Presently world is on a war with the novel coronavirus and with no immediate treatments available the scourge caused by the SARS-CoV-2 is increasing day by day. A lot of researches are going on for the potential drug candidate that could help the healthcare system in this fight. Plants are a natural data bank of bioactive compounds. Many phytochemicals are being studied for various ailments including cancer, bacterial and viral infections, etc. The present study aims to screen 38 bioactive compounds from 5 selected plants viz., Azadirachta indica , Curcuma longa , Zingiber officinale , Ocimum basilicum and Panax ginseng against SARS-CoV-2. Lipinski’s rule was taken as the foundation for initial screening. Shortlisted compounds were subjected to molecular docking study with M pro receptor present in SARS-CoV-2. The study identified that gedunin, epoxyazadiradione, nimbin and ginsenosides have potential to inhibit M pro activity and their binding energies are − 9.51 kcal/mol, − 8.47 kcal/mol, − 8.66 kcal/mol and − 9.63 kcal/mol respectively. Based on bioavailability radar studies gedunin and epoxyazadiradione are the two most potent compounds which are used for molecular dynamics simulation studies. Molecular dynamics studies showed that gedunin is more potent than epoxyazadiradione. To find the effectiveness and to propose the exact mechanism, in-vitro studies can be further performed on gedunin.

Software libraries and frameworks, consisting of a collection of Class and Interface definitions, provide a mechanism for code reuse by providing methods, APIs, components (generic functionality) and a support structure for developers to build applications, products and solutions. KitKat, Jelly Bean, Ice Cream Sandwich, Honeycomb and Gingerbread are different versions (open-source) of Android, one of the most popular mobile platforms in the world. In this paper, we present the results of our large-scale (consisting of 1, 120 open-source applications and 17.4 million lines of code) API usage analysis of Android applications. Our work is motivated by the need to mine actual Android API usage, frequent API call usage patterns and trends to understand and generate empirical data on how developers are using the mobile platform in their applications.Extracting popular and frequently-invoked methods, API packages and API call-usage patterns is useful to both the API Producers and API Consumers. For example, API Producers can view the quantitative data on API usage as a feedback from users on the relevance, usability and applicability of the respective APIs. We conduct a series of experiments on analysing the Android platform API usage (usage of different packages, usage of methods, usage across categories) and present the results of our analysis using graphs such as Bubble Chart, Radar Chart, Heat-Map for effective visualization of the results and for extraction of actionable information.

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