A Global Comparison of the Human and T. brucei Degradomes Gives Insights about Possible Parasite Drug Targets

We performed a genome-level computational study of sequence and structure similarity, the latter using crystal structures and models, of the proteases of Homo sapiens and the human parasite Trypanosoma brucei. Using sequence and structure similarity networks to summarize the results, we constructed global views that show visually the relative abundance and variety of proteases in the degradome landscapes of these two species, and provide insights into evolutionary relationships between proteases. The results also indicate how broadly these sequence sets are covered by three-dimensional structures. These views facilitate cross-species comparisons and offer clues for drug design from knowledge about the sequences and structures of potential drug targets and their homologs. Two protease groups (“M32” and “C51”) that are very different in sequence from human proteases are examined in structural detail, illustrating the application of this global approach in mining new pathogen genomes for potential drug targets. Based on our analyses, a human ACE2 inhibitor was selected for experimental testing on one of these parasite proteases, TbM32, and was shown to inhibit it. These sequence and structure data, along with interactive versions of the protein similarity networks generated in this study, are available at http://babbittlab.ucsf.edu/resources.html.     

Integrating protein structural dynamics and evolutionary analysis with Bio3D

Background

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution.

Results

Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case.

Conclusions

The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0399-6) contains supplementary material, which is available to authorized users.     

Combining Physicochemical and Evolutionary Information for Protein Contact Prediction

We introduce a novel contact prediction method that achieves high prediction accuracy by combining evolutionary and physicochemical information about native contacts. We obtain evolutionary information from multiple-sequence alignments and physicochemical information from predicted ab initio protein structures. These structures represent low-energy states in an energy landscape and thus capture the physicochemical information encoded in the energy function. Such low-energy structures are likely to contain native contacts, even if their overall fold is not native. To differentiate native from non-native contacts in those structures, we develop a graph-based representation of the structural context of contacts. We then use this representation to train an support vector machine classifier to identify most likely native contacts in otherwise non-native structures. The resulting contact predictions are highly accurate. As a result of combining two sources of information—evolutionary and physicochemical—we maintain prediction accuracy even when only few sequence homologs are present. We show that the predicted contacts help to improve ab initio structure prediction. A web service is available at http://compbio.robotics.tu-berlin.de/epc-map/.     

ExonVisualiser – application for visualization exon units in 2D and 3D protein structures

The web application oriented on identification and visualization of protein regions encoded by exons is presented. The Exon Visualiser can be used for visualisation on different levels of protein structure: at the primary (sequence) level and secondary structures level, as well as at the level of tertiary protein structure. The programme is suitable for processing data for all genes which have protein expressions deposited in the PDB database. The procedure steps implemented in the application: I) loading exons sequences and theirs coordinates from GenBank file as well as protein sequences: CDS from GenBank and aminoacid sequence from PDB II) consensus sequence creation (comparing amino acid sequences form PDB file with the CDS sequence from GenBank file) III) matching exon coordinates IV) visualisation in 2D and 3D protein structures. Presented web-tool among others provides the color-coded graphical display of protein sequences and chains in three dimensional protein structures which are correlated with the corresponding exons.

Availability

http://149.156.12.53/ExonVisualiser/     

FastBLAST: homology relationships for millions of proteins

Background

All-versus-all BLAST, which searches for homologous pairs of sequences in a database of proteins, is used to identify potential orthologs, to find new protein families, and to provide rapid access to these homology relationships. As DNA sequencing accelerates and data sets grow, all-versus-all BLAST has become computationally demanding.

Methodology/Principal Findings

We present FastBLAST, a heuristic replacement for all-versus-all BLAST that relies on alignments of proteins to known families, obtained from tools such as PSI-BLAST and HMMer. FastBLAST avoids most of the work of all-versus-all BLAST by taking advantage of these alignments and by clustering similar sequences. FastBLAST runs in two stages: the first stage identifies additional families and aligns them, and the second stage quickly identifies the homologs of a query sequence, based on the alignments of the families, before generating pairwise alignments. On 6.53 million proteins from the non-redundant Genbank database (“NR”), FastBLAST identifies new families 25 times faster than all-versus-all BLAST. Once the first stage is completed, FastBLAST identifies homologs for the average query in less than 5 seconds (8.6 times faster than BLAST) and gives nearly identical results. For hits above 70 bits, FastBLAST identifies 98% of the top 3,250 hits per query.

Conclusions/Significance

FastBLAST enables research groups that do not have supercomputers to analyze large protein sequence data sets. FastBLAST is open source software and is available at http://microbesonline.org/fastblast.     

Alignment of Helical Membrane Protein Sequences Using AlignMe

Few sequence alignment methods have been designed specifically for integral membrane proteins, even though these important proteins have distinct evolutionary and structural properties that might affect their alignments. Existing approaches typically consider membrane-related information either by using membrane-specific substitution matrices or by assigning distinct penalties for gap creation in transmembrane and non-transmembrane regions. Here, we ask whether favoring matching of predicted transmembrane segments within a standard dynamic programming algorithm can improve the accuracy of pairwise membrane protein sequence alignments. We tested various strategies using a specifically designed program called AlignMe. An updated set of homologous membrane protein structures, called HOMEP2, was used as a reference for optimizing the gap penalties. The best of the membrane-protein optimized approaches were then tested on an independent reference set of membrane protein sequence alignments from the BAliBASE collection. When secondary structure (S) matching was combined with evolutionary information (using a position-specific substitution matrix (P)), in an approach we called AlignMePS, the resultant pairwise alignments were typically among the most accurate over a broad range of sequence similarities when compared to available methods. Matching transmembrane predictions (T), in addition to evolutionary information, and secondary-structure predictions, in an approach called AlignMePST, generally reduces the accuracy of the alignments of closely-related proteins in the BAliBASE set relative to AlignMePS, but may be useful in cases of extremely distantly related proteins for which sequence information is less informative. The open source AlignMe code is available at https://sourceforge.net/projects/alignme/, and at http://www.forrestlab.org, along with an online server and the HOMEP2 data set.     

Divergent evolution within protein superfolds inferred from profile-based phylogenetics

Many dissimilar protein sequences fold into similar structures. A central and persistent challenge facing protein structural analysis is the discrimination between homology and convergence for structurally similar domains that lack significant sequence similarity. Classic examples are the OB-fold and SH3 domains, both small, modular beta-barrel protein superfolds. The similarities among these domains have variously been attributed to common descent or to convergent evolution. Using a sequence profile-based phylogenetic technique, we analyzed all structurally characterized OB-fold, SH3, and PDZ domains with less than 40% mutual sequence identity. An all-against-all, profile-versus-profile analysis of these domains revealed many previously undetectable significant interrelationships. The matrices of scores were used to infer phylogenies based on our derivation of the relationships between sequence similarity E-values and evolutionary distances. The resulting clades of domains correlate remarkably well with biological function, as opposed to structural similarity, indicating that the functionally distinct sub-families within these superfolds are homologous. This method extends phylogenetics into the challenging "twilight zone" of sequence similarity, providing the first objective resolution of deep evolutionary relationships among distant protein families.     

Protein backbone structure determination using only residual dipolar couplings from one ordering medium

Residual dipolar couplings provide significant structural information for proteins in the solution state, which makes them attractive for the rapid determination of protein folds. Unfortunately, dipolar couplings contain inherent structural ambiguities which make them difficult to use in the absence of additional information. In this paper, we describe an approach to the construction of protein backbone folds using experimental dipolar couplings based on a bounded tree search through a structural database. We filter out false positives via an overlap similarity measure that insists that protein fragments assigned to overlapping regions of the sequence must have self-consistent structures. This allows us to determine a backbone fold (including the correct C-C bond orientations) using only residual dipolar coupling data obtained from one ordering medium. We demonstrate the applicability of the method using experimental data for ubiquitin.     

Use of a structural alphabet to find compatible folds for amino acid sequences

The structural annotation of proteins with no detectable homologs of known 3D structure identified using sequence‐search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino‐acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as “Protein Blocks” (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence‐search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z‐score cutoff that achieved 95% specificity (i.e., less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2%, respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologs in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales‐up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web‐server that is freely available at http://www.bo‐protscience.fr/forsa .     

A bioinformatics classifier and database for heme-copper oxygen reductases

Background

Heme-copper oxygen reductases (HCOs) are the last enzymatic complexes of most aerobic respiratory chains, reducing dioxygen to water and translocating up to four protons across the inner mitochondrial membrane (eukaryotes) or cytoplasmatic membrane (prokaryotes). The number of completely sequenced genomes is expanding exponentially, and concomitantly, the number and taxonomic distribution of HCO sequences. These enzymes were initially classified into three different types being this classification recently challenged.

Methodology

We reanalyzed the classification scheme and developed a new bioinformatics classifier for the HCO and Nitric oxide reductases (NOR), which we benchmark against a manually derived gold standard sequence set. It is able to classify any given sequence of subunit I from HCO and NOR with a global recall and precision both of 99.8%. We use this tool to classify this protein family in 552 completely sequenced genomes.

Conclusions

We concluded that the new and broader data set supports three functional and evolutionary groups of HCOs. Homology between NORs and HCOs is shown and NORs closest relationship with C Type HCOs demonstrated. We established and made available a classification web tool and an integrated Heme-Copper Oxygen reductase and NOR protein database (www.evocell.org/hco).     

DisCons: a novel tool to quantify and classify evolutionary conservation of intrinsic protein disorder

Background

Analyzing the amino acid sequence of an intrinsically disordered protein (IDP) in an evolutionary context can yield novel insights on the functional role of disordered regions and sequence element(s). However, in the case of many IDPs, the lack of evolutionary conservation of the primary sequence can hamper the study of functionality, because the conservation of their disorder profile and ensuing function(s) may not appear in a traditional analysis of the evolutionary history of the protein.

Results

Here we present DisCons (Disorder Conservation), a novel pipelined tool that combines the quantification of sequence- and disorder conservation to classify disordered residue positions. According to this scheme, the most interesting categories (for functional purposes) are constrained disordered residues and flexible disordered residues. The former residues show conservation of both the sequence and the property of disorder and are associated mainly with specific binding functionalities (e.g., short, linear motifs, SLiMs), whereas the latter class correspond to segments where disorder as a feature is important for function as opposed to the identity of the underlying sequence (e.g., entropic chains and linkers). DisCons therefore helps with elucidating the function(s) arising from the disordered state by analyzing individual proteins as well as large-scale proteomics datasets.

Conclusions

DisCons is an openly accessible sequence analysis tool that identifies and highlights structurally disordered segments of proteins where the conformational flexibility is conserved across homologs, and therefore potentially functional. The tool is freely available both as a web application and as stand-alone source code hosted at http://pedb.vib.be/discons.     

Structural and histone binding ability characterizations of human PWWP domains

Background

The PWWP domain was first identified as a structural motif of 100–130 amino acids in the WHSC1 protein and predicted to be a protein-protein interaction domain. It belongs to the Tudor domain ‘Royal Family’, which consists of Tudor, chromodomain, MBT and PWWP domains. While Tudor, chromodomain and MBT domains have long been known to bind methylated histones, PWWP was shown to exhibit histone binding ability only until recently.

Methodology/Principal Findings

The PWWP domain has been shown to be a DNA binding domain, but sequence analysis and previous structural studies show that the PWWP domain exhibits significant similarity to other ‘Royal Family’ members, implying that the PWWP domain has the potential to bind histones. In order to further explore the function of the PWWP domain, we used the protein family approach to determine the crystal structures of the PWWP domains from seven different human proteins. Our fluorescence polarization binding studies show that PWWP domains have weak histone binding ability, which is also confirmed by our NMR titration experiments. Furthermore, we determined the crystal structures of the BRPF1 PWWP domain in complex with H3K36me3, and HDGF2 PWWP domain in complex with H3K79me3 and H4K20me3.

Conclusions

PWWP proteins constitute a new family of methyl lysine histone binders. The PWWP domain consists of three motifs: a canonical β-barrel core, an insertion motif between the second and third β-strands and a C-terminal α-helix bundle. Both the canonical β-barrel core and the insertion motif are directly involved in histone binding. The PWWP domain has been previously shown to be a DNA binding domain. Therefore, the PWWP domain exhibits dual functions: binding both DNA and methyllysine histones.

Enhanced version

This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.     

Complete protein structure determination using backbone residual dipolar couplings and sidechain rotamer prediction

Residual dipolar couplings provide significant structural information for proteins in the solution state, which makes them attractive for the rapid determination of protein structures. While dipolar couplings contain inherent structural ambiguities, these can be reduced via an overlap similarity measure that insists that protein fragments assigned to overlapping regions of the sequence must have self-consistent structures. This allows us to determine a backbone fold (including the correct C–C bond orientations) using only residual dipolar coupling data from one ordering medium. The resulting backbone structures are of sufficient quality to allow for modeling of sidechain rotamer states using a rotamer prediction algorithm and a force field employing the Surface Generalized Born continuum solvation model. We demonstrate the applicability of the method using experimental data for ubiquitin. These results illustrate the synergies that are possible between protein structural database and molecular modeling methods and NMR spectroscopy, and we expect that the further development of these methods will lead to the extraction of high resolution structural information from minimal NMR data.     

Determination of Molecular Structures of HIV Envelope Glycoproteins using Cryo-Electron Tomography and Automated Sub-tomogram Averaging

Since its discovery nearly 30 years ago, more than 60 million people have been infected with the human immunodeficiency virus (HIV) (www.usaid.gov). The virus infects and destroys CD4+ T-cells thereby crippling the immune system, and causing an acquired immunodeficiency syndrome (AIDS) ². Infection begins when the HIV Envelope glycoprotein "spike" makes contact with the CD4 receptor on the surface of the CD4+ T-cell. This interaction induces a conformational change in the spike, which promotes interaction with a second cell surface co-receptor ^5,9. The significance of these protein interactions in the HIV infection pathway makes them of profound importance in fundamental HIV research, and in the pursuit of an HIV vaccine.The need to better understand the molecular-scale interactions of HIV cell contact and neutralization motivated the development of a technique to determine the structures of the HIV spike interacting with cell surface receptor proteins and molecules that block infection. Using cryo-electron tomography and 3D image processing, we recently demonstrated the ability to determine such structures on the surface of native virus, at ˜20 Å resolution ^9,14. This approach is not limited to resolving HIV Envelope structures, and can be extended to other viral membrane proteins and proteins reconstituted on a liposome. In this protocol, we describe how to obtain structures of HIV envelope glycoproteins starting from purified HIV virions and proceeding stepwise through preparing vitrified samples, collecting, cryo-electron microscopy data, reconstituting and processing 3D data volumes, averaging and classifying 3D protein subvolumes, and interpreting results to produce a protein model. The computational aspects of our approach were adapted into modules that can be accessed and executed remotely using the Biowulf GNU/Linux parallel processing cluster at the NIH (http://biowulf.nih.gov). This remote access, combined with low-cost computer hardware and high-speed network access, has made possible the involvement of researchers and students working from school or home.Download video file.^{(47M, mov)}     

Geometry motivated alternative view on local protein backbone structures

We present an alternative to the classical Ramachandran plot (R-plot) to display local protein backbone structure. Instead of the (ϕ, ψ)-backbone angles relating to the chemical architecture of polypeptides generic helical parameters are used. These are the rotation or twist angle ϑ and the helical rise parameter d. Plots with these parameters provide a different view on the nature of local protein backbone structures. It allows to display the local structures in polar (d, ϑ)-coordinates, which is not possible for an R-plot, where structural regimes connected by periodicity appear disconnected. But there are other advantages, like a clear discrimination of the handedness of a local structure, a larger spread of the different local structure domains—the latter can yield a better separation of different local secondary structure motives—and many more. Compared to the R-plot we are not aware of any major disadvantage to classify local polypeptide structures with the (d, ϑ)-plot, except that it requires some elementary computations. To facilitate usage of the new (d, ϑ)-plot for protein structures we provide a web application (http://agknapp.chemie.fu-berlin.de/secsass), which shows the (d, ϑ)-plot side-by-side with the R-plot.     

A phase II, randomized study on an investigational DTPw-HBV/Hib-MenAC conjugate vaccine administered to infants in Northern Ghana

Background

Combining meningococcal vaccination with routine immunization in infancy may reduce the burden of meningococcal meningitis, especially in the meningitis belt of Africa. We have evaluated the immunogenicity, persistence of immune response, immune memory and safety of an investigational DTPw-HBV/Hib-MenAC conjugate vaccine given to infants in Northern Ghana.

Methods and Findings

In this phase II, double blind, randomized, controlled study, 280 infants were primed with DTPw-HBV/Hib-MenAC or DTPw-HBV/Hib vaccines at 6, 10 and 14 weeks of age. At 12 months of age, children in each group received a challenge dose of serogroup A+C polysaccharides. Antibody responses were assessed pre, and one month-post dose 3 of the priming schedule and pre and 1 month after administration of the challenge dose. One month post-dose 3, 87.8% and 88.2% of subjects in the study group had bactericidal meningococcal serogroup A (SBA-MenA) and meningococcal serogroup C (SBA-MenC) antibody titres ≥1∶8 respectively. Seroprotection/seropositivity rates to the 5 antigens administered in the routine EPI schedule were non-inferior in children in the study group compared to those in the control group. The percentages of subjects in the study group with persisting SBA-MenA titres ≥ 1∶8 or SBA-MenC titres ≥1∶8 at the age of 12 months prior to challenge were significantly higher than in control group (47.7% vs 25.7% and 56.4% vs 5.1% respectively). The administration of 10 μg of serogroup A polysaccharide increased the SBA-MenA GMT by 14.0-fold in the DTPW-HBV/HibMenAC-group compared to a 3.8 fold increase in the control-group. Corresponding fold-increases in SBA-MenC titres following challenge with 10 μg of group C polysaccharide were 18.8 and 1.9 respectively. Reactogenicity following primary vaccination or the administration of the challenge dose was similar in both groups, except for swelling (Grade 3) after primary vaccination which was more frequent in children in the vaccine than in the control group (23.7%; 95%CI [19.6–28.1] of doses vs 14.1%; 95% CI [10.9–17.8] of doses). Fifty-nine SAEs (including 8 deaths), none of them related to vaccination, were reported during the entire study.

Conclusions

Three dose primary vaccination with DTPw-HBV/Hib-MenAC was non-inferior to DTPw-HBV/Hib for the 5 common antigens used in the routine EPI schedule and induced bactericidal antibodies against Neisseria meningitidis of serogroups A and C in the majority of infants. Serogroup A and C bactericidal antibody levels had fallen below titres associated with protection in nearly half of the infants by the age of 12 months confirming that a booster dose is required at about that age. An enhanced memory response was shown after polysaccharide challenge. This vaccine could provide protection against 7 important childhood diseases (including meningococcal A and C) and be of particular value in countries of the African meningitis belt.

Trial Registration

Controlled-Trials.com ISRCTN35754083     

SMpred: a support vector machine approach to identify structural motifs in protein structure without using evolutionary information

Knowledge of three dimensional structure is essential to understand the function of a protein. Although the overall fold is made from the whole details of its sequence, a small group of residues, often called as structural motifs, play a crucial role in determining the protein fold and its stability. Identification of such structural motifs requires sufficient number of sequence and structural homologs to define conservation and evolutionary information. Unfortunately, there are many structures in the protein structure databases have no homologous structures or sequences. In this work, we report an SVM method, SMpred, to identify structural motifs from single protein structure without using sequence and structural homologs. SMpred method was trained and tested using 132 proteins domains containing 581 motifs. SMpred method achieved 78.79% accuracy with 79.06% sensitivity and 78.53% specificity. The performance of SMpred was evaluated with MegaMotifBase using 188 proteins containing 1161 motifs. Out of 1161 motifs, SMpred correctly identified 1503 structural motifs reported in MegaMotifBase. Further, we showed that SMpred is useful approach for the length deviant superfamilies and single member superfamilies. This result suggests the usefulness of our approach for facilitating the identification of structural motifs in protein structure in the absence of sequence and structural homologs. The dataset and executable for the SMpred algorithm is available at http://www3.ntu.edu.sg/home/EPNSugan/index_files/SMpred.htm.     

A Novel Role of the N Terminus of Budding Yeast Histone H3 Variant Cse4 in Ubiquitin-Mediated Proteolysis

Understanding the molecular basis of common traits is a primary challenge of modern genetics. One model holds that rare mutations in many genetic backgrounds may often phenocopy one another, together explaining the prevalence of the resulting trait in the population. For the vast majority of phenotypes, the role of rare variants and the evolutionary forces that underlie them are unknown. In this work, we use a population of Saccharomyces paradoxus yeast as a model system for the study of common trait variation. We observed an unusual, flocculation and invasive-growth phenotype in one-third of S. paradoxus strains, which were otherwise unrelated. In crosses with each strain in turn, these morphologies segregated as a recessive Mendelian phenotype, mapping either to IRA1 or to IRA2, yeast homologs of the hypermutable human neurofibromatosis gene NF1. The causal IRA1 and IRA2 haplotypes were of distinct evolutionary origin and, in addition to their morphological effects, associated with hundreds of stress-resistance and growth traits, both beneficial and disadvantageous, across S. paradoxus. Single-gene molecular genetic analyses confirmed variant IRA1 and IRA2 haplotypes as causal for these growth characteristics, many of which were independent of morphology. Our data make clear that common growth and morphology traits in yeast result from a suite of variants in master regulators, which function as a mutation-driven switch between phenotypic states.     

Near-native protein loop sampling using nonparametric density estimation accommodating sparcity

Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM) has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM). Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD <2.0 Å), the DPM-HMM method performs as well or better than the best templates, demonstrating that our automated method recaptures these canonical loops without inclusion of any IgG specific terms or manual intervention. In cases with poor or few good templates (mean RMSD >7.0 Å), this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.