Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

Polymeric microspheres as protein transduction reagents

Discovering the function of an unknown protein, particularly one with neither structural nor functional correlates, is a daunting task. Interaction analyses determine binding partners, whereas DNA transfection, either transient or stable, leads to intracellular expression, though not necessarily at physiologically relevant levels. In theory, direct intracellular protein delivery (protein transduction) provides a conceptually simpler alternative, but in practice the approach is problematic. Domains such as HIV TAT protein are valuable, but their effectiveness is protein specific. Similarly, the delivery of intact proteins via endocytic pathways (e.g. using liposomes) is problematic for functional analysis because of the potential for protein degradation in the endosomes/lysosomes. Consequently, recent reports that microspheres can deliver bio-cargoes into cells via a non-endocytic, energy-independent pathway offer an exciting and promising alternative for in vitro delivery of functional protein. In order for such promise to be fully exploited, microspheres are required that (i) are stably linked to proteins, (ii) can deliver those proteins with good efficiency, (iii) release functional protein once inside the cells, and (iv) permit concomitant tracking. Herein, we report the application of microspheres to successfully address all of these criteria simultaneously, for the first time. After cellular uptake, protein release was autocatalyzed by the reducing cytoplasmic environment. Outside of cells, the covalent microsphere-protein linkage was stable for ≥90 h at 37°C. Using conservative methods of estimation, 74.3% ± 5.6% of cells were shown to take up these microspheres after 24 h of incubation, with the whole process of delivery and intracellular protein release occurring within 36 h. Intended for in vitro functional protein research, this approach will enable study of the consequences of protein delivery at physiologically relevant levels, without recourse to nucleic acids, and offers a useful alternative to commercial protein transfection reagents such as Chariot™. We also provide clear immunostaining evidence to resolve residual controversy surrounding FACS-based assessment of microsphere uptake. © 2014 by The American Society for Biochemistry and Molecular Biology Inc.

Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide:can the α3 and β2m domains be neglected?

Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histo-compatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVY-DGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide–MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the α1–α2 domain, the α3 and β2m domains cannot be neglected. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1803–1813, 2004

A proteo-liposome system for the analysis of the intracellular interactome of membrane proteins using amyloid precursor protein as a model

Transmembrane proteins play crucial roles in many important physiological processes. The intracellular domain of membrane proteins is key for their function by interacting with a wide variety of cytosolic proteins. It is therefore important to examine this interaction. A recently developed method to study these interactions, based on the use of liposomes as a model membrane, involves the covalent coupling of the cytoplasmic domains of membrane proteins to the liposome membrane. This allows for the analysis of interaction partners requiring both protein and membrane lipid binding. This thesis further establishes the liposome recruitment system and utilises it to examine the intracellular interactome of the amyloid precursor protein (APP), most well-known for its proteolytic cleavage that results in the production and accumulation of amyloid beta fragments, the main constituent of amyloid plaques in Alzheimer’s disease pathology. Despite this, the physiological function of APP remains largely unclear. Through the use of the proteo-liposome recruitment system two novel interactions of APP’s intracellular domain (AICD) are examined with a view to gaining a greater insight into APP’s physiological function. One of these novel interactions is between AICD and the mTOR complex, a serine/threonine protein kinase that integrates signals from nutrients and growth factors. The kinase domain of mTOR directly binds to AICD and the N-terminal amino acids of AICD are crucial for this interaction. The second novel interaction is between AICD and the endosomal PIKfyve complex, a lipid kinase involved in the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2) from phosphatidylinositol-3-phosphate, which has a role in controlling ensdosome dynamics. The scaffold protein Vac14 of the PIKfyve complex binds directly to AICD and the C-terminus of AICD is important for its interaction with the PIKfyve complex. Using a recently developed intracellular PI(3,5)P2 probe it is shown that APP controls the formation of PI(3,5)P2 positive vesicular structures and that the PIKfyve complex is involved in the trafficking and degradation of APP. Both of these novel APP interactors have important implications of both APP function and Alzheimer’s disease. The proteo-liposome recruitment method is further validated through its use to examine the recruitment and assembly of the AP-2/clathrin coat from purified components to two membrane proteins containing different sorting motifs. Taken together this thesis highlights the proteo-liposome recruitment system as a valuable tool for the study of membrane proteins intracellular interactome. It allows for the mimicking of the protein in its native configuration therefore identifying weaker interactions that are not detected by more conventional methods and also detecting interactions that are mediated by membrane phospholipids.

Receptor activity-modifying proteins; multifunctional G protein-coupled receptor accessory proteins

Receptor activity-modifying proteins (RAMPs) are single pass membrane proteins initially identified by their ability to determine the pharmacology of the calcitonin receptor-like receptor (CLR), a family B G protein-coupled receptor (GPCR). It is now known that RAMPs can interact with a much wider range of GPCRs. This review considers recent developments on the structure of the complexes formed between the extracellular domains (ECDs) of CLR and RAMP1 or RAMP2 as these provide insights as to how the RAMPs direct ligand binding. The range of RAMP interactions is also considered; RAMPs can interact with numerous family B GPCRs as well as examples of family A and family C GPCRs. They influence receptor expression at the cell surface, trafficking, ligand binding and G protein coupling. The GPCR-RAMP interface offers opportunities for drug targeting, illustrated by examples of drugs developed for migraine.