Derivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct?

Many existing derivations of knowledge-based statistical pair potentials invoke the quasichemical approximation to estimate the expected side-chain contact frequency if there were no amino acid pair-specific interactions. At first glance, the quasichemical approximation that treats the residues in a protein as being disconnected and expresses the side-chain contact probability as being proportional to the product of the mole fractions of the pair of residues would appear to be rather severe. To investigate the validity of this approximation, we introduce two new reference states in which no specific pair interactions between amino acids are allowed, but in which the connectivity of the protein chain is retained. The first estimates the expected number of side-chain contracts by treating the protein as a Gaussian random coil polymer. The second, more realistic reference state includes the effects of chain connectivity, secondary structure, and chain compactness by estimating the expected side-chain contrast probability by placing the sequence of interest in each member of a library of structures of comparable compactness to the native conformation. The side-chain contact maps are not allowed to readjust to the sequence of interest, i.e., the side chains cannot repack. This situation would hold rigorously if all amino acids were the same size. Both reference states effectively permit the factorization of the side-chain contact probability into sequence-dependent and structure-dependent terms. Then, because the sequence distribution of amino acids in proteins is random, the quasichemical approximation to each of these reference states is shown to be excellent. Thus, the range of validity of the quasichemical approximation is determined by the magnitude of the side-chain repacking term, which is, at present, unknown. Finally, the performance of these two sets of pair interaction potentials as well as side-chain contact fraction-based interaction scales is assessed by inverse folding tests both without and with allowing for gaps.     

Statistical significance of hierarchical multi-body potentials based on Delaunay tessellation and their application in sequence-structure alignment.

Statistical potentials based on pairwise interactions between C alpha atoms are commonly used in protein threading/fold-recognition attempts. Inclusion of higher order interaction is a possible means of improving the specificity of these potentials. Delaunay tessellation of the C alpha-atom representation of protein structure has been suggested as a means of defining multi-body interactions. A large number of parameters are required to define all four-body interactions of 20 amino acid types (20(4) = 160,000). Assuming that residue order within a four-body contact is irrelevant reduces this to a manageable 8,855 parameters, using a nonredundant dataset of 608 protein structures. Three lines of evidence support the significance and utility of the four-body potential for sequence-structure matching. First, compared to the four-body model, all lower-order interaction models (three-body, two-body, one-body) are found statistically inadequate to explain the frequency distribution of residue contacts. Second, coherent patterns of interaction are seen in a graphic presentation of the four-body potential. Many patterns have plausible biophysical explanations and are consistent across sets of residues sharing certain properties (e.g., size, hydrophobicity, or charge). Third, the utility of the multi-body potential is tested on a test set of 12 same-length pairs of proteins of known structure for two protocols: Sequence-recognizes-structure, where a query sequence is threaded (without gap) through the native and a non-native structure; and structure-recognizes-sequence, where a query structure is threaded by its native and another non-native sequence. Using cross-validated training, protein sequences correctly recognized their native structure in all 24 cases. Conversely, structures recognized the native sequence in 23 of 24 cases. Further, the score differences between correct and decoy structures increased significantly using the three- or four-body potential compared to potentials of lower order.     

The cytidylyltransferase superfamily: Identification of the nucleotide-binding site and fold prediction

The crystal structure of glycerol-3-phosphate cytidylyltransferase from B. subtilis (TagD) is about to be solved. Here, we report a testable structure prediction based on the identification by sequence analysis of a superfamily of functionally diverse but structurally similar nucleotide-binding enzymes. We predict that TagD is a member of this family. The most conserved region in this superfamily resembles the ATP-binding HiGH motif of class I aminoacyI-tRNA synthetases. The predicted secondary structure of cytidylyltransferase and its homologues is compatible with the α/β topography of the class I aminoacyl-tRNA synthetases. The hypothesis of similarity of fold is strengthened by sequence-structure alignment and 3D model building using the known structure of tyrosyl tRNA synthetase as template. The proposed 3D model of TagD is plausible both structurally, with a well packed hydrophobic core, and functionally, as the most conserved residues cluster around the putative nucleotide binding site. If correct, the model would imply a very ancient evolutionary link between class I tRNA synthetases and the novel cytidylyltransferase superfamily. © 1995 Wiley-Liss, Inc.     

Predicting the functional motions of p97 using symmetric normal modes

p97 is a protein complex of the AAA+ family. Although functions of p97 are well understood, the mechanism by which p97 performs its unfolding activities remains unclear. In this work, we present a novel way of applying normal mode analysis to study this six‐fold symmetric molecular machine. By selecting normal modes that are axial symmetric and give the largest movements at D1 or D2 pore residues, we are able to predict the functional motions of p97, which are then validated by experimentally observed conformational changes. Our results shed light and provide new understandings on several key steps of the p97 functional process that were previously unclear or controversial, and thus are able to reconcile multiple previous findings. Specifically, our results reveal that (i) a venous valve‐like mechanism is used at D2 pore to ensure a one‐way exit‐only traffic of substrates; (ii) D1 pore remains shut during the functional process; (iii) the “swing‐up” motion of the N domain is closely coupled with the vertical motion of the D1 pore along the pore axis; (iv) because of the shut D1 pore and the one‐way traffic at D2 pore, it is highly likely that substrates enter the chamber through the gaps at the D1/D2 interface. The limited chamber volume inside p97 suggests that a substrate may be pulling out from D2 while at the same time being pulling in at the interface; (v) lastly, p97 uses a series of actions that alternate between twisting and pulling to remove the substrate. Proteins 2016; 84:1823–1835. © 2016 Wiley Periodicals, Inc.     

New local potential useful for genome annotation and 3D modeling

A new potential energy function representing the conformational preferences of sequentially local regions of a protein backbone is presented. This potential is derived from secondary structure probabilities such as those produced by neural network-based prediction methods. The potential is applied to the problem of remote homolog identification, in combination with a distance-dependent inter-residue potential and position-based scoring matrices. This fold recognition jury is implemented in a Java application called JThread. These methods are benchmarked on several test sets, including one released entirely after development and parameterization of JThread. In benchmark tests to identify known folds structurally similar to (but not identical with) the native structure of a sequence, JThread performs significantly better than PSI-BLAST, with 10% more structures identified correctly as the most likely structural match in a fold library, and 20% more structures correctly narrowed down to a set of five possible candidates. JThread also improves the average sequence alignment accuracy significantly, from 53% to 62% of residues aligned correctly. Reliable fold assignments and alignments are identified, making the method useful for genome annotation. JThread is applied to predicted open reading frames (ORFs) from the genomes of Mycoplasma genitalium and Drosophila melanogaster, identifying 20 new structural annotations in the former and 801 in the latter.     

On the structure of hisH: protein structure prediction in the context of structural and functional genomics

We predict a structure of the glutamine amidotransferase subunit (hisH) of imidazole glycerol phosphate synthase (IGPS) which catalyzes the fifth step of the histidine biosynthesis in Escherichia coli. The model is constructed using an energy-based threading program augmented by a multiple sequence to structure profile analysis. In developing our model we identified a conserved core region within hisH and a variable domain which is the likely site of interaction with the synthase subunit (hisF) of IGPS. Information available from structural and functional genomics studies was used to improve the structure prediction, to discuss parallels between histidine biosynthesis and other amino acid and nucleotide metabolic pathways, and to better understand the protein-protein interactions between the hisH and hisF domains of IGPS. This work allows us to develop a preliminary model for the structure of the entire IGPS holoenzyme.     

A cytochrome b origin of photosynthetic reaction centers: an evolutionary link between respiration and photosynthesis

The evolutionary origin of photosynthetic reaction centers has long remained elusive. Here, we use sequence and structural analysis to demonstrate an evolutionary link between the cytochrome b subunit of the cytochrome bc(1) complex and the core polypeptides of the photosynthetic bacterial reaction center. In particular, we have identified an area of significant sequence similarity between a three contiguous membrane-spanning domain of cytochrome b, which contains binding sites for two hemes, and a three contiguous membrane-spanning domain in the photosynthetic reaction center core subunits, which contains binding sites for cofactors such as (bacterio)chlorophylls, (bacterio)pheophytin and a non-heme iron. Three of the four heme ligands in cytochrome b are found to be conserved with the cofactor ligands in the reaction center polypeptides. Since cytochrome b and reaction center polypeptides both bind tetrapyrroles and quinones for electron transfer, the observed sequence, functional and structural similarities can best be explained with the assumption of a common evolutionary origin. Statistical analysis further supports a distant but significant homologous relationship. On the basis of previous evolutionary analyses that established a scenario that respiration evolved prior to photosynthesis, we consider it likely that cytochrome b is the evolutionary precursor for type II reaction center apoproteins. With a structural analysis confirming a common evolutionary origin of both type I and type II reaction centers, we further propose a novel "reaction center apoprotein early" hypothesis to account for the development of photosynthetic reaction center holoproteins.     

Expanding the nitrogen regulatory protein superfamily: Homology detection at below random sequence identity

Nitrogen regulatory (PII) proteins are signal transduction molecules involved in controlling nitrogen metabolism in prokaryots. PII proteins integrate the signals of intracellular nitrogen and carbon status into the control of enzymes involved in nitrogen assimilation. Using elaborate sequence similarity detection schemes, we show that five clusters of orthologs (COGs) and several small divergent protein groups belong to the PII superfamily and predict their structure to be a (betaalphabeta)(2) ferredoxin-like fold. Proteins from the newly emerged PII superfamily are present in all major phylogenetic lineages. The PII homologs are quite diverse, with below random (as low as 1%) pairwise sequence identities between some members of distant groups. Despite this sequence diversity, evidence suggests that the different subfamilies retain the PII trimeric structure important for ligand-binding site formation and maintain a conservation of conservations at residue positions important for PII function. Because most of the orthologous groups within the PII superfamily are composed entirely of hypothetical proteins, our remote homology-based structure prediction provides the only information about them. Analogous to structural genomics efforts, such prediction gives clues to the biological roles of these proteins and allows us to hypothesize about locations of functional sites on model structures or rationalize about available experimental information. For instance, conserved residues in one of the families map in close proximity to each other on PII structure, allowing for a possible metal-binding site in the proteins coded by the locus known to affect sensitivity to divalent metal ions. Presented analysis pushes the limits of sequence similarity searches and exemplifies one of the extreme cases of reliable sequence-based structure prediction. In conjunction with structural genomics efforts to shed light on protein function, our strategies make it possible to detect homology between highly diverse sequences and are aimed at understanding the most remote evolutionary connections in the protein world.     

Triage protein fold prediction

We have constructed, in a completely automated fashion, a new structure template library for threading that represents 358 distinct SCOP folds where each model is mathematically represented as a Hidden Markov model (HMM). Because the large number of models in the library can potentially dilute the prediction measure, a new triage method for fold prediction is employed. In the first step of the triage method, the most probable structural class is predicted using a set of manually constructed, high-level, generalized structural HMMs that represent seven general protein structural classes: all-alpha, all-beta, alpha/beta, alpha+beta, irregular small metal-binding, transmembrane beta-barrel, and transmembrane alpha-helical. In the second step, only those fold models belonging to the determined structural class are selected for the final fold prediction. This triage method gave more predictions as well as more correct predictions compared with a simple prediction method that lacks the initial classification step. Two different schemes of assigning Bayesian model priors are presented and discussed.