Interaction between double helix DNA fragments and a new topopyrone acting as human topoisomerase I poison

Scaglioni, Leonardo; Mazzini, Stefania; Mondelli, R.; Dallavalle, Sabrina; Gattinoni, Sonia; Tinelli, Stella; Beretta, Giovanni Luca; Zunino, Franco; Ragg, Enzio

doi:10.1016/j.bmc.2008.12.005

Cited by 11 publications

(5 citation statements)

References 27 publications

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“…[35,52] A linear correlation of log(D) values versus log(M w ) was derived by using different standards. [53] The GL3 siRNA was also included as an additional standard. Linear least-squares fitting was achieved by using Equation (11), with a correlation coefficient R 2 of 0.9947. logðDÞ ¼ À0:4333 Â logðM w ÞÀ8:1987 ð11Þ…”

Section: Nmr Experimentsmentioning

confidence: 99%

PAMAM Dendrimers for siRNA Delivery: Computational and Experimental Insights

Pavan

Posocco

Tagliabue

et al. 2010

Chemistry A European J

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Short double-stranded RNAs, which are known as short interfering RNA (siRNA), can be used to specifically down-regulate the expression of the targeted gene in a process known as RNA interference (RNAi). However, the success of gene silencing applications based on the use of synthetic siRNA critically depends on efficient intracellular delivery. Polycationic branched macromolecules such as poly(amidoamine) (PAMAM) dendrimers show a strong binding affinity for RNA molecules and, hence, can provide an effective, reproducible, and relatively nontoxic method for transferring siRNAs into animal cells. Notwithstanding these perspectives, relatively few attempts have been made so far along these lines to study in detail the molecular mechanisms underlying the complexation process between PAMAMs and siRNAs. In this work we combine molecular simulation and experimental approaches to study the molecular requirements of the interaction of RNA-based therapeutics and PAMAM dendrimers of different generations. The dendrimers and their siRNA complexes were structurally characterized, and the free energy of binding between each dendrimer and a model siRNA was quantified by using the well-known MM/PBSA approach. DOSY NMR experiments confirmed the structural in silico prediction and yielded further information on both the complex structure and stoichiometry at low N/P ratio values. siRNA/PAMAM complex formation was monitored at different N/P ratios using gel retardation assays, and a simple model was proposed, which related the amount of siRNA complexed to the entropy variation upon complex formation obtained from the computer simulations.

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Section: Nmr Experimentsmentioning

confidence: 99%

PAMAM Dendrimers for siRNA Delivery: Computational and Experimental Insights

Pavan

Posocco

Tagliabue

et al. 2010

Chemistry A European J

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“…The power for classification of BCPs by anti-TOP-I activity was 0.87–0.93 for total accuracy and 0.22 for cross-validation error. Moreover, the final SVM model was applied to classify a set of 10 BCP analogues recently synthesized by Lavoie et al , which so-called application set or external test set 2 and detailed chemical structures and TOP-I activities are shown in Table 5 [ 22 , 23 , 24 , 25 , 26 ]. According to literature, among these 10 BCP analogues, seven compounds have stronger anti-TOP-I activity than topotecan and three compounds are weaker than topotecan.…”

Section: Resultsmentioning

confidence: 99%

A Support Vector Machine Classification Model for Benzo[c]phenathridine Analogues with Topoisomerase-I Inhibitory Activity

Thai

Nguyen²,

Ngo³

et al. 2012

Molecules

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Benzo[c]phenanthridine (BCP) derivatives were identified as topoisomerase I (TOP-I) targeting agents with pronounced antitumor activity. In this study, a support vector machine model was performed on a series of 73 analogues to classify BCP derivatives according to TOP-I inhibitory activity. The best SVM model with total accuracy of 93% for training set was achieved using a set of 7 descriptors identified from a large set via a random forest algorithm. Overall accuracy of up to 87% and a Matthews coefficient correlation (MCC) of 0.71 were obtained after this SVM classifier was validated internally by a test set of 15 compounds. For two external test sets, 89% and 80% BCP compounds, respectively, were correctly predicted. The results indicated that our SVM model could be used as the filter for designing new BCP compounds with higher TOP-I inhibitory activity.

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“…The linearly fused topopyrones B and D are especially potent, and indeed, the activity of 53 against topo-I appears to be comparable to that of camptothecin [90–91 100–101]. Accordingly, our research centered on the linear series of compounds.…”

Section: Reviewmentioning

confidence: 99%