Fibroblast Growth Receptor Factor (FGFR) are a family of proteins which are, in addition to their biological role, are involved in various pathological functions, such as cancer cellular proliferation, and metastasis. Deregulation of FGFRs at various points could result in malignancy. A conformational transition of the DFG (Asp-Phe-Gly) motif can switch the enzyme from a catalytically active (DFG-in) to an inactive (DFG-out) state. There are a few FDFR inhibitors which have received approval from the FDA, but these have adverse side effects. Hence, there is a demand for safer alternatives. With this aim, Ligand and Structure based virtual screening was carried to identify suitable lead molecule. In this process, Four Featured atom-based 3D Pharmacophore with quantitative structure-activity relationship analysis (3D-QSAR) was developed. The External validation of the hypothesis was carried invoking criteria such as Area under the ROC curve. Natural plant compound databases such as the Traditional Chinese medicine, NPACT and the ZINC Natural databases were chosen for pharmacophore filtering, which was followed by virtual screening against FGFR isoforms. The compound Sanggenol B was identified as the most suitable lead molecule. Structural stability of the protein-ligand complex and interactions of the ligand (Sanggenol B & the reference compound Ponatinib) with FGFR were analysed for 1000 ns (triplicate) by means of molecular simulation and the binding free energy was calculated using MMGBSA. Sanggenol B (PubChem CID: 15233694) binds effectively at the active site with favourable energies and is proposed as a safe alternative from a natural source.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2023.2245047 | DOI Listing |
Sci Rep
December 2024
Department of Chemical and Biological Engineering, Gachon University, Seongnam, 13120, Republic of Korea.
The Crimean Congo virus has been reported to be a part of the spherical RNA-enveloped viruses from the Bunyaviridae family. Crimean Congo fever (CCHF) is a fatal disease with having fatality rate of up to 40%. It is declared endemic by the World Health Organization.
View Article and Find Full Text PDFNat Commun
December 2024
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial intelligence (AI) and virtual screening to facilitate the rational design of ionizable lipids by predicting two key properties of LNPs, apparent pKa and mRNA delivery efficiency.
View Article and Find Full Text PDFJ Biomol Struct Dyn
December 2024
Department of Biotechnology, School of Bioengineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamilnadu, India.
Antimicrobial Resistance poses a major threat to human health worldwide. Microorganisms develop multi-drug resistance due to intrinsic factors, evolutionary chromosomal alterations, and horizontal gene transfer. , a common nosocomial bacterium, can cause various infections and is classified as multidrug-resistant.
View Article and Find Full Text PDFAlcohol Clin Exp Res (Hoboken)
December 2024
Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA.
Background: Researchers have long been interested in identifying objective markers for problem drinking susceptibility informed by the environments in which individuals drink. However, little is known of objective cognitive-behavioral indices relevant to the social contexts in which alcohol is typically consumed. Combining group-based alcohol administration, eye-tracking technology, and longitudinal follow-up over a 2-year span, the current study examined the role of social attention in predicting patterns of problem drinking over time.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Beijing 100020, China.
Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discovery, repurposing clinically approved or investigational drugs for the treatment of tuberculosis by computational methods has become an attractive strategy. In this study, we developed a virtual screening workflow that combines multiple machine learning and deep learning models, and 11 576 compounds extracted from the DrugBank database were screened against Mtb.
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