Targeting Protein-protein Interactions Research Articles

Targeting Unoccupied Surfaces on Protein-Protein Interfaces.

The use of peptidomimetic scaffolds to target protein-protein interfaces is a promising strategy for inhibitor design. The strategy relies on mimicry of protein motifs that exhibit a concentration of native hot spot residues. To address this constraint, we present a pocket-centric computational design strategy guided by AlphaSpace to identify high-quality pockets near the peptidomimetic motif that are both targetable and unoccupied. Alpha-clusters serve as a spatial representation of pocket space and are used to guide the selection of natural and non-natural amino acid mutations to design inhibitors that optimize pocket occupation across the interface. We tested the strategy against a challenging protein-protein interaction target, KIX/MLL, by optimizing a single helical motif within MLL to compete against the full-length wild-type MLL sequence. Molecular dynamics simulation and experimental fluorescence polarization assays are used to verify the efficacy of the optimized peptide sequence.

Bicyclic Peptides as Next-Generation Therapeutics.

Bicyclic peptides have greater conformational rigidity and metabolic stability than linear and monocyclic peptides and are capable of binding to challenging drug targets with antibody-like affinity and specificity. Powerful combinatorial library technologies have recently been developed to rapidly synthesize and screen large bicyclic peptide libraries for ligands against enzymes, receptors, and protein-protein interaction targets. Bicyclic peptides have been developed as potential therapeutics against a wide range of diseases, drug targeting agents, imaging/diagnostic probes, and research tools. In this Minireview, we provide a summary of the recent progresses on the synthesis and applications of bicyclic peptides.

Potential Strategies to Target Protein-Protein Interactions in the DNA Damage Response and Repair Pathways.

This review article discusses some insights about generating novel mechanistic inhibitors of the DNA damage response and repair (DDR) pathways by focusing on protein-protein interactions (PPIs) of the key DDR components. General requirements for PPI strategies, such as selecting the target PPI site on the basis of its functionality, are discussed first. Next, on the basis of functional rationale and biochemical feasibility to identify a PPI inhibitor, 26 PPIs in DDR pathways (BER, MMR, NER, NHEJ, HR, TLS, and ICL repair) are specifically discussed for inhibitor discovery to benefit cancer therapies using a DNA-damaging agent.

QSAR modeling and in silico design of small-molecule inhibitors targeting the interaction between E3 ligase VHL and HIF-1α.

Protein-protein interactions (PPIs) have attracted much attention recently because of their preponderant role in most biological processes. The prevention of the interaction between E3 ligase VHL and HIF-1[Formula: see text] may improve tolerance to hypoxia and ameliorate the prognosis of many diseases. To obtain novel potent inhibitors of VHL/HIF-1[Formula: see text] interaction, a series of hydroxyproline-based inhibitors were investigated for structural optimization using a combination of QSAR modeling and molecular docking. Here, 2D- and 3D-QSAR models were developed by genetic function approximation (GFA) and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods, respectively. The top-ranked models with strict validation revealed satisfactory statistical parameters (CoMFA with [Formula: see text], 0.637; [Formula: see text], 0.955; [Formula: see text], 0.944; CoMSIA with [Formula: see text], 0.649; [Formula: see text], 0.954; [Formula: see text], 0.911; GFA with [Formula: see text], 0.721; [Formula: see text], 0.801; [Formula: see text], 0.861). The selected five 2D-QSAR descriptors were in good accordance with the 3D-QSAR results, and contour maps gave the visualization of feature requirements for inhibitory activity. A new diverse molecular database was created by molecular fragment replacement and BREED techniques for subsequent virtual screening. Eventually, 31 novel hydroxyproline derivatives stood out as potential VHL/HIF-1[Formula: see text] inhibitors with favorable predictions by the CoMFA, CoMSIA and GFA models. The reliability of this protocol suggests that it could also be applied to the exploration of lead optimization of other PPI targets.

Protein Domain Mimics as Modulators of Protein-Protein Interactions.

Protein-protein interactions (PPIs) are ubiquitous in biological systems and often misregulated in disease. As such, specific PPI modulators are desirable to unravel complex PPI pathways and expand the number of druggable targets available for therapeutic intervention. However, the large size and relative flatness of PPI interfaces make them challenging molecular targets. This Account describes our systematic approach using secondary and tertiary protein domain mimics (PDMs) to specifically modulate PPIs. Our strategy focuses on mimicry of regular secondary and tertiary structure elements from one of the PPI partners to inspire rational PDM design. We have compiled three databases (HIPPDB, SIPPDB, and DIPPDB) of secondary and tertiary structures at PPI interfaces to guide our designs and better understand the energetics of PPI secondary and tertiary structures. Our efforts have focused on three of the most common secondary and tertiary structures: α-helices, β-strands, and helix dimers (e.g., coiled coils). To mimic α-helices, we designed the hydrogen bond surrogate (HBS) as an isosteric PDM and the oligooxopiperazine helix mimetic (OHM) as a topographical PDM. The nucleus of the HBS approach is a peptide macrocycle in which the N-terminal i, i + 4 main-chain hydrogen bond is replaced with a covalent carbon-carbon bond. In mimicking a main-chain hydrogen bond, the HBS approach stabilizes the α-helical conformation while leaving all helical faces available for functionalization to tune binding affinity and specificity. The OHM approach, in contrast, envisions a tetrapeptide to mimic one face of a two-turn helix. We anticipated that placement of ethylene bridges between adjacent amides constrains the tetrapeptide backbone to mimic the i, i + 4, and i + 7 side chains on one face of an α-helix. For β-strands, we developed triazolamers, a topographical PDM where the peptide bonds are replaced by triazoles. The triazoles simultaneously stabilize the extended, zigzag conformation of β-strands and transform an otherwise ideal protease substrate into a stable molecule by replacement of the peptide bonds. We turned to a salt bridge surrogate (SBS) approach as a means for stabilizing very short helix dimers. As with the HBS approach, the SBS strategy replaces a noncovalent interaction with a covalent bond. Specifically, we used a bis-triazole linkage that mimics a salt bridge interaction to drive helix association and folding. Using this approach, we were able to stabilize helix dimers that are less than half of the length required to form a coiled coil from two independent strands. In addition to demonstrating the stabilization of desired structures, we have also shown that our designed PDMs specifically modulate target PPIs in vitro and in vivo. Examples of PPIs successfully targeted include HIF1α/p300, p53/MDM2, Bcl-xL/Bak, Ras/Sos, and HIV gp41. The PPI databases and designed PDMs created in these studies will aid development of a versatile set of molecules to probe complex PPI functions and, potentially, PPI-based therapeutics.

Annotating function to differentially expressed LincRNAs in myelodysplastic syndrome using a network-based method.

Long non-coding RNAs (lncRNAs) have been implicated in the regulation of diverse biological functions. The number of newly identified lncRNAs has increased dramatically in recent years but their expression and function have not yet been described from most diseases. To elucidate lncRNA function in human disease, we have developed a novel network based method (NLCFA) integrating correlations between lncRNA, protein coding genes and noncoding miRNAs. We have also integrated target gene associations and protein-protein interactions and designed our model to provide information on the combined influence of mRNAs, lncRNAs and miRNAs on cellular signal transduction networks. We have generated lncRNA expression profiles from the CD34+ haematopoietic stem and progenitor cells (HSPCs) from patients with Myelodysplastic syndromes (MDS) and healthy donors. We report, for the first time, aberrantly expressed lncRNAs in MDS and further prioritize biologically relevant lncRNAs using the NLCFA. Taken together, our data suggests that aberrant levels of specific lncRNAs are intimately involved in network modules that control multiple cancer-associated signalling pathways and cellular processes. Importantly, our method can be applied to prioritize aberrantly expressed lncRNAs for functional validation in other diseases and biological contexts. The method is implemented in R language and Matlab. xizhou@wakehealth.edu. Supplementary data are available at Bioinformatics online.

Salivary miR-16, miR-191 and miR-223: intuitive indicators of dominant ovarian follicles in buffaloes.

Estrus or sexual receptivity determination is utmost important for efficient breeding programs for female buffaloes. Prominent estrus behavioral symptoms are the result of several molecular and neuroendocrine events involving the ovary and the brain. Expression of estrus behavior is poor in buffaloes during the summer season. Hence, the discovery of biomarkers specific to the estrus stage or its related ovarian events, like the presence of dominant ovarian follicle, is helpful for developing an easy estrus determination method. MicroRNA are small non-coding RNA with a potential to be biomarkers. Therefore, the present study targeted to investigate the potential of estrogen responsive miRNAs (miR-24, miR-200c, miR-16, miR-191, miR-223 and miR-203) as estrus biomarkers in buffalo saliva, a non-invasive fluid representing animals' pathophysiology. There was a significant (P<0.05) increase in the salivary presence of the miR-16, miR-191 and miR-223 at 6th and 18th-19th days than the 0day (estrus), 10th day and the following consecutive estrus day. These observations may indicate an association between the representative lower presence of these miRNA in saliva and the presence of dominant ovarian follicles. To test this association, pathway analysis, target gene identification, functional annotation and protein-protein interaction networks (PPI) were performed for miR-16, miR-191 and miR-223 by different bioinformatics tools. Interestingly, the top pathways (fatty acid biosynthesis and oocyte meiosis), target genes (FGF, BDNF and IGF1) and PPI hub genes (KRAS, BCL2 and IGF1) of these miRNAs were found essential for ovarian follicular dominance. In conclusion, the miR-16, miR-191 and miR-223 may not be the perfect estrus stage-specific biomarkers. However, their lower presence in saliva at estrus and 9th-10th day of estrous cycles, when the ovary usually has a dominant follicle in buffaloes, may intuitively indicate the follicular dominance. Further studies are needed to prove this association in a large population.

Ultrasensitive Scaffold-Dependent Protease Sensors with Large Dynamic Range

The rational construction of synthetic protein switches with predefined input-output parameters constitutes a key goal of synthetic biology with many potential applications ranging from metabolic engineering to diagnostics. Yet, generally applicable strategies to construct tailor-engineered protein switches have so far remained elusive. Here, we use SpyTag/SpyCatcher-mediated protein ligation to engineer modularly organized, scaffold-dependent protease sensors that exploit a combination of affinity targeting and protease-inducible protein-protein interactions. We use this architecture to create a suite of integrated signal sensing and amplification circuits that can detect the activity of α-thrombin and prostate specific antigen with a dynamic range covering 5 orders of magnitude. We determine the key design features critical for signal transmission between protease-based sensors, transducers, and actuators.

The OncoPPi network of cancer-focused protein\u2013protein interactions to inform biological insights and therapeutic strategies

As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein–protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes. PPI hubs reveal new regulatory mechanisms for cancer genes like MYC, STK11, RASSF1 and CDK4. As example, the NSD3 (WHSC1L1)–MYC interaction suggests a new mechanism for NSD3/BRD4 chromatin complex regulation of MYC-driven tumours. Association of undruggable tumour suppressors with drug targets informs therapeutic options. Based on OncoPPi-derived STK11-CDK4 connectivity, we observe enhanced sensitivity of STK11-silenced lung cancer cells to the FDA-approved CDK4 inhibitor palbociclib. OncoPPi is a focused PPI resource that links cancer genes into a signalling network for discovery of PPI targets and network-implicated tumour vulnerabilities for therapeutic interrogation.

Computational design of an epitope-specific Keap1 binding antibody using hotspot residues grafting and CDR loop swapping

Therapeutic and diagnostic applications of monoclonal antibodies often require careful selection of binders that recognize specific epitopes on the target molecule to exert a desired modulation of biological function. Here we present a proof-of-concept application for the rational design of an epitope-specific antibody binding with the target protein Keap1, by grafting pre-defined structural interaction patterns from the native binding partner protein, Nrf2, onto geometrically matched positions of a set of antibody scaffolds. The designed antibodies bind to Keap1 and block the Keap1-Nrf2 interaction in an epitope-specific way. One resulting antibody is further optimised to achieve low-nanomolar binding affinity by in silico redesign of the CDRH3 sequences. An X-ray co-crystal structure of one resulting design reveals that the actual binding orientation and interface with Keap1 is very close to the design model, despite an unexpected CDRH3 tilt and VH/VL interface deviation, which indicates that the modelling precision may be improved by taking into account simultaneous CDR loops conformation and VH/VL orientation optimisation upon antibody sequence change. Our study confirms that, given a pre-existing crystal structure of the target protein-protein interaction, hotspots grafting with CDR loop swapping is an attractive route to the rational design of an antibody targeting a pre-selected epitope.

Inhibition of the Ras/Raf interaction and repression of renal cancer xenografts in vivo by an enantiomeric iridium(iii) metal-based compound.

Targeting protein-protein interactions (PPIs) offers tantalizing opportunities for therapeutic intervention for the treatment of human diseases. Modulating PPI interfaces with organic small molecules has been found to be exceptionally challenging, and few candidates have been successfully developed into clinical drugs. Meanwhile, the striking array of distinctive properties exhibited by metal compounds renders them attractive scaffolds for the development of bioactive leads. Here, we report the identification of iridium(iii) compounds as inhibitors of the H-Ras/Raf-1 PPI. The lead iridium(iii) compound 1 exhibited potent inhibitory activity against the H-Ras/Raf-1 interaction and its signaling pathway in vitro and in vivo, and also directly engaged both H-Ras and Raf-1-RBD in cell lysates. Moreover, 1 repressed tumor growth in a mouse renal xenograft tumor model. Intriguingly, the Δ-enantiomer of 1 showed superior potency in the biological assays compared to Λ-1 or racemic 1. These compounds could potentially be used as starting scaffolds for the development of more potent Ras/Raf PPI inhibitors for the treatment of kidney cancer or other proliferative diseases.

Abstract A28: Differentially expressed microRNA profiles in pancreatic ductal and ampullary adenocarcinomas

Abstract Background: Pancreatic cancer is associated with 6.9% and 4% of all cancer-related deaths in the United States and Brazil, respectively. Pancreatic ductal carcinoma comprises 90% of cases, the majority being of adenocarcinoma subtype. Approximately 12% of periampullary tumors are adenocarcinomas of Vater papilla (ampullary adenocarcinomas); ampullary tumors are often associated with a better prognosis than ductal adenocarcinomas. Although genetic alterations were previously identified in pancreatic carcinomas, there is still a lack of effective treatment strategies. Therefore, the identification of new biomarkers, such as alterations in non-coding RNAs, is urgently needed for the development of novel molecularly targeted therapies for these cancers. microRNAs (miRNAs) are frequently deregulated and contribute to cancer development and progression and have potential prognostic and predictive value. Global miRNA expression profiling analysis in pancreatic cancer, followed by the identification of miRNA target genes may lead to the identification of clinically applicable biomarkers. The novel aspect of our work is the investigation of pancreatic tumors from Brazilian patients, with the inclusion of ampullary adenocarcinomas, a rare subtype. Objectives: To identify global miRNA expression profiles and miRNA target genes in pancreatic ductal and ampullary adenocarcinomas compared to paired histologically normal pancreatic tissue. Patients and Methods: 30 formalin fixed, paraffin embedded (FFPE) pancreatic carcinoma samples were used, including 24 pancreatic ductal adenocarcinomas (PDAC) and 6 ampullary adenocarcinomas (AMP). Paired histologically normal pancreatic tissues were used as controls. All tumor and normal tissues were needle microdissected (Leica EZ4 stereomicroscope). Global miRNA expression profiles were determined using the TaqMan Array Human MicroRNA Cards (TLDA) (card A, v3.0) (Life Technologies) platform. Data analysis was performed using the ExpressionSuite Software v1.0.3. Statistical analysis was performed to correlate miRNA expression with relevant clinical data, using SAS 9.3 software. Computational bioinformatics analysis was performed to identify miRNA target genes, as well as to construct protein-protein interaction and miRNA-gene targets networks. Results and Discussion: We identified 63 significantly deregulated (FC≥2 and p&amp;lt;0.05) miRNAs in PDAC (33 over- and 30 under-expressed) compared to paired histologically normal pancreatic tissue. In AMP, a group of 7 miRNAs was significantly deregulated (4 over- and 3 under-expressed) compared to normal pancreas. Our results showed differentially expressed miRNAs and a complexity of miRNA changes potentially associated to PDAC and AMP tumorigenesis. 3/7 miRNAs (miR-222, 148a and 375) were commonly deregulated in PDAC and AMP tumors. Furthermore, miRNA-gene targets networks were distinct in these different histological subtypes of pancreatic carcinomas. Global miRNA expression profiles showed that PDAC have a significantly higher number of altered miRNAs and a higher number of predicted miRNA target genes than AMP tumors, which could be potentially associated to disease progression and tumor aggressiveness in PDAC compared to AMP. Although these tumors have biological differences, commonly deregulated miRNAs in PDAC and AMP suggest that PDAC and AMP tumorigenesis may share commonly deregulated pathways. Conclusion: miRNAs identified herein may be associated to the biology of PDAC and AMP. Among the miRNAs exclusively deregulated in PDAC, we identified known and not previously reported (novel) miRNAs. In addition, we identified several miRNA target genes associated with tumor invasion, metastasis and poor patient prognosis. Functional in vitro and in vivo validation studies may elucidate the role of identified miRNAs as modulators of oncogenesis mechanisms in PDAC and AMP. T. Felix was funded through São Paulo Research Foundation (FAPESP), MSc. fellowship (2014/00367-4) Citation Format: Tainara F. Felix, Tomas Tokar, Maria A. M. Rodrigues, Rogerio A. Oliveira, Claudia N. Hasimoto, Juan C. Llanos, Robson F. Carvalho, Silvia R. Rogatto, Wan Lam, Igor Jurisica, Sandra A. Drigo, Patricia P. Reis.{Authors}. Differentially expressed microRNA profiles in pancreatic ductal and ampullary adenocarcinomas. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr A28.

Harnessing benefit from targeting tumor associated carbohydrate antigens

ABSTRACTIntegrating additive or synergistic antitumor effects that focus on distinct elements of tumor biology are the most rational strategies for cancer treatment. Treatments for breast cancer have increased overall survival, but remain limited by lack of efficacy in a subset of breast cancer patients. The real challenge is to define what elements of tumor biology make the most sense to be integrated. An emerging strategy is to consider a systems biology approach to impact multiple interactions in networks as compare with hitting a specific protein-protein interaction target. In this review, we consider how targeting tumor associated carbohydrate antigens (TACA) that are fundamental to signal pathways might be tailored to harness benefit from combination therapy of sustained immunity with chemotherapy. An approach we are developing makes use of a carbohydrate mimetic peptide (CMP) to induce polyspecific antibodies, which by their nature have numerous on and off target effects. Linking multi-target TACA recognition with mechanisms affecting tumor growth in the context of network heterogeneity and concepts of immune surveillance to tumor cells and the type of breast cancer patients that would benefit from such an approach provides a novel integrative treatment.

Structural quality of unrefined models in protein docking.

Structural characterization of protein-protein interactions is essential for understanding life processes at the molecular level. However, only a fraction of protein interactions have experimentally resolved structures. Thus, reliable computational methods for structural modeling of protein interactions (protein docking) are important for generating such structures and understanding the principles of protein recognition. Template-based docking techniques that utilize structural similarity between target protein-protein interaction and cocrystallized protein-protein complexes (templates) are gaining popularity due to generally higher reliability than that of the template-free docking. However, the template-based approach lacks explicit penalties for intermolecular penetration, as opposed to the typical free docking where such penalty is inherent due to the shape complementarity paradigm. Thus, template-based docking models are commonly assumed to require special treatment to remove large structural penetrations. In this study, we compared clashes in the template-based and free docking of the same proteins, with crystallographically determined and modeled structures. The results show that for the less accurate protein models, free docking produces fewer clashes than the template-based approach. However, contrary to the common expectation, in acceptable and better quality docking models of unbound crystallographically determined proteins, the clashes in the template-based docking are comparable to those in the free docking, due to the overall higher quality of the template-based docking predictions. This suggests that the free docking refinement protocols can in principle be applied to the template-based docking predictions as well. Proteins 2016; 85:39-45. © 2016 Wiley Periodicals, Inc.

Inhibition of Mcl-1 through covalent modification of a noncatalytic lysine side chain.

Targeted covalent inhibition of disease-associated proteins has become a powerful methodology in the field of drug discovery, leading to the approval of new therapeutics. Nevertheless, current approaches are often limited owing to their reliance on a cysteine residue to generate the covalent linkage. Here we used aryl boronic acid carbonyl warheads to covalently target a noncatalytic lysine side chain, and generated to our knowledge the first reversible covalent inhibitors for Mcl-1, a protein-protein interaction (PPI) target that has proven difficult to inhibit via traditional medicinal chemistry strategies. These covalent binders exhibited improved potency in comparison to noncovalent congeners, as demonstrated in biochemical and cell-based assays. We identified Lys234 as the residue involved in covalent modification, via point mutation. The covalent binders discovered in this study will serve as useful starting points for the development of Mcl-1 therapeutics and probes to interrogate Mcl-1-dependent biological phenomena.

Probing the Small-Molecule Inhibition of an Anticancer Therapeutic Protein-Protein Interaction Using a Solid-State Nanopore

Targeting protein–protein interactions (PPIs) for therapeutic interventions has been an attractive strategy in drug discovery. Because drug development for enzyme targets has been limited by the difficulties in achieving sufficient specificity, PPI inhibitors with extremely high specificity have recently attracted considerable attention. Despite advances in various techniques, such as nuclear magnetic resonance (NMR), surface plasma resonance (SPR), and fluorescence polarization (FP), the high-throughput screening (HTS) of small-molecule PPI inhibitors is highly challenging owing to several critical limitations: i) the large amount (mg quantities) of sample required for NMR; ii) the low sensitivity of SPR for detection of small-molecule binding to proteins; and iii) the requirement for fluorophore labeling in FP. Hence, there is a need to develop a robust HTS methodology to facilitate the discovery of small molecule drugs against PPI targets. Nanopore sensors have several unique advantages compared with more conventional techniques, including single-molecule resolution and ultrasensitivity, label-free and real-time measurements, and high-throughput detection. Although nanopores have been used to characterize the biophysical properties of diverse biomolecules, including DNA, RNA, and proteins, they have never been applied to the screening of small-molecule drugs such as PPI inhibitors. Blocking the interaction between mouse double minute 2 (MDM2) and p53 transactivation domain (p53TAD) has been an attractive strategy for cancer therapy because it can restore p53 function, resulting in cancer cell apoptosis. Using this therapeutic strategy, many p53TAD-mimetic lead compounds have been identified for cancer treatment. Among them, Nutlin-3 is one of the most potent MDM2 antagonists and acts as a competitive inhibitor of the MDM2/p53TAD interaction (Kd=0.1 μM). Nutlin-3 structurally mimics the 15-residue a-helical p53TAD peptide that binds to MDM2 (Kd=0.6μM). To probe the MDM2/p53TAD interaction and its small molecule inhibition using solid-state nanopores, we fabricated ~10–15 nm-sized nanopores in low-pressure chemical vapor deposition (LPCVD) SiNx membranes transferred to the Pyrex substrates. The structure of the N-terminal p53TAD binding domain of MDM2 (PDB code: 1YCR) showed dimensions of 3.1 nm × 3.5 nm × 4.2 nm. At the applied voltage of -175 mV across the nanopore, the positively charged MDM2 domain (residues 3–109, MW=12.3 kDa, net charge at pH 7.4=+2.9e, pI=9.02) was electrophoretically driven from one chamber toward the negative electrode in the other chamber. The passage of MDM2 through the nanopore gave rise to a temporary reduction in the ionic current, leading to the detection of MDM2 translocation events at the single-molecule level. In contrast to the vigorous translocation of free MDM2, the number of translocation events for the MDM2/GST-p53TAD complex through the nanopore was dramatically reduced to a negligible level. Upon complex formation, the net charge of the proteins at pH 7.4 changes from +2.9e (in free MDM2) to -13.7e (in the MDM2/GST-p53TAD complex) owing to charge masking of MDM2 by negatively charged GST-p53TAD. As a result, the overall negatively charged protein complex could not translocate through the nanopore at the applied negative voltage. We measured the nanopore translocation of the MDM2/GST-p53TAD complex in the presence of Nutlin-3. After the addition of Nutlin-3 to the protein complex, the translocation of free MDM2 was almost recovered, which indicated that the disruption of the MDM2/GST-p53TAD interaction by Nutlin-3 liberated MDM2 from the GST-p53TAD-bound complex. To test whether the MDM2/GST-p53TAD interaction is indeed specifically inhibited by Nutlin-3, we repeated the nanopore experiment with a negative control, ABT-737, which is an inhibitor of Bcl-2 family proteins and does not bind to MDM2. Unlike Nutlin-3, ABT-737 could not recover the translocation of MDM2, confirming that Nutlin-3 specifically blocked the interaction between MDM2 and GST-p53TAD. We believe that this nanopore-based drug screening platform will provide a remarkable improvement over current technological limitations in drug discovery at protein-protein interfaces.

Process of Fragment-Based Lead Discovery-A Perspective from NMR.

Fragment-based lead discovery (FBLD) has proven fruitful during the past two decades for a variety of targets, even challenging protein–protein interaction (PPI) systems. Nuclear magnetic resonance (NMR) spectroscopy plays a vital role, from initial fragment-based screening to lead generation, because of its power to probe the intrinsically weak interactions between targets and low-molecular-weight fragments. Here, we review the NMR FBLD process from initial library construction to lead generation. We describe technical aspects regarding fragment library design, ligand- and protein-observed screening, and protein–ligand structure model generation. For weak binders, the initial hit-to-lead evolution can be guided by structural information retrieved from NMR spectroscopy, including chemical shift perturbation, transferred pseudocontact shifts, and paramagnetic relaxation enhancement. This perspective examines structure-guided optimization from weak fragment screening hits to potent leads for challenging PPI targets.

A novel small-molecule PPI inhibitor targeting integrin αvβ3-osteopontin interface blocks bone resorption in vitro and prevents bone loss in mice

Small molecule-inhibition targeting protein-protein interaction (PPI) is now recognized as an emerging and challenging area in drug design. We developed a novel interactive drug discovery methodology known as Protein Chip technology (ProteoChip) as a cutting-edge PPI assay system applicable for unique PPI-targeting therapeutics integrated with computer-aided drug design (CADD). Here, we describe a novel small molecular PPI inhibitor, IPS-02001, which the blocks integrin αvβ3-osteopontin interface a novel PPI inhibitor identified by the interactive methodology of both ProteoChip- and CADD-based PPI assay. IPS-02001 (6,7-Dichloro-2,3,5,8-tetrahydroxy-1,4-naphthoquinone) was screened from different compound libraries (InterBioScreen, Commercial libraries) using an in silico structure-based molecular docking simulation method and a protein chip-based protein-protein interaction assay system. Additionally, integrin αvβ3, an adhesion receptor expressed in osteoclasts (OCs), was implicated in the regulation of OC function via regulation of the cytoskeletal organization of OCs. IPS-02001 blocked OC maturation from murine bone marrow-derived macrophages, as well as the resorptive function of OCs. Moreover, treatment with IPS-02001 impaired downstream signaling of integrin αvβ3 linked to Pyk2, c-Src, PLCγ2, and Vav3 and disrupted the actin cytoskeleton in mature OCs. Furthermore, IPS-02001 blocked RANKL-induced bone destruction by reducing the number of OCs and protected against ovariectomy-induced bone loss in mice. Thus, IPS-02001 may represent a promising new class of anti-resorptive drugs for treatment of bone diseases associated with increased OC function.

Small molecules, big targets: drug discovery faces the protein-protein interaction challenge.

Protein-protein interactions (PPIs) are of pivotal importance in the regulation of biological systems and are consequently implicated in the development of disease states. Recent work has begun to show that, with the right tools, certain classes of PPI can yield to the efforts of medicinal chemists to develop inhibitors, and the first PPI inhibitors have reached clinical development. In this Review, we describe the research leading to these breakthroughs and highlight the existence of groups of structurally related PPIs within the PPI target class. For each of these groups, we use examples of successful discovery efforts to illustrate the research strategies that have proved most useful.

Probing the Small-Molecule Inhibition of an Anticancer Therapeutic Protein-Protein Interaction Using a Solid-State Nanopore.

Nanopore sensing is an emerging technology for the single-molecule-based detection of various biomolecules. In this study, we probed the anticancer therapeutic p53 transactivation domain (p53TAD)/MDM2 interaction and its inhibition with a small-molecule MDM2 antagonist, Nutlin-3, using low-noise solid-state nanopores. Although the translocation of positively charged MDM2 through a nanopore was detected at the applied negative voltage, this MDM2 translocation was almost completely blocked upon formation of the MDM2/GST-p53TAD complex owing to charge conversion. In combination with NMR data, the nanopore measurements showed that the addition of Nutlin-3 rescued MDM2 translocation, indicating that Nutlin-3 disrupted the MDM2/GST-p53TAD complex, thereby releasing MDM2. Taken together, our results reveal that solid-state nanopores can be a valuable platform for the ultrasensitive, picomole-scale screening of small-molecule drugs against protein-protein interaction (PPI) targets.