aminopeptidase inhibitors
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2021 ◽  
Vol 35 (S1) ◽  
Author(s):  
Alex Croes ◽  
Jamila Boukari ◽  
Melissa Alvarez ◽  
Jennifer Clymer ◽  
Robert Flores ◽  
...  


Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1527
Author(s):  
Juho J. Miettinen ◽  
Romika Kumari ◽  
Gunnhildur Asta Traustadottir ◽  
Maiju-Emilia Huppunen ◽  
Philipp Sergeev ◽  
...  

Multiple myeloma (MM) is characterized by extensive immunoglobulin production leading to an excessive load on protein homeostasis in tumor cells. Aminopeptidases contribute to proteolysis by catalyzing the hydrolysis of amino acids from proteins or peptides and function downstream of the ubiquitin–proteasome pathway. Notably, aminopeptidases can be utilized in the delivery of antibody and peptide-conjugated drugs, such as melflufen, currently in clinical trials. We analyzed the expression of 39 aminopeptidase genes in MM samples from 122 patients treated at Finnish cancer centers and 892 patients from the CoMMpass database. Based on ranked abundance, LAP3, ERAP2, METAP2, TTP2, and DPP7 were highly expressed in MM. ERAP2, XPNPEP1, DPP3, RNPEP, and CTSV were differentially expressed between relapsed/refractory and newly diagnosed MM samples (p < 0.05). Sensitivity to melflufen was detected ex vivo in 11/15 MM patient samples, and high sensitivity was observed, especially in relapsed/refractory samples. Survival analysis revealed that high expression of XPNPEP1, RNPEP, DPP3, and BLMH (p < 0.05) was associated with shorter overall survival. Hydrolysis analysis demonstrated that melflufen is a substrate for aminopeptidases LAP3, LTA4H, RNPEP, and ANPEP. The sensitivity of MM cell lines to melflufen was reduced by aminopeptidase inhibitors. These results indicate critical roles of aminopeptidases in disease progression and the activity of melflufen in MM.



Biomolecules ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 659 ◽  
Author(s):  
Michał Talma ◽  
Artur Mucha

Designing side chain substituents complementary to enzyme binding pockets is of great importance in the construction of potent and selective phosphinic dipeptide inhibitors of metallo-aminopeptidases. Proper structure selection makes inhibitor construction more economic, as the development process typically consists of multiple iterative preparation/bioassay steps. On the basis of these principles, using noncomplex computation and modeling methodologies, we comprehensively screened 900 commercial precursors of the P1′ residues of phosphinic dipeptide and dehydrodipeptide analogs to identify the most promising ligands of 52 metallo-dependent aminopeptidases with known crystal structures. The results revealed several nonproteinogenic residues with an improved energy of binding compared with the best known inhibitors. The data are discussed taking into account the selectivity and stereochemical implications of the enzymes. Using this approach, we were able to identify nontrivial structural elements substituting the recognized phosphinic peptidomimetic scaffold of metallo-aminopeptidase inhibitors.



Molecules ◽  
2020 ◽  
Vol 25 (7) ◽  
pp. 1753 ◽  
Author(s):  
Joanna Ziemska ◽  
Jolanta Solecka ◽  
Małgorzata Jarończyk

Cancers are the leading cause of deaths worldwide. In 2018, an estimated 18.1 million new cancer cases and 9.6 million cancer-related deaths occurred globally. Several previous studies have shown that the enzyme, leucine aminopeptidase is involved in pathological conditions such as cancer. On the basis of the knowledge that isoquinoline alkaloids have antiproliferative activity and inhibitory activity towards leucine aminopeptidase, the present study was conducted a study which involved database search, virtual screening, and design of new potential leucine aminopeptidase inhibitors with a scaffold based on 3,4-dihydroisoquinoline. These compounds were then filtered through Lipinski’s “rule of five,” and 25 081 of them were then subjected to molecular docking. Next, three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed for the selected group of compounds with the best binding score results. The developed model, calculated by leave-one-out method, showed acceptable predictive and descriptive capability as represented by standard statistical parameters r2 (0.997) and q2 (0.717). Further, 35 compounds were identified to have an excellent predictive reliability. Finally, nine selected compounds were evaluated for drug-likeness and different pharmacokinetics parameters such as absorption, distribution, metabolism, excretion, and toxicity. Our methodology suggested that compounds with 3,4-dihydroisoquinoline moiety were potentially active in inhibiting leucine aminopeptidase and could be used for further in-depth in vitro and in vivo studies.



2020 ◽  
Vol 34 (S1) ◽  
pp. 1-1
Author(s):  
Natalia Condic ◽  
Cassandra Ramtahal ◽  
Jamila Boukari ◽  
Alex Croes ◽  
Calvin Nguyen ◽  
...  


Hypertension ◽  
2019 ◽  
Vol 74 (Suppl_1) ◽  
Author(s):  
Sharenya Chelvaretnam ◽  
Matthew Shen ◽  
Simon J Mountford ◽  
Philip E Thompson ◽  
Siew Yeen Chai ◽  
...  


2019 ◽  
Vol 72 (6) ◽  
pp. 461-468
Author(s):  
Tianhu Zhao ◽  
Jian Zhang ◽  
Maomao Tang ◽  
Luyan Z. Ma ◽  
Xiaoguang Lei


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3945-3945 ◽  
Author(s):  
Jacqueline Cloos ◽  
Godefridus J Peters ◽  
Marjon Al ◽  
Yehuda G Assaraf ◽  
Lixia Wang ◽  
...  

Abstract Tosedostat represents a next generation oral aminopeptidase inhibitor prodrug that has recently demonstrated promising activity in elderly patients with relapsed and refractory acute myeloid leukemia (AML). This prodrug is bio-activated to its hydrophilic active metabolite by intracellular esterases including carboxylesterase 1 (CES1) hence enhancing its cellular retention and promoting targeting of multiple aminopeptidases. Aminopeptidase inhibition provokes an amino acid deprivation response, inhibition of mTOR activity and blockade of protein synthesis. The fact that CES1 also has an important physiological function in cholesterol metabolism (i.e. conversion of cholesteryl-esters to cholesterol), and the notion that AML cells display an aberrant cholesterol metabolism, prompted us to explore whether or not statins, as inhibitors of the mevalonate-cholesterol biosynthesis pathway, can potentiate the cytotoxic activity of aminopeptidase inhibitor prodrugs. Here, we discovered that the antitumor activity of CHR2863, a close structural analogue of Tosedostat, is markedly potentiated by non-toxic and clinically achievable concentrations of statins. These findings were supported by the following lines of experimental evidence; (i) A strong synergy in cell growth inhibition (combination indices < 0.1) of CHR2863 with various statins (simvastatin, fluvastatin, lovastatin and pravastatin) was demonstrated for U937 AML cells and U937 sublines displaying acquired resistance to CHR2863. (ii) This potent synergy between CHR2863 and simvastatin was also observed with a spectrum of human AML cell lines including THP1, MV4-11, and KG1, but not with acute lymphocytic leukemia (CCRF-CEM) or solid tumor cell lines (MCF7 breast cancer, KB nasopharyngeal carcinoma and SW1573 non-small cell lung cancer). (iii) The synergistic effects with non-toxic concentrations of statins were specific for aminopeptidase inhibitors, either prodrugs (CHR2863) or direct inhibitors (e.g. Bestatin), but not for other unrelated cytotoxic agents, including daunorubicin and an esterase-dependent prodrug of a histone deacetylase inhibitor. (iv) The synergy of CHR2863 with statins was also corroborated by enhanced apoptosis induction and cell cycle arrest which increased the sub-G1 fraction. (v) Statin potentiation of CHR2863 activity was abrogated by co-administration with mevalonate or farnesylpyrophosphate, and partly by geranylgeranylpyrophosphate, suggesting the involvement of protein prenylation. Consistenly, the farnesyltransferase inhibitor FTI-277 also synergized with CHR2863 activity. (vi) Mechanistically, non-toxic concentrations of simvastatin impaired Rheb prenylation which is required for lysosomal membrane association and activation of mTOR. Hence, we propose that the dual inhibitory effect of impaired Rheb prenylation by statins and CHR2863-induced mTOR inhibition achieves a potent synergistic inhibition on human AML cells. (viii) Finally, retrospective analysis in a clinical trial of relapsed and refractory elderly AML patients treated with combination chemotherapy including Tosedostat (Cortes et al, Lancet Oncol 2013), revealed a clinical benefit for patients who used a statin. AML patients on statins (n=8) and Tosedostat (switching from 240 to 120 mg/m2) had a 50% probability of 6 months survival as compared to 3 months survival for patients not on statins (n= 27). The two-year overall survival (20%) was not impacted by statin administration. Collectively, these novel findings uncover a potent therapeutic combination of statins and aminopeptidase inhibitors for the treatment of AML. This drug combination warrants further clinical evaluation, particularly in the context of elderly patients using statins for other comorbidities. Disclosures Cloos: Takeda: Research Funding; Merus: Research Funding; Novartis: Research Funding; Helsinn: Research Funding; Johnson&Johnson: Research Funding. Wang:CTI BioPharma: Employment, Equity Ownership. Singer:CTI BioPharma: Employment, Other: Stock options. Cortes:Novartis: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Arog: Research Funding. Ossenkoppele:Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Genentech: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Research Funding; Roche: Consultancy, Honoraria; Celgene: Honoraria, Research Funding; Johnson & Johnson: Consultancy, Honoraria, Research Funding; Genmab: Research Funding.



2017 ◽  
Vol 71 (12) ◽  
pp. 2557-2568 ◽  
Author(s):  
Joanna Ziemska ◽  
Jolanta Solecka ◽  
Małgorzata Jarończyk


2017 ◽  
Vol 28 (5) ◽  
pp. 1044-1048 ◽  
Author(s):  
Fan Zhang ◽  
Dang Wu ◽  
Gao-Lei Wang ◽  
Shuang Hou ◽  
Ping Ou-Yang ◽  
...  


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