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      AIDrugApp: artificial intelligence-based Web-App for virtual screening of inhibitors against SARS-COV-2

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          Matplotlib: A 2D Graphics Environment

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            Is Open Access

            Array programming with NumPy

            Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
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              SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

              To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.
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                Author and article information

                Contributors
                Journal
                Journal of Experimental & Theoretical Artificial Intelligence
                Journal of Experimental & Theoretical Artificial Intelligence
                Informa UK Limited
                0952-813X
                1362-3079
                April 03 2023
                April 20 2022
                April 03 2023
                : 35
                : 3
                : 395-443
                Affiliations
                [1 ]Chemical Engineering and Process Development (Cepd) Division, CSIR-National Chemical Laboratory, Pune India
                [2 ]Department of Research and Development, Algosurg Products Pvt. Ltd, Mumbai, India
                Article
                10.1080/0952813X.2022.2058619
                d21dc506-ace3-48ad-a3c6-7d2220ca26e9
                © 2023
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