The use of virtual screening and differential scanning fluorimetry for the rapid identification of fragments active against MEK1

Amaning, Kwame; Lowinski, Maryse; Vallée, François; Steier, Valérie; Marcireau, Christophe; Ugolini, Antonio; Delorme, Cécile; Foucalt, Frédéric; McCort, Gary; Derimay, Nathalie; Andouche, Cyrielle; Vougier, Stéphanie; Llopart, Sylvie; Halland, Nis; Rak, Alexey

doi:10.1016/j.bmcl.2013.04.003

Cited by 22 publications

(20 citation statements)

References 31 publications

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“… 10 The library used for screening was designed by a target-restrained virtual screening campaign, so that a large number of binding fragments was expected. 11 The results presented here demonstrate that MST generates quantitative data for affinity rankings in a rapid and precise manner. Fourteen out of 19 fragments subjected to crystallization studies within the MST top-25 affinity ranking were shown to bind to MEK1 by X-ray crystallography.…”

Section: Introductionmentioning

confidence: 66%

“…The relatively high hit rate reflects the preselection of the library by virtual screen for fragments that specifically bind to the ATP binding cleft of MEK1. 11 The hit rate determined by MST is higher than those determined by other biophysical techniques for the same library on MEK1, highlighting the technique’s ability to identify a larger pool of chemical matter that could be explored at the start of a hit-to-lead process. From the 73 fragments that induced MST responses, 25 showed dose–response curves with clearly defined bound and unbound states and K d values of <200 µM, and were classified as best hits ( Fig.…”

Section: Resultsmentioning

confidence: 90%

“…Seven out of eight previously characterized X-ray positive binders 11 were among the top-15 fragments ranked based on their MST affinity ( Fig. 2A ).…”

Section: Resultsmentioning

confidence: 99%

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An Automated Microscale Thermophoresis Screening Approach for Fragment-Based Lead Discovery

et al. 2016

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Fragment-based lead discovery has proved to be an effective alternative to high-throughput screenings in identifying chemical matter that can be developed into robust lead compounds. The search for optimal combinations of biophysical techniques that can correctly and efficiently identify and quantify binding can be challenging due to the physicochemical properties of fragments. In order to minimize the time and costs of screening, optimal combinations of biophysical techniques with maximal information content, sensitivity, and robustness are needed. Here we describe an approach utilizing automated microscale thermophoresis (MST) affinity screening to identify fragments active against MEK1 kinase. MST identified multiple hits that were confirmed by X-ray crystallography but not detected by orthogonal methods. Furthermore, MST also provided information about ligand-induced aggregation and protein denaturation. The technique delivered a large number of binders while reducing experimentation time and sample consumption, demonstrating the potential of MST to execute and maximize the efficacy of fragment screening campaigns.

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Section: Introductionmentioning

confidence: 66%

Section: Resultsmentioning

confidence: 90%

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An Automated Microscale Thermophoresis Screening Approach for Fragment-Based Lead Discovery

et al. 2016

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“…32−34 It is ignored in the majority of cases by docking compounds strictly to a crystal structure, 35−37 although there are examples that have used multiple crystal structures, 38−40 NMR structures, 41−44 or a combination of the two. 451,461 Albeit less common, the use of molecular dynamics (MD) simulations to generate an ensemble of structures has also been reported in virtual screening efforts that have led to active compounds.…”

Section: Introductionmentioning

confidence: 99%

Enrichment of Chemical Libraries Docked to Protein Conformational Ensembles and Application to Aldehyde Dehydrogenase 2

Wang

Buchman

et al. 2014

J. Chem. Inf. Model.

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Molecular recognition is a complex process that involves a large ensemble of structures of the receptor and ligand. Yet, most structure-based virtual screening is carried out on a single structure typically from X-ray crystallography. Explicit-solvent molecular dynamics (MD) simulations offer an opportunity to sample multiple conformational states of a protein. Here we evaluate our recently developed scoring method SVMSP in its ability to enrich chemical libraries docked to MD structures of seven proteins from the Directory of Useful Decoys (DUD). SVMSP is a target-specific rescoring method that combines machine learning with statistical potentials. We find that enrichment power as measured by the area under the ROC curve (ROC-AUC) is not affected by increasing the number of MD structures. Among individual MD snapshots, many exhibited enrichment that was significantly better than the crystal structure, but no correlation between enrichment and structural deviation from crystal structure was found. We followed an innovative approach by training SVMSP scoring models using MD structures (SVMSPMD). The resulting models were applied to two difficult cases (p38 and CDK2) for which enrichment was not better than random. We found remarkable increase in enrichment power, particularly for p38, where the ROC-AUC increased by 0.30 to 0.85. Finally, we explored approaches for a priori identification of MD snapshots with high enrichment power from an MD simulation in the absence of active compounds. We found that the use of randomly selected compounds docked to the target of interest using SVMSP led to notable enrichment for EGFR and Src MD snapshots. SVMSP rescoring of protein–compound MD structures was applied for the search of small-molecule inhibitors of the mitochondrial enzyme aldehyde dehydrogenase 2 (ALDH2). Rank-ordering of a commercial library of 50 000 compounds docked to MD structures of ALDH2 led to five small-molecule inhibitors. Four compounds had IC50s below 5 μM. These compounds serve as leads for the design and synthesis of more potent and selective ALDH2 inhibitors.

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“…Virtual screening requires a minimum of two inputs, (1) a three-dimensional model of the ligand (drug), and (2) a three-dimensional model of the receptor (protein) [ 322 ], the latter generated from the atomic studies of proteins via X-ray crystallography or NMR spectroscopy [ 323 ]. Virtual screening is not a truly “stand-alone” technique and has often been combined with additional biophysical techniques besides NMR spectroscopy and/or X-ray crystallography [ 324 ], such as differential scanning fluorimetry [ 325 ], fluorescence polarization, and surface plasmon resonance [ 324 ]. In this section, we briefly introduce how virtual screening has been combined with NMR spectroscopy, and how they are complementary approaches to each other in drug design.…”

Section: Nmr Methods For Drug Discovery and Drug Developmentmentioning

confidence: 99%

NMR as a “Gold Standard” Method in Drug Design and Discovery

et al. 2020

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Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a “gold standard” platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development.

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The use of virtual screening and differential scanning fluorimetry for the rapid identification of fragments active against MEK1

Cited by 22 publications

References 31 publications

An Automated Microscale Thermophoresis Screening Approach for Fragment-Based Lead Discovery

An Automated Microscale Thermophoresis Screening Approach for Fragment-Based Lead Discovery

Enrichment of Chemical Libraries Docked to Protein Conformational Ensembles and Application to Aldehyde Dehydrogenase 2

NMR as a “Gold Standard” Method in Drug Design and Discovery

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