A Brownian dynamics study of the effects of cytochrome f structure and deletion of its small domain in interactions with cytochrome c6 and plastocyanin in Chlamydomonas reinhardtii

New Insights into the Evolution of the Electron Transfer from Cytochrome f to Photosystem I in the Green and Red Branches of Photosynthetic Eukaryotes

In cyanobacteria and most green algae of the eukaryotic green lineage, the copper-protein plastocyanin (Pc) alternatively replaces the heme-protein cytochrome c6 (Cc6) as the soluble electron carrier from cytochrome f (Cf) to photosystem I (PSI). The functional and structural equivalence of 'green' Pc and Cc6 has been well established, representing an example of convergent evolution of two unrelated proteins. However, plants only produce Pc, despite having evolved from green algae. On the other hand, Cc6 is the only soluble donor available in most species of the red lineage of photosynthetic organisms, which includes, among others, red algae and diatoms. Interestingly, Pc genes have been identified in oceanic diatoms, probably acquired by horizontal gene transfer from green algae. However, the mechanisms that regulate the expression of a functional Pc in diatoms are still unclear. In the green eukaryotic lineage, the transfer of electrons from Cf to PSI has been characterized in depth. The conclusion is that in the green lineage, this process involves strong electrostatic interactions between partners, which ensure a high affinity and an efficient electron transfer (ET) at the cost of limiting the turnover of the process. In the red lineage, recent kinetic and structural modeling data suggest a different strategy, based on weaker electrostatic interactions between partners, with lower affinity and less efficient ET, but favoring instead the protein exchange and the turnover of the process. Finally, in diatoms the interaction of the acquired green-type Pc with both Cf and PSI may not yet be optimized.

Classification of protein-protein association rates based on biophysical informatics

BACKGROUND

Proteins form various complexes to carry out their versatile functions in cells. The dynamic properties of protein complex formation are mainly characterized by the association rates which measures how fast these complexes can be formed. It was experimentally observed that the association rates span an extremely wide range with over ten orders of magnitudes. Identification of association rates within this spectrum for specific protein complexes is therefore essential for us to understand their functional roles.

RESULTS

To tackle this problem, we integrate physics-based coarse-grained simulations into a neural-network-based classification model to estimate the range of association rates for protein complexes in a large-scale benchmark set. The cross-validation results show that, when an optimal threshold was selected, we can reach the best performance with specificity, precision, sensitivity and overall accuracy all higher than 70%. The quality of our cross-validation data has also been testified by further statistical analysis. Additionally, given an independent testing set, we can successfully predict the group of association rates for eight protein complexes out of ten. Finally, the analysis of failed cases suggests the future implementation of conformational dynamics into simulation can further improve model.

CONCLUSIONS

In summary, this study demonstrated that a new modeling framework that combines biophysical simulations with bioinformatics approaches is able to identify protein-protein interactions with low association rates from those with higher association rates. This method thereby can serve as a useful addition to a collection of existing experimental approaches that measure biomolecular recognition.

Understanding the Impacts of Conformational Dynamics on the Regulation of Protein-Protein Association by a Multiscale Simulation Method

Complexes formed among diverse proteins carry out versatile functions in nearly all physiological processes. Association rates which measure how fast proteins form various complexes are of fundamental importance to characterize their functions. The association rates are not only determined by the energetic features at binding interfaces of a protein complex but also influenced by the intrinsic conformational dynamics of each protein in the complex. Unfortunately, how this conformational effect regulates protein association has never been calibrated on a systematic level. To tackle this problem, we developed a multiscale strategy to incorporate the information on protein conformational variations from Langevin dynamic simulations into a kinetic Monte Carlo algorithm of protein-protein association. By systematically testing this approach against a large-scale benchmark set, we found the association of a protein complex with a relatively rigid structure tends to be reduced by its conformational fluctuations. With specific examples, we further show that higher degrees of structural flexibility in various protein complexes can facilitate the searching and formation of intermolecular interactions and thereby accelerate their associations. In general, the integration of conformational dynamics can improve the correlation between experimentally measured association rates and computationally derived association probabilities. Finally, we analyzed the statistical distributions of different secondary structural types on protein-protein binding interfaces and their preference to the change of association rates. Our study, to the best of our knowledge, is the first computational method that systematically estimates the impacts of protein conformational dynamics on protein-protein association. It throws lights on the molecular mechanisms of how protein-protein recognition is kinetically modulated.

Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association

The formation of functionally versatile protein complexes underlies almost every biological process. The estimation of how fast these complexes can be formed has broad implications for unravelling the mechanism of biomolecular recognition. This kinetic property is traditionally quantified by association rates, which can be measured through various experimental techniques. To complement these time-consuming and labor-intensive approaches, we developed a coarse-grained simulation approach to study the physical processes of protein–protein association. We systematically calibrated our simulation method against a large-scale benchmark set. By combining a physics-based force field with a statistically-derived potential in the simulation, we found that the association rates of more than 80% of protein complexes can be correctly predicted within one order of magnitude relative to their experimental measurements. We further showed that a mixture of force fields derived from complementary sources was able to describe the process of protein–protein association with mechanistic details. For instance, we show that association of a protein complex contains multiple steps in which proteins continuously search their local binding orientations and form non-native-like intermediates through repeated dissociation and re-association. Moreover, with an ensemble of loosely bound encounter complexes observed around their native conformation, we suggest that the transition states of protein–protein association could be highly diverse on the structural level. Our study also supports the idea in which the association of a protein complex is driven by a “funnel-like” energy landscape. In summary, these results shed light on our understanding of how protein–protein recognition is kinetically modulated, and our coarse-grained simulation approach can serve as a useful addition to the existing experimental approaches that measure protein–protein association rates.

Comparative analysis of plastocyanin-cytochrome f complex formation in higher plants, green algae and cyanobacteria

Mechanisms of the complex formation between plastocyanin and cytochrome f in higher plants (Spinacia oleracea and Brassica rapa), green microalgae Chlamydomonas reinhardtii and two species of cyanobacteria (Phormidium laminosum and Nostoc sp.) were investigated using combined Brownian and molecular dynamics simulations and hierarchical cluster analysis. In higher plants and green algae, electrostatic interactions force plastocyanin molecule close to the heme of cytochrome f. In the subsequent rotation of plastocyanin molecule around the point of electrostatic contact in the vicinity of cytochrome f, copper (Cu) atom approaches cytochrome heme forming a stable configuration where cytochrome f molecule behaves as a rather rigid body without conformational changes. In Nostoc plastocyanin molecule approaches cytochrome f in a different orientation (head-on) where the stabilization of the plastocyanin-cytochrome f complex is accompanied by the conformational changes of the G188E189D190 loop that stabilizes the whole complex. In cyanobacterium P. laminosum, electrostatic preorientation of the approaching molecules was not detected, thus indicating that random motions rather than long-range electrostatic interactions are responsible for the proper mutual orientation. We demonstrated that despite the structural similarity of the investigated electron transport proteins in different photosynthetic organisms, the complexity of molecular mechanisms of the complex formation increases in the following sequence: non-heterocystous cyanobacteria - heterocystous cyanobacteria - green algae - flowering plants.

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Redox regulation in the thylakoid lumen

Higher plants need to balance the efficiency of light energy absorption and dissipative photo-protection when exposed to fluctuations in light quantity and quality. This aim is partially realized through redox regulation within the chloroplast, which occurs in all chloroplast compartments except the envelope intermembrane space. In contrast to the chloroplast stroma, less attention has been paid to the thylakoid lumen, an inner, continuous space enclosed by the thylakoid membrane in which redox regulation is also essential for photosystem biogenesis and function. This sub-organelle compartment contains at least 80 lumenal proteins, more than 30 of which are known to contain disulfide bonds. Thioredoxins (Trx) in the chloroplast stroma are photo-reduced in the light, transferring reducing power to the proteins in the thylakoid membrane and ultimately the lumen through a trans-thylakoid membrane-reduced, equivalent pathway. The discovery of lumenal thiol oxidoreductase highlights the importance of the redox regulation network in the lumen for controlling disulfide bond formation, which is responsible for protein activity and folding and even plays a role in photo-protection. In addition, many lumenal members involved in photosystem assembly and non-photochemical quenching are likely required for reduction and/or oxidation to maintain their proper efficiency upon changes in light intensity. In light of recent findings, this review summarizes the multiple redox processes that occur in the thylakoid lumen in great detail, highlighting the essential auxiliary roles of lumenal proteins under fluctuating light conditions.

Ionic strength dependence of F-actin and glycolytic enzyme associations: a Brownian dynamics simulations approach

The association of glycolytic enzymes with F-actin is proposed to be one mechanism by which these enzymes are compartmentalized, and, as a result, may possibly play important roles for: regulation of the glycolytic pathway, potential substrate channeling, and increasing glycolytic flux. Historically, in vitro experiments have shown that many enzyme/actin interactions are dependent on ionic strength. Herein, Brownian dynamics (BD) examines how ionic strength impacts the energetics of the association of F-actin with the glycolytic enzymes: lactate dehydrogenase (LDH), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), fructose-1,6-bisphosphate aldolase (aldolase), and triose phosphate isomerase (TPI). The BD simulations are steered by electrostatics calculated by Poisson-Boltzmann theory. The BD results confirm experimental observations that the degree of association diminishes as ionic strength increases but also suggest that these interactions are significant, at physiological ionic strengths. Furthermore, BD agrees with experiments that muscle LDH, aldolase, and GAPDH interact significantly with F-actin whereas TPI does not. BD indicates similarities in binding regions for aldolase and LDH among the different species investigated. Furthermore, the residues responsible for salt bridge formation in stable complexes persist as ionic strength increases. This suggests the importance of the residues determined for these binary complexes and specificity of the interactions. That these interactions are conserved across species, and there appears to be a general trend among the enzymes, support the importance of these enzyme-F-actin interactions in creating initial complexes critical for compartmentation.

Predicting kinetic constants of protein-protein interactions based on structural properties

Elucidating kinetic processes of protein-protein interactions (PPI) helps to understand how basic building blocks affect overall behavior of living systems. In this study, we used structure-based properties to build predictive models for kinetic constants of PPI. A highly diverse PPI dataset, protein-protein kinetic interaction data and structures (PPKIDS), was built. PPKIDS contains 62 PPI with complex structures and kinetic constants measured experimentally. The influence of structural properties on kinetics of PPI was studied using 35 structure-based features, describing different aspects of complex structures. Linear models for the prediction of kinetic constants were built by fitting with selected subsets of structure-based features. The models gave correlation coefficients of 0.801, 0.732, and 0.770 for k(off), k(on), and K(d), respectively, in leave-one-out cross validations. The predictive models reported here use only protein complex structures as input and can be generally applied in PPI studies as well as systems biology modeling. Our study confirmed that different properties play different roles in the kinetic process of PPI. For example, k(on) was affected by overall structural features of complexes, such as the composition of secondary structures, the change of translational and rotational entropy, and the electrostatic interaction; while k(off) was determined by interfacial properties, such as number of contacted atom pairs per 100 Ų. This information provides useful hints for PPI design.

Electrostatic strain and concerted motions in the transient complex between plastocyanin and cytochrome f from the cyanobacterium Phormidium laminosum

Many fleeting macromolecular interactions, like those being involved in electron transport, are essential in biology. However, little is known about the behaviour of the partners and their dynamics within their short-lived complex. To tackle such issue, we have performed molecular dynamics simulations on an electron transfer complex formed by plastocyanin and cytochrome f from the cyanobacterium Phormidium laminosum. Besides simulations of the isolated partners, two independent trajectories of the complex were calculated, starting from the two different conformations in the NMR ensemble. The first one leads to a more stable ensemble with a shorter distance between the metal sites of the two partners. The second experiences a significant drift of the complex conformation. Analyses of the distinct calculations show that the conformation of cytochrome f is strained upon binding of its partner, and relaxes upon its release. Interestingly, the principal component analysis of the trajectories indicates that plastocyanin displays a concerted motion with the small domain of cytochrome f that can be attributed to electrostatic interactions between the two proteins.

Investigating the mechanisms of photosynthetic proteins using continuum electrostatics

Computational methods based on continuum electrostatics are widely used in theoretical biochemistry to analyze the function of proteins. Continuum electrostatic methods in combination with quantum chemical and molecular mechanical methods can help to analyze even very complex biochemical systems. In this article, applications of these methods to proteins involved in photosynthesis are reviewed. After giving a short introduction to the basic concepts of the continuum electrostatic model based on the Poisson-Boltzmann equation, we describe the application of this approach to the docking of electron transfer proteins, to the comparison of isofunctional proteins, to the tuning of absorption spectra, to the analysis of the coupling of electron and proton transfer, to the analysis of the effect of membrane potentials on the energetics of membrane proteins, and to the kinetics of charge transfer reactions. Simulations as those reviewed in this article help to analyze molecular mechanisms on the basis of the structure of the protein, guide new experiments, and provide a better and deeper understanding of protein functions.

A Brownian Dynamics computational study of the interaction of spinach plastocyanin with turnip cytochrome f: the importance of plastocyanin conformational changes

Brownian Dynamics (BD) computer simulations were used to study electrostatic interactions between turnip cytochrome f (cyt f) and spinach plastocyanin (PC). Three different spinach PC structures were studied: The X-ray crystal structure of Xue and coworkers [(1998) Protein Sci 7:2099-2105] and the NMR structure of Musiani et al. [(2005) J Biol Chem 280:18833-18841] and Ubbink and co-workers [(1998) Structure 6:323-335]. Significant differences exist in the backbone conformation between the PC taken from Ubbink and coworkers and the other two PC structures particularly the regions surrounding G10, E59-E60, and D51. Complexes formed in BD simulations using the PC of Ubbink and colleagues had a smaller Cu-Fe distance than the other two. These results suggest that different PC conformations may exist in solution with different capabilities of forming electron-transfer-active docks. All three types of complexes show electrostatic contacts between D42, E43, and D44 on PC and K187 on cyt f as well as between E59 on PC and K58 on cyt f. However, the PC of Ubbink and coworkers reveals additional contacts between D51 and cyt f as a result of the difference in backbone configuration. A second minor complex component was observed for the PC of Ubbink and co-workers and Xue and co-workers which had contacts between K187 on cyt f and E59 and E60 on PC rather than between K187 on cyt f and D42-D44 on PC as observed for the major components. This second type of complex may represent an earlier complex which rearranges to form a final complex capable of electron transfer.

A Brownian dynamics study of the interactions of the luminal domains of the cytochrome b6f complex with plastocyanin and cytochrome c6: the effects of the Rieske FeS protein on the interactions

The availability of the structures of the cytochrome b6f complex (cyt b6f), plastocyanin (PC), and cytochrome c6 (cyt c6) from Chlamydomonas reinhardtii allowed us, for the first time, to model electron transfer interactions between the luminal domains of this complex (including cyt f and the Rieske FeS protein) and its redox partners in the same species. We also generated a model structure in which the FeS center of the Rieske protein was positioned closer to the heme of cyt f than observed in the crystal structure and studied its interactions with both PC and cyt c6. Our data showed that the Rieske protein in both the original crystal structure and in our modeled structure of the cyt b6f complex did not physically interfere with binding position or orientation of PC or cyt c6 on cyt f. PC docked on cyt f with the same orientation in the presence or the absence of the Rieske protein, which matched well with the previously reported NMR structures of complexes between cyt f and PC. When the FeS center of the Rieske protein was moved close to the heme of cyt f, it even enhanced the interaction rates. Studies using a cyt f modified in the 184-191 loop showed that the cyt f structure is a more important factor in determining the rate of complex formations than is the presence or the absence of the Rieske protein or its position with respect to cyt f.