Identification of a novel class of androgen receptor antagonists based on the bicyclic-1H-isoindole-1,3(2H)-dione nucleus

Salvati, Mark; Balog, Aaron; Wei, Donna; Pickering, Dacia; Attar, Ricardo M.; Geng, Jieping; Rizzo, Christopher; Hunt, John T.; Gottardis, Marco M.; Weinmann, Roberto; Martinez, Rogelio L.

doi:10.1016/j.bmcl.2004.10.051

Cited by 46 publications

(28 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All molecular structures and biological activities of the studied hydantoin compounds as androgen receptor antagonists were taken from the literature . The biological activities reported as IC 50 (n m ) values were firstly converted as usual into logarithmic scale pIC 50 (M), which were used as dependent variable in the present modeling.…”

Section: Methodsmentioning

confidence: 99%

Ligand Efficiency Outperforms pIC₅₀ on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Bai

Liu

et al. 2015

Chem Biol Drug Des

View full text Add to dashboard Cite

The concept of ligand efficiency is defined as biological activity in each molecular size and is widely accepted throughout the drug design community. Among different LE indices, surface efficiency index (SEI) was reported to be the best one in support vector machine modeling, much better than the generally and traditionally used end-point pIC50. In this study, 2D multiple linear regression and 3D comparative molecular field analysis methods are employed to investigate the structure-activity relationships of a series of androgen receptor antagonists, using pIC50 and SEI as dependent variables to verify the influence of using different kinds of end-points. The obtained results suggest that SEI outperforms pIC50 on both MLR and CoMFA models with higher stability and predictive ability. After analyzing the characteristics of the two dependent variables SEI and pIC50, we deduce that the superiority of SEI maybe lie in that SEI could reflect the relationship between molecular structures and corresponding bioactivities, in nature, better than pIC50. This study indicates that SEI could be a more rational parameter to be optimized in the drug discovery process than pIC50.

show abstract

Section: Methodsmentioning

confidence: 99%

Ligand Efficiency Outperforms pIC₅₀ on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Bai

Liu

et al. 2015

Chem Biol Drug Des

View full text Add to dashboard Cite

show abstract

“…BMS has a very broad portfolio of AR ligands, many of which are antagonists [ Balog et al, 2004 ; Salvati et al, 2005a ; Salvati et al, 2005b ]. Examples of the diversity within the patented AR ligand template portfolio have been recently reviewed [ Mohler et al, 2008 ].…”

Section: Sarms In Preclinical Developmentmentioning

confidence: 99%

Selective androgen receptor modulators in preclinical and clinical development

et al. 2008

View full text Add to dashboard Cite

Androgen receptor (AR) plays a critical role in the function of several organs including primary and accessory sexual organs, skeletal muscle, and bone, making it a desirable therapeutic target. Selective androgen receptor modulators (SARMs) bind to the AR and demonstrate osteo-and myo-anabolic activity; however, unlike testosterone and other anabolic steroids, these nonsteroidal agents produce less of a growth effect on prostate and other secondary sexual organs. SARMs provide therapeutic opportunities in a variety of diseases, including muscle wasting associated with burns, cancer, or end-stage renal disease, osteoporosis, frailty, and hypogonadism. This review summarizes the current standing of research and development of SARMs, crystallography of AR with SARMs, plausible mechanisms for their action and the potential therapeutic indications for this emerging class of drugs.

show abstract

“…Novel classes of AR antagonists are being developed which have binding affinities for wild‐type AR that are over 10 times greater than that of bicalutamide, which of the clinically available nonsteroidal AR antagonists has the highest affinity for AR [16]. Importantly, some of these compounds also potently bind to and antagonize AR with mutations, such as T877A and other mutations in the AR LBD.…”

Section: Novel Classical Ar Antagonistsmentioning

confidence: 99%

Secondary hormonal therapy for prostate cancer: what lies on the horizon?

2007

View full text Add to dashboard Cite

Androgen deprivation therapy with medical or surgical castration is generally the first‐line treatment against advanced prostate cancer. Almost invariably, metastatic prostate cancer overcomes testosterone depletion and grows, despite castrate levels of testosterone. Despite advances in cytotoxic chemotherapy, secondary hormonal therapies are often used after the development of castrate‐resistant prostate cancer. Secondary hormonal therapies either lower the androgen levels further or directly antagonize the androgen receptor in prostate cancer cells. We discuss novel secondary hormonal agents that are under development, which work by either inhibiting androgen synthesis or directly targeting the androgen receptor.

show abstract

Identification of a novel class of androgen receptor antagonists based on the bicyclic-1H-isoindole-1,3(2H)-dione nucleus

Cited by 46 publications

References 15 publications

Ligand Efficiency Outperforms pIC₅₀ on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Ligand Efficiency Outperforms pIC₅₀ on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Selective androgen receptor modulators in preclinical and clinical development

Secondary hormonal therapy for prostate cancer: what lies on the horizon?

Contact Info

Product

Resources

About

Identification of a novel class of androgen receptor antagonists based on the bicyclic-1H-isoindole-1,3(2H)-dione nucleus

Cited by 46 publications

References 15 publications

Ligand Efficiency Outperforms pIC50 on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Ligand Efficiency Outperforms pIC50 on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Selective androgen receptor modulators in preclinical and clinical development

Secondary hormonal therapy for prostate cancer: what lies on the horizon?

Contact Info

Product

Resources

About

Ligand Efficiency Outperforms pIC₅₀ on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists

Ligand Efficiency Outperforms pIC₅₀ on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists