Sajjad Karim
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Recent Grants
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Application of artificial intelligence for comprehensive genomic diagnosis of complex genetic diseases using microarray and next generation sequencing platforms
Open Date: 2020-12-01
Close Date: 2024-12-01
Grant: Close
Applications of artificial intelligence in translating cancer genomics into precision medicine
Open Date: 2020-12-01
Close Date: 2022-12-01
Grant: Close
Discovery and Validation of Molecular Biomarker and Therapeutic Targets through Integrated Technology Approach to Guide Clinical Decision Making and Improve Cancer Treatment.
Open Date: 2019-11-01
Close Date: 2023-11-01
Grant: Close
Gene Mapping and Molecular Analysis of Congenital Heart Disease in Saudi Population and Functional Analysis of Identified Genes and Mutations in Cell Models and Zebra Fish
Open Date: 2019-11-01
Close Date: 2023-11-01
Grant: Close
Study of novel gene and mutations from primary Microcephaly in Saudi Arabia using advanced high-density array technology to detect genome-wide copy number variations and single nucleotide polymorphisms
Open Date: 2015-10-01
Close Date: 2019-10-01
Articles (11)
Acute myeloid leukemia (AML) is hallmarked by the clonal proliferation of myeloid blasts. Mutations that result in the constitutive activation of the fms-like tyrosine kinase 3 (FLT3) gene, coding for a class III receptor tyrosine kinase, are significantly associated with this heterogeneous hematologic malignancy. The fms-related tyrosine kinase 3 ligand binds to the extracellular domain of the FLT3 receptor, inducing homodimer formation in the plasma membrane, leading to autophosphorylation and activation of apoptosis, proliferation, and differentiation of hematopoietic cells in bone marrow. In the present study, we evaluated the association of FLT3 as a significant biomarker for AML and tried to comprehend the effects of specific variations on the FLT3 protein’s structure and function. We also examined the effects of I836 variants on binding affinity to sorafenib using molecular docking. We integrated multiple bioinformatics tools, databases, and resources such as OncoDB, UniProt, COSMIC, UALCAN, PyMOL, ProSA, Missense3D, InterProScan, SIFT, PolyPhen, and PredictSNP to annotate the structural, functional, and phenotypic impact of the known variations associated with FLT3. Twenty-nine FLT3 variants were analyzed using in silico approaches such as DynaMut, CUPSAT, AutoDock, and Discovery Studio for their impact on protein stability, flexibility, function, and binding affinity. The OncoDB and UALCAN portals confirmed the association of FLT3 gene expression and its mutational status with AML. A computational structural analysis of the deleterious variants of FLT3 revealed I863F mutants as destabilizers of the protein structure, possibly leading to functional changes. Many single-nucleotide variations in FLT3 have an impact on its structure and function. Thus, the annotation of FLT3 SNVs and the prediction of their deleterious pathogenic impact will facilitate an insight into the tumorigenesis process and guide experimental studies and clinical implications.
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2024
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2023
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2023
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2023
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2023
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2022
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2022
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2022
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2022
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2022
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2021
Collaborators (2)
Sayaka Miura
Temple University
Haneen Banjar
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