Protein-protein interactions as targets for small-molecule therapeutics in cancer

Targeting the protein-protein interaction between IRS1 and mutant p110α for cancer therapy

Phosphoinositide-3-kinase, catalytic, alpha polypeptide, which encodes the catalytic p110α subunit of phosphatidylinositol 3-kinase α, is the most frequently mutated oncogene in human cancers. Targeting mutant p110α holds great promise for cancer therapy. However, it is challenging to develop p110α isoform-specific inhibitors. Most p110α mutations occur at two hot spot regions: an acidic cluster (E542, E545, and Q546) in the helical domain and a histidine residue (H1047) in the kinase domain. We recently discovered that p110α helical domain mutant proteins, but not the kinase domain mutant proteins, directly associate with insulin receptor substrate 1 (IRS1). Moreover, we demonstrated that disruption of protein-protein interaction between p110α helical domain mutant and IRS1 inhibits the growth of tumors with such mutations. The direct protein interaction between IRS1 and p110α helical domain mutants may provide a more accessible target for developing novel precision cancer therapy.

Identifying chemicals with potential therapy of HIV based on protein-protein and protein-chemical interaction network

Acquired immune deficiency syndrome (AIDS) is a severe infectious disease that causes a large number of deaths every year. Traditional anti-AIDS drugs directly targeting the HIV-1 encoded enzymes including reverse transcriptase (RT), protease (PR) and integrase (IN) usually suffer from drug resistance after a period of treatment and serious side effects. In recent years, the emergence of numerous useful information of protein-protein interactions (PPI) in the HIV life cycle and related inhibitors makes PPI a new way for antiviral drug intervention. In this study, we identified 26 core human proteins involved in PPI between HIV-1 and host, that have great potential for HIV therapy. In addition, 280 chemicals that interact with three HIV drugs targeting human proteins can also interact with these 26 core proteins. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying novel anti-HIV drugs.

Gain of interaction with IRS1 by p110α-helical domain mutants is crucial for their oncogenic functions

PIK3CA, which encodes the p110α catalytic subunit of phosphatidylinositol 3-kinase α, is frequently mutated in human cancers. Most of these mutations occur at two hot-spots: E545K and H1047R located in the helical domain and the kinase domain, respectively. Here, we report that p110α E545K, but not p110α H1047R, gains the ability to associate with IRS1 independent of the p85 regulatory subunit, thereby rewiring this oncogenic signaling pathway. Disruption of the IRS1-p110α E545K interaction destabilizes the p110α protein, reduces AKT phosphorylation, and slows xenograft tumor growth of a cancer cell line expressing p110α E545K. Moreover, a hydrocarbon-stapled peptide that disrupts this interaction inhibits the growth of tumors expressing p110α E545K.

Structural insights into inhibition of the bivalent menin-MLL interaction by small molecules in leukemia

Menin functions as a critical oncogenic cofactor of mixed lineage leukemia (MLL) fusion proteins in the development of acute leukemias, and inhibition of the menin interaction with MLL fusion proteins represents a very promising strategy to reverse their oncogenic activity. MLL interacts with menin in a bivalent mode involving 2 N-terminal fragments of MLL. In the present study, we reveal the first high-resolution crystal structure of human menin in complex with a small-molecule inhibitor of the menin-MLL interaction, MI-2. The structure shows that the compound binds to the MLL pocket in menin and mimics the key interactions of MLL with menin. Based on the menin-MI-2 structure, we developed MI-2-2, a compound that binds to menin with low nanomolar affinity (K(d) = 22nM) and very effectively disrupts the bivalent protein-protein interaction between menin and MLL. MI-2-2 demonstrated specific and very pronounced activity in MLL leukemia cells, including inhibition of cell proliferation, down-regulation of Hoxa9 expression, and differentiation. Our results provide the rational and essential structural basis to design next generation of inhibitors for effective targeting of the menin-MLL interaction in leukemia and demonstrate a proof of concept that inhibition of complex multivalent protein-protein interactions can be achieved by a small-molecule inhibitor.

Computational prediction of protein hot spot residues

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.

Expanding the conformational selection paradigm in protein-ligand docking

Conformational selection emerges as a theme in macromolecular interactions. Data validate it as a prevailing mechanism in protein-protein, protein-DNA, protein-RNA, and protein-small molecule drug recognition. This raises the question of whether this fundamental biomolecular binding mechanism can be used to improve drug docking and discovery. Actually, in practice this has already been taking place for some years in increasing numbers. Essentially, it argues for using not a single conformer, but an ensemble. The paradigm of conformational selection holds that because the ensemble is heterogeneous, within it there will be states whose conformation matches that of the ligand. Even if the population of this state is low, since it is favorable for binding the ligand, it will bind to it with a subsequent population shift toward this conformer. Here we suggest expanding it by first modeling all protein interactions in the cell by using Prism, an efficient motif-based protein-protein interaction modeling strategy, followed by ensemble generation. Such a strategy could be particularly useful for signaling proteins, which are major targets in drug discovery and bind multiple partners through a shared binding site, each with some-minor or major-conformational change.

Chemical modulators working at pharmacological interface of target proteins

For last few decades, the active site cleft and substrate-binding site of enzymes as well as ligand-binding site of the receptors have served as the main pharmacological space for drug discovery. However, rapid accumulation of proteome and protein network analysis data has opened a new therapeutic space that is the interface between the interacting proteins. Due to the complexity of the interaction modes and the numbers of the participating components, it is still challenging to identify the chemicals that can accurately control the protein-protein interactions at desire. Nonetheless, the number of chemical drugs and candidates working at the interface of the interacting proteins are rapidly increasing. This review addresses the current case studies and state-of-the-arts in the development of small chemical modulators controlling the interactions of the proteins that have pathological implications in various human diseases such as cancer, immune disorders, neurodegenerative and infectious diseases.

On target? Strategies and progress in the development of therapies for colorectal cancer targeted against WNT signalling

Chemotherapy is an integral part of treatment for colorectal cancer (CRC), especially in the context of metastatic cancer. Targeted therapies in the form of monoclonal antibodies directed against the endothelial growth factor receptor or the vascular endothelial growth factor have met with success, and have demonstrated the advantages of molecularly targeted therapy in colorectal cancer. Nevertheless, CRC remains a major cause of death, which demonstrates the urgent need for improved treatment strategies. The pathway activated by the Wingless-type mouse mammary tumour virus integration site (WNT) family members is constitutively active and promotes cancer growth in the majority of CRCs. As a result, there has been interest in developing therapeutics that circumvent it either by inhibiting WNT-mediated transcription or by inactivating the target genes. This review considers the current therapies approved for use in CRC and discusses the progress with therapies designed to target the WNT signalling pathway.

Computational alanine scanning with linear scaling semiempirical quantum mechanical methods

Alanine scanning is a powerful experimental tool for understanding the key interactions in protein-protein interfaces. Linear scaling semiempirical quantum mechanical calculations are now sufficiently fast and robust to allow meaningful calculations on large systems such as proteins, RNA and DNA. In particular, they have proven useful in understanding protein-ligand interactions. Here we ask the question: can these linear scaling quantum mechanical methods developed for protein-ligand scoring be useful for computational alanine scanning? To answer this question, we assembled 15 protein-protein complexes with available crystal structures and sufficient alanine scanning data. In all, the data set contains Delta Delta Gs for 400 single point alanine mutations of these 15 complexes. We show that with only one adjusted parameter the quantum mechanics-based methods outperform both buried accessible surface area and a potential of mean force and compare favorably to a variety of published empirical methods. Finally, we closely examined the outliers in the data set and discuss some of the challenges that arise from this examination.

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing

BACKGROUND

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.

METHODOLOGY

In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.

CONCLUSIONS

The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

ANCHOR: a web server and database for analysis of protein-protein interaction binding pockets for drug discovery

ANCHOR is a web-based tool whose aim is to facilitate the analysis of protein–protein interfaces with regard to its suitability for small molecule drug design. To this end, ANCHOR exploits the so-called anchor residues, i.e. amino acid side-chains deeply buried at protein–protein interfaces, to indicate possible druggable pockets to be targeted by small molecules. For a given protein–protein complex submitted by the user, ANCHOR calculates the change in solvent accessible surface area (ΔSASA) upon binding for each side-chain, along with an estimate of its contribution to the binding free energy. A Jmol-based tool allows the user to interactively visualize selected anchor residues in their pockets as well as the stereochemical properties of the surrounding region such as hydrogen bonding. ANCHOR includes a Protein Data Bank (PDB) wide database of pre-computed anchor residues from more than 30 000 PDB entries with at least two protein chains. The user can query according to amino acids, buried area (SASA), energy or keywords related to indication areas, e.g. oncogene or diabetes. This database provides a resource to rapidly assess protein–protein interactions for the suitability of small molecules or fragments with bioisostere anchor analogues as possible compounds for pharmaceutical intervention. ANCHOR web server and database are freely available at http://structure.pitt.edu/anchor.

Systematic prediction of human membrane receptor interactions

Membrane receptor-activated signal transduction pathways are integral to cellular functions and disease mechanisms in humans. Identification of the full set of proteins interacting with membrane receptors by high-throughput experimental means is difficult because methods to directly identify protein interactions are largely not applicable to membrane proteins. Unlike prior approaches that attempted to predict the global human interactome, we used a computational strategy that only focused on discovering the interacting partners of human membrane receptors leading to improved results for these proteins. We predict specific interactions based on statistical integration of biological data containing highly informative direct and indirect evidences together with feedback from experts. The predicted membrane receptor interactome provides a system-wide view, and generates new biological hypotheses regarding interactions between membrane receptors and other proteins. We have experimentally validated a number of these interactions. The results suggest that a framework of systematically integrating computational predictions, global analyses, biological experimentation and expert feedback is a feasible strategy to study the human membrane receptor interactome.

Homology Modelling of Human E1 Ubiquitin Activating Enzyme

Human E1 is a key player in protein ubiquitination, however the E1 structure is not available. In this paper, we describe the derivation of a human E1 structure using molecular modelling based on the crystal structure of S. cerevisiae E1 and M. Musculus E1. Key interactions between our E1 model and ubiquitin are also discussed.

The FRS2 family of docking/scaffolding adaptor proteins as therapeutic targets of cancer treatment

BACKGROUND

There are two members--FRS2alpha and FRS2beta--in the fibroblast growth factor receptor substrate 2 (FRS2) family of docking/scaffolding adaptor proteins. These proteins function downstream of certain kinds of receptor tyrosine kinases (RTKs) that are important for tumorigenesis. FRS2alpha acts as a control centre for fibroblast growth factor receptor signalling and encourages tumorigenesis, while FRS2beta regulates EGFR signalling negatively, and might have a tumour suppressive role. Therefore, both proteins could be good therapeutic targets for the treatment of cancer.

OBJECTIVE

To examine the physiological and pathological roles of FRS2, especially in cancer, and describe their potential value as therapeutic targets.

METHODS

A review of relevant literature.

RESULTS/CONCLUSIONS

Although it is still difficult to develop small compounds to modify functions of FRS2 adaptor proteins, such compounds may be useful as the next generation of molecular targeting drugs. Combination therapy with RTK-targeting drugs and FRS2-targeting drugs may be useful for cancer treatment in the near future.

Increasingly accurate dynamic molecular models of G-protein coupled receptor oligomers: Panacea or Pandora's box for novel drug discovery?

For years, conventional drug design at G-protein coupled receptors (GPCRs) has mainly focused on the inhibition of a single receptor at a usually well-defined ligand-binding site. The recent discovery of more and more physiologically relevant GPCR dimers/oligomers suggests that selectively targeting these complexes or designing small molecules that inhibit receptor-receptor interactions might provide new opportunities for novel drug discovery. To uncover the fundamental mechanisms and dynamics governing GPCR dimerization/oligomerization, it is crucial to understand the dynamic process of receptor-receptor association, and to identify regions that are suitable for selective drug binding. This minireview highlights current progress in the development of increasingly accurate dynamic molecular models of GPCR oligomers based on structural, biochemical, and biophysical information that has recently appeared in the literature. In view of this new information, there has never been a more exciting time for computational research into GPCRs than at present. Information-driven modern molecular models of GPCR complexes are expected to efficiently guide the rational design of GPCR oligomer-specific drugs, possibly allowing researchers to reach for the high-hanging fruits in GPCR drug discovery, i.e. more potent and selective drugs for efficient therapeutic interventions.

CCAAT/enhancer-binding protein beta: its role in breast cancer and associations with receptor tyrosine kinases

The CCAAT/enhancer-binding proteins (C/EBPs) are a family of leucine-zipper transcription factors that regulate gene expression to control cellular proliferation, differentiation, inflammation and metabolism. Encoded by an intronless gene, C/EBPbeta is expressed as several distinct protein isoforms (LAP1, LAP2, LIP) whose expression is regulated by the differential use of several in-frame translation start sites. LAP1 and LAP2 are transcriptional activators and are associated with differentiation, whereas LIP is frequently elevated in proliferative tissue and acts as a dominant-negative inhibitor of transcription. However, emerging evidence suggests that LIP can serve as a transcriptional activator in some cellular contexts, and that LAP1 and LAP2 might also have unique actions. The LIP:LAP ratio is crucial for the maintenance of normal growth and development, and increases in this ratio lead to aggressive forms of breast cancer. This review discusses the regulation of C/EBPbeta activity by post-translational modification, the individual actions of LAP1, LAP2 and LIP, and the functions and downstream targets that are unique to each isoform. The role of the C/EBPbeta isoforms in breast cancer is discussed and emphasis is placed on their interactions with receptor tyrosine kinases.