Biomolecular diffusional association

The primary method for the computational study of biomolecular diffusional association is Brownian dynamics. Recent work has seen advances in the efficiency of computing association rates and in the accuracy of simulation models. New areas to which Brownian dynamics has been applied include protein polymerisation and protein adsorption to a surface. There has recently been particularly intense study of protein-protein association, and Brownian dynamics, together with other theoretical and experimental approaches, has led to new insights into the determinants of protein-protein binding kinetics.     

Limitations of Time-Resolved Fluorescence Suggested by Molecular Simulations: Assessing the Dynamics of T?cell Receptor Binding Loops

Time-resolved fluorescence anisotropy (TRFA) has a rich history in evaluating protein dynamics. Yet as often employed, TRFA assumes that the motional properties of a covalently tethered fluorescent probe accurately portray the motional properties of the protein backbone at the probe attachment site. In an extensive survey using TRFA to study the dynamics of the binding loops of a αβ T cell receptor, we observed multiple discrepancies between the TRFA data and previously published results that led us to question this assumption. We thus simulated several of the experimentally probed systems using a protocol that permitted accurate determination of probe and protein time correlation functions. We found excellent agreement in the decays of the experimental and simulated correlation functions. However, the motional properties of the probe were poorly correlated with those of the backbone of both the labeled and unlabeled protein. Our results warrant caution in the interpretation of TRFA data and suggest further studies to ascertain the extent to which probe dynamics reflect those of the protein backbone. Meanwhile, the agreement between experiment and computation validates the use of molecular dynamics simulations as an accurate tool for exploring the molecular motion of T cell receptors and their binding loops.     

Hydrophobic core mutations in CI2 globally perturb fast side-chain dynamics similarly without regard to position

Protein dynamics is currently an area of intense research because of its importance as complementary information to the huge quantity of available data relating protein structure and function. Because it is usually the influence of dynamics on function that is studied, the physical determinants of the distribution of flexibility in proteins have not been explored as thoroughly. In the present NMR study, an expanded suite of five (2)H relaxation experiments was used to characterize the picosecond-to-nanosecond side-chain dynamics of chymotrypsin inhibitor 2 (CI2) and five hydrophobic core mutants, some of which are members of the folding nucleus. Because CI2 is a homologue of the serine protease inhibitor eglin c, which has already been extensively characterized in terms of its dynamics, it was possible to compare not only side-chain dynamics but also the responses of these dynamics to analogous mutations. Remarkably, each of the five core mutations in CI2 led to similar and reproducible increases in side-chain flexibility throughout the entire structure. Although the expanded suite of (2)H relaxation experiments does not affect model selection for the vast majority of residues, it did enable the detection of increasing levels of nanosecond-scale motions in CI2's reactive site binding loop as the L68 side chain was progressively shortened by mutation. Collectively, we observed that the CI2 mutants are more dynamically similar to each other than to the more rigid wild-type CI2, from which we propose that wild-type CI2 has been optimized to a specific level of rigidity which may aid in its function as a serine protease inhibitor. We also observed that the pattern of side-chain dynamics of CI2 is quantitatively similar to eglin c, but that this similarity is lost upon mutating both proteins at an equivalent position. Finally, (15)N relaxation was used to characterize the backbone dynamics of wild-type and mutant CI2. Interestingly, mutation at folding nucleus positions led to widespread increases in backbone flexibility, whereas non-folding-nucleus positions led to increases in flexibility in the C-terminal half of the protein only.     

How much can physics do for protein design?

Physics and physical chemistry are an important thread in computational protein design, complementary to knowledge-based tools. They provide molecular mechanics scoring functions that need little or no ad hoc parameter readjustment, methods to thoroughly sample equilibrium ensembles, and different levels of approximation for conformational flexibility. They led recently to the successful redesign of a small protein using a physics-based folded state energy. Adaptive Monte Carlo or molecular dynamics schemes were discovered where protein variants are populated as per their ligand-binding free energy or catalytic efficiency. Molecular dynamics have been used for backbone flexibility. Implicit solvent models have been refined, polarizable force fields applied, and many physical insights obtained.     

Structure,function, and regulation of mitofusin‐2 in health and disease

Mitochondria are highly dynamic organelles that constantly migrate, fuse, and divide to regulate their shape, size, number, and bioenergetic function. Mitofusins (Mfn1/2), optic atrophy 1 (OPA1), and dynamin‐related protein 1 (Drp1), are key regulators of mitochondrial fusion and fission. Mutations in these molecules are associated with severe neurodegenerative and non‐neurological diseases pointing to the importance of functional mitochondrial dynamics in normal cell physiology. In recent years, significant progress has been made in our understanding of mitochondrial dynamics, which has raised interest in defining the physiological roles of key regulators of fusion and fission and led to the identification of additional functions of Mfn2 in mitochondrial metabolism, cell signalling, and apoptosis. In this review, we summarize the current knowledge of the structural and functional properties of Mfn2 as well as its regulation in different tissues, and also discuss the consequences of aberrant Mfn2 expression.     

Specificity and evolvability in eukaryotic protein interaction networks

Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10⁻⁵ interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10³ interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.     

Regulation of mitochondrial morphology and function by O-GlcNAcylation in neonatal cardiac myocytes

Mitochondria are crucial organelles in cell life serving as a source of energy production and as regulators of Ca(2+) homeostasis, apoptosis, and development. Mitochondria frequently change their shape by fusion and fission, and recent research on these morphological dynamics of mitochondria has highlighted their role in normal cell physiology and disease. In this study, we investigated the effect of high glucose on mitochondrial dynamics in neonatal cardiac myocytes (NCMs). High-glucose treatment of NCMs significantly decreased the level of optical atrophy 1 (OPA1) (mitochondrial fusion-related protein) protein expression. NCMs exhibit two different kinds of mitochondrial structure: round shape around the nuclear area and elongated tubular structures in the pseudopod area. High-glucose-treated NCMs exhibited augmented mitochondrial fragmentation in the pseudopod area. This effect was significantly decreased by OPA1 overexpression. High-glucose exposure also led to increased O-GlcNAcylation of OPA1 in NCMs. GlcNAcase (GCA) overexpression in high-glucose-treated NCMs decreased OPA1 protein O-GlcNAcylation and significantly increased mitochondrial elongation. In addition to the morphological change caused by high glucose, we observed that high glucose decreased mitochondrial membrane potential and complex IV activity and that OPA1 overexpression increased both levels to the control level. These data suggest that decreased OPA1 protein level and increased O-GlcNAcylation of OPA1 protein by high glucose lead to mitochondrial dysfunction by increasing mitochondrial fragmentation, decreasing mitochondrial membrane potential, and attenuating the activity of mitochondrial complex IV, and that overexpression of OPA1 and GCA in cardiac myocytes may help improve the cardiac dysfunction in diabetes.     

Extending the New Generation of Structure Predictors to Account for Dynamics and Allostery

Recent progress in structure-prediction methods that rely on deep learning suggests that the atomic structure of almost any protein may soon be predictable directly from its amino acid sequence. This much-awaited revolution was driven by substantial improvements in the reliability of methods for inferring the spatial distances between amino acid pairs from an analysis of homologous sequences. Improved reliability has been accompanied, however, by a reduced ability to detect amino acid relationships that are not due to direct spatial contacts, such as those that arise from protein dynamics or allostery. Given the central importance of dynamics and allostery to protein activity, we argue that an important future advance would extend modeling beyond predicting a single static structure. Here, we briefly review some of the developments that have led to the remarkable recent achievement in structure prediction and speculate what methods and sources of information may be leveraged in the future to develop a modeling framework that addresses protein dynamics and allostery.     

A fast inverse dynamics model of walking for use in optimisation studies

Computer simulation of human gait, based on measured motion data, is a well-established technique in biomechanics. However, optimisation studies requiring many iterative gait cycle simulations have not yet found widespread application because of their high computational cost. Therefore, a computationally efficient inverse dynamics model of 3D human gait has been designed and compared with an equivalent model, created using a commercial multi-body dynamics package. The fast inverse dynamics model described in this paper led to an eight fold increase in execution speed. Sufficient detail is provided to allow readers to implement the model themselves.     

Exploring the role of structure and dynamics in the function of chymotrypsin inhibitor 2

Increasing awareness of the possible role of internal dynamics in protein function has led to the development of new methods for experimentally characterizing protein dynamics across multiple time scales, especially using NMR spectroscopy. A few analyses of the conformational dynamics of proteins ranging from nonallosteric single domains to multidomain allosteric enzymes are now available; however, demonstrating a connection between dynamics and function remains difficult on account of the comparative lack of studies examining both changes in dynamics and changes in function in response to the same perturbations. In previous work, we characterized changes in structure and dynamics on the ps–ns time scale resulting from hydrophobic core mutations in chymotrypsin inhibitor 2 and found that there are moderate, persistent global changes in dynamics in the absence of gross structural changes (Whitley et al., Biochemistry 2008;47:8566–8576). Here, we assay those and additional mutants for inhibitory ability toward the serine proteases elastase and chymotrypsin to determine the effects of mutation on function. Results indicate that core mutation has only a subtle effect on CI2 function. Using chemical shifts, we also studied the effect of complex formation on CI2 structure and found that perturbations are greatest at the complex interface but also propagate toward CI2's hydrophobic core. The structure–dynamics–function data set completed here suggests that dynamics plays a limited role in the function of this small model system, although we do observe a correlation between nanosecond-scale reactive loop motions and inhibitory ability for mutations at one key position in the hydrophobic core.     

Functional modes and residue flexibility control the anisotropic response of guanylate kinase to mechanical stress

The coupling between the mechanical properties of enzymes and their biological activity is a well-established feature that has been the object of numerous experimental and theoretical works. In particular, recent experiments show that enzymatic function can be modulated anisotropically by mechanical stress. We study such phenomena using a method for investigating local flexibility on the residue scale that combines a reduced protein representation with Brownian dynamics simulations. We performed calculations on the enzyme guanylate kinase to study its mechanical response when submitted to anisotropic deformations. The resulting modifications of the protein's rigidity profile can be related to the changes in substrate binding affinity observed experimentally. Further analysis of the principal components of motion of the trajectories shows how the application of a mechanical constraint on the protein can disrupt its dynamics, thus leading to a decrease of the enzyme's catalytic rate. Eventually, a systematic probe of the protein surface led to the prediction of potential hotspots where the application of an external constraint would produce a large functional response both from the mechanical and dynamical points of view. Such enzyme-engineering approaches open the possibility to tune catalytic function by varying selected external forces.     

Computationally guided identification of Akt-3, a serine/threonine kinase inhibitors: Insights from homology modelling,structure-based screening,molecular dynamics and quantum mechanical calculations

Abstract

Chemical entities targeting kinase signalling pathways serve as a potential strategy to combat malignancies. Protein Kinase B or Akt is a validated target for various malignancies and Akt3 remains the least explored isoform among all its isoforms. Initially, homology modelling technique was used for generating protein structure and further validation was performed using molecular dynamics simulation and Ramachandran plot. The validated protein structure was then subjected for active site analysis which led to identification of active site residues based on metrics provided by site score. The important residues in binding site were identified as Thr81, Asp271 and Asp289 for binding energetics and inhibition. Subsequently, virtual screening methodologies were used for identification of novel hits for inhibition of Protein Kinase B or Akt3. This led to the identification of two hits, i.e. thiophene derivative and thieno-pyridine derivative which were selected on the basis of their binding affinity and drug likeliness. These identified hits were subjected for molecular dynamics simulations, quantum mechanical and synthetic accessibility studies. The role of crucial residues in binding site stood validated as suggested by molecular dynamics simulations studies.

Communicated by Ramaswamy H. Sarma     

Coarse-grained normal mode analysis in structural biology

The realization that experimentally observed functional motions of proteins can be predicted by coarse-grained normal mode analysis has renewed interest in applications to structural biology. Notable applications include the prediction of biologically relevant motions of proteins and supramolecular structures driven by their structure-encoded collective dynamics; the refinement of low-resolution structures, including those determined by cryo-electron microscopy; and the identification of conserved dynamic patterns and mechanically key regions within protein families. Additionally, hybrid methods that couple atomic simulations with deformations derived from coarse-grained normal mode analysis are able to sample collective motions beyond the range of conventional molecular dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.     

Mitochondrial DNA ligase function in Saccharomyces cerevisiae

The Saccharomyces cerevisiae CDC9 gene encodes a DNA ligase protein that is targeted to both the nucleus and the mitochondria. While nuclear Cdc9p is known to play an essential role in nuclear DNA replication and repair, its role in mitochondrial DNA dynamics has not been defined. It is also unclear whether additional DNA ligase proteins are present in yeast mitochondria. To address these issues, mitochondrial DNA ligase function in S.cerevisiae was analyzed. Biochemical analysis of mitochondrial protein extracts supported the conclusion that Cdc9p was the sole DNA ligase protein present in this organelle. Inactivation of mitochondrial Cdc9p function led to a rapid decline in cellular mitochondrial DNA content in both dividing and stationary yeast cultures. In contrast, there was no apparent defect in mitochondrial DNA dynamics in a yeast strain deficient in Dnl4p (Deltadnl4). The Escherichia coli ECO:RI endonuclease was targeted to yeast mitochondria. Transient expression of this recombinant ECO:RI endonuclease led to the formation of mitochondrial DNA double-strand breaks. While wild-type and Deltadnl4 yeast were able to rapidly recover from this mitochondrial DNA damage, clones deficient in mitochondrial Cdc9p were not. These results support the conclusion that yeast rely upon a single DNA ligase, Cdc9p, to carry out mitochondrial DNA replication and recovery from both spontaneous and induced mitochondrial DNA damage.     

Cytosolic aggregates in presence of non‐translocated proteins perturb endoplasmic reticulum structure and dynamics

Presence of cytosolic protein aggregates and membrane damage are two common attributes of neurodegenerative diseases. These aggregates delay degradation of non‐translocated protein precursors leading to their persistence and accumulation in the cytosol. Here, we find that cells with intracellular protein aggregates (of cytosolic prion protein or huntingtin) destabilize the endoplasmic reticulum (ER) morphology and dynamics when non‐translocated protein load is high. This affects trafficking of proteins out from the ER, relative distribution of the rough and smooth ER and three‐way junctions that are essential for the structural integrity of the membrane network. The changes in ER membranes may be due to high aggregation tendency of the ER structural proteins—reticulons, and altered distribution of those associated with the three‐way ER junctions—Lunapark. Reticulon4 is seen to be enriched in the aggregate fractions in presence of non‐translocated protein precursors. This could be mitigated by improving signal sequence efficiencies of the proteins targeted to the ER. These were observed using PrP variants and the seven‐pass transmembrane protein (CRFR1) with different signal sequences that led to diverse translocation efficiencies. This identifies a previously unappreciated consequence of cytosolic aggregates on non‐translocated precursor proteins—their persistent presence affects ER morphology and dynamics. This may be one of the ways in which cytosolic aggregates can affect endomembranes during neurodegenerative disease.     

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities.     

Cellular organization by self-organization: mechanisms and models for Min protein dynamics

We use the oscillating Min proteins of Escherichia coli as a prototype system to illustrate the current state and potential of modeling protein dynamics in space and time. We demonstrate how a theoretical approach has led to striking new insights into the mechanisms of self-organization in bacterial cells and indicate how these ideas may be applicable to more complex structure formation in eukaryotic cells.     

Consequences of depletion of the signal recognition particle in Escherichia coli

Thus far, the role of the Escherichia coli signal recognition particle (SRP) has only been studied using targeted approaches. It has been shown for a handful of cytoplasmic membrane proteins that their insertion into the cytoplasmic membrane is at least partially SRP-dependent. Furthermore, it has been proposed that the SRP plays a role in preventing toxic accumulation of mistargeted cytoplasmic membrane proteins in the cytoplasm. To complement the targeted studies on SRP, we have studied the consequences of the depletion of the SRP component Fifty-four homologue (Ffh) in E. coli using a global approach. The steady-state proteomes and the proteome dynamics were evaluated using one- and two-dimensional gel analysis, followed by mass spectrometry-based protein identification and immunoblotting. Our analysis showed that depletion of Ffh led to the following: (i) impaired kinetics of the biogenesis of the cytoplasmic membrane proteome; (ii) lowered steady-state levels of the respiratory complexes NADH dehydrogenase, succinate dehydrogenase, and cytochrome bo(3) oxidase and lowered oxygen consumption rates; (iii) increased levels of the chaperones DnaK and GroEL at the cytoplasmic membrane; (iv) a σ(32) stress response and protein aggregation in the cytoplasm; and (v) impaired protein synthesis. Our study shows that in E. coli SRP-mediated protein targeting is directly linked to maintaining protein homeostasis and the general fitness of the cell.     

XMAP215: a key component of the dynamic microtubule cytoskeleton

Microtubules are essential for various cellular processes including cell division and intracellular organization. Their function depends on their ability to rearrange their distribution at different times and places. Microtubules are dynamic polymers and their behaviour is described as dynamic instability. Rearrangement of the microtubule cytoskeleton is made possible by proteins that modulate the parameters of dynamic instability. Studies using Xenopus egg extracts led to identification of a microtubule-associated protein called XMAP215 as a major regulator of physiological microtubule dynamics. XMAP215 belongs to an evolutionarily conserved protein family present in organisms ranging from yeast to mammals. Together with members of the Kin I family of kinesins, XMAP215 and its orthologues form an essential circuit for generating dynamic microtubules in vivo.