Assessment and significance of protein–protein interactions during development of protein biopharmaceuticals

Early development of protein biotherapeutics using recombinant DNA technology involved progress in the areas of cloning, screening, expression and recovery/purification. As the biotechnology industry matured, resulting in marketed products, a greater emphasis was placed on development of formulations and delivery systems requiring a better understanding of the chemical and physical properties of newly developed protein drugs. Biophysical techniques such as analytical ultracentrifugation, dynamic and static light scattering, and circular dichroism were used to study protein–protein interactions during various stages of development of protein therapeutics. These studies included investigation of protein self-association in many of the early development projects including analysis of highly glycosylated proteins expressed in mammalian CHO cell cultures. Assessment of protein–protein interactions during development of an IgG1 monoclonal antibody that binds to IgE were important in understanding the pharmacokinetics and dosing for this important biotherapeutic used to treat severe allergic IgE-mediated asthma. These studies were extended to the investigation of monoclonal antibody–antigen interactions in human serum using the fluorescent detection system of the analytical ultracentrifuge. Analysis by sedimentation velocity analytical ultracentrifugation was also used to investigate competitive binding to monoclonal antibody targets. Recent development of high concentration protein formulations for subcutaneous administration of therapeutics posed challenges, which resulted in the use of dynamic and static light scattering, and preparative analytical ultracentrifugation to understand the self-association and rheological properties of concentrated monoclonal antibody solutions.     

PCS-based structure determination of protein–protein complexes

A simple and fast nuclear magnetic resonance method for docking proteins using pseudo-contact shift (PCS) and ¹H^N/¹⁵N chemical shift perturbation is presented. PCS is induced by a paramagnetic lanthanide ion that is attached to a target protein using a lanthanide binding peptide tag anchored at two points. PCS provides long-range (~40 Å) distance and angular restraints between the lanthanide ion and the observed nuclei, while the ¹H^N/¹⁵N chemical shift perturbation data provide loose contact-surface information. The usefulness of this method was demonstrated through the structure determination of the p62 PB1-PB1 complex, which forms a front-to-back 20 kDa homo-oligomer. As p62 PB1 does not intrinsically bind metal ions, the lanthanide binding peptide tag was attached to one subunit of the dimer at two anchoring points. Each monomer was treated as a rigid body and was docked based on the backbone PCS and backbone chemical shift perturbation data. Unlike NOE-based structural determination, this method only requires resonance assignments of the backbone ¹H^N/¹⁵N signals and the PCS data obtained from several sets of two-dimensional ¹⁵N-heteronuclear single quantum coherence spectra, thus facilitating rapid structure determination of the protein–protein complex.     

Two-hybrid-based analysis of protein–protein interactions of the yeast multidrug resistance protein, Pdr5p

The ATP-binding cassette (ABC) transporters are a large family of proteins responsible for the translocation of a variety of compounds across the membranes of both prokaryotes and eukaryotes. The inter-protein and intra-protein interactions in these traffic ATPases are still only poorly understood. In the present study we describe, for the first time, an extensive yeast two-hybrid (Y2H)-based analysis of the interactions of the cytoplasmic loops of the yeast pleiotropic drug resistance (Pdr) protein, Pdr5p, an ABC transporter of Saccharomyces cerevisiae. Four of the major cytosolic loops that have been predicted for this protein [including the two nucleotide-binding domain (NBD)-containing loops and the cytosolic C-terminal region] were subjected to an extensive inter-domain interaction study in addition to being used as baits to identify potential interacting proteins within the cell using the Y2H system. Results of these studies have revealed that the first cytosolic loop (CL1) – containing the first NBD domain – and also the C-terminal region of Pdr5p interact with several candidate proteins. The possibility of an interaction between the CL1 loops of two neighboring Pdr5p molecules was also indicated, which could possibly have implications for dimerization of this protein. Electronic Publication     

Simulation of protein diffusion: a sensitive probe of protein–solvent interactions

Aqueous solutions of Candida antarctica lipase B (CALB) were simulated considering three different water models (SPC/E, TIP3P, TIP4P) by a series of molecular dynamics (MD) simulations of three different box sizes (L = 9, 14, and 19 nm) to determine the diffusion coefficient, the water viscosity and the protein density. The protein–water systems were equilibrated for 500 ns, followed by 100 ns production runs which were analysed. The diffusional properties of CALB were characterized by the Stokes radius (R_S), which was derived from the diffusion coefficient and the viscosity. R_S was compared to the geometric radius (R_G) of CALB, which was derived from the protein density. R_S and R_G differed by 0.27 nm for SPC/E and by 0.40 and 0.39 nm for TIP3P and TIP4P, respectively, which characterizes the thickness of the diffusive hydration layer on the protein surface. The simulated hydration layer of CALB resulted in agreement with those experimentally determined for other seven different proteins of comparable size. By avoiding the most common pitfalls, protein diffusion can be reliably simulated: simulating different box sizes to account for the finite size effect, equilibrating the protein–water system sufficiently, and using the complete production run for the determination of the diffusion coefficient.     

Peptides and peptidomimetics as regulators of protein–protein interactions

1. Download : Download high-res image (114KB)
2. Download : Download full-size image

     

SH3 domains: modules of protein–protein interactions

Src homology 3 (SH3) domains are involved in the regulation of important cellular pathways, such as cell proliferation, migration and cytoskeletal modifications. Recognition of polyproline and a number of noncanonical sequences by SH3 domains has been extensively studied by crystallography, nuclear magnetic resonance and other methods. High-affinity peptides that bind SH3 domains are used in drug development as candidates for anticancer treatment. This review summarizes the latest achievements in deciphering structural determinants of SH3 function.     

Alternative modulation of protein–protein interactions by small molecules

1. Download : Download high-res image (97KB)
2. Download : Download full-size image

     

Automated feature engineering improves prediction of protein–protein interactions

Amino Acids - Over the last decade, various machine learning (ML) and statistical approaches for protein–protein interaction (PPI) predictions have been developed to help annotating...     

Structural basis of protein–protein interaction studied by NMR

This paper describes efforts of the structural genomics project in the nuclear magnetic resonance (NMR) laboratory at the University of Science and Technology of China. This structural genomics project is biological-functional driven. Targets are mainly selected from two systems: proteins related with regulation of gene expression in humans and other eukaryotes, and proteins existing in the cell junction in humans. The majority of proteins selected from these two systems are related with human health and diseases, and some are potential drug targets. Twenty-five protein structures from Homo sapiens and other eukaryotes have been determined during last 5 years in this laboratory. Nuclear magnetic resonance (NMR) spectroscopy is highly suited to investigate molecular interactions at a close physiological condition and is particularly suited for the study of low-affinity, transient complexes. It can provide information on protein surface interaction, their complex structure, and their dynamic properties during protein recognition. Several examples are given in this paper.     

The influence of protein coding sequences on protein folding rates of all-β proteins

It is currently believed that the protein folding rate is related to the protein structures and its amino acid sequence. However, few studies have been done on the problem that whether the protein folding rate is influenced by its corresponding mRNA sequence. In this paper, we analyzed the possible relationship between the protein folding rates and the corresponding mRNA sequences. The content of guanine and cytosine (GC content) of palindromes in protein coding sequence was introduced as a new parameter and added in the Gromiha's model of predicting protein folding rates to inspect its effect in protein folding process. The multiple linear regression analysis and jack-knife test show that the new parameter is significant. The linear correlation coefficient between the experimental and the predicted values of the protein folding rates increased significantly from 0.96 to 0.99, and the population variance decreased from 0.50 to 0.24 compared with Gromiha's results. The results show that the GC content of palindromes in the corresponding protein coding sequence really influences the protein folding rate. Further analysis indicates that this kind of effect mostly comes from the synonymous codon usage and from the information of palindrome structure itself, but not from the translation information from codons to amino acids.     

Comparative mapping of host–pathogen protein–protein interactions

1. Download : Download high-res image (177KB)
2. Download : Download full-size image

     

Functional dissection of an intrinsically disordered protein: Understanding the roles of different domains of Knr4 protein in protein�Cprotein interactions

Knr4, recently characterized as an intrinsically disordered Saccharomyces cerevisiae protein, participates in cell wall formation and cell cycle regulation. It is constituted of a functional central globular core flanked by a poorly structured N‐terminal and large natively unfolded C‐terminal domains. Up to now, about 30 different proteins have been reported to physically interact with Knr4. Here, we used an in vivo two‐hybrid system approach and an in vitro surface plasmon resonance (BIAcore) technique to compare the interaction level of different Knr4 deletion variants with given protein partners. We demonstrate the indispensability of the N‐terminal domain of Knr4 for the interactions. On the other hand, presence of the unstructured C‐terminal domain has a negative effect on the interaction strength. In protein interactions networks, the most highly connected proteins or “hubs” are significantly enriched in unstructured regions, and among them the transient hub proteins contain the largest and most highly flexible regions. The results presented here of our analysis of Knr4 protein suggest that these large disordered regions are not always involved in promoting the protein–protein interactions of hub proteins, but in some cases, might rather inhibit them. We propose that this type of regions could prevent unspecific protein interactions, or ensure the correct timing of occurrence of transient interactions, which may be of crucial importance for different signaling and regulation processes.