Structural biology and drug discovery for protein-protein interactions

Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.

Prediction and redesign of protein-protein interactions

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.

Memory enhancement by targeting Cdk5 regulation of NR2B

Many psychiatric and neurological disorders are characterized by learning and memory deficits, for which cognitive enhancement is considered a valid treatment strategy. The N-methyl-D-aspartate receptor (NMDAR) is a prime target for the development of cognitive enhancers because of its fundamental role in learning and memory. In particular, the NMDAR subunit NR2B improves synaptic plasticity and memory when overexpressed in neurons. However, NR2B regulation is not well understood and no therapies potentiating NMDAR function have been developed. Here, we show that serine 1116 of NR2B is phosphorylated by cyclin-dependent kinase 5 (Cdk5). Cdk5-dependent NR2B phosphorylation is regulated by neuronal activity and controls the receptor's cell surface expression. Disrupting NR2B-Cdk5 interaction via a small interfering peptide (siP) increases NR2B surface levels, facilitates synaptic transmission, and improves memory formation in vivo. Our results reveal a regulatory mechanism critical to NR2B function that can be targeted for the development of cognitive enhancers.

VIDEO ABSTRACT

Discovery of novel drugs for promising targets

BACKGROUND

Once a promising drug target is identified, the steps to actually discover and optimize a drug are diverse and challenging.

OBJECTIVE

The goal of this study was to provide a road map to navigate drug discovery.

METHODS

Review general steps for drug discovery and provide illustrating references.

RESULTS

A number of approaches are available to enhance and accelerate target identification and validation. Consideration of a variety of potential mechanisms of action of potential drugs can guide discovery efforts. The hit to lead stage may involve techniques such as high-throughput screening, fragment-based screening, and structure-based design, with informatics playing an ever-increasing role. Biologically relevant screening models are discussed, including cell lines, 3-dimensional culture, and in vivo screening. The process of enabling human studies for an investigational drug is also discussed.

CONCLUSIONS

Drug discovery is a complex process that has significantly evolved in recent years.

Oncogenic protein interfaces: small molecules, big challenges

Historically, targeting protein-protein interactions with small molecules was not thought possible because the corresponding interfaces were considered mostly flat and featureless and therefore 'undruggable'. Instead, such interactions were targeted with larger molecules, such as peptides and antibodies. However, the past decade has seen encouraging breakthroughs through the refinement of existing techniques and the development of new ones, together with the identification and exploitation of unexpected aspects of protein-protein interaction surfaces. In this Review, we describe some of the latest techniques to discover modulators of protein-protein interactions and how current drug discovery approaches have been adapted to successfully target these interfaces.

A systems wide mass spectrometric based linear motif screen to identify dominant in-vivo interacting proteins for the ubiquitin ligase MDM2

Linear motifs mediate protein-protein interactions (PPI) that allow expansion of a target protein interactome at a systems level. This study uses a proteomics approach and linear motif sub-stratifications to expand on PPIs of MDM2. MDM2 is a multi-functional protein with over one hundred known binding partners not stratified by hierarchy or function. A new linear motif based on a MDM2 interaction consensus is used to select novel MDM2 interactors based on Nutlin-3 responsiveness in a cell-based proteomics screen. MDM2 binds a subset of peptide motifs corresponding to real proteins with a range of allosteric responses to MDM2 ligands. We validate cyclophilin B as a novel protein with a consensus MDM2 binding motif that is stabilised by Nutlin-3 in vivo, thus identifying one of the few known interactors of MDM2 that is stabilised by Nutlin-3. These data invoke two modes of peptide binding at the MDM2 N-terminus that rely on a consensus core motif to control the equilibrium between MDM2 binding proteins. This approach stratifies MDM2 interacting proteins based on the linear motif feature and provides a new biomarker assay to define clinically relevant Nutlin-3 responsive MDM2 interactors.

Four structural subclasses of the antivirulence drug target disulfide oxidoreductase DsbA provide a platform for design of subclass-specific inhibitors

By catalyzing oxidative protein folding, the bacterial disulfide bond protein A (DsbA) plays an essential role in the assembly of many virulence factors. Predictably, DsbA disruption affects multiple downstream effector molecules, resulting in pleiotropic effects on the virulence of important human pathogens. These findings mark DsbA as a master regulator of virulence, and identify the enzyme as a target for a new class of antivirulence agents that disarm pathogenic bacteria rather than killing them. The purpose of this article is to discuss and expand upon recent findings on DsbA and to provide additional novel insights into the druggability of this important disulfide oxidoreductase by comparing the structures and properties of 13 well-characterized DsbA enzymes. Our structural analysis involved comparison of the overall fold, the surface properties, the conformations of three loops contributing to the binding surface and the sequence identity of residues contributing to these loops. Two distinct structural classes were identified, classes I and II, which are differentiated by their central β-sheet arrangements and which roughly separate the DsbAs produced by Gram-negative from Gram-positive organisms. The classes can be further subdivided into a total of four subclasses on the basis of surface features. Class Ia is equivalent to the Enterobacteriaceae class that has been defined previously. Bioinformatic analyses support the classification of DsbAs into 3 of the 4 subclasses, but did not pick up the 4th subclass which is only apparent from analysis of DsbA electrostatic surface properties. In the context of inhibitor development, the discrete structural subclasses provide a platform for developing DsbA inhibitory scaffolds with a subclass-wide spectrum of activity. We expect that more DsbA classes are likely to be identified, as enzymes from other pathogens are explored, and we highlight the issues associated with structure-based inhibitor development targeting this pivotal mediator of bacterial virulence. This article is part of a Special Issue entitled: Thiol-Based Redox Processes.

Adaptability in protein structures: structural dynamics and implications in ligand design

The basic framework of understanding the mechanisms of protein functions is achieved from the knowledge of their structures which can model the molecular recognition. Recent advancement in the structural biology has revealed that in spite of the availability of the structural data, it is nontrivial to predict the mechanism of the molecular recognition which progresses via situation-dependent structural adaptation. The mutual selectivity of protein-protein and protein-ligand interactions often depends on the modulations of conformations empowered by their inherent flexibility, which in turn regulates the function. The mechanism of a protein's function, which used to be explained by the ideas of 'lock and key' has evolved today as the concept of 'induced fit' as well as the 'population shift' models. It is felt that the 'dynamics' is an essential feature to take into account for understanding the mechanism of protein's function. The design principles of therapeutic molecules suffer from the problems of plasticity of the receptors whose binding conformations are accurately not predictable from the prior knowledge of a template structure. On the other hand, flexibility of the receptors provides the opportunity to improve the binding affinity of a ligand by suitable substitution that will maximize the binding by modulating the receptors surface. In this paper, we discuss with example how the protein's flexibility is correlated with its functions in various systems, revealing the importance of its understanding and for making applications. We also highlight the methodological challenges to investigate it computationally and to account for the flexible nature of the molecules in drug design.

The critical residues of helix 5 for in vitro pentamer formation and stability of the papillomavirus capsid protein, L1

The mono-site mutation of the conserved residues, ⁴⁶⁴LGR⁴⁶⁶, in the helix 5 of HPV16 L1 completely disrupted the pentamer formation.

iPfam: a database of protein family and domain interactions found in the Protein Data Bank

The database iPfam, available at http://ipfam.org, catalogues Pfam domain interactions based on known 3D structures that are found in the Protein Data Bank, providing interaction data at the molecular level. Previously, the iPfam domain–domain interaction data was integrated within the Pfam database and website, but it has now been migrated to a separate database. This allows for independent development, improving data access and giving clearer separation between the protein family and interactions datasets. In addition to domain–domain interactions, iPfam has been expanded to include interaction data for domain bound small molecule ligands. Functional annotations are provided from source databases, supplemented by the incorporation of Wikipedia articles where available. iPfam (version 1.0) contains >9500 domain–domain and 15 500 domain–ligand interactions. The new website provides access to this data in a variety of ways, including interactive visualizations of the interaction data.

Developing epigenetic diagnostics and therapeutics for brain disorders

Perturbations in epigenetic mechanisms have emerged as cardinal features in the molecular pathology of major classes of brain disorders. We therefore highlight evidence which suggests that specific epigenetic signatures measurable in central - and possibly even in peripheral tissues - have significant value as translatable biomarkers for screening, early diagnosis, and prognostication; developing molecularly targeted medicines; and monitoring disease progression and treatment responses. We also draw attention to existing and novel therapeutic approaches directed at epigenetic factors and mechanisms, including strategies for modulating enzymes that write and erase DNA methylation and histone/chromatin marks; protein-protein interactions responsible for reading epigenetic marks; and non-coding RNA pathways.

Inhibitors of difficult protein-protein interactions identified by high-throughput screening of multiprotein complexes

Protein-protein interactions (PPIs) are important in all aspects of cellular function, and there is interest in finding inhibitors of these contacts. However, PPIs with weak affinities and/or large interfaces have traditionally been more resistant to the discovery of inhibitors, partly because it is more challenging to develop high-throughput screening (HTS) methods that permit direct measurements of these physical interactions. Here, we explored whether the functional consequences of a weak PPI might be used as a surrogate for binding. As a model, we used the bacterial ATPase DnaK and its partners DnaJ and GrpE. Both DnaJ and GrpE bind DnaK and catalytically accelerate its ATP cycling, so we used stimulated nucleotide turnover to indirectly report on these PPIs. In pilot screens, we identified compounds that block activation of DnaK by either DnaJ or GrpE. Interestingly, at least one of these molecules blocked binding of DnaK to DnaJ, while another compound disrupted allostery between DnaK and GrpE without altering the physical interaction. These findings suggest that the activity of a reconstituted multiprotein complex might be used in some cases to identify allosteric inhibitors of challenging PPIs.

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.

Development of a fluorescent monoclonal antibody-based assay to measure the allosteric effects of synthetic peptides on self-oligomerization of AGR2 protein

Many regulatory proteins are homo-oligomeric and designing assays that measure self-assembly will provide novel approaches to study protein allostery and screen for novel small molecule modulators of protein interactions. We present an assay to begin to define the biochemical determinants that regulate dimerization of the cancer-associated oncoprotein AGR2. A two site-sandwich microtiter assay ((2S) MTA) was designed using a DyLight800-labeled monoclonal antibody that binds to an epitope in AGR2 to screen for synthetic self-peptides that might regulate dimer stability. Peptides derived from the intrinsically disordered N-terminal region of AGR2 increase in trans oligomer stability as defined using the (2S) MTA assay. A DSS-crosslinking assay that traps the AGR2 dimer through K95-K95 adducts confirmed that Δ45-AGR2 was a more stable dimer using denaturing gel electrophoresis. A titration of wt-AGR2, Δ45-AGR2 (more stable dimer), and monomeric AGR2(E60A) revealed that Δ45-AGR2 was more active in binding to Reptin than either wt-AGR2 or the AGR2(E60A) mutant. Our data have defined a functional role for the AGR2 dimer in the binding to its most well characterized interacting protein, Reptin. The ability to regulate AGR2 oligomerization in trans opens the possibility for developing small molecules that regulate its' biochemical activity as potential cancer therapeutics. The data also highlight the utility of this oligomerization assay to screen chemical libraries for ligands that could regulate AGR2 dimer stability and its' oncogenic potential.

Scoring functions for protein-protein interactions

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning.

iPPI-DB: a manually curated and interactive database of small non-peptide inhibitors of protein-protein interactions

The development of small molecule drugs targeting protein-protein interactions (PPI) represents a major challenge, in part owing to the misunderstanding of the PPI chemical space. To this end, we have manually collected the structures, the physicochemical and pharmacological profiles of 1650 PPI inhibitors across 13 families of PPI targets in a database named iPPI-DB. To access iPPI-DB, we propose a user-friendly web application (www.ippidb.cdithem.fr) with customizable queries and intuitive visualizing functionalities for associated properties of the compounds. This could assist scientists to design the next generation of PPI drugs. In this review, we describe iPPI-DB in the context of other low molecular weight molecule databases.

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

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

The regulation of vascular tetrahydrobiopterin bioavailability

6R l-erythro-5,6,7,8-tetrahydrobiopterin (BH4) is an essential cofactor for several enzymes including phenylalanine hydroxylase and the nitric oxide synthases (NOS). Oral supplementation of BH4 has been successfully employed to treat subsets of patients with hyperphenylalaninaemia. More recently, research efforts have focussed on understanding whether BH4 supplementation may also be efficacious in cardiovascular disorders that are underpinned by reduced nitric oxide bioavailability. Whilst numerous preclinical and clinical studies have demonstrated a positive association between enhanced BH4 and vascular function, the efficacy of orally administered BH4 in human cardiovascular disease remains unclear. Furthermore, interventions that limit BH4 bioavailability may provide benefit in diseases where nitric oxide over production contributes to pathology. This review describes the pathways involved in BH4 bio-regulation and discusses other endogenous mechanisms that could be harnessed therapeutically to manipulate vascular BH4 levels.

Oligomerization of rab/effector complexes in the regulation of vesicle trafficking

Rabs comprise the largest member of the Ras superfamily of small GTPases with over 60 proteins in mammals and 11 proteins in yeast. Like all small GTPases, Rabs oscillate between an inactive GDP-bound conformation and an active GTP-bound state that is tethered to lipid membranes via a C-terminal prenylation site on conserved cysteine residues. In their active state, Rabs regulate various aspects of membrane trafficking, including vesicle formation, transport, docking, and fusion. The critical element of biological activity is the recruitment of cytosolic effector proteins to specific endomembranes by active Rabs. The importance of Rabs in cellular processes is apparent from their links to genetic disorders, immunodeficiency, cancer, and pathogen invasion. During the last decade, numerous structures of complexes have shed light on the molecular basis for Rab/effector specificity and their topological organization on subcellular membranes. Here, I review the known structures of Rab/effector complexes and their modes of oligomerization. This is followed by a brief discussion on the thermodynamics of effector recruitment, which has not been documented sufficiently in previous reviews. A summary of diseases associated with Rab/effector trafficking pathways concludes this chapter.

On the binding affinity of macromolecular interactions: daring to ask why proteins interact

Interactions between proteins are orchestrated in a precise and time-dependent manner, underlying cellular function. The binding affinity, defined as the strength of these interactions, is translated into physico-chemical terms in the dissociation constant (K_d), the latter being an experimental measure that determines whether an interaction will be formed in solution or not. Predicting binding affinity from structural models has been a matter of active research for more than 40 years because of its fundamental role in drug development. However, all available approaches are incapable of predicting the binding affinity of protein–protein complexes from coordinates alone. Here, we examine both theoretical and experimental limitations that complicate the derivation of structure–affinity relationships. Most work so far has concentrated on binary interactions. Systems of increased complexity are far from being understood. The main physico-chemical measure that relates to binding affinity is the buried surface area, but it does not hold for flexible complexes. For the latter, there must be a significant entropic contribution that will have to be approximated in the future. We foresee that any theoretical modelling of these interactions will have to follow an integrative approach considering the biology, chemistry and physics that underlie protein–protein recognition.

Physiology and pathophysiology of the blood-brain barrier: P-glycoprotein and occludin trafficking as therapeutic targets to optimize central nervous system drug delivery

The blood-brain barrier (BBB) is a physical and metabolic barrier that separates the central nervous system from the peripheral circulation. Central nervous system drug delivery across the BBB is challenging, primarily because of the physical restriction of paracellular diffusion between the endothelial cells that comprise the microvessels of the BBB and the activity of efflux transporters that quickly expel back into the capillary lumen a wide variety of xenobiotics. Therapeutic manipulation of protein trafficking is emerging as a novel means of modulating protein function, and in this minireview, the targeting of the trafficking of 2 key BBB proteins, P-glycoprotein and occludin, is presented as a novel, reversible means of optimizing central nervous system drug delivery.

Pocket-based drug design: exploring pocket space

The identification and application of druggable pockets of targets play a key role in in silico drug design, which is a fundamental step in structure-based drug design. Herein, some recent progresses and developments of the computational analysis of pockets have been covered. Also, the pockets at the protein-protein interfaces (PPI) have been considered to further explore the pocket space for drug discovery. We have presented two case studies targeting the kinetic pockets generated by normal mode analysis and molecular dynamics method, respectively, in which we focus upon incorporating the pocket flexibility into the two-dimensional virtual screening with both affinity and specificity. We applied the specificity and affinity (SPA) score to quantitatively estimate affinity and evaluate specificity using the intrinsic specificity ratio (ISR) as a quantitative criterion. In one of two cases, we also included some applications of pockets located at the dimer interfaces to emphasize the role of PPI in drug discovery. This review will attempt to summarize the current status of this pocket issue and will present some prospective avenues of further inquiry.

Biophysical and computational fragment-based approaches to targeting protein-protein interactions: applications in structure-guided drug discovery

Drug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein-protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Nevertheless, encouragement has come from the recognition that a few amino acids - so-called hotspots - may contribute the majority of interaction-free energy. The challenges posed by protein-protein interactions have led to a wellspring of creative approaches, including proteomimetics, stapled α-helical peptides and a plethora of antibody inspired molecular designs. Here, we review a more generic approach: fragment-based drug discovery. Fragments allow novel areas of chemical space to be explored more efficiently, but the initial hits have low affinity. This means that they will not normally disrupt PPIs, unless they are tethered, an approach that has been pioneered by Wells and co-workers. An alternative fragment-based approach is to stabilise the uncomplexed components of the multiprotein system in solution and employ conventional fragment-based screening. Here, we describe the current knowledge of the structures and properties of protein-protein interactions and the small molecules that can modulate them. We then describe the use of sensitive biophysical methods - nuclear magnetic resonance, X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry or isothermal calorimetry - to screen and validate fragment binding. Fragment hits can subsequently be evolved into larger molecules with higher affinity and potency. These may provide new leads for drug candidates that target protein-protein interactions and have therapeutic value.

Features of protein-protein interactions that translate into potent inhibitors: topology, surface area and affinity

Protein-protein interactions (PPIs) control the assembly of multi-protein complexes and, thus, these contacts have enormous potential as drug targets. However, the field has produced a mix of both exciting success stories and frustrating challenges. Here, we review known examples and explore how the physical features of a PPI, such as its affinity, hotspots, off-rates, buried surface area and topology, might influence the chances of success in finding inhibitors. This analysis suggests that concise, tight binding PPIs are most amenable to inhibition. However, it is also clear that emerging technical methods are expanding the repertoire of 'druggable' protein contacts and increasing the odds against difficult targets. In particular, natural product-like compound libraries, high throughput screens specifically designed for PPIs and approaches that favour discovery of allosteric inhibitors appear to be attractive routes. The first group of PPI inhibitors has entered clinical trials, further motivating the need to understand the challenges and opportunities in pursuing these types of targets.