Relationship between the longitudinal relaxation rates of water protons and of well defined paramagnetic centers at low temperature in hydrated vermiculite

A good agreement has been observed between the proton longitudinal relaxation rate in the two and one layer hydrate of the Na-Llano vermiculite, the location of the Fe³⁺ paramagnetic centers within the octahedral and tetrahedral layers of the lattice and the electronic longitudinal relaxation rate using the dipolar electronic—proton spin interaction. The water content influences noticeably the electronic longitudinal relaxation time.     

Prediction of protein folding rates from primary sequences using hybrid sequence representation

The ability to predict protein folding rates constitutes an important step in understanding the overall folding mechanisms. Although many of the prediction methods are structure based, successful predictions can also be obtained from the sequence. We developed a novel method called prediction of protein folding rates (PPFR), for the prediction of protein folding rates from protein sequences. PPFR implements a linear regression model for each of the mainstream folding dynamics including two-, multi-, and mixed-state proteins. The proposed method provides predictions characterized by strong correlations with the experimental folding rates, which equal 0.87 for the two- and multistate proteins and 0.82 for the mixed-state proteins, when evaluated with out-of-sample jackknife test. Based on in-sample and out-of-sample tests, the PPFR's predictions are shown to be better than most of other sequence only and structure-based predictors and complementary to the predictions of the most recent sequence-based QRSM method. We show that simultaneous incorporation of several characteristics, including the sequence, physiochemical properties of residues, and predicted secondary structure provides improved quality. This hybridized prediction model was analyzed to reveal the complementary factors that can be used in tandem to predict folding rates. We show that bigger proteins require more time for folding, higher helical and coil content and the presence of Phe, Asn, and Gln may accelerate the folding process, the inclusion of Ile, Val, Thr, and Ser may slow down the folding process, and for the two-state proteins increased beta-strand content may decelerate the folding process. Finally, PPFR provides strong correlation when predicting sequences with low similarity.     

Analysis and prediction of protein folding rates using quadratic response surface models

Understanding the relationship between amino acid sequences and folding rates of proteins is an important task in computational and molecular biology. In this work, we have systematically analyzed the composition of amino acid residues for proteins with different ranges of folding rates. We observed that the polar residues, Asn, Gln, Ser, and Lys, are dominant in fast folding proteins whereas the hydrophobic residues, Ala, Cys, Gly, and Leu, prefer to be in slow folding proteins. Further, we have developed a method based on quadratic response surface models for predicting the folding rates of 77 two- and three-state proteins. Our method showed a correlation of 0.90 between experimental and predicted protein folding rates using leave-one-out cross-validation method. The classification of proteins based on structural class improved the correlation to 0.98 and it is 0.99, 0.98, and 0.96, respectively, for all-alpha, all-beta, and mixed class proteins. In addition, we have utilized Baysean classification theory for discriminating two- and three-state proteins, which showed an accuracy of 90%. We have developed a web server for predicting protein folding rates and it is available at http://bioinformatics.myweb.hinet.net/foldrate.htm.     

Reduction of the Search Space for the Folding of Proteins at the Level of Formation and Assembly of Secondary Structures: A New View on the Solution of Levinthal′s Paradox

The complete volume of the protein conformation space is, by many orders of magnitude, smaller at the level of secondary structure elements than that at the level of amino acid residues; the latter, according to Levinthal′s estimate, scales approximately as 10^{2 L}, with L being the number of residues in the chain, whereas the former, as demonstrated in this paper, scales no faster than ～L^N, with N being the number of the secondary structure elements, which is approximately equal to L/15. This drastic decrease in the exponent (L/15 instead of 2 L) explains why sampling of the conformation space does not contradict the ability of the protein chain to find its most stable fold.     

Comparison of stochastic optimization methods for all-atom folding of the Trp-Cage protein.

The performances of three different stochastic optimization methods for all-atom protein structure prediction are investigated and compared. We use the recently developed all-atom free-energy force field (PFF01), which was demonstrated to correctly predict the native conformation of several proteins as the global optimum of the free energy surface. The trp-cage protein (PDB-code 1L2Y) is folded with the stochastic tunneling method, a modified parallel tempering method, and the basin-hopping technique. All the methods correctly identify the native conformation, and their relative efficiency is discussed.     

Cyano groups as probes of protein microenvironments and dynamics

Probe probation: The cyano group is sensitive to its environment, absorbs in a unique region of protein IR spectra, and may be appended to an amino acid. When investigated in variants of cytochrome?c (see picture: heme-pocket structure) by steady-state and time-resolved methods, it was found to be a useful site-specific probe of protein microenvironments and dynamics; however, it can also perturb its environment and destabilize the folded state of the protein.     

“Invisible” Conformers of an Antifungal Disulfide Protein Revealed by Constrained Cold and Heat Unfolding,CEST‐NMR Experiments,and Molecular Dynamics Calculations

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two‐ and three‐state analysis of thermal unfolding, that the population of hidden states may weight 20–40 % at 298 K in a disulfide‐rich protein. In addition, sensitive ¹⁵N‐CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR “dark matter”. Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction.     

Tightening up the structure,lighting up the pathway: application of molecular constraints and light to manipulate protein folding,self-assembly and function

Chemical cross-linking provides an effective avenue to reduce the conformational entropy of polypeptide chains and hence has become a popular method to induce or force structural formation in peptides and proteins.Recently,other types of molecular constraints,especially photoresponsive linkers and functional groups,have also found increased use in a wide variety of applications.Herein,we provide a concise review of using various forms of molecular strategies to constrain proteins,thereby stabilizing their native states,gaining insight into their folding mechanisms,and/or providing a handle to trigger a conformational process of interest with light.The applications discussed here cover a wide range of topics,ranging from delineating the details of the protein folding energy landscape to controlling protein assembly and function.     

A designed well-folded monomeric four-helix bundle protein prepared by Fmoc solid-phase peptide synthesis and native chemical ligation

The design and total chemical synthesis of a monomeric native-like four-helix bundle protein is presented. The designed protein, GTD-Lig, consists of 90 amino acids and is based on the dimeric structure of the de novo designed helix-loop-helix GTD-43. GTD-Lig was prepared by the native chemical ligation strategy and the fragments (45 residues long) were synthesized by applying standard fluorenylmethoxycarbonyl (Fmoc) chemistry. The required peptide-thioester fragment was prepared by anchoring the free gamma-carboxy group of Fmoc-Glu-allyl to the solid phase. After chain elongation the allyl moiety was orthogonally removed and the resulting carboxy group was functionalized with a glycine-thioester followed by standard trifluoroacetic acid (TFA) cleavage to produce the unprotected peptide-thioester. The structure of the synthetic protein was examined by far- and near-UV circular dichroism (CD), sedimentation equilibrium ultracentrifugation, and NMR and fluorescence spectroscopy. The spectroscopic methods show a highly helical and native-like monomeric protein consistent with the design. Heat-induced unfolding was studied by tryptophan absorbance and far-UV CD. The thermal unfolding of GTD-Lig occurs in two steps; a cooperative transition from the native state to an intermediate state and thereafter by noncooperative melting to the unfolded state. The intermediate exhibits the properties of a molten globule such as a retained native secondary structure and a compact hydrophobic core. The thermodynamics of GuHCl-induced unfolding were evaluated by far-UV CD monitoring and the unfolding exhibited a cooperative transition that is well-fitted by a two-state mechanism from the native to the unfolded state. GTD-Lig clearly shows the characteristics of a native protein with a well-defined structure and typical unfolding transitions. The design and synthesis presented herein is of general applicability for the construction of large monomeric proteins.     

Topology-based models and NMR structures in protein folding simulations

Topology-based interaction potentials are simplified models that use the native contacts in the folded structure of a protein to define an energetically unfrustrated folding funnel. They have been widely used to analyze the folding transition and pathways of different proteins through computer simulations. Obviously, they need a reliable, experimentally determined folded structure to define the model interactions. In structures elucidated through NMR spectroscopy, a complex treatment of the raw experimental data usually provides a series of models, a set of different conformations compatible with the available experimental data. Here, we use an efficient coarse-grained simulation technique to independently consider the contact maps from every different NMR model in a protein whose structure has been resolved by the use of NMR spectroscopy. For lambda-Cro repressor, a homodimeric protein, we have analyzed its folding characteristics with a topology-based model. We have focused on the competition between the folding of the individual chains and their binding to form the final quaternary structure. From 20 different NMR models, we find a predominant three-state folding behavior, in agreement with experimental data on the folding pathway for this protein. Individual NMR models, however, show distinct characteristics, which are analyzed both at the level of the interplay between tertiary/quaternary structure formation and also regarding the thermal stability of the tertiary structure of every individual chain.     

Collisional and Coulombic Unfolding of Gas‐Phase Proteins: High Correlation to Their Domain Structures in Solution

The three‐dimensional structures adopted by proteins are predicated by their many biological functions. Mass spectrometry has played a rapidly expanding role in protein structure discovery, enabling the generation of models for both proteins and their higher‐order assemblies. While important coursed‐grained insights have been generated, relatively few examples exist where mass spectrometry has been successfully applied to the characterization of protein tertiary structure. Here, we demonstrate that gas‐phase unfolding can be used to determine the number of autonomously folded domains within monomeric proteins. Our ion mobility‐mass spectrometry data highlight a strong, positive correlation between the number of protein unfolding transitions observed in the gas phase and the number of known domains within a group of sixteen proteins ranging from 8–78 kDa. This correlation and its potential uses for structural biology is discussed.     

Multiple Stable Conformations Account for Reversible Concentration‐Dependent Oligomerization and Autoinhibition of a Metamorphic Metallopeptidase

Molecular plasticity controls enzymatic activity: the native fold of a protein in a given environment is normally unique and at a global free‐energy minimum. Some proteins, however, spontaneously undergo substantial fold switching to reversibly transit between defined conformers, the “metamorphic” proteins. Here, we present a minimal metamorphic, selective, and specific caseinolytic metallopeptidase, selecase, which reversibly transits between several different states of defined three‐dimensional structure, which are associated with loss of enzymatic activity due to autoinhibition. The latter is triggered by sequestering the competent conformation in incompetent but structured dimers, tetramers, and octamers. This system, which is compatible with a discrete multifunnel energy landscape, affords a switch that provides a reversible mechanism of control of catalytic activity unique in nature.     

Efficient modeling of symmetric protein aggregates from NMR data

An efficient approach to determine the structures of symmetric protein aggregates from liquid and solid-state NMR data is presented. Any symmetry can be used (cyclic or dihedral point symmetries, helical symmetries, crystallographic symmetries). Because the starting point is the random structure of the monomer, the knowledge of the 3D structure of the monomer is not required.