Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins

A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed

Structural Model of the Rev Regulatory Protein from Equine Infectious Anemia Virus

Rev is an essential regulatory protein in the equine infectious anemia virus (EIAV) and other lentiviruses, including HIV-1. It binds incompletely spliced viral mRNAs and shuttles them from the nucleus to the cytoplasm, a critical prerequisite for the production of viral structural proteins and genomic RNA. Despite its important role in production of infectious virus, the development of antiviral therapies directed against Rev has been hampered by the lack of an experimentally-determined structure of the full length protein. We have used a combined computational and biochemical approach to generate and evaluate a structural model of the Rev protein. The modeled EIAV Rev (ERev) structure includes a total of 6 helices, four of which form an anti-parallel four-helix bundle. The first helix contains the leucine-rich nuclear export signal (NES). An arginine-rich RNA binding motif, RRDRW, is located in a solvent-exposed loop region. An ERLE motif required for Rev activity is predicted to be buried in the core of modeled structure where it plays an essential role in stabilization of the Rev fold. This structural model is supported by existing genetic and functional data as well as by targeted mutagenesis of residues predicted to be essential for overall structural integrity. Our predicted structure should increase understanding of structure-function relationships in Rev and may provide a basis for the design of new therapies for lentiviral diseases

Interaction Pattern of Arg 62 in the A-Pocket of Differentially Disease-Associated HLA-B27 Subtypes Suggests Distinct TCR Binding Modes

The single amino acid replacement Asp116His distinguishes the two subtypes HLA-B*2705 and HLA-B*2709 which are, respectively, associated and non-associated with Ankylosing Spondylitis, an autoimmune chronic inflammatory disease. The reason for this differential association is so far poorly understood and might be related to subtype-specific HLA:peptide conformations as well as to subtype/peptide-dependent dynamical properties on the nanoscale. Here, we combine functional experiments with extensive molecular dynamics simulations to investigate the molecular dynamics and function of the conserved Arg62 of the α1-helix for both B27 subtypes in complex with the self-peptides pVIPR (RRKWRRWHL) and TIS (RRLPIFSRL), and the viral peptides pLMP2 (RRRWRRLTV) and NPflu (SRYWAIRTR). Simulations of HLA:peptide systems suggest that peptide-stabilizing interactions of the Arg62 residue observed in crystal structures are metastable for both B27 subtypes under physiological conditions, rendering this arginine solvent-exposed and, probably, a key residue for TCR interaction more than peptide-binding. This view is supported by functional experiments with conservative (R62K) and non-conservative (R62A) B*2705 and B*2709 mutants that showed an overall reduction in their capability to present peptides to CD8+ T cells. Moreover, major subtype-dependent differences in the peptide recognition suggest distinct TCR binding modes for the B*2705 versus the B*2709 subtype

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/

Allele-dependent Similarity between Viral and Self-peptide Presentation by HLA-B27 Subtypes.

Molecular mimicry is discussed as a possible mechanism that may contribute to the development of autoimmune diseases. It could also be involved in the differential association of the human major histocompatibility subtypes HLA-B*2705 and HLA-B*2709 with ankylosing spondylitis. These two subtypes differ only in residue 116 of the heavy chain (Asp in B*2705 and His in B*2709), but the reason for the differential disease association is not understood. Using x-ray crystallography, we show here that the viral peptide pLMP2 (RRRWRRLTV, derived from latent membrane protein 2 (residues 236–244) of Epstein-Barr virus) is presented by the B*2705 and B*2709 molecules in two drastically deviating conformations. Extensive structural similarity between pLMP2 and the self-peptide pVIPR (RRKWRRWHL, derived from vasoactive intestinal peptide type 1 receptor (residues 400–408)) is observed only when the peptides are presented by B*2705 because of a salt bridge between Arg5 of both peptides and the subtype-specific heavy chain residue Asp116. Combined with functional studies using pLMP2/pVIPR-cross-reactive cytotoxic T cell lines and clones, together with target cells presenting these peptides or a modified peptide analogue, our results reveal that a pathogen-derived peptide can exhibit major histocompatibility complex class I subtype-dependent, drastically distinct binding modes. Furthermore, the results demonstrate that molecular mimicry between pLMP2 and pVIPR in the HLA-B27 context is an allele-dependent property

An engineered lipocalin specific for CTLA-4 reveals a combining site with structural and conformational features similar to antibodies

Biomolecular reagents that enable the specific molecular recognition of proteins play a crucial role in basic research as well as medicine. Up to now, antibodies (immunoglobulins) have been widely used for this purpose. Their predominant feature is the vast repertoire of antigen-binding sites that arise from a set of 6 hypervariable loops. However, antibodies suffer from practical disadvantages because of their complicated architecture, large size, and multiple functions. The lipocalins, on the other hand, have evolved as a protein family that primarily serves for the binding of small molecules. Here, we show that an engineered lipocalin, derived from human Lcn2, can specifically bind the T cell coreceptor CTLA-4 as a prescribed protein target with subnanomolar affinity. Crystallographic analysis reveals that its reshaped cup-like binding site, which is formed by 4 variable loops, provides perfect structural complementarity with this “antigen.” Furthermore, comparison with the crystal structure of the uncomplexed engineered lipocalin indicates a pronounced induced-fit mechanism, a phenomenon so far considered typical for antibodies. By recognizing the same epitope on CTLA-4 that interacts with the counterreceptors B7.1/B7.2 on antigen-presenting cells the engineered Lcn2 exhibits strong, cross-species antagonistic activity, as evidenced by biological effects comparable with a CTLA-4-specific antibody. With its proven stimulatory activity on T cells in vivo, the CTLA-4 blocking lipocalin offers potential for immunotherapy of cancer and infectious disease. Beyond that, lipocalins with engineered antigen-binding sites, so-called Anticalins, provide a class of small (≈180 residues), structurally simple, and robust binding proteins with applications in the life sciences in general