DNA-PKcs structure suggests an allosteric mechanism modulating DNA double-strand break repair.
Science. 2017 Feb 03;355(6324):520-524
Authors: Sibanda BL, Chirgadze DY, Ascher DB, Blundell TL
DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is a central component of nonhomologous end joining (NHEJ), repairing DNA double-strand breaks that would otherwise lead to apoptosis or cancer. We have solved its structure in complex with the C-terminal peptide of Ku80 at 4.3 angstrom resolution using x-ray crystallography. We show that the 4128-amino acid structure comprises three large structural units: the N-terminal unit, the Circular Cradle, and the Head. Conformational differences between the two molecules in the asymmetric unit are correlated with changes in accessibility of the kinase active site, which are consistent with an allosteric mechanism to bring about kinase activation. The location of KU80ct194 in the vicinity of the breast cancer 1 (BRCA1) binding site suggests competition with BRCA1, leading to pathway selection between NHEJ and homologous recombination.
PMID: 28154079 [PubMed - in process]
Structure-guided, target-based drug discovery - exploiting genome information from HIV to mycobacterial infections.
Postepy Biochem. 2016;62(3):262-272
Authors: Malhotra S, Thomas SE, Ochoa Montano B, Blundell TL
The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead optimisation using fragment-based approaches in the development of new antimicrobials for mycobacterial infections.
PMID: 28132480 [PubMed - in process]
In silico functional dissection of saturation mutagenesis: Interpreting the relationship between phenotypes and changes in protein stability, interactions and activity.
Sci Rep. 2016 Jan 22;6:19848
Authors: Pires DE, Chen J, Blundell TL, Ascher DB
Despite interest in associating polymorphisms with clinical or experimental phenotypes, functional interpretation of mutation data has lagged behind generation of data from modern high-throughput techniques and the accurate prediction of the molecular impact of a mutation remains a non-trivial task. We present here an integrated knowledge-driven computational workflow designed to evaluate the effects of experimental and disease missense mutations on protein structure and interactions. We exemplify its application with analyses of saturation mutagenesis of DBR1 and Gal4 and show that the experimental phenotypes for over 80% of the mutations correlate well with predicted effects of mutations on protein stability and RNA binding affinity. We also show that analysis of mutations in VHL using our workflow provides valuable insights into the effects of mutations, and their links to the risk of developing renal carcinoma. Taken together the analyses of the three examples demonstrate that structural bioinformatics tools, when applied in a systematic, integrated way, can rapidly analyse a given system to provide a powerful approach for predicting structural and functional effects of thousands of mutations in order to reveal molecular mechanisms leading to a phenotype. Missense or non-synonymous mutations are nucleotide substitutions that alter the amino acid sequence of a protein. Their effects can range from modifying transcription, translation, processing and splicing, localization, changing stability of the protein, altering its dynamics or interactions with other proteins, nucleic acids and ligands, including small molecules and metal ions. The advent of high-throughput techniques including sequencing and saturation mutagenesis has provided large amounts of phenotypic data linked to mutations. However, one of the hurdles has been understanding and quantifying the effects of a particular mutation, and how they translate into a given phenotype. One approach to overcome this is to use robust, accurate and scalable computational methods to understand and correlate structural effects of mutations with disease.
PMID: 26797105 [PubMed - indexed for MEDLINE]
Arpeggio: A web server for calculating and visualising interatomic interactions in protein structures.
J Mol Biol. 2016 Dec 10;:
Authors: Jubb HC, Higueruelo AP, Ochoa-Montaño B, Pitt WR, Ascher DB, Blundell TL
Interactions between proteins and their ligands, such as small molecules, other proteins and DNA, depend on specific interatomic interactions that can be classified on the basis of atom type, distance and angle constraints. Visualisation of these interactions provides insights into the nature of molecular recognition events, and has practical uses in guiding drug design and understanding the structural and functional impacts of mutations. We present Arpeggio, a web server for calculating interactions within and between proteins and protein, DNA, or small-molecule ligands, including van der Waals', ionic, carbonyl, metal, hydrophobic and halogen-halogen bond contacts, as well as hydrogen bonds specific atom-aromatic ring (cation-π, donor-π, halogen-π and carbon-π) and aromatic ring-aromatic ring (π-π) interactions, within user submitted macromolecule structures. PyMOL session files can be downloaded allowing high quality publication images of the interactions to be generated. Arpeggio is implemented in Python and available as a user-friendly web interface at http://structure.bioc.cam.ac.uk/arpeggio/and as a downloadable package athttps://bitbucket.org/harryjubb/arpeggio.
PMID: 27964945 [PubMed - as supplied by publisher]
A fragment merging approach towards the development of small molecule inhibitors of Mycobacterium tuberculosis EthR for use as ethionamide boosters.
Org Biomol Chem. 2016 Feb 21;14(7):2318-26
Authors: Nikiforov PO, Surade S, Blaszczyk M, Delorme V, Brodin P, Baulard AR, Blundell TL, Abell C
With the ever-increasing instances of resistance to frontline TB drugs there is the need to develop novel strategies to fight the worldwide TB epidemic. Boosting the effect of the existing second-line antibiotic ethionamide by inhibiting the mycobacterial transcriptional repressor protein EthR is an attractive therapeutic strategy. Herein we report the use of a fragment based drug discovery approach for the structure-guided systematic merging of two fragment molecules, each binding twice to the hydrophobic cavity of EthR from M. tuberculosis. These together fill the entire binding pocket of EthR. We elaborated these fragment hits and developed small molecule inhibitors which have a 100-fold improvement of potency in vitro over the initial fragments.
PMID: 26806381 [PubMed - indexed for MEDLINE]