canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of ...experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface.
E3 ligase mediated targeted protein degradation is an ever more important area in drug discovery. In the case of cereblon two avenues exist; either heterobifunctional PROTACs, or discrete cereblon ...ligands that induce a specific neosubstrate degron association to the complex. Here we present a degron blocking approach, whereby structural and in silico understandings of degron association has directed ligand design to block IMiD‐like binding of degron containing neosubstrates, thus enhancing PROTAC selectivity. More information can be found in the Research Article by H. Bouguenina, J. J. Caldwell et al.
Small molecules inducing protein degradation are important pharmacological tools to interrogate complex biology and are rapidly translating into clinical agents. However, to fully realise the ...potential of these molecules, selectivity remains a limiting challenge. Herein, we addressed the issue of selectivity in the design of CRL4CRBN recruiting PROteolysis TArgeting Chimeras (PROTACs). Thalidomide derivatives used to generate CRL4CRBN recruiting PROTACs have well described intrinsic monovalent degradation profiles by inducing the recruitment of neo‐substrates, such as GSPT1, Ikaros and Aiolos. We leveraged structural insights from known CRL4CRBN neo‐substrates to attenuate and indeed remove this monovalent degradation function in well‐known CRL4CRBN molecular glues degraders, namely CC‐885 and Pomalidomide. We then applied these design principles on a previously published BRD9 PROTAC (dBRD9‐A) and generated an analogue with improved selectivity profile. Finally, we implemented a computational modelling pipeline to show that our degron blocking design does not impact PROTAC‐induced ternary complex formation. We believe that the tools and principles presented in this work will be valuable to support the development of targeted protein degradation.
Small molecules inducing protein degradation are important pharmacological tools to interrogate complex biology and are rapidly translating into clinical agents. However, to fully realise the ...potential of these molecules, selectivity remains a limiting challenge. Herein, we addressed the issue of selectivity in the design of CRL4
recruiting PROteolysis TArgeting Chimeras (PROTACs). Thalidomide derivatives used to generate CRL4
recruiting PROTACs have well described intrinsic monovalent degradation profiles by inducing the recruitment of neo-substrates, such as GSPT1, Ikaros and Aiolos. We leveraged structural insights from known CRL4
neo-substrates to attenuate and indeed remove this monovalent degradation function in well-known CRL4
molecular glues degraders, namely CC-885 and Pomalidomide. We then applied these design principles on a previously published BRD9 PROTAC (dBRD9-A) and generated an analogue with improved selectivity profile. Finally, we implemented a computational modelling pipeline to show that our degron blocking design does not impact PROTAC-induced ternary complex formation. We believe that the tools and principles presented in this work will be valuable to support the development of targeted protein degradation.
We conducted a genome-wide association study of male breast cancer comprising 823 cases and 2,795 controls of European ancestry, with validation in independent sample sets totaling 438 cases and 474 ...controls. A SNP in RAD51B at 14q24.1 was significantly associated with male breast cancer risk (P = 3.02 × 10(-13); odds ratio (OR) = 1.57). We also refine association at 16q12.1 to a SNP within TOX3 (P = 3.87 × 10(-15); OR = 1.50).
The clinical and pathological heterogeneity of breast cancer has instigated efforts to stratify breast cancer sub-types according to molecular profiles. These profiling efforts are now being ...augmented by large-scale functional screening of breast tumour cell lines, using approaches such as RNA interference. We have developed ROCK (rock.icr.ac.uk) to provide a unique, publicly accessible resource for the integration of breast cancer functional and molecular profiling datasets. ROCK provides a simple online interface for the navigation and cross-correlation of gene expression, aCGH and RNAi screen data. It enables the interrogation of gene lists in the context of statistically analysed functional genomic datasets, interaction networks, pathways, GO terms, mutations and drug targets. The interface also provides interactive visualisations of datasets and interaction networks. ROCK collates data from a wealth of breast cancer molecular profiling and functional screening studies into a single portal, where analysed and annotated results can be accessed at the level of a gene, sample or study. We believe that portals such as ROCK will not only afford researchers rapid access to profiling data, but also aid the integration of different data types, thus enhancing the discovery of novel targets and biomarkers for breast cancer.
Cancer is caused by mutations in oncogenes and tumor suppressor genes, resulting in the deregulation of processes fundamental to the normal behavior of cells. The identification and characterization ...of oncogenes and tumor suppressors has led to new treatment strategies that have significantly improved cancer outcome. The advent of next generation sequencing has allowed the elucidation of the fine structure of cancer genomes, however, the identification of pathogenic changes is complicated by the inherent genomic instability of cancer cells. Therefore, functional approaches for the identification of novel genes involved in the initiation and development of tumors are critical. Here we report the first whole human genome in vivo RNA interference screen to identify functionally important tumor suppressor genes. Using our novel approach, we identify previously validated tumor suppressor genes including
TP53
and
MNT
, as well as several novel candidate tumor suppressor genes including
leukemia inhibitory factor receptor
(
LIFR
). We show that LIFR is a key novel tumor suppressor, whose deregulation may drive the transformation of a significant proportion of human breast cancers. These results demonstrate the power of genome wide in vivo RNAi screens as a method for identifying novel genes regulating tumorigenesis.
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