Covalent Allosteric Inhibitors of Akt Generated Using a Click Fragment Approach

Westhuizen, Leandi van der; Weisner, Jörn; Taher, Abu; Landel, Ina; Quambusch, Lena; Lindemann, Marius; Uhlenbrock, Niklas; Müller, Matthias; Green, Ivan R.; Pelly, Stephen C.; Rauh, Daniel; Otterlo, Willem A. L. van

doi:10.1002/cmdc.202100776

Cited by 3 publications

(2 citation statements)

References 48 publications

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“…In addition to these, application of ML/AI in CCDD has recently started emerging both in academia ,, and in industry . Although not extensively, computational strategies have also been explored in the design of allosteric covalent drugs. ,− Despite these advancements, CCDD still has a long way to go. Unlike computational treatments for non-covalent drug discovery, which is quite matured, ,− CCDD has to improve significantly in several areas to become a reliable tool to guide medicinal chemists on a daily basis.…”

Section: Discussionmentioning

confidence: 99%

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Hasan,

Ray,

Saha

2023

J. Phys. Chem. B

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Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where "evaluation of the binding affinity" and "a detailed mechanistic understanding on covalent inhibition" are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in "Computational Covalent Drug Discovery (CCDD)". We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.

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Section: Discussionmentioning

confidence: 99%

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Hasan,

Ray,

Saha

2023

J. Phys. Chem. B

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“…Fourth, of particular interest, is the absence of publications reporting on the computer-assisted design of covalent inhibitors. It is worth noting that two specific cysteine residues, well conserved among the three AKT isoforms (corresponding to Cys296 and Cys310 in AKT1), are located in the proximity of the allosteric site and have been already exploited in the identification of covalent inhibitors [ 8 , 71 , 83 , 84 , 85 ]. These small molecules possess both the selectivity resulting from targeting the allosteric pocket and the prolonged target residence time ensured by the covalent modification of the two non-catalytic cysteines in the AKT activation loop.…”

Section: Discussionmentioning

confidence: 99%

Computer-Aided Identification of Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein

Primavera,

Palazzotti,

Barreca

et al. 2023

Pharmaceuticals

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AKT (also known as PKB) is a serine/threonine kinase that plays a pivotal regulatory role in the PI3K/AKT/mTOR signaling pathway. Dysregulation of AKT activity, especially its hyperactivation, is closely associated with the development of various human cancers and resistance to chemotherapy. Over the years, a wide array of AKT inhibitors has been discovered through experimental and computational approaches. In this regard, herein we present a comprehensive overview of AKT inhibitors identified using computer-assisted drug design methodologies (including docking-based and pharmacophore-based virtual screening, machine learning, and quantitative structure–activity relationships) and successfully validated small molecules endowed with anticancer activity. Thus, this review provides valuable insights to support scientists focused on AKT inhibition for cancer treatment and suggests untapped directions for future computer-aided drug discovery efforts.

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Covalent Allosteric Inhibitors of Akt Generated Using a Click Fragment Approach

et al. 2022

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Akt is a protein kinase that has been implicated in the progression of cancerous tumours. A number of covalent allosteric Akt inhibitors are known, and based on these scaffolds, a small library of novel potential covalent allosteric imidazopyridine-based inhibitors was designed. The envisaged compounds were synthesised, with click chemistry enabling a modular approach to a number of the target compounds. The binding modes, potencies and antiproliferative activities of these synthesised compounds were explored, thereby furthering the structure activity relationship knowledge of this class of Akt inhibitors. Three novel covalent inhibitors were identified, exhibiting moderate activity against Akt1 and various cancer cell lines, potentially paving the way for future covalent allosteric inhibitors with improved properties.

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Covalent Allosteric Inhibitors of Akt Generated Using a Click Fragment Approach

Cited by 3 publications

References 48 publications

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Computer-Aided Identification of Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein

Covalent Allosteric Inhibitors of Akt Generated Using a Click Fragment Approach

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