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Open Access
Abstract: ragment screening by crystallography has recently skyrocketed. Multiple synchrotrons have built specialized screening platforms, established workflows, and assembled compound libraries. Crystallographic fragment screening is now widely accessible to groups that had previously not considered the approach. While hundreds of crystallographic fragment-screening campaigns have been conducted in the last few years, most of the underlying data have neither been published nor made publicly accessible. This perspective highlights the importance of establishing effective mechanisms for preserving large and often heterogeneous groups of datasets intrinsic to crystallographic fragment-screening campaigns, thereby ensuring their accessibility for advancing research and enabling applications such as training AI-based models.
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May 2025
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Daren
Fearon
,
Ailsa
Powell
,
Alice
Douangamath
,
Alexandre
Dias
,
Charles W. E.
Tomlinson
,
Blake H.
Balcomb
,
Jasmin C.
Aschenbrenner
,
Anthony
Aimon
,
Isabel A.
Barker
,
Jose
Brandao-Neto
,
Patrick
Collins
,
Louise E.
Dunnett
,
Michael
Fairhead
,
Richard J.
Gildea
,
Mathew
Golding
,
Tyler
Gorrie-Stone
,
Paul V.
Hathaway
,
Lizbe
Koekemoer
,
Tobias
Krojer
,
Ryan
Lithgo
,
Elizabeth M.
Maclean
,
Peter G.
Marples
,
Xiaomin
Ni
,
Rachael
Skyner
,
Romain
Talon
,
Warren
Thompson
,
Conor F.
Wild
,
Max
Winokan
,
Nathan D.
Wright
,
Graeme
Winter
,
Elizabeth J.
Shotton
,
Frank
Von Delft
Open Access
Abstract: Fragment-based drug discovery is a well-established method for the identification of chemical starting points for development into clinical candidates. Historically, crystallographic fragment screening was perceived to be low-throughput and time consuming. However, thanks to advances in synchrotron capabilities and the introduction of dedicated facilities, such as the XChem platform at Diamond Light Source, there have been substantial improvements in throughput and integration between sample preparation, data collection and hit identification. Herein we share our experiences of establishing a crystallographic fragment screening facility, our learnings from operating a user programme for ten years and our perspective on applying structural enablement to rapidly progress initial fragment hits to lead-like molecules.
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Nov 2024
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I04-1-Macromolecular Crystallography (fixed wavelength)
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Martin P.
Schwalm
,
Johannes
Dopfer
,
Adarsh
Kumar
,
Francesco A.
Greco
,
Nicolas
Bauer
,
Frank
Löhr
,
Jan
Heering
,
Sara
Cano-Franco
,
Severin
Lechner
,
Thomas
Hanke
,
Ivana
Jaser
,
Viktoria
Morasch
,
Christopher
Lenz
,
Daren
Fearon
,
Peter G.
Marples
,
Charles W. E.
Tomlinson
,
Lorene
Brunello
,
Krishna
Saxena
,
Nathan B. P.
Adams
,
Frank
Von Delft
,
Susanne
Müller
,
Alexandra
Stolz
,
Ewgenij
Proschak
,
Bernhard
Kuster
,
Stefan
Knapp
,
Vladimir V.
Rogov
Diamond Proposal Number(s):
[29658]
Open Access
Abstract: Recent successes in developing small molecule degraders that act through the ubiquitin system have spurred efforts to extend this technology to other mechanisms, including the autophagosomal-lysosomal pathway. Therefore, reports of autophagosome tethering compounds (ATTECs) have received considerable attention from the drug development community. ATTECs are based on the recruitment of targets to LC3/GABARAP, a family of ubiquitin-like proteins that presumably bind to the autophagosome membrane and tether cargo-loaded autophagy receptors into the autophagosome. In this work, we rigorously tested the target engagement of the reported ATTECs to validate the existing LC3/GABARAP ligands. Surprisingly, we were unable to detect interaction with their designated target LC3 using a diversity of biophysical methods. Intrigued by the idea of developing ATTECs, we evaluated the ligandability of LC3/GABARAP by in silico docking and large-scale crystallographic fragment screening. Data based on approximately 1000 crystal structures revealed that most fragments bound to the HP2 but not to the HP1 pocket within the LIR docking site, suggesting a favorable ligandability of HP2. Through this study, we identified diverse validated LC3/GABARAP ligands and fragments as starting points for chemical probe and ATTEC development.
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Nov 2024
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I04-1-Macromolecular Crystallography (fixed wavelength)
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Thibault
Vantieghem
,
Nayyar A.
Aslam
,
Evgenii M.
Osipov
,
Muluembet
Akele
,
Siska
Van Belle
,
Steven
Beelen
,
Matúš
Drexler
,
Terezia
Paulovcakova
,
Vanda
Lux
,
Daren
Fearon
,
Alice
Douangamath
,
Frank
Von Delft
,
Frauke
Christ
,
Václav
Veverka
,
Peter
Verwilst
,
Arthur
Van Aerschot
,
Zeger
Debyser
,
Sergei V.
Strelkov
Diamond Proposal Number(s):
[25544]
Abstract: Lens epithelium-derived growth factor p75 (LEDGF/p75), member of the hepatoma-derived growth-factor-related protein (HRP) family, is a transcriptional co-activator and involved in several pathologies including HIV infection and malignancies such as MLL-rearranged leukemia. LEDGF/p75 acts by tethering proteins to the chromatin through its integrase binding domain. This chromatin interaction occurs between the PWWP domain of LEDGF/p75 and nucleosomes carrying a di- or trimethylation mark on histone H3 Lys36 (H3K36me2/3). Our aim is to rationally devise small molecule drugs capable of inhibiting such interaction. To bootstrap this development, we resorted to X-ray crystallography-based fragment screening (FBS-X). Given that the LEDGF PWWP domain crystals were not suitable for FBS-X, we employed crystals of the closely related PWWP domain of paralog HRP-2. As a result, as many as 68 diverse fragment hits were identified, providing a detailed sampling of the H3K36me2/3 pocket pharmacophore. Subsequent structure-guided fragment expansion in three directions yielded multiple compound series binding to the pocket, as verified through X-ray crystallography, nuclear magnetic resonance and differential scanning fluorimetry. Our best compounds have double-digit micromolar affinity and optimally sample the interactions available in the pocket, judging by the Kd-based ligand efficiency exceeding 0.5 kcal/mol per non-hydrogen atom. Beyond π-stacking within the aromatic cage of the pocket and hydrogen bonding, the best compounds engage in a σ-hole interaction between a halogen atom and a conserved water buried deep in the pocket. Notably, the binding pocket in LEDGF PWWP is considerably smaller compared to the related PWWP1 domains of NSD2 and NSD3 which feature an additional subpocket and for which nanomolar affinity compounds have been developed recently. The absence of this subpocket in LEDGF PWWP limits the attainable affinity. Additionally, these structural differences in the H3K36me2/3 pocket across the PWWP domain family translate into a distinct selectivity of the compounds we developed. Our top ranked compounds are interacting with both homologous LEDGF and HRP-2 PWWP domains, yet they showed no affinity for the NSD2 PWWP1 and BRPF2 PWWP domains which belong to other PWWP domain subfamilies. Nevertheless, our developed compound series provide a strong foundation for future drug discovery targeting the LEDGF PWWP domain as they can further be explored through combinatorial chemistry. Given that the affinity of H3K36me2/3 nucleosomes to LEDGF/p75 is driven by interactions within the pocket as well as with the DNA-binding residues, we suggest that future compound development should target the latter region as well. Beyond drug discovery, our compounds can be employed to devise tool compounds to investigate the mechanism of LEDGF/p75 in epigenetic regulation.
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Oct 2024
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I04-1-Macromolecular Crystallography (fixed wavelength)
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Melissa L.
Boby
,
Daren
Fearon
,
Matteo
Ferla
,
Mihajlo
Filep
,
Lizbe
Koekemoer
,
Matthew C.
Robinson
,
The Covid
Moonshot Consortium
,
John D.
Chodera
,
Alpha A.
Lee
,
Nir
London
,
Annette
Von Delft
,
Frank
Von Delft
Abstract: We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property–free knowledge base for future anticoronavirus drug discovery.
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Nov 2023
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I04-1-Macromolecular Crystallography (fixed wavelength)
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Vijil
Chenthamarakshan
,
Samuel C.
Hoffman
,
C. David
Owen
,
Petra
Lukacik
,
Claire
Strain-Damerell
,
Daren
Fearon
,
Tika R.
Malla
,
Anthony
Tumber
,
Christopher J.
Schofield
,
Helen M. E.
Duyvesteyn
,
Wanwisa
Dejnirattisai
,
Loic
Carrique
,
Thomas S.
Walter
,
Gavin R.
Screaton
,
Tetiana
Matviiuk
,
Aleksandra
Mojsilovic
,
Jason
Crain
,
Martin A.
Walsh
,
David I.
Stuart
,
Payel
Das
Diamond Proposal Number(s):
[27995]
Open Access
Abstract: Inhibitor discovery for emerging drug-target proteins is challenging, especially when target structure or active molecules are unknown. Here, we experimentally validate the broad utility of a deep generative framework trained at-scale on protein sequences, small molecules, and their mutual interactions—unbiased toward any specific target. We performed a protein sequence-conditioned sampling on the generative foundation model to design small-molecule inhibitors for two dissimilar targets: the spike protein receptor-binding domain (RBD) and the main protease from SARS-CoV-2. Despite using only the target sequence information during the model inference, micromolar-level inhibition was observed in vitro for two candidates out of four synthesized for each target. The most potent spike RBD inhibitor exhibited activity against several variants in live virus neutralization assays. These results establish that a single, broadly deployable generative foundation model for accelerated inhibitor discovery is effective and efficient, even in the absence of target structure or binder information.
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Jun 2023
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I04-1-Macromolecular Crystallography (fixed wavelength)
Krios II-Titan Krios II at Diamond
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Andre
Schutzer Godoy
,
Aline Minalli
Nakamura
,
Alice
Douangamath
,
Yun
Song
,
Gabriela
Dias Noske
,
Victor
Oliveira Gawriljuk
,
Rafaela
Sachetto Fernandes
,
Humberto
D'Muniz Pereira
,
Ketllyn irene
Zagato Oliveira
,
Daren
Fearon
,
Alexandre
Dias
,
Tobias
Krojer
,
Michael
Fairhead
,
Alisa
Powell
,
Louise
Dunnett
,
Jose
Brandao-Neto
,
Rachael
Skyner
,
Rod
Chalk
,
Dávid
Bajusz
,
Miklós
Bege
,
Anikó
Borbás
,
György Miklós
Keserű
,
Frank
Von Delft
,
Glaucius
Oliva
Diamond Proposal Number(s):
[27083, 27023]
Open Access
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The NSP15 endoribonuclease enzyme, known as NendoU, is highly conserved and plays a critical role in the ability of the virus to evade the immune system. NendoU is a promising target for the development of new antiviral drugs. However, the complexity of the enzyme's structure and kinetics, along with the broad range of recognition sequences and lack of structural complexes, hampers the development of inhibitors. Here, we performed enzymatic characterization of NendoU in its monomeric and hexameric form, showing that hexamers are allosteric enzymes with a positive cooperative index, and with no influence of manganese on enzymatic activity. Through combining cryo-electron microscopy at different pHs, X-ray crystallography and biochemical and structural analysis, we showed that NendoU can shift between open and closed forms, which probably correspond to active and inactive states, respectively. We also explored the possibility of NendoU assembling into larger supramolecular structures and proposed a mechanism for allosteric regulation. In addition, we conducted a large fragment screening campaign against NendoU and identified several new allosteric sites that could be targeted for the development of new inhibitors. Overall, our findings provide insights into the complex structure and function of NendoU and offer new opportunities for the development of inhibitors.
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Apr 2023
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William
Mccorkindale
,
Kadi L.
Saar
,
Daren
Fearon
,
Melissa
Boby
,
Haim
Barr
,
Amir
Ben-Shmuel
,
Nir
London
,
Frank
Von Delft
,
John D.
Chodera
,
Alpha. A.
Lee
,
The
Covid Moonshot Consortium
Open Access
Abstract: A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein–ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein–ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein–ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry.
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Mar 2023
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I03-Macromolecular Crystallography
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Diamond Proposal Number(s):
[23459]
Open Access
Abstract: The worldwide public health and socioeconomic consequences caused by the COVID-19 pandemic highlight the importance of increasing preparedness for viral disease outbreaks by providing rapid disease prevention and treatment strategies. The NSP3 macrodomain of coronaviruses including SARS-CoV-2 is among the viral protein repertoire that was identified as a potential target for the development of antiviral agents, due to its critical role in viral replication and consequent pathogenicity in the host. By combining virtual and biophysical screening efforts, we discovered several experimental small molecules and FDA-approved drugs as inhibitors of the NSP3 macrodomain. Analogue characterisation of the hit matter and crystallographic studies confirming binding modes, including that of the antibiotic compound aztreonam, to the active site of the macrodomain provide valuable structure–activity relationship information that support current approaches and open up new avenues for NSP3 macrodomain inhibitor development.
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Feb 2023
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Stefan
Gahbauer
,
Galen J.
Correy
,
Marion
Schuller
,
Matteo P.
Ferla
,
Yagmur Umay
Doruk
,
Moira
Rachman
,
Taiasean
Wu
,
Morgan
Diolaiti
,
Siyi
Wang
,
R. Jeffrey
Neitz
,
Daren
Fearon
,
Dmytro S.
Radchenko
,
Yurii S.
Moroz
,
John J.
Irwin
,
Adam R.
Renslo
,
Jenny C.
Taylor
,
Jason E.
Gestwicki
,
Frank
Von Delft
,
Alan
Ashworth
,
Ivan
Ahel
,
Brian K.
Shoichet
,
James S.
Fraser
Open Access
Abstract: The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high-resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 153 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated conformational changes within the active site, and key inhibitor motifs that will template future drug development against Mac1.
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Jan 2023
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