De novo designing, assessment of target affinity and binding interactions against aromatase: Discovery of novel leads as
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ORIGINAL RESEARCH
De novo designing, assessment of target affinity and binding interactions against aromatase: Discovery of novel leads as anti-breast cancer agents Sant Kumar Verma 1 & Pooja Ratre 2 & Akhlesh Kumar Jain 2 & Chengyuan Liang 3 & Ghanshyam Das Gupta 1 & Suresh Thareja 4 Received: 10 September 2020 / Accepted: 29 October 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Aromatase inhibitors (AIs) have been emerged as promising anti-cancer agents for the treatment of hormone dependent breast cancer (HDBC) in women because of their excellent ability of inhibiting oestrogen synthesis. Here, we have implicated structurebased comprehensive approaches to discover novel drug/lead-like AIs. The molecular modelling and energy optimization were performed using Chem Office package. The e-LEA3D web server was used to design novel drug/lead-like AIs as well as generation of ADME/drug-likeness parameters. Target binding affinities and mode of binding interactions were mapped using Molegro Virtual Docker (MVD) to re-optimize the best de novo generated molecules. We have successfully designed novel AIs (compounds 1–7) using de novo technique performed on e-LEA3D. All the designed molecules were found optimum drug-like candidates based on various in silico screening parameters including ‘rule of five’. The energy optimized conformers of generated molecules (1–7) were docked in the active site, corresponding to co-crystallized androstenedione (ASD), of aromatase to predict ligand-target binding affinity and their binding interactions. The molecules (1–7) showed comparable to higher binding affinity towards aromatase with MolDock Score ranges from − 134.881 to − 152.453 Kcal/mol as compared with natural substrate ASD (− 128.639 Kcal/mol) and standard letrozole (− 136.784 Kcal/mol). The de novo designed molecules (1–7) can be developed as novel AIs, and their binding properties can be used for the further designing of newer AIs by medicinal chemists. Keywords Anti-cancer agents . Aromatase inhibitors . Breast cancer . De novo designing . e-LEA3D . Molecular docking
Introduction Breast cancer is the most common cancer amongst women, impacting 2.1 million feminine lives every year. It causes Sant Kumar Verma and Pooja Ratre contributed equally to this work. * Suresh Thareja [email protected] 1
ISF College of Pharmacy, Moga, Punjab 142 001, India
2
School of Pharmaceutical Sciences, Guru Ghasidas Central University, Bilaspur, C.G. 495 009, India
3
School of Food and Bioengineering, Shaanxi University of Science & Technology, Xi’an 710 021, People’s Republic of China
4
Department of Pharmaceutical Sciences and Natural Products, School of Basic and Applied Sciences, Central University of Punjab, Bathinda, Punjab 151 019, India
highest women’s mortality with 627,000 deaths in the year 2018, which was ~ 15% of all cancer deaths occurred in women. Breast cancer incidences are continuously increasing in nearly all the regions of globe with greater rate of occurrences in the develop
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