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      Graph Theory Network, Molecular Docking, Quantum Chemicals and Pharmacokinetics-Based Investigation on Phytochemicals from Sida rhombifolia against Alzheimer’s Disease

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          The Protein Data Bank.

          The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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            Is Open Access

            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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              pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

              Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties.
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                Author and article information

                Contributors
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                Journal
                Polycyclic Aromatic Compounds
                Polycyclic Aromatic Compounds
                Informa UK Limited
                1040-6638
                1563-5333
                March 15 2024
                May 10 2023
                March 15 2024
                : 44
                : 3
                : 1947-1970
                Affiliations
                [1 ]Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu, India
                [2 ]Department of Biotechnology, Kamaraj College of Engineering and Technology, Madurai, Tamil Nadu, India
                [3 ]Department of Biotechnology, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, India
                [4 ]Condensed Matter Physics Laboratory, Department of Physics, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, India
                Article
                10.1080/10406638.2023.2209259
                1de854f1-97e3-4bfb-9237-7df8bf9b6cc5
                © 2024
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