Orthologue chemical space and its influence on target prediction

Motivation

In silico approaches often fail to utilize bioactivity data available for orthologous targets due to insufficient evidence highlighting the benefit for such an approach. Deeper investigation into orthologue chemical space and its influence toward expanding compound and target coverage is necessary to improve the confidence in this practice.

Results

Here we present analysis of the orthologue chemical space in ChEMBL and PubChem and its impact on target prediction. We highlight the number of conflicting bioactivities between human and orthologues is low and annotations are overall compatible. Chemical space analysis shows orthologues are chemically dissimilar to human with high intra-group similarity, suggesting they could effectively extend the chemical space modelled. Based on these observations, we show the benefit of orthologue inclusion in terms of novel target coverage. We also benchmarked predictive models using a time-series split and also using bioactivities from Chemistry Connect and HTS data available at AstraZeneca, showing that orthologue bioactivity inclusion statistically improved performance.

Availability and implementation

Orthologue-based bioactivity prediction and the compound training set are available at www.github.com/lhm30/PIDGINv2.

Contact

ab454@cam.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Understanding Cytotoxicity and Cytostaticity in a High-Throughput Screening Collection

While mechanisms of cytotoxicity and cytostaticity have been studied extensively from the biological side, relatively little is currently understood regarding areas of chemical space leading to cytotoxicity and cytostasis in large compound collections. Predicting and rationalizing potential adverse mechanism-of-actions (MoAs) of small molecules is however crucial for screening library design, given the link of even low level cytotoxicity and adverse events observed in man. In this study, we analyzed results from a cell-based cytotoxicity screening cascade, comprising 296 970 nontoxic, 5784 cytotoxic and cytostatic, and 2327 cytostatic-only compounds evaluated on the THP-1 cell-line. We employed an in silico MoA analysis protocol, utilizing 9.5 million active and 602 million inactive bioactivity points to generate target predictions, annotate predicted targets with pathways, and calculate enrichment metrics to highlight targets and pathways. Predictions identify known mechanisms for the top ranking targets and pathways for both phenotypes after review and indicate that while processes involved in cytotoxicity versus cytostaticity seem to overlap, differences between both phenotypes seem to exist to some extent. Cytotoxic predictions highlight many kinases, including the potentially novel cytotoxicity-related target STK32C, while cytostatic predictions outline targets linked with response to DNA damage, metabolism, and cytoskeletal machinery. Fragment analysis was also employed to generate a library of toxicophores to improve general understanding of the chemical features driving toxicity. We highlight substructures with potential kinase-dependent and kinase-independent mechanisms of toxicity. We also trained a cytotoxic classification model on proprietary and public compound readouts, and prospectively validated these on 988 novel compounds comprising difficult and trivial testing instances, to establish the applicability domain of models. The proprietary model performed with precision and recall scores of 77.9% and 83.8%, respectively. The MoA results and top ranking substructures with accompanying MoA predictions are available as a platform to assess screening collections.

Targeted Metabolic Profiling of the Tg197 Mouse Model Reveals Itaconic Acid as a Marker of Rheumatoid Arthritis

Rheumatoid arthritis is a progressive, highly debilitating disease where early diagnosis, enabling rapid clinical intervention, would provide obvious benefits to patients, healthcare systems, and society. Novel biomarkers that enable noninvasive early diagnosis of the onset and progression of the disease provide one route to achieving this goal. Here a metabolic profiling method has been applied to investigate disease development in the Tg197 arthritis mouse model. Hind limb extract profiling demonstrated clear differences in metabolic phenotypes between control (wild type) and Tg197 transgenic mice and highlighted raised concentrations of itaconic acid as a potential marker of the disease. These changes in itaconic acid concentrations were moderated or indeed reversed when the Tg197 mice were treated with the anti-hTNF biologic infliximab (10 mg/kg twice weekly for 6 weeks). Further in vitro studies on synovial fibroblasts obtained from healthy wild-type, arthritic Tg197, and infliximab-treated Tg197 transgenic mice confirmed the association of itaconic acid with rheumatoid arthritis and disease-moderating drug effects. Preliminary indications of the potential value of itaconic acid as a translational biomarker were obtained when studies on K4IM human fibroblasts treated with hTNF showed an increase in the concentrations of this metabolite.

Preliminary Survey of Ectoparasites and Associated Pathogens from Norway Rats in New York City

The Norway rat (Rattus norvegicus) is a reservoir of many zoonotic pathogens and lives in close proximity to humans in urban environments. Human infection with rodent-borne disease occurs either directly through contact with a rat or its excreta, or indirectly via arthropod vectors such as fleas and ticks. Here, we report on the diversity and abundance of ectoparasitic arthropod species and associated pathogenic bacteria from 133 Norway rats trapped over a 10-mo period in Manhattan, New York, NY. Norway rats were host to the tropical rat mite [Ornithonyssus bacoti (Hirst)], the spiny rat mite (Laelaps echidnina Berlese), Laelaps nuttalli Hirst, the spined rat louse [Polyplax spinulosa (Burmeister)], and the Oriental rat flea [(Xenopsylla cheopis) (Rothschild)], with an average of 1.7 species per individual. A flea index of 4.1 X. cheopis was determined, whereas previous studies in New York City reported 0.22 fleas per rat. Multiple species of pathogenic Bartonella were identified from Oriental rat fleas that were related to Bartonella tribocorum, Bartonella rochalimae, and Bartonella elizabethae. However, no evidence of Yersinia pestis or Rickettsia spp. infection was detected in fleas. The identification of multiple medically important ectoparasite species in New York City underscores the need for future efforts to fully characterize the diversity and distribution of ectoparasites on Norway rats, and assess the risk to humans of vector-borne disease transmission.

Genome-wide pharmacogenetic investigation of a hepatic adverse event without clinical signs of immunopathology suggests an underlying immune pathogenesis

One of the major goals of pharmacogenetics is to elucidate mechanisms and identify patients at increased risk of adverse events (AEs). To date, however, there have been only a few successful examples of this type of approach. In this paper, we describe a retrospective case-control pharmacogenetic study of an AE of unknown mechanism, characterized by elevated levels of serum alanine aminotransferase (ALAT) during long-term treatment with the oral direct thrombin inhibitor ximelagatran. The study was based on 74 cases and 130 treated controls and included both a genome-wide tag single nucleotide polymorphism and large-scale candidate gene analysis. A strong genetic association between elevated ALAT and the MHC alleles DRB1(*)07 and DQA1(*)02 was discovered and replicated, suggesting a possible immune pathogenesis. Consistent with this hypothesis, immunological studies suggest that ximelagatran may have the ability to act as a contact sensitizer, and hence be able to stimulate an adaptive immune response.

PRO_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology

This paper describes a novel methodology, PRO_SELECT, which combines elements of structure-based drug design and combinatorial chemistry to create a new paradigm for accelerated lead discovery. Starting with a synthetically accessible template positioned in the active site of the target of interest, PRO_SELECT employs database searching to generate lists of potential substituents for each substituent position on the template. These substituents are selected on the basis of their being able to couple to the template using known synthetic routes and their possession of the correct functionality to interact with specified residues in the active site. The lists of potential substituents are then screened computationally against the active site using rapid algorithms. An empirical scoring function, correlated to binding free energy, is used to rank the substituents at each position. The highest scoring substituents at each position can then be examined using a variety of techniques and a final selection is made. Combinatorial enumeration of the final lists generates a library of synthetically accessible molecules, which may then be prioritized for synthesis and assay. The results obtained using PRO_SELECT to design thrombin inhibitors are briefly discussed.

MOLMAKER: de novo generation of 3D databases for use in drug design

A program, MOLMAKER, is described which, in conjunction with a 2D-3D conversion program and 3D database software, can generate de novo 3D databases to aid in drug design. MOLMAKER is based upon graph-theoretical techniques for vertex degree set generation and constructive enumeration of molecular graphs. The generated molecular graphs are then functionalised in a probabilistic manner but in accordance with various constraints specified by the user. The resulting connection tables can be converted into 3D structures by commercial software and loaded into a 3D database for pharmacophore searching. The utility of MOLMAKER is illustrated by two examples of interest from the recent scientific literature: the design of novel protein kinase C agonists and of a bridging ligand for cyclophilin-calcineurin.

Protein fold recognition by threading: comparison of algorithms and analysis of results

Optimal sequence threading can be used to recognize members of a library of protein folds which are closely related in 3-D structure to the native fold of an input test sequence, even when the test sequence is not significantly homologous to the sequence of any member of the fold library. The methods provide an alignment between the residues of the test sequence and the residue positions in a template fold. This alignment optimizes a score function, and the predicted fold is the highest scoring member of the library of folds. Most score functions contain a pairwise interaction energy term. This, coupled with the need to introduce gaps into the alignment, means that the optimization problem is NP hard. We report a comparison between two heuristic optimization algorithms used in the literature, double dynamic programming and an iterative algorithm based on the so-called frozen approximation. These are compared in terms of both the ranking of likely folds and the quality of the alignment produced.

Research note: the use of the Birleson Depression Scale with a non-clinical sample of boys

Attempts have been made to develop self-rating scales to assess depression in children. One of these scales, the Birleson Self-rating Scale, was administered to a non-clinical sample of boys which was larger, and covered a wider age-range, than Birleson's own non-clinical group. A comparison is made with Birleson's findings, and in addition data from the administration of the scale to a group of boys aged 13 to 18 years is presented.

Diagnosis of Duchenne muscular dystrophy: experiences of parents of sufferers

Sixty nine parents of boys suffering from Duchenne muscular dystrophy were interviewed at home. The interview explored the parents' experiences at the time of their son's diagnosis. Many families had experienced distressing delays (average 2.5 years) between the time they first became aware of symptoms and the time of the diagnosis. On only 18 occasions were both parents told of the diagnosis together. One third of the parents were "not satisfied" with the way the diagnosis had been communicated. Parents want to know as soon as possible if there is something wrong with their child. They should be told the diagnosis together and in private. Full information should be given and a series of contacts should be arranged.