Atomic contact vectors in protein-protein recognition

The ability to analyze and compare protein-protein interactions on the structural level is critical to our understanding of various aspects of molecular recognition and the functional interplay of components of biochemical networks. In this study, we introduce atomic contact vectors (ACVs) as an intuitive way to represent the physico-chemical characteristics of a protein-protein interface as well as a way to compare interfaces to each other. We test the utility of ACVs in classification by using them to distinguish between homodimers and crystal contacts. Our results compare favorably with those reported by other authors. We then apply ACVs to mine the PDB for all known protein-protein complexes and separate transient recognition complexes from permanent oligomeric ones. Getting at the basis of this difference is important for our understanding of recognition and we achieved a success rate of 91% for distinguishing these two classes of complexes. Although accessible surface area of the interface is a major discriminating feature, we also show that there are distinct differences in the contact preferences between the two kinds of complexes. Illustrating the superiority of ACVs as a basic comparison measure over a sequence-based approach, we derive a general rule of thumb to determine whether two protein-protein interfaces are redundant. With this method, we arrive at a nonredundant set of 209 recognition complexes--the largest set reported so far.     

Soluble mimics of a chemokine receptor: chemokine binding by receptor elements juxtaposed on a soluble scaffold

Despite the broad biological importance of G protein-coupled receptors (GPCRs), ligand recognition by GPCRs remains poorly understood. To explore the roles of GPCR extracellular elements in ligand binding and to provide a tractable system for structural analyses of GPCR/ligand interactions, we have developed a soluble protein that mimics ligand recognition by a GPCR. This receptor analog, dubbed CROSS5, consists of the N-terminal and third extracellular loop regions of CC chemokine receptor 3 (CCR3) displayed on the surface of a small soluble protein, the B1 domain of Streptococcal protein G. CROSS5 binds to the CCR3 ligand eotaxin with a dissociation equilibrium constant of 2.9 +/- 0.8 microM and competes with CCR3 for eotaxin binding. Control proteins indicate that juxtaposition of both CCR3 elements is required for optimal binding to eotaxin. Moreover, the affinities of CROSS5 for a series of eotaxin mutants are highly correlated with the apparent affinities of CCR3 for the same mutants, demonstrating that CROSS5 uses many of the same interactions as does the native receptor. The strategy used to develop CROSS5 could be applied to many other GPCRs, with a variety of potential applications.     

Dissecting protein-protein recognition sites

The recognition sites in 70 pairwise protein-protein complexes of known three-dimensional structure are dissected in a set of surface patches by clustering atoms at the interface. When the interface buries <2000 A2 of protein surface, the recognition sites usually form a single patch on the surface of each component protein. In contrast, larger interfaces are generally multipatch, with at least one pair of patches that are equivalent in size to a single-patch interface. Each recognition site, or patch within a site, contains a core made of buried interface atoms, surrounded by a rim of atoms that remain accessible to solvent in the complex. A simple geometric model reproduces the number and distribution of atoms within a patch. The rim is similar in composition to the rest of the protein surface, but the core has a distinctive amino acid composition, which may help in identifying potential protein recognition sites on single proteins of known structures.     

Atomically detailed potentials to recognize native and approximate protein structures

Atomically detailed potentials for recognition of protein folds are presented. The potentials consist of pair interactions between atoms. One or three distance steps are used to describe the range of interactions between a pair. Training is carried out with the mathematical programming approach on the decoy sets of Baker, Levitt, and some of our own design. Recognition is required not only for decoy-native structural pairs but also for pairs of decoy and homologous structures. Performance is tested on the targets of CASP5 using templates from the Protein Data Bank, on two test ab initio decoy sets from Skolnick's laboratory, and on decoy sets from Moult's laboratory. We conclude that the newly derived potentials have significant recognition capacity, comparable to the best models derived from other techniques. The new potentials require a significantly smaller number of parameters. The enhanced recognition capacity extends primarily to the identification of structures generated by ab initio simulation and less to the recognition of approximate shapes created by homology.     

Protein–protein alternative binding modes do not overlap

Proteins often bind other proteins in more than one way. Thus alternative binding modes is an essential feature of protein interactions. Such binding modes may be detected by X‐ray crystallography and thus reflected in Protein Data Bank. The alternative binding is often observed not for the protein itself but for its structural homolog. The results of this study based on the analysis of a comprehensive set of co‐crystallized protein–protein complexes show that the alternative binding modes generally do not overlap, but are spatially separated. This effect is based on molecular recognition characteristics of the protein structures. The results are also in excellent agreement with the intermolecular energy funnel size estimates obtained previously by an independent methodology. The results provide an important insight into the principles of protein association, as well as potential guidelines for modeling of protein complexes and the design of protein interfaces.     

Temperature-induced complementarity as a mechanism for biomolecular assembly

Recent advances in the measurement and theory of “hydration” interactions between biomolecules provide a basis on which to formulate mechanisms of biomolecular recognition. In this paper we have developed a mathematical formalism for analyzing specificity encoded in dynamic distributions of surface polar groups, a formalism that incorporates newly recognized properties of directly measured “hydration” forces. As expected, attraction between surfaces requires complementary patterns of surface polar groups. In contrast to usual expectations, thermal motion can create these complementary surface configurations. We have demonstrated that assembly can occur with an increase in conformational entropy of polar residues. Elevated temperature then facilitates recognition rather than hinders it. This mechanism might underlie some temperature-favored assembly reactions common in biological systems that are usually associated with the “hydrophobic effect” only. © 1994 Wiley-Liss, Inc.     

Structural predictions on the 33 kDa extrinsic protein associated to the oxygen evolving complex of photosynthetic organisms

Modern computational methods for protein structure prediction have been used to study the structure of the 33 kDa extrinsic membrane protein, associated to the oxygen evolving complex of photosynthetic organisms. A multiple alignment of 14 sequences of this protein from cyanobacteria, algae and plants is presented. The alignment allows the identification of fully conserved residues and the recognition of one deletion and one insertion present in the plant sequences but not in cyanobacteria. A tree of similarity, deduced from pair-wise comparison and cluster analysis of the sequences, is also presented. The alignment and the consensus sequence derived are used for prediction the secondary structure of the protein. This prediction indicates that it is a mainly-beta protein (25–38% of -strands) with no more than 4% of -helix. Fold recognition by threading is applied to obtain a topological 2D model of the protein. In this model the secondary structure elements are located, including several highly conserved loops. Some of these conserved loops are suggested to be important for the binding of the 33 kDa protein to Photosystem II and for the stability of the manganese cluster. These structural predictions are in good agreement with experimental data reported by several authors.     

Intramembrane client recognition potentiates the chaperone functions of calnexin

One‐third of the human proteome is comprised of membrane proteins, which are particularly vulnerable to misfolding and often require folding assistance by molecular chaperones. Calnexin (CNX), which engages client proteins via its sugar‐binding lectin domain, is one of the most abundant ER chaperones, and plays an important role in membrane protein biogenesis. Based on mass spectrometric analyses, we here show that calnexin interacts with a large number of nonglycosylated membrane proteins, indicative of additional nonlectin binding modes. We find that calnexin preferentially bind misfolded membrane proteins and that it uses its single transmembrane domain (TMD) for client recognition. Combining experimental and computational approaches, we systematically dissect signatures for intramembrane client recognition by calnexin, and identify sequence motifs within the calnexin TMD region that mediate client binding. Building on this, we show that intramembrane client binding potentiates the chaperone functions of calnexin. Together, these data reveal a widespread role of calnexin client recognition in the lipid bilayer, which synergizes with its established lectin‐based substrate binding. Molecular chaperones thus can combine different interaction modes to support the biogenesis of the diverse eukaryotic membrane proteome.     

基于BERT与Text-CNN的抗菌肽识别方法

抗菌肽(antimicrobial peptides,AMPs)广泛存在于生命体中,是一种具有广谱抗菌活性、免疫调节功能的小分子多肽。抗菌肽不易产生耐药性,适用范围广,具有极大的临床价值,是传统抗生素的有力竞争者。识别抗菌肽是抗菌肽研究领域中的重要研究方向,湿实验法在进行大规模抗菌肽识别时存在成本高、效率低、周期长等难点,计算机辅助识别法是抗菌肽识别手段的重要补充,如何提升准确率是其中的关键问题。蛋白质序列可以被近似地看作是由氨基酸组成的语言,运用自然语言处理(natural language processing,NLP)技术可能提取到丰富的特征。本文将自然语言处理领域中的预训练模型BERT和微调结构Text-CNN结合,对蛋白质语言进行建模,提供了开源可用的抗菌肽识别工具,并与已发表的5种抗菌肽识别工具进行了比较。结果表明,优化“预训练-微调”策略带来了准确率、敏感度、特异性和马修相关系数的整体提升,为进一步研究抗菌肽识别算法提供了新思路。     

Human and viral membrane–associated E3 ubiquitin ligases MARCH1 and MIR2 recognize different features of CD86 to downregulate surface expression

Immune-stimulatory ligands, such as major histocompatibility complex molecules and the T-cell costimulatory ligand CD86, are central to productive immunity. Endogenous mammalian membrane-associated RING-CHs (MARCH) act on these and other targets to regulate antigen presentation and activation of adaptive immunity, whereas virus-encoded homologs target the same molecules to evade immune responses. Substrate specificity is encoded in or near the membrane-embedded domains of MARCHs and the proteins they regulate, but the exact sequences that distinguish substrates from nonsubstrates are poorly understood. Here, we examined the requirements for recognition of the costimulatory ligand CD86 by two different MARCH-family proteins, human MARCH1 and Kaposi''s sarcoma herpesvirus modulator of immune recognition 2 (MIR2), using deep mutational scanning. We identified a highly specific recognition surface in the hydrophobic core of the CD86 transmembrane (TM) domain (TMD) that is required for recognition by MARCH1 and prominently features a proline at position 254. In contrast, MIR2 requires no specific sequences in the CD86 TMD but relies primarily on an aspartic acid at position 244 in the CD86 extracellular juxtamembrane region. Surprisingly, MIR2 recognized CD86 with a TMD composed entirely of valine, whereas many different single amino acid substitutions in the context of the native TM sequence conferred MIR2 resistance. These results show that the human and viral proteins evolved completely different recognition modes for the same substrate. That some TM sequences are incompatible with MIR2 activity, even when no specific recognition motif is required, suggests a more complicated mechanism of immune modulation via CD86 than was previously appreciated.     

Actin interacts with CCT via discrete binding sites: a binding transition-release model for CCT-mediated actin folding

The chaperones prefoldin and the cytosolic chaperonin CCT-containing TCP-1 (CCT) guide the cytoskeletal protein actin to its native conformation. Performing an alanine scan of actin, we identified discrete recognition determinants for CCT interaction. Interestingly, one of these is similar and functional in the non-homologous protein Cdc20, suggesting that some of the binding information in the CCT target proteins is shared. The information in actin for recognition by CCT and for folding is different, as all but one of the mutants in the recognition determinants are folding-competent. In addition, some other actin mutants remain CCT-arrested and are not released in a native conformation, whereas others do fold but remain bound to CAP. Kinetic experiments provide evidence that CCT-mediated folding of non-native actin occurs in at least two steps, in which initially the recognition determinant 245-249 contacts CCT and the other determinants interact at later stages. Actin mutants that are CCT-arrested demonstrate that some regions neighbouring the recognition determinants are involved in modulating the correct folding transitions of actin on CCT, or its release from this chaperonin. Further, we found that the ATP binding of actin is not a prerequisite for its release, and we suggest that CAP may be involved in charging the nucleotide. Based on the kinetics of CCT binding and folding of actin and actin mutants, we propose a multi-step recognition-transition-release model. This also implies that the currently accepted notion of CCT-mediated actin folding is probably more complex.     

Structural basis of HP1/PXVXL motif peptide interactions and HP1 localisation to heterochromatin

HP1 family proteins are adaptor molecules, containing two related chromo domains that are required for chromatin packaging and gene silencing. Here we present the structure of the chromo shadow domain from mouse HP1beta bound to a peptide containing a consensus PXVXL motif found in many HP1 binding partners. The shadow domain exhibits a novel mode of peptide recognition, where the peptide binds across the dimer interface, sandwiched in a beta-sheet between strands from each monomer. The structure allows us to predict which other shadow domains bind similar PXVXL motif-containing peptides and provides a framework for predicting the sequence specificity of the others. We show that targeting of HP1beta to heterochromatin requires shadow domain interactions with PXVXL-containing proteins in addition to chromo domain recognition of Lys-9-methylated histone H3. Interestingly, it also appears to require the simultaneous recognition of two Lys-9-methylated histone H3 molecules. This finding implies a further complexity to the histone code for regulation of chromatin structure and suggests how binding of HP1 family proteins may lead to its condensation.     

Molecular recognition by a binary code

Functional antibodies were obtained from a library of antigen-binding sites generated by a binary code restricted to tyrosine and serine. An antibody raised against human vascular endothelial growth factor recognized the antigen with high affinity (K(D)=60 nM) and high specificity in cell-based assays. The crystal structure of another antigen binding fragment in complex with its antigen (human death receptor DR5) revealed the structural basis for this minimalist mode of molecular recognition. Natural antigen-binding sites are enriched for tyrosine and serine, and we show that these amino acid residues are intrinsically well suited for molecular recognition. Furthermore, these results demonstrate that molecular recognition can evolve from even the simplest chemical diversity.     

Distinguishing native conformations of proteins from decoys with an effective free energy estimator based on the OPLS all-atom force field and the Surface Generalized Born solvent model

Protein decoy data sets provide a benchmark for testing scoring functions designed for fold recognition and protein homology modeling problems. It is commonly believed that statistical potentials based on reduced atomic models are better able to discriminate native-like from misfolded decoys than scoring functions based on more detailed molecular mechanics models. Recent benchmark tests on small data sets, however, suggest otherwise. In this work, we report the results of extensive decoy detection tests using an effective free energy function based on the OPLS all-atom (OPLS-AA) force field and the Surface Generalized Born (SGB) model for the solvent electrostatic effects. The OPLS-AA/SGB effective free energy is used as a scoring function to detect native protein folds among a total of 48,832 decoys for 32 different proteins from Park and Levitt's 4-state-reduced, Levitt's local-minima, Baker's ROSETTA all-atom, and Skolnick's decoy sets. Solvent electrostatic effects are included through the Surface Generalized Born (SGB) model. All structures are locally minimized without restraints. From an analysis of the individual energy components of the OPLS-AA/SGB energy function for the native and the best-ranked decoy, it is determined that a balance of the terms of the potential is responsible for the minimized energies that most successfully distinguish the native from the misfolded conformations. Different combinations of individual energy terms provide less discrimination than the total energy. The results are consistent with observations that all-atom molecular potentials coupled with intermediate level solvent dielectric models are competitive with knowledge-based potentials for decoy detection and protein modeling problems such as fold recognition and homology modeling.     

Chirality-independent protein-protein recognition between transmembrane domains in vivo

Stereospecificity in protein-protein recognition and docking is an unchallenged dogma. Soluble proteins provide the main source of evidence for stereospecificity. In contrast, within the membrane little is known about the role of stereospecificity in the recognition process. Here, we have reassessed the stereospecificity of protein-protein recognition by testing whether it holds true for the well-defined glycophorin A (GPA) transmembrane domain in vivo. We found that the all-D amino acid GPA transmembrane domain and two all-D mutants specifically associated with an all-L GPA transmembrane domain, within the membrane milieu of Escherichia coli. Molecular dynamics techniques reveal a possible structural explanation to the observed interaction between all-D and all-L transmembrane domains. A very strong correlation was found between amino acid residues at the interface of both the all-L homodimer structure and the mixed L/D heterodimer structure, suggesting that the original interactions are conserved. The results suggest that GPA helix-helix recognition within the membrane is chirality-independent.     

Josef Rudinger Memorial Lecture: Use of peptides to modulate protein‐protein interactions

Peptides are destined to play a major role as therapeutic agents. My laboratory is contributing to speeding up this process. On the one hand, we devote efforts to studying the molecular details and dynamics of the events that occur during molecular recognition at protein surfaces. We succeeded to design and synthesize peptides able to modulate these recognition events either permanently or in response to light. On the other hand, we are discovering and designing peptides able to cross biological barriers. Our aim is to use these peptides as shuttles for targeting therapeutic agents to organs, tissues, or cells, with a special emphasis on drug delivery to the brain. Copyright © 2015 European Peptide Society and John Wiley & Sons, Ltd.     

昆虫肽聚糖识别蛋白研究进展

在脊椎动物和非脊椎动物中,识别非己是天生免疫反应中的第一步。肽聚糖是细菌细胞壁的必需成分,属于进化上保守的微生物表面病原相关分子模式(pathogen-associated molecular pattern, PAMP),可以被模式识别蛋白(pattern recognition proteins, PRRs)如肽聚糖识别蛋白(peptidoglycan recognition proteins, PGRPs)识别。 在昆虫的天生免疫系统中,有些PGRPs能够利用细菌独有的肽聚糖识别入侵细菌,并将细菌入侵信号传递给下游的抗菌肽(antimicrobial peptide, AMP)合成途径,启动抗菌肽基因的转录及合成;PGRPs对肽聚糖的识别也会启动酚氧化酶原途径的激活,引起黑化反应。有些具有酰胺酶活性的PGRPs可以促进吞噬作用;有些可以抑制抗菌肽合成以减弱过度免疫反应带来的损伤。还有一些PGRPs作为效应因子直接作用于细菌将细菌杀死。本文主要从昆虫PGRPs作为识别受体(recognition receptor)、调节子(regulator)和效应因子(effector) 3个方面进行了综述,并分析了目前PGRPs研究中仍不清楚的问题和未来研究的方向。     

Distinct domains of small Tims involved in subunit interaction and substrate recognition

Tim9 and Tim10 belong to the small Tim family of mitochondrial ATP-independent chaperones. They are organised in a specific hetero-oligomeric complex (TIM10) that escorts polytopic proteins into the mitochondrial inner membrane. The contributions of the individual subunits to the assembly and function of the TIM10 complex remain poorly understood. Here, we show that substrate recognition and assembly of the complex are mediated by distinct domains of the subunits. These are unrelated to the characteristic "twin CX3C" motif that is present in all small Tims and ensures proper folding of the unassembled subunits. Specifically, we show that substrate recognition is achieved by the Tim10 subunit, whilst Tim9 serves a more structural role. The N-terminal domain of Tim10 is a substrate sensor whilst its C-terminal part is essential for complex formation. By contrast, both N and C-terminal domains of Tim9 are involved in the stability of the complex.     

Modeling protein recognition of carbohydrates

We have a limited understanding of the details of molecular recognition of carbohydrates by proteins, which is critical to a multitude of biological processes. Furthermore, carbohydrate-modifying proteins such as glycosyl hydrolases and phosphorylases are of growing importance as potential drug targets. Interactions between proteins and carbohydrates have complex thermodynamics, and in general the specific positioning of only a few hydroxyl groups determines their binding affinities. A thorough understanding of both carbohydrate and protein structures is thus essential to predict these interactions. An atomic-level view of carbohydrate recognition through structures of carbohydrate-active enzymes complexed with transition-state inhibitors reveals some of the distinctive molecular features unique to protein-carbohydrate complexes. However, the inherent flexibility of carbohydrates and their often water-mediated hydrogen bonding to proteins makes simulation of their complexes difficult. Nonetheless, recent developments such as the parameterization of specific force fields and docking scoring functions have greatly improved our ability to predict protein-carbohydrate interactions. We review protein-carbohydrate complexes having defined molecular requirements for specific carbohydrate recognition by proteins, providing an overview of the different computational techniques available to model them.