Biology subjects

Blundell, T. L.

Publications and source records attributed to Blundell, T. L..

13 recordsLinked to original sources

bioRxiv2026

HANSEN: An Integrated Structural and Functional Proteome Resource for Structure-Guided Drug Discovery in Mycobacterium leprae

Leprosy remains a leading infectious cause of preventable disability, yet its causative agent, Mycobacterium leprae (M. leprae), is structurally under-characterised. Only ten Protein Data Bank (PDB) entries represent seven of its 1,603 protein-coding genes. We present HANSEN, a proteome-wide structural and functional resource for M. leprae. Monomeric and oligomeric models were generated with AlphaFold 3, Boltz-1, Boltz-2 and Chai-1, and annotated with per-residue confidence, predicted aligned error and, for assemblies, interface confidence. Ligand-binding pockets were predicted with AF2BIND, P2Rank and fpocket, template-derived ligands were modelled within oligomeric complexes, residue-level B-cell epitope propensity was estimated with DiscoTope-3.0, and gene essentiality was transferred from Mycobacterium tuberculosis transposon-sequencing labels. These features are integrated in a relational database with interactive visualisation and combined into a calibrated Target Priority Score that ranks all 1,603 proteins into four tiers and recovers established antimycobacterial targets. HANSEN (https://hansen-leprosy.medschl.cam.ac.uk/home) provides a practical basis for target prioritisation and structure-guided drug discovery in leprosy.

bioinformatics↗

bioRxiv2023

Selective inhibitors of the Aurora A-TPX2 protein-protein interaction exhibit in vivo efficacy as targeted anti-mitotic agents

The protein kinase Aurora A, and its close relative, Aurora B, regulate human cell division. Aurora A is frequently overexpressed in cancers of the breast, ovary, pancreas and blood, provoking genome instability and resistance to anti-mitotic chemotherapy. Intracellular localization and enzymatic activity of Aurora A are regulated by its interaction with the spindle assembly factor TPX2. Here, we have used fragment-based, structure-guided lead discovery to develop small-molecule inhibitors of the Aurora A-TPX2 protein-protein interaction (PPI). These compounds act by novel mechanism compared to existing Aurora A inhibitors and they are highly specific to Aurora A over Aurora B. Our biophysically, structurally and phenotypically validated lead compound, CAM2602, exhibits oral bioavailability, favourable pharmacokinetics, pharmacodynamic biomarker modulation, and arrest of growth in tumour xenografts. Consistent with our original finding that Aurora A overexpression drives taxane-resistance in cancer cells, inhibition of Aurora A-TPX2 PPI synergizes with paclitaxel to suppress the outgrowth of pancreatic cancer cells. Our results provide a blueprint for targeting the Aurora A-TPX2 PPI for cancer therapy and suggest a promising clinical utility for this mode of action.

biochemistry↗

bioRxiv2022

Mutational spectra analysis reveals bacterial niche and transmission routes

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to identify disrupted DNA repair processes and niche-specific mutagen exposure. Here we reconstructed mutational spectra for 84 clades from 31 diverse bacterial species, assigned signatures to specific DNA repair pathways using hypermutator lineages, and, by comparing mutational spectra of clades from different environmental and biological locations, extracted reproducible niche-associated mutational signatures. We show that mutational spectra can predict general and specific bacterial niches and therefore reveal the site of infection and types of transmission routes for established and emergent human bacterial pathogens. One sentence summaryVariable mutagen exposure and DNA repair drive differential mutational spectra between bacteria and enable niche inference

microbiology↗

bioRxiv2022

Decoding Surface Fingerprints for Protein-Ligand Interactions

AO_SCPLOWBSTRACTC_SCPLOWSmall molecules have been the preferred modality for drug development and therapeutic interventions. This molecular format presents a number of advantages, e.g. long half-lives and cell permeability, making it possible to access a wide range of therapeutic targets. However, finding small molecules that engage "hard-to-drug" protein targets specifically and potently remains an arduous process, requiring experimental screening of extensive compound libraries to identify candidate leads. The search continues with further optimization of compound leads to meet the required potency and toxicity thresholds for clinical applications. Here, we propose a new computational workflow for high-throughput fragment-based screening and binding affinity prediction where we leverage the available protein-ligand complex structures using a state-of-the-art protein surface embedding framework (dMaSIF). We developed a tool capable of finding suitable ligands and fragments for a given protein pocket solely based on protein surface descriptors, that capture chemical and geometric features of the target pocket. The identified fragments can be further combined into novel ligands. Using the structural data, our ligand discovery pipeline learns the signatures of interactions between surface patches and small pharmacophores. On a query target pocket, the algorithm matches known target pockets and returns either potential ligands or identifies multiple ligand fragments in the binding site. Our binding affinity predictor is capable of predicting the affinity of a given protein-ligand pair, requiring only limited information about the ligand pose. This enables screening without the costly step of first docking candidate molecules. Our framework will facilitate the design of ligands based on the targets surface information. It may significantly reduce the experimental screening load and ultimately reveal novel chemical compounds for targeting challenging proteins.

bioinformatics↗

bioRxiv2021

Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism of the virus. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known or predicted three-dimensional protein models with the receptor-binding motifs and verify potential mimicry with protein docking simulations. Both human and non-human proteins were found to be similar to all three receptor-binding motifs. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins. HighlightsO_LIPotential coronavirus spike protein mimicry revealed by structural comparison C_LIO_LIHuman and non-human protein potential interactions with virus identified C_LIO_LIPredicted structural mimicry corroborated by protein-protein docking C_LIO_LIEpitope-based alignments may help guide vaccine efforts C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/441187v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1f09454org.highwire.dtl.DTLVardef@19a5557org.highwire.dtl.DTLVardef@158d3fdorg.highwire.dtl.DTLVardef@c59511_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2021

A Fragment-based approach to assess the ligandability of ArgB, ArgC, ArgD and ArgF in the L-arginine biosynthetic pathway of Mycobacterium tuberculosis.

The L-arginine biosynthesis pathway consists of eight enzymes that catalyse the conversion of L-glutamate to L-arginine, appears to be attractive target for anti-Tuberculosis (TB) drug discovery. Starvation of M. tuberculosis deleted for either argB or argF genes led to rapid sterilization of these strains in mice while Chemical inhibition of ArgJ with Pranlukast was also found to clear chronic M. tuberculosis infection in animal models. In this work, the ligandability of four enzymes of the pathway ArgB, ArgC, ArgD and ArgF is explored using a fragment-based approach. We reveal several hits for these enzymes validated with biochemical and biophysical assays, and X-ray crystallographic data, which in the case of ArgB were further confirmed to have on-target activity against M. tuberculosis. These results demonstrate the potential of more enzymes in this pathway to be targeted with dedicated drug discovery programmes.

biochemistry↗

bioRxiv2020

Chemical validation of Mycobacterium tuberculosis phosphopantetheine adenylyltransferase using fragment linking and CRISPR interference

The coenzyme A (CoA) biosynthesis pathway has attracted attention as a potential target for much-needed novel antimicrobial drugs, including for the treatment of tuberculosis (TB), the lethal disease caused by Mycobacterium tuberculosis (Mtb). Seeking to identify the first inhibitors of Mtb phosphopantetheine adenylyltransferase (MtbPPAT), the enzyme that catalyses the penultimate step in CoA biosynthesis, we performed a fragment screen. In doing so, we discovered three series of fragments that occupy distinct regions of the MtbPPAT active site, presenting a unique opportunity for fragment linking. Here we show how, guided by X-ray crystal structures, we could link weakly-binding fragments to produce an active site binder with a KD < 20 M and on-target anti-Mtb activity, as demonstrated using CRISPR interference. This study represents a big step toward validating MtbPPAT as a potential drug target and designing a MtbPPAT-targeting anti-TB drug. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biochemistry↗

bioRxiv2020

A small-molecule inhibitor of the BRCA2-RAD51 interaction modulates RAD51 assembly and potentiates DNA damage-induced cell death

BRCA2 controls RAD51 recombinase during homologous DNA recombination (HDR) through eight evolutionarily-conserved BRC repeats, which individually engage RAD51 via the motif Phe-x-x-Ala. Using structure-guided molecular design, templated on a monomeric thermostable chimera between human RAD51 and archaeal RadA, we identify CAM833, a 529 Da orthosteric inhibitor of RAD51:BRC with a Kd of 366 nM. The quinoline of CAM833 occupies a hotspot, the Phe-binding pocket on RAD51 and the methyl of the substituted -methylbenzyl group occupies the Ala-binding pocket. In cells, CAM833 diminishes formation of damage-induced RAD51 nuclear foci; inhibits RAD51 molecular clustering, suppressing extended RAD51 filament assembly; potentiates cytotoxicity by ionising radiation, augmenting 4N cell-cycle arrest and apoptotic cell death and works with poly-ADP ribose polymerase (PARP)1 inhibitors to suppress growth in BRCA2-wildtype cells. Thus, chemical inhibition of the protein-protein interaction between BRCA2 and RAD51 disrupts HDR and potentiates DNA damage-induced cell death, with implications for cancer therapy.

cancer biology↗

bioRxiv2020

Using a fragment-based approach to identify novel chemical scaffolds targeting the dihydrofolate reductase (DHFR) from Mycobacterium tuberculosis

Dihydrofolate reductase (DHFR), a key enzyme involved in folate metabolism, is a widely explored target in the treatment of cancer, immune diseases, bacteria and protozoa infections. Although several antifolates have proved successful in the treatment of infectious diseases, none have been developed to combat tuberculosis, despite the essentiality of M. tuberculosis DHFR (MtDHFR). Herein, we describe an integrated fragment-based drug discovery approach to target MtDHFR that has identified hits with scaffolds not yet explored in any previous drug design campaign for this enzyme. The application of a SAR by catalog strategy of an in house library for one of the identified fragments has led to a series of molecules that bind MtDHFR with low micromolar affinities. Crystal structures of MtDHFR in complex with compounds of this series demonstrated a novel binding mode that differs from other DHFR antifolates, thus opening perspectives for the development of novel and relevant MtDHFR inhibitors.

biochemistry↗

bioRxiv2019

Mycobacterial OtsA structures reveal an allosteric site regulated by 2-oxoglutarate and 2-phosphoglycerate and the mechanism for substrate preference.

Trehalose is an essential disaccharide for mycobacteria and a key constituent of several cell wall glycolipids with fundamental roles in pathogenesis. Mycobacteria possess two pathways for trehalose biosynthesis. However, only the OtsAB pathway was found to be essential in M. tuberculosis, with marked growth and virulence defects of OtsA mutants and strict essentiality of OtsB2. Herein, we report the first mycobacterial OtsA structures from M. thermoresistibile in both apo and ligand-bound forms. Structural information reveals three key residues in the mechanism of substrate preference that were further confirmed by site-directed mutagenesis. Additionally, we identify 2-oxoglutarate and 2-phosphoglycerate as allosteric regulators of OtsA. The structural analysis in this work strongly contributed to define the mechanisms for feedback inhibition, show different conformational states of the enzyme and map a new allosteric site.

biochemistry↗

bioRxiv2019

Computational Saturation Mutagenesis of the β subunit of RNA polymerase in Mycobacterium leprae

In contrast to the situation with tuberculosis, rifampin resistance in leprosy may remain undetected due to the lack of rapid and effective diagnostic methods. A quick and reliable method is essential to determine the impacts of emerging detrimental mutations. The functional consequences of missense mutations within the {beta}-subunit of RNA polymerase in Mycobacterium leprae (M. leprae) contribute to phenotypic rifampin resistance outcomes in leprosy. Here we report in-silico saturation mutagenesis of all residues in the {beta}-subunit of RNA polymerase to all other 19 amino acid types and predict their impacts on overall thermodynamic stability, on interactions at subunit interfaces, and on {beta}-subunit-RNA and rifampin affinities using state-of-the-art structure, sequence and normal mode analysis-based methods. A total of 21,394 mutations were analysed, and it was noted that mutations in the conserved residues that line the active-site cleft show largely destabilizing effects, resulting in increased relative solvent accessibility and concomitant decrease in depth of the mutant residues. The mutations at residues S437, G459, H451, P489, K884 and H1035 are identified as extremely detrimental as they induce highly destabilizing effects on the overall stability, nucleic acid and rifampin affinities. Destabilizing effects were predicted for all the experimentally identified rifampin-resistant mutations in M. leprae indicating that this model can be used as a surveillance tool to monitor emerging detrimental mutations conferring rifampin resistance in leprosy.\n\nAUTHOR SUMMARYEmergence of primary and secondary drug resistance to rifampin in leprosy is a growing concern and poses threat to the leprosy control and elimination measures globally. In the absence of an effective in-vitro system to detect and monitor phenotypic rifampin resistance in leprosy, most of the diagnosis relies on detecting mutations in the drug resistance determining regions of the rpoB gene that encodes the {beta} subunit of RNA polymerase in M. leprae. Few labs in the world perform mouse food pad propagation of M. leprae in the presence of drugs (rifampin) to determine growth patterns and confirm resistance, however the duration of these methods lasts from 8 to 12 months making them impractical for diagnosis. Understanding molecular mechanisms of drug resistance is vital to associating mutations to clinical resistance outcomes in leprosy. Here we propose an in-silico saturation mutagenesis approach to comprehensively elucidate the structural implications of any mutations that exist or can arise in the {beta} subunit of RNA polymerase in M. leprae. Most of the predicted mutations may not occur in M. leprae due to fitness costs but the information thus generated by this approach help decipher the impacts of mutations across the structure and conversely enable identification of stable regions in the protein that are least impacted by mutations (mutation coolspots) which can be a choice for small molecule binding and structure guided drug discovery.

bioinformatics↗

bioRxiv2019

Fragment-based discovery of a new class of inhibitors targeting mycobacterial tRNA modification

Translational frameshift errors are often deleterious to the synthesis of functional proteins as they lead to the production of truncated or inactive proteins. TrmD (tRNA-(N(1)G37) methyltransferase) is an essential tRNA modification enzyme in bacteria that prevents +1 errors in the reading frame during protein translation and has been identified as a therapeutic target for several bacterial infections. Here we validate TrmD as a target in Mycobacterium abscessus and describe the application of a structure-guided fragment-based drug discovery approach for the design of a new class of inhibitors against this enzyme. A fragment library screening followed by structure-guided chemical elaboration of hits led to the development of compounds with potent in vitro TrmD inhibitory activity. Several of these compounds exhibit activity against planktonic M. abscessus and Mycobacterium tuberculosis. The compounds were further active in macrophage infection models against Mycobacterium leprae and M. abscessus suggesting the potential for novel broad-spectrum mycobacterial drugs.

biochemistry↗

bioRxiv2019

Comparative analyses of metabolic pathways in mycobacteria: Insights into the identification and characterisation of new drug targets in M. tuberculosis, M. leprae and M. abscessus

Three related mycobacteria are the cause of widespread infections in man and are the focus of intense research and drug-discovery efforts in the face of growing antimicrobial resistance. Mycobacterium tuberculosis, the causative agent of tuberculosis, is currently one of the top ten causes of death in the world according to WHO; M. abscessus, a group of non-tuberculous mycobacteria causes lung infections and other opportunistic infections in humans; and M. leprae, the causative agent of leprosy, remains endemic in tropical countries. There is an urgent need to design alternatives to conventional treatment strategies, due to the increase in resistance to standard antibacterials. In this study, we present a comparative analysis of chokepoint and essentiality datasets that will provide insight into the development of new treatment regimes. We illustrate the key metabolic pathways shared between these three organisms and identify drug targets with a wide metabolic impact that are common to the three species. We demonstrate that 72% of the chokepoint enzymes are proteins essential to Mycobacterium tuberculosis. We show also that 78% of the drug targets, prioritized based on their presence in multiple paths on the metabolic network, are present in pathways shared by M. tuberculosis, M. leprae and M. abscessus, including biosynthesis of amino acids, carbohydrates, cell structures, fatty acid and lipid biosynthesis. A further 17% is found in the prioritised pathways shared between M. tuberculosis and M. abscessus. We have performed comparative structure modelling of potential drug targets identified using our analysis in order to assess druggability and demonstrate the importance of chokepoint analysis in terms of drug target identification. AUTHOR SUMMARYComputer simulation studies to design new drugs against mycobacteria

bioinformatics↗