On the Contribution of Water-Mediated Interactions to Protein-Complex Stability

De novo design of mini-binder proteins against IL-2 receptor β chain

IL-2 regulates the immune response by interacting with different IL-2 receptor (IL-2R) subunits. High dose of IL-2 binds to IL-2Rβγc heterodimer, which induce various side effects while activating immune function. Disrupting IL-2 and IL-2R interactions can block IL-2 mediated immune response. Here, we used a computational approach to de novo design mini-binder proteins against IL-2R β chain (IL-2Rβ) to block IL-2 signaling. The hydrophobic region where IL-2 binds to IL-2Rβ was selected and the promising binding mode was broadly explored. Three mini-binders with amino acid numbers ranging from 55 to 65 were obtained and binder 1 showed the best effects in inhibiting CTLL-2 cells proliferation and STAT5 phosphorylation. Molecular dynamics simulation showed that the binding of binder 1 to IL-2Rβ was stable; the free energy of binder1/IL-2Rβ complex was lower, indicating that the affinity of binder 1 to IL-2Rβ was higher than that of IL-2. Free energy decomposition suggested that the ARG35 and ARG131 of IL-2Rβ might be the key to improve the affinity of binder. Our efforts provided new insights in developing of IL-2R blocker, offering a potential strategy for ameliorating the side effects of IL-2 treatment.

The first structure of human Golm1 coiled coil domain reveals an unexpected tetramer and highlights its structural diversity

Golgi membrane protein 1 (Golm1), a transmembrane protein with diverse subcellular localizations, has garnered significant attention in recent years due to its strong association with the development and progression of liver diseases and numerous cancers. Interestingly, although Golm1 is a membrane protein, the C-terminal of Golm1, which contains a coiled coil domain and a flexible acid region, can also be detected in the plasma of patients with various liver diseases. Notably, the coiled coil domain of serum Golm1 is postulated to play a pivotal role in physiological and pathological functions. However, little is currently known about the structure of this coiled coil domain and the full-length protein, which may limit our understanding of Golm1. Therefore, this study aims to address this gap in knowledge and reports the first crystal structure of the coiled coil domain of Golm1 at a resolution of 2.28 Å. Meanwhile, we have also confirmed that the Golm1 coiled coil domain in solution can form tetramer. Our results reveal that Golm1 can form a novel tetrameric structure that differs from the previous reported dimeric structure Golm1 could assemble, which may provide novel insights into the diversity of physiological functions and pathological roles.

Exploring the uncharted territory of the potential protein-protein interactions of cytosolic malate dehydrogenase

In this review, we examine the protein-protein interactions of cytosolic malate dehydrogenase (MDH), an under-studied area in cellular metabolism. We provide a comprehensive overview of MDH involvement in metabolism, especially its interactions with metabolic partners and dynamics of changing metabolism. We present an analysis of the biophysical nature of these interactions and the current methods used to study them. Our review includes an assessment of computational docking studies, which offer initial hypotheses about potential MDH interaction partners. Furthermore, we provide a summary of the sparse yet insightful experimental evidence available, establishing a foundation for future research. By integrating biophysical analysis and methodological advancements, this paper aims to illuminate the intricate network of interactions involving cytosolic MDH and their metabolic implications. This work not only contributes to our understanding of MDH's role in metabolism but also highlights the potential impact of these interactions in metabolic disorders.

Phase separation of multicomponent peptide mixtures into dehydrated clusters with hydrophilic cores

Phase separation of biomolecules underlies the formation and regulation of various membraneless condensates in cells. How condensates function reliably while surrounded by heterogeneous and dynamic mixtures of biomolecular components with specific and nonspecific interactions is yet to be understood. Studying multicomponent biomolecular mixtures with designer peptides has recently become an attractive avenue for learning about physicochemical principles governing cellular condensates. In this work, we employed long-timescale atomistic simulations of multicomponent tripeptide mixtures with all residue substitutions to illuminate the nature of direct and water-mediated interactions in a prototypical cellular condensate environment. We find that peptide mixtures form clusters with inverse hydrophobic order. Most multivalent and charged residues are localized in the cluster's core, with a large fraction of nonaromatic hydrophobic residues remaining on the surface. This inverse hydrophobic order in peptide clusters is partly driven by the expulsion of nonspecifically bound water molecules following peptide cluster growth. The growth of clusters is also accompanied by the formation of increasing numbers of specific water-mediated interactions between polar and charged residues. While the present study focused on the condensation of short peptide motifs, the general findings and analysis techniques should be helpful for future studies on larger peptides and protein condensation.

De novo design of a protein binder against Staphylococcus enterotoxin B

Staphylococcus enterotoxin B (SEB) interacts with MHC-II molecules to overactivate immune cells and thereby to produce excessive pro-inflammatory cytokines. Disrupting the interactions between SEB and MHC-II helps eliminate the lethal threat posed by SEB. In this study, a de novo computational approach was used to design protein binders targeting SEB. The MHC-II binding domain of SEB was selected as the target, and the possible promising binding mode was broadly explored. The obtained original binder was folded into triple-helix bundles and contained 56 amino acids with molecular weight 5.9 kDa. The interface of SEB and the binder was highly hydrophobic. ProteinMPNN optimization further enlarged the hydrophobic region of the binder and improved the stability of the binder-SEB complex. In vitro study demonstrated that the optimized binder significantly inhibited the inflammatory response induced by SEB. Overall, our research demonstrated the applicability of this approach in de novo designing protein binders against SEB, and thereby providing potential therapeutics for SEB induced diseases.

The Cdc48 N-terminal domain has a molecular switch that mediates the Npl4-Ufd1-Cdc48 complex formation

Cdc48 (VCP/p97) is a major AAA-ATPase involved in protein quality control, along with its canonical cofactors Ufd1 and Npl4 (UN). Here, we present novel structural insights into the interactions within the Cdc48-Npl4-Ufd1 ternary complex. Using integrative modeling, we combine subunit structures with crosslinking mass spectrometry (XL-MS) to map the interaction between Npl4 and Ufd1, alone and in complex with Cdc48. We describe the stabilization of the UN assembly upon binding with the N-terminal-domain (NTD) of Cdc48 and identify a highly conserved cysteine, C115, at the Cdc48-Npl4-binding interface which is central to the stability of the Cdc48-Npl4-Ufd1 complex. Mutation of Cys115 to serine disrupts the interaction between Cdc48-NTD and Npl4-Ufd1 and leads to a moderate decrease in cellular growth and protein quality control in yeast. Our results provide structural insight into the architecture of the Cdc48-Npl4-Ufd1 complex as well as its in vivo implications.

Quantifying the Molecular Polarization Response of Liquid Water Interfaces at Heterogeneously Charged Surfaces

The hydration shells of proteins mediate interactions, such as small molecule binding, that are vital to their biological function or in some cases their dysfunction. However, even when the structure of a protein is known, the properties of its hydration environment cannot be easily predicted due to the complex interplay between protein surface heterogeneity and the collective structure of water's hydrogen bonding network. This manuscript presents a theoretical study of the influence of surface charge heterogeneity on the polarization response of the liquid water interface. We focus our attention on classical point charge models of water, where the polarization response is limited to molecular reorientation. We introduce a new computational method for analyzing simulation data that is capable of quantifying water's collective polarization response and determining the effective surface charge distribution of hydrated surfaces over atomistic length scales. To illustrate the utility of this method, we present the results of molecular dynamics simulations of liquid water in contact with a heterogeneous model surface and the CheY protein.

Guanidinium–amino acid hydrogen-bonding interactions in protein crystal structures: implications for guanidinium-induced protein denaturation

Structural analysis of guanidinium–amino acid interaction pairs in protein crystal structures is coupled with an effective scheme for classifying the optimized pairs, to gain understanding of the guanidinium:protein hydrogen bonding modes.

Antibody CDR amino acids underlying the functionality of antibody repertoires in recognizing diverse protein antigens

Antibodies recognize protein antigens with exquisite specificity in a complex aqueous environment, where interfacial waters are an integral part of the antibody–protein complex interfaces. In this work, we elucidate, with computational analyses, the principles governing the antibodies’ specificity and affinity towards their cognate protein antigens in the presence of explicit interfacial waters. Experimentally, in four model antibody–protein complexes, we compared the contributions of the interaction types in antibody–protein antigen complex interfaces with the antibody variants selected from phage-displayed synthetic antibody libraries. Evidently, the specific interactions involving a subset of aromatic CDR (complementarity determining region) residues largely form the predominant determinant underlying the specificity of the antibody–protein complexes in nature. The interfacial direct/water-mediated hydrogen bonds accompanying the CDR aromatic interactions are optimized locally but contribute little in determining the epitope location. The results provide insights into the phenomenon that natural antibodies with limited sequence and structural variations in an antibody repertoire can recognize seemingly unlimited protein antigens. Our work suggests guidelines in designing functional artificial antibody repertoires with practical applications in developing novel antibody-based therapeutics and diagnostics for treating and preventing human diseases.

GalaxyWater-CNN: Prediction of Water Positions on the Protein Structure by a 3D-Convolutional Neural Network

Proteins interact with numerous water molecules to perform their physiological functions in biological organisms. Most water molecules act as solvent media; hence, their roles may be considered implicitly in theoretical treatments of protein structure and function. However, some water molecules interact intimately with proteins and require explicit treatment to understand their effects. Most physics-based computational methods are limited in their ability to accurately locate water molecules on protein surfaces because of inaccurate energy functions. Instead of relying on an energy function, this study attempts to learn the locations of water molecules from structural data. GalaxyWater-convolutional neural network (CNN) predicts water positions on protein chains, protein-protein interfaces, and protein-compound binding sites using a 3D-CNN model that is trained to generate a water score map on a given protein structure. The training data are compiled from high-resolution protein crystal structures resolved together with water molecules. GalaxyWater-CNN shows improved water prediction performance both in the coverage of crystal water molecules and in the accuracy of the predicted water positions when compared with previous energy-based methods. This method shows a superior performance in predicting water molecules that form hydrogen-bond networks precisely. The web service and the source code of this water prediction method are freely available at https://galaxy.seoklab.org/gwcnn and https://github.com/seoklab/GalaxyWater-CNN, respectively.

Protein Engineering in the Design of Protein-Protein Interactions: SARS-CoV-2 Inhibitors as a Test Case

The formation of specific protein-protein interactions (PPIs) drive most biological processes. Malfunction of such interactions is the molecular driver of many diseases. Our ability to engineer existing PPIs or create new ones has become a vital research tool. In addition, engineered proteins with new or altered interactions are among the most critical drugs that have been developed in recent years. These include antibodies, cytokines, inhibitors, and others. Here, we provide a perspective on the current status of the methods used to engineer new or altered PPIs. The emergence of the COVID-19 pandemic, which resulted in a worldwide quest to develop specific PPI inhibitors as drugs, provided an up-to-date and state-of-the-art status report on the methodologies for engineering PPIs targeting the interaction of the viral spike protein with its cellular target, ACE2. Multiple, very high affinity binders were generated within a few months using in vitro evolution by itself, or in combination with computational design. The different experimental and computational methods used to block this interaction provide a road map for the future of PPI engineering.

Identifying hydrophobic protein patches to inform protein interaction interfaces

Interactions between proteins lie at the heart of numerous biological processes and are essential for the proper functioning of the cell. Although the importance of hydrophobic residues in driving protein interactions is universally accepted, a characterization of protein hydrophobicity, which informs its interactions, has remained elusive. The challenge lies in capturing the collective response of the protein hydration waters to the nanoscale chemical and topographical protein patterns, which determine protein hydrophobicity. To address this challenge, here, we employ specialized molecular simulations wherein water molecules are systematically displaced from the protein hydration shell; by identifying protein regions that relinquish their waters more readily than others, we are then able to uncover the most hydrophobic protein patches. Surprisingly, such patches contain a large fraction of polar/charged atoms and have chemical compositions that are similar to the more hydrophilic protein patches. Importantly, we also find a striking correspondence between the most hydrophobic protein patches and regions that mediate protein interactions. Our work thus establishes a computational framework for characterizing the emergent hydrophobicity of amphiphilic solutes, such as proteins, which display nanoscale heterogeneity, and for uncovering their interaction interfaces.

GalaxyWater-wKGB: Prediction of Water Positions on Protein Structure Using wKGB Statistical Potential

Proteins fold and function in water, and protein-water interactions play important roles in protein structure and function. In computational studies on protein structure and interaction, the effect of water is considered either implicitly or explicitly. Implicit water models are frequently used in protein structure prediction and docking because they are computationally much more efficient than explicit water models, which are often employed in molecular dynamics (MD) simulations. However, implicit water models that treat water as a continuous solvent medium cannot account for specific atomistic protein-water interactions that are critical for structure formation and interactions with other molecules. Various methods for predicting water molecules that form specific atomistic interactions with proteins have been developed. Methods involving MD simulations or the integral equation theory tend to produce more accurate results at a higher computational cost than simple geometry- or energy-based methods. Here, we present a novel method for predicting water positions on a protein surface called GalaxyWater-wKGB, which is based on a statistical potential, a water knowledge-based potential based on the generalized Born model (wKGB). This method is accurate and rapid because it does not require conformational sampling or iterative computation owing to the effective statistical treatment employed to derive the potential. The statistical potential describes specific protein atom-water interactions more accurately than conventional potentials by considering the dependence on the degree of solvent accessibility of protein atoms as well as on protein atom-water distances and orientations. The introduction of solvent accessibility allows effective consideration of competing nonspecific protein-water and intraprotein interactions. When tested on high-resolution protein crystal structures, this method could recover similar or larger fractions of crystallographic water 180 times faster than the sophisticated integral equation theory, 3D-RISM. A web service of this water prediction method is freely available at http://galaxy.seoklab.org/wkgb.

A structure-based model for the prediction of protein-RNA binding affinity

Protein-RNA recognition is highly affinity-driven and regulates a wide array of cellular functions. In this study, we have curated a binding affinity data set of 40 protein-RNA complexes, for which at least one unbound partner is available in the docking benchmark. The data set covers a wide affinity range of eight orders of magnitude as well as four different structural classes. On average, we find the complexes with single-stranded RNA have the highest affinity, whereas the complexes with the duplex RNA have the lowest. Nevertheless, free energy gain upon binding is the highest for the complexes with ribosomal proteins and the lowest for the complexes with tRNA with an average of -5.7 cal/mol/Å2 in the entire data set. We train regression models to predict the binding affinity from the structural and physicochemical parameters of protein-RNA interfaces. The best fit model with the lowest maximum error is provided with three interface parameters: relative hydrophobicity, conformational change upon binding and relative hydration pattern. This model has been used for predicting the binding affinity on a test data set, generated using mutated structures of yeast aspartyl-tRNA synthetase, for which experimentally determined ΔG values of 40 mutations are available. The predicted ΔGempirical values highly correlate with the experimental observations. The data set provided in this study should be useful for further development of the binding affinity prediction methods. Moreover, the model developed in this study enhances our understanding on the structural basis of protein-RNA binding affinity and provides a platform to engineer protein-RNA interfaces with desired affinity.

Local and global anatomy of antibody-protein antigen recognition

Deciphering antibody-protein antigen recognition is of fundamental and practical significance. We constructed an antibody structural dataset, partitioned it into human and murine subgroups, and compared it with nonantibody protein-protein complexes. We investigated the physicochemical properties of regions on and away from the antibody-antigen interfaces, including net charge, overall antibody charge distributions, and their potential role in antigen interaction. We observed that amino acid preference in antibody-protein antigen recognition is entropy driven, with residues having low side-chain entropy appearing to compensate for the high backbone entropy in interaction with protein antigens. Antibodies prefer charged and polar antigen residues and bridging water molecules. They also prefer positive net charge, presumably to promote interaction with negatively charged protein antigens, which are common in proteomes. Antibody-antigen interfaces have large percentages of Tyr, Ser, and Asp, but little Lys. Electrostatic and hydrophobic interactions in the Ag binding sites might be coupled with Fab domains through organized charge and residue distributions away from the binding interfaces. Here we describe some features of antibody-antigen interfaces and of Fab domains as compared with nonantibody protein-protein interactions. The distributions of interface residues in human and murine antibodies do not differ significantly. Overall, our results provide not only a local but also a global anatomy of antibody structures.

Towards designing new nano-scale protein architectures

The complexity of designed bionano-scale architectures is rapidly increasing mainly due to the expanding field of DNA-origami technology and accurate protein design approaches. The major advantage offered by polypeptide nanostructures compared with most other polymers resides in their highly programmable complexity. Proteins allow in vivo formation of well-defined structures with a precise spatial arrangement of functional groups, providing extremely versatile nano-scale scaffolds. Extending beyond existing proteins that perform a wide range of functions in biological systems, it became possible in the last few decades to engineer and predict properties of completely novel protein folds, opening the field of protein nanostructure design. This review offers an overview on rational and computational design approaches focusing on the main achievements of novel protein nanostructure design.

Systematic substitutions at BLIP position 50 result in changes in binding specificity for class A β-lactamases

Background

The production of β-lactamases by bacteria is the most common mechanism of resistance to the widely prescribed β-lactam antibiotics. β-lactamase inhibitory protein (BLIP) competitively inhibits class A β-lactamases via two binding loops that occlude the active site. It has been shown that BLIP Tyr50 is a specificity determinant in that substitutions at this position result in large differential changes in the relative affinity of BLIP for class A β-lactamases.

Results

In this study, the effect of systematic substitutions at BLIP position 50 on binding to class A β-lactamases was examined to further explore the role of BLIP Tyr50 in modulating specificity. The results indicate the sequence requirements at position 50 are widely different depending on the target β-lactamase. Stringent sequence requirements were observed at Tyr50 for binding Bacillus anthracis Bla1 while moderate requirements for binding TEM-1 and relaxed requirements for binding KPC-2 β-lactamase were seen. These findings cannot be easily rationalized based on the β-lactamase residues in direct contact with BLIP Tyr50 since they are identical for Bla1 and KPC-2 suggesting that differences in the BLIP-β-lactamase interface outside the local environment of Tyr50 influence the effect of substitutions.

Conclusions

Results from this study and previous studies suggest that substitutions at BLIP Tyr50 may induce changes at the interface outside its local environment and point to the complexity of predicting the impact of substitutions at a protein-protein interaction interface.

Modulation of Re-initiation of Measles Virus Transcription at Intergenic Regions by PXD to NTAIL Binding Strength

Measles virus (MeV) and all Paramyxoviridae members rely on a complex polymerase machinery to ensure viral transcription and replication. Their polymerase associates the phosphoprotein (P) and the L protein that is endowed with all necessary enzymatic activities. To be processive, the polymerase uses as template a nucleocapsid made of genomic RNA entirely wrapped into a continuous oligomer of the nucleoprotein (N). The polymerase enters the nucleocapsid at the 3'end of the genome where are located the promoters for transcription and replication. Transcription of the six genes occurs sequentially. This implies ending and re-initiating mRNA synthesis at each intergenic region (IGR). We explored here to which extent the binding of the X domain of P (XD) to the C-terminal region of the N protein (NTAIL) is involved in maintaining the P/L complex anchored to the nucleocapsid template during the sequential transcription. Amino acid substitutions introduced in the XD-binding site on NTAIL resulted in a wide range of binding affinities as determined by combining protein complementation assays in E. coli and human cells and isothermal titration calorimetry. Molecular dynamics simulations revealed that XD binding to NTAIL involves a complex network of hydrogen bonds, the disruption of which by two individual amino acid substitutions markedly reduced the binding affinity. Using a newly designed, highly sensitive dual-luciferase reporter minigenome assay, the efficiency of re-initiation through the five measles virus IGRs was found to correlate with NTAIL/XD KD. Correlatively, P transcript accumulation rate and F/N transcript ratios from recombinant viruses expressing N variants were also found to correlate with the NTAIL to XD binding strength. Altogether, our data support a key role for XD binding to NTAIL in maintaining proper anchor of the P/L complex thereby ensuring transcription re-initiation at each intergenic region.

Structure of the ordered hydration of amino acids in proteins: analysis of crystal structures

Crystallography provides unique information about the arrangement of water molecules near protein surfaces. Using a nonredundant set of 2818 protein crystal structures with a resolution of better than 1.8 Å, the extent and structure of the hydration shell of all 20 standard amino-acid residues were analyzed as function of the residue conformation, secondary structure and solvent accessibility. The results show how hydration depends on the amino-acid conformation and the environment in which it occurs. After conformational clustering of individual residues, the density distribution of water molecules was compiled and the preferred hydration sites were determined as maxima in the pseudo-electron-density representation of water distributions. Many hydration sites interact with both main-chain and side-chain amino-acid atoms, and several occurrences of hydration sites with less canonical contacts, such as carbon-donor hydrogen bonds, OH-π interactions and off-plane interactions with aromatic heteroatoms, are also reported. Information about the location and relative importance of the empirically determined preferred hydration sites in proteins has applications in improving the current methods of hydration-site prediction in molecular replacement, ab initio protein structure prediction and the set-up of molecular-dynamics simulations.

Molecular basis of in vitro affinity maturation and functional evolution of a neutralizing anti-human GM-CSF antibody

X-ray structure analysis of 4 antibody Fab fragments, each in complex with human granulocyte macrophage colony stimulating factor (GM-CSF), was performed to investigate the changes at the protein-protein binding interface during the course of in vitro affinity maturation by phage display selection. The parental antibody MOR03929 was compared to its derivatives MOR04252 (CDR-H2 optimized), MOR04302 (CDR-L3 optimized) and MOR04357 (CDR-H2 and CDR-L3 optimized). All antibodies bind to a conformational epitope that can be divided into 3 sub-epitopes. Specifically, MOR04357 binds to a region close to the GM-CSF N-terminus (residues 11-24), a short second sub-epitope (residues 83-89) and a third at the C-terminus (residues 112-123). Modifications introduced during affinity maturation in CDR-H2 and CDR-L3 led to the establishment of additional hydrogen bonds and van der Waals contacts, respectively, providing a rationale for the observed improvement in binding affinity and neutralization potency. Once GM-CSF is complexed to the antibodies, modeling predicts a sterical clash with GM-CSF binding to GM-CSF receptor α and β chain. This predicted mutually exclusive binding was confirmed by a GM-CSF receptor α chain ligand binding inhibition assay. Finally, high throughput sequencing of clones obtained after affinity maturation phage display pannings revealed highly selected consensus sequences for CDR-H2 as well for CDR-L3, which are in accordance with the sequence of the highest affinity antibody MOR04357. The resolved crystal structures highlight the criticality of these strongly selected residues for high affinity interaction with GM-CSF.

Molecular Docking studies of FKBP12-mTOR inhibitors using binding predictions

Mammalian target of rapamycin (mTOR) is a key regulator of cell growth, proliferation and angiogenesis. mTOR signaling is frequently hyper activated in a broad spectrum of human cancers thereby making it a potential drug target. The current drugs available have been successful in inhibiting the mTOR signaling, nevertheless, show low oral bioavailability and suboptimal solubility. Considering the narrow therapeutic window of the available inhibitors, through computational approaches, the present study pursues to identify a compound with optimal oral bioavailability and better solubility properties in addition ensuing high affinity between FKBP12 and FRB domain of mTOR. Current mTOR inhibitors; Everolimus, Temsirolimus Deforolimus and Echinomycin served as parent molecules for similarity search with a threshold of 95%. The query molecules and respective similar molecules were docked at the binding cleft of FKBP12 protein. Aided by MolDock algorithm, high affinity compounds against FKBP12 were retrieved. Patch Dock supervised protein-protein interactions were established between FRB domain of mTOR and ligand (query and similar) bound and free states of FKBP12. All the similar compounds thus retrieved showed better solubility properties and enabled better complex formation of mTOR and FKBP12. In particular Everolimus similar compound PubChem ID: 57284959 showed appreciable drugs like properties bestowed with better solubility higher oral bioavailability. In addition this compound brought about enhanced interaction between FKBP12 and FRB domain of mTOR. In the study, we report Everolimus similar compound PubChem ID: 57284959 to be potential inhibitor for mTOR pathway which can overcome the affinity and solubility concerns of current mTOR drugs.

ABBREVIATIONS

mTOR - Mammalian Target of Rapamycin, FRB domain - FKBP12-rapamycin associated protein, FKBP12 - FK506-binding protein 12, OPLS - Optimized Potentials for Liquid Simulations, Akt - RAC-alpha serine/threonine-protein kinase, PI3K - phosphatidylinositide 3-kinases.

Weighted protein residue networks based on joint recurrences between residues

BACKGROUND

Weighted and un-weighted protein residue networks can predict key functional residues in proteins based on the closeness centrality C and betweenness centrality B values for each residue. A static snapshot of the protein structure, and a cutoff distance, are used to define edges between the network nodes. In this work we apply the weighted network approach to study the β-Lactamase Inhibitory Protein (BLIP). Joint recurrences extracted from molecular dynamics MD trajectory positions of the protein residue carbon alpha atoms are used to define edge weights between nodes, and no cutoff distance is used. The results for B and C from our approach are compared with those extracted from an un-weighted network, and a weighted network that uses interatomic contacts to define edge weights between nodes, respectively.

RESULTS

The joint recurrence weighted network approach performs well in pointing out key protein residues. Furthermore, it seems to emphasize residues with medium to high relative solvent accessibility that lie in loop regions between secondary structure elements of the protein.

CONCLUSIONS

Protein residue networks that use joint recurrences extracted from molecular dynamics simulations of a solvated protein perform well in pointing to hotspot residues and hotspot clusters. This approach uses no distance cutoff threshold, and does not exclude any interactions between the residues, including water-mediated interactions.

Molecular docking analysis of RN18 and VEC5 in A3G-Vif inhibition

The HIV-1 protein Vif is essential for in vivo viral replication that targets the human DNA-editing enzyme, APOBEC3G (A3G), which inhibits replication of retroviruses. The Vif-A3G interactions are believed to be important targets for antiviral drug development. Since the interactions of A3G and Vif evade the ubiquitination pathways in human host, the viral replication precedes which otherwise spreads infection. In this study, two potent Vif inhibitors RN 18 and VEC5 have been evaluated for their inhibitory potential employing ligand receptor and protein-protein interactions studies. VEC 5 showed better interaction with Vif than RN18. Predicted data show that VEC5 bound Vif and RN18 bound Vif showed diminished interaction to A3G compared to inhibitor unbound Vif. However, this should be further validated using in vitro studies.

Hydration of protein-RNA recognition sites

We investigate the role of water molecules in 89 protein–RNA complexes taken from the Protein Data Bank. Those with tRNA and single-stranded RNA are less hydrated than with duplex or ribosomal proteins. Protein–RNA interfaces are hydrated less than protein–DNA interfaces, but more than protein–protein interfaces. Majority of the waters at protein–RNA interfaces makes multiple H-bonds; however, a fraction do not make any. Those making H-bonds have preferences for the polar groups of RNA than its partner protein. The spatial distribution of waters makes interfaces with ribosomal proteins and single-stranded RNA relatively ‘dry’ than interfaces with tRNA and duplex RNA. In contrast to protein–DNA interfaces, mainly due to the presence of the 2′OH, the ribose in protein–RNA interfaces is hydrated more than the phosphate or the bases. The minor groove in protein–RNA interfaces is hydrated more than the major groove, while in protein–DNA interfaces it is reverse. The strands make the highest number of water-mediated H-bonds per unit interface area followed by the helices and the non-regular structures. The preserved waters at protein–RNA interfaces make higher number of H-bonds than the other waters. Preserved waters contribute toward the affinity in protein–RNA recognition and should be carefully treated while engineering protein–RNA interfaces.

Molecular simulations of a dynamic protein complex: role of salt-bridges and polar interactions in configurational transitions

Ion charge pairs and hydrogen bonds have been extensively studied for their roles in stabilizing protein complexes and in steering the process of protein association. Recently, it has become clear that some protein complexes are dynamic in that they interconvert between several alternate configurations. We have previously characterized one such system: the EphA2:SHIP2 SAM-SAM heterodimer by solution NMR. Here we carried out extensive all-atom molecular-dynamics simulations on a microsecond time-scale starting with different NMR-derived structures for the complex. Transitions are observed between several discernible configurations at average time intervals of 50-100 ns. The domains reorient relative to one another by substantial rotation and a slight shifting of the interfaces. Bifurcated and intermediary salt-bridge and hydrogen-bond interactions play a role in the transitions in a process that can be described as moving along a "monkey-bar". We notice an increased density of salt bridges near protein interaction surfaces that appear to enable these transitions, also suggesting why the trajectories can become kinetically hindered in regions where fewer of such interactions are possible. In this context, even microsecond molecular-dynamics simulations are not sufficient to sample the energy landscape unless the structures remain close to their experimentally derived low-energy configurations.

Structural basis of recognition of interferon-α receptor by tyrosine kinase 2

Tyrosine kinase 2 (TYK2) is a member of the Janus kinase (JAK) family of non-receptor tyrosine kinases, which are essential for proper signaling in immune responses and development. Here we present a 2.0 angstrom resolution crystal structure of a receptor-binding fragment of human TYK2 encompassing the FERM and SH2 domains in complex with a so-called “box2” containing intracellular peptide motif from the IFNα receptor (IFNAR1). The TYK2–IFNAR1 interface reveals an unexpected receptor-binding mode that mimics a SH2 domain–phosphopeptide interaction, with a glutamate replacing the canonical phosphotyrosine residue. This structure provides the first view to our knowledge of a JAK in complex with its cognate receptor and defines the molecular logic through which JAKs evolved to interact with divergent receptor sequences.

High-resolution crystal structure of Streptococcus pyogenes β-NAD⁺ glycohydrolase in complex with its endogenous inhibitor IFS reveals a highly water-rich interface

One of the virulence factors produced by Streptococcus pyogenes is β-NAD(+) glycohydrolase (SPN). S. pyogenes injects SPN into the cytosol of an infected host cell using the cytolysin-mediated translocation pathway. As SPN is toxic to bacterial cells themselves, S. pyogenes possesses the ifs gene that encodes an endogenous inhibitor for SPN (IFS). IFS is localized intracellularly and forms a complex with SPN. This intracellular complex must be dissociated during export through the cell envelope. To provide a structural basis for understanding the interactions between SPN and IFS, the complex was overexpressed between the mature SPN (residues 38-451) and the full-length IFS (residues 1-161), but it could not be crystallized. Therefore, limited proteolysis was used to isolate a crystallizable SPNct-IFS complex, which consists of the SPN C-terminal domain (SPNct; residues 193-451) and the full-length IFS. Its crystal structure has been determined by single anomalous diffraction and the model refined at 1.70 Å resolution. Interestingly, our high-resolution structure of the complex reveals that the interface between SPNct and IFS is highly rich in water molecules and many of the interactions are water-mediated. The wet interface may facilitate the dissociation of the complex for translocation across the cell envelope.

Quinary protein structure and the consequences of crowding in living cells: leaving the test-tube behind

Although the importance of weak protein-protein interactions has been understood since the 1980s, scant attention has been paid to this "quinary structure". The transient nature of quinary structure facilitates dynamic sub-cellular organization through loose grouping of proteins with multiple binding partners. Despite our growing appreciation of the quinary structure paradigm in cell biology, we do not yet understand how the many forces inside the cell--the excluded volume effect, the "stickiness" of the cytoplasm, and hydrodynamic interactions--perturb the weakest functional protein interactions. We discuss the unresolved problem of how the forces in the cell modulate quinary structure, and to what extent the cell has evolved to exert control over the weakest biomolecular interactions. We conclude by highlighting the new experimental and computational tools coming on-line for in vivo studies, which are a critical next step if we are to understand quinary structure in its native environment.

Probing the role of interfacial waters in protein-DNA recognition using a hybrid implicit/explicit solvation model

When proteins bind to their DNA target sites, ordered water molecules are often present at the protein-DNA interface bridging protein and DNA through hydrogen bonds. What is the role of these ordered interfacial waters? Are they important determinants of the specificity of DNA sequence recognition, or do they act in binding in a primarily nonspecific manner, by improving packing of the interface, shielding unfavorable electrostatic interactions, and solvating unsatisfied polar groups that are inaccessible to bulk solvent? When modeling details of structure and binding preferences, can fully implicit solvent models be fruitfully applied to protein-DNA interfaces, or must the individualistic properties of these interfacial waters be accounted for? To address these questions, we have developed a hybrid implicit/explicit solvation model that specifically accounts for the locations and orientations of small numbers of DNA-bound water molecules, while treating the majority of the solvent implicitly. Comparing the performance of this model with that of its fully implicit counterpart, we find that explicit treatment of interfacial waters results in a modest but significant improvement in protein side-chain placement and DNA sequence recovery. Base-by-base comparison of the performance of the two models highlights DNA sequence positions whose recognition may be dependent on interfacial water. Our study offers large-scale statistical evidence for the role of ordered water for protein-DNA recognition, together with detailed examination of several well-characterized systems. In addition, our approach provides a template for modeling explicit water molecules at interfaces that should be extensible to other systems.

Progressive dry-core-wet-rim hydration trend in a nested-ring topology of protein binding interfaces

BACKGROUND

Water is an integral part of protein complexes. It shapes protein binding sites by filling cavities and it bridges local contacts by hydrogen bonds. However, water molecules are usually not included in protein interface models in the past, and few distribution profiles of water molecules in protein binding interfaces are known.

RESULTS

In this work, we use a tripartite protein-water-protein interface model and a nested-ring atom re-organization method to detect hydration trends and patterns from an interface data set which involves immobilized interfacial water molecules. This data set consists of 206 obligate interfaces, 160 non-obligate interfaces, and 522 crystal packing contacts. The two types of biological interfaces are found to be drier than the crystal packing interfaces in our data, agreeable to a hydration pattern reported earlier although the previous definition of immobilized water is pure distance-based. The biological interfaces in our data set are also found to be subject to stronger water exclusion in their formation. To study the overall hydration trend in protein binding interfaces, atoms at the same burial level in each tripartite protein-water-protein interface are organized into a ring. The rings of an interface are then ordered with the core atoms placed at the middle of the structure to form a nested-ring topology. We find that water molecules on the rings of an interface are generally configured in a dry-core-wet-rim pattern with a progressive level-wise solvation towards to the rim of the interface. This solvation trend becomes even sharper when counterexamples are separated.

CONCLUSIONS

Immobilized water molecules are regularly organized in protein binding interfaces and they should be carefully considered in the studies of protein hydration mechanisms.

Using quantitative redox proteomics to dissect the yeast redoxome

To understand and eventually predict the effects of changing redox conditions and oxidant levels on the physiology of an organism, it is essential to gain knowledge about its redoxome: the proteins whose activities are controlled by the oxidation status of their cysteine thiols. Here, we applied the quantitative redox proteomic method OxICAT to Saccharomyces cerevisiae and determined the in vivo thiol oxidation status of almost 300 different yeast proteins distributed among various cellular compartments. We found that a substantial number of cytosolic and mitochondrial proteins are partially oxidized during exponential growth. Our results suggest that prevailing redox conditions constantly control central cellular pathways by fine-tuning oxidation status and hence activity of these proteins. Treatment with sublethal H(2)O(2) concentrations caused a subset of 41 proteins to undergo substantial thiol modifications, thereby affecting a variety of different cellular pathways, many of which are directly or indirectly involved in increasing oxidative stress resistance. Classification of the identified protein thiols according to their steady-state oxidation levels and sensitivity to peroxide treatment revealed that redox sensitivity of protein thiols does not predict peroxide sensitivity. Our studies provide experimental evidence that the ability of protein thiols to react to changing peroxide levels is likely governed by both thermodynamic and kinetic parameters, making predicting thiol modifications challenging and de novo identification of peroxide sensitive protein thiols indispensable.

Bound water at protein-protein interfaces: partners, roles and hydrophobic bubbles as a conserved motif

Background

There is a great interest in understanding and exploiting protein-protein associations as new routes for treating human disease. However, these associations are difficult to structurally characterize or model although the number of X-ray structures for protein-protein complexes is expanding. One feature of these complexes that has received little attention is the role of water molecules in the interfacial region.

Methodology

A data set of 4741 water molecules abstracted from 179 high-resolution (≤ 2.30 Å) X-ray crystal structures of protein-protein complexes was analyzed with a suite of modeling tools based on the HINT forcefield and hydrogen-bonding geometry. A metric termed Relevance was used to classify the general roles of the water molecules.

Results

The water molecules were found to be involved in: a) (bridging) interactions with both proteins (21%), b) favorable interactions with only one protein (53%), and c) no interactions with either protein (26%). This trend is shown to be independent of the crystallographic resolution. Interactions with residue backbones are consistent for all classes and account for 21.5% of all interactions. Interactions with polar residues are significantly more common for the first group and interactions with non-polar residues dominate the last group. Waters interacting with both proteins stabilize on average the proteins' interaction (−0.46 kcal mol⁻¹), but the overall average contribution of a single water to the protein-protein interaction energy is unfavorable (+0.03 kcal mol⁻¹). Analysis of the waters without favorable interactions with either protein suggests that this is a conserved phenomenon: 42% of these waters have SASA ≤ 10 Ų and are thus largely buried, and 69% of these are within predominantly hydrophobic environments or “hydrophobic bubbles”. Such water molecules may have an important biological purpose in mediating protein-protein interactions.

Analysis of the binding forces driving the tight interactions between beta-lactamase inhibitory protein-II (BLIP-II) and class A beta-lactamases

β-Lactamases hydrolyze β-lactam antibiotics to provide drug resistance to bacteria. β-Lactamase inhibitory protein-II (BLIP-II) is a potent proteinaceous inhibitor that exhibits low picomolar affinity for class A β-lactamases. This study examines the driving forces for binding between BLIP-II and β-lactamases using a combination of presteady state kinetics, isothermal titration calorimetry, and x-ray crystallography. The measured dissociation rate constants for BLIP-II and various β-lactamases ranged from 10(-4) to 10(-7) s(-1) and are comparable with those found in some of the tightest known protein-protein interactions. The crystal structures of BLIP-II alone and in complex with Bacillus anthracis Bla1 β-lactamase revealed no significant side-chain movement in BLIP-II in the complex versus the monomer. The structural rigidity of BLIP-II minimizes the loss of the entropy upon complex formation and, as indicated by thermodynamics experiments, may be a key determinant of the observed potent inhibition of β-lactamases.

Structural linkage between ligand discrimination and receptor activation by type I interferons

Type I Interferons (IFNs) are important cytokines for innate immunity against viruses and cancer. Sixteen human type I IFN variants signal through the same cell-surface receptors, IFNAR1 and IFNAR2, yet they can evoke markedly different physiological effects. The crystal structures of two human type I IFN ternary signaling complexes containing IFNα2 and IFNω reveal recognition modes and heterotrimeric architectures that are unique among the cytokine receptor superfamily but conserved between different type I IFNs. Receptor-ligand cross-reactivity is enabled by conserved receptor-ligand "anchor points" interspersed among ligand-specific interactions that "tune" the relative IFN-binding affinities, in an apparent extracellular "ligand proofreading" mechanism that modulates biological activity. Functional differences between IFNs are linked to their respective receptor recognition chemistries, in concert with a ligand-induced conformational change in IFNAR1, that collectively control signal initiation and complex stability, ultimately regulating differential STAT phosphorylation profiles, receptor internalization rates, and downstream gene expression patterns.

Modeling of the water network at protein-RNA interfaces

Water plays an important role in the mediation of biomolecular interactions. Thus, accurate prediction and evaluation of water-mediated interactions is an important element in the computational design of interfaces involving proteins, RNA, and DNA. Here, we use an algorithm (WATGEN) to predict the locations of interfacial water molecules for a data set of 224 protein-RNA interfaces. The accuracy of the prediction is validated against water molecules present in the X-ray structures of 105 of these complexes. The complexity of the water networks is deconvoluted through definition of the characteristics of each water molecule based on its bridging properties between the protein and RNA and on its depth in the interface with respect to the bulk solvent. This approach has the potential for scoring the water network for incorporation into the computational design of protein-RNA complexes.

Stabilization of a protein nanocage through the plugging of a protein-protein interfacial water pocket

The unique structural properties of the ferritin protein cages have provided impetus to focus on the methodical study of these self-assembling nanosystems. Among these proteins, Escherichia coli bacterioferritin (EcBfr), although architecturally very similar to other members of the family, shows structural instability and an incomplete self-assembly behavior by populating two oligomerization states. Through computational analysis and comparison to its homologues, we have found that this protein has a smaller than average dimeric interface on its 2-fold symmetry axis mainly because of the existence of an interfacial water pocket centered around two water-bridged asparagine residues. To investigate the possibility of engineering EcBfr for modified structural stability, we have used a semiempirical computational method to virtually explore the energy differences of the 480 possible mutants at the dimeric interface relative to that of wild-type EcBfr. This computational study also converged on the water-bridged asparagines. Replacing these two asparagines with hydrophobic amino acids resulted in proteins that folded into α-helical monomers and assembled into cages as evidenced by circular dichroism and transmission electron microscopy. Both thermal and chemical denaturation confirmed that, in all cases, these proteins, in agreement with the calculations, possessed increased stability. One of the three mutations shifts the population in favor of the higher-order oligomerization state in solution as evidenced by both size exclusion chromatography and native gel electrophoresis. These results taken together suggest that our low-level design was successful and that it may be possible to apply the strategy of targeting water pockets at protein--protein interfaces to other protein cage and self-assembling systems. More generally, this study further demonstrates the power of jointly employing in silico and in vitro techniques to understand and enhance biostructural energetics.

Role of bridging water molecules in GSK3β-inhibitor complexes: insights from QM/MM, MD, and molecular docking studies

The role of water molecules is increasingly gaining interest in drug design, and several studies have highlighted their paramount contributions to the specificity and the affinity of ligand binding. In this study, we employ the two-layer ONIOM-based quantum mechanics/molecular mechanics (QM/MM) calculations, molecular dynamics (MD) simulations, and molecular docking studies to investigate the effect of bridging water molecules at the GSK3β-inhibitors interfaces. The results obtained from the ONIOM geometry optimization and AIM analysis corroborated the presence of bridging water molecules that form hydrogen bonds with protein side chain of Thr138 and/or backbone of Gln185, and mediate interactions with inhibitors in the 10 selected GSK3β-inhibitor complexes. Subsequently, MD simulations carried out on a representative system of 1R0E demonstrated that the bridging water molecule is stable at the GSK3β-inhibitor interface and appears to contribute to the stability of the protein-inhibitor interactions. Furthermore, molecular docking studies of GSK3β-inhibitor complexes indicated that the inhibitors can increase binding affinities and the better docked conformation of inhibitors can be obtained by inclusion of the bridging water molecules, especially for the flexible inhibitors, in docking experiments into individual protein conformations. Our results elucidate the importance of bridging water molecules at the GSK3β-inhibitor interfaces and suggest that they might prove useful in rational drug design.

Triathlon for energy functions: who is the winner for design of protein-protein interactions?

Computational prediction of stabilizing mutations into monomeric proteins has become an almost ordinary task. Yet, computational stabilization of protein–protein complexes remains a challenge. Design of protein–protein interactions (PPIs) is impeded by the absence of an energy function that could reliably reproduce all favorable interactions between the binding partners. In this work, we present three energy functions: one function that was trained on monomeric proteins, while the other two were optimized by different techniques to predict side-chain conformations in a dataset of PPIs. The performances of these energy functions are evaluated in three different tasks related to design of PPIs: predicting side-chain conformations in PPIs, recovering native binding-interface sequences, and predicting changes in free energy of binding due to mutations. Our findings show that both functions optimized on side-chain repacking in PPIs are more suitable for PPI design compared to the function trained on monomeric proteins. Yet, no function performs best at all three tasks. Comparison of the three energy functions and their performances revealed that (1) burial of polar atoms should not be penalized significantly in PPI design as in single-protein design and (2) contribution of electrostatic interactions should be increased several-fold when switching from single-protein to PPI design. In addition, the use of a softer van der Waals potential is beneficial in cases when backbone flexibility is important. All things considered, we define an energy function that captures most of the nuances of the binding energetics and hence, should be used in future for design of PPIs.

Novel modulation factor quantifies the role of water molecules in protein interactions

Water molecules decrease the potential of mean force of a hydrogen bond (H-bond), as well as modulate (de)solvation forces, but exactly how much has not been easy to determine. Crystallographic water molecules provide snapshots of optimal solutions for the role of solvent in protein interactions, information that is often ignored by implicit solvent models. Motivated by high-resolution crystal structures, we describe a simple quantitative approach to explicitly incorporate the role of molecular water in protein interactions. Applications to protein-DNA interactions show that the accuracy of binding free-energy estimates improves significantly if a distinction is made between H-bonds that are desolvated (or only contact crystal waters), solvated by mobile waters trapped at the binding interface, or partially solvated through connections to bulk water. These different environments are modeled by a unique "water" scaling factor that decreases or increases the strength of hydrogen bonds depending on whether water contacts the acceptor or donor atoms or the bond is fully desolvated, respectively. Our empirical energies are fully consistent with mobile water molecules having a strong polarization effect in direct intermolecular interactions.

The interaction of microsomal cytochrome P450 2B4 with its redox partners, cytochrome P450 reductase and cytochrome b(5)

Cytochrome P450 2B4 is a microsomal protein with a multi-step reaction cycle similar to that observed in the majority of other cytochromes P450. The cytochrome P450 2B4-substrate complex is reduced from the ferric to the ferrous form by cytochrome P450 reductase. After binding oxygen, the oxyferrous protein accepts a second electron which is provided by either cytochrome P450 reductase or cytochrome b(5). In both instances, product formation occurs. When the second electron is donated by cytochrome b(5), catalysis (product formation) is ∼10- to 100-fold faster than in the presence of cytochrome P450 reductase. This allows less time for side product formation (hydrogen peroxide and superoxide) and improves by ∼15% the coupling of NADPH consumption to product formation. Cytochrome b(5) has also been shown to compete with cytochrome P450 reductase for a binding site on the proximal surface of cytochrome P450 2B4. These two different effects of cytochrome b(5) on cytochrome P450 2B4 reactivity can explain how cytochrome b(5) is able to stimulate, inhibit, or have no effect on cytochrome P450 2B4 activity. At low molar ratios (<1) of cytochrome b(5) to cytochrome P450 reductase, the more rapid catalysis results in enhanced substrate metabolism. In contrast, at high molar ratios (>1) of cytochrome b(5) to cytochrome P450 reductase, cytochrome b(5) inhibits activity by binding to the proximal surface of cytochrome P450 and preventing the reductase from reducing ferric cytochrome P450 to the ferrous protein, thereby aborting the catalytic reaction cycle. When the stimulatory and inhibitory effects of cytochrome b(5) are equal, it will appear to have no effect on the enzymatic activity. It is hypothesized that cytochrome b(5) stimulates catalysis by causing a conformational change in the active site, which allows the active oxidizing oxyferryl species of cytochrome P450 to be formed more rapidly than in the presence of reductase.

Stabilizing of a globular protein by a highly complex water network: a molecular dynamics simulation study on factor Xa

The role of water molecules is increasingly attracting attention in structural biology, and many studies have demonstrated their crucial contribution to the stability and function of proteins. Here, we present molecular dynamics studies on factor Xa (fXa) to investigate the effect of water molecules in this serine protease. fXa is a key enzyme in the blood coagulation cascade, and thus, an important target for antithrombotic drugs. A reasonable representation of the structure is crucial for an investigation at the molecular level and, thus, a prerequisite for structure-based drug design. Simulations of well-resolved fXa X-ray structures with different sets of water molecules show the importance of a well-determined water set for the simulation. We discuss implications of different water sets on the structure and dynamics of fXa.

Classical to path-integral adaptive resolution in molecular simulation: towards a smooth quantum-classical coupling

Simulations that couple different molecular models in an adaptive way by changing resolution on the fly allow us to identify the relevant degrees of freedom of a system. This, in turn, leads to a detailed understanding of the essential physics which characterizes a system. While the delicate process of transition from one model to another is well understood for the adaptivity between classical molecular models the same cannot be said for the quantum-classical adaptivity. The main reason for this is the difficulty in describing a continuous transition between two different kinds of physical principles: probabilistic for the quantum and deterministic for the classical. Here we report the basic principles of an algorithm that allows for a continuous and smooth transition by employing the path integral description of atoms.