Characterizing the regularity of tetrahedral packing motifs in protein tertiary structure

MOTIVATION: While protein secondary structure is well understood, representing the repetitive nature of tertiary packing in proteins remains difficult. We have developed a construct called the relative packing group (RPG) that applies the clique concept from graph theory as a natural basis for defining the packing motifs in proteins. An RPG is defined as a clique of residues, where every member contacts all others as determined by the Delaunay tessellation. Geometrically similar RPGs define a regular element of tertiary structure or tertiary motif (TerMo). This intuitive construct provides a simple approach to characterize general repetitive elements of tertiary structure. RESULTS: A dataset of over 4 million tetrahedral RPGs was clustered using different criteria to characterize the various aspects of regular tertiary structure in TerMos. Grouping this data within the SCOP classification levels of Family, Superfamily, Fold, Class and PDB showed that similar packing is shared across different folds. Classification of RPGs based on residue sequence locality reveals topological preferences according to protein sizes and secondary structure. We find that larger proteins favor RPGs with three local residues packed against a non-local residue. Classifying by secondary structure, helices prefer mostly local residues, sheets favor at least two local residues, while turns and coil populate with more local residues. To depict these TerMos, we have developed 2 complementary and intuitive representations: (i) Dirichlet process mixture density estimation of the torsion angle distributions and (ii) kernel density estimation of the Cartesian coordinate distribution. The TerMo library and representations software are available upon request.     

The automatic detection of known beta-propeller structural motifs from protein tertiary structure

Following our previous work on the analysis of 'structural plasticity' associated with the beta-propeller structural motifs, we have now developed a simple method that can automatically detect all the known beta-propellers in protein tertiary structure, given a list of Protein Data Bank (PDB) codes as input to the computer program. Our beta-propeller detection (BPD) method identifies the location of beta-propellers in the protein structure, specifies the beta-propeller type, the beta-sheet associated beta-strand pattern and the structurally similar beta-propellers observed in other proteins. When tested on 21,566 proteins in the PDB, the BPD method was capable of correctly identifying all the known 245 beta-propellers described in the structural classification of proteins (SCOP) with the number of false positives detected being less than 0.2%. Forty-one false positives were detected that correspond to eight known protein families. When compared with some of the popular web-based programs that can automatically detect 'structural similarities' between the query and target proteins, our method has the advantage of also being capable of detecting beta-propellers associated with 'structural plasticity' and in situations where the target and query proteins differ in amino acid sequence length.     

Large-scale discovery and characterization of protein regulatory motifs in eukaryotes

The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior. Here we show that short, linear protein motifs can be efficiently recovered from proteome-scale datasets such as sub-cellular localization, molecular function, half-life, and protein abundance data using an information theoretic approach. Using this approach, we have identified many known protein motifs, such as phosphorylation sites and localization signals, and discovered a large number of candidate elements. We estimate that ~80% of these are novel predictions in that they do not match a known motif in both sequence and biological context, suggesting that post-translational regulation of protein behavior is still largely unexplored. These predicted motifs, many of which display preferential association with specific biological pathways and non-random positioning in the linear protein sequence, provide focused hypotheses for experimental validation.     

Modeling RNA tertiary structure motifs by graph-grammars

A new approach, graph-grammars, to encode RNA tertiary structure patterns is introduced and exemplified with the classical sarcin-ricin motif. The sarcin-ricin motif is found in the stem of the crucial ribosomal loop E (also referred to as the sarcin-ricin loop), which is sensitive to the alpha-sarcin and ricin toxins. Here, we generate a graph-grammar for the sarcin-ricin motif and apply it to derive putative sequences that would fold in this motif. The biological relevance of the derived sequences is confirmed by a comparison with those found in known sarcin-ricin sites in an alignment of over 800 bacterial 23S ribosomal RNAs. The comparison raised alternative alignments in few sarcin-ricin sites, which were assessed using tertiary structure predictions and 3D modeling. The sarcin-ricin motif graph-grammar was built with indivisible nucleotide interaction cycles that were recently observed in structured RNAs. A comparison of the sequences and 3D structures of each cycle that constitute the sarcin-ricin motif gave us additional insights about RNA sequence-structure relationships. In particular, this analysis revealed the sequence space of an RNA motif depends on a structural context that goes beyond the single base pairing and base-stacking interactions.     

Automated extraction and classification of RNA tertiary structure cyclic motifs

A minimum cycle basis of the tertiary structure of a large ribosomal subunit (LSU) X-ray crystal structure was analyzed. Most cycles are small, as they are composed of 3- to 5 nt, and repeated across the LSU tertiary structure. We used hierarchical clustering to quantify and classify the 4 nt cycles. One class is defined by the GNRA tetraloop motif. The inspection of the GNRA class revealed peculiar instances in sequence. First is the presence of UA, CA, UC and CC base pairs that substitute the usual sheared GA base pair. Second is the revelation of GNR(X(n))A tetraloops, where X(n) is bulged out of the classical GNRA structure, and of GN/RA formed by the two strands of interior-loops. We were able to unambiguously characterize the cycle classes using base stacking and base pairing annotations. The cycles identified correspond to small and cyclic motifs that compose most of the LSU RNA tertiary structure and contribute to its thermodynamic stability. Consequently, the RNA minimum cycles could well be used as the basic elements of RNA tertiary structure prediction methods.     

Engineering of zinc finger and MHC motifs to locked-in tertiary folds

The assembly of helical and -sheet peptide blocks containing reactive chain ends results inhighly branched chain architectures (locked-in folds) mimicking native tertiary structures.This molecular kit strategy allows to bypass the protein folding problem in protein de novodesign and gives access to protein mimetics of high thermodynamic stability. The validity ofthis concept is exemplified for the design and synthesis of locked-in folds mimicking the zincfinger and MHC folding motifs.     

Engineering of zinc finger and MHC motifs to locked-in tertiary folds

Summary The assembly of helical and β-sheet peptide blocks containing reactive chain ends results in highly branched chain architectures (‘locked-in folds’) mimicking native tertiary structures. This molecular kit strategy allows to bypass the protein folding problem in protein de novo design and gives access to protein mimetics of high thermodynamic stability. The validity of this concept is exemplified for the design and synthesis of locked-in folds mimicking the zinc finger and MHC folding motifs.     

Functional characterization of and cooperation between the double-stranded RNA-binding motifs of the protein kinase PKR

The interferon-inducible double-stranded RNA (dsRNA)-activated protein kinase PKR is regulated by dsRNAs that interact with the two dsRNA-binding motifs (dsRBMs) in its N terminus. The dsRBM is a conserved protein motif found in many proteins from most organisms. In this study, we investigated the biochemical functions and cytological activities of the two PKR dsRBMs (dsRBM1 and dsRBM2) and the cooperation between them. We found that dsRBM1 has a higher affinity for binding to dsRNA than dsRBM2. In addition, dsRBM1 has RNA-annealing activity that is not displayed by dsRBM2. Both dsRBMs have an intrinsic ability to dimerize (dsRBM2) or multimerize (dsRBM1). Binding to dsRNA inhibits oligomerization of dsRBM1 but not dsRBM2 and strongly inhibits the dimerization of the intact PKR N terminus (p20) containing both dsRBMs. dsRBM1, like p20, activates reporter gene expression in transfection assays, and it plays a determinative role in localizing PKR to the nucleolus and cytoplasm of the cell. Thus, dsRBM2 has weak or no activity in dsRNA binding, stimulation of gene expression, and PKR localization, but it strongly enhances these functions of dsRBM1 when contained in p20. However, dsRBM2 does not enhance the annealing activity of dsRBM1. This study shows that the dsRBMs of PKR possess distinct properties and that some, but not all, of the functions of the enzyme depend on cooperation between the two motifs.     

Bioactive motifs of agouti signal protein

The switch between the synthesis of eu- and pheomelanins is modulated by the interaction of two paracrine signaling molecules, alpha-melanocyte stimulating hormone (MSH) and agouti signal protein (ASP), which interact with melanocytes via the MSH receptor (MC1R). Comparison of the primary sequence of ASP with the known MSH pharmacophore provides no suggestion about the putative bioactive domain(s) of ASP. To identify such bioactive motif(s), we synthesized 15-mer peptides that spanned the primary sequence of ASP and determined their effects on the melanogenic activities of murine melanocytes. Northern and Western blotting were used, together with chemical analysis of melanins and enzymatic assays, to identify three distinct bioactive regions of ASP that down-regulate eumelanogenesis. The decrease in eumelanin production was mediated by down-regulation of mRNA levels for tyrosinase and other melanogenic enzymes, as occurs in vivo, and these effects were comparable to those elicited by intact recombinant ASP. Shorter peptides in those motifs were synthesized and their effects on melanogenesis were further investigated. The amino acid arginine, which is present in the MSH peptide pharmacophore (HFRW), is also in the most active domain of ASP (KVARP). Our data suggest that lysines and an arginine (in motifs such as KxxxxKxxR or KxxRxxxxK) are important for the bioactivity of ASP. Identification of the specific ASP epitope that interacts with the MC1R has potential pharmacological applications in treating dysfunctions of skin pigmentation.     

NMR characterization of intramolecular interaction of osteopontin, an intrinsically disordered protein with cryptic integrin-binding motifs

Osteopontin (OPN) is an integrin-binding protein found in a variety of tissues and physiological fluids and is involved in divergent biological processes such as migration, adhesion and signaling in integrin-independent as well as dependent manners. The adhesive activity of this protein is modulated upon cleavage by thrombin at the central part of the molecule, in the vicinity of the integrin-binding sequences. Although detailed structural characterization is crucial for further understanding of the regulatory mechanisms of the OPN functions, its intrinsically disordered property hampers in-depth conformational analyses. Here we report an NMR study of mouse OPN and its N-terminal thrombin-cleavage product to characterize intramolecular interaction of this molecule. Paramagnetic relaxation enhancement experiment revealed that OPN exhibits a long-range intramolecular interaction between the N- and C-terminal regions. Furthermore, our NMR data showed that anti-OPN antibody OPN1.2, whose reactivity is impaired by deletion or amino acid substitutions of the arginine-aspartate-glycine integrin-binding motif, binds the N-terminal side of the integrin-binding motifs suggesting the existence of intramolecular interaction. These data suggest that functional interactions of OPN with integrins and the other binding partners can be modulated by the intramolecular interactions.     

Predicting conserved protein motifs with Sub-HMMs

Background  

Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is the difficulty to pinpoint their much shorter functional sub-features, such as catalytically relevant sequence motifs in enzymes or ligand binding signatures of receptor proteins.     

Calculation of protein tertiary structure

We describe a method for calculating the tertiary structure of proteins given their amino acid sequence. The algorithm involves locally minimizing an energylike expression as a function of the Cartesian co-ordinates of the C_β of all residues. Although the approximation to the true polypeptide geometry and conformational energies is extremely approximate, quite respectable results have been obtained for the small proteins rubredoxin and trypsin inhibitor, where the root mean square errors are as low as 4.0 Å and 4.7 Å, respectively.     

Mining protein sequences for motifs.

We use methods from Data Mining and Knowledge Discovery to design an algorithm for detecting motifs in protein sequences. The algorithm assumes that a motif is constituted by the presence of a "good" combination of residues in appropriate locations of the motif. The algorithm attempts to compile such good combinations into a "pattern dictionary" by processing an aligned training set of protein sequences. The dictionary is subsequently used to detect motifs in new protein sequences. Statistical significance of the detection results are ensured by statistically determining the various parameters of the algorithm. Based on this approach, we have implemented a program called GYM. The Helix-Turn-Helix motif was used as a model system on which to test our program. The program was also extended to detect Homeodomain motifs. The detection results for the two motifs compare favorably with existing programs. In addition, the GYM program provides a lot of useful information about a given protein sequence.     

Refinement and prediction of protein prenylation motifs

We refined the motifs for carboxy-terminal protein prenylation by analysis of known substrates for farnesyltransferase (FT), geranylgeranyltransferase I (GGT1) and geranylgeranyltransferase II (GGT2). In addition to the CaaX box for the first two enzymes, we identify a preceding linker region that appears constrained in physicochemical properties, requiring small or flexible, preferably hydrophilic, amino acids. Predictors were constructed on the basis of sequence and physical property profiles, including interpositional correlations, and are available as the Prenylation Prediction Suite (PrePS, ) which also allows evaluation of evolutionary motif conservation. PrePS can predict partially overlapping substrate specificities, which is of medical importance in the case of understanding cellular action of FT inhibitors as anticancer and anti-parasite agents.     

Neural network‐derived Potts models for structure‐based protein design using backbone atomic coordinates and tertiary motifs

Designing novel proteins to perform desired functions, such as binding or catalysis, is a major goal in synthetic biology. A variety of computational approaches can aid in this task. An energy‐based framework rooted in the sequence‐structure statistics of tertiary motifs (TERMs) can be used for sequence design on predefined backbones. Neural network models that use backbone coordinate‐derived features provide another way to design new proteins. In this work, we combine the two methods to make neural structure‐based models more suitable for protein design. Specifically, we supplement backbone‐coordinate features with TERM‐derived data, as inputs, and we generate energy functions as outputs. We present two architectures that generate Potts models over the sequence space: TERMinator, which uses both TERM‐based and coordinate‐based information, and COORDinator, which uses only coordinate‐based information. Using these two models, we demonstrate that TERMs can be utilized to improve native sequence recovery performance of neural models. Furthermore, we demonstrate that sequences designed by TERMinator are predicted to fold to their target structures by AlphaFold. Finally, we show that both TERMinator and COORDinator learn notions of energetics, and these methods can be fine‐tuned on experimental data to improve predictions. Our results suggest that using TERM‐based and coordinate‐based features together may be beneficial for protein design and that structure‐based neural models that produce Potts energy tables have utility for flexible applications in protein science.     

MSDmotif: exploring protein sites and motifs

Background  

Protein structures have conserved features – motifs, which have a sufficient influence on the protein function. These motifs can be found in sequence as well as in 3D space. Understanding of these fragments is essential for 3D structure prediction, modelling and drug-design. The Protein Data Bank (PDB) is the source of this information however present search tools have limited 3D options to integrate protein sequence with its 3D structure.     

Conserved internal hydration motifs in protein kinases

Crystal structures of diverse protein kinase catalytic subunits reveal a number of water molecules whose positions within the protein core are better preserved than amino acid types in many functionally important locations. It remains unknown whether they play any particular role, and whether their removal, disturbing local interaction patterns to no smaller degree than amino acid mutations, can affect kinase stability and function. In this study, we apply an array of computational approaches to characterize hydration of kinase catalytic subunits. First, we systematically screen multiple crystal structures with the use of a simplified hydration model in order to determine the distribution of internal solvent and the degree of its conservation. Second, we analyze water structure, dynamics and binding affinity to buried hydration sites in a number of kinases, also taking into account their variable functional state. We find that a large portion of buried solvent is dynamic, possibly contributing to kinase conformational changes related to the activation process. In turn, binding free energies of some of tightly bound conserved water molecules to different kinases tend to shift in a similar manner following the change of their functional state. This finding highlights the likely specific role of internal solvent in fine tuning local protein plasticity.