Protein-protein interactions: principles, techniques, and their potential role in new drug development

DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning

Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.

Precise Recognition in Water by an Endo-Functionalized Cavity: Tuning the Complementarity of Binding Sites

Precise binding towards structurally similar substrates is a common feature of biomolecular recognition. However, achieving such selectivity-especially in distinguishing subtle differences in substrates-with synthetic hosts can be quite challenging. Herein, we report a novel design strategy involving the combination of different rigid skeletons to adjust the distance between recognition sites within the cavity, which allows for the highly selective recognition of hydrogen-bonding complementary substrates, such as 4-chromanone. X-ray single-crystal structures and density functional theory calculations confirmed that the distance of endo-functionalized groups within the rigid cavity is crucial for achieving high binding selectivity through hydrogen bonding. The thermodynamic data and molecular dynamics simulations revealed a significant influence of the hydrophobic cavity on the binding affinity. The new receptor possesses both high selectivity and high affinity, which provide valuable insights for the design of customized receptors.

Drug discovery by targeting the protein-protein interactions involved in autophagy

Autophagy is a cellular process in which proteins and organelles are engulfed in autophagosomal vesicles and transported to the lysosome/vacuole for degradation. Protein-protein interactions (PPIs) play a crucial role at many stages of autophagy, which present formidable but attainable targets for autophagy regulation. Moreover, selective regulation of PPIs tends to have a lower risk in causing undesired off-target effects in the context of a complicated biological network. Thus, small-molecule regulators, including peptides and peptidomimetics, targeting the critical PPIs involved in autophagy provide a new opportunity for innovative drug discovery. This article provides general background knowledge of the critical PPIs involved in autophagy and reviews a range of successful attempts on discovering regulators targeting those PPIs. Successful strategies and existing limitations in this field are also discussed.

Molecular Interactions of the Copper Chaperone Atx1 of Paracoccidioides brasiliensis with Fungal Proteins Suggest a Crosstalk between Iron and Copper Homeostasis

Paracoccidioides spp. are endemic fungi from Latin America that cause Paracoccidioidomycosis, a systemic disease. These fungi present systems for high-affinity metal uptake, storage, and mobilization, which counteract host nutritional immunity and mitigate the toxic effects of metals. Regarding Cu mobilization, the metallochaperone Atx1 is regulated according to Cu bioavailability in Paracoccidioides spp., contributing to metal homeostasis. However, additional information in the literature on PbAtx1 is scarce. Therefore, in the present work, we aimed to study the PbAtx1 protein-protein interaction networks. Heterologous expressed PbAtx1 was used in a pull-down assay with Paracoccidioides brasiliensis cytoplasmic extract. Nineteen proteins that interacted with PbAtx1 were identified by HPLC-MS^E. Among them, a relevant finding was a Cytochrome b₅ (PbCyb5), regulated by Fe bioavailability in Aspergillus fumigatus and highly secreted by P. brasiliensis in Fe deprivation. We validated the interaction between PbAtx1-PbCyb5 through molecular modeling and far-Western analyses. It is known that there is a relationship between Fe homeostasis and Cu homeostasis in organisms. In this sense, would PbAtx1-PbCyb5 interaction be a new metal-sensor system? Would it be supported by the presence/absence of metals? We intend to answer those questions in future works to contribute to the understanding of the strategies employed by Paracoccidioides spp. to overcome host defenses.

Single-Molecule Sensing of an Anticancer Therapeutic Protein-Protein Interaction Using the Chemically Modified OmpG Nanopore

Nanopore sensors are a highly attractive platform for single-molecule sensing for sequencing, disease diagnostics, and drug screening. Outer membrane protein G (OmpG) nanopores have advantages for single-molecule sensing owing to their rigid monomeric structure, which comprises seven flexible loops, providing distinct gating patterns upon analyte binding. Blocking of the protein-protein interaction between B-cell lymphoma-extra-large (Bcl-xL) and the BH3 domain of Bcl-2 homologous antagonist/killer (Bak-BH3) has been reported as a promising strategy for anticancer therapy. Here, we characterized the interaction between Bcl-xL and Bak-BH3 as well as its inhibition by a small-molecule inhibitor using click chemistry-based Bak-BH3 peptide-conjugated OmpG nanopores. The binding of Bcl-xL to Bak-BH3 generated characteristic gating signals involving significant changes in the amplitudes of noise and gating parameters such as gating frequency, open probability, and durations of open and closed states. Notably, specific inhibition of Bcl-xL by the small-molecule antagonist, ABT-737, led to the recovery of the noise and gating parameters. Collectively, these results revealed that the chemically modified OmpG nanopore can serve as a valuable sensor platform for ultrasensitive, rapid, and single-molecule-based drug screening against protein-protein interactions, which are therapeutic targets for various diseases.

Selective Modulation of Dynamic Protein Complexes

Dynamic proteins perform critical roles in cellular machines, including those that control proteostasis, transcription, translation, and signaling. Thus, dynamic proteins are prime candidates for chemical probe and drug discovery but difficult targets because they do not conform to classical rules of design and screening. Selectivity is pivotal for candidate probe molecules due to the extensive interaction network of these dynamic hubs. Recognition that the traditional rules of probe discovery are not necessarily applicable to dynamic proteins and their complexes, as well as technological advances in screening, have produced remarkable results in the last 2-4 years. Particularly notable are the improvements in target selectivity for small-molecule modulators of dynamic proteins, especially with techniques that increase the discovery likelihood of allosteric regulatory mechanisms. We focus on approaches to small-molecule screening that appear to be more suitable for highly dynamic targets and have the potential to streamline identification of selective modulators.

Molecular dynamics simulation study of Plasmodium falciparum and Escherichia coli SufA: Exploration of conformational changes possibly involved in iron-sulfur cluster transfer

Iron-sulfur (Fe-S) clusters are one of the earliest known metal complexes in biological molecules. Suf system is one of the Fe-S biogenesis pathways. SufA belongs to the Suf pathway. It is an A-type carrier protein that transfers Fe-S clusters from the scaffold to target proteins. Structural studies were performed for the Suf pathway protein, SufA, in order to explore the conformational changes that probably aid in the transfer of Fe-S clusters to target proteins. Three-dimensional (3D) structure of Plasmodium falciparum (Pf) SufA homodimer was obtained by homology modeling using 3D structure of Escherichia coli (Ec) SufA as template. Molecular dynamics (MD) simulation of Pf SufA and Ec SufA homodimers followed by trajectory and pocket analyses were carried out. A co-ordinated displacement of the homodimeric chains in the interfacial region, resembling a swinging trapeze-like movement was observed. Potential involvement of this swinging trapeze-like movement of the residues belonging to the interfacial region has been proposed as a probable mechanism that assists in the transfer of Fe-S cluster from SufA to apo proteins. This was substantiated by protein-protein interaction studies in Pf SufA by performing molecular docking of 3D conformations of Pf SufA obtained from MD trajectory at every 1 ns interval with Pf ferredoxin.Communicated by Ramaswamy H. Sarma.

Protein-Protein Interactions in Candida albicans

Despite being one of the most important human fungal pathogens, Candida albicans has not been studied extensively at the level of protein-protein interactions (PPIs) and data on PPIs are not readily available in online databases. In January 2018, the database called "Biological General Repository for Interaction Datasets (BioGRID)" that contains the most PPIs for C. albicans, only documented 188 physical or direct PPIs (release 3.4.156) while several more can be found in the literature. Other databases such as the String database, the Molecular INTeraction Database (MINT), and the Database for Interacting Proteins (DIP) database contain even fewer interactions or do not even include C. albicans as a searchable term. Because of the non-canonical codon usage of C. albicans where CUG is translated as serine rather than leucine, it is often problematic to use the yeast two-hybrid system in Saccharomyces cerevisiae to study C. albicans PPIs. However, studying PPIs is crucial to gain a thorough understanding of the function of proteins, biological processes and pathways. PPIs can also be potential drug targets. To aid in creating PPI networks and updating the BioGRID, we performed an exhaustive literature search in order to provide, in an accessible format, a more extensive list of known PPIs in C. albicans.

Interaction of piroxicam with bovine serum albumin investigated by spectroscopic, calorimetric and computational molecular methods

The binding of drugs to serum proteins is governed by weak non-covalent forces. In this study, the nature and magnitude of the interactions between piroxicam (PRX) and bovine serum albumin (BSA) was assessed using spectroscopic, calorimetric and computational molecular methods. The fluorescence data revealed an atypical behavior during PRX and BSA interaction. The quenching process of tryptophan (Trp) by PRX is a dual one (approximately equal static and dynamic quenched components). The FRET results indicate that a non-radiative transfer of energy occurred. The association constant and the number of binding sites indicate moderate PRX and BSA binding. The competitive binding study indicates that PRX is bound to site I from the hydrophobic pocket of subdomain IIA of BSA. The synchronous spectra showed that the microenvironment around the BSA fluorophores and protein conformation do not change considerably. The Trp lifetimes revealed that PRX mainly quenches the fluorescence of Trp-213 situated in the hydrophobic domain. The CD and DSC investigation show that addition of PRX stabilizes the protein structure. ITC results revealed that BSA-PRX binding involves a combination of electrostatic, hydrophobic and hydrogen interactions. The analysis of the computational data is consistent with the experimental results. This thorough investigation of the PRX-BSA binding may provide support for other studies concerning moderate affinity drugs with serum protein.Communicated by Ramaswamy H. Sarma.

Borrelia burgdorferi protein interactions critical for microbial persistence in mammals

Borrelia burgdorferi is the causative agent of Lyme disease that persists in a complex enzootic life cycle, involving Ixodes ticks and vertebrate hosts. The microbe invades ticks and vertebrate hosts in spite of active immune surveillance and potent microbicidal responses, and establishes long-term infection utilising mechanisms that are yet to be unravelled. The pathogen can cause multi-system disorders when transmitted to susceptible mammalian hosts, including in humans. In the past decades, several studies identified a limited number of B. burgdorferi gene-products critical for pathogen persistence, transmission between the vectors and the host, and host-pathogen interactions. This review will focus on the interactions between B. burgdorferi proteins, as well as between microbial proteins and host components, protein and non-protein components, highlighting their roles in pathogen persistence in the mammalian host. A better understanding of the contributions of protein interactions in the microbial virulence and persistence of B. burgdorferi would support development of novel therapeutics against the infection.

A protein-protein interaction dictates Borrelial infectivity

Two Borrelia burgdorferi interacting proteins, BB0238 and BB0323, play distinct roles in pathogen biology and infectivity although a significance of their interaction remained enigmatic. Here we identified the polypeptide segment essential for BB0238-BB0323 interaction and examined how it supports spirochete infectivity. We show that the interaction region in BB0323 requires amino acid residues 22-200, suggesting that the binding encompasses discontinuous protein segments. In contrast, the interaction region in BB0238 spans only 11 amino acids, residues 120-130. A deletion of these 11 amino acids neither alters the overall secondary structure of the protein, nor affects its stability or oligomerization property, however, it reduces the post-translational stability of the binding partner, BB0323. Mutant B. burgdorferi isolates producing BB0238 lacking the 11-amino acid interaction region were able to persist in ticks but failed to transmit to mice or to establish infection. These results suggest that BB0238-BB0323 interaction is critical for post-translational stability of BB0323, and that this interaction is important for mammalian infectivity and transmission of B. burgdorferi. We show that saturation or inhibition of BB0238-BB0323 interaction could be studied in a luciferase assay, which could be amenable for future identification of small molecule inhibitors to combat B. burgdorferi infection.

Insight into the intermolecular recognition mechanism involved in complement component 4 activation through serine protease-trypsin

Serine protease cleaved-complement component 4 (C4) at sessile loop, which is significant for completion of lectin and classical complement pathways at the time of infections. The co-crystalized structure of C4 with Mannose-binding protein-associated serine protease 2 (MASP2) provided the structural and functional aspects of its interaction and underlined the C4 activation by MASP2. The same study also revealed the significance of complement control protein (CCP) domain through mutational study, where mutated CCP domain led to the inhibition of C4 activation. However, the interaction of trypsin serine domain with C4α sessile loop revealed another aspect of C4 activation. The human C4 cleavage by Trypsin (Tryp) in a control manner was explored but not yet revealed the identification of cleaved fragments. Hence, the present study investigated the Tryp mediated C4 activation using computational approach (protein-protein docking and molecular dynamics simulation) by comparing with the co-crystalized structure of C4-MASP2. Docking result identified the crucial interacting residues Gly219, Gln178, and Asn102 of Tryp catalytic pocket which were interacting with Arg756 and Glu759 (sessile loop) of α-Chain (C4) in a similar manner to C4-MASP2 co-crystallized complex. Moreover, MD simulation results and mutational study underlined the conformational rearrangements in the C4 due to the Tryp interaction. Comparative analysis of C4 alone, C4-Tryp, and C4-MASP2 revealed the impact of Tryp on C4 was similar as MASP2. These studies designate the role of sessile loop in the interaction with serine domain, which could be useful to understand the various interactions of C4 with other complement components.

A novel index of protein-protein interface propensity improves interface residue recognition

Background

Protein-protein interface holds important information of protein-protein interactions which play key roles in most biological processes. In the past few years, a lot of efforts have been made to improve interface residue recognition by characterizing protein-protein interfaces and extracting relevant features. However, most previous studies were carried out in a qualitative level, and there are also some inconsistencies between them.

Results

In the present work, to improve interface residue recognition, we built a novel quantitative residue protein-protein interface propensity index (QIPI) and gained a comprehensive picture of protein-protein interface through analyzing protein-protein interfaces on our comprehensive protein-protein interfaces dataset (Astral2.05-40-4506). Furthermore, in order to assess the effect of QIPI in improving the protein-protein interface prediction, we developed an interface residue recognition method SPR (Single domain based Patch Recognition) based on the QIPI. The evaluation results proved that our novel QIPI is able to improve the interface residue recognition.

Conclusions

Through a comprehensive quantitative analysis of protein-protein interface, we constructed a novel quantitative protein-protein interface propensity index (QIPI), which could be easily applied to improve the interface residue recognition and helpful in understanding the protein-protein interface.

Availability

QIPI and SPR are available to non-commercial users at our website: http://www.scbit.org/QIPI/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0351-7) contains supplementary material, which is available to authorized users.

Reactive oxygen species and energy machinery: an integrated dynamic model

The role of several important reactive oxygen species (ROS) on the Krebs cycle, the electron transport chain (ETC) and the two important shuttles has been modelled. Major part of the ROS is produced during oxygen reduction in the ETC, which has been kinetically simulated, and the changes in the final concentrations of several important metabolites were found. The simulation is based on chemical kinetics equation, and the associated set of differential equations was solved by the ordinary differential equation package in Octave. The validity of the model is checked by comparing the experimental results available in the literature with the simulations when a part of the ETC is blocked (80%) in the script. The present approach is versatile and flexible and has potential applications in various simulations. It is easy to study the change in concentrations of various metabolites when a particular enzyme or pathway is blocked (say by a drug). The Octave script is presented in the text.

Efficient prediction of human protein-protein interactions at a global scale

BACKGROUND

Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.

RESULTS

On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments.

CONCLUSIONS

The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

The functional landscape of Hsp27 reveals new cellular processes such as DNA repair and alternative splicing and proposes novel anticancer targets

Previously, we identified the stress-induced chaperone, Hsp27, as highly overexpressed in castration-resistant prostate cancer and developed an Hsp27 inhibitor (OGX-427) currently tested in phase I/II clinical trials as a chemosensitizing agent in different cancers. To better understand the Hsp27 poorly-defined cytoprotective functions in cancers and increase the OGX-427 pharmacological safety, we established the Hsp27-protein interaction network using a yeast two-hybrid approach and identified 226 interaction partners. As an example, we showed that targeting Hsp27 interaction with TCTP, a partner protein identified in our screen increases therapy sensitivity, opening a new promising field of research for therapeutic approaches that could decrease or abolish toxicity for normal cells. Results of an in-depth bioinformatics network analysis allying the Hsp27 interaction map into the human interactome underlined the multifunctional character of this protein. We identified interactions of Hsp27 with proteins involved in eight well known functions previously related to Hsp27 and uncovered 17 potential new ones, such as DNA repair and RNA splicing. Validation of Hsp27 involvement in both processes in human prostate cancer cells supports our system biology-predicted functions and provides new insights into Hsp27 roles in cancer cells.

Live cell imaging of interactions between replicase and capsid protein of Brome mosaic virus using Bimolecular Fluorescence Complementation: implications for replication and genome packaging

In Brome mosaic virus, it was hypothesized that a physical interaction between viral replicase and capsid protein (CP) is obligatory to confer genome packaging specificity. Here we tested this hypothesis by employing Bimolecular Fluorescent Complementation (BiFC) as a tool for evaluating protein-protein interactions in living cells. The efficacy of BiFC was validated by a known interaction between replicase protein 1a (p1a) and protein 2a (p2a) at the endoplasmic reticulum (ER) site of viral replication. Additionally, co-expression in planta of a bona fide pair of interacting protein partners of p1a and p2a had resulted in the assembly of a functional replicase. Subsequent BiFC assays in conjunction with mCherry labeled ER as a fluorescent cellular marker revealed that CP physically interacts with p2a, but not p1a, and this CP:p2a interaction occurs at the cytoplasmic phase of the ER. The significance of the CP:p2a interaction in BMV replication and genome packaging is discussed.

Role of β-lactamase residues in a common interface for binding the structurally unrelated inhibitory proteins BLIP and BLIP-II

The β-lactamase inhibitory proteins (BLIPs) are a model system for examining molecular recognition in protein-protein interactions. BLIP and BLIP-II are structurally unrelated proteins that bind and inhibit TEM-1 β-lactamase. Both BLIPs share a common binding interface on TEM-1 and make contacts with many of the same TEM-1 surface residues. BLIP-II, however, binds TEM-1 over 150-fold tighter than BLIP despite the fact that it has fewer contact residues and a smaller binding interface. The role of eleven TEM-1 amino acid residues that contact both BLIP and BLIP-II was examined by alanine mutagenesis and determination of the association (k on) and dissociation (k off) rate constants for binding each partner. The substitutions had little impact on association rates and resulted in a wide range of dissociation rates as previously observed for substitutions on the BLIP side of the interface. The substitutions also had less effect on binding affinity for BLIP than BLIP-II. This is consistent with the high affinity and small binding interface of the TEM-1-BLIP-II complex, which predicts per residue contributions should be higher for TEM-1 binding to BLIP-II versus BLIP. Two TEM-1 residues (E104 and M129) were found to be hotspots for binding BLIP while five (L102, Y105, P107, K111, and M129) are hotspots for binding BLIP-II with only M129 as a common hotspot for both. Thus, although the same TEM-1 surface binds to both BLIP and BLIP-II, the distribution of binding energy on the surface is different for the two target proteins, that is, different binding strategies are employed.

POODLE: tools predicting intrinsically disordered regions of amino acid sequence

Protein intrinsic disorder, a widespread phenomenon characterized by a lack of stable three-dimensional structure, is thought to play an important role in protein function. In the last decade, dozens of computational methods for predicting intrinsic disorder from amino acid sequences have been developed. They are widely used by structural biologists not only for analyzing the biological function of intrinsic disorder but also for finding flexible regions that possibly hinder successful crystallization of the full-length protein. In this chapter, I introduce Prediction Of Order and Disorder by machine LEarning (POODLE), which is a series of programs accurately predicting intrinsic disorder. After giving the theoretical background for predicting intrinsic disorder, I give a detailed guide to using POODLE. I then also briefly introduce a case study where using POODLE for functional analyses of protein disorder led to a novel biological findings.

De-peptidising protein-protein interactions - big jobs for small molecules

Virtually all biological processes rely on protein-protein interactions (PPIs) for signal propagation, therefore representing a vast array of potentially viable therapeutic intervention points. Targeting PPIs is a relatively novel drug development strategy so computational approaches towards analysing the interface between protein partners and predicting the likelihood of developing a small molecule inhibitor are still progressing. This review provides an overview of recent successful examples of computational methodologies used to predict druggable PPIs and small molecules designed to inhibit them.

SRChing for the substrates of Src

By the mid 1980's, it was clear that the transforming activity of oncogenic Src was linked to the activity of its tyrosine kinase domain and attention turned to identifying substrates, the putative next level of control in the pathway to transformation. Among the first to recognize the potential of phosphotyrosine-specific antibodies, Parsons and colleagues launched a risky shotgun-based approach that led ultimately to the cDNA cloning and functional characterization of many of today's best-known Src substrates (for example, p85-Cortactin, p110-AFAP1, p130Cas, p125FAK and p120-catenin). Two decades and over 6000 citations later, the original goals of the project may be seen as secondary to the enormous impact of these protein substrates in many areas of biology. At the request of the editors, this review is not restricted to the current status of the substrates, but reflects also on the anatomy of the project itself and some of the challenges and decisions encountered along the way.

Protein-protein interactions among West Nile non-structural proteins and transmembrane complex formation in mammalian cells

To study the membrane orientation of flavivirus non-structural proteins (NSPs) in the replication complex, the seven major West Nile (WN) NSPs were separately expressed in monkey cells, and their subcellular localization was investigated by imaging-based techniques. First, we observed by confocal microscopy that four small transmembrane proteins (TP) (NS2A, NS2B, NS4A, and NS4B) were located to the endoplasmic reticulum (ER), whereas the largest NSPs, NS1, NS3, and NS5 were not. We then analyzed the colocalization and the association of WN NSPs using the methods of confocal microscopy, fluorescence resonance energy transfer (FRET), and biologic fluorescence complementation (BiFC). Through these combined imaging techniques, protein-protein interactions (PPI) among WNNSPs were detected. Our data demonstrate that there are interactions between NS2A and NS4A, and interactions of NS2B with three other TPs (NS2A, NS4A, and NS4B) as well as the expected interaction with NS3. PPI between NS2A and NS4B or between NS4A and NS4B were not detected. By the criteria of these techniques, NS5 interacted only with NS3, and NS1 was not shown to be in close proximity with other NSPs. In addition, homo-oligomerization of some NSPs was observed and three-way interactions between NS2A, NS4A, and NA4B with NS2B-NS3 were also observed, respectively. Our results suggest that the four TPs are required for formation of transmembrane complex. NS2B protein seems to play a key role in bringing the TPs together on the ER membrane and in bridging the TPs with non-membrane-associated proteins (NS3 and NS5).

Protein interaction networks as starting points to identify novel antimicrobial drug targets

Novel classes of antimicrobials are needed to address the challenge of multidrug-resistant bacteria. Current bacterial drug targets mainly consist of specific proteins or subsets of proteins without regard for either how these targets are integrated in cellular networks or how they may interact with host proteins. However, proteins rarely act in isolation, and the majority of biological processes are dependent on interactions with other proteins. Consequently, protein-protein interaction (PPI) networks offer a realm of unexplored potential for next-generation drug targets. In this review, we argue that the architecture of bacterial or host-pathogen protein interactomes can provide invaluable insights for the identification of novel antibacterial drug targets.

Host-rabies virus protein-protein interactions as druggable antiviral targets

We present an unconventional approach to antiviral drug discovery, which is used to identify potent small molecules against rabies virus. First, we conceptualized viral capsid assembly as occurring via a host-catalyzed biochemical pathway, in contrast to the classical view of capsid formation by self-assembly. This suggested opportunities for antiviral intervention by targeting previously unappreciated catalytic host proteins, which were pursued. Second, we hypothesized these host proteins to be components of heterogeneous, labile, and dynamic multi-subunit assembly machines, not easily isolated by specific target protein-focused methods. This suggested the need to identify active compounds before knowing the precise protein target. A cell-free translation-based small molecule screen was established to recreate the hypothesized interactions involving newly synthesized capsid proteins as host assembly machine substrates. Hits from the screen were validated by efficacy against infectious rabies virus in mammalian cell culture. Used as affinity ligands, advanced analogs were shown to bind a set of proteins that effectively reconstituted drug sensitivity in the cell-free screen and included a small but discrete subfraction of cellular ATP-binding cassette family E1 (ABCE1), a host protein previously found essential for HIV capsid formation. Taken together, these studies advance an alternate view of capsid formation (as a host-catalyzed biochemical pathway), a different paradigm for drug discovery (whole pathway screening without knowledge of the target), and suggest the existence of labile assembly machines that can be rendered accessible as next-generation drug targets by the means described.

Free and total biotherapeutic evaluation in chromatographic assays: interference from targets and immunogenicity

Measurement of drug concentrations is critical during drug development, supporting evaluation of safety and efficacy in the context of pharmacokinetics. Protein-based therapeutics have been historically measured by immunoassay methods. Technological advances provide new opportunities to measure these biotherapeutics using previously incompatible chromatographic techniques, such as MS. These advances are breaking down the barriers between ‘large-molecule’ and ‘small-molecule’ bioanalysis, and pushing scientists outside their comfort zones. One challenge in measuring biotherapeutic concentration is potential impact from other matrix components, such as therapeutic target or antidrug antibodies. Depending on the specific assay development objective, target interference could be either desired (favoring free measurement) or undesired (favoring total measurement). Orthogonal techniques provide additional tools to meet this challenge. The goal of this review is to introduce both small- and large-molecule bioanalytical scientists to the opportunities and challenges to consider while evaluating orthogonal methods for biotherapeutic bioanalysis.

Polyproline and Tat transduction peptides in the study of the rapid actions of steroid receptors

Cellular responses to signals require the action of a myriad of protein networks, which are regulated by protein/protein associations. Rapid actions of steroid hormones are also subject to this regulation. They induce direct association of steroid receptors with different proteins (e.g., growth factor receptors, signaling effectors, scaffold proteins, transcription factors). These multi-molecular complexes drive signaling activation and finally trigger basic hormonal effects. Receptor/protein associations are attracting increased interest concerning their role in hormone action as well as their potential use as therapeutic targets in hormonal diseases.

Inhibition of protein-protein interaction of HER2-EGFR and HER2-HER3 by a rationally designed peptidomimetic

Protein-protein interactions (PPI) play a crucial role in many biological processes and modulation of PPI using small molecules to target hot spots has therapeutic value. As a model system we will use PPI of human epidermal growth factor receptors (EGFRs). Among the four EGFRs, EGFR-HER2 and HER2-HER3 are well known in cancer. We have designed a small molecule that is targeted to modulate HER2-mediated signaling. Our approach is novel because the small molecule designed disrupts dimerization not only of EGFR-HER2, but also of HER2-HER3. In the present study we have shown, using surface plasmon resonance analysis, that a peptidomimetic, compound 5, binds specifically to HER2 protein extracellular domain and disrupts the dimerization of EGFRs. To evaluate the effect of compound 5 on HER2 signaling in vitro, Western blot and PathHunter assays were used. Results indicated that compound 5 inhibits the phosphorylation of HER2 kinase domain and inhibits the heterodimerization in a dose-dependent manner. Molecular modeling methods were used to model the PPI of HER2-HER3 heterodimer.

Understanding the molecular basis of MK2-p38α signaling complex assembly: insights into protein-protein interaction by molecular dynamics and free energy studies

The formation of a p38 MAPK and MAPK-activated protein kinase 2 (MK2) signaling complex is physiologically relevant to cellular responses such as the proinflammatory cytokine production. The interaction between p38α isoform and MK2 is of great importance for this signaling. In this study, molecular dynamics simulation and binding free energy calculation were performed on the MK2-p38α signaling complex to investigate the protein-protein interaction between the two proteins. Dynamic domain motion analyses were performed to analyze the conformational changes between the unbound and bound states of proteins during the interaction. The activation loop, αF-I helices, and loops among α helices in the C-lobe of MK2 are found to be highly flexible and exhibit significant changes upon p38α binding. The results also show that after the binding of p38α, the N- and C-terminal domains of MK2 display an opening and twisting motion centered on the activation loop. The molecular mechanics Poisson-Boltzmann and generalized-Born surface area (MM-PB/GBSA) methods were used to calculate binding free energies between MK2 and p38α. The analysis of the components of binding free energy calculation indicates that the van der Waals interaction and the nonpolar solvation energy provide the driving force for the binding process, while the electrostatic interaction contributes critically to the specificity, rather than to MK2-p38α binding affinity. The contribution of each residue at the interaction interface to the binding affinity of MK2 with p38α was also analyzed by free energy decomposition. Several important residues responsible for the protein-protein interaction were also identified.

LDGIdb: a database of gene interactions inferred from long-range strong linkage disequilibrium between pairs of SNPs

Background

Complex human diseases may be associated with many gene interactions. Gene interactions take several different forms and it is difficult to identify all of the interactions that are potentially associated with human diseases. One approach that may fill this knowledge gap is to infer previously unknown gene interactions via identification of non-physical linkages between different mutations (or single nucleotide polymorphisms, SNPs) to avoid hitchhiking effect or lack of recombination. Strong non-physical SNP linkages are considered to be an indication of biological (gene) interactions. These interactions can be physical protein interactions, regulatory interactions, functional compensation/antagonization or many other forms of interactions. Previous studies have shown that mutations in different genes can be linked to the same disorders. Therefore, non-physical SNP linkages, coupled with knowledge of SNP-disease associations may shed more light on the role of gene interactions in human disorders. A user-friendly web resource that integrates information about non-physical SNP linkages, gene annotations, SNP information, and SNP-disease associations may thus be a good reference for biomedical research.

Findings

Here we extracted the SNPs located within the promoter or exonic regions of protein-coding genes from the HapMap database to construct a database named the Linkage-Disequilibrium-based Gene Interaction database (LDGIdb). The database stores 646,203 potential human gene interactions, which are potential interactions inferred from SNP pairs that are subject to long-range strong linkage disequilibrium (LD), or non-physical linkages. To minimize the possibility of hitchhiking, SNP pairs inferred to be non-physically linked were required to be located in different chromosomes or in different LD blocks of the same chromosomes. According to the genomic locations of the involved SNPs (i.e., promoter, untranslated region (UTR) and coding region (CDS)), the SNP linkages inferred were categorized into promoter-promoter, promoter-UTR, promoter-CDS, CDS-CDS, CDS-UTR and UTR-UTR linkages. For the CDS-related linkages, the coding SNPs were further classified into nonsynonymous and synonymous variations, which represent potential gene interactions at the protein and RNA level, respectively. The LDGIdb also incorporates human disease-association databases such as Genome-Wide Association Studies (GWAS) and Online Mendelian Inheritance in Man (OMIM), so that the user can search for potential disease-associated SNP linkages. The inferred SNP linkages are also classified in the context of population stratification to provide a resource for investigating potential population-specific gene interactions.

Conclusion

The LDGIdb is a user-friendly resource that integrates non-physical SNP linkages and SNP-disease associations for studies of gene interactions in human diseases. With the help of the LDGIdb, it is plausible to infer population-specific SNP linkages for more focused studies, an avenue that is potentially important for pharmacogenetics. Moreover, by referring to disease-association information such as the GWAS data, the LDGIdb may help identify previously uncharacterized disease-associated gene interactions and potentially lead to new discoveries in studies of human diseases.

Keywords

Gene interaction, SNP, Linkage disequilibrium, Systems biology, Bioinformatics

Biaryl-bridged macrocyclic peptides: conformational constraint via carbogenic fusion of natural amino acid side chains

A general method for constraining peptide conformations via linkage of aromatic sidechains has been developed. Macrocyclization of suitably functionalized tri-, tetra- and pentapeptides via Suzuki-Miyaura cross-coupling has been used to generate side chain to side chain, biaryl-bridged 14- to 21-membered macrocyclic peptides. Biaryl bridges possessing three different configurations, meta-meta, meta-ortho, and ortho-meta, were systematically explored through regiochemical variation of the aryl halide and aryl boronate coupling partners, allowing fine-tuning of the resultant macrocycle conformation. Suzuki-Miyaura macrocyclizations were successfully achieved both in solution and on solid phase for all three sizes of peptide. This approach constitutes a means of constraining peptide conformation via direct carbogenic fusion of side chains of naturally occurring amino acids such as phenylalanine and tyrosine, and so is complementary to strategies involving non-natural, for example, hydrocarbon, bridges.

Protein-protein interactions and substrate channeling in orthologous and chimeric aldolase-dehydrogenase complexes

Bacterial aldolase-dehydrogenase complexes catalyze the last steps in the meta cleavage pathway of aromatic hydrocarbon degradation. The aldolase (TTHB246) and dehydrogenase (TTHB247) from Thermus thermophilus were separately expressed and purified from recombinant Escherichia coli. The aldolase forms a dimer, while the dehydrogenase is a monomer; these enzymes can form a stable tetrameric complex in vitro, consisting of two aldolase and two dehydrogenase subunits. Upon complex formation, the K(m) value of 4-hydroxy-2-oxopentanoate, the substrate of TTHB246, is decreased 4-fold while the K(m) of acetaldehyde, the substrate of TTHB247, is increased 3-fold. The k(cat) values of each enzyme were reduced by ~2-fold when they were in a complex. The half-life of TTHB247 at 50 °C increased by ~4-fold when it was in a complex with TTHB246. The acetaldehyde product from TTHB246 could be efficiently channelled directly to TTHB247, but the channeling efficiency for the larger propionaldehyde was ~40% lower. A single A324G substitution in TTHB246 increased the channeling efficiency of propionaldehyde to a value comparable to that of acetaldehyde. Stable and catalytically competent chimeric complexes could be formed between the T. thermophilus enzymes and the orthologous aldolase (BphI) and dehydrogenase (BphJ) from the biphenyl degradation pathway of Burkholderia xenovorans LB400. However, channeling efficiencies for acetaldehyde in these chimeric complexes were ~10%. Structural and sequence analysis suggests that interacting residues in the interface of the aldolase-dehydrogenase complex are highly conserved among homologues, but coevolution of partner enzymes is required to fine-tune this interaction to allow for efficient substrate channeling.

Isothermal titration calorimetry in nanoliter droplets with subsecond time constants

We reduced the reaction volume in microfabricated suspended-membrane titration calorimeters to nanoliter droplets and improved the sensitivities to below a nanowatt with time constants of around 100 ms. The device performance was characterized using exothermic acid-base neutralizations and a detailed numerical model. The finite element based numerical model allowed us to determine the sensitivities within 1% and the temporal dynamics of the temperature rise in neutralization reactions as a function of droplet size. The model was used to determine the optimum calorimeter design (membrane size and thickness, junction area, and thermopile thickness) and sensitivities for sample volumes of 1 nL for silicon nitride and polymer membranes. We obtained a maximum sensitivity of 153 pW/(Hz)(1/2) for a 1 μm SiN membrane and 79 pW/(Hz)(1/2) for a 1 μm polymer membrane. The time constant of the calorimeter system was determined experimentally using a pulsed laser to increase the temperature of nanoliter sample volumes. For a 2.5 nanoliter sample volume, we experimentally determined a noise equivalent power of 500 pW/(Hz)(1/2) and a 1/e time constant of 110 ms for a modified commercially available infrared sensor with a thin-film thermopile. Furthermore, we demonstrated detection of 1.4 nJ reaction energies from injection of 25 pL of 1 mM HCl into a 2.5 nL droplet of 1 mM NaOH.