Abstract

Inhibition of the MDM2-p53 interaction is considered to be a new therapeutic strategy to activate wild-type p53 in tumors. Recently, a series of potent and specific small-molecule spiro-oxindole inhibitors of the MDM2 were reported. In the current study, the interaction modes between 21 spiro-oxindole MDM2 inhibitors and the protein were studied by using the combination of molecular docking, molecular dynamics simulation and three-dimensional quantitative structure-activity relationships (3D-QSAR). The QSAR predictive models were established by using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) techniques. The predictive power of the 3D-QSAR models were determined from external test sets that were excluded during model development. The inhibitors in test sets were given exactly the same pretreatment as the inhibitors in the corresponding training sets. The correlation between the experimental and predicted activity for all models was calculated as a predictive r 2 value. With the CoMFA model, the cross-validated value (q 2 ) was 0.573, the non-cross-validated value (r 2 ) was 0.948. And with the CoMSIA model, the corresponding q 2 and r 2 were 0.651 and 0.98, respectively. The interaction mode obtained by molecular docking was in agreement with the results of molecular dynamics simulations, the interaction mode revealed that the hydrophobic interaction and H-bond played an im- portant role in the binding of spiro-oxindole derivatives and MDM2. Compounds designed by our group were synthesized and tested their in vitro cytotoxic activities against the MDM2 positive prostatic carcinoma LNCaP cell line. Two com- pounds, namely 5 and 6, with favorable scores from the CoMFA and CoMSIA models, showed potent cytotoxic activities with IC50 values lower than 1.0 μgmL -1 . The result was corresponding with that in experiment. And it was very significance to discover novel spiro-oxindole inhibitors which are mainly aimed at the MDM2-p53 interaction. It was expected that the information provided here was helpful for the study toward more accurate structure based on 3D-QSAR modeling and anti-tumor drug design and discovery. Keywords spiro-oxindole derivatives; molecular docking; molecular dynamics; comparative molecular field analysis; comparative molecular similarity indices analysis

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