An Integrated Approach to Fragment-Based Lead Generation:Philosophy, Strategy and Case Studies from AstraZenecas Drug Discovery Programmes

Albert, Jeffrey S.; Blomberg, Niklas; Breeze, Alexander L.; Brown, Alastair; Burrows, Jeremy N.; Edwards, Philip D.; Folmer, R.H.A.; Geschwindner, Stefan; Griffen, Ed; Kenny, Peter W.; Nowak, Thorsten; Olsson, Lars‐Inge; Sanganee, Hitesh J.; Shapiro, Adam B.

doi:10.2174/156802607782341091

Cited by 125 publications

(87 citation statements)

References 128 publications

(165 reference statements)

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“…This active rate, although much higher than under conventional HTS settings, is comparable to those reported for GPCRs using diverse assays as TINS, SPR, 10 intact cell binding 14 and conventional biochemical screening. 16,17 24% of confirmed hits were found to prefer α 2C over an unrelated target, and 76% of these displayed significant activity in a biochemical assay as well. In virtual screening 2 out of the 16 hits were identified in the top 1% of the fragment library providing moderate enrichment but useful structural information on the hits.…”

Section: Discussionmentioning

confidence: 99%

“…Apart from these successful examples, where challenging targetspecific preparations were crucial for the actual screening process, some experiences with more generic assay formats for probing membrane proteins have been reported as well. [15][16][17] Often, drug discovery programs require ligands that stimulate or potentiate membrane receptors. Although the understanding on the molecular basis of GPCR function increased tremendously in the last years, 18 the structural basis of distinct biological responses is still poorly understood.…”

Section: Introductionmentioning

confidence: 99%

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Cell-based and virtual fragment screening for adrenergic α2C receptor agonists

Szollosi

Bobok

Kiss

et al. 2015

Bioorganic & Medicinal Chemistry

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cell-based and virtual fragment screening for adrenergic α2C receptor agonists

Szollosi

Bobok

Kiss

et al. 2015

Bioorganic & Medicinal Chemistry

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“…The study detailed in this paper uses a test-set of 950 diverse fragment-sized molecules [11] to allow an in silico druggability prediction through docking against a target binding site. This can be considered as the computational equivalent of a fragment screen, but where a specific pocket is targeted by each run.…”

Section: Introductionmentioning

confidence: 99%

“…This can be considered as the computational equivalent of a fragment screen, but where a specific pocket is targeted by each run. These fragments have been filtered using previously reported criteria and largely consistent with reported fragment library characteristics [11,12]. Although docking scores do not consistently show a correlation with ligand binding affinities [13], the expectation is that a druggable binding site is likely to score fragments more highly when productive hydrogen bonding and lipophillic interactions with the protein can be identified.…”

Section: Introductionmentioning

confidence: 99%

Using protein-ligand docking to assess the chemical tractability of inhibiting a protein target

Ward

2010

J Mol Model

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Assessing the difficulty of inhibiting a specific protein by a small molecule can be highly valuable in risk-assessment and prioritisation of a new target. In particular, when the disease linkage for a number of targets is broadly similar, being able to identify the most tractable can have a significant impact on informing target selection. With an increasing focus against new and novel protein classes, being able to assess the most likely targets to yield lead-like chemical start points can guide the selection and the lead-generation strategy implemented. This study exploits protein-ligand docking studies on published protein x-ray crystal structures to provide guidance on the feasibility of identifying small molecule inhibitors against a range of targets.Response to Reviewers: 1) I am not convinced that a biased fragment library (the bias is introduced via the filter criteria for logP, MW, and other parameters) should be able to judge the tractability of any target in general. What if potent fragment binders could not idenitified via docking just because they were removed from the initial fragment collection because of the filter criteria ? This concern is somehow reflected already in Fig 7A and 7B. A more general characterization of the fragment library (as expressed by the mean score of t he top 10% docking hits) is only hardly able to distinguish between druggable and "prodrug" binding sites (SP) or "prodrug" and undruggable sites (XP) . A more rigorous approach could for instance be based on a random selection of compounds rather than on a biased fragment library.The key criteria used to build this fragment library is chemical/structural diversity (there is a reference to the details behind how this library was built). This ensures that the library covers a broad range of scaffolds and interaction types. This allows the mapping of a target binding site by fragment screening (experimentally or computationally). The reason for focusing this fragment library around the stated criteria is that fragment hits with properties in these ranges are suggested as being good chemical start points for fragment-based lead generation projects where achieving an orally bioavailable drug is the aim (i.e. a molecule largely compliant with Lipinski-like criteria). See the report below (also reference 12) from Astex on 'Rule of Three' criteria. Our fragment library, however, has not been filtered as harshly as this library as we want to maximise the information from the screen (which is to some extent addressing the issue raised by the reviewer). The other key reason for using this library is that published fragment libraries (filtered similarly to the library I have used in this study) have been used to assess drugability using experimental screening approaches as shown in the reference 4 in the manuscript (below). Therefore there is validation for the use of libraries filtered by these criteria to assess drugability experimentally so I believe it is a suitable fragment set to assess targets computationally. Due to ...

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“…NMR affinity screening was used to identify the initial hits that were evolved into micromolar inhibitors using a combination of X-ray crystallography, molecular modeling, surface plasmon resonance and functional enzyme assays. Fragment-based lead generation has also been successfully applied across a number of therapeutic areas at AstraZeneca [26].…”

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confidence: 99%

Challenges of fragment screening

Joseph‐McCarthy

2009

J Comput Aided Mol Des

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An Integrated Approach to Fragment-Based Lead Generation:Philosophy, Strategy and Case Studies from AstraZenecas Drug Discovery Programmes

Cited by 125 publications

References 128 publications

Cell-based and virtual fragment screening for adrenergic α2C receptor agonists

Cell-based and virtual fragment screening for adrenergic α2C receptor agonists

Using protein-ligand docking to assess the chemical tractability of inhibiting a protein target

Challenges of fragment screening

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