Exploring the conformational space of protein loops using a mean field technique with MOLS sampling

We have recently developed a computational technique that uses mutually orthogonal Latin square sampling to explore the conformational space of oligopeptides in an exhaustive manner. In this article, we report its use to analyze the conformational spaces of 120 protein loop sequences in proteins, culled from the PDB, having the length ranging from 5 to 10 residues. The force field used did not have any information regarding the sequences or structures that flanked the loop. The results of the analyses show that the native structure of the loop, as found in the PDB falls at one of the low energy points in the conformational landscape of the sequences. Thus, a large portion of the structural determinants of the loop may be considered intrinsic to the sequence, regardless of either adjacent sequences or structures, or the interactions that the atoms of the loop make with other residues in the protein or in neighboring proteins.     

Protein structure prediction using mutually orthogonal Latin squares and a genetic algorithm

We combine a new, extremely fast technique to generate a library of low energy structures of an oligopeptide (by using mutually orthogonal Latin squares to sample its conformational space) with a genetic algorithm to predict protein structures. The protein sequence is divided into oligopeptides, and a structure library is generated for each. These libraries are used in a newly defined mutation operator that, together with variation, crossover, and diversity operators, is used in a modified genetic algorithm to make the prediction. Application to five small proteins has yielded near native structures.     

Conformational space exploration of Met- and Leu-enkephalin using the MOLS method, molecular dynamics, and Monte Carlo simulation--a comparative study

We report here a comparative study of the molecular conformational energy landscape generated using the mutually orthogonal Latin squares (MOLS) method, molecular dynamics (MD), and Monte Carlo (MC) simulation. The MOLS method, as described earlier from our laboratory, uses an experimental design technique to rapidly and exhaustively sample the low energy conformations of a molecule. MD and MC simulations have been used to perform similar tasks. In the comparison reported here, the three methods were applied to a pair of neuropeptides, namely Met- and Leu-enkephalin. A set of 1500 conformations of these enkephalins were generated using these methods with CHARMM22 force field, and the resulting samples were analyzed to determine the extent and nature of coverage of the conformational space. The results indicate that the MOLS method samples a larger number of possible conformations and identifies conformations closer to the experimental structures than the MD and MC simulations.     

An application of experimental design using mutually orthogonal Latin squares in conformational studies of peptides

We address the question-can we use experimental design methods to investigate peptide conformation and identify conformational parameters that may contribute more significantly to the potential energy than others? We used mutually orthogonal Latin square design to sample the conformational space of peptides and analysed the samples using analysis of variance. We examined the equality of the effect of the torsion angles on the conformational potential energy. The results showed that different torsion angles contributed differently to the conformational energy. We are able to identify those parameters that may have to be more carefully considered in conformational studies of peptides.     

Enhanced sampling of the molecular potential energy surface using mutually orthogonal latin squares: application to peptide structures

The computational identification of the optimal three-dimensional fold of even a small peptide chain from its sequence, without reference to other known structures, is a complex problem. There have been several attempts at solving this by sampling the potential energy surface of the molecule in a systematic manner. Here we present a new method to carry out the sampling, and to identify low energy conformers of the molecule. The method uses mutually orthogonal Latin squares to select (of the order of) n(2) points from the multidimensional conformation space of size m(n), where n is the number of dimensions (i.e., the number of conformational variables), and m specifies the fineness of the search grid. The sampling is accomplished by first calculating the value of the potential energy function at each one of the selected points. This is followed by analysis of these values of the potential energy to obtain the optimal value for each of the n-variables separately. We show that the set of the n-optimal values obtained in this manner specifies a low energy conformation of the molecule. Repeated application of the method identifies other low energy structures. The computational complexity of this algorithm scales as the fourth power of the size of the molecule. We applied this method to several small peptides, such as the neuropeptide enkephalin, and could identify a set of low energy conformations for each. Many of the structures identified by this method have also been previously identified and characterized by experiment and theory. We also compared the best structures obtained for the tripeptide (Ala)(3) by the present method, with those obtained by an exhaustive grid search, and showed that the algorithm is successful in identifying all the low energy conformers of this molecule.     

Enhanced sampling of peptide and protein conformations using replica exchange simulations with a peptide backbone biasing-potential

During replica exchange molecular dynamics (RexMD) simulations, several replicas of a system are simulated at different temperatures in parallel allowing for exchange between replicas at frequent intervals. This technique allows significantly improved sampling of conformational space and is increasingly being used for structure prediction of peptides and proteins. A drawback of the standard temperature RexMD is the rapid increase of the replica number with increasing system size to cover a desired temperature range. In an effort to limit the number of replicas, a new Hamiltonian-RexMD method has been developed that is specifically designed to enhance the sampling of peptide and protein conformations by applying various levels of a backbone biasing potential for each replica run. The biasing potential lowers the barrier for backbone dihedral transitions and promotes enhanced peptide backbone transitions along the replica coordinate. The application on several peptide cases including in all cases explicit solvent indicates significantly improved conformational sampling when compared with standard MD simulations. This was achieved with a very modest number of 5-7 replicas for each simulation system making it ideally suited for peptide and protein folding simulations as well as refinement of protein model structures in the presence of explicit solvent.     

Folding simulations of Trp‐cage mini protein in explicit solvent using biasing potential replica‐exchange molecular dynamics simulations

Replica exchange molecular dynamics (RexMD) simulations are frequently used for studying structure formation and dynamics of peptides and proteins. A significant drawback of standard temperature RexMD is, however, the rapid increase of the replica number with increasing system size to cover a desired temperature range. A recently developed Hamiltonian RexMD method has been used to study folding of the Trp‐cage protein. It employs a biasing potential that lowers the backbone dihedral barriers and promotes peptide backbone transitions along the replica coordinate. In two independent applications of the biasing potential RexMD method including explicit solvent and starting from a completely unfolded structure the formation of near‐native conformations was observed after 30–40 ns simulation time. The conformation representing the most populated cluster at the final simulation stage had a backbone root mean square deviation of ～1.3 Å from the experimental structure. This was achieved with a very modest number of five replicas making it well suited for peptide and protein folding and refinement studies including explicit solvent. In contrast, during five independent continuous 70 ns molecular dynamics simulations formation of collapsed states but no near native structure formation was observed. The simulations predict a largely collapsed state with a significant helical propensity for the helical domain of the Trp‐cage protein already in the unfolded state. Hydrogen bonded bridging water molecules were identified that could play an active role by stabilizing the arrangement of the helical domain with respect to the rest of the chain already in intermediate states of the protein. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

Large loop conformation sampling using the activation relaxation technique, ART-nouveau method

We present an adaptation of the ART-nouveau energy surface sampling method to the problem of loop structure prediction. This method, previously used to study protein folding pathways and peptide aggregation, is well suited to the problem of sampling the conformation space of large loops by targeting probable folding pathways instead of sampling exhaustively that space. The number of sampled conformations needed by ART nouveau to find the global energy minimum for a loop was found to scale linearly with the sequence length of the loop for loops between 8 and about 20 amino acids. Considering the linear scaling dependence of the computation cost on the loop sequence length for sampling new conformations, we estimate the total computational cost of sampling larger loops to scale quadratically compared to the exponential scaling of exhaustive search methods.     

Conformational studies of the alpha-helical 28-43 fragment of the B3 domain of the immunoglobulin binding protein G from Streptococcus

To determine whether the alpha-helix in the B3 immunoglobulin binding domain of protein G from group G Streptococcus has conformational stability as an isolated fragment, we carried out a CD and NMR study of the 16-residue peptide in solution corresponding to this alpha-helix. Based on two-dimensional H-NMR spectra recorded at three different temperatures (283, 305, and 313 K), it was found that this peptide is mostly unstructured in water at these temperatures. Weak signals corresponding to i,i+3 or i,i+4 interactions, which are characteristic of formation of turn-like structures, were observed in the ROE spectra at all temperatures. The absence of a stable three-dimensional structure of the investigated peptide supports an earlier study (Blanco and Serrano, Eur J Biochem 1995, 230, 634-649) of a possible mechanism for folding of other (B1 and B2) immunoglobulin binding domains of Protein G. (c) 2008 Wiley Periodicals, Inc. Biopolymers 89: 1032-1044, 2008.This article was originally published online as an accepted preprint. The "Published Online" date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com.     

Conformational solution studies of the anti-microbial temporin A retro-analogues by using NMR spectroscopy.

Temporin A (TA) is a small, basic and highly hydrophobic peptide, isolated from the skin of the European red frog, Rana temporaria. The TA (FLPLIGRVLSGIL-NH2) displays a broad spectrum of anti-microbial activity against Gram-positive bacteria and fungi Candida albicans. In this study we investigate the solution structure of two TA retro-analogues, (6-1)(7-13)-TA (GILPLFRVLSGIL-NH2) and retro-TA (LIGSLVRGILPLF-NH2) by using nuclear magnetic resonance (NMR). The 3D solution structure of the analogues was established by using inter-proton distances and vicinal coupling constants in the Simulated Annealing (SA) calculations (XPLOR program). The NMR conformational studies show the existence of the helical structure in the middle part of the (6-1)(7-13)-TA peptide and an unordered structure of the retro-TA analogue under the D3-TFE/H2O (3:7, v/v) conditions. Our investigations have shown that the hydrophobic cluster at N-terminus with the Pro amino acid residue in position 3 or 4, the helical structure and the amphipathic character of the peptide are responsible for the anti-microbial activity of the TA analogues.     

Predicting the structures of 18 peptides using Geocore

We describe an extensive test of Geocore, an ab initio peptide folding algorithm. We studied 18 short molecules for which there are structures in the Protein Data Bank; chains are up to 31 monomers long. Except for the very shortest peptides, an extremely simple energy function is sufficient to discriminate the true native state from more than 10(8) lowest energy conformations that are searched explicitly for each peptide. A high incidence of native-like structures is found within the best few hundred conformations generated by Geocore for each amino acid sequence. Predictions improve when the number of discrete phi/psi choices is increased.     

Conformational studies of the α-helical proteins from wool keratin by c.d.

The conformation and conformational change of wool keratin $\text{S-}\text{carboxymethylated}$ low-sulphur proteins (SCMKA), which are α-helical fibrous proteins, have been investigated in aqueous solution by means of c.d. Comparisons of various methods proposed for c.d. analysis of protein secondary structure are made using least-squares curve-fitting of the observed c.d. spectra of SCMKA with a linear combination of the corresponding reference spectra of secondary structures. It has been found that (i) the most satisfactory results are obtained with the method¹³ which takes into account the β-turn contribution: (ii) SCMKA is 52–54% α-helical in water and has little β-form, (iii) the addition of n-propanol produces, even at higher concentrations of n-propanol, little chnage in spectra with respect to helical character in water; (iv) SCMKA undergoes a thermally-induced conformational transition from α-helix to random coil around 50 C; and (v) $\text{S-}\text{aminoethylated}$ low-sulphur proteins with positively charged protecting groups are /_~50% α-helical in water, which is similar to SCMKA, showing that the protecting groups introduced in the low-sulphur proteins are little effect upon their conformation in water     

Conformational studies of the C-terminal 16-amino-acid-residue fragment of the B3 domain of the immunoglobulin binding protein G from Streptococcus

The structure and stability of the 16-amino-acid-residue fragment [IG(46-61)] corresponding to the C-terminal beta-hairpin of the B3 domain of the immunoglobulin binding protein G from Streptococcus was investigated by means of CD and NMR spectroscopy and by differential scanning calorimetry. The CD and 2D NMR experiments were carried out (i) in water at different temperatures and (ii) at one temperature (305 K), with only CD, at different TFE concentrations. Our results show that the IG(46-61) peptide possesses organized three-dimensional structure at all investigated temperatures. The three-dimensional structure of the IG(46-61) peptide resembles the general shape of a beta-hairpin that is also observed for this peptide in the experimental structure of the B3 domain in the whole G protein; the structure is stabilized by hydrophobic interactions between nonpolar side chains. Our study shows that the melting temperature of the IG(46-61) peptide is about 320 K which supports the hypothesis that the investigated peptide can serve as a folding initiation site of the B3 domain of the immunoglobulin binding protein G.     

A pH-dependent variation in alpha-helix structure of the S-peptide of ribonuclease A studied by Monte Carlo simulated annealing.

Low-energy conformations of the S-peptide fragment (20 amino acid residues long) of ribonuclease A were studied by Monte Carlo simulated annealing. The obtained lowest-energy structures have alpha-helices with different size and location, depending distinctively on the ionizing states of acidic amino acid residues. The simulation started from completely random initial conformation and was performed without any bias toward a particular structure. The most conspicuous alpha-helices arose from the simulation when both Glu 9 and Asp 14 were assumed to be electrically neutral, whereas the resulting conformations became much less helical when Asp 14 rather than Glu 9 was allowed to have a negative charge. Together with experimental evidence that the alpha-helix in the S-peptide is most stable at pH 3.8, we consider the helix formation need the carboxyl group of Asp 14 to be electrically neutral in this weakly acidic condition. In contrast, a negative charge at Asp 14 appears to function in support of a view that this residue is crucial to helix termination owing to its possibility to form a salt bridge with His 12. These results indicate that the conformation of the S-peptide depends considerably on the ionizing state of Asp 14.     

Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures.

For successful ab initio protein structure prediction, a method is needed to identify native-like structures from a set containing both native and non-native protein-like conformations. In this regard, the use of distance geometry has shown promise when accurate inter-residue distances are available. We describe a method by which distance geometry restraints are culled from sets of 500 protein-like conformations for four small helical proteins generated by the method of Simons et al. (1997). A consensus-based approach was applied in which every inter-Calpha distance was measured, and the most frequently occurring distances were used as input restraints for distance geometry. For each protein, a structure with lower coordinate root-mean-square (RMS) error than the mean of the original set was constructed; in three cases the topology of the fold resembled that of the native protein. When the fold sets were filtered for the best scoring conformations with respect to an all-atom knowledge-based scoring function, the remaining subset of 50 structures yielded restraints of higher accuracy. A second round of distance geometry using these restraints resulted in an average coordinate RMS error of 4.38 A.     

Finding the needle in the haystack: towards solving the protein-folding problem computationally

Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as “the protein folding problem,” has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.     

Understanding the evolutionary relationship of hemagglutinin protein from influenza viruses using phylogenetic and molecular modeling studies

The existing H1N1 (2009) swine flu is pandemic in nature and is responsible for global economic losses and fatalities. Among the eight gene segments of H1N1, hemagglutinin (HA) plays a major role in the attachment of the virus to the host cell surface and entry of viral RNA into the host cell leads to infection. In this study, sequence and phylogenetic analysis of the H1N1 (2009) HA, from Mexico City along with 1952 sequences, from different subtypes of pandemic influenza A virus were studied and results showed that the closest relationship of H1N1 (2009) Mexico strain was with the H1N1 (2007) Mallard Norway strain. Analysis of secondary structures predicted from the protein sequence revealed that diminishing of alpha helixes was observed in many areas of the sequences between the years 2005 to 2010. Conversely, analysis at the structural level is necessary to critically assess the functional significance. Structural level investigation was therefore done for the above said proteins by constructing the 3D structure of these proteins through homology modeling. The models were validated and structural level similarities were evaluated through superimposition. Subsequently, docking studies were done to find the binding mode of the sialic acid (SA) with influenza HA. Molecular dynamics simulations were executed to study the interactions of SA molecule with the HA. Energetic analysis reveals that van der Waal interaction is more favorable for binding of HA with SA of the whole influenza virus. Binding pocket analysis shows that intensities of H-bond donor and acceptor are more in H1N1 (2009).     

Distinguish protein decoys by using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model

Recent works have shown the ability of physics-based potentials (e.g., CHARMM and OPLS-AA) and energy minimization to differentiate the native protein structures from large ensemble of non-native structures. In this study, we extended previous work by other authors and developed an energy scoring function using a new set of AMBER parameters (also recently developed in our laboratory) in conjunction with molecular dynamics and the Generalized Born solvent model. We evaluated the performance of our new scoring function by examining its ability to distinguish between the native and decoy protein structures. Here we present a systematic comparison of our results with those obtained with use of other physics-based potentials by previous authors. A total of 7 decoy sets, 117 protein sequences, and more than 41,000 structures were evaluated. The results of our study showed that our new scoring function represents a significant improvement over previously published physics-based scoring functions.     

Conformational solution studies of the SDS micelle-bound 11-28 fragment of two Alzheimer's beta-amyloid variants (E22K and A21G) using CD, NMR, and MD techniques

The beta-amyloid (Abeta) is the major peptide constituent of neuritic plaques in Alzheimer's disease (AD) and its aggregation is believed to play a central role in the pathogenesis of the disease. Naturally occurring mutations resulting in changes in the Abeta sequence (pos. 21-23) are associated with familial AD-like diseases with extensive cerebrovascular pathology. It was proved that the mutations alter the aggregation ability of Abeta and its neurotoxicity. Among five mutations at positions 21-23 there are two mutations with distinct clinical characteristics and potentially distinct pathogenic mechanism-the Italian (E22K) and the Flemish (A21G) mutations. In our studies we have examined the structures of the 11-28 fragment of the Italian and Flemish Abeta variants. The fragment was chosen because it has been shown to be the most important for amyloid fibril formation. The detailed structure of both variants Abeta(11-28) was determined using CD, 2D NMR, and molecular dynamics techniques under water-SDS micelle conditions. The NMR analysis revealed two distinct sets of proton resonances for the peptides. The studies of both peptides pointed out the existence of well-defined alpha-helical conformation in the Italian mutant, whereas the Flemish was found to be unstructured with the possibility of a bent structure in the central part of the peptide.     

Effects of radiofrequency field exposure on proteotoxic-induced and heat-induced HSF1 response in live cells using the bioluminescence resonance energy transfer technique

As of today, only acute effects of RF fields have been confirmed to represent a potential health hazard and they are attributed to non-specific heating (≥ 1 °C) under high-level exposure. Yet, the possibility that environmental RF impact living matter in the absence of temperature elevation needs further investigation. Since HSF1 is both a thermosensor and the master regulator of heat-shock stress response in eukaryotes, it remains to assess HSF1 activation in live cells under exposure to low-level RF signals. We thus measured basal, temperature-induced, and chemically induced HSF1 trimerization, a mandatory step on the cascade of HSF1 activation, under RF exposure to continuous wave (CW), Global System for Mobile (GSM), and Wi-Fi-modulated 1800 MHz signals, using a bioluminescence resonance energy transfer technique (BRET) probe. Our results show that, as expected, HSF1 is heat-activated by acute exposure of transiently transfected HEK293T cells to a CW RF field at a specific absorption rate of 24 W/kg for 30 min. However, we found no evidence of HSF1 activation under the same RF exposure condition when the cell culture medium temperature was fixed. We also found no experimental evidence that, at a fixed temperature, chronic RF exposure for 24 h at a SAR of 1.5 and 6 W/kg altered the potency or the maximal capability of the proteasome inhibitor MG132 to activate HSF1, whatever signal used. We only found that RF exposure to CW signals (1.5 and 6 W/kg) and GSM signals (1.5 W/kg) for 24 h marginally decreased basal HSF1 activity.Electronic supplementary materialThe online version of this article (10.1007/s12192-020-01172-3) contains supplementary material, which is available to authorized users.