. Using the "double mutant cycle" analysis, the strength of the pairwise interactions between K11 and E34 was estimated to be favorable by 3.6kJ/mol. Further, the salt bridge of the reverse orientation, i.e. E11/K34, can be formed and is found to have a strength (3.8kJ/mol) similar to that of the K11/E34 pair. However, the global stability of the K11/E34 variant of ubiquitin is 2.2kJ/mol higher than that of the E11/K34 variant. The difference in the contribution of the opposing salt bridge orientations to the overall stability of the ubiquitin molecule is attributed to the difference in the charge-charge interactions between residues forming the salt bridge and the rest of the ionizable groups in this protein. On the basis of these results, we concluded that surface salt bridges are stabilizing, but their contribution to the overall protein stability is strongly context-dependent, with charge-charge interactions being the largest determinant. Analysis of 16 salt bridges from six different proteins, for which detailed experimental data on energetics have been reported, support the conclusions made from the analysis of the salt bridge in ubiquitin. Implications of these findings for engineering proteins with enhanced thermostability are discussed.     

The role of residue stability in transient protein–protein interactions involved in enzymatic phosphate hydrolysis. A computational study

Finding why protein–protein interactions (PPIs) are so specific can provide a valuable tool in a variety of fields. Statistical surveys of so‐called transient complexes (like those relevant for signal transduction mechanisms) have shown a tendency of polar residues to participate in the interaction region. Following this scheme, residues in the unbound partners have to compete between interacting with water or interacting with other residues of the protein. On the other hand, several works have shown that the notion of active site electrostatic preorganization can be used to interpret the high efficiency in enzyme reactions. This preorganization can be related to the instability of the residues important for catalysis. In some enzymes, in addition, conformational changes upon binding to other proteins lead to an increase in the activity of the enzymatic partner. In this article the linear response approximation version of the semimacroscopic protein dipoles Langevin dipoles (PDLD/S‐LRA) model is used to evaluate the stability of several residues in two phosphate hydrolysis enzymes upon complexation with their activating partners. In particular, the residues relevant for PPI and for phosphate hydrolysis in the CDK2/Cyclin A and Ras/GAP complexes are analyzed. We find that the evaluation of the stability of residues in these systems can be used to identify not only active site regions but it can also be used as a guide to locate “hot spots” for PPIs. We also show that conformational changes play a major role in positioning interfacing residues in a proper “energetic” orientation, ready to interact with the residues in the partner protein surface. Thus, we extend the preorganization theory to PPIs, extrapolating the results we obtained from the above‐mentioned complexes to a more general case. We conclude that the correlation between stability of a residue in the surface and the likelihood that it participates in the interaction can be a general fact for transient PPIs. Proteins 2006. © 2005 Wiley‐Liss, Inc.     

The effects of amino acid replacements of glycine 20 on conformational stability and catalysis of staphylococcal nuclease

Staphylococcal nuclease (SNase) is a well-established model for protein folding studies. Its three-dimensional structure has been determined. The enzyme, Ca2+, and DNA or RNA substrate form a ternary complex. Glycine 20 is the second position of the first beta-turn of SNase, which may serve as the folding initiation site for the SNase polypeptide. To study the role of Gly20 in the conformational stability and catalysis of SNase, three mutants, in which Gly20 was replaced by alanine, valine, or isoleucine, were constructed and studied by using circular dichroism spectra, intrinsic and ANS-binding fluorescence spectra, stability and activity assays. The mutations have little effect on the conformational integrity of the mutants. However, the catalytic activity is reduced drastically by the mutations, and the stability of the protein is progressively decreased in the order G20A相似文献   

Stability of a guest protein depends on stability of a host protein in insertional fusion

Insertional fusion between host and guest protein domains has been employed to create multi-domain protein complexes displaying integrated and coupled functionalities. The effects of insertional fusion on the stability of a guest protein are however rather controversial. In the study described here, we examined whether the stability of inserted TEM1 beta-lactamase (BLA), as a guest protein, might be affected by the stability of a maltodextrin-binding protein (MBP), as a host protein. Our results indicate that expression levels and in vitro stability of the BLA domain were significantly higher when inserted into thermophilic MBP from Pyrococcus furiosus (PfMBP) compared to mesophilic MBP from Escherichia coli (EcMBP). Moreover, insertion into PfMBP at selected sites was found to improve thermal stability of the BLA domain without compromise in expression levels and BLA activity. Kinetic stabilization during prolonged thermal denaturation of the BLA domain was not guaranteed by insertion into PfMBP, but rather relied on the insertion sites. Taken together, we provide evidence that (i) the stability of the guest protein depended on the stability of the host protein in insertional fusion and (ii) insertion into PfMBP, at least at selected locations, can serve as a novel method of improving protein thermal stability.     

Effect of polyethylene glycol on the thermal stability of green fluorescent protein

Green fluorescent protein (GFP) shows remarkable structural stability and high fluorescence; its stability can be directly related to its fluorescence output, among other characteristics. GFP is stable under increasing temperatures, and its thermal denaturation is highly reproducible. Some polymers, such as polyethylene glycol, are often used as modifiers of characteristics of biological macromolecules, to improve the biochemical activity and stability of proteins or drug bioavailability. The aim of this study was to evaluate the thermal stability of GFP in the presence of different PEG molar weights at several concentrations and exposed to constant temperatures, in a range of 70–95°C. Thermal stability was expressed in decimal reduction time. It was observed that the D‐values obtained were almost constant for temperatures of 85, 90, and 95°C, despite the PEG concentration or molar weight studied. Even though PEG can stabilize proteins, only at 75°C, PEG 600 and 4,000 g/mol stabilized GFP. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Identification of protein stability determinants in chloroplasts

Although chloroplast protein stability has long been recognised as a major level of post‐translational regulation in photosynthesis and gene expression, the factors determining protein stability in plastids are largely unknown. Here, we have identified stability determinants in vivo by producing plants with transgenic chloroplasts that express a reporter protein whose N‐ and C‐termini were systematically modified. We found that major stability determinants are located in the N‐terminus. Moreover, testing of all 20 amino acids in the position after the initiator methionine revealed strong differences in protein stability and indicated an important role of the penultimate N‐terminal amino acid residue in determining the protein half life. We propose that the stability of plastid proteins is largely determined by three factors: (i) the action of methionine aminopeptidase (the enzyme that removes the initiator methionine and exposes the penultimate N‐terminal amino acid residue), (ii) an N‐end rule‐like protein degradation pathway, and (iii) additional sequence determinants in the N‐terminal region.     

Kinetic stability and crystal structure of the viral capsid protein SHP

SHP, the capsid-stabilizing protein of lambdoid phage 21, is highly resistant against denaturant-induced unfolding. We demonstrate that this high functional stability of SHP is due to a high kinetic stability with a half-life for unfolding of 25 days at zero denaturant, while the thermodynamic stability is not unusually high. Unfolding experiments demonstrated that the trimeric state (also observed in crystals and present on the phage capsid) of SHP is kinetically stable in solution, while the monomer intermediate unfolds very rapidly. We also determined the crystal structure of trimeric SHP at 1.5A resolution, which was compared to that of its functional homolog gpD. This explains how a tight network of H-bonds rigidifies crucial interpenetrating residues, leading to the observed extremely slow trimer dissociation or denaturation. Taken as a whole, our results provide molecular-level insights into natural strategies to achieve kinetic stability by taking advantage of protein oligomerization. Kinetic stability may be especially needed in phage capsids to allow survival in harsh environments.