QSAR and Docking Studies on Some Potential Anti-Cancer Agents to Predict their Effect on M14 Melanoma Cell Line
- PDF / 1,809,596 Bytes
- 14 Pages / 595.276 x 790.866 pts Page_size
- 23 Downloads / 166 Views
ORIGINAL ARTICLE
QSAR and Docking Studies on Some Potential Anti‑Cancer Agents to Predict their Effect on M14 Melanoma Cell Line Abdullahi Bello Umar1 · Adamu Uzairu1 · Sani Uba1 · Gideon Adamu Shallangwa1 Received: 14 May 2020 / Accepted: 7 September 2020 © The Tunisian Chemical Society and Springer Nature Switzerland AG 2020
Abstract The global incidence of melanoma cancer is increasing rapidly and its metastatic form causes high mortality rates. The research report illustrates the development of a quantitative structure–activity relationship (QSAR) to predict the activities (pGI50) of some anti-cancer agents on melanoma cancer cell line. Subsequently, most potent compounds that showed better pGI50 activities were selected and screened via Lipinski’s rule of five for drug likeness, ADMET risk parameters and lastly docking simulation studies was performed to elucidate their binding mode. Kennard-Stone algorithm was adopted for the data division, the genetic function algorithm was employed for variable selection and multiple linear regressions method was utilized for model development. The derived QSAR model showed, respectively acceptable [(R2 (0.805), R2adjusted (0.773), Q2cv (0.754) and R2pred (0.703)]. The obtained cR2P for Y-randomization is 0.649, and applicability-domain (A-D) was assessed via leveraged method. Among the screened compounds via Lipinski’s rule of five for oral bioavailability, ADMET risk filter for drug-like features and Docking simulation studies, compound 18 and 25 were identified as the best ligands having the better interactions energies (− 150.679 kcal mol−1 and − 176.246 kcal mol−1) and showed better interactions with the receptor than vemurafenib (− 147.245 kcal mol−1). Thus, the results of this research would be helpful in identification of lead molecule and optimization of novel drug. Keywords Melanoma · DFT · QSAR · GFA · Docking · V600E-BRAF Abbreviations DFT Density Functional Theory MVD Molegro Virtual Docker QSAR Quantitative structure–activity relationship ADMET Absorption, distribution, metabolism, excretion, and toxicity
* Abdullahi Bello Umar [email protected] Adamu Uzairu [email protected] Sani Uba [email protected] Gideon Adamu Shallangwa [email protected] 1
Department of Chemistry, Faculty of Physical Sciences, Ahmad Bello University, P.M.B 1045, Zaria, Kaduna, Nigeria
1 Background Melanoma is the most severe form of skin cancer resulted from the melanocytes disordered proliferation in the epidermis and it has a high metastatic rate [1]. It has a poor diagnosis for patients with the advanced stage of the disease and appears to be resistant to popular therapeutic strategies [2, 3]. The first alternative approach was the operational elimination of the neoplasm and chemotherapeutic treatment was also adopted. In the occurrence of metastasis, the possibilities of cure are almost zero, and the known treatments are merely palliative care [4]. The most popular chemotherapeutic drugs used for the therapy of melanoma are temozolomide, dacarbazine, ni
Data Loading...
