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Artificial Intelligence and Plant Extracts: A Better Approach to Combat Antimicrobial Resistance
Author(s):
1. Muhammad Shahid: Medicinal Biochemistry Research Lab., Department of Biochemistry, UAF, Pakistan
2. M. Tajammal Rehman: Medicinal Biochemistry Research Lab., Department of Biochemistry, UAF, Pakistan
3. Mahwish Salman: Department of Biochemistry, GCU, Faisalabad, Pakistan
4. Fozia Anjum: Department of Chemistry, GCU, Faisalabad, Pakistan
Abstract:
In future the new pandemic will be due to the pan drug resistance in microbes. In clinical practice, the global use of antibiotics not only led to the emergence of bacteria that are resistant to drugs but also threats regarding the development of super-resistant bacteria. The long-term synthesis of lead antimicrobial bioactives and the wide formation of drugresistant bacteria resulted in bacterial resistance development which has become a worldwide health crisis. Artificial intelligence (AI) computing knowledge of intelligent behavior and the field of infectious disease can effectively cope the antibiotic resistance by developing biologically active compound's rational designs that are effective in animal models, demonstrating that in silico can generate preclinical antibiotic candidates. Since plants are rich reservoir of fundamental nutrients and different biological active compounds. So, they are effective against diseases of humans and plants. Computational predictive models play a key role in technological and pharmaceutical advancement as they are used to select procedures through computerized predictions of pharmacokinetic, toxicological, and pharmacological production. Molecular docking is an affordable and effective methodology for making and investigating drugs. By using these multiple approaches, the interaction between receptor and drug can be determined and can be used to predict how a model drug will bind to the target protein resulting in reliable binding to the ligand's binding sites. Also the interaction of biopolymer with the drug moiety for control drug delivery.
Page(s): 92-92
DOI: DOI not available
Published: Journal: Abstract Book on International Conference on Life Sciences (ICLS-23) 11-12 May 22-23, Volume: 0, Issue: 0, Year: 2023
Keywords:
Artificial Intelligence and Plant Extracts , use of antibiotics
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