Rapid detection, classification and accurate alignment of up to a million or more related protein sequences

Automated hierarchical classification of protein domain subfamilies based on functionally-divergent residue signatures

Background

The NCBI Conserved Domain Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are at various stages of being manually curated into evolutionary hierarchies based on conserved and divergent sequence and structural features. These domain models are annotated to provide insights into the relationships between sequence, structure and function via web-based BLAST searches.

Results

Here we automate the generation of conserved domain (CD) hierarchies using a combination of heuristic and Markov chain Monte Carlo (MCMC) sampling procedures and starting from a (typically very large) multiple sequence alignment. This procedure relies on statistical criteria to define each hierarchy based on the conserved and divergent sequence patterns associated with protein functional-specialization. At the same time this facilitates the sequence and structural annotation of residues that are functionally important. These statistical criteria also provide a means to objectively assess the quality of CD hierarchies, a non-trivial task considering that the protein subgroups are often very distantly related—a situation in which standard phylogenetic methods can be unreliable. Our aim here is to automatically generate (typically sub-optimal) hierarchies that, based on statistical criteria and visual comparisons, are comparable to manually curated hierarchies; this serves as the first step toward the ultimate goal of obtaining optimal hierarchical classifications. A plot of runtimes for the most time-intensive (non-parallelizable) part of the algorithm indicates a nearly linear time complexity so that, even for the extremely large Rossmann fold protein class, results were obtained in about a day.

Conclusions

This approach automates the rapid creation of protein domain hierarchies and thus will eliminate one of the most time consuming aspects of conserved domain database curation. At the same time, it also facilitates protein domain annotation by identifying those pattern residues that most distinguish each protein domain subgroup from other related subgroups.

Structural and evolutionary divergence of eukaryotic protein kinases in Apicomplexa

Background

The Apicomplexa constitute an evolutionarily divergent phylum of protozoan pathogens responsible for widespread parasitic diseases such as malaria and toxoplasmosis. Many cellular functions in these medically important organisms are controlled by protein kinases, which have emerged as promising drug targets for parasitic diseases. However, an incomplete understanding of how apicomplexan kinases structurally and mechanistically differ from their host counterparts has hindered drug development efforts to target parasite kinases.

Results

We used the wealth of sequence data recently made available for 15 apicomplexan species to identify the kinome of each species and quantify the evolutionary constraints imposed on each family of apicomplexan kinases. Our analysis revealed lineage-specific adaptations in selected families, namely cyclin-dependent kinase (CDK), calcium-dependent protein kinase (CDPK) and CLK/LAMMER, which have been identified as important in the pathogenesis of these organisms. Bayesian analysis of selective constraints imposed on these families identified the sequence and structural features that most distinguish apicomplexan protein kinases from their homologs in model organisms and other eukaryotes. In particular, in a subfamily of CDKs orthologous to Plasmodium falciparum crk-5, the activation loop contains a novel PTxC motif which is absent from all CDKs outside Apicomplexa. Our analysis also suggests a convergent mode of regulation in a subset of apicomplexan CDPKs and mammalian MAPKs involving a commonly conserved arginine in the αC helix. In all recognized apicomplexan CLKs, we find a set of co-conserved residues involved in substrate recognition and docking that are distinct from metazoan CLKs.

Conclusions

We pinpoint key conserved residues that can be predicted to mediate functional differences from eukaryotic homologs in three identified kinase families. We discuss the structural, functional and evolutionary implications of these lineage-specific variations and propose specific hypotheses for experimental investigation. The apicomplexan-specific kinase features reported in this study can be used in the design of selective kinase inhibitors.

Surveying the manifold divergence of an entire protein class for statistical clues to underlying biochemical mechanisms

Certain residues have no known function yet are co-conserved across distantly related protein families and diverse organisms, suggesting that they perform critical roles associated with as-yet-unidentified molecular properties and mechanisms. This raises the question of how to obtain additional clues regarding these mysterious biochemical phenomena with a view to formulating experimentally testable hypotheses. One approach is to access the implicit biochemical information encoded within the vast amount of genomic sequence data now becoming available. Here, a new Gibbs sampling strategy is formulated and implemented that can partition hundreds of thousands of sequences within a major protein class into multiple, functionally-divergent categories based on those pattern residues that best discriminate between categories. The sampler precisely defines the partition and pattern for each category by explicitly modeling unrelated, non-functional and related-yet-divergent proteins that would otherwise obscure the analysis. To aid biological interpretation, auxiliary routines can characterize pattern residues within available crystal structures and identify those structures most likely to shed light on the roles of pattern residues. This approach can be used to define and annotate automatically subgroup-specific conserved domain profiles based on statistically-rigorous empirical criteria rather than on the subjective and labor-intensive process of manual curation. Incorporating such profiles into domain database search sites (such as the NCBI BLAST site) will provide biologists with previously inaccessible molecular information useful for hypothesis generation and experimental design. Analyses of P-loop GTPases and of AAA+ ATPases illustrate the sampler's ability to obtain such information.

Co-conserved features associated with cis regulation of ErbB tyrosine kinases

Background

The epidermal growth factor receptor kinases, or ErbB kinases, belong to a large sub-group of receptor tyrosine kinases (RTKs), which share a conserved catalytic core. The catalytic core of ErbB kinases have functionally diverged from other RTKs in that they are activated by a unique allosteric mechanism that involves specific interactions between the kinase core and the flanking Juxtamembrane (JM) and COOH-terminal tail (C-terminal tail). Although extensive studies on ErbB and related tyrosine kinases have provided important insights into the structural basis for ErbB kinase functional divergence, the sequence features that contribute to the unique regulation of ErbB kinases have not been systematically explored.

Methodology/Principal Findings

In this study, we use a Bayesian approach to identify the selective sequence constraints that most distinguish ErbB kinases from other receptor tyrosine kinases. We find that strong ErbB kinase-specific constraints are imposed on residues that tether the JM and C-terminal tail to key functional regions of the kinase core. A conserved RIxKExE motif in the JM-kinase linker region and a glutamine in the inter-lobe linker are identified as two of the most distinguishing features of the ErbB family. While the RIxKExE motif tethers the C-terminal tail to the N-lobe of the kinase domain, the glutamine tethers the C-terminal tail to hinge regions critical for inter-lobe movement. Comparison of the active and inactive crystal structures of ErbB kinases indicates that the identified residues are conformationally malleable and can potentially contribute to the cis regulation of the kinase core by the JM and C-terminal tail. ErbB3, and EGFR orthologs in sponges and parasitic worms, diverge from some of the canonical ErbB features, providing insights into sub-family and lineage-specific functional specialization.

Conclusion/Significance

Our analysis pinpoints key residues for mutational analysis, and provides new clues to cancer mutations that alter the canonical modes of ErbB kinase regulation.

Bayesian classification of residues associated with protein functional divergence: Arf and Arf-like GTPases

Background

Certain residues within proteins are highly conserved across very distantly related organisms, yet their (presumably critical) structural or mechanistic roles are completely unknown. To obtain clues regarding such residues within Arf and Arf-like (Arf/Arl) GTPases--which function as on/off switches regulating vesicle trafficking, phospholipid metabolism and cytoskeletal remodeling--I apply a new sampling procedure for comparative sequence analysis, termed multiple category Bayesian Partitioning with Pattern Selection (mcBPPS).

Results

The mcBPPS sampler classified sequences within the entire P-loop GTPase class into multiple categories by identifying those evolutionarily-divergent residues most likely to be responsible for functional specialization. Here I focus on categories of residues that most distinguish various Arf/Arl GTPases from other GTPases. This identified residues whose specific roles have been previously proposed (and in some cases corroborated experimentally and that thus serve as positive controls), as well as several categories of co-conserved residues whose possible roles are first hinted at here. For example, Arf/Arl/Sar GTPases are most distinguished from other GTPases by a conserved aspartate residue within the phosphate binding loop (P-loop) and by co-conserved residues nearby that, together, can form a network of salt-bridge and hydrogen bond interactions centered on the GTPase active site. Residues corresponding to an N-[VI] motif that is conserved within Arf/Arl GTPases may play a role in the interswitch toggle characteristic of the Arf family, whereas other, co-conserved residues may modulate the flexibility of the guanine binding loop. Arl8 GTPases conserve residues that strikingly diverge from those typically found in other Arf/Arl GTPases and that form structural interactions suggestive of a novel interswitch toggle mechanism.

Conclusions

This analysis suggests specific mutagenesis experiments to explore mechanisms underlying GTP hydrolysis, nucleotide exchange and interswitch toggling within Arf/Arl GTPases. More generally, it illustrates how the mcBPPS sampler can complement traditional evolutionary analyses by providing an objective, quantitative and statistically rigorous way to explore protein functional-divergence in molecular detail. Because the sampler classifies the input sequences at the same time, it can be used to generate subgroup profiles, in which functionally-divergent categories of residues are annotated automatically.

Reviewers

This article was reviewed by Frank Eisenhaber, L Aravind and Daniel Gaston (nominated by Eric Bapteste). For the full reviews, go to the Reviewers' comments section.

Detecting subtle functional differences in ketopantoate reductase and related enzymes using a rule-based approach with sequence-structure homology recognition scores

Ketopatoate reductase (KPR) is the second enzyme in the pantothenate (vitamin B(5)) biosynthesis pathway, an essential metabolic pathway identified as a potential target for new antimicrobials. The sequence similarity among putative KPRs is limited and KPR itself belongs to a large superfamily of 6-phosphogluconate dehydrogenases. Therefore, it is necessary to discriminate between true and other enzymes. In this paper, we describe a systematic analysis of putative KPRs in the context of this superfamily. Detailed structural analysis allowed us to define key residues for KPR activity and we classified eight structural genomics structures of the KPR family into four functional subclasses. We proposed a semi-automatic protocol, using sequence-structure homology recognition scores, for assigning KPR and related proteins to these subclasses and applied it to a representative set of 103 completely sequenced bacterial genomes. A similar approach can be applied to other enzyme families, which would aid the correct identification of drug targets and help design novel specific inhibitors.