Accelerating protein docking in ZDOCK using an advanced 3D convolution library

Computational prediction of the 3D structures of molecular interactions is a challenging area, often requiring significant computational resources to produce structural predictions with atomic-level accuracy. This can be particularly burdensome when modeling large sets of interactions, macromolecular assemblies, or interactions between flexible proteins. We previously developed a protein docking program, ZDOCK, which uses a fast Fourier transform to perform a 3D search of the spatial degrees of freedom between two molecules. By utilizing a pairwise statistical potential in the ZDOCK scoring function, there were notable gains in docking accuracy over previous versions, but this improvement in accuracy came at a substantial computational cost. In this study, we incorporated a recently developed 3D convolution library into ZDOCK, and additionally modified ZDOCK to dynamically orient the input proteins for more efficient convolution. These modifications resulted in an average of over 8.5-fold improvement in running time when tested on 176 cases in a newly released protein docking benchmark, as well as substantially less memory usage, with no loss in docking accuracy. We also applied these improvements to a previous version of ZDOCK that uses a simpler non-pairwise atomic potential, yielding an average speed improvement of over 5-fold on the docking benchmark, while maintaining predictive success. This permits the utilization of ZDOCK for more intensive tasks such as docking flexible molecules and modeling of interactomes, and can be run more readily by those with limited computational resources

Computational design of the affinity and specificity of a therapeutic T cell receptor

T cell receptors (TCRs) are key to antigen-specific immunity and are increasingly being explored as therapeutics, most visibly in cancer immunotherapy. As TCRs typically possess only low-to-moderate affinity for their peptide/MHC (pMHC) ligands, there is a recognized need to develop affinity-enhanced TCR variants. Previous in vitro engineering efforts have yielded remarkable improvements in TCR affinity, yet concerns exist about the maintenance of peptide specificity and the biological impacts of ultra-high affinity. As opposed to in vitro engineering, computational design can directly address these issues, in theory permitting the rational control of peptide specificity together with relatively controlled increments in affinity. Here we explored the efficacy of computational design with the clinically relevant TCR DMF5, which recognizes nonameric and decameric epitopes from the melanoma-associated Melan-A/MART-1 protein presented by the class I MHC HLA-A2. We tested multiple mutations selected by flexible and rigid modeling protocols, assessed impacts on affinity and specificity, and utilized the data to examine and improve algorithmic performance. We identified multiple mutations that improved binding affinity, and characterized the structure, affinity, and binding kinetics of a previously reported double mutant that exhibits an impressive 400-fold affinity improvement for the decameric pMHC ligand without detectable binding to non-cognate ligands. The structure of this high affinity mutant indicated very little conformational consequences and emphasized the high fidelity of our modeling procedure. Overall, our work showcases the capability of computational design to generate TCRs with improved pMHC affinities while explicitly accounting for peptide specificity, as well as its potential for generating TCRs with customized antigen targeting capabilities

Rational Design of an Epitope-Based Hepatitis C Virus Vaccine

Despite improving treatment methods and therapeutic options, hepatitis C virus (HCV) remains a major global disease burden, and a vaccine would help greatly in reducing its incidence. Due to its extremely high sequence variability, HCV can readily escape the immune response, thus a vaccine must elicit an immune response toward conserved, functionally important epitopes. Using structural data of the broadly neutralizing antibody HCV1 in complex with a conserved linear epitope from the HCV E2 protein (aa 412-423, referred to as epitope I or domain E), we performed structure-based design to generate vaccine immunogens to induce antibody responses to this epitope. Designs selected for immunological characterization included a stabilized minimal epitope structure based on a defensin protein, as well as a bivalent vaccine featuring two copies of epitope I on the E2 surface. In vivo studies confirmed that these designs successfully generated robust antibody responses to this epitope, and sera from vaccinated mice neutralized HCV. In addition to presenting several effective HCV vaccine immunogens, this study demonstrates that induction of neutralizing anti-HCV antibodies is possible using an epitope-based vaccine, providing the basis for further efforts in structure-based vaccine design to target this and other critical epitopes of HCV

Reduced primary patency rate in diabetic patients after percutaneous intervention results from more frequent presentation with limb-threatening ischemia

ObjectiveAlthough patients with diabetes are at increased risk of amputation from peripheral vascular disease, excellent limb-salvage rates have been achieved with aggressive surgical revascularization. It is less clear whether patients with diabetes will fare as well as nondiabetics after undergoing percutaneous lower extremity revascularization, a modality which is becoming increasingly utilized for this disease process. This study aimed to assess differential outcomes in between diabetics and nondiabetics in lower extremity percutaneous interventions.MethodsWe retrospectively studied 291 patients with respect to patient variables, complications, and outcomes for percutaneous interventions performed for peripheral occlusive disease between 2002 and 2005. Tibial vessel run-off was assessed by angiography. Patency (assessed arterial duplex) was expressed by Kaplan-Meier method and log-rank analysis. Mean follow-up was 11.6 months (range 1 to 56 months).ResultsA total of 385 interventions for peripheral occlusive disease with claudication (52.2%), rest pain (16.4%), or tissue loss (31.4%) were analyzed, including 336 primary interventions and 49 reinterventions (mean patient age 73.9 years, 50.8% male). Comorbidities included diabetes mellitus (57.2%), chronic renal insufficiency (18.4%), hemodialysis (3.8%), hypertension (81.9%), hypercholesterolemia (57%), coronary artery disease (58%), tobacco use (63.2%). Diabetics were significantly more likely to be female (55.3% vs 40.8%), and suffer from CRI (23.5% vs 12.0%), a history of myocardial infarction (36.5% vs 18.0%), and <three-vessel tibial outflow (83.5% vs 71.8%), compared with nondiabetics, although all other comorbidities and lesion characteristics were equivalent between these groups. Overall primary patency (± SE) at 6, 12, and 18 months was 85 ± 2%, 63 ± 3% and 56 ± 4%, respectively. Patients with diabetes suffered reduced primary patency at 1 year compared with nondiabetics. For nondiabetics, primary patency was 88 ± 2%, 71 ± 4%, and 58 ± 4% at 6, 12, and 18 months, while for diabetics it was 82 ± 2%, 53 ± 4%, and 49 ± 4%, respectively (P = .05). Overall secondary patency at 6, 12, and 18 months was 88 ± 2%, 76 ± 3%, and 69 ± 3%, and did not vary by diabetes status. One-year limb salvage rate was 88.3% for patients with limb-threatening ischemia, which was also similar between diabetics and nondiabetics. While univariate analysis revealed that female gender, <three-vessel tibial outflow, and a history of tobacco use were all predictive of reduced primary patency (P < .05), none of these factors significantly impacted secondary patency or limb-salvage rate. Furthermore, only limb-threatening ischemia remained a significant predictor of outcome on multivariate analysis, suggesting that the poorer primary patency in diabetics is related primarily to their propensity to present with limb-threatening disease compared with nondiabetics.ConclusionPatients with diabetes demonstrate reduced primary patency rates after percutaneous treatment of lower extremity occlusive disease, most likely due to their advanced stage of disease at presentation. However, despite a higher reintervention rate, diabetics and others with risk factors predictive of reduced primary patency can attain equivalent short-term secondary patency and limb-salvage rates. Therefore, these patient characteristics should not be considered contraindications to endovascular therapy

Structure-based Design of Broadly Neutralizing HCV Antibody and Vaccine

Hepatitis C virus (HCV) chronically infects nearly 200 million people worldwide. Antibodies have the potential to prevent establishment of chronic HCV infection in individuals exposed to the virus. Several broadly neutralizing monoclonal antibodies capable of binding HCV surface glycoproteins have been identified, including HCV1 identified by MassBiologics at UMMS, which targets a highly conserved linear epitope. We utilized the recently solved structure of the HCV1-bound epitope to identify regions of the antibody that could be modified to potentially improve binding to a mutation (N415K) which facilitates escape from neutralization. Based on systematic in silico mutagenesis of HCV1 residues in the Rosetta protein modeling program, a number of single or double antibody mutants were selected for in vitro evaluation. The mutated antibodies were synthesized and their ability to neutralize HCV pseudoviruses expressing either wild-type epitope sequence or the N415K variant was evaluated. Antibodies with mutations on the heavy chain, R65Q and V50L, demonstrated improved neutralizing activity against the N415K escape mutant without impacting their ability to neutralize wild type virus. We also sought to design a novel HCV vaccine that could focus the response to a small conserved neutralizing epitope of the virus defined by HCV1. The HCV1 epitope structure was used to search a large dataset of known protein structures from the Protein Data Bank, resulting in designs of scaffolds that were predicted to stably accommodate the epitope. These epitope-presenting scaffold proteins have been made and will be screened in animal studies to determine their potential as vaccine candidates for HCV prevention

How structural adaptability exists alongside HLA-A2 bias in the human alphabeta TCR repertoire

How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining alphabeta TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged hot-spot region that is almost exclusive to the alpha1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Valpha and Vbeta genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs

Exploring the DNA-recognition potential of homeodomains

The recognition potential of most families of DNA-binding domains (DBDs) remains relatively unexplored. Homeodomains (HDs), like many other families of DBDs, display limited diversity in their preferred recognition sequences. To explore the recognition potential of HDs, we utilized a bacterial selection system to isolate HD variants, from a randomized library, that are compatible with each of the 64 possible 3′ triplet sites (i.e., TAANNN). The majority of these selections yielded sets of HDs with overrepresented residues at specific recognition positions, implying the selection of specific binders. The DNA-binding specificity of 151 representative HD variants was subsequently characterized, identifying HDs that preferentially recognize 44 of these target sites. Many of these variants contain novel combinations of specificity determinants that are uncommon or absent in extant HDs. These novel determinants, when grafted into different HD backbones, produce a corresponding alteration in specificity. This information was used to create more explicit HD recognition models, which can inform the prediction of transcriptional regulatory networks for extant HDs or the engineering of HDs with novel DNA-recognition potential. The diversity of recovered HD recognition sequences raises important questions about the fitness barrier that restricts the evolution of alternate recognition modalities in natural systems

The Missing Heritability in T1D and Potential New Targets for Prevention

Type 1 diabetes (T1D) is a T cell-mediated disease. It is strongly associated with susceptibility haplotypes within the major histocompatibility complex, but this association accounts for an estimated 50% of susceptibility. Other studies have identified as many as 50 additional susceptibility loci, but the effect of most is very modest (odds ratio (OR) 5) and that deletion of V beta 13+ T cells prevents diabetes. A role for the TCR is also suspected in NOD mice, but TCR regions have not been associated with human T1D. To investigate this disparity, we tested the hypothesis in silico that previous studies of human T1D genetics were underpowered to detect MHC-contingent TCR susceptibility. We show that stratifying by MHC markedly increases statistical power to detect potential TCR susceptibility alleles. We suggest that the TCR regions are viable candidates for T1D susceptibility genes, could account for missing heritability, and could be targets for prevention

Updates to the Integrated Protein–Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2

We present an updated and integrated version of our widely used protein–protein docking and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality structures of protein–protein complexes along with the unbound structures of their components. Fifty-five new complexes were added to the docking benchmark, 35 of which have experimentally measured binding affinities. These updated docking and affinity benchmarks now contain 230 and 179 entries, respectively. In particular, the number of antibody–antigen complexes has increased significantly, by 67% and 74% in the docking and affinity benchmarks, respectively. We tested previously developed docking and affinity prediction algorithms on the new cases. Considering only the top 10 docking predictions per benchmark case, a prediction accuracy of 38% is achieved on all 55 cases and up to 50% for the 32 rigid-body cases only. Predicted affinity scores are found to correlate with experimental binding energies up to r = 0.52 overall and r = 0.72 for the rigid complexes.Peer ReviewedPostprint (author's final draft