Dataset Information

3D-QSAR Study of Combretastatin A-4 Analogs Based on Molecular Docking.

ABSTRACT: Combretastatin A-4 (CA-4), its analogues and their excellent antitumoral and antivascular activities, have attracted considerable interest of medicinal chemists. In this article, a docking simulation was used to identify molecules having the same binding mode as the lead compound, and 3D-QSAR models had been built by using CoMFA based on docking. As a result, these studies indicated that the QSAR models were statistically significant with high predictabilities (CoMFA model, q2 = 0.786, r2 = 0.988). Our models may offer help to better comprehend the structure-activity relationships for this class of compounds and also facilitate the design of novel inhibitors with good chemical diversity.

SUBMITTER: Jin Y

PROVIDER: S-EPMC6264539 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

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3D-QSAR Study of Combretastatin A-4 Analogs Based on Molecular Docking.

Jin Yinghua Y Qi Ping P Wang Zhiwei Z Shen Qirong Q Wang Jian J Zhang Weige W Song Hongrui H

Molecules (Basel, Switzerland) 20110808 8

Combretastatin A-4 (CA-4), its analogues and their excellent antitumoral and antivascular activities, have attracted considerable interest of medicinal chemists. In this article, a docking simulation was used to identify molecules having the same binding mode as the lead compound, and 3D-QSAR models had been built by using CoMFA based on docking. As a result, these studies indicated that the QSAR models were statistically significant with high predictabilities (CoMFA model, q2 = 0.786, r2 = 0.98 ...[more]

PMID: 25134772

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Project description:Cancer continues to be one of the world's most severe public health issues. Polo-like kinase 1 (PLK1) is one of the most studied members of the polo-like kinase subfamily of serine/threonine protein kinases. PLK1 is a key mitotic regulator responsible for cell cycle processes, such as mitosis initiation, bipolar mitotic spindle formation, centrosome maturation, the metaphase to anaphase transition, and mitotic exit, whose overexpression is often associated with oncogenesis. Moreover, it is also involved in DNA damage response, autophagy, cytokine signaling, and apoptosis. Due to its fundamental role in cell cycle regulation, PLK1 has been linked to various types of cancer onset and progression, such as lung, colon, prostate, ovary, breast cancer, melanoma, and AML. Hence, PLK1 is recognized as a critical therapeutic target in the treatment of various proliferative diseases. PLK1 inhibitors developed in recent years have been researched and studied through clinical trials; however, most of them have failed because of their toxicity and poor therapeutic response. To design more potent and selective PLK1 inhibitors, we performed a receptor-based hybrid 3D-QSAR study of two datasets, possessing similar common scaffolds. The developed hybrid CoMFA (q2 = 0.628, r2 = 0.905) and CoMSIA (q2 = 0.580, r2 = 0.895) models showed admissible statistical results. Comprehensive, molecular docking of one of the most active compounds from the dataset and hybrid 3D-QSAR studies revealed important active site residues of PLK1 and requisite structural characteristics of ligand to design potent PLK1 inhibitors. Based on this information, we have proposed approximately 38 PLK1 inhibitors. The newly designed PLK1 inhibitors showed higher activity (predicted pIC50) than the most active compounds of all the derivatives selected for this study. We selected and synthesized two compounds, which were ultimately found to possess good IC50 values. Our design strategy provides insight into development of potent and selective PLK1 inhibitors.

Project description:Background: The dipeptide-alkylated nitrogen-mustard compound is a new kind of nitrogen-mustard derivative with a strong anti-tumor activity, which can be used as a potential anti-osteosarcoma chemotherapy drug. Objective: 2D- and 3D-QSAR (structure–activity relationship quantification) models were established to predict the anti-tumor activity of dipeptide-alkylated nitrogen-mustard compounds. Method: In this study, a linear model was established using a heuristic method (HM) and a non-linear model was established using the gene expression programming (GEP) algorithm, but there were more limitations in the 2D model, so a 3D-QSAR model was introduced and established through the CoMSIA method. Finally, a series of new dipeptide-alkylated nitrogen-mustard compounds were redesigned using the 3D-QSAR model; docking experiments were carried out on several compounds with the highest activity against tumors. Result: The 2D- and 3D-QSAR models obtained in this experiment were satisfactory. A linear model with six descriptors was obtained in this experiment using the HM through CODESSA software, where the descriptor “Min electroph react index for a C atom” has the greatest effect on the compound activity; a reliable non-linear model was obtained using the GEP algorithm model (the best model was generated in the 89th generation cycle, with a correlation coefficient of 0.95 and 0.87 for the training and test set, respectively, and a mean error of 0.02 and 0.06, respectively). Finally, 200 new compounds were designed by combining the contour plots of the CoMSIA model with each other, together with the descriptors in the 2D-QSAR, among which compound I1.10 had a high anti-tumor and docking ability. Conclusion: Through the model established in this study, the factors influencing the anti-tumor activity of dipeptide-alkylated nitrogen-thaliana compounds were revealed, providing direction and guidance for the further design of efficient chemotherapy drugs against osteosarcoma.

Dataset Information

3D-QSAR Study of Combretastatin A-4 Analogs Based on Molecular Docking.

Publications

3D-QSAR Study of Combretastatin A-4 Analogs Based on Molecular Docking.

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