For research use only. Not for therapeutic Use.
MMAD (Cat No.:I002573) is a potent synthetic antineoplastic agent derived from auristatins, which are peptide-based compounds. It functions as a microtubule-disrupting agent, inhibiting cell division by preventing the proper formation and function of microtubules during mitosis. MMAD is often utilized in antibody-drug conjugates (ADCs), where it is linked to antibodies targeting specific cancer cells, allowing for targeted delivery and enhanced therapeutic efficacy. Its effectiveness against various cancers, including hematological malignancies, is under investigation, with ongoing studies exploring its potential in combination therapies to improve outcomes in cancer treatment.
| Catalog Number | I002573 |
| CAS Number | 203849-91-6 |
| Molecular Formula | C41H66N6O6S |
| Purity | ≥95% |
| Target | Microtubule/Tubulin |
| Solubility | DMSO: ≥ 24.5 mg/mL |
| Storage | Store at -20°C |
| IUPAC Name | (2S)-N-[(2S)-1-[[(3R,4S,5S)-3-methoxy-1-[(2S)-2-[(1R,2R)-1-methoxy-2-methyl-3-oxo-3-[[(1S)-2-phenyl-1-(1,3-thiazol-2-yl)ethyl]amino]propyl]pyrrolidin-1-yl]-5-methyl-1-oxoheptan-4-yl]-methylamino]-3-methyl-1-oxobutan-2-yl]-3-methyl-2-(methylamino)butanamide |
| InChI | InChI=1S/C41H66N6O6S/c1-12-27(6)36(46(9)41(51)35(26(4)5)45-39(50)34(42-8)25(2)3)32(52-10)24-33(48)47-21-16-19-31(47)37(53-11)28(7)38(49)44-30(40-43-20-22-54-40)23-29-17-14-13-15-18-29/h13-15,17-18,20,22,25-28,30-32,34-37,42H,12,16,19,21,23-24H2,1-11H3,(H,44,49)(H,45,50)/t27-,28+,30-,31-,32+,34-,35-,36-,37+/m0/s1 |
| InChIKey | BLUGYPPOFIHFJS-UUFHNPECSA-N |
| SMILES | CC[C@H](C)[C@@H]([C@@H](CC(=O)N1CCC[C@H]1[C@@H]([C@@H](C)C(=O)N[C@@H](CC2=CC=CC=C2)C3=NC=CS3)OC)OC)N(C)C(=O)[C@H](C(C)C)NC(=O)[C@H](C(C)C)NC |
| Reference | 1:Bioinformatics. 2014 Mar 1;30(5):682-9. doi: 10.1093/bioinformatics/btt566. Epub 2013 Oct 1. MMAD: microarray microdissection with analysis of differences is a computational tool for deconvoluting cell type-specific contributions from tissue samples.Liebner DA,Huang K,Parvin JD, PMID: 24085566 PMCID: PMC3933869 DOI: 10.1093/bioinformatics/btt566 </br><span>Abstract:</span> BACKGROUND: One of the significant obstacles in the development of clinically relevant microarray-derived biomarkers and classifiers is tissue heterogeneity. Physical cell separation techniques, such as cell sorting and laser-capture microdissection, can enrich samples for cell types of interest, but are costly, labor intensive and can limit investigation of important interactions between different cell types.RESULTS: We developed a new computational approach, called microarray microdissection with analysis of differences (MMAD), which performs microdissection in silico. Notably, MMAD (i) allows for simultaneous estimation of cell fractions and gene expression profiles of contributing cell types, (ii) adjusts for microarray normalization bias, (iii) uses the corrected Akaike information criterion during model optimization to minimize overfitting and (iv) provides mechanisms for comparing gene expression and cell fractions between samples in different classes. Computational microdissection of simulated and experimental tissue mixture datasets showed tight correlations between predicted and measured gene expression of pure tissues as well as tight correlations between reported and estimated cell fraction for each of the individual cell types. In simulation studies, MMAD showed superior ability to detect differentially expressed genes in mixed tissue samples when compared with standard metrics, including both significance analysis of microarrays and cell type-specific significance analysis of microarrays.CONCLUSIONS: We have developed a new computational tool called MMAD, which is capable of performing robust tissue microdissection in silico, and which can improve the detection of differentially expressed genes. MMAD software as implemented in MATLAB is publically available for download at http://sourceforge.net/projects/mmad/. |
