Identifying specificity profiles for peptide recognition modules from phage-displayed peptide libraries

Signaling complexes usually involve multidomain proteins containing catalytic domains and peptide recognition modules (PRMs), which mediate protein-protein interactions and assemble complexes by binding to ligands containing a core sequence motif. Concomitant to large-scale physical interaction screening, considerable effort has been devoted toward the elucidation of consensus profiles for common PRMs. We describe herein a robust and proven protocol to generate consensus profiles for PRMs using phage-displayed peptide libraries. The initial phase of the protocol entails the cloning, expression and purification of PRMs as fusion proteins, in addition to the construction of highly diverse phage-displayed peptide libraries. The affinity selection process described thereafter enables a single researcher to efficiently probe the recognition profiles of numerous PRMs in a 1 week time period.     

MHC Class I/peptide interactions: Binding specificity and kinetics

Recent developments in the preparation of soluble analogues of the major histocompatibility complex (MHC) class l molecules as well as in the applications of real time biosensor technology have permitted the direct analysis of the binding of MHC class l molecules to antigenic peptides. Using synthetic peptide analogues with cysteine substitutions at appropriate positions, peptides can be immobilized on a dextran-modified gold biosensor surface with a specific spatial orientation. A full set of such substituted peptides (known as ‘pepsicles’, as they are peptides on a stick) representing antigenic or self peptides can be used in the functional mapping of the MHC class l peptide binding site. Scans of sets of peptide analogues reveal that some amino acid side chains of the peptide are critical to stable binding to the MHC molecule, while others are not. This is consistent with functional experiments using substituted peptides and three-dimensional molecular models of MHC/peptide complexes. Details analysis of the kinetic dissociation rates (k_d) of the MHC molecules from the specifically coupled solid phase peptides revels that the stability of the complex is a function of the particular peptide, its coupling position, and the MHC molecule. Measured k_d values for antigenic peptide/class I interactions at 25°C are in the range of ca 10^?4–10^?6/s. Biosensor methodology for the analysis of the binding of MHC class I molecules to solid-phase peptides using real time surface plasmon resonance offers a rational approach to the general analysis of protein/peptide interactions.     

Molecular basis for recognition of an arthritic peptide and a foreign epitope on distinct MHC molecules by a single TCR

KRN TCR transgenic T cells recognize two self-MHC molecules: a foreign peptide, bovine RNase 42-56, on I-Ak and an autoantigen, glucose-6-phosphate isomerase 282-294, on I-Ag7. Because the latter recognition event initiates a disease closely resembling human rheumatoid arthritis, we investigated the structural basis of this pathogenic TCR's dual specificity. While peptide recognition is altered to a minor degree between the MHC molecules, we show that the receptor's cross-reactivity critically depends upon a TCR contact residue completely conserved in the foreign and self peptides. Further, the altered recognition of peptide derives from discrete differences on the MHC recognition surfaces and not the disparate binding grooves. This work provides a detailed structural comparison of an autoreactive TCR's interactions with naturally occurring peptides on distinct MHC molecules. The capacity to interact with multiple self-MHCs in this manner increases the number of potentially pathogenic self-interactions available to a T cell.     

Assisted peptide folding by surface pattern recognition

Natively disordered proteins belong to a unique class of biomolecules whose function is related to their flexibility and their ability to adopt desired conformations upon binding to substrates. In some cases these proteins can bind multiple partners, which can lead to distinct structures and promiscuity in functions. In other words, the capacity to recognize molecular patterns on the substrate is often essential for the folding and function of intrinsically disordered proteins. Biomolecular pattern recognition is extremely relevant both in vivo (e.g., for oligomerization, immune response, induced folding, substrate binding, and molecular switches) and in vitro (e.g., for biosensing, catalysis, chromatography, and implantation). Here, we use a minimalist computational model system to investigate how polar/nonpolar patterns on a surface can induce the folding of an otherwise unstructured peptide. We show that a model peptide that exists in the bulk as a molten globular state consisting of many interconverting structures can fold into either a helix-coil-helix or an extended helix structure in the presence of a complementary designed patterned surface at low hydrophobicity (3.7%) or a uniform surface at high hydrophobicity (50%). However, we find that a carefully chosen surface pattern can bind to and catalyze the folding of a natively unfolded protein much more readily or effectively than a surface with a noncomplementary or uniform distribution of hydrophobic residues.     

Predicting amino acid residues responsible for enzyme specificity solely from protein sequences

We describe a general, modular method for developing protocols to identify the amino acid residues that most likely define the division of a protein superfamily into two subsets. As one possibility, we use PROBE to gather superfamily members and perform an ungapped alignment. We then use a modified BLOSUM62 substitution matrix to determine the discriminating power of each column of aligned residues. The overall method is particularly useful for predicting amino acids responsible for substrate or binding specificity when no structures are available. We apply our method to three pairs of protein classes in three different superfamilies, and present our results, some of which have been experimentally verified. This approach may accelerate the elucidation of enzymic substrate specificity, which is critical for both mechanistic insights into biocatalysis and ultimate application.     

On the specificity of cytochrome c synthetase in recognition of the amino acid sequence of apocytochrome c

Two forms of yeast cytochrome c synthetases with different specificities were resolved, one (synthetase I), solubilized from mitochondria or the cell debris with Triton X-100, recognizing not horse apocytochrome c but yeast apo-iso-1-cytochrome c as a substrate and the other (synthetase II) still bound with the particulate fraction from mitochondria after treatment with Triton, recognizing both horse and yeast apocytochromes c. The activity with labeled yeast apo-iso-1-cytochrome c as a substrate of cytochrome c synthetase I can be quantitatively inhibited by nonlabeled Candida krusei apocytochrome c and partially by nonlabeled tuna apocytochrome c but not by nonlabeled horse apocytochrome c indicating a specific amino acid sequence being recognized. However, an enzyme similarly solubilized from beef heart mitochondria recognized both horse apocytochrome c and yeast apo-iso-1-cytochrome c for attachment of heme. In view of the fact that the yeast synthetase II and the beef synthetase can both utilize either horse apocytochrome c or yeast apo-iso-1-cytochrome c as substrates, we suggest that these enzymes may also be involved in biosynthesis of cytochrome c1, that is, the ability to attach heme to apocytochrome c and apocytochrome c1 may have been conserved in eucaryotic cells, and that both synthetases may therefore be homologous.     

Switching DNA-binding specificity by unnatural amino acid substitution

The specificity of protein–nucleic acid recognition is believed to originate largely from hydrogen bonding between protein polar atoms, primarily side-chain and polar atoms of nucleic acid bases. One way to design new nucleic acid binding proteins of novel specificity is by structure-guided alterations of the hydrogen bonding patterns of a nucleic acid–protein complex. We have used cI repressor of bacteriophage λ as a model system. In the λ-repressor–DNA complex, the -NH₂ group (hydrogen bond donor) of lysine-4 of λ-repressor forms hydrogen bonds with the amide carbonyl atom of asparagine-55 (acceptor) and the O6 (acceptor) of CG6 of operator site O_L1. Substitution of lysine-4 (two donors) by iso-steric S-(2-hydroxyethyl)-cysteine (one donor and one acceptor), by site-directed mutagenesis and chemical modification, leads to switch of binding specificity of λ-repressor from C:G to T:A at position 6 of O_L1. This suggests that unnatural amino acid substitutions could be a simple way of generating nucleic acid binding proteins of altered specificity.     

T cell receptor binding transition states and recognition of peptide/MHC

T cell receptor recognition of peptide/MHC has been described as proceeding through a "two-step" process in which the TCR first contacts the MHC molecule prior to formation of the binding transition state using the germline-encoded CDR1 and CDR2 loops. The receptor then contacts the peptide using the hypervariable CDR3 loops as the transition state decays to the bound state. The model subdivides TCR binding into peptide-independent and peptide-dependent steps, demarcated at the binding transition state. Investigating the two-step model, here we show that two TCRs that recognize the same peptide/MHC bury very similar amounts of solvent-accessible surface area in their transition states. However, 1300-1500 A2 of surface area is buried in each, a significant amount suggestive of participation of peptide and associated CDR3 surface. Consistent with this interpretation, analysis of peptide and TCR variants indicates that stabilizing contacts to the peptide are formed within both transition states. These data are incompatible with the original two-step model, as are transition state models built using the principle of minimal frustration commonly employed in the investigation of protein folding and binding transition states. These findings will be useful in further explorations of the nature of TCR binding transition states, as well as ongoing efforts to understand the mechanisms by which T cell receptors recognize the composite peptide/MHC surface.     

Pyridoxyl amino acid esters in peptide synthesis

Pyridoxyl residue was suggested to be used as a multifunctional protective and modifying group in peptide synthesis. The modification was carried out by introducing the pyridoxyl residue in free or partially protected peptides or by the addition of amino acid pyridoxyl esters by the methods of conventional peptide synthesis without the removal of the pyridoxyl group at the terminal stages of the synthesis (the second approach is more convenient). Pyridoxyl residue was also used as a spacer in solid phase peptide synthesis. It was attached to the polymer by the alkylation of the hydroxyl groups or of the pyridine ring of the pyridoxyl derivatives with the chloromethylated styrene-divinylbenzene copolymer (the standard Merrifield resin). Potentials for the use of pyridoxyl derivatives in the synthesis of linear, multiplet, and cyclic peptides are discussed.     

Describing inhibitor specificity for the amino acid transporter LAT1 from metainference simulations

The human L-type amino acid transporter 1 (LAT1; SLC7A5) is a membrane transporter of amino acids, thyroid hormones, and drugs such as the Parkinson’s disease drug levodopa (L-Dopa). LAT1 is found in the blood-brain barrier, testis, bone marrow, and placenta, and its dysregulation has been associated with various neurological diseases, such as autism and epilepsy, as well as cancer. In this study, we combine metainference molecular dynamics simulations, molecular docking, and experimental testing, to characterize LAT1-inhibitor interactions. We first conducted a series of molecular docking experiments to identify the most relevant interactions between LAT1’s substrate-binding site and ligands, including both inhibitors and substrates. We then performed metainference molecular dynamics simulations using cryoelectron microscopy structures in different conformations of LAT1 with the electron density map as a spatial restraint, to explore the inherent heterogeneity in the structures. We analyzed the LAT1 substrate-binding site to map important LAT1-ligand interactions as well as newly described druggable pockets. Finally, this analysis guided the discovery of previously unknown LAT1 ligands using virtual screening and cellular uptake experiments. Our results improve our understanding of LAT1-inhibitor recognition, providing a framework for rational design of future lead compounds targeting this key drug target.     

Prediction of amino acid residues participated in substrate recognition by cytochrome P450 subfamilies with broad substrate specificity

Cytochromes P450 comprise a large superfamily and several of their isoforms play a crucial role in metabolism of xenobiotics, including drugs. Although these enzymes demonstrate broad and cross‐substrate specificity, different cytochrome P450 subfamilies exhibit certain selectivity for some types of substrates. Analysis of amino acid residues of the active sites of six cytochrome subfamilies (CYP1А, CYP2А, CYP2С, CYP2D, CYP2E and CYP3А) enables to define subfamily‐specific patterns that consist of four residues. These residues are located on the periphery of the active sites of these cytochromes. We suggest that they can form a primary binding site at the entrance to the active site, defining cytochrome substrate recognition. Copyright © 2013 John Wiley & Sons, Ltd.     

The multiple‐specificity landscape of modular peptide recognition domains

Modular protein interaction domains form the building blocks of eukaryotic signaling pathways. Many of them, known as peptide recognition domains, mediate protein interactions by recognizing short, linear amino acid stretches on the surface of their cognate partners with high specificity. Residues in these stretches are usually assumed to contribute independently to binding, which has led to a simplified understanding of protein interactions. Conversely, we observe in large binding peptide data sets that different residue positions display highly significant correlations for many domains in three distinct families (PDZ, SH3 and WW). These correlation patterns reveal a widespread occurrence of multiple binding specificities and give novel structural insights into protein interactions. For example, we predict a new binding mode of PDZ domains and structurally rationalize it for DLG1 PDZ1. We show that multiple specificity more accurately predicts protein interactions and experimentally validate some of the predictions for the human proteins DLG1 and SCRIB. Overall, our results reveal a rich specificity landscape in peptide recognition domains, suggesting new ways of encoding specificity in protein interaction networks.