Temperature as an Extra Dimension in Multidimensional Protein NMR Spectroscopy

NMR spectroscopy is a particularly informative method for studying protein structures and dynamics in solution; however, it is also one of the most time-consuming. Modern approaches to biomolecular NMR spectroscopy are based on lengthy multidimensional experiments, the duration of which grows exponentially with the number of dimensions. The experimental time may even be several days in the case of 3D and 4D spectra. Moreover, the experiment often has to be repeated under several different conditions, for example, to measure the temperature-dependent effects in a spectrum (temperature coefficients (TCs)). Herein, a new approach that involves joint sampling of indirect evolution times and temperature is proposed. This allows TCs to be measured through 3D spectra in even less time than that needed to acquire a single spectrum by using the conventional approach. Two signal processing methods that are complementary, in terms of sensitivity and resolution, 1) dividing data into overlapping subsets followed by compressed sensing reconstruction, and 2) treating the complete data set with a variant of the Radon transform, are proposed. The temperature-swept 3D HNCO spectra of two intrinsically disordered proteins, osteopontin and CD44 cytoplasmic tail, show that this new approach makes it possible to determine TCs and their non-linearities effectively. Non-linearities, which indicate the presence of a compact state, are particularly interesting. The complete package of data acquisition and processing software for this new approach are provided.     

Global and local indices for characterizing biomolecular flexibility and rigidity

Understanding flexibility and rigidity characteristics of biomolecules is a prerequisite for understanding biomolecular structural stability and function. Computational methods have been implemented that directly characterize biomolecular flexibility and rigidity by constraint network analysis. For deriving maximal advantage from these analyses, their results need to be linked to biologically relevant characteristics of a structure. Such links are provided by global and local measures (“indices”) of biomolecular flexibility and rigidity. To date, more than 14 indices are available with sometimes overlapping or only vague definitions. We present concise definitions of these indices, analyze the relation between, and the scope and limitations of them, and compare their informative value. For this, we probe the structural stability of the calcium binding protein α‐lactalbumin as a showcase, both in the “ground state” and after perturbing the system by changing the network topology. In addition, we introduce three indices for the first time that extend the application domain of flexibility and rigidity analyses. The results allow us to provide guidelines for future studies suggesting which of these indices could best be used for analyzing, understanding, and quantifying structural features that are important for biomolecular stability and function. Finally, we make suggestions for proper index notations in future studies to prevent the misinterpretation and to facilitate the comparison of results obtained from flexibility and rigidity analyses. © 2012 Wiley Periodicals, Inc.     

Enhanced sampling method in molecular simulations using genetic algorithm for biomolecular systems

We propose a molecular simulation method using genetic algorithm (GA) for biomolecular systems to obtain ensemble averages efficiently. In this method, we incorporate the genetic crossover, which is one of the operations of GA, to any simulation method such as conventional molecular dynamics (MD), Monte Carlo, and other simulation methods. The genetic crossover proposes candidate conformations by exchanging parts of conformations of a target molecule between a pair of conformations during the simulation. If the candidate conformations are accepted, the simulation resumes from the accepted ones. While conventional simulations are based on local update of conformations, the genetic crossover introduces global update of conformations. As an example of the present approach, we incorporated genetic crossover to MD simulations. We tested the validity of the method by calculating ensemble averages and the sampling efficiency by using two kinds of peptides, ALA3 and (AAQAA)₃. The results show that for ALA3 system, the distribution probabilities of backbone dihedral angles are in good agreement with those of the conventional MD and replica-exchange MD simulations. In the case of (AAQAA)₃ system, our method showed lower structural correlation of α-helix structures than the other two methods and more flexibility in the backbone ψ angles than the conventional MD simulation. These results suggest that our method gives more efficient conformational sampling than conventional simulation methods based on local update of conformations. © 2018 Wiley Periodicals, Inc.     

Future in biomolecular computation

Summary Large-scale computations for biomolecules are dominated by three levels of theory: rigorous quantum mechanical calculations for molecules with up to about 30 atoms, semi-empirical quantum mechanical calculations for systems with up to several hundred atoms, and force-field molecular dynamics studies of biomacromolecules with 10,000 atoms and more including surrounding solvent molecules. It can be anticipated that increased computational power will allow the treatment of larger systems of ever growing complexity. Due to the scaling of the computational requirements with increasing number of atoms, the force-field approaches will benefit the most from increased computational power. On the other hand, progress in methodologies such as density functional theory will enable us to treat larger systems on a fully quantum mechanical level and a combination of molecular dynamics and quantum mechanics can be envisioned. One of the greatest challenges in biomolecular computation is the protein folding problem. It is unclear at this point, if an approach with current methodologies will lead to a satisfactory answer or if unconventional, new approaches will be necessary. In any event, due to the complexity of biomolecular systems, a hierarchy of approaches will have to be established and used in order to capture the wide ranges of length-scales and time-scales involved in biological processes. In terms of hardware development, speed and power of computers will increase while the price/performance ratio will become more and more favorable. Parallelism can be anticipated to become an integral architectural feature in a range of computers. It is unclear at this point, how fast massively parallel systems will become easy enough to use so that new methodological developments can be pursued on such computers. Current trends show that distributed processing such as the combination of convenient graphics workstations and powerful general-purpose supercomputers will lead to a new style of computing in which the calculations are monitored and manipulated as they proceed. The combination of a numeric approach with artificial-intelligence approaches can be expected to open up entirely new possibilities. Ultimately, the most exciding aspect of the future in biomolecular computing will be the unexpected discoveries.     

Molecular dynamics study of polymeric chemical gels: Effect of persistence length and crosslinker density

Using molecular dynamics, we study the formation of chemical gels from an initial solution of reactive polymers that undergo a crosslinking reaction. We study the effect of the polymer persistence length and different densities of crosslinkers along the chains. As the reaction progresses, different structural features are identified in the system leading to the development of a percolated cluster. These features are (a) single strands, (b) double strands, and (c) bridges. We found that the total numbers of these three kinds of features are roughly independent of the persistence length; however, the average lengths of single and double strands grow with this variable. The average length of double strands strongly increases with increasing crosslinker density and the amount of single strands sharply falls as crosslinker density grows. We also found that general structural features of polymer networks are highly dependent on chain persistence length and crosslinker density. Fully flexible chains with high density of crosslinkers result in inhomogeneous network structures with large voids. In contrast, precursor chains with high rigidity and scarce number of crosslinkers result in homogeneous networks having small cavities. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 1343–1350     

Development of a multiplex system to assess DNA persistence in taphonomic studies

In this study, we have developed a PCR multiplex that can be used to assess DNA degradation and at the same time monitor for inhibition: primers have been designed to amplify human, pig, and rabbit DNA, allowing pig and rabbit to be used as experimental models for taphonomic research, but also enabling studies on human DNA persistence in forensic evidence. Internal amplified controls have been added to monitor for inhibition, allowing the effects of degradation and inhibition to be differentiated. Sequence data for single‐copy nuclear recombination activation gene (RAG‐1) from human, pig, and rabbit were aligned to identify conserved regions and primers were designed that targeted amplicons of 70, 194, 305, and 384 bp. Robust amplification in all three species was possible using as little as 0.3 ng of template DNA. These have been combined with primers that will amplify a bacterial DNA template within the PCR. The multiplex has been evaluated in a series of experiments to gain more knowledge of DNA persistence in soft tissues, which can be important when assessing what material to collect following events such as mass disasters or conflict, when muscle or bone material can be used to aid with the identification of human remains. The experiments used pigs as a model species. When whole pig bodies were exposed to the environment in Northwest England, DNA in muscle tissue persisted for over 24 days in the summer and over 77 days in the winter, with full profiles generated from these samples. In addition to time, accumulated degree days (ADD) were also used as a measure that combines both time and temperature—24 days was in summer equivalent to 295 ADD whereas 77 days in winter was equivalent to 494 ADD.     

Multidimensional tunneling dynamics of proton transfer in malonaldehyde molecule and its isotopomers

The twenty-one-dimensional Hamiltonian of malonaldehyde molecule and a number of its isotopomers (H/D, ¹³C/¹²C) was reconstructed in the low-energy region (<3000 cm^–1). Parameters of the Hamiltonian were obtained from quantum-chemical calculations of the energies, equilibrium geometries, and eigenvectors and eigenfrequencies of normal vibrations at the stationary points corresponding to the ground state and transition state. Despite substantial variation of the barrier height calculated using different quantum-chemical methods (from 2.8 to 10.3 kcal mol^–1), the corresponding potential energy surfaces can be matched with high accuracy by scaling only one parameter (the semiclassical parameter , which defines the scales of potential, energy, and action). Scaling invariance allows optimization of the Hamiltonian in such a way that the calculated ground-state tunneling splitting coincides with the experimental value. The corresponding potential barrier height is estimated at 4.34±0.4 kcal mol^–1. The quantum dynamics problem was solved using the perturbative instanton approach without reducing the number of degrees of freedom. The role of all transverse vibrations in proton tunneling is characterized. Vibration-tunneling spectrum is calculated for the ground state and low-lying excited states and mode-specific isotope effects are predicted.     

Protein structure prediction: combining de novo modeling with sparse experimental data

Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction.     

Determination of Enantiomer Ratios of Bornane Congeners in Biological Samples Using Heart-Cut Multidimensional Gas Chromatography

The enantiomeric ratios of the chlorinated bornanes, 2-exo, 5,5,9,9,10, 10-heptachlorobornane (B[20030]-(022)), 2-endo,3-exo,5-endo,6-exo,8, 8,10,10-octachlorobornane (B[12012]-(202), Parlar No. 26), 2-exo,3-endo,6-endo,8,9,10,10-heptachlorobornane (B[21001]-(112)), 2,2,5,5,9,9, 10,10-octachlorobornane (B[30030]-(022), Parlar No. 38), 2-endo,3-exo,5-endo6-exo,8,8,9,10,10-nonachlorobornane (B[12012]-(212), Parlar No. 50), and 2,2,5,5,8,9,9,10,10-nonachlorobornane (B[30030]-(122), Parlar No. 62) were determined in a hake liver (Merluccius merluccius) and in two whitebeaked dolphin blubber (Lagenorynchus albirostris) samples. The analysis was performed by heart-cut multidimensional gas chromatography using an electron capture detector (ECD). Ultra 2 (5%-phenyl-95%-methylsilicone) was used as stationary phase in the first column and enantioselectivity was obtained in the second column with a phase consisting of a mixture of OV-1701 and heptakis(2,3,6-O-tert- butyldimethylsilyl)-β-cyclodextrin (10 : 1). All reference standards were also tested on the enantioselective column alone. The comparison of the two systems showed that deviations of ±0.12 from the racemic enantiomer ratio can be observed for the single column due to co-eluting impurities which are present in the reference standards. In most of the heart-cut chromatograms of the biota samples about 15 peaks could be found, showing the importance of a multidimensional separation system for an interference-free quantification by ECD. In all biological samples a significant deviation from the racemic enantiomer ratio was found for B[30030]-(022) (Parlar No. 38) and for B[30030]-(122) (Parlar No. 62). This indicates that an enantioselective disposition of the congeners occurs. In addition, considerations are presented concerning the relationship between congener structure and enantiomeric disposition.     

An Electrochemical Biosensor Architecture Based on Protein Folding Supports Direct Real-Time Measurements in Whole Blood

The ability to monitor drug and biomarker concentrations in the body with high frequency and in real time would revolutionize our understanding of biology and our capacity to personalize medicine. The few in vivo molecular sensors that currently exist, however, all rely on the specific chemical or enzymatic reactivity of their targets and thus are not generalizable. In response, we demonstrate here an electrochemical sensing architecture based on binding-induced protein folding that is 1) independent of the reactivity of its targets, 2) reagentless, real-time, and with a resolution of seconds, and 3) selective enough to deploy in undiluted bodily fluids. As a proof of principle, we use the SH3 domain from human Fyn kinase to build a sensor that discriminates between the protein's peptide targets and responds rapidly and quantitatively even when challenged in whole blood. The resulting sensor architecture could drastically expand the chemical space accessible to continuous, real-time biosensors.     

Biased fragment distribution in MC simulation of protein folding

Monte Carlo (MC) methods play an important role in simulations of protein folding. These methods rely on a random sampling of moves on a potential energy surface. To improve the efficiency of the sampling, we propose a new selection of trial moves based on an empirical distribution of three-residue (triplet) conformations. This selection is compared to random combinations of the preferred conformations of the three amino acids, and it is shown that the new trial moves lead to finding structures closer to the native conformation.     

Amyloid Polymorphism in the Protein Folding and Aggregation Energy Landscape

Protein folding involves a large number of steps and conformations in which the folding protein samples different thermodynamic states characterized by local minima. Kinetically trapped on‐ or off‐pathway intermediates are metastable folding intermediates towards the lowest absolute energy minima, which have been postulated to be the natively folded state where intramolecular interactions dominate, and the amyloid state where intermolecular interactions dominate. However, this view largely neglects the rich polymorphism found within amyloid species. We review the protein folding energy landscape in view of recent findings identifying specific transition routes among different amyloid polymorphs. Observed transitions such as twisted ribbon→crystal or helical ribbon→nanotube, and forbidden transitions such helical ribbon?crystal, are discussed and positioned within the protein folding and aggregation energy landscape. Finally, amyloid crystals are identified as the ground state of the protein folding and aggregation energy landscape.     

Structural Stability of Azurin Encapsulated in Sol-Gel Glasses: A Fluorometric Study

In this study we investigated the structural features of azurin, a blue copper-containing enzyme, upon encapsulation in tetramethoxysilane derived sol-gel glasses. Fluorescence spectroscopy revealed that gelation of inorganic networks does not affect the protein tertiary structure and only after two months solvent phase loss altered protein stability. In case of organically modified sol-gel matrices, the protein stability was reduced after encapsulation into hosts modified by adding 3-Mercaptopropyl-trimethoxysilane, 3-Glycidyloxypropyl-trimethoxysilane and Trimethoxy octylsilane, while it was found to be enhanced in networks doped with 3-Trimethoxysilyl-propyl methacrylate and 3-Aminopropyl-trimethoxysilane. In order to better investigate the effects of silica glasses on azurin stability, unfolding experiments of the protein, in solution or entrapped, were also performed in the presence of both methanol and guanidinium hydrochloride (GdHCl). Our results suggest that the matrix protects azurin against the aggregation induced by alcohol, and that the free energy change value upon unfolding by GdHCl was lower than the value calculated for azurin in solution and was dependent on the surface chemistry of silica matrix.     

How Post‐Translational Modifications Influence Amyloid Formation: A Systematic Study of Phosphorylation and Glycosylation in Model Peptides

A reciprocal relationship between phosphorylation and O‐glycosylation has been reported for many cellular processes and human diseases. The accumulated evidence points to the significant role these post‐translational modifications play in aggregation and fibril formation. Simplified peptide model systems provide a means for investigating the molecular changes associated with protein aggregation. In this study, by using an amyloid‐forming model peptide, we show that phosphorylation and glycosylation can affect folding and aggregation kinetics differently. Incorporation of phosphoserines, regardless of their quantity and position, turned out to be most efficient in preventing amyloid formation, whereas O‐glycosylation has a more subtle effect. The introduction of a single β‐galactose does not change the folding behavior of the model peptide, but does alter the aggregation kinetics in a site‐specific manner. The presence of multiple galactose residues has an effect similar to that of phosphorylation.     

Predicting NMR Relaxation Rates in Anisotropically Tumbling Proteins through Networks of Coupled Rotators

We show that the prediction of ¹⁵N relaxation rates in proteins can be extended to systems with anisotropic global rotational diffusion by using a network of coupled rotators (NCR), starting from a three‐dimensional structure. The relaxation rates predicted by this method are confronted in several examples with experiments performed by other groups. The NCR spectral density functions are compared with the results obtained from reduced spectral density mapping. The consequence of the timescales of internal motions on the predicted relaxation rates and the effects of the predicted local anisotropy—present only in the case of anisotropic overall tumbling—on dynamic parameters, are discussed.