Specificity in protein-protein interactions: the structural basis for dual recognition in endonuclease colicin-immunity protein complexes

Some Challenges of Diffused Interfaces in Implicit-Solvent Models

The standard Poisson-Boltzmann (PB) model for molecular electrostatics assumes a sharp variation of the permittivity and salt concentration along the solute-solvent interface. The discontinuous field parameters are not only difficult numerically, but also are not a realistic physical picture, as it forces the dielectric constant and ionic strength of bulk in the near-solute region. An alternative to alleviate some of these issues is to represent the molecular surface as a diffuse interface, however, this also presents challenges. In this work we analyzed the impact of the shape of the interfacial variation of the field parameters in solvation and binding energy. However we used a hyperbolic tangent functiontanh k p x $$ \left(\tanh \left({k}_px\right)\right) $$ to couple the internal and external regions, our analysis is valid for other definitions. Our methodology, restricted to the linear PB, was based on a coupled finite element (FEM) and boundary element (BEM) scheme that allowed us to have a special treatment of the permittivity and ionic strength in a bounded FEM region near the interface, while maintaining BEM elsewhere. Our results suggest that the shape of the function (represented byk p $$ {k}_p $$ ) has a large impact on solvation and binding energy. We saw that high values ofk p $$ {k}_p $$ induce a high gradient on the interface, to the limit of recovering the sharp jump whenk p → ∞ $$ {k}_p\to \infty $$ , presenting a numerical challenge where careful meshing is key. Using the FreeSolv database to compare with molecular dynamics, our calculations indicate that an optimal value ofk p $$ {k}_p $$ for solvation energies was around 3. However, more challenging binding free energy tests make this conclusion more difficult, as binding showed to be very sensitive to small variations ofk p $$ {k}_p $$ . In that case, optimal values ofk p $$ {k}_p $$ ranged from 2 to 20.

De novo design of high-affinity binders of bioactive helical peptides

Many peptide hormones form an α-helix on binding their receptors1-4, and sensitive methods for their detection could contribute to better clinical management of disease5. De novo protein design can now generate binders with high affinity and specificity to structured proteins6,7. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion8 to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

A simple method for developing lysine targeted covalent protein reagents

Peptide-based covalent probes can target shallow protein surfaces not typically addressable using small molecules, yet there is a need for versatile approaches to convert native peptide sequences into covalent binders that can target a broad range of residues. Here we report protein-based thio-methacrylate esters-electrophiles that can be installed easily on unprotected peptides and proteins via cysteine side chains, and react efficiently and selectively with cysteine and lysine side chains on the target. Methacrylate phosphopeptides derived from 14-3-3-binding proteins irreversibly label 14-3-3σ via either lysine or cysteine residues, depending on the position of the electrophile. Methacrylate peptides targeting a conserved lysine residue exhibit pan-isoform binding of 14-3-3 proteins both in lysates and in extracellular media. Finally, we apply this approach to develop protein-based covalent binders. A methacrylate-modified variant of the colicin E9 immunity protein irreversibly binds to the E9 DNAse, resulting in significantly higher thermal stability relative to the non-covalent complex. Our approach offers a simple and versatile route to convert peptides and proteins into potent covalent binders.

Structural disruption of Ntox15 nuclease effector domains by immunity proteins protects against type VI secretion system intoxication in Bacteroidales

Bacteroidales use type VI secretion systems (T6SS) to competitively colonize and persist in the colon. We identify a horizontally transferred T6SS with Ntox15 family nuclease effector (Tde1) that mediates interbacterial antagonism among Bacteroidales, including several derived from a single human donor. Expression of cognate (Tdi1) or orphan immunity proteins in acquired interbacterial defense systems protects against Tde1-dependent attack. We find that immunity protein interaction induces a large effector conformational change in Tde nucleases, disrupting the active site and altering the DNA-binding site. Crystallographic snapshots of isolated Tde1, the Tde1/Tdi1 complex, and homologs from Phocaeicola vulgatus (Tde2/Tdi2) illustrate a conserved mechanism of immunity inserting into the central core of Tde, splitting the nuclease fold into two subdomains. The Tde/Tdi interface and immunity mechanism are distinct from all other polymorphic toxin-immunity interactions of known structure. Bacteroidales abundance has been linked to inflammatory bowel disease activity in prior studies, and we demonstrate that Tde and T6SS structural genes are each enriched in fecal metagenomes from ulcerative colitis subjects. Genetically mobile Tde1-encoding T6SS in Bacteroidales mediate competitive growth and may be involved in inflammatory bowel disease. Broad immunity is conferred by Tdi1 homologs through a fold-disrupting mechanism unique among polymorphic effector-immunity pairs of known structure. IMPORTANCE Bacteroidales are related to inflammatory bowel disease severity and progression. We identify type VI secretion system (T6SS) nuclease effectors (Tde) which are enriched in ulcerative colitis and horizontally transferred on mobile genetic elements. Tde-encoding T6SSs mediate interbacterial competition. Orphan and cognate immunity proteins (Tdi) prevent intoxication by multiple Tde through a new mechanism among polymorphic toxin systems. Tdi inserts into the effector central core, splitting Ntox15 into two subdomains and disrupting the active site. This mechanism may allow for evolutionary diversification of the Tde/Tdi interface as observed in colicin nuclease-immunity interactions, promoting broad neutralization of Tde by orphan Tdi. Tde-dependent T6SS interbacterial antagonism may contribute to Bacteroidales diversity in the context of ulcerative colitis.

Quantification and Neutralization of the Interfacial Electrostatic Potential and Visualization of the Dispersion Interaction in Visualization of the Interfacial Electrostatic Complementarity

Visualization of the interfacial electrostatic complementarity (VIINEC) is a quantum chemistry-based method to examine protein-protein interactions (PPI). In VIINEC, the electrostatic complementarity between proteins at the interface is visually and quantitatively evaluated using the partial electrostatic potential (pESP), which is defined based on the fragment molecular orbital method. In this work, new quantification and neutralization methods of the pESP were proposed together with a method to visualize the dispersion interaction. The reliability and efficiency of these methods were evaluated using 17 models of the complex. It was found that the quantification of the electrostatic complementarity with the pESP using the new neutralization method has a high correlation with the interaction energy, supporting the reliability of VIINEC. As an illustrative example, the PPI between a major histocompatibility complex class I molecule and a T-cell receptor was examined, which demonstrated the value of VIINEC in chemical and biological research.

A dynamical view of protein-protein complexes: Studies by molecular dynamics simulations

Protein-protein interactions are at the basis of many protein functions, and the knowledge of 3D structures of protein-protein complexes provides structural, mechanical and dynamical pieces of information essential to understand these functions. Protein-protein interfaces can be seen as stable, organized regions where residues from different partners form non-covalent interactions that are responsible for interaction specificity and strength. They are commonly described as a peripheral region, whose role is to protect the core region that concentrates the most contributing interactions, from the solvent. To get insights into the dynamics of protein-protein complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on eight different protein-protein complexes of different functional class and interface size by taking into account the bound and unbound forms. On the one hand, we characterized structural changes upon binding of the proteins, and on the other hand we extensively analyzed the interfaces and the structural waters involved in the binding. Based on our analysis, in 6 cases out of 8, the interfaces rearranged during the simulation time, in stable and long-lived substates with alternative residue-residue contacts. These rearrangements are not restricted to side-chain fluctuations in the periphery but also affect the core interface. Finally, the analysis of the waters at the interface and involved in the binding pointed out the importance to take into account their role in the estimation of the interaction strength.

RosettaSurf-A surface-centric computational design approach

Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.

Computational Alanine Scanning Reveals Common Features of TCR/pMHC Recognition in HLA-DQ8-Associated Celiac Disease

In HLA-DQ8-associated celiac disease, Gliadin-γ1 or Gliadin-α1 peptide is presented to the cell surface and recognized by several types of T-cell receptor (TCR), but it is still unclear how the TCR, peptide, and the major histocompatibility complex (MHC) act together to trigger celiac disease. For now, most of the analysis is based on static crystal structures. And the detailed information about these structures based on energetic interaction is still lacking. Here, we took four types of celiac disease-related MHC-peptide-TCR structures from three patients to perform computational alanine scanning calculations using the molecular mechanics generalized born surface area (MM/GBSA) approach combined with a recently developed interaction entropy (IE) method to identify the key residues on TCR, peptide, and MHC. Our study aims to shed some light on the interaction mechanism of this complex protein interaction system. Based on detailed computational analysis and mutational calculations, important binding interactions in these triple-interaction complexes are analyzed, and critical residues responsible for TCR/pMHC recognition pattern in HLA-DQ8-associated celiac disease are presented. These detailed analysis and computational result should help shed light on our understanding of the celiac disease and the development of the medical treatment.

Fundamentals and Design-Led Synthesis of Emulsion-Templated Porous Materials for Environmental Applications

Emulsion templating is at the forefront of producing a wide array of porous materials that offers interconnected porous structure, easy permeability, homogeneous flow-through, high diffusion rates, convective mass transfer, and direct accessibility to interact with atoms/ions/molecules throughout the exterior and interior of the bulk. These interesting features together with easily available ingredients, facile preparation methods, flexible pore-size tuning protocols, controlled surface modification strategies, good physicochemical and dimensional stability, lightweight, convenient processing and subsequent recovery, superior pollutants remediation/monitoring performance, and decent recyclability underscore the benchmark potential of the emulsion-templated porous materials in large-scale practical environmental applications. To this end, many research breakthroughs in emulsion templating technique witnessed by the recent achievements have been widely unfolded and currently being extensively explored to address many of the environmental challenges. Taking into account the burgeoning progress of the emulsion-templated porous materials in the environmental field, this review article provides a conceptual overview of emulsions and emulsion templating technique, sums up the general procedures to design and fabricate many state-of-the-art emulsion-templated porous materials, and presents a critical overview of their marked momentum in adsorption, separation, disinfection, catalysis/degradation, capture, and sensing of the inorganic, organic and biological contaminants in water and air.

Structural design principles for specific ultra-high affinity interactions between colicins/pyocins and immunity proteins

The interactions of the antibiotic proteins colicins/pyocins with immunity proteins is a seminal model system for studying protein–protein interactions and specificity. Yet, a precise and quantitative determination of which structural elements and residues determine their binding affinity and specificity is still lacking. Here, we used comparative structure-based energy calculations to map residues that substantially contribute to interactions across native and engineered complexes of colicins/pyocins and immunity proteins. We show that the immunity protein α1–α2 motif is a unique structurally-dissimilar element that restricts interaction specificity towards all colicins/pyocins, in both engineered and native complexes. This motif combines with a diverse and extensive array of electrostatic/polar interactions that enable the exquisite specificity that characterizes these interactions while achieving ultra-high affinity. Surprisingly, the divergence of these contributing colicin residues is reciprocal to residue conservation in immunity proteins. The structurally-dissimilar immunity protein α1–α2 motif is recognized by divergent colicins similarly, while the conserved immunity protein α3 helix interacts with diverse colicin residues. Electrostatics thus plays a key role in setting interaction specificity across all colicins and immunity proteins. Our analysis and resulting residue-level maps illuminate the molecular basis for these protein–protein interactions, with implications for drug development and rational engineering of these interfaces.

Molecular Structure and Functional Analysis of Pyocin S8 from Pseudomonas aeruginosa Reveals the Essential Requirement of a Glutamate Residue in the H-N-H Motif for DNase Activity

Multidrug resistance (MDR) is a serious threat to public health, making the development of new antimicrobials an urgent necessity. Pyocins are protein antibiotics produced by Pseudomonas aeruginosa strains to kill closely related cells during intraspecific competition. Here, we report an in-depth biochemical, microbicidal, and structural characterization of a new S-type pyocin, named S8. Initially, we described the domain organization and secondary structure of S8. Subsequently, we observed that a recombinant S8 composed of the killing subunit in complex with the immunity (ImS8) protein killed the strain PAO1. Furthermore, mutation of a highly conserved glutamic acid to alanine (Glu100Ala) completely inhibited this antimicrobial activity. The integrity of the H-N-H motif is probably essential in the killing activity of S8, as Glu100 is a highly conserved residue of this motif. Next, we observed that S8 is a metal-dependent endonuclease, as EDTA treatment abolished its ability to cleave supercoiled pUC18 plasmid. Supplementation of apo S8 with Ni²⁺ strongly induced this DNase activity, whereas Mn²⁺ and Mg²⁺ exhibited moderate effects and Zn²⁺ was inhibitory. Additionally, S8 bound Zn²⁺ with a higher affinity than Ni²⁺ and the Glu100Ala mutation decreased the affinity of S8 for these metals, as shown by isothermal titration calorimetry (ITC). Finally, we describe the crystal structure of the Glu100Ala S8 DNase-ImS8 complex at 1.38 Å, which gave us new insights into the endonuclease activity of S8. Our results reinforce the possibility of using pyocin S8 as an alternative therapy for infections caused by MDR strains, while leaving commensal human microbiota intact.IMPORTANCE Pyocins are proteins produced by Pseudomonas aeruginosa strains that participate in intraspecific competition and host-pathogen interactions. They were first described in the 1950s and since then have gained attention as possible new antibiotics. However, there is still only scarce information about the molecular mechanisms by which these molecules induce cell death. Here, we show that the metal-dependent endonuclease activity of pyocin S8 is involved with its antimicrobial action against strain PAO1. We also describe that this killing activity is dependent on a conserved Glu residue within the H-N-H motif. The potency and selectivity of pyocin S8 toward a narrow spectrum of P. aeruginosa strains make this protein an attractive antimicrobial alternative for combatting MDR strains, while leaving commensal human microbiota intact.

Using collections of structural models to predict changes of binding affinity caused by mutations in protein-protein interactions

Protein-protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state-of-the-art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state-of-art methods.

Basic Principles of Emulsion Templating and Its Use as an Emerging Manufacturing Method of Tissue Engineering Scaffolds

Tissue engineering (TE) aims to regenerate critical size defects, which cannot heal naturally, by using highly porous matrices called TE scaffolds made of biocompatible and biodegradable materials. There are various manufacturing techniques commonly used to fabricate TE scaffolds. However, in most cases, they do not provide materials with a highly interconnected pore design. Thus, emulsion templating is a promising and convenient route for the fabrication of matrices with up to 99% porosity and high interconnectivity. These matrices have been used for various application areas for decades. Although this polymer structuring technique is older than TE itself, the use of polymerised internal phase emulsions (PolyHIPEs) in TE is relatively new compared to other scaffold manufacturing techniques. It is likely because it requires a multidisciplinary background including materials science, chemistry and TE although producing emulsion templated scaffolds is practically simple. To date, a number of excellent reviews on emulsion templating have been published by the pioneers in this field in order to explain the chemistry behind this technique and potential areas of use of the emulsion templated structures. This particular review focusses on the key points of how emulsion templated scaffolds can be fabricated for different TE applications. Accordingly, we first explain the basics of emulsion templating and characteristics of PolyHIPE scaffolds. Then, we discuss the role of each ingredient in the emulsion and the impact of the compositional changes and process conditions on the characteristics of PolyHIPEs. Afterward, current fabrication methods of biocompatible PolyHIPE scaffolds and polymerisation routes are detailed, and the functionalisation strategies that can be used to improve the biological activity of PolyHIPE scaffolds are discussed. Finally, the applications of PolyHIPEs on soft and hard TE as well as in vitro models and drug delivery in the literature are summarised.

QM Implementation in Drug Design: Does It Really Help?

Computational chemistry allows one to characterize the structure, dynamics, and energetics of protein-ligand interactions, which makes it a valuable tool in drug discovery in both academic research and pharmaceutical industry. Molecular mechanics (MM)-based approaches are widely utilized to assist the discovery of new drug candidates. However, the complexity of protein-ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. Aiming to provide better accuracy in the description of protein-ligand interactions, quantum mechanics (QM)-based approaches are becoming increasingly explored. In principle, QM calculation includes all contributions to the energy, accounting for terms usually missing in empirical force fields, and provides a greater degree of transferability. The usefulness of QM in drug design cannot be overemphasized. In this chapter, we present recent developments and applications of fragment-based QM method in studying the protein-ligand and protein-protein interactions. We critically discuss the performance of the fragment-based QM method at different ab initio levels while trying to answer a critical question: do QM-based methods really help in drug design?

Computational studies of protein-protein dissociation by statistical potential and coarse-grained simulations: a case study on interactions between colicin E9 endonuclease and immunity proteins

Proteins carry out their diverse functions in cells by forming interactions with each other. The dynamics of these interactions are quantified by the measurement of association and dissociation rate constants. Relative to the efforts made to model the association of biomolecules, little has been studied to understand the principles of protein complex dissociation. Using the interaction between colicin E9 endonucleases and immunity proteins as a test system, here we develop a coarse-grained simulation method to explore the dissociation mechanisms of protein complexes. The interactions between proteins in the complex are described by the knowledge-based potential that was constructed by the statistics from available protein complexes in the structural database. Our study provides the supportive evidences to the dual recognition mechanism for the specificity of binding between E9 DNase and immunity proteins, in which the conserved residues of helix III of Im2 and Im9 proteins act as the anchor for binding, while the sequence variations in helix II make positive or negative contributions to specificity. Beyond that, we further suggest that this binding specificity is rooted in the process of complex dissociation instead of association. While we increased the flexibility of protein complexes, we further found that they are less prone to dissociation, suggesting that conformational fluctuations of protein complexes play important functional roles in regulating their binding and dissociation. Our studies therefore bring new insights to the molecule mechanisms of protein-protein interactions, while the method can serve as a new addition to a suite of existing computational tools for the simulations of protein complexes.

Ultrahigh specificity in a network of computationally designed protein-interaction pairs

Protein networks in all organisms comprise homologous interacting pairs. In these networks, some proteins are specific, interacting with one or a few binding partners, whereas others are multispecific and bind a range of targets. We describe an algorithm that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences. Applied to a high-affinity bacterial pair, the algorithm results in 18 new ones, with cognate affinities from pico- to micromolar. Three pairs exhibit 3-5 orders of magnitude switch in specificity relative to the wild type, whereas others are multispecific, collectively forming a protein-interaction network. Crystallographic analysis confirms design accuracy, including in new backbones and polar interactions. Preorganized polar interaction networks are responsible for high specificity, thus defining design principles that can be applied to program synthetic cellular interaction networks of desired affinity and specificity.

The molecular basis of ultrahigh specificity in protein-protein interactions remains obscure. The authors present a computational method to design atomically accurate new pairs exhibiting >100,000-fold specificity switches, generating a large and complex interaction network.

Fragment-based quantum mechanical calculation of protein-protein binding affinities

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc.

Properties that rank protein:protein docking poses with high accuracy

The development of docking algorithms to predict near-native structures of protein:protein complexes from the structure of the isolated monomers is of paramount importance for molecular biology and drug discovery.

Treating ion distribution with Gaussian-based smooth dielectric function in DelPhi

The standard treatment of ions in the framework of the Poisson-Boltzmann equation relies on molecular surfaces, which are commonly constructed along with the Stern layer. The molecular surface determines where ions can be present. In the Gaussian-based smooth dielectric function in DelPhi, smooth boundaries between the solute and solvent take the place of molecular surface. Therefore, this invokes the question of how to model mobile ions in the water phase without a definite solute-solvent boundary. This article reports a natural extension of the Gaussian-based smooth dielectric function approach that treats mobile ions via Boltzmann distribution with an added desolvation penalty. Thus, ion concentration near macromolecules is governed by the local electrostatic potential and the desolvation penalty (from being partially desolvated). The approach is tested against the experimental salt dependence of binding free energy on 7 protein-protein complexes and 12 DNA-protein complexes, resulting in Pearson correlations of 0.95 and 0.88, respectively. © 2017 Wiley Periodicals, Inc.

Non-Debye frustrated hydration steers biomolecular association: interfacial tension for the drug designer

Many cellular functions involve the assembly of biomolecular complexes, a process mediated by water that gets displaced as subunits bind. This process affects water frustration, that is, the number of unmet hydrogen-bonding opportunities at the protein-water interface. By searching for least-frustrated aqueous interfaces, this study delineates the role of frustration in steering molecular assemblage. The search entails a trajectory sampling using a functional that measures the gradient of frustration and computing the resulting non-Debye electrostatics within relaxation times for coupled protein-water systems. The minimal frustration principle is validated against spectroscopic measurements of frustration-dependent dielectric relaxation, affinity scanning of protein-protein interfaces, and NMR-inferred association propensities of protein-complex intermediates. The methods are applied to drug design, revealing the targetable nature of the aqueous interface.

Performance of ZDOCK and IRAD in CAPRI rounds 28-34

We report the performance of our protein-protein docking pipeline, including the ZDOCK rigid-body docking algorithm, on 19 targets in CAPRI rounds 28-34. Following the docking step, we reranked the ZDOCK predictions using the IRAD scoring function, pruned redundant predictions, performed energy landscape analysis, and utilized our interface prediction approach RCF. In addition, we applied constraints to the search space based on biological information that we culled from the literature, which increased the chance of making a correct prediction. For all but two targets we were able to find and apply biological information and we found the information to be highly accurate, indicating that effective incorporation of biological information is an important component for protein-protein docking. Proteins 2017; 85:408-416. © 2016 Wiley Periodicals, Inc.

Structural and biophysical analysis of nuclease protein antibiotics

Protein antibiotics (bacteriocins) are a large and diverse family of multidomain toxins that kill specific Gram-negative bacteria during intraspecies competition for resources. Our understanding of the mechanism of import of such potent toxins has increased significantly in recent years, especially with the reporting of several structures of bacteriocin domains. Less well understood is the structural biochemistry of intact bacteriocins and how these compare across bacterial species. Here, we focus on endonuclease (DNase) bacteriocins that target the genomes of Escherichia coli and Pseudomonas aeruginosa, known as E-type colicins and S-type pyocins, respectively, bound to their specific immunity (Im) proteins. First, we report the 3.2 Å structure of the DNase colicin ColE9 in complex with its ultra-high affinity Im protein, Im9. In contrast with Im3, which when bound to the ribonuclease domain of the homologous colicin ColE3 makes contact with the translocation (T) domain of the toxin, we find that Im9 makes no such contact and only interactions with the ColE9 cytotoxic domain are observed. Second, we report small-angle X-ray scattering data for two S-type DNase pyocins, S2 and AP41, into which are fitted recently determined X-ray structures for isolated domains. We find that DNase pyocins and colicins are both highly elongated molecules, even though the order of their constituent domains differs. We discuss the implications of these architectural similarities and differences in the context of the translocation mechanism of protein antibiotics through the cell envelope of Gram-negative bacteria.

Discrete structural features among interface residue-level classes

BACKGROUND

Protein-protein interaction (PPI) is essential for molecular functions in biological cells. Investigation on protein interfaces of known complexes is an important step towards deciphering the driving forces of PPIs. Each PPI complex is specific, sensitive and selective to binding. Therefore, we have estimated the relative difference in percentage of polar residues between surface and the interface for each complex in a non-redundant heterodimer dataset of 278 complexes to understand the predominant forces driving binding.

RESULTS

Our analysis showed ~60% of protein complexes with surface polarity greater than interface polarity (designated as class A). However, a considerable number of complexes (~40%) have interface polarity greater than surface polarity, (designated as class B), with a significantly different p-value of 1.66E-45 from class A. Comprehensive analyses of protein complexes show that interface features such as interface area, interface polarity abundance, solvation free energy gain upon interface formation, binding energy and the percentage of interface charged residue abundance distinguish among class A and class B complexes, while electrostatic visualization maps also help differentiate interface classes among complexes.

CONCLUSIONS

Class A complexes are classical with abundant non-polar interactions at the interface; however class B complexes have abundant polar interactions at the interface, similar to protein surface characteristics. Five physicochemical interface features analyzed from the protein heterodimer dataset are discriminatory among the interface residue-level classes. These novel observations find application in developing residue-level models for protein-protein binding prediction, protein-protein docking studies and interface inhibitor design as drugs.

Examining the assumptions underlying continuum-solvent models

Continuum-solvent models (CSMs) have successfully predicted many quantities, including the solvation-free energies (ΔG) of small molecules, but they have not consistently succeeded at reproducing experimental binding free energies (ΔΔG), especially for protein-protein complexes. Several CSMs break ΔG into the free energy (ΔGvdw) of inserting an uncharged molecule into solution and the free energy (ΔGel) gained from charging. Some further divide ΔGvdw into the free energy (ΔGrep) of inserting a nearly hard cavity into solution and the free energy (ΔGatt) gained from turning on dispersive interactions between the solute and solvent. We show that for 9 protein-protein complexes neither ΔGrep nor ΔGvdw was linear in the solvent-accessible area A, as assumed in many CSMs, and the corresponding components of ΔΔG were not linear in changes in A. We show that linear response theory (LRT) yielded good estimates of ΔGatt and ΔΔGatt, but estimates of ΔΔGatt obtained from either the initial or final configurations of the solvent were not consistent with those from LRT. The LRT estimates of ΔGel differed by more than 100 kcal/mol from the explicit solvent model's (ESM's) predictions, and its estimates of the corresponding component (ΔΔGel) of ΔΔG differed by more than 10 kcal/mol. Finally, the Poisson-Boltzmann equation produced estimates of ΔGel that were correlated with those from the ESM, but its estimates of ΔΔGel were much less so. These findings may help explain why many CSMs have not been consistently successful at predicting ΔΔG for many complexes, including protein-protein complexes.

Structures of the Ultra-High-Affinity Protein-Protein Complexes of Pyocins S2 and AP41 and Their Cognate Immunity Proteins from Pseudomonas aeruginosa

How ultra-high-affinity protein-protein interactions retain high specificity is still poorly understood. The interaction between colicin DNase domains and their inhibitory immunity (Im) proteins is an ultra-high-affinity interaction that is essential for the neutralisation of endogenous DNase catalytic activity and for protection against exogenous DNase bacteriocins. The colicin DNase-Im interaction is a model system for the study of high-affinity protein-protein interactions. However, despite the fact that closely related colicin-like bacteriocins are widely produced by Gram-negative bacteria, this interaction has only been studied using colicins from Escherichia coli. In this work, we present the first crystal structures of two pyocin DNase-Im complexes from Pseudomonas aeruginosa, pyocin S2 DNase-ImS2 and pyocin AP41 DNase-ImAP41. These structures represent divergent DNase-Im subfamilies and are important in extending our understanding of protein-protein interactions for this important class of high-affinity protein complex. A key finding of this work is that mutations within the immunity protein binding energy hotspot, helix III, are tolerated by complementary substitutions at the DNase-Immunity protein binding interface. Im helix III is strictly conserved in colicins where an Asp forms polar interactions with the DNase backbone. ImAP41 contains an Asp-to-Gly substitution in helix III and our structures show the role of a co-evolved substitution where Pro in DNase loop 4 occupies the volume vacated and removes the unfulfilled hydrogen bond. We observe the co-evolved mutations in other DNase-Immunity pairs that appear to underpin the split of this family into two distinct groups.

Extraction of accurate biomolecular parameters from single-molecule force spectroscopy experiments

The atomic force microscope (AFM) is able to manipulate biomolecules and their complexes with exquisite force sensitivity and distance resolution. This capability, complemented by theoretical models, has greatly improved our understanding of the determinants of mechanical strength in proteins and revealed the diverse effects of directional forces on the energy landscape of biomolecules. In unbinding experiments, the interacting partners are usually immobilized on their respective substrates via extensible linkers. These linkers affect both the force and contour length (Lc) of the complex at rupture. Surprisingly, while the former effect is well understood, the latter is largely neglected, leading to incorrect estimations of Lc, a parameter that is often used as evidence for the detection of specific interactions and remodeling events and for the inference of interaction regions. To address this problem, a model that predicts contour length measurements from single-molecule forced-dissociation experiments is presented that considers attachment position on the AFM tip, geometric effects, and polymer dynamics of the linkers. Modeled data are compared with measured contour length distributions from several different experimental systems, revealing that current methods underestimate contour lengths. The model enables nonspecific interactions to be identified unequivocally, allows accurate determination of Lc, and, by comparing experimental and modeled distributions, enables partial unfolding events before rupture to be identified unequivocally.

Structural basis of protein-protein interactions

Regulated interactions between proteins govern signaling pathways within and between cells. Structural studies on protein complexes formed reversibly and/or transiently illustrate the remarkable diversity of interactions, both in terms of interfacial size and nature. In recent years, "domain-peptide" interactions have gained much greater recognition and may be viewed as both pre-translational and posttranslational-dependent functional switches. Our understanding of the multistep regulation of auto-inhibited multidomain proteins has also grown. Their activity may be understood as the "combinatorial" output of multiple input signals, including phosphorylation, location, and mechanical force. The prospects for bridging the gap between the new "systems biology" data and the traditional "reductionist" data are also discussed.

A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy

Protein-protein (P-P) 3D structures are fundamental to structural biology and drug discovery. However, most of them have never been determined. Many docking algorithms were developed for that purpose, but they have a very limited accuracy in generating native-like structures and identifying the most correct one, in particular when a single answer is asked for. With such a low success rate it is difficult to point out one docked structure as being native-like. Here we present a new, high accuracy, scoring method to identify the 3D structure of P-P complexes among a set of trial poses. It incorporates alanine scanning mutagenesis experimental data that need to be obtained a priori. The scoring scheme works by matching the computational and the experimental alanine scanning mutagenesis results. The size of the trial P-P interface area is also taken into account. We show that the method ranks the trial structures and identifies the native-like structures with unprecedented accuracy (∼94%), providing the correct P-P 3D structures that biochemists and molecular biologists need to pursue their studies. With such a success rate, the bottleneck of protein-protein docking moves from the scoring to searching algorithms.

A "fuzzy"-logic language for encoding multiple physical traits in biomolecules

To carry out their activities, biological macromolecules balance different physical traits, such as stability, interaction affinity, and selectivity. How such often opposing traits are encoded in a macromolecular system is critical to our understanding of evolutionary processes and ability to design new molecules with desired functions. We present a framework for constraining design simulations to balance different physical characteristics. Each trait is represented by the equilibrium fractional occupancy of the desired state relative to its alternatives, ranging from none to full occupancy, and the different traits are combined using Boolean operators to effect a "fuzzy"-logic language for encoding any combination of traits. In another paper, we presented a new combinatorial backbone design algorithm AbDesign where the fuzzy-logic framework was used to optimize protein backbones and sequences for both stability and binding affinity in antibody-design simulation. We now extend this framework and find that fuzzy-logic design simulations reproduce sequence and structure design principles seen in nature to underlie exquisite specificity on the one hand and multispecificity on the other hand. The fuzzy-logic language is broadly applicable and could help define the space of tolerated and beneficial mutations in natural biomolecular systems and design artificial molecules that encode complex characteristics.

Blind prediction of interfacial water positions in CAPRI

We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.

A new insight into the zinc-dependent DNA-cleavage by the colicin E7 nuclease: a crystallographic and computational study

The crystal structure of a colicin E7 metallonuclease mutant complemented by QM/MM calculations suggests an alternative catalytic mechanism of Zn²⁺-containing HNH nucleases.

RecA-dependent programmable endonuclease Ref cleaves DNA in two distinct steps

The bacteriophage P1 recombination enhancement function (Ref) protein is a RecA-dependent programmable endonuclease. Ref targets displacement loops formed when an oligonucleotide is bound by a RecA filament and invades homologous double-stranded DNA sequences. Mechanistic details of this reaction have been explored, revealing that (i) Ref is nickase, cleaving the two target strands of a displacement loop sequentially, (ii) the two strands are cleaved in a prescribed order, with the paired strand cut first and (iii) the two cleavage events have different requirements. Cutting the paired strand is rapid, does not require RecA-mediated ATP hydrolysis and is promoted even by Ref active site variant H153A. The displaced strand is cleaved much more slowly, requires RecA-mediated ATP hydrolysis and does not occur with Ref H153A. The two cleavage events are also affected differently by solution conditions. We postulate that the second cleavage (displaced strand) is limited by some activity of RecA protein.

Inclusion of the orientational entropic effect and low-resolution experimental information for protein-protein docking in Critical Assessment of PRedicted Interactions (CAPRI)

Inclusion of entropy is important and challenging for protein-protein binding prediction. Here, we present a statistical mechanics-based approach to empirically consider the effect of orientational entropy. Specifically, we globally sample the possible binding orientations based on a simple shape-complementarity scoring function using an FFT-type docking method. Then, for each generated orientation, we calculate the probability through the partition function of the ensemble of accessible states, which are assumed to be represented by the set of nearby binding modes. For each mode, the interaction energy is calculated using our ITScorePP scoring function that was developed in our laboratory based on principles of statistical mechanics. Using the above protocol, we present the results of our participation in Rounds 22-27 of the Critical Assessment of PRedicted Interactions (CAPRI) experiment for 10 targets (T46-T58). Additional experimental information, such as low-resolution small-angle X-ray scattering data, was used when available. In the prediction (or docking) experiments of the 10 target complexes, we achieved correct binding modes for six targets: one with high accuracy (T47), two with medium accuracy (T48 and T57), and three with acceptable accuracy (T49, T50, and T58). In the scoring experiments of seven target complexes, we obtained correct binding modes for six targets: one with high accuracy (T47), two with medium accuracy (T49 and T50), and three with acceptable accuracy (T46, T51, and T53).

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets. For example, for DNase domain of Colicin E2-Im2 immunity protein, RosettaDock and RosettaLigand were used to predict the positions of water molecules at the interface, recovering 46% of the native water-mediated contacts. For α-repeat Rep4-Rep2 and g-type lysozyme-PliG inhibitor complexes, homology models were built and standard and pH-sensitive docking algorithms were used to generate structures with interface RMSD values of 3.3 Å and 2.0 Å, respectively. A novel flexible sugar-protein docking protocol was also developed and used for structure prediction of the BT4661-heparin-like saccharide complex, recovering 71% of the native contacts. Challenges remain in the generation of accurate homology models for protein mutants and sampling during global docking. On proteins designed to bind influenza hemagglutinin, only about half of the mutations were identified that affect binding (T55: 54%; T56: 48%). The prediction of the structure of the xylanase complex involving homology modeling and multidomain docking pushed the limits of global conformational sampling and did not result in any successful prediction. The diversity of problems at hand requires computational algorithms to be versatile; the recent additions to the Rosetta suite expand the capabilities to encompass more biologically realistic docking problems.

Expanding the frontiers of protein-protein modeling: from docking and scoring to binding affinity predictions and other challenges

In addition to protein-protein docking, this CAPRI edition included new challenges, like protein-water and protein-sugar interactions, or the prediction of binding affinities and ΔΔG changes upon mutation. Regarding the standard protein-protein docking cases, our approach, mostly based on the pyDock scheme, submitted correct models as predictors and as scorers for 67% and 57% of the evaluated targets, respectively. In this edition, available information on known interface residues hardly made any difference for our predictions. In one of the targets, the inclusion of available experimental small-angle X-ray scattering (SAXS) data using our pyDockSAXS approach slightly improved the predictions. In addition to the standard protein-protein docking assessment, new challenges were proposed. One of the new problems was predicting the position of the interface water molecules, for which we submitted models with 20% and 43% of the water-mediated native contacts predicted as predictors and scorers, respectively. Another new problem was the prediction of protein-carbohydrate binding, where our submitted model was very close to being acceptable. A set of targets were related to the prediction of binding affinities, in which our pyDock scheme was able to discriminate between natural and designed complexes with area under the curve = 83%. It was also proposed to estimate the effect of point mutations on binding affinity. Our approach, based on machine learning methods, showed high rates of correctly classified mutations for all cases. The overall results were highly rewarding, and show that the field is ready to move forward and face new interesting challenges in interactomics.

Identification of the β-lactamase inhibitor protein-II (BLIP-II) interface residues essential for binding affinity and specificity for class A β-lactamases

The interactions between β-lactamase inhibitory proteins (BLIPs) and β-lactamases have been used as model systems to understand the principles of affinity and specificity in protein-protein interactions. The most extensively studied tight binding inhibitor, BLIP, has been characterized with respect to amino acid determinants of affinity and specificity for binding β-lactamases. BLIP-II, however, shares no sequence or structural homology to BLIP and is a femtomolar to picomolar potency inhibitor, and the amino acid determinants of binding affinity and specificity are unknown. In this study, alanine scanning mutagenesis was used in combination with determinations of on and off rates for each mutant to define the contribution of residues on the BLIP-II binding surface to both affinity and specificity toward four β-lactamases of diverse sequence. The residues making the largest contribution to binding energy are heavily biased toward aromatic amino acids near the center of the binding surface. In addition, substitutions that reduce binding energy do so by increasing off rates without impacting on rates. Also, residues with large contributions to binding energy generally exhibit low temperature factors in the structures of complexes. Finally, with the exception of D206A, BLIP-II alanine substitutions exhibit a similar trend of effect for all β-lactamases, i.e., a substitution that reduces affinity for one β-lactamase usually reduces affinity for all β-lactamases tested.

A force-activated trip switch triggers rapid dissociation of a colicin from its immunity protein

A single-molecule force study shows that rapid dissociation of a high-affinity protein interaction can be triggered by site-specific remodelling of one protein partner, and that prevention of remodelling maintains avidity.

Colicins are protein antibiotics synthesised by Escherichia coli strains to target and kill related bacteria. To prevent host suicide, colicins are inactivated by binding to immunity proteins. Despite their high avidity (K_d≈fM, lifetime ≈4 days), immunity protein release is a pre-requisite of colicin intoxication, which occurs on a timescale of minutes. Here, by measuring the dynamic force spectrum of the dissociation of the DNase domain of colicin E9 (E9) and immunity protein 9 (Im9) complex using an atomic force microscope we show that application of low forces (<20 pN) increases the rate of complex dissociation 10⁶-fold, to a timescale (lifetime ≈10 ms) compatible with intoxication. We term this catastrophic force-triggered increase in off-rate a trip bond. Using mutational analysis, we elucidate the mechanism of this switch in affinity. We show that the N-terminal region of E9, which has sparse contacts with the hydrophobic core, is linked to an allosteric activator region in E9 (residues 21–30) whose remodelling triggers immunity protein release. Diversion of the force transduction pathway by the introduction of appropriately positioned disulfide bridges yields a force resistant complex with a lifetime identical to that measured by ensemble techniques. A trip switch within E9 is ideal for its function as it allows bipartite complex affinity, whereby the stable colicin:immunity protein complex required for host protection can be readily converted to a kinetically unstable complex whose dissociation is necessary for cellular invasion and competitor death. More generally, the observation of two force phenotypes for the E9:Im9 complex demonstrates that force can re-sculpt the underlying energy landscape, providing new opportunities to modulate biological reactions in vivo; this rationalises the commonly observed discrepancy between off-rates measured by dynamic force spectroscopy and ensemble methods.

Many proteins interact with other proteins as part of their function. One method of modulating the activity of protein complexes is to break them apart. Some complexes, however, are extremely kinetically stable and it is unclear how these can dissociate on a biologically relevant timescale. In this study we address this question using protein complexes between colicin E9 (a bacterial toxin) and its immunity protein Im9. These highly avid complexes (with a lifetime of days) must be broken apart for colicin to be activated. By using single-molecule force methods we show that pulling on one end of colicin E9 drastically destabilises the complex so that it dissociates a million-fold faster than its intrinsic rate. We then show that preventing this destabilisation (by the insertion of cross-links that pin the N-terminus of E9 in place) yields a kinetically stable complex. It has previously been postulated that force can destabilise a protein complex by partially unfolding one or more binding partners. Our work provides new experimental evidence that shows this is the case and provides a mechanism for this phenomenon, which we term a trip bond. For the E9:Im9 complex, trip bond behaviour allows a stable complex to be rapidly dissociated by application of a surprisingly small force.

Communication: Nanoscale electrostatic theory of epistructural fields at the protein-water interface

Nanoscale solvent confinement at the protein-water interface promotes dipole orientations that are not aligned with the internal electrostatic field of a protein, yielding what we term epistructural polarization. To quantify this effect, an equation is derived from first principles relating epistructural polarization with the magnitude of local distortions in water coordination causative of interfacial tension. The equation defines a nanoscale electrostatic model of water and enables an estimation of protein denaturation free energies and the inference of hot spots for protein associations. The theoretical results are validated vis-à-vis calorimetric data, revealing the destabilizing effect of epistructural polarization and its molecular origin.

Differential dynamic engagement within 24 SH3 domain: peptide complexes revealed by co-linear chemical shift perturbation analysis

There is increasing evidence for the functional importance of multiple dynamically populated states within single proteins. However, peptide binding by protein-protein interaction domains, such as the SH3 domain, has generally been considered to involve the full engagement of peptide to the binding surface with minimal dynamics and simple methods to determine dynamics at the binding surface for multiple related complexes have not been described. We have used NMR spectroscopy combined with isothermal titration calorimetry to comprehensively examine the extent of engagement to the yeast Abp1p SH3 domain for 24 different peptides. Over one quarter of the domain residues display co-linear chemical shift perturbation (CCSP) behavior, in which the position of a given chemical shift in a complex is co-linear with the same chemical shift in the other complexes, providing evidence that each complex exists as a unique dynamic rapidly inter-converting ensemble. The extent the specificity determining sub-surface of AbpSH3 is engaged as judged by CCSP analysis correlates with structural and thermodynamic measurements as well as with functional data, revealing the basis for significant structural and functional diversity amongst the related complexes. Thus, CCSP analysis can distinguish peptide complexes that may appear identical in terms of general structure and percent peptide occupancy but have significant local binding differences across the interface, affecting their ability to transmit conformational change across the domain and resulting in functional differences.

Primordial enemies: fungal pathogens in thrips societies

Microbial pathogens are ancient selective agents that have driven many aspects of multicellular evolution, including genetic, behavioural, chemical and immune defence systems. It appears that fungi specialised to attack insects were already present in the environments in which social insects first evolved and we hypothesise that if the early stages of social evolution required antifungal defences, then covariance between levels of sociality and antifungal defences might be evident in extant lineages, the defences becoming stronger with group size and increasing social organisation. Thus, we compared the activity of cuticular antifungal compounds in thrips species (Insecta: Thysanoptera) representing a gradient of increasing group size and sociality: solitary, communal, social and eusocial, against the entomopathogen Cordyceps bassiana. Solitary and communal species showed little or no activity. In contrast, the social and eusocial species killed this fungus, suggesting that the evolution of sociality has been accompanied by sharp increases in the effectiveness of antifungal compounds. The antiquity of fungal entomopathogens, demonstrated by fossil finds, coupled with the unequivocal response of thrips colonies to them shown here, suggests two new insights into the evolution of thrips sociality: First, traits that enabled nascent colonies to defend themselves against microbial pathogens should be added to those considered essential for social evolution. Second, limits to the strength of antimicrobials, through resource constraints or self-antibiosis, may have been overcome by increase in the numbers of individuals secreting them, thus driving increases in colony size. If this is the case for social thrips, then we may ask: did antimicrobial traits and microbes such as fungal entomopathogens play an integral part in the evolution of insect sociality in general?

Role of tyrosine hot-spot residues at the interface of colicin E9 and immunity protein 9: a comparative free energy simulation study

The endonuclease activity of the bacterial colicin 9 enzyme is controlled by the specific and high-affinity binding of immunity protein 9 (Im9). Molecular dynamics simulation studies in explicit solvent were used to investigate the free energy change associated with the mutation of two hot-spot interface residues [tyrosine (Tyr): Tyr54 and Tyr55] of Im9 to Ala. In addition, the effect of several other mutations (Leu33Ala, Leu52Ala, Val34Ala, Val37Ala, Ser48Ala, and Ile53Ala) with smaller influence on binding affinity was also studied. Good qualitative agreement of calculated free energy changes and experimental data on binding affinity of the mutations was observed. The simulation studies can help to elucidate the molecular details on how the mutations influence protein-protein binding affinity. The role of solvent and conformational flexibility of the partner proteins was studied by comparing the results in the presence or absence of solvent and with or without positional restraints. Restriction of the conformational mobility of protein partners resulted in significant changes of the calculated free energies but of similar magnitude for isolated Im9 and for the complex and therefore in only modest changes of binding free energy differences. Although the overall binding free energy change was similar for the two Tyr-Ala mutations, the physical origin appeared to be different with solvation changes contributing significantly to the Tyr55Ala mutation and to a loss of direct protein-protein interactions dominating the free energy change due to the Tyr54Ala mutation.

Combining coarse-grained nonbonded and atomistic bonded interactions for protein modeling

A hybrid coarse-grained (CG) and atomistic (AT) model for protein simulations and rapid searching and refinement of peptide-protein complexes has been developed. In contrast to other hybrid models that typically represent spatially separate parts of a protein by either a CG or an AT force field model, the present approach simultaneously represents the protein by an AT (united atom) and a CG model. The interactions of the protein main chain are described based on the united atom force field allowing a realistic representation of protein secondary structures. In addition, the AT description of all other bonded interactions keeps the protein compatible with a realistic bonded geometry. Nonbonded interactions between side chains and side chains and main chain are calculated at the level of a CG model using a knowledge-based potential. Unrestrained molecular dynamics simulations on several test proteins resulted in trajectories in reasonable agreement with the corresponding experimental structures. Applications to the refinement of docked peptide-protein complexes resulted in improved complex structures. Application to the rapid refinement of docked protein-protein complex is also possible but requires further optimization of force field parameters.

Coarse-grained simulations of protein-protein association: an energy landscape perspective

Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes.