scholarly journals Structure-Based Virtual Screening, Molecular Docking, MolecularDynamics Simulation of VEGF Inhibitors for the Clinical Treatment of Ovarian Cancer

2021 ◽  
Author(s):  
Sourav Mukherjee ◽  
Mohnad Abdalla ◽  
Manasi Yadav ◽  
Maddala Madhavi ◽  
Ravina Khandelwal ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Virtual Screening ◽  
Cancer Progression ◽  
Docking Study ◽  
Dynamics Simulation ◽  
Vegf Inhibitors ◽  
High Affinity ◽  
Vegf Inhibitor ◽  
Rank Score ◽  
Immunosuppressive Microenvironment

Abstract VEGF and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential VEGF inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumour cells of ovary and to examine for an effectiveness of identified inhibitor for treatment of ovarian cancer using various In silico approaches. 12 established VEGF inhibitors were collected from various literature. The compound AEE788 displays the great affinity towards the target protein as a result of docking study. AEE78 was further used for structure base virtual screening in order to obtain more structurally similar compound with high affinity. Among the 80 Virtual screened compounds, CID 88265020, explicates much better affinity than established compound AEE788. Based on Molecular Dynamics Simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 have the high affinity with the lowest re-rank score, and holds a huge potential to inhibit the VGFR and can be implemented for prospective of future investigations in Ovarian Cancer.

scholarly journals The Complement System in Ovarian Cancer: An Underexplored Old Path

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3806
Author(s):  
Yaiza Senent ◽  
Daniel Ajona ◽  
Antonio González-Martín ◽  
Ruben Pio ◽  
Beatriz Tavira
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
Complement System ◽  
Response To Treatment ◽  
Ovarian Cancer Cells ◽  
Detailed Knowledge ◽  
System A ◽  
Immunosuppressive Microenvironment ◽  
Temporary Control ◽  
The Complement System

Ovarian cancer is one of the most lethal gynecological cancers. Current therapeutic strategies allow temporary control of the disease, but most patients develop resistance to treatment. Moreover, although successful in a range of solid tumors, immunotherapy has yielded only modest results in ovarian cancer. Emerging evidence underscores the relevance of the components of innate and adaptive immunity in ovarian cancer progression and response to treatment. Particularly, over the last decade, the complement system, a pillar of innate immunity, has emerged as a major regulator of the tumor microenvironment in cancer immunity. Tumor-associated complement activation may support chronic inflammation, promote an immunosuppressive microenvironment, induce angiogenesis, and activate cancer-related signaling pathways. Recent insights suggest an important role of complement effectors, such as C1q or anaphylatoxins C3a and C5a, and their receptors C3aR and C5aR1 in ovarian cancer progression. Nevertheless, the implication of these factors in different clinical contexts is still poorly understood. Detailed knowledge of the interplay between ovarian cancer cells and complement is required to develop new immunotherapy combinations and biomarkers. In this context, we discuss the possibility of targeting complement to overcome some of the hurdles encountered in the treatment of ovarian cancer.

scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Simulation Analysis ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Multilinear Regression ◽  
Qsar Analysis ◽  
Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

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