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Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study.

ABSTRACT: BACKGROUND:Human leukocyte antigen (HLA) surface proteins are directly involved in idiosyncratic adverse drug reactions. Herein, we present a structure-based analysis of the common HLA-B*57:01 variant known to be responsible for several HLA-linked adverse effects such as the abacavir hypersensitivity syndrome. METHODS:First, we analyzed three X-ray crystal structures involving the HLA-B*57:01 protein variant, the anti-HIV drug abacavir, and different co-binding peptides present in the antigen-binding cleft. We superimposed the three complexes and showed that abacavir had no significant conformational variation whatever the co-binding peptide. Second, we self-docked abacavir in the HLA-B*57:01 antigen binding cleft with and without peptide using Glide. Third, we docked a small test set of 13 drugs with known ADRs and suspected HLA associations. RESULTS:In the presence of an endogenous co-binding peptide, we found a significant stabilization (~2 kcal/mol) of the docking scores and identified several modified abacavir-peptide interactions indicating that the peptide does play a role in stabilizing the HLA-abacavir complex. Next, our model was used to dock a test set of 13 drugs at HLA-B*57:01 and measured their predicted binding affinities. Drug-specific interactions were observed at the antigen-binding cleft and we were able to discriminate the compounds with known HLA-B*57:01 liability from inactives. CONCLUSIONS:Overall, our study highlights the relevance of molecular docking for evaluating and analyzing complex HLA-drug interactions. This is particularly important for virtual drug screening over thousands of HLA variants as other experimental techniques (e.g., in vitro HTS) and computational approaches (e.g., molecular dynamics) are more time consuming and expensive to conduct. As the attention for drugs' HLA liability is on the rise, we believe this work participates in encouraging the use of molecular modeling for reliably studying and predicting HLA-drug interactions. Graphical abstract.

SUBMITTER: Van Den Driessche G

PROVIDER: S-EPMC5337232 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study.

Van Den Driessche George G Fourches Denis D

Journal of cheminformatics 20170304

<h4>Background</h4>Human leukocyte antigen (HLA) surface proteins are directly involved in idiosyncratic adverse drug reactions. Herein, we present a structure-based analysis of the common HLA-B*57:01 variant known to be responsible for several HLA-linked adverse effects such as the abacavir hypersensitivity syndrome.<h4>Methods</h4>First, we analyzed three X-ray crystal structures involving the HLA-B*57:01 protein variant, the anti-HIV drug abacavir, and different co-binding peptides present in ...[more]

PMID: 28303164

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Project description:BACKGROUND:Idiosyncratic adverse drug reactions have been linked to a drug's ability to bind with a human leukocyte antigen (HLA) protein. However, due to the thousands of HLA variants and limited structural data for drug-HLA complexes, predicting a specific drug-HLA combination represents a significant challenge. Recently, we investigated the binding mode of abacavir with the HLA-B*57:01 variant using molecular docking. Herein, we developed a new ensemble screening workflow involving three X-ray crystal derived docking procedures to screen the DrugBank database and identify potentially HLA-B*57:01 liable drugs. Then, we compared our workflow's performance with another model recently developed by Metushi et al., which proposed seven in silico HLA-B*57:01 actives, but were later found to be experimentally inactive. METHODS:After curation, there were over 6000 approved and experimental drugs remaining in DrugBank for docking using Schrodinger's GLIDE SP and XP scoring functions. Docking was performed with our new consensus-like ensemble workflow, relying on three different X-ray crystals (3VRI, 3VRJ, and 3UPR) in presence and absence of co-binding peptides. The binding modes of HLA-B*57:01 hit compounds for all three peptides were further explored using 3D interaction fingerprints and hierarchical clustering. RESULTS:The screening resulted in 22 hit compounds forecasted to bind HLA-B*57:01 in all docking conditions (SP and XP with and without peptides P1, P2, and P3). These 22 compounds afforded 2D-Tanimoto similarities being less than 0.6 when compared to the structure of native abacavir, whereas their 3D binding mode similarities varied in a broader range (0.2-0.8). Hierarchical clustering using a Ward Linkage revealed different clustering patterns for each co-binding peptide. When we docked Metushi et al.'s seven proposed hits using our workflow, our screening platform identified six out of seven as being inactive. Molecular dynamic simulations were used to explore the stability of abacavir and acyclovir in complex with peptide P3. CONCLUSIONS:This study reports on the extensive docking of the DrugBank database and the 22 HLA-B*57:01 liable candidates we identified. Importantly, comparisons between this study and the one by Metushi et al. highlighted new critical and complementary knowledge for the development of future HLA-specific in silico models.

Project description:Phenytoin (PHT) is one of the most commonly reported aromatic anti-epileptic drugs (AEDs) to cause cutaneous adverse reactions (CADRs), particularly severe cutaneous adverse reactions (SCARs). Although human leukocyte antigen (HLA)-B*15:02 is associated with PHT-induced Steven Johnson syndrome/toxic epidermal necrosis (SJS/TEN) in East Asians, the association is much weaker than it is reported for carbamazepine (CBZ). In this study, we investigated the association of pharmacogenetic variants of the HLA B gene and CYP2C9*3 with PHT-CADRs in South Indian epileptic patients. This prospective case-controlled study included 25 PHT-induced CADRs, 30 phenytoin-tolerant patients, and 463 (HLA-B) and 82 (CYP2C9*3) normal-controls from previous studies included for the case and normal-control comparison. Six SCARs cases and 19 mild-moderate reactions were observed among the 25 cases. Pooled data analysis was performed for the HLA B*51:01 and PHT-CADRs associations. The Fisher exact test and multivariate binary logistic regression analysis were used to identify the susceptible alleles associated with PHT-CADRs. Multivariate analysis showed that CYP2C9*3 was significantly associated with overall PHT-CADRs (OR = 12.00, 95% CI 2.759-84.87, p = 003). In subgroup analysis, CYP2C9*3 and HLA B*55:01 were found to be associated with PHT-SCARs (OR = 12.45, 95% CI 1.138-136.2, p = 0.003) and PHT-maculopapular exanthema (MPE) (OR = 4.041, 95% CI 1.125-15.67, p = 0.035), respectively. Pooled data analysis has confirmed the association between HLA B*51:01/PHT-SCARs (OR = 6.273, 95% CI 2.24-16.69, p = <0.001) and HLA B*51:01/PHT-overall CADRs (OR = 2.323, 95% CI 1.22-5.899, p = 0.037). In this study, neither the case nor the control groups had any patients with HLA B*15:02. The risk variables for PHT-SCARs, PHT-overall CADRs, and PHT-MPE were found to be HLA B*51:01, CYP2C9*3, and HLA B*55:01, respectively. These alleles were identified as the risk factors for the first time in the South Indian Tamil population for PHT-CADRs. Further investigation is warranted to establish the clinical relevance of these alleles in this population with larger sample size.

Project description:UnlabelledKiller cell immunoglobulin-like receptors (KIRs) play an important role in the activation of natural killer (NK) cells, which in turn contribute to the effective immune control of many viral infections. In the context of HIV infection, the closely related KIR3DL1 and KIR3DS1 molecules, in particular, have been associated with disease outcome. Inhibitory signals via KIR3DL1 are disrupted by downregulation of HLA class I ligands on the infected cell surface and can also be impacted by changes in the presented peptide repertoire. In contrast, the activatory ligands for KIR3DS1 remain obscure. We used a structure-driven approach to define the characteristics of HLA class I-restricted peptides that interact with KIR3DL1 and KIR3DS1. In the case of HLA-B*57:01, we used this knowledge to identify bona fide HIV-derived peptide epitopes with similar properties. Two such peptides facilitated productive interactions between HLA-B*57:01 and KIR3DS1. These data reveal the presence of KIR3DS1 ligands within the HIV-specific peptide repertoire presented by a protective HLA class I allotype, thereby enhancing our mechanistic understanding of the processes that enable NK cells to impact disease outcome.ImportanceNatural killer (NK) cells are implicated as determinants of immune control in many viral infections, but the precise molecular mechanisms that initiate and control these responses are unclear. The activating receptor KIR3DS1 in combination with HLA-Bw4 has been associated with better outcomes in HIV infection. However, evidence of a direct interaction between these molecules is lacking. In this study, we demonstrate that KIR3DS1 recognition of HLA-Bw4 is peptide dependent. We also identify HIV-derived peptide epitopes presented by the protective HLA-B*57:01 allotype that facilitate productive interactions with KIR3DS1. Collectively, these findings suggest a mechanism whereby changes in the peptide repertoire associated with viral infection provide a trigger for KIR3DS1 engagement and NK cell activation.

Project description:Adverse drug reactions have been linked with genetic polymorphisms in HLA genes in numerous different studies. HLA proteins have an essential role in the presentation of self and non-self peptides, as part of the adaptive immune response. Amongst the associated drugs-allele combinations, anti-HIV drug Abacavir has been shown to be associated with the HLA-B*57:01 allele, and anti-epilepsy drug Carbamazepine with B*15:02, in both cases likely following the altered peptide repertoire model of interaction. Under this model, the drug binds directly to the antigen presentation region, causing different self peptides to be presented, which trigger an unwanted immune response. There is growing interest in searching for evidence supporting this model for other ADRs using bioinformatics techniques. In this study, in silico docking was used to assess the utility and reliability of well-known docking programs when addressing these challenging HLA-drug situations. The overall aim was to address the uncertainty of docking programs giving different results by completing a detailed comparative study of docking software, grounded in the MHC-ligand experimental structural data - for Abacavir and to a lesser extent Carbamazepine - in order to assess their performance. Four docking programs: SwissDock, ROSIE, AutoDock Vina and AutoDockFR, were used to investigate if each software could accurately dock the Abacavir back into the crystal structure for the protein arising from the known risk allele, and if they were able to distinguish between the HLA-associated and non-HLA-associated (control) alleles. The impact of using homology models on the docking performance and how using different parameters, such as including receptor flexibility, affected the docking performance were also investigated to simulate the approach where a crystal structure for a given HLA allele may be unavailable. The programs that were best able to predict the binding position of Abacavir were then used to recreate the docking seen for Carbamazepine with B*15:02 and controls alleles. It was found that the programs investigated were sometimes able to correctly predict the binding mode of Abacavir with B*57:01 but not always. Each of the software packages that were assessed could predict the binding of Abacavir and Carbamazepine within the correct sub-pocket and, with the exception of ROSIE, was able to correctly distinguish between risk and control alleles. We found that docking to homology models could produce poorer quality predictions, especially when sequence differences impact the architecture of predicted binding pockets. Caution must therefore be used as inaccurate structures may lead to erroneous docking predictions. Incorporating receptor flexibility was found to negatively affect the docking performance for the examples investigated. Taken together, our findings help characterise the potential but also the limitations of computational prediction of drug-HLA interactions. These docking techniques should therefore always be used with care and alongside other methods of investigation, in order to be able to draw strong conclusions from the given results.

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Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study.

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Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study.

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