Downhill binding energy surface of the barnase-barstar complex

Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD

The dissociation rate, or its reciprocal, the residence time (τ), is a crucial parameter for understanding the duration and biological impact of biomolecular interactions. Accurate prediction of τ is essential for understanding protein-protein interactions (PPIs) and identifying potential drug targets or modulators for tackling diseases. Conventional molecular dynamics simulation techniques are inherently constrained by their limited timescales, making it challenging to estimate residence times, which typically range from minutes to hours. Building upon its successful application in protein-small molecule systems, τ-Random Acceleration Molecular Dynamics (τRAMD) is here investigated for estimating dissociation rates of protein-protein complexes. τRAMD enables the observation of unbinding events on the nanosecond timescale, facilitating rapid and efficient computation of relative residence times. We tested this methodology for three protein-protein complexes and their extensive mutant datasets, achieving good agreement between computed and experimental data. By combining τRAMD with MD-IFP (Interaction Fingerprint) analysis, dissociation mechanisms were characterized and their sensitivity to mutations investigated, enabling the identification of molecular hotspots for selective modulation of dissociation kinetics. In conclusion, our findings underscore the versatility of τRAMD as a simple and computationally efficient approach for computing relative protein-protein dissociation rates and investigating dissociation mechanisms, thereby aiding the design of PPI modulators.

Structural and Functional Differences between Homologous Bacterial Ribonucleases

Small cationic guanyl-preferring ribonucleases (RNases) produced by the Bacillus species share a similar protein tertiary structure with a high degree of amino acid sequence conservation. However, they form dimers that differ in conformation and stability. Here, we have addressed the issues (1) whether the homologous RNases also have distinctions in catalytic activity towards different RNA substrates and interactions with the inhibitor protein barstar, and (2) whether these differences correlate with structural features of the proteins. Circular dichroism and dynamic light scattering assays revealed distinctions in the structures of homologous RNases. The activity levels of the RNases towards natural RNA substrates, as measured spectrometrically by acid-soluble hydrolysis products, were similar and decreased in the row high-polymeric RNA >>> transport RNA > double-stranded RNA. However, stopped flow kinetic studies on model RNA substrates containing the guanosine residue in a hairpin stem or a loop showed that the cleavage rates of these enzymes were different. Moreover, homologous RNases were inhibited by the barstar with diverse efficiency. Therefore, minor changes in structure elements of homologous proteins have a potential to significantly effect molecule stability and functional activities, such as catalysis or ligand binding.

A critical perspective on Markov state model treatments of protein-protein association using coarse-grained simulations

Atomic-level information is essential to explain the specific interactions governing protein–protein recognition in terms of structure and dynamics. Of particular interest is a characterization of the time-dependent kinetic aspects of protein–protein association and dissociation. A powerful framework to characterize the dynamics of complex molecular systems is provided by Markov State Models (MSMs). The central idea is to construct a reduced stochastic model of the full system by defining a set of conformational featured microstates and determining the matrix of transition probabilities between them. While a MSM framework can sometimes be very effective, different combinations of input featurization and simulation methods can significantly affect the robustness and the quality of the information generated from MSMs in the context of protein association. Here, a systematic examination of a variety of MSMs methodologies is undertaken to clarify these issues. To circumvent the uncertainties caused by sampling issues, we use a simplified coarse-grained model of the barnase–barstar protein complex. A sensitivity analysis is proposed to identify the microstates of an MSM that contribute most to the error in conjunction with the transition-based reweighting analysis method for a more efficient and accurate MSM construction.

Exploring the Free-Energy Landscape and Thermodynamics of Protein-Protein Association

We report the free-energy landscape and thermodynamics of the protein-protein association responsible for the drug-induced multimerization of HIV-1 integrase (IN). Allosteric HIV-1 integrase inhibitors promote aberrant IN multimerization by bridging IN-IN intermolecular interactions. However, the thermodynamic driving forces and kinetics of the multimerization remain largely unknown. Here, we explore the early steps in the IN multimerization by using umbrella sampling and unbiased molecular dynamics simulations in explicit solvent. In direct simulations, the two initially separated dimers spontaneously associate to form near-native complexes that resemble the crystal structure of the aberrant tetramer. Most strikingly, the effective interaction of the protein-protein association is very short-ranged: the two dimers associate rapidly within tens of nanoseconds when their binding surfaces are separated by d ≤ 4.3 Å (less than two water diameters). Beyond this distance, the oligomerization kinetics appears to be diffusion controlled with a much longer association time. The free-energy profile also captured the crucial role of allosteric IN inhibitors in promoting multimerization and explained why several C-terminal domain mutations are remarkably resistant to the drug-induced multimerization. The results also show that at small separation, the protein-protein binding process contains two consecutive phases with distinct thermodynamic signatures. First, interprotein water molecules are expelled to the bulk, resulting in a small increase in entropy, as the solvent entropy gain from the water release is nearly cancelled by the loss of side-chain entropies as the two proteins approach each other. At shorter distances, the two dry binding surfaces adapt to each other to optimize their interaction energy at the expense of further protein configurational entropy loss. Although the binding interfaces feature clusters of hydrophobic residues, overall, the protein-protein association in this system is driven by enthalpy and opposed by entropy.

Protein-Protein Binding as a Two-Step Mechanism: Preselection of Encounter Poses during the Binding of BPTI and Trypsin

Biomolecular recognition between proteins follows complex mechanisms, the understanding of which can substantially advance drug discovery efforts. Here, we track each step of the binding process in atomistic detail with molecular dynamics simulations using trypsin and its inhibitor bovine pancreatic trypsin inhibitor (BPTI) as a model system. We use umbrella sampling to cover a range of unbinding pathways. Starting from these simulations, we subsequently seed classical simulations at different stages of the process and combine them to a Markov state model. We clearly identify three kinetically separated states (an unbound state, an encounter state, and the final complex) and describe the mechanisms that dominate the binding process. From our model, we propose the following sequence of events. The initial formation of the encounter complex is driven by long-range interactions because opposite charges in trypsin and BPTI draw them together. The encounter complex features the prealigned binding partners with binding sites still partially surrounded by solvation shells. Further approaching leads to desolvation and increases the importance of van der Waals interactions. The native binding pose is adopted by maximizing short-range interactions. Thereby side-chain rearrangements ensure optimal shape complementarity. In particular, BPTI’s P1 residue adapts to the S1 pocket and prime site residues reorient to optimize interactions. After the paradigm of conformation selection, binding-competent conformations of BPTI and trypsin are already present in the apo ensembles and their probabilities increase during this proposed two-step association process. This detailed characterization of the molecular forces driving the binding process includes numerous aspects that have been discussed as central to the binding of trypsin and BPTI and protein complex formation in general. In this study, we combine all these aspects into one comprehensive model of protein recognition. We thereby contribute to enhance our general understanding of this fundamental mechanism, which is particularly critical as the development of biopharmaceuticals continuously gains significance.

Deamidation disrupts native and transient contacts to weaken the interaction between UBC13 and RING-finger E3 ligases

The deamidase OspI from enteric bacteria Shigella flexneri deamidates a glutamine residue in the host ubiquitin-conjugating enzyme UBC13 and converts it to glutamate (Q100E). Consequently, its polyubiquitination activity in complex with the RING-finger ubiquitin ligase TRAF6 and the downstream NF-κB inflammatory response is silenced. The precise role of deamidation in silencing the UBC13/TRAF6 complex is unknown. We report that deamidation inhibits the interaction between UBC13 and TRAF6 RING-domain (TRAF6^RING) by perturbing both the native and transient interactions. Deamidation creates a new intramolecular salt-bridge in UBC13 that competes with a critical intermolecular salt-bridge at the native UBC13/TRAF6^RING interface. Moreover, the salt-bridge competition prevents transient interactions necessary to form a typical UBC13/RING complex. Repulsion between E100 and the negatively charged surface of RING also prevents transient interactions in the UBC13/RING complex. Our findings highlight a mechanism wherein a post-translational modification perturbs the conformation and stability of transient complexes to inhibit protein-protein association.

Shigella is a highly infectious group of bacteria that attack the human digestive tract, causing severe and often deadly diarrhoea, especially in children. There is currently no vaccine to protect against the disease, and some strains are also now resistant to antibiotics. People get infected by eating or drinking contaminated foods and water. After passing through the stomach, Shigella invades and then multiplies in the lining of the intestine, eventually causing tissue damage and irritation.

During this process, Shigella ‘hides’ from its host’s immune system by blocking how intestinal cells respond to infection. Normally, infected cells send out chemical signals that act like a call for help, attracting specialised immune cells to clear the infection. In intestinal cells, two proteins called UBC13 and TRAF6 work together to switch on this response. Specifically, TRAF6 needs to bind to UBC13 for the switch to turn on.

Like many proteins, UBC13 is formed of thousands of atoms; some of these are organized in ‘functional groups’, a collection of atoms joined in a specific manner and with special chemical properties. During Shigella infection, the bacteria produce an enzyme that changes a single functional group (an amino group) at a specific location within UBC13 for a different one (an hydroxyl group).

Previous research showed that this could stop the immune response in intestinal cells, but the mechanism remained unknown. Mohanty et al. therefore set out to determine exactly how a change of so few atoms could have such a dramatic effect.

Biochemical studies using purified proteins revealed that Shigella’s alteration to UBC13 did not change its overall structure. However, the altered protein could no longer bind to its partner TRAF6. Theoretical analysis and computer simulations revealed that the normal binding process relies on a positively charged amino acid (one of the protein’s building blocks) in UBC13 and a negatively charged one in TRAF6 being attracted to each other. Shigella’s substitution, however, introduces a second negatively charged amino acid in UBC13. This ‘steals’ the positively charged amino acid that would normally interact with TRAF6: the electrical attraction between the two proteins is disrupted, and this stops them from binding.

The work by Mohanty et al. reveals the exact mechanism Shigella uses to dampen its host’s immune response during infection. In the future, this knowledge could be used to develop more effective drugs that would help control outbreaks of diarrhoea.

Modified Potential Functions Result in Enhanced Predictions of a Protein Complex by All-Atom Molecular Dynamics Simulations, Confirming a Stepwise Association Process for Native Protein-Protein Interactions

The relative prevalence of native protein-protein interactions (PPIs) are the cornerstone for understanding the structure, dynamics and mechanisms of function of protein complexes. In this study, we develop a scheme for scaling the protein-water interaction in the CHARMM36 force field, in order to better fit the solvation free energy of amino acids side-chain analogues. We find that the molecular dynamics simulation with the scaled force field, CHARMM36s, as well as a recently released version, CHARMM36m, effectively improve on the overly sticky association of proteins, such as ubiquitin. We investigate the formation of a heterodimer protein complex between the SAM domains of the EphA2 receptor and the SHIP2 enzyme by performing a combined total of 48 μs simulations with the different potential functions. While the native SAM heterodimer is only predicted at a low rate of 6.7% with the original CHARMM36 force field, the yield is increased to 16.7% with CHARMM36s, and to 18.3% with CHARMM36m. By analyzing the 25 native SAM complexes formed in the simulations, we find that their formation involves a preorientation guided by Coulomb interactions, consistent with an electrostatic steering mechanism. In 12 cases, the complex could directly transform to the native protein interaction surfaces with only small adjustments in domain orientation. In the other 13 cases, orientational and/or translational adjustments are needed to reach the native complex. Although the tendency for non-native complexes to dissociate has nearly doubled with the modified potential functions, a dissociation followed by a reassociation to the correct complex structure is still rare. Instead, the remaining non-native complexes undergo configurational changes/surface searching, which, however, rarely leads to native structures on a time scale of 250 ns. These observations provide a rich picture of the mechanisms of protein-protein complex formation and suggest that computational predictions of native complex PPIs could be improved further.

Theoretical Study of the Initial Stages of Self-Assembly of a Carboxysome's Facet

Bacterial microcompartments, BMCs, are organelles that exist within wide variety of bacteria and act as nanofactories. Among the different types of known BMCs, the carboxysome has been studied the most. The carboxysome plays an important role in the light-independent part of the photosynthesis process, where its icosahedral-like proteinaceous shell acts as a membrane that controls the transport of metabolites. Although a structural model exists for the carboxysome shell, it remains largely unknown how the shell proteins self-assemble. Understanding the self-assembly process can provide insights into how the shell affects the carboxysome's function and how it can be modified to create new functionalities, such as artificial nanoreactors and artificial protein membranes. Here, we describe a theoretical framework that employs Monte Carlo simulations with a coarse-grain potential that reproduces well the atomistic potential of mean force; employing this framework, we are able to capture the initial stages of the 2D self-assembly of CcmK2 hexamers, a major protein-shell component of the carboxysome's facet. The simulations reveal that CcmK2 hexamers self-assemble into clusters that resemble what was seen experimentally in 2D layers. Further analysis of the simulation results suggests that the 2D self-assembly of carboxysome's facets is driven by a nucleation-growth process, which in turn could play an important role in the hierarchical self-assembly of BMC shells in general.

Energetics of Hydrophilic Protein-Protein Association and the Role of Water

Hydrophilic protein-protein interfaces constitute a major part of all protein-protein interfaces and are thus of great importance. However, the quantitative characterization of their association is still an ongoing challenge and the driving force behind their association remains poorly characterized. Here, we have addressed the association of hydrophilic proteins and the role of water by means of extensive molecular dynamics simulations in explicit water using three well studied protein complexes; Barnase-Barstar, cytochrome c-cytochrome c peroxidase, and the N-terminal domain of enzyme I-histidine-containing phosphocarrier. The one-dimensional free energy profiles obtained from umbrella sampling simulations are downhill or, in other words, barrierless. Using these one-dimensional free energy profiles, the computed standard free energies of binding are -12.7 ± 1.1 kcal/mol, -9.4 ± 0.7 kcal/mol, and -8.4 ± 1.9 kcal/mol that are in reasonable to very good agreement with the experimental values of -19.6 kcal/mol, -8.8 kcal/mol, and -7.8 kcal/mol. As expected, analysis of the confined water between the hydrophilic complex partners shows that the density and the orientational order parameter deviate noticeably from the bulk values, especially at close separations of the confining proteins.

Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling

Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape.

Dynamic nature of the protein-protein interactions is an important element of cellular processes such as metabolic reactions and signal transduction, but its atomistic details are still unclear. Computational survey using molecular dynamics simulation is a straightforward method to elucidate these atomistic protein-protein interaction processes. However, a sufficient configurational sampling of the large system containing the atomistic protein complex model and explicit solvent remains a great challenge due to the long timescale involved. Here, we demonstrate that the multiscale enhanced sampling (MSES) successfully captured the atomistic details of the association/dissociation processes of a barnase-barstar complex covering the sampled space from the native complex structure to fully non-native configurations. The landscape derived from the simulation indicates that the association process is funnel-like downhill, analogously to the funnel landscape of fast-folding proteins. The funnel was found to be originated from near-native orientations guided by the shape complementarity between barnase and barstar, accelerating the formation of native inter-molecular interactions to complete the final complex structure.

Efficient determination of protein-protein standard binding free energies from first principles

Characterizing protein-protein association quantitatively has been a longstanding challenge for computer simulations. Here, a theoretical framework is put forth that addresses this challenge on the basis of detailed all-atom molecular dynamics simulations with explicit solvent. The proposed methodology relies upon independent potential of mean force (PMF) free-energy calculations carried out sequentially, wherein the biological objects are restrained in the conformation, position and orientation of the bound state, using adequately chosen biasing potentials. These restraints systematically narrow down the configurational entropy available to the system and effectively guarantee that the relevant network of interactions is properly sampled as the two proteins reversibly associate. Decomposition of the binding process into consecutive, well-delineated stages, for both the protein complex and the individual, unbound partners, offers a rigorous definition of the standard state, from which the absolute binding free energy can be determined. The method is applied to the difficult case of the extracellular ribonuclease barnase binding to its intracellular inhibitor barstar. The calculated binding free energy is -21.0 ± 1.4 kcal/mol, which compares well with the experimental value of -19.0 ± 0.2 kcal/mol. The relatively small statistical error reflects the precision and convergence afforded by the PMF-based simulation methodology. In addition to providing an accurate reproduction of the standard binding free energy, the proposed strategy offers a detailed picture of the protein-protein interface, illuminating the thermodynamic forces that underlie reversible association. The application of the present formal framework to barnase:barstar binding provides a foundation for tackling nearly any protein-protein complex.

Hydrodynamic effects on the relative rotational velocity of associating proteins

Hydrodynamic steering effects on the barnase-barstar association were studied through the analysis of the relative rotational velocity of the proteins. We considered the two proteins approaching each other in response to their electrostatic attraction and employed a method that accounts for the long-range and many-body character of the hydrodynamic interactions, as well as the complicated shapes of the proteins. Hydrodynamic steering effects were clearly seen when attractive forces were applied to the geometric centers of the proteins (resulting in zero torques) and the attraction acted along the line that connects centers of geometry of proteins in their crystallographic complex. When we rotated barstar relative to barnase around this line by an angle in the range from -90° to 60°, the rotational velocity arising solely from hydrodynamic interactions restored the orientation of the proteins in the crystal structure. However, because, in reality, both electrostatic forces and torques act on the proteins and these forces and torques depend on the protein-protein distance and the relative orientation of the binding partners, we also investigated more realistic situations employing continuum electrostatics calculations based on atomistic protein models. Overall, we conclude that hydrodynamic interactions aid barnase and barstar in assuming a proper relative orientation upon complex formation.

Coupled folding-binding in a hydrophobic/polar protein model: impact of synergistic folding and disordered flanks

Coupled folding-binding is central to the function of many intrinsically disordered proteins, yet not fully understood. With a continuous three-letter protein model, we explore the free-energy landscape of pairs of interacting sequences and how it is impacted by 1), variations in the binding mechanism; and 2), the addition of disordered flanks to the binding region. In particular, we focus on two sequences, one with 16 and one with 35 amino acids, which make a stable dimeric three-helix bundle at low temperatures. Three distinct binding mechanisms are realized by altering the stabilities of the individual monomers: docking, coupled folding-binding of a single α-helix, and synergistic folding and binding. Compared to docking, the free-energy barrier for binding is reduced when the single α-helix is allowed to fold upon binding, but only marginally. A greater reduction is found for synergistic folding, which in addition results in a binding transition state characterized by very few interchain contacts. Disordered flanking chain segments attached to the α-helix sequence can, despite a negligible impact on the dimer stability, lead to a downhill free-energy surface in which the barrier for binding is eliminated.

Electrostatically biased binding of kinesin to microtubules

An electrostatic field rotates, slides, and guides the kinesin head to bind the microtubule at a site a short distance ahead, thus determining the direction of movement of the motor.

The minimum motor domain of kinesin-1 is a single head. Recent evidence suggests that such minimal motor domains generate force by a biased binding mechanism, in which they preferentially select binding sites on the microtubule that lie ahead in the progress direction of the motor. A specific molecular mechanism for biased binding has, however, so far been lacking. Here we use atomistic Brownian dynamics simulations combined with experimental mutagenesis to show that incoming kinesin heads undergo electrostatically guided diffusion-to-capture by microtubules, and that this produces directionally biased binding. Kinesin-1 heads are initially rotated by the electrostatic field so that their tubulin-binding sites face inwards, and then steered towards a plus-endwards binding site. In tethered kinesin dimers, this bias is amplified. A 3-residue sequence (RAK) in kinesin helix alpha-6 is predicted to be important for electrostatic guidance. Real-world mutagenesis of this sequence powerfully influences kinesin-driven microtubule sliding, with one mutant producing a 5-fold acceleration over wild type. We conclude that electrostatic interactions play an important role in the kinesin stepping mechanism, by biasing the diffusional association of kinesin with microtubules.

Animal and plant cells contain a molecular-scale “railway” network, in which the tracks, called microtubules, radiate out from the cell centre and locomotive proteins, called kinesins, haul their molecular cargoes along the microtubule tracks. This railway system transports many different cargoes to where they are needed, so it is crucial for the cell's organization and function. Breakdowns in this transport system can cause diseases like Alzheimer's, and drugs that temporarily halt transport make powerful anti-cancer agents. Precisely how kinesin motor proteins move along their microtubule tracks is an important question in biology. We know that some kinesins have twin “heads” that alternately bind to and step along microtubules in a coordinated walking action. But more usually, kinesins have only one head. How single-headed kinesins produce force and movement is poorly understood. In this study, we address this question and show that electrical attraction between single kinesin heads and microtubules is a critical factor deciding the direction of movement: each time the head approaches a microtubule, it slides forwards by the electrical attraction between the engine and the track.

Barnase and binase: twins with distinct fates

RNases are enzymes that cleave RNAs, resulting in remarkably diverse biological consequences. Many RNases are cytotoxic. In some cases, they attack selectively malignant cells triggering an apoptotic response. A number of eukaryotic and bacterial RNase-based strategies are being developed for use in anticancer and antiviral therapy. However, the physiological functions of these RNases are often poorly understood. This review focuses on the properties of the extracellular RNases from Bacillus amyloliquefaciens (barnase) and Bacillus intermedius (binase), the characteristics of their biosynthesis regulation and their physiological role, with an emphasis on the similarities and differences. Barnase and binase can be regarded as molecular twins according to their highly similar structure, physical-chemical and catalytic properties. Nevertheless, the 'life paths' of these enzymes are not the same, as their expression in bacteria is controlled by diverse signals. Binase is predominantly synthesized under phosphate starvation, whereas barnase production is strictly dependent on the multifunctional Spo0A regulator controlling sporulation, biofilm formation and cannibalism. Barnase and binase also have some distinctions in practical applications. Barnase was initially suggested to be useful in research and biotechnology as a tool for studying protein-protein interactions, for RNA elimination from biological samples, for affinity purification of RNase fusion proteins, for the development of cloning vectors and for sterility acquisition by transgenic plants. Binase, as later barnase, was tested for antiviral, antitumour and immunogenic effects. Both RNases have found their own niche in cancer research as a result of success in targeted delivery and selectivity towards tumour cells.