Discovery and SAR Studies of Orally Active Somatostatin Receptor Subtype-2 (SSTR2) Agonists for the Treatment of Acromegaly

Ishida, Akiharu; Tajima, Yuko; Okabe, Yasuyuki; Matsushita, Tomonori; Sekiguchi, Tetsuya; Imaide, Satomi; Nomura, Yoshihiko; Tanaka, Motoyuki; Nojima, Shoji; Yoshida, Atsushi; Iyoda, Yoko; Aoki, Shohei; Nishio, Takuya; Komagata, Tatsuya; Iwaki, Masanori; Shono, Tomoyuki; Naganawa, Atsushi; Imagawa, Akira

doi:10.1021/acschemneuro.0c00124

Cited by 10 publications

(8 citation statements)

References 10 publications

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“…Ishida et al [115] set out to identify nonpeptidic orally available small molecule somatostatin receptor subtype-2 (SSTR2) agonists. The group decided on a quinoline scaffold and synthesized a series of derivatives, testing their SSTR2 agonist activity by an intracellular cAMP concentration measurement assay.…”

Section: Somatostatin Receptor Subtype-2mentioning

confidence: 99%

Mind the Gap—Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

et al. 2022

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G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, the discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and the elucidation of ligand–receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning are highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

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Section: Somatostatin Receptor Subtype-2mentioning

confidence: 99%

Mind the Gap—Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

et al. 2022

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show abstract

“…Ishida et al [121] set out to identify nonpeptidic orally available small molecule somatostatin receptor subtype-2 (SSTR2) agonists. The group synthesized quinoline derivatives and tested their SSTR2 agonist activity by an intracellular cAMP concentration measurement assay.…”

Section: Somatostatin Receptor Subtype-2mentioning

confidence: 99%

Mind the Gap – Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

Noonan¹,

Denzinger²,

Talagayev³

et al. 2022

Preprint

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G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. 3D pharmacophore models are powerful computational tools in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning will be highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

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“…Neuroendocrine tumors (NETs) are rare and serious tumors that are commonly caused by the excessive secretion of hormones, which result in complicated clinical syndromes and disorders 1 , 2 . For example, pituitary adenoma is a tumor of the pituitary gland that produces too much growth hormone (GH) and can lead to acromegaly 3 .…”

Section: Introductionmentioning

confidence: 99%

Prospect of acromegaly therapy: molecular mechanism of clinical drugs octreotide and paltusotine

Zhao

et al. 2023

Nat Commun

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Somatostatin receptor 2 (SSTR2) is highly expressed in neuroendocrine tumors and represents as a therapeutic target. Several peptide analogs mimicking the endogenous ligand somatostatin are available for clinical use, but poor therapeutic effects occur in a subset of patients, which may be correlated with subtype selectivity or cell surface expression. Here, we clarify the signal bias profiles of the first-generation peptide drug octreotide and a new-generation small molecule paltusotine by evaluating their pharmacological characteristics. We then perform cryo-electron microscopy analysis of SSTR2-Gi complexes to determine how the drugs activate SSTR2 in a selective manner. In this work, we decipher the mechanism of ligand recognition, subtype selectivity and signal bias property of SSTR2 sensing octreotide and paltusotine, which may aid in designing therapeutic drugs with specific pharmacological profiles against neuroendocrine tumors.

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Discovery and SAR Studies of Orally Active Somatostatin Receptor Subtype-2 (SSTR2) Agonists for the Treatment of Acromegaly

Cited by 10 publications

References 10 publications

Mind the Gap—Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

Mind the Gap—Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

Mind the Gap – Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

Prospect of acromegaly therapy: molecular mechanism of clinical drugs octreotide and paltusotine

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