Deep Analysis of Residue Constraints (DARC): identifying determinants of protein functional specificity

SPARC: Structural properties associated with residue constraints

SPARC facilitates the generation of plausible hypotheses regarding underlying biochemical mechanisms by structurally characterizing protein sequence constraints. Such constraints appear as residues co-conserved in functionally related subgroups, as subtle pairwise correlations (i.e., direct couplings), and as correlations among these sequence features or with structural features. SPARC performs three types of analyses. First, based on pairwise sequence correlations, it estimates the biological relevance of alternative conformations and of homomeric contacts, as illustrated here for death domains. Second, it estimates the statistical significance of the correspondence between directly coupled residue pairs and interactions at heterodimeric interfaces. Third, given molecular dynamics simulated structures, it characterizes interactions among constrained residues or between such residues and ligands that: (a) are stably maintained during the simulation; (b) undergo correlated formation and/or disruption of interactions with other constrained residues; or (c) switch between alternative interactions. We illustrate this for two homohexameric complexes: the bacterial enhancer binding protein (bEBP) NtrC1, which activates transcription by remodeling RNA polymerase (RNAP) containing σ⁵⁴, and for DnaB helicase, which opens DNA at the bacterial replication fork. Based on the NtrC1 analysis, we hypothesize possible mechanisms for inhibiting ATP hydrolysis until ADP is released from an adjacent subunit and for coupling ATP hydrolysis to restructuring of σ⁵⁴ binding loops. Based on the DnaB analysis, we hypothesize that DnaB 'grabs' ssDNA by flipping every fourth base and inserting it into cavities between subunits and that flipping of a DnaB-specific glutamine residue triggers ATP hydrolysis.

Identifying Function Determining Residues in Neuroimmune Semaphorin 4A

Semaphorin 4A (Sema4A) exerts a stabilizing effect on human Treg cells in PBMC and CD4+ T cell cultures by engaging Plexin B1. Sema4A deficient mice display enhanced allergic airway inflammation accompanied by fewer Treg cells, while Sema4D deficient mice displayed reduced inflammation and increased Treg cell numbers even though both Sema4 subfamily members engage Plexin B1. The main objectives of this study were: 1. To compare the in vitro effects of Sema4A and Sema4D proteins on human Treg cells; and 2. To identify function-determining residues in Sema4A critical for binding to Plexin B1 based on Sema4D homology modeling. We report here that Sema4A and Sema4D display opposite effects on human Treg cells in in vitro PBMC cultures; Sema4D inhibited the CD4+CD25+Foxp3+ cell numbers and CD25/Foxp3 expression. Sema4A and Sema4D competitively bind to Plexin B1 in vitro and hence may be doing so in vivo as well. Bayesian Partitioning with Pattern Selection (BPPS) partitioned 4505 Sema domains from diverse organisms into subgroups based on distinguishing sequence patterns that are likely responsible for functional differences. BPPS groups Sema3 and Sema4 into one family and further separates Sema4A and Sema4D into distinct subfamilies. Residues distinctive of the Sema3,4 family and of Sema4A (and by homology of Sema4D) tend to cluster around the Plexin B1 binding site. This suggests that the residues both common to and distinctive of Sema4A and Sema4D may mediate binding to Plexin B1, with subfamily residues mediating functional specificity. We mutated the Sema4A-specific residues M198 and F223 to alanine; notably, F223 in Sema4A corresponds to alanine in Sema4D. Mutant proteins were assayed for Plexin B1-binding and Treg stimulation activities. The F223A mutant was unable to stimulate Treg stability in in vitro PBMC cultures despite binding Plexin B1 with an affinity similar to the WT protein. This research is a first step in generating potent mutant Sema4A molecules with stimulatory function for Treg cells with a view to designing immunotherapeutics for asthma.

Modulating Glycoside Hydrolase Activity between Hydrolysis and Transfer Reactions Using an Evolutionary Approach

The proteins within the CAZy glycoside hydrolase family GH13 catalyze the hydrolysis of polysaccharides such as glycogen and starch. Many of these enzymes also perform transglycosylation in various degrees, ranging from secondary to predominant reactions. Identifying structural determinants associated with GH13 family reaction specificity is key to modifying and designing enzymes with increased specificity towards individual reactions for further applications in industrial, chemical, or biomedical fields. This work proposes a computational approach for decoding the determinant structural composition defining the reaction specificity. This method is based on the conservation of coevolving residues in spatial contacts associated with reaction specificity. To evaluate the algorithm, mutants of α-amylase (TmAmyA) and glucanotransferase (TmGTase) from Thermotoga maritima were constructed to modify the reaction specificity. The K98P/D99A/H222Q variant from TmAmyA doubled the transglycosydation/hydrolysis (T/H) ratio while the M279N variant from TmGTase increased the hydrolysis/transglycosidation ratio five-fold. Molecular dynamic simulations of the variants indicated changes in flexibility that can account for the modified T/H ratio. An essential contribution of the presented computational approach is its capacity to identify residues outside of the active center that affect the reaction specificity.

Computational approaches to predict protein functional families and functional sites

Understanding the mechanisms of protein function is indispensable for many biological applications, such as protein engineering and drug design. However, experimental annotations are sparse, and therefore, theoretical strategies are needed to fill the gap. Here, we present the latest developments in building functional subclassifications of protein superfamilies and using evolutionary conservation to detect functional determinants, for example, catalytic-, binding- and specificity-determining residues important for delineating the functional families. We also briefly review other features exploited for functional site detection and new machine learning strategies for combining multiple features.

eCOMPASS: evaluative comparison of multiple protein alignments by statistical score

Motivation

Detecting subtle biologically relevant patterns in protein sequences often requires the construction of a large and accurate multiple sequence alignment (MSA). Methods for constructing MSAs are usually evaluated using benchmark alignments, which, however, typically contain very few sequences and are therefore inappropriate when dealing with large numbers of proteins.

Results

eCOMPASS addresses this problem using a statistical measure of relative alignment quality based on direct coupling analysis (DCA): to maintain protein structural integrity over evolutionary time, substitutions at one residue position typically result in compensating substitutions at other positions. eCOMPASS computes the statistical significance of the congruence between high scoring directly coupled pairs and 3D contacts in corresponding structures, which depends upon properly aligned homologous residues. We illustrate eCOMPASS using both simulated and real MSAs.

Availability and implementation

The eCOMPASS executable, C++ open source code and input data sets are available at https://www.igs.umaryland.edu/labs/neuwald/software/compass

Supplementary information

Supplementary data are available at Bioinformatics online.

Allosteric communication in DNA polymerase clamp loaders relies on a critical hydrogen-bonded junction

Clamp loaders are AAA+ ATPases that load sliding clamps onto DNA. We mapped the mutational sensitivity of the T4 bacteriophage sliding clamp and clamp loader by deep mutagenesis, and found that residues not involved in catalysis or binding display remarkable tolerance to mutation. An exception is a glutamine residue in the AAA+ module (Gln 118) that is not located at a catalytic or interfacial site. Gln 118 forms a hydrogen-bonded junction in a helical unit that we term the central coupler, because it connects the catalytic centers to DNA and the sliding clamp. A suppressor mutation indicates that hydrogen bonding in the junction is important, and molecular dynamics simulations reveal that it maintains rigidity in the central coupler. The glutamine-mediated junction is preserved in diverse AAA+ ATPases, suggesting that a connected network of hydrogen bonds that links ATP molecules is an essential aspect of allosteric communication in these proteins.

Fine-Tuning of Alanyl-tRNA Synthetase Quality Control Alleviates Global Dysregulation of the Proteome

One integral step in the transition from a nucleic acid encoded-genome to functional proteins is the aminoacylation of tRNA molecules. To perform this activity, aminoacyl-tRNA synthetases (aaRSs) activate free amino acids in the cell forming an aminoacyl-adenylate before transferring the amino acid on to its cognate tRNA. These newly formed aminoacyl-tRNA (aa-tRNA) can then be used by the ribosome during mRNA decoding. In Escherichia coli, there are twenty aaRSs encoded in the genome, each of which corresponds to one of the twenty proteinogenic amino acids used in translation. Given the shared chemicophysical properties of many amino acids, aaRSs have evolved mechanisms to prevent erroneous aa-tRNA formation with non-cognate amino acid substrates. Of particular interest is the post-transfer proofreading activity of alanyl-tRNA synthetase (AlaRS) which prevents the accumulation of Ser-tRNA^Ala and Gly-tRNA^Ala in the cell. We have previously shown that defects in AlaRS proofreading of Ser-tRNA^Ala lead to global dysregulation of the E. coli proteome, subsequently causing defects in growth, motility, and antibiotic sensitivity. Here we report second-site AlaRS suppressor mutations that alleviate the aforementioned phenotypes, revealing previously uncharacterized residues within the AlaRS proofreading domain that function in quality control.