High-throughput screening and structure-based approaches to hit discovery: is there a clear winner?

Jhoti, Harren; Rees, Stephen Edward; Solari, Roberto

doi:10.1517/17460441.2013.857654

Cited by 14 publications

(9 citation statements)

References 34 publications

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“…1 Kinases modify substrates by chemically adding a phosphate group from adenosine triphosphate (ATP), and this phosphorylation event controls many cellular processes, making them attractive therapeutic targets. 2 Identification of starting hits for biological targets can be based on approaches such as high throughput screening (HTS) for diversity or structure-based drug design (SBDD) as a focused design approach, 3 but in a target class such as kinases an efficient way of finding hits is from focused or knowledgebased screening. Screening a focused set containing compounds that have previously been shown to have activity against kinases has proven to be a highly successful strategy in discovering hits against new kinases.…”

mentioning

confidence: 99%

From PIM1 to PI3Kδ via GSK3β: Target Hopping through the Kinome

Henley

Bax²,

Inglesby³

et al. 2017

ACS Med. Chem. Lett.

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Selective inhibitors of phosphoinositide 3-kinase delta are of interest for the treatment of inflammatory diseases. Initial optimization of a 3-substituted indazole hit compound targeting the kinase PIM1 focused on improving selectivity over GSK3β through consideration of differences in the ATP binding pockets. Continued kinase cross-screening showed PI3Kδ activity in a series of 4,6-disubstituted indazole compounds, and subsequent structure-activity relationship exploration led to the discovery of an indole-containing lead compound as a potent PI3Kδ inhibitor with selectivity over the other PI3K isoforms.

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mentioning

confidence: 99%

From PIM1 to PI3Kδ via GSK3β: Target Hopping through the Kinome

Henley

Bax²,

Inglesby³

et al. 2017

ACS Med. Chem. Lett.

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“…Drug discovery and development takes an average of 10-15 years with an approximate cost of US$800 million (DiMasi et al 2003;Song et al 2009) to US$1.8 billion (Paul et al 2010). Innovations in combinatorial chemistry that led to the increase of compound databases covering large chemical spaces aided in the expansion of drug discovery and the development of high-throughput screening (HTS) (Jhoti et al 2013;Lavecchia and Di Giovanni 2013). Despite this, the number of new molecular entities (NMEs) successfully launched into the market continued to decrease over the last several years (Paul et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Role of computer-aided drug design in modern drug discovery

Macalino¹,

Gosu²,

Hong³

et al. 2015

Arch. Pharm. Res.

575

316

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Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.

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“…Since the 1960s, molecular docking has become the most widely used method in SBDD. 37 Docking can provide theoretical calculations for target-ligand binding conformation and scores of their binding affinity, making it of great significance for both the initial screening of hit compounds and the computational analysis of lead compound binding patterns. Docking approaches comprise rigid docking from the classical drug-ligand “lock-and-key model”, and flexible docking from the later development of an “induced-fit model” and “conformational selection model”.…”

Section: Introductionmentioning

confidence: 99%

“…Since the 1960s, molecular docking has become the most widely used method in SBDD. 37 Docking can provide theoretical calculations for targetligand binding conformation and scores of their binding General workflow of computational approaches, including SBDD and LBDD, commonly used for GPCR drug discovery. General procedures for SBDD start with a compound library collection and target identification.…”

Section: Introductionmentioning

confidence: 99%

Trends in application of advancing computational approaches in GPCR ligand discovery

Zhu

Huang

et al. 2021

Exp Biol Med (Maywood)

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G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological structures, as well as improvements on computer power and algorithms, have led to unprecedented use of CADD for the discovery of novel GPCR modulators. Similarly, machine learning approaches are now widely applied in various fields of drug target research. This review briefly summarizes the application of rising CADD methodologies, as well as novel machine learning techniques, in GPCR structural studies and bioligand discovery in the past few years. Recent novel computational strategies and feasible workflows are updated, and representative cases addressing challenging issues on olfactory receptors, biased agonism, and drug-induced cardiotoxic effects are highlighted to provide insights into future GPCR drug discovery.

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High-throughput screening and structure-based approaches to hit discovery: is there a clear winner?

Cited by 14 publications

References 34 publications

From PIM1 to PI3Kδ via GSK3β: Target Hopping through the Kinome

From PIM1 to PI3Kδ via GSK3β: Target Hopping through the Kinome

Role of computer-aided drug design in modern drug discovery

Trends in application of advancing computational approaches in GPCR ligand discovery

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