Human leukocyte antigen (HLA)-B27-positive subjects are uncommon in their ability to control infection with human immunodeficiency virus type 1 (HIV-1). However, late viral escape from a narrowly directed immunodominant Gag-specific CD8؉ T-lymphocyte (CTL) response has been linked to AIDS progression in these individuals. Identifying the mechanism of the immune-mediated control may provide critical insights into HIV-1 vaccine development. Here, we illustrate that the CTL escape mutation R 264 K in the HLA-B27-restricted KK10 epitope in the capsid resulted in a significant defect in viral replication in vitro. The R 264 K variant was impaired in generating late reverse transcription products, indicating that replication was blocked at a postentry step. Notably, the R 264 K mutation was associated in vivo with the development of a rare secondary mutation, S 173 A, which restored viral replication in vitro. Furthermore, infectivity of the R 264 K variant was rescued by the addition of cyclosporine A or infection of a cyclophilin A-deficient cell line. These data demonstrate a severe functional defect imposed by the R 264 K mutation during an early step in viral replication that is likely due to the inability of this variant to replicate efficiently in the presence of normal levels of cyclophilin A. We conclude that the impact of the R 264 K substitution on capsid structure constrains viral escape and enables long-term maintenance of the dominant CTL response against B27-KK10, providing an explanation for the protective effect of HLA-B27 during HIV infection.

With the burgeoning immunological data in the scientific literature, scientists must increasingly rely on Internet resources to inform and enhance their work. Here we provide a brief overview of the adaptive immune response and summaries of immunoinformatics resources, emphasizing those with Web interfaces. These resources include searchable databases of epitopes and immune-related molecules, and analysis tools for T cell and B cell epitope prediction, vaccine design, and protein structure comparisons. There is an agreeable synergy between the growing collections in immune-related databases and the growing sophistication of analysis software; the databases provide the foundation for developing predictive computational tools, which in turn enable more rapid identification of immune responses to populate the databases. Collectively, these resources contribute to improved understanding of immune responses and escape, and evolution of pathogens under immune pressure. The public health implications are vast, including designing vaccines, understanding autoimmune diseases, and defining the correlates of immune protection.

The relative contributions of HLA alleles and T-cell receptors (TCRs) to the prevention of mutational viral escape are unclear. Here, we examined human immunodeficiency virus type 1 (HIV-1)-specific CD8 ؉ T-cell responses restricted by two closely related HLA class I alleles, B*5701 and B*5703, that differ by two amino acids but are both associated with a dominant response to the same HIV-1 Gag epitope KF11 (KAFSPEVIP MF). When this epitope is presented by HLA-B*5701, it induces a TCR repertoire that is highly conserved among individuals, cross-recognizes viral epitope variants, and is rarely associated with mutational escape. In contrast, KF11 presented by HLA-B*5703 induces an entirely different, more heterogeneous TCR ␤-chain repertoire that fails to recognize specific KF11 escape variants which frequently arise in clade C-infected HLA-B*5703 ؉ individuals. These data show the influence of HLA allele subtypes on TCR selection and indicate that extensive TCR diversity is not a prerequisite to prevention of allowable viral mutations. Sequence mutations resulting in loss of recognition by CD8ϩ

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60–0.69 and 0.61–0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number of CPUs to tens of thousands of protein targets and millions of potential drug candidates.

We have examined cobalt based valence tautomer molecules such as Co(SQ)$_2$(phen) using density functional theory (DFT) and variational configuration interaction (VCI) approaches based upon a model Hamiltonian. Our DFT results extend earlier work by finding a reduced total energy gap (order 0.6 eV) between high temperature and low temperature states when we fully relax the coordinates (relative to experimental ones). Futhermore we demonstrate that the charge transfer picture based upon formal valence arguments succeeds qualitatively while failing quantitatively due to strong covalency between the Co 3$d$ orbitals and ligand $p$ orbitals. With the VCI approach, we argue that the high temperature, high spin phase is strongly mixed valent, with about 30 % admixture of Co(III) into the predominantly Co(II) ground state. We confirm this mixed valence through a fit to the XANES spectra. Moreover, the strong electron correlations of the mixed valent phase provide an energy lowering of about 0.2-0.3 eV of the high temperature phase relative to the low temperature one. Finally, we use the domain model to account for the extraordinarily large entropy and enthalpy values associated with the transition.Comment: 10 pages, 4 figures, submitted to J. Chem. Phy