Structure–Affinity Relationship Analysis of Selective FKBP51 Ligands

The FK506-binding protein 51 (FKBP51) is a promising drug target for the treatment of stress-related psychiatric or metabolic disorders. Just recently, the first selective ligands for FKBP51 were reported based on an induced fit mechanism, but they are too large for a further drug development process. We therefore designed and synthesized a novel series of selective ligands to explore the requirements necessary for binding to the induced-fit conformation. All ligands of this series show no binding toward the structurally very similar antitarget FKBP52. With the cocrystal structure of the best ligand in this novel series we confirmed the induced fit mechanism. Furthermore, the structure–affinity relationship provides information about beneficial structural features, which is valuable for the development of improved FKBP51-directed drugs

Rapid, Structure-Based Exploration of Pipecolic Acid Amides as Novel Selective Antagonists of the FK506-Binding Protein 51

The FK506-binding protein 51 (FKBP51) is a key regulator of stress hormone receptors and an established risk factor for stress-related disorders. Drug development for FKBP51 has been impaired by the structurally similar but functionally opposing homologue FKBP52. High selectivity between FKBP51 and FKBP52 can be achieved by ligands that stabilize a recently discovered FKBP51-favoring conformation. However, drug-like parameters for these ligands remained unfavorable. In the present study, we replaced the potentially labile pipecolic ester group of previous FKBP51 ligands by various low molecular weight amides. This resulted in the first series of pipecolic acid amides, which had much lower molecular weights without affecting FKBP51 selectivity. We discovered a geminally substituted cyclopentyl amide as a preferred FKBP51-binding motif and elucidated its binding mode to provide a new lead structure for future drug optimization

Rapid, Structure-Based Exploration of Pipecolic Acid Amides as Novel Selective Antagonists of the FK506-Binding Protein 51

The FK506-binding protein 51 (FKBP51) is a key regulator of stress hormone receptors and an established risk factor for stress-related disorders. Drug development for FKBP51 has been impaired by the structurally similar but functionally opposing homologue FKBP52. High selectivity between FKBP51 and FKBP52 can be achieved by ligands that stabilize a recently discovered FKBP51-favoring conformation. However, drug-like parameters for these ligands remained unfavorable. In the present study, we replaced the potentially labile pipecolic ester group of previous FKBP51 ligands by various low molecular weight amides. This resulted in the first series of pipecolic acid amides, which had much lower molecular weights without affecting FKBP51 selectivity. We discovered a geminally substituted cyclopentyl amide as a preferred FKBP51-binding motif and elucidated its binding mode to provide a new lead structure for future drug optimization

Rapid, Structure-Based Exploration of Pipecolic Acid Amides as Novel Selective Antagonists of the FK506-Binding Protein 51

The FK506-binding protein 51 (FKBP51) is a key regulator of stress hormone receptors and an established risk factor for stress-related disorders. Drug development for FKBP51 has been impaired by the structurally similar but functionally opposing homologue FKBP52. High selectivity between FKBP51 and FKBP52 can be achieved by ligands that stabilize a recently discovered FKBP51-favoring conformation. However, drug-like parameters for these ligands remained unfavorable. In the present study, we replaced the potentially labile pipecolic ester group of previous FKBP51 ligands by various low molecular weight amides. This resulted in the first series of pipecolic acid amides, which had much lower molecular weights without affecting FKBP51 selectivity. We discovered a geminally substituted cyclopentyl amide as a preferred FKBP51-binding motif and elucidated its binding mode to provide a new lead structure for future drug optimization

A Novel Decalin-Based Bicyclic Scaffold for FKBP51-Selective Ligands

Selective inhibition of FKBP51 has emerged as possible novel treatment for diseases like major depressive disorder, obesity, chronic pain, and certain cancers. The current FKBP51 inhibitors are rather large, flexible, and have to be further optimized. By using a structure-based rigidification strategy, we hereby report the design and synthesis of a novel promising bicyclic scaffold for FKBP51 ligands. The structure–activity analysis revealed the decalin scaffold as the best moiety for the selectivity-enabling subpocket of FBKP51. The resulting compounds retain high potency for FKBP51 and excellent selectivity over the close homologue FKBP52. With the cocrystal structure of an advanced ligand in this novel series, we show how the decalin locks the key selectivity-inducing cyclohexyl moiety of the ligand in a conformation typical for FKBP51-selective binding. The best compound 29 produces cell death in a HeLa-derived KB cell line, a cellular model of cervical adenocarcinoma, where FKBP51 is highly overexpressed. Our results show how FKBP51 inhibitors can be rigidified and extended while preserving FKBP51 selectivity. Such inhibitors might be novel tools in the treatment of human cancers with deregulated FKBP51

A Novel Decalin-Based Bicyclic Scaffold for FKBP51-Selective Ligands

Selective inhibition of FKBP51 has emerged as possible novel treatment for diseases like major depressive disorder, obesity, chronic pain, and certain cancers. The current FKBP51 inhibitors are rather large, flexible, and have to be further optimized. By using a structure-based rigidification strategy, we hereby report the design and synthesis of a novel promising bicyclic scaffold for FKBP51 ligands. The structure–activity analysis revealed the decalin scaffold as the best moiety for the selectivity-enabling subpocket of FBKP51. The resulting compounds retain high potency for FKBP51 and excellent selectivity over the close homologue FKBP52. With the cocrystal structure of an advanced ligand in this novel series, we show how the decalin locks the key selectivity-inducing cyclohexyl moiety of the ligand in a conformation typical for FKBP51-selective binding. The best compound 29 produces cell death in a HeLa-derived KB cell line, a cellular model of cervical adenocarcinoma, where FKBP51 is highly overexpressed. Our results show how FKBP51 inhibitors can be rigidified and extended while preserving FKBP51 selectivity. Such inhibitors might be novel tools in the treatment of human cancers with deregulated FKBP51

Additional file 1 of Propensity score analysis with missing data using a multi-task neural network

Additional file 1: Table S1 Variable descriptions for the real dataset. Table S2 Summary of the real dataset. Table S3 Estimation of the true effect in the simulated datasets using three different methods under the MAR mechanism. Table S4 Estimation of the true effect in the simulated datasets using three different methods under the MNAR mechanism. Table S5 Estimation of the true effect in the real datasets using three different methods under the MAR mechanism. Table S6 Estimation of the true effect in the real datasets using three different methods under the MNAR mechanism. Table S7 Regression coefficients for real-world data without missing values. Table S8 Spearman's correlation coefficient for each input variable in real-world data

Table_1_A systemic review and meta-analysis comparing the ability of diagnostic of the third heart sound and left ventricular ejection fraction in heart failure.docx

ObjectiveThis study aimed to compare the sensitivity and specificity of diagnosis between the third heart sound (S3) and left ventricular ejection fraction (LVEF) in heart failure (HF).MethodsRelevant studies were searched in PubMed, SinoMed, China National Knowledge Infrastructure, and the Cochrane Trial Register until February 20, 2022. The sensitivity, specificity, likelihood ratio (LR), and diagnostic odds ratio (DOR) were pooled. The symmetric receiver operator characteristic curve (SROC) and Fagan’s nomogram were drawn. The source of heterogeneity was explored by meta-regression and subgroup analysis.ResultsA total of 19 studies, involving 5,614 participants, were included. The combined sensitivity of S3 was 0.23 [95% confidence interval (CI) (0.15–0.33), specificity was 0.94 [95% CI (0.82–0.98)], area under the SROC curve was 0.49, and the DOR was 4.55; while the sensitivity of LVEF was 0.70 [95% CI (0.53–0.83)], specificity was 0.79 [95% CI (0.75–0.82)], area under the SROC curve was 0.79, and the DOR was 8.64. No publication bias was detected in Deeks’ funnel plot. The prospective design, partial verification bias, and blind contributed to the heterogeneity in specificity, while adequate description of study participants contributed to the heterogeneity in sensitivity. In Fagan’s nomogram, the post-test probability was 48% when the pre-test probability was set as 20%, while in LVEF, the post-test probability was 45% when the pre-test probability was set as 20%.ConclusionThe use of S3 alone presented lower sensitivity in diagnosing HF compared with LVEF, whereas it was useful in early pathological assessment.</p

Image_2_A systemic review and meta-analysis comparing the ability of diagnostic of the third heart sound and left ventricular ejection fraction in heart failure.TIF

ObjectiveThis study aimed to compare the sensitivity and specificity of diagnosis between the third heart sound (S3) and left ventricular ejection fraction (LVEF) in heart failure (HF).MethodsRelevant studies were searched in PubMed, SinoMed, China National Knowledge Infrastructure, and the Cochrane Trial Register until February 20, 2022. The sensitivity, specificity, likelihood ratio (LR), and diagnostic odds ratio (DOR) were pooled. The symmetric receiver operator characteristic curve (SROC) and Fagan’s nomogram were drawn. The source of heterogeneity was explored by meta-regression and subgroup analysis.ResultsA total of 19 studies, involving 5,614 participants, were included. The combined sensitivity of S3 was 0.23 [95% confidence interval (CI) (0.15–0.33), specificity was 0.94 [95% CI (0.82–0.98)], area under the SROC curve was 0.49, and the DOR was 4.55; while the sensitivity of LVEF was 0.70 [95% CI (0.53–0.83)], specificity was 0.79 [95% CI (0.75–0.82)], area under the SROC curve was 0.79, and the DOR was 8.64. No publication bias was detected in Deeks’ funnel plot. The prospective design, partial verification bias, and blind contributed to the heterogeneity in specificity, while adequate description of study participants contributed to the heterogeneity in sensitivity. In Fagan’s nomogram, the post-test probability was 48% when the pre-test probability was set as 20%, while in LVEF, the post-test probability was 45% when the pre-test probability was set as 20%.ConclusionThe use of S3 alone presented lower sensitivity in diagnosing HF compared with LVEF, whereas it was useful in early pathological assessment.</p

Image_1_A systemic review and meta-analysis comparing the ability of diagnostic of the third heart sound and left ventricular ejection fraction in heart failure.TIF

ObjectiveThis study aimed to compare the sensitivity and specificity of diagnosis between the third heart sound (S3) and left ventricular ejection fraction (LVEF) in heart failure (HF).MethodsRelevant studies were searched in PubMed, SinoMed, China National Knowledge Infrastructure, and the Cochrane Trial Register until February 20, 2022. The sensitivity, specificity, likelihood ratio (LR), and diagnostic odds ratio (DOR) were pooled. The symmetric receiver operator characteristic curve (SROC) and Fagan’s nomogram were drawn. The source of heterogeneity was explored by meta-regression and subgroup analysis.ResultsA total of 19 studies, involving 5,614 participants, were included. The combined sensitivity of S3 was 0.23 [95% confidence interval (CI) (0.15–0.33), specificity was 0.94 [95% CI (0.82–0.98)], area under the SROC curve was 0.49, and the DOR was 4.55; while the sensitivity of LVEF was 0.70 [95% CI (0.53–0.83)], specificity was 0.79 [95% CI (0.75–0.82)], area under the SROC curve was 0.79, and the DOR was 8.64. No publication bias was detected in Deeks’ funnel plot. The prospective design, partial verification bias, and blind contributed to the heterogeneity in specificity, while adequate description of study participants contributed to the heterogeneity in sensitivity. In Fagan’s nomogram, the post-test probability was 48% when the pre-test probability was set as 20%, while in LVEF, the post-test probability was 45% when the pre-test probability was set as 20%.ConclusionThe use of S3 alone presented lower sensitivity in diagnosing HF compared with LVEF, whereas it was useful in early pathological assessment.</p