The atomic structure of protein-protein recognition sites

Aromatic clusters in protein-protein and protein-drug complexes

Aromatic rings are important residues for biological interactions and appear to a large extent as part of protein-drug and protein-protein interactions. They are relevant for both protein stability and molecular recognition processes due to their natural occurrence in aromatic aminoacids (Trp, Phe, Tyr and His) as well as in designed drugs since they are believed to contribute to optimizing both affinity and specificity of drug-like molecules. Despite the mentioned relevance, the impact of aromatic clusters on protein-protein and protein-drug complexes is still poorly characterized, especially in those that go beyond a dimer. In this work, we studied protein-drug and protein-protein complexes and systematically analyzed the presence and structure of their aromatic clusters. Our results show that aromatic clusters are highly prevalent in both protein-protein and protein-drug complexes, and suggest that protein-protein aromatic clusters have idealized interactions, probably because they were optimized by evolution, as compared to protein-drug clusters that were manually designed. Interestingly, the configuration, solvent accessibility and secondary structure of aromatic residues in protein-drug complexes shed light on the relation between these properties and compound affinity, allowing researchers to better design new molecules.

The Power of Assemblies at Interfaces: Nanosensor Platforms Based on Synthetic Receptor Membranes

Synthetic sensing materials (artificial receptors) are some of the most attractive components of chemical/biosensors because of their long-term stability and low cost of production. However, the strategy for the practical design of these materials toward specific molecular recognition in water is not established yet. For the construction of artificial material-based chemical/biosensors, the bottom-up assembly of these materials is one of the effective methods. This is because the driving forces of molecular recognition on the receptors could be enhanced by the integration of such kinds of materials at the 'interfaces', such as the boundary portion between the liquid and solid phases. Additionally, the molecular assembly of such self-assembled monolayers (SAMs) can easily be installed in transducer devices. Thus, we believe that nanosensor platforms that consist of synthetic receptor membranes on the transducer surfaces can be applied to powerful tools for high-throughput analyses of the required targets. In this review, we briefly summarize a comprehensive overview that includes the preparation techniques for molecular assemblies, the characterization methods of the interfaces, and a few examples of receptor assembly-based chemical/biosensing platforms on each transduction mechanism.

PCR Detection of Oxacillinases in Bacteria

Oxacillinases (OXA) have been mostly described in Enterobacteriaceae, Acinetobacter, and Pseudomonas species. Recent years have witnessed an increased prevalence of intrinsic and/or acquired β-lactamase-producing Acinetobacter in food-producing animals. This study was conducted to assess the prevalence of OXA among selected bacterial species and to characterize these enzymes by in silico analysis. Screening of OXA was performed by PCR amplification using specific pairs of oligonucleotides. Overall, 40 pairs of primers were designed, of which 6 were experimentally tested in vitro. Among 49 bacterial isolates examined, the presence of bla_OXA-1-like genes was confirmed in 20 cases (41%; 19 times in Klebsiella pneumoniae and once in Enterobacter cloacae). No OXA were found in animal isolates. The study results confirmed the specificity of the designed oligonucleotide pairs. Furthermore, the designed primers were found to possess the ability to specifically detect 90.2% of all OXA. These facts suggest that the in silico and in vitro tested primers could be used for single or multiplex PCR to screen for the presence of OXA in various bacteria, as well as to monitor their spread. At the same time, the presence of conserved characteristic amino acids and motifs was confirmed by in silico analysis of sequences of representative members of OXA.

Broadly Protective Multivalent OspA Vaccine against Lyme Borreliosis, Developed Based on Surface Shaping of the C-Terminal Fragment

The development of vaccines for prevention of diseases caused by pathogenic species can encounter major obstacles if high sequence diversity is observed between individual strains. Therefore, development might be restricted either to conserved antigens, which are often rare, or to multivalent vaccines, which renders the production more costly and cumbersome. In light of this complexity, we applied a structure-based surface shaping approach for the development of a Lyme borreliosis (LB) vaccine suitable for the United States and Europe. The surface of the C-terminal fragment of outer surface protein A (OspA) was divided into distinct regions, based primarily on binding sites of monoclonal antibodies (MAbs). In order to target the six clinically most relevant OspA serotypes (ST) in a single protein, exposed amino acids of the individual regions were exchanged to corresponding amino acids of a chosen OspA serotype. Six chimeric proteins were constructed, and, based on their immunogenicity, four of these chimeras were tested in mouse challenge models. Significant protection could be demonstrated for all four proteins following challenge with infected ticks (OspA ST1, OspA ST2, and OspA ST4) or with in vitro-grown spirochetes (OspA ST1 and OspA ST5). Two of the chimeric proteins were linked to form a fusion protein, which provided significant protection against in vitro-grown spirochetes (OspA ST1) and infected ticks (OspA ST2). This article presents the proof-of-concept study for a multivalent OspA vaccine targeting a wide range of pathogenic LB Borrelia species with a single recombinant antigen for prevention of Lyme borreliosis.

On the evolution of protein-adenine binding

Proteins' interactions with ancient ligands may reveal how molecular recognition emerged and evolved. We explore how proteins recognize adenine: a planar rigid fragment found in the most common and ancient ligands. We have developed a computational pipeline that extracts protein-adenine complexes from the Protein Data Bank, structurally superimposes their adenine fragments, and detects the hydrogen bonds mediating the interaction. Our analysis extends the known motifs of protein-adenine interactions in the Watson-Crick edge of adenine and shows that all of adenine's edges may contribute to molecular recognition. We further show that, on the proteins' side, binding is often mediated by specific amino acid segments ("themes") that recur across different proteins, such that different proteins use the same themes when binding the same adenine-containing ligands. We identify numerous proteins that feature these themes and are thus likely to bind adenine-containing ligands. Our analysis suggests that adenine binding has emerged multiple times in evolution.

Melting of Hemoglobin in Native Solutions as measured by IMS-MS

Thermally induced structural transitions of the quaternary structure of the hemoglobin tetramer (human) in aqueous solution (150 mM ammonium acetate) were investigated using a variable temperature electrospray ionization (vt-ESI) technique in combination with ion mobility spectrometry (IMS) and mass spectrometry (MS) measurements. At low solution temperatures (28 to ∼40 °C), a heterotetrameric (α2β2) complex is the most abundant species that is observed. When the solution temperature is increased, this assembly dissociates into heterodimers (holo αβ forms) before ultimately forming insoluble aggregates at higher temperatures (>60 °C). In addition to the holo αβ forms, a small population of αβ dimers containing only a single heme ligand and having a dioxidation modification mapping to the β subunit are observed. The oxidized heterodimers are less stable than the unmodified holo-heterodimer. The Cys93 residue of the β subunit is the primary site of dioxidation. The close proximity of this post translational modification to both the αβ subunit interface and the heme binding site suggests that this modification is coupled to the loss of the heme and decreased protein stability. Changes in the charge state and collision cross sections of these species indicate that the tetramers and dimers favor less compact structures at elevated temperatures (prior to temperatures where dissociation dominates).

Interaction Energetics and Druggability of the Protein-Protein Interaction between Kelch-like ECH-Associated Protein 1 (KEAP1) and Nuclear Factor Erythroid 2 Like 2 (Nrf2)

Development of small molecule inhibitors of protein-protein interactions (PPIs) is hampered by our poor understanding of the druggability of PPI target sites. Here, we describe the combined application of alanine-scanning mutagenesis, fragment screening, and FTMap computational hot spot mapping to evaluate the energetics and druggability of the highly charged PPI interface between Kelch-like ECH-associated protein 1 (KEAP1) and nuclear factor erythroid 2 like 2 (Nrf2), an important drug target. FTMap identifies four binding energy hot spots at the active site. Only two of these are exploited by Nrf2, which alanine scanning of both proteins shows to bind primarily through E79 and E82 interacting with KEAP1 residues S363, R380, R415, R483, and S508. We identify fragment hits and obtain X-ray complex structures for three fragments via crystal soaking using a new crystal form of KEAP1. Combining these results provides a comprehensive and quantitative picture of the origins of binding energy at the interface. Our findings additionally reveal non-native interactions that might be exploited in the design of uncharged synthetic ligands to occupy the same site on KEAP1 that has evolved to bind the highly charged DEETGE binding loop of Nrf2. These include π-stacking with KEAP1 Y525 and interactions at an FTMap-identified hot spot deep in the binding site. Finally, we discuss how the complementary information provided by alanine-scanning mutagenesis, fragment screening, and computational hot spot mapping can be integrated to more comprehensively evaluate PPI druggability.

Protein-protein interactions: a structural view of inhibition strategies and the IL-23/IL-17 axis

Protein-protein interactions are central to biology and provide opportunities to modulate disease with small-molecule or protein therapeutics. Recent developments in the understanding of the tractability of protein-protein interactions are discussed with a focus on the ligandable nature of protein-protein interaction surfaces. General principles of inhibiting protein-protein interactions are illustrated with structural biology examples from six members of the IL-23/IL-17 signaling family (IL-1, IL-6, IL-17, IL-23 RORγT and TNFα). These examples illustrate the different approaches to discover protein-protein interaction inhibitors on a target-specific basis that has proven fruitful in terms of discovering both small molecule and biologic based protein-protein interaction inhibitors.

Immunological role and underlying mechanisms of B7-H6 in tumorigenesis

B7 homolog 6 (B7-H6) has been identified as involved in tumorigenesis. Elucidating its role and potential mechanism of action is essential for understanding tumorigenesis and the potential development of an effective clinical strategy. Abnormal overexpression of B7-H6 in various types of tumors was reported to be linked with poor prognosis. B7-H6 suppresses the initiation of the "caspase cascade" and induces anti-apoptosis by STAT3 pathway activation to provoke tumorigenesis. B7-H6 facilitates tumor proliferation and cell cycle progression by regulating apoptosis suppressors. B7-H6 induces cellular cytotoxicity, secretion of TNF-α and IFN-γ and B7-H6-specific BiTE triggers T cells to accelerate tumorigenesis. B7-H6 induces abnormal immunological progression by HER2-scFv mediated ADCC and NKp30 immune escape to promote tumorigenesis. B7-H6 promotes tumorigenesis via apoptosis inhibition, proliferation and immunological progression. B7-H6 may a valuable potential biomarker and therapeutic strategy for diagnostics, prognostics and treatment in cancer.

Design of a basigin-mimicking inhibitor targeting the malaria invasion protein RH5

Many human pathogens use host cell-surface receptors to attach and invade cells. Often, the host-pathogen interaction affinity is low, presenting opportunities to block invasion using a soluble, high-affinity mimic of the host protein. The Plasmodium falciparum reticulocyte-binding protein homolog 5 (RH5) provides an exciting candidate for mimicry: it is highly conserved and its moderate affinity binding to the human receptor basigin (KD  ≥1 μM) is an essential step in erythrocyte invasion by this malaria parasite. We used deep mutational scanning of a soluble fragment of human basigin to systematically characterize point mutations that enhance basigin affinity for RH5 and then used Rosetta to design a variant within the sequence space of affinity-enhancing mutations. The resulting seven-mutation design exhibited 1900-fold higher affinity (KD approximately 1 nM) for RH5 with a very slow binding off rate (0.23 h-1 ) and reduced the effective Plasmodium growth-inhibitory concentration by at least 10-fold compared to human basigin. The design provides a favorable starting point for engineering on-rate improvements that are likely to be essential to reach therapeutically effective growth inhibition.

Self-assembly of azaphthalocyanine–oligodeoxynucleotide conjugates into J-dimers: towards biomolecular logic gates

Unique spatial self-assembly of azaphthalocyanine–oligonucleotide–fluorescein conjugates can be selectively dissociated by a complementary sequence or coordinating solvent and used for the development of biomolecular logic gates.

Protein A superantigen: structure, engineering and molecular basis of antibody recognition

Staphylococcus aureus interacts with the human immune system through the production of secreted factors. Key among these is protein A, a B-cell superantigen capable of interacting with both antibody Fc and VH regions. Here, we review structural and molecular features of this important example of naturally occurring bacterial superantigens, as well as engineered variants and their application in biotechnology.

Antibody Structure and Function: The Basis for Engineering Therapeutics

Antibodies and antibody-derived macromolecules have established themselves as the mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure–function relationships of antibodies provides a platform for protein engineering that has been exploited to generate a wide range of biologics for a host of therapeutic indications. In this review, our basic understanding of the antibody structure is described along with how that knowledge has leveraged the engineering of antibody and antibody-related therapeutics having the appropriate antigen affinity, effector function, and biophysical properties. The platforms examined include the development of antibodies, antibody fragments, bispecific antibody, and antibody fusion products, whose efficacy and manufacturability can be improved via humanization, affinity modulation, and stability enhancement. We also review the design and selection of binding arms, and avidity modulation. Different strategies of preparing bispecific and multispecific molecules for an array of therapeutic applications are included.

Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment

We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

Physicochemical determinants of antibody-protein interactions

Antibodies are specialized proteins generated by immune system for high specificity and affinity binding to target antigens. Because of their essential roles in immune system, antibodies have been successfully developed and engineered as biopharmaceuticals for treatment of various diseases. Analysis of antibody-protein interactions is always required to get detailed information on effectivity of such antibody-based therapeutics. Although physicochemical rules cannot be generalized for every antibody-protein interaction, there are some features which should be taken into account during antibody development and engineering efforts. In this chapter, physicochemical analysis of antibody paratope-protein epitope interactions will be discussed to highlight important characteristics. First, paratope and non-paratope regions of antibodies will be described and important roles of these regions on binding and biophysical features of antibodies will be discussed. Then, general features of epitope regions of protein antigens will be introduced along with several computational/experimental tools to identify them. Lastly, a rising star of antibody biopharmaceuticals, nanobodies, will be described to show importance of next-generation antibody fragment based biopharmaceuticals in drug development.

Modeling Antibody-Antigen Complexes by Information-Driven Docking

Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.

Site-selective 1H/2H labeling enables artifact-free 1H CPMG relaxation dispersion experiments in aromatic side chains

Aromatic side chains are often key residues in enzyme active sites and protein binding sites, making them attractive probes of protein dynamics on the millisecond timescale. Such dynamic processes can be studied by aromatic ¹³C or ¹H CPMG relaxation dispersion experiments. Aromatic ¹H CPMG relaxation dispersion experiments in phenylalanine, tyrosine and the six-ring moiety of tryptophan, however, are affected by ³J ¹H-¹H couplings which are causing anomalous relaxation dispersion profiles. Here we show that this problem can be addressed by site-selective ¹H/²H labeling of the aromatic side chains and that artifact-free relaxation dispersion profiles can be acquired. The method has been further validated by measuring folding-unfolding kinetics of the small protein GB1. The determined rate constants and populations agree well with previous results from ¹³C CPMG relaxation dispersion experiments. Furthermore, the CPMG-derived chemical shift differences between the folded and unfolded states are in excellent agreement with those obtained directly from the spectra. In summary, site-selective ¹H/²H labeling enables artifact-free aromatic ¹H CPMG relaxation dispersion experiments in phenylalanine and the six-ring moiety of tryptophan, thereby extending the available methods for studying millisecond dynamics in aromatic protein side chains.

Crystal Structure-Based Exploration of Arginine-Containing Peptide Binding in the ADP-Ribosyltransferase Domain of the Type III Effector XopAI Protein

Plant pathogens secrete proteins called effectors into the cells of their host to modulate the host immune response against colonization. Effectors can either modify or arrest host target proteins to sabotage the signaling pathway, and therefore are considered potential drug targets for crop disease control. In earlier research, the Xanthomonas type III effector XopAI was predicted to be a member of the arginine-specific mono-ADP-ribosyltransferase family. However, the crystal structure of XopAI revealed an altered active site that is unsuitable to bind the cofactor NAD+, but with the capability to capture an arginine-containing peptide from XopAI itself. The arginine peptide consists of residues 60 through 69 of XopAI, and residue 62 (R62) is key to determining the protein–peptide interaction. The crystal structure and the molecular dynamics simulation results indicate that specific arginine recognition is mediated by hydrogen bonds provided by the backbone oxygen atoms from residues W154, T155, and T156, and a salt bridge provided by the E265 sidechain. In addition, a protruding loop of XopAI adopts dynamic conformations in response to arginine peptide binding and is probably involved in target protein recognition. These data suggest that XopAI binds to its target protein by the peptide-binding ability, and therefore, it promotes disease progression. Our findings reveal an unexpected and intriguing function of XopAI and pave the way for further investigation on the role of XopAI in pathogen invasion.

Computational Analysis of Non-covalent Interactions in Phycocyanin Subunit Interfaces

Protein-protein interactions are an important phenomenon in biological processes and functions. We used the manually curated non-redundant dataset of 118 phycocyanin interfaces to gain additional insight into this phenomenon using a robust inter-atomic non-covalent interaction analyzing tool PPCheck. Our observations indicate that there is a relatively high composition of hydrophobic residues at the interfaces. Most of the interface residues are clustered at the middle of the range which we call "standard-size" interfaces. Furthermore, the multiple interaction patterns founded in the present study indicate that more than half of the residues involved in these interactions participate in multiple and water-bridged hydrogen bonds. Thus, hydrogen bonds contribute maximally towards the stability of protein-protein complexes. The analysis shows that hydrogen bond energies contribute to about 88 % to the total energy and it also increases with interface size. Van der Waals (vdW) energy contributes to 9.3 %±1.7 % on average in these complexes. Moreover, there is about 1.9 %±1.5 % contribution by electrostatic energy. Nevertheless, the role by vdW and electrostatic energy could not be ignored in interface binding. Results show that the total binding energy is more for large phycocyanin interfaces. The normalized energy per residue was less than -16 kJ mol^-1 , while most of them have energy in the range from -6 to -14 kJ mol^-1 . The non-covalent interacting residues in these proteins were found to be highly conserved. Obtained results might contribute to the understanding of structural stability of this class of evolutionary essential proteins with increased practical application and future designs of novel protein-bioactive compound interactions.

Small protein-protein interfaces rich in electrostatic are often linked to regulatory function

Protein-protein interaction (PPI) is critical for several biological functions in living cells through the formation of an interface. Therefore, it is of interest to characterize protein-protein interfaces using an updated non-redundant structural dataset of 2557 homo (identical subunits) and 393 hetero (different subunits) dimer protein complexes determined by X-ray crystallography. We analyzed the interfaces using van der Waals (vdW), hydrogen bonding and electrostatic energies. Results show that on average homo and hetero interfaces are similar. Hence, we further grouped the 2950 interfaces based on percentage vdW to total energies into dominant (≥60%) and sub-dominant (<60%) vdW interfaces. Majority (92%) of interfaces have dominant vdW energy with large interface size (146 ± 87 (homo) and 137 ± 76 (hetero) residues) and interface area (1622 ± 1135 Ų (homo) and 1579 ± 1060 Ų (hetero)). However, a proportion (8%) of interfaces have sub-dominant vdW energy with small interface size (85 ± 46 (homo) and 88 ± 36 (hetero) residues) and interface area (823 ± 538 Ų (homo) and 881 ± 377 Ų (hetero)). It is found that large interfaces have two-fold more interface area and interface size than small interfaces with increasing hydrogen bonding energy to interface size. However, small interfaces have three-fold more electrostatics energy than large interfaces with increasing electrostatics to interface size. Thus, 8% of complexes having small interfaces with limited interface area and sub-dominant vdW energy are rich in electrostatics. It is interesting to observe that complexes having small interfaces are often associated with regulatory function. Hence, the observed structural features with known molecular function provide insights for the better understanding of PPI.Communicated by Ramaswamy H. Sarma.

Effects of Arginine Deimination and Citrulline Side-Chain Length on Peptide Secondary Structure Formation

Post-translational modifications expand the chemical functionality of peptides and proteins beyond that originating from the encoded amino acids, but studies on the structural effects of these modifications have been limited. Arginine undergoes deimination to give citrulline (Cit), converting the positively charged guanidinium moiety into a neutral urea group. Herein, we report the effect of Arg deimination on secondary structure formation. To understand the reason for the number of methylene units in Cit, the effect of Cit side-chain length on secondary structure formation was also studied. Ala-based peptides and β-hairpin peptides were used to study α-helix and β-sheet formation, respectively. Peptides containing Cit analogues were prepared by an orthogonal protecting group strategy coupled with solid-phase carbamylation. The CD data for the Ala-based peptides were analyzed by using modified Lifson-Roig theory, showing that the helix propensity of Arg decreased upon deimination and that either shortening or lengthening Cit also decreased the helix propensity. The β-hairpin peptides were analyzed by NMR methods, showing minimal change in strand formation energetics upon Arg deimination. Altering the Cit side-chain length did not affect strand formation energetics either. These results should be useful for the preparation of urea-bearing systems and the design of peptides incorporating urea-bearing residues with varying side-chain length.

Binding of ferredoxin NADP+ oxidoreductase (FNR) to plant photosystem I

The binding of FNR to PSI has been postulated long ago, however, a clear evidence is still missing. In this work, using isothermal titration calorimetry (ITC), we found that FNR binds to photosystem I with its light harvesting complex I (PSI-LHCI) from C. reinhardtii with a 1:1 stoichiometry, a Kd of ~0.8 μM and ∆H of -20.7 kcal/mol. Titrations at different temperatures were used to determine the heat capacity change, ∆CP, of the binding, through which the size of the interface area between the proteins was assessed as ~3000 Ų. In a different set of ITC experiments, introduction of various sucrose concentrations was used to estimate that ~95 water molecules are released to the solvent. These observations support the notion of a binding site shared by few of the photosystem I - light harvesting complex I (PSI-LHCI) subunits in addition to PsaE. Based on these results, a hypothetical model was built for the binding site of FNR at PSI, using known crystallographic structures of: cyanobacterial PSI in complex with ferredoxin (Fd), plant PSI-LHCI and Fd:FNR complex from cyanobacteria. FNR binding site location is proposed to be at the foot of the stromal ridge and above the inner LHCI belt. It is expected to form contacts with PsaE, PsaB, PsaF and at least one of the LHCI. In addition, a ~4.5-fold increased affinity between FNR and PSI-LHCI under crowded 1 M sucrose environment led us to conclude that in C. reinhardtii FNR also functions as a subunit of PSI-LHCI.

Binding symmetry and surface flexibility mediate antibody self-association

Solution stability is an important factor in the optimization of engineered biotherapeutic candidates such as monoclonal antibodies because of its possible effects on manufacturability, pharmacology, efficacy and safety. A detailed atomic understanding of the mechanisms governing self-association of natively folded protein monomers is required to devise predictive tools to guide screening and re-engineering along the drug development pipeline. We investigated pairs of affinity-matured full-size antibodies and observed drastically different propensities to aggregate from variants differing by a single amino-acid. Biophysical testing showed that antigen-binding fragments (Fabs) from the aggregating antibodies also reversibly associated with equilibrium dissociation constants in the low-micromolar range. Crystal structures (PDB accession codes 6MXR, 6MXS, 6MY4, 6MY5) and bottom-up hydrogen-exchange mass spectrometry revealed that Fab self-association occurs in a symmetric mode that involves the antigen complementarity-determining regions. Subtle local conformational changes incurred upon point mutation of monomeric variants foster formation of complementary polar interactions and hydrophobic contacts to generate a dimeric Fab interface. Testing of popular in silico tools generally indicated low reliabilities for predicting the aggregation propensities observed. A structure-aggregation data set is provided here in order to stimulate further improvements of in silico tools for prediction of native aggregation. Incorporation of intermolecular docking, conformational flexibility, and short-range packing interactions may all be necessary features of the ideal algorithm.

PEPOP 2.0: new approaches to mimic non-continuous epitopes

BACKGROUND

Bioinformatics methods are helpful to identify new molecules for diagnostic or therapeutic applications. For example, the use of peptides capable of mimicking binding sites has several benefits in replacing a protein which is difficult to produce, or toxic. Using peptides is less expensive. Peptides are easier to manipulate, and can be used as drugs. Continuous epitopes predicted by bioinformatics tools are commonly used and these sequential epitopes are used as is in further experiments. Numerous discontinuous epitope predictors have been developed but only two bioinformatics tools have been proposed so far to predict peptide sequences: Superficial and PEPOP 2.0. PEPOP 2.0 can generate series of peptide sequences that can replace continuous or discontinuous epitopes in their interaction with their cognate antibody.

RESULTS

We have developed an improved version of PEPOP (PEPOP 2.0) dedicated to answer to experimentalists' need for a tool able to handle proteins and to turn them into peptides. The PEPOP 2.0 web site has been reorganized by peptide prediction category and is therefore better formulated to experimental designs. Since the first version of PEPOP, 32 new methods of peptide design were developed. In total, PEPOP 2.0 proposes 35 methods in which 34 deal specifically with discontinuous epitopes, the most represented epitope type in nature.

CONCLUSION

Through the presentation of its user-friendly, well-structured new web site conceived in close proximity to experimentalists, we report original methods that show how PEPOP 2.0 can assist biologists in dealing with discontinuous epitopes.

Applications of in Silico Methods for Design and Development of Drugs Targeting Protein-Protein Interactions

BACKGROUND

Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.

OBJECTIVE

Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, when deregulated. Multiplicity and great amount of PPIs structures offer a huge number of new and potential targets for the treatment of different diseases.

METHODS

Computational techniques are becoming predominant in PPIs studies for their effectiveness, flexibility, accuracy and cost. As a matter of fact, there are effective in silico approaches which are able to identify PPIs and PPI site. Such methods for computational target prediction have been developed through molecular descriptors and data-mining procedures.

RESULTS

In this review, we present different types of interactions between protein-protein and the application of in silico methods for design and development of drugs targeting PPIs. We described computational approaches for the identification of possible targets on protein surface and to detect of stimulator/ inhibitor molecules.

CONCLUSION

A deeper study of the most recent bioinformatics methodologies for PPIs studies is vital for a better understanding of protein complexes and for discover new potential PPI modulators in therapeutic intervention.

Dissecting macromolecular recognition sites in ribosome: implication to its self-assembly

Interactions between macromolecules play a crucial role in ribosome assembly that follows a highly coordinated process involving RNA folding and binding of ribosomal proteins (r-proteins). Although extensive studies have been carried out to understand macromolecular interactions in ribosomes, most of them are confined to either large or small ribosomal-subunit of few species. A comparative analysis of macromolecular interactions across different domains is still missing. We have analyzed the structural and physicochemical properties of protein-protein (PP), protein-RNA (PR) and RNA-RNA (RR) interfaces in small and large subunits of ribosomes, as well as in between the two subunits. Additionally, we have also developed Random Forest (RF) classifier to catalog the r-proteins. We find significant differences as well as similarities in macromolecular recognition sites between ribosomal assemblies of prokaryotes and eukaryotes. PR interfaces are substantially larger and have more ionic interactions than PP and RR interfaces in both prokaryotes and eukaryotes. PP, PR and RR interfaces in eukaryotes are well packed compared to those in prokaryotes. However, the packing density between the large and the small subunit interfaces in the entire assembly is strikingly low in both prokaryotes and eukaryotes, indicating the periodic association and dissociation of the two subunits during the translation. The structural and physicochemical properties of PR interfaces are used to predict the r-proteins in the assembly pathway into early, intermediate and late binders using RF classifier with an accuracy of 80%. The results provide new insights into the classification of r-proteins in the assembly pathway.

Predicting Protein-Protein Interfaces that Bind Intrinsically Disordered Protein Regions

A long-standing goal in biology is the complete annotation of function and structure on all protein-protein interactions, a large fraction of which is mediated by intrinsically disordered protein regions (IDRs). However, knowledge derived from experimental structures of such protein complexes is disproportionately small due, in part, to challenges in studying interactions of IDRs. Here, we introduce IDRBind, a computational method that by combining gradient boosted trees and conditional random field models predicts binding sites of IDRs with performance approaching state-of-the-art globular interface predictions, making it suitable for proteome-wide applications. Although designed and trained with a focus on molecular recognition features, which are long interaction-mediating-elements in IDRs, IDRBind also predicts the binding sites of short peptides more accurately than existing specialized predictors. Consistent with IDRBind's specificity, a comparison of protein interface categories uncovered uniform trends in multiple physicochemical properties, positioning molecular recognition feature interfaces between peptide and globular interfaces.

Enhancement of RNA/Ligand Association Kinetics via an Electrostatic Anchor

The diverse biological processes mediated by RNA rest upon its recognition of various ligands, including small molecules and nucleic acids. Nevertheless, a recent literature survey suggests that RNA molecular recognition of these ligands is slow, with association rate constants orders of magnitude below the diffusional limit. Thus, we were prompted to consider strategies for increasing RNA association kinetics. Proteins can accelerate ligand association via electrostatic forces, and here, using the Tetrahymena group I ribozyme, we provide evidence that electrostatic forces can accelerate RNA/ligand association. This RNA enzyme (E) catalyzes cleavage of an oligonucleotide substrate (S) by an exogenous guanosine (G) cofactor. The G 2′- and 3′-OH groups interact with an active site metal ion, termed M_C, within E·S·G, and we perturbed each of these contacts via −NH₃⁺ substitution. New and prior data indicate that G(2′NH₃⁺) and G(3′NH₃⁺) bind as strongly as G, suggesting that the −NH₃⁺ substituents of these analogues avoid repulsive interactions with M_C and make alternative interactions. Unexpectedly, removal of the adjacent −OH via −H substitution to give G(2′H,3′NH₃⁺) and G(2′NH₃⁺_,3′H) enhanced binding, in stark contrast to the deleterious effect of these substitutions on G binding. Pulse–chase experiments indicate that the −NH₃⁺ moiety of G(2′H,3′NH₃⁺) increases the rate of G association. These results suggest that the positively charged −NH₃⁺ group can act as a molecular “anchor” to increase the residence time of the encounter complex and thereby enhance productive binding. Electrostatic anchors may provide a broadly applicable strategy for the development of fast binding RNA ligands and RNA-targeted therapeutics.

Design and Synthetic Strategies for Helical Peptides

Abnormal protein-protein interactions (PPIs) are the basis of multiple diseases, and the large and shallow PPI interfaces make the target "undruggable" for traditional small molecules. Peptides, emerging as a new therapeutic modality, can efficiently mimic PPIs with their large scaffolds. Natural peptides are flexible and usually have poor serum stability and cell permeability, features that limit their further biological applications. To satisfy the clinical application of peptide inhibitors, many strategies have been developed to constrain peptides in their bioactive conformation. In this report, we describe several classic methods used to constrain peptides into a fixed secondary structure which could significantly improve their biophysical properties.

Interfaces Between Alpha-helical Integral Membrane Proteins: Characterization, Prediction, and Docking

Protein-protein interaction (PPI) is an essential mechanism by which proteins perform their biological functions. For globular proteins, the molecular characteristics of such interactions have been well analyzed, and many computational tools are available for predicting PPI sites and constructing structural models of the complex. In contrast, little is known about the molecular features of the interaction between integral membrane proteins (IMPs) and few methods exist for constructing structural models of their complexes. Here, we analyze the interfaces from a non-redundant set of complexes of α-helical IMPs whose structures have been determined to a high resolution. We find that the interface is not significantly different from the rest of the surface in terms of average hydrophobicity. However, the interface is significantly better conserved and, on average, inter-subunit contacting residue pairs correlate more strongly than non-contacting pairs, especially in obligate complexes. We also develop a neural network-based method, with an area under the receiver operating characteristic curve of 0.75 and a Pearson correlation coefficient of 0.70, for predicting interface residues and their weighted contact numbers (WCNs). We further show that predicted interface residues and their WCNs can be used as restraints to reconstruct the structure α-helical IMP dimers through docking for fourteen out of a benchmark set of sixteen complexes. The RMSD100 values of the best-docked ligand subunit to its native structure are <2.5 Å for these fourteen cases. The structural analysis conducted in this work provides molecular details about the interface between α-helical IMPs and the WCN restraints represent an efficient means to score α-helical IMP docking candidates.

Directed evolution of the metalloproteinase inhibitor TIMP-1 reveals that its N- and C-terminal domains cooperate in matrix metalloproteinase recognition

Tissue inhibitors of metalloproteinases (TIMPs) are natural inhibitors of matrix metalloproteinases (MMPs), enzymes that contribute to cancer and many inflammatory and degenerative diseases. The TIMP N-terminal domain binds and inhibits an MMP catalytic domain, but the role of the TIMP C-terminal domain in MMP inhibition is poorly understood. Here, we employed yeast surface display for directed evolution of full-length human TIMP-1 to develop MMP-3-targeting ultrabinders. By simultaneously incorporating diversity into both domains, we identified TIMP-1 variants that were up to 10-fold improved in binding MMP-3 compared with WT TIMP-1, with inhibition constants (K_i ) in the low picomolar range. Analysis of individual and paired mutations from the selected TIMP-1 variants revealed cooperative effects between distant residues located on the N- and C-terminal TIMP domains, positioned on opposite sides of the interaction interface with MMP-3. Crystal structures of MMP-3 complexes with TIMP-1 variants revealed conformational changes in TIMP-1 near the cooperative mutation sites. Affinity was strengthened by cinching of a reciprocal "tyrosine clasp" formed between the N-terminal domain of TIMP-1 and proximal MMP-3 interface and by changes in secondary structure within the TIMP-1 C-terminal domain that stabilize interdomain interactions and improve complementarity to MMP-3. Our protein engineering and structural studies provide critical insight into the cooperative function of TIMP domains and the significance of peripheral TIMP epitopes in MMP recognition. Our findings suggest new strategies to engineer TIMP proteins for therapeutic applications, and our directed evolution approach may also enable exploration of functional domain interactions in other protein systems.

Human antibody response to Zika targets type-specific quaternary structure epitopes

The recent Zika virus (ZIKV) epidemic in the Americas has revealed rare but serious manifestations of infection. ZIKV has emerged in regions endemic for dengue virus (DENV), a closely related mosquito-borne flavivirus. Cross-reactive antibodies confound studies of ZIKV epidemiology and pathogenesis. The immune responses to ZIKV may be different in people, depending on their DENV immune status. Here, we focus on the human B cell and antibody response to ZIKV as a primary flavivirus infection to define the properties of neutralizing and protective antibodies generated in the absence of preexisting immunity to DENV. The plasma antibody and memory B cell response is highly ZIKV type-specific, and ZIKV-neutralizing antibodies mainly target quaternary structure epitopes on the viral envelope. To map viral epitopes targeted by protective antibodies, we isolated 2 type-specific monoclonal antibodies (mAbs) from a ZIKV case. Both mAbs were strongly neutralizing in vitro and protective in vivo. The mAbs recognize distinct epitopes centered on domains I and II of the envelope protein. We also demonstrate that the epitopes of these mAbs define antigenic regions commonly targeted by plasma antibodies in individuals from endemic and nonendemic regions who have recovered from ZIKV infections.

Emerging roles of allosteric modulators in the regulation of protein-protein interactions (PPIs): A new paradigm for PPI drug discovery

Protein-protein interactions (PPIs) are closely implicated in various types of cellular activities and are thus pivotal to health and disease states. Given their fundamental roles in a wide range of biological processes, the modulation of PPIs has enormous potential in drug discovery. However, owing to the general properties of large, flat, and featureless interfaces of PPIs, previous attempts have demonstrated that the generation of therapeutic agents targeting PPI interfaces is challenging, rendering them almost "undruggable" for decades. To date, rapid progress in chemical and structural biology techniques has promoted the exploitation of allostery as a novel approach in drug discovery. By attaching to allosteric sites that are topologically and spatially distinct from PPI interfaces, allosteric modulators can achieve improved physiochemical properties. Thus, allosteric modulators may represent an alternative strategy to target intractable PPIs and have attracted intense pharmaceutical interest. In this review, we first briefly introduce the characteristics of PPIs and then present different approaches for investigating PPIs, as well as the latest methods for modulating PPIs. Importantly, we comprehensively review the recent progress in the development of allosteric modulators to inhibit or stabilize PPIs. Finally, we conclude with future perspectives on the discovery of allosteric PPI modulators, especially the application of computational methods to aid in allosteric PPI drug discovery.

Principles and characteristics of biological assemblies in experimentally determined protein structures

More than half of all structures in the PDB are assemblies of two or more proteins, including both homooligomers and heterooligomers. Structural information on these assemblies comes from X-ray crystallography, NMR, and cryo-EM spectroscopy. The correct assembly in an X-ray structure is often ambiguous, and computational methods have been developed to identify the most likely biologically relevant assembly based on physical properties of assemblies and sequence conservation in interfaces. Taking advantage of the large number of structures now available, some of the most recent methods have relied on similarity of interfaces and assemblies across structures of homologous proteins.

Design criteria for minimalist mimics of protein-protein interface segments

Small molecules that can interrupt or inhibit protein-protein interactions (PPIs) are valuable as probes in chemical biology and medicinal chemistry, but they are also notoriously difficult to develop. Design of non-peptidic small molecules that mimic amino acid side-chain interactions in PPIs ("minimalist mimics") is seen as a way to fast track discovery of PPI inhibitors. However, there has been little comment on general design criteria for minimalist mimics, even though such guidelines could steer construction of libraries to screen against multiple PPI targets. We hypothesized insight into general design criteria for minimalist mimics could be gained by comparing preferred conformations of typical minimalist mimic designs against side-chain orientations on a huge number of PPI interfaces. That thought led to this work which features nine minimalist mimic designs: one from the literature, and eight new "hypothetical" ones conceived by us. Simulated preferred conformers of these were systematically aligned with >240 000 PPI interfaces from the Protein Data Bank. Conclusions from those analyses did indeed reveal various design considerations that are discussed here. Surprisingly, this study also showed one of the minimalist mimic designs aligned on PPI interface segments more than 15 times more frequently than any other in the series (according to uniform standards described herein); reasons for this are also discussed.

ALTHEA Gold Libraries™: antibody libraries for therapeutic antibody discovery

We describe here the design, construction and validation of ALTHEA Gold Libraries™. These single-chain variable fragment (scFv), semisynthetic libraries are built on synthetic human well-known IGHV and IGKV germline genes combined with natural human complementarity-determining region (CDR)-H3/J_H (H3J) fragments. One IGHV gene provided a universal V_H scaffold and was paired with two IGKV scaffolds to furnish different topographies for binding distinct epitopes. The scaffolds were diversified at positions identified as in contact with antigens in the known antigen-antibody complex structures. The diversification regime consisted of high-usage amino acids found at those positions in human antibody sequences. Functionality, stability and diversity of the libraries were improved throughout a three-step construction process. In a first step, fully synthetic primary libraries were generated by combining the diversified scaffolds with a set of synthetic neutral H3J germline gene fragments. The second step consisted of selecting the primary libraries for enhanced thermostability based on the natural capacity of Protein A to bind the universal V_H scaffold. In the third and final step, the resultant stable synthetic antibody fragments were combined with natural H3J fragments obtained from peripheral blood mononuclear cells of a large pool of 200 donors. Validation of ALTHEA Gold Libraries™ with seven targets yielded specific antibodies in all the cases. Further characterization of the isolated antibodies indicated K_D values as human IgG1 molecules in the single-digit and sub-nM range. The thermal stability (Tm) of all the antigen-binding fragments was 75°C–80°C, demonstrating that ALTHEA Gold Libraries™ are a valuable source of specific, high affinity and highly stable antibodies.

Rapid Mapping of Protein Binding Sites and Conformational Epitopes by Coupling Yeast Surface Display to Chemical Labeling and Deep Sequencing

Delineating the precise regions on an antigen that are targeted by antibodies is important for the development of vaccines and antibody therapeutics. X-ray crystallography and NMR are considered the gold standard for providing precise information about these binding sites at atomic resolution. However, these are labor-intensive and require purified protein at high concentration. We have recently described [1] a rapid and reliable method that overcomes these constraints, using a panel of single cysteine mutants of the protein of interest and now provide protocols to facilitate its adoption. Mutants are displayed on the yeast cell surface either individually or as a pool, and labeled covalently with a cysteine specific probe. Binding site residues are inferred by monitoring loss of ligand or antibody binding by flow cytometry coupled to deep sequencing of sorted populations, or Sanger sequencing of individual clones. Buried cysteine residues are not labeled and library sizes are small, facilitating rapid identification of binding-site residues. The methodology was used to identify epitopes on the bacterial toxin CcdB targeted by twenty-four different monoclonal antibodies as well as by polyclonal sera. The method does not require purified protein or protein structural information and can be applied to a variety of display formats.

Epitope Mapping Using Yeast Display and Next Generation Sequencing

Monoclonal antibodies are the largest class of therapeutic proteins due in part to their ability to bind an antigen with a high degree of affinity and specificity. A precise determination of their epitope is important for gaining insights into their therapeutic mechanism of action and to help differentiate antibodies that bind the same antigen. Here, we describe a method to precisely and efficiently map the epitopes of multiple antibodies in parallel over the course of just several weeks. This approach is based on a combination of rational library design, yeast surface display, and next generation DNA sequencing and provides quantitative insights into the epitope residues most critical for the antibody-antigen interaction. As an example, we will use this method to map the epitopes of several antibodies that neutralize alpha toxin from Staphylococcus aureus.

Crystal structure of the complex between venom toxin and serum inhibitor from Viperidae snake

Venomous snakes have endogenous proteins that neutralize the toxicity of their venom components. We previously identified five small serum proteins (SSP-1-SSP-5) from a highly venomous snake belonging to the family Viperidae as inhibitors of various toxins from snake venom. The endogenous inhibitors belong to the prostate secretory protein of 94 amino acids (PSP94) family. SSP-2 interacts with triflin, which is a member of the cysteine-rich secretory protein (CRISP) family that blocks smooth muscle contraction. However, the structural basis for the interaction and the biological roles of these inhibitors are largely unknown. Here, we determined the crystal structure of the SSP-2-triflin complex at 2.3 Å resolution. A concave region centrally located in the N-terminal domain of triflin is fully occupied by the terminal β-strands of SSP-2. SSP-2 does not bind tightly to the C-terminal cysteine-rich domain of triflin; this domain is thought to be responsible for its channel-blocker function. Instead, the cysteine-rich domain is tilted 7.7° upon binding to SSP-2, and the inhibitor appears to sterically hinder triflin binding to calcium channels. These results help explain how an endogenous inhibitor prevents the venomous protein from maintaining homeostasis in the host. Furthermore, this interaction also sheds light on the binding interface between the human homologues PSP94 and CRISP-3, which are up-regulated in prostate and ovarian cancers.

Protein-protein binding supersites

The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding regulatory mechanisms of the functions they mediate. Understanding protein-protein interactions is also essential for designing specific chemical modifications to develop new reagents and therapeutics. We explored the hypothesis of whether protein interaction sites serve as generic biding sites for non-cognate protein ligands, just as it has been observed for small-molecule-binding sites in the past. Using extensive computational docking experiments on a test set of 241 protein complexes, we found that indeed there is a strong preference for non-cognate ligands to bind to the cognate binding site of a receptor. This observation appears to be robust to variations in docking programs, types of non-cognate protein probes, sizes of binding patches, relative sizes of binding patches and full-length proteins, and the exploration of obligate and non-obligate complexes. The accuracy of the docking scoring function appears to play a role in defining the correct site. The frequency of interaction of unrelated probes recognizing the binding interface was utilized in a simple prediction algorithm that showed accuracy competitive with other state of the art methods.

In silico structure-based design of enhanced peptide inhibitors targeting RNA polymerase PAN-PB1C interaction

Developing antivirals for influenza A virus (FluA) has become more challenging due to high range of antigenic mutation and increasing numbers of drug-resistant viruses. Finding a selective inhibitor to target highly conserved region of protein-protein interactions interface, thereby increasing its efficiency against drug resistant virus could be highly beneficial. In this study, we used in silico approach to derive FluAPep1 from highly conserved region, PA_N-PB1_C interface and generated 121 FluAPep1 analogues. Interestingly, we found that the FluAPep1 interaction region in the PA_N domain are highly conserved in many FluA subtypes. Especially, FluAPep1 targets two pandemic FluA strains, H1N1/avian/2009 and H3N2/Victoria/1975. All of these FluA subtypes PA_N domain (H1N1/H3N2CAN/H3N2VIC/H7N1/H7N2) were superimposed with PA_N domain from H17N10 and the calculated root mean standards deviations were less than 3 Å. FlexPepDock analysis revealed that FluAPep1 exhibited higher binding affinity (score -246.155) with the PA_N domain. In addition, around 86% of non-hot spot mutated peptides (FluAPep28-122) showed enhanced binding affinity with PA_N domain. ToxinPred analysis confirmed that designed peptides were non-toxic. Thus, FluAPep1 and its analogues has potential to be further developed into an antiviral treatment against FluA infection.

Allosteric Modulators of Protein-Protein Interactions (PPIs)

Protein-protein interactions (PPIs) represent promising drug targets of broad-spectrum therapeutic interests due to their critical implications in both health and disease circumstances. Hence, they are widely accepted as the Holy Grail of drug development. Historically, PPIs were rendered "undruggable" for their large, flat, and pocket-less structures. Current attempts to drug these "intractable" targets include orthosteric and allosteric methodologies. Previous efforts employing orthosteric approaches like protein therapeutics and orthosteric small molecules frequently suffered from poor performance caused by the difficulties in directly targeting PPI interfaces. As structural biology progresses rapidly, allosteric modulators, which direct to the allosteric regulatory sites remote to the PPI surfaces, have gradually established as a potential solution. Allosteric pockets are topologically distal from the PPI orthosteric sites, and their ligands do not need to compete with the PPI partners, which helps to improve the physiochemical and pharmacological properties of allosteric PPI modulators. Thus, exploiting allostery to tailor PPIs is regarded as a tempting strategy in future PPI drug discovery. Here, we provide a comprehensive review of our representative achievements along the way we utilize allosteric effects to tame the difficult PPI systems into druggable targets. Importantly, we provide an in-depth mechanistic analysis of this success, which will be instructive to future related lead optimizations and drug design. Finally, we discuss the current challenges in allosteric PPI drug discovery. Their solutions as well as future perspectives are also presented.