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  1. Article: Combining machine learning and structure-based approaches to develop oncogene PIM kinase inhibitors.

    Almukadi, Haifa / Jadkarim, Gada Ali / Mohammed, Arif / Almansouri, Majid / Sultana, Nasreen / Shaik, Noor Ahmad / Banaganapalli, Babajan

    Frontiers in chemistry

    2023  Volume 11, Page(s) 1137444

    Abstract: Introduction: ...

    Abstract Introduction:
    Language English
    Publishing date 2023-03-10
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2711776-5
    ISSN 2296-2646
    ISSN 2296-2646
    DOI 10.3389/fchem.2023.1137444
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Computational Molecular Phenotypic Analysis of PTPN22 (W620R), IL6R (D358A), and TYK2 (P1104A) Gene Mutations of Rheumatoid Arthritis.

    Shaik, Noor Ahmad / Banaganapalli, Babajan

    Frontiers in genetics

    2019  Volume 10, Page(s) 168

    Abstract: Rheumatoid arthritis (RA) is a chronic autoimmune disorder of bone joints caused by the complex interplay between several factors like body physiology, the environment with genetic background. The recent meta-analysis of GWAS has expanded the total ... ...

    Abstract Rheumatoid arthritis (RA) is a chronic autoimmune disorder of bone joints caused by the complex interplay between several factors like body physiology, the environment with genetic background. The recent meta-analysis of GWAS has expanded the total number of RA-associated loci to more than 100, out of which approximately ∼97% (98 variants) loci are located in non-coding regions, and the other ∼3% (3 variants) are in three different non-HLA genes, i.e., TYK2 (Prp1104Ala), IL6R (Asp358Ala), and PTPN22 (Trp620Arg). However, whether these variants prompt changes in the protein phenotype with regards to its stability, structure, and interaction with other molecules, remains unknown. Thus, we selected the three clinically pathogenic variants described above, as positive controls and applied diverse computational methods to scrutinize if those mutations cause changes in the protein phenotype. Both wild type and mutant protein structures of PTPN22 (W620R), IL6R (D358A), and TYK2 (P1104A) were modeled and studied for structural deviations. Furthermore, we have also studied the secondary structure characteristics, solvent accessibility and stability, and the molecular interaction deformities caused by the amino acid substitutions. We observed that simple nucleotide predictions of SIFT, PolyPhen, CADD and FATHMM yields mixed findings in screening the RA-missense variants which showed a ≥
    Language English
    Publishing date 2019-03-07
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2019.00168
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Granulomatous hepatitis in a Saudi child with

    Alaifan, Meshari A / Abusharifah, Ohood / Bokhary, Rana Yagoub / Banaganapalli, Babajan / Shaik, Noor Ahmad / Kamal, Naglaa M / Saadah, Omar I

    Therapeutic advances in chronic disease

    2022  Volume 13, Page(s) 20406223221116798

    Abstract: Interleukin-2 receptor alpha ( ...

    Abstract Interleukin-2 receptor alpha (
    Language English
    Publishing date 2022-08-09
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2554816-5
    ISSN 2040-6231 ; 2040-6223
    ISSN (online) 2040-6231
    ISSN 2040-6223
    DOI 10.1177/20406223221116798
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Paget's disease: a review of the epidemiology, etiology, genetics, and treatment.

    Banaganapalli, Babajan / Fallatah, Ibrahim / Alsubhi, Fai / Shetty, Preetha Jayasheela / Awan, Zuhier / Elango, Ramu / Shaik, Noor Ahmad

    Frontiers in genetics

    2023  Volume 14, Page(s) 1131182

    Abstract: Paget's disease of bone (PDB) is the second most prevalent metabolic bone disorder worldwide, with a prevalence rate of 1.5%-8.3%. It is characterized by localized areas of accelerated, disorganized, and excessive bone production and turnover. Typically, ...

    Abstract Paget's disease of bone (PDB) is the second most prevalent metabolic bone disorder worldwide, with a prevalence rate of 1.5%-8.3%. It is characterized by localized areas of accelerated, disorganized, and excessive bone production and turnover. Typically, PDB develops in the later stages of life, particularly in the late 50s, and affects men more frequently than women. PDB is a complex disease influenced by both genetic and environmental factors. PDB has a complex genetic basis involving multiple genes, with SQSTM1 being the gene most frequently associated with its development. Mutations affecting the UBA domain of SQSTM1 have been detected in both familial and sporadic PDB cases, and these mutations are often associated with severe clinical expression. Germline mutations in other genes such as TNFRSF11A, ZNF687 and PFN1, have also been associated with the development of the disease. Genetic association studies have also uncovered several PDB predisposing risk genes contributing to the disease pathology and severity. Epigenetic modifications of genes involved in bone remodelling and regulation, including RANKL, OPG, HDAC2, DNMT1, and SQSTM1, have been implicated in the development and progression of Paget's disease of bone, providing insight into the molecular basis of the disease and potential targets for therapeutic intervention. Although PDB has a tendency to cluster within families, the variable severity of the disease across family members, coupled with decreasing incidence rates, indicates that environmental factors may also play a role in the pathophysiology of PDB. The precise nature of these environmental triggers and how they interact with genetic determinants remain poorly understood. Fortunately, majority of PDB patients can achieve long-term remission with an intravenous infusion of aminobisphosphonates, such as zoledronic acid. In this review, we discuss aspects like clinical characteristics, genetic foundation, and latest updates in PDB research.
    Language English
    Publishing date 2023-04-26
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2023.1131182
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Combining machine learning and structure-based approaches to develop oncogene PIM kinase inhibitors

    Haifa Almukadi / Gada Ali Jadkarim / Arif Mohammed / Majid Almansouri / Nasreen Sultana / Noor Ahmad Shaik / Babajan Banaganapalli

    Frontiers in Chemistry, Vol

    2023  Volume 11

    Abstract: Introduction: PIM kinases are targets for therapeutic intervention since they are associated with a number of malignancies by boosting cell survival and proliferation. Over the past years, the rate of new PIM inhibitors discovery has increased ... ...

    Abstract Introduction: PIM kinases are targets for therapeutic intervention since they are associated with a number of malignancies by boosting cell survival and proliferation. Over the past years, the rate of new PIM inhibitors discovery has increased significantly, however, new generation of potent molecules with the right pharmacologic profiles were in demand that can probably lead to the development of Pim kinase inhibitors that are effective against human cancer.Method: In the current study, a machine learning and structure based approaches were used to generate novel and effective chemical therapeutics for PIM-1 kinase. Four different machine learning methods, namely, support vector machine, random forest, k-nearest neighbour and XGBoost have been used for the development of models. Total, 54 Descriptors have been selected using the Boruta method.Results: SVM, Random Forest and XGBoost shows better performance as compared to k-NN. An ensemble approach was implemented and, finally, four potential molecules (CHEMBL303779, CHEMBL690270, MHC07198, and CHEMBL748285) were found to be effective for the modulation of PIM-1 activity. Molecular docking and molecular dynamic simulation corroborated the potentiality of the selected molecules. The molecular dynamics (MD) simulation study indicated the stability between protein and ligands.Discussion: Our findings suggest that the selected models are robust and can be potentially useful for facilitating the discovery against PIM kinase.
    Keywords PIM kinase ; classification models ; virtual screening ; molecular docking ; cancer drug treatment ; Chemistry ; QD1-999
    Subject code 006
    Language English
    Publishing date 2023-03-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article: Protein structural insights into a rare PCSK9 gain-of-function variant (R496W) causing familial hypercholesterolemia in a Saudi family: whole exome sequencing and computational analysis.

    Shaik, Noor Ahmad / Al-Shehri, Najla / Athar, Mohammad / Awan, Ahmed / Khalili, Mariam / Al Mahadi, Hadiah Bassam / Hejazy, Gehan / Saadah, Omar I / Al-Harthi, Sameer Eida / Elango, Ramu / Banaganapalli, Babajan / Alefishat, Eman / Awan, Zuhier

    Frontiers in physiology

    2023  Volume 14, Page(s) 1204018

    Abstract: Familial hypercholesterolemia (FH) is a globally underdiagnosed genetic condition associated with premature cardiovascular death. The genetic etiology data on Arab FH patients is scarce. Therefore, this study aimed to identify the genetic basis of FH in ... ...

    Abstract Familial hypercholesterolemia (FH) is a globally underdiagnosed genetic condition associated with premature cardiovascular death. The genetic etiology data on Arab FH patients is scarce. Therefore, this study aimed to identify the genetic basis of FH in a Saudi family using whole exome sequencing (WES) and multidimensional bioinformatic analysis. Our WES findings revealed a rare heterozygous gain-of-function variant (R496W) in the exon 9 of the
    Language English
    Publishing date 2023-07-04
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2564217-0
    ISSN 1664-042X
    ISSN 1664-042X
    DOI 10.3389/fphys.2023.1204018
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Genome-Wide Association Study-Guided Exome Rare Variant Burden Analysis Identifies IL1R1 and CD3E as Potential Autoimmunity Risk Genes for Celiac Disease.

    Mansour, Haifa / Banaganapalli, Babajan / Nasser, Khalidah Khalid / Al-Aama, Jumana Yousuf / Shaik, Noor Ahmad / Saadah, Omar Ibrahim / Elango, Ramu

    Frontiers in pediatrics

    2022  Volume 10, Page(s) 837957

    Abstract: Celiac disease (CeD) is a multifactorial autoimmune enteropathy characterized by the overactivation of the immune system in response to dietary gluten. The molecular etiology of CeD is still not well-understood. Therefore, this study aims to identify ... ...

    Abstract Celiac disease (CeD) is a multifactorial autoimmune enteropathy characterized by the overactivation of the immune system in response to dietary gluten. The molecular etiology of CeD is still not well-understood. Therefore, this study aims to identify potential candidate genes involved in CeD pathogenesis by applying multilayered system biology approaches. Initially, we identified rare coding variants shared between the affected siblings in two rare Arab CeD families by whole-exome sequencing (WES). Then we used the STRING database to construct a protein network of rare variants and genome-wide association study (GWAS) loci to explore their molecular interactions in CeD. Furthermore, the hub genes identified based on network topology parameters were subjected to a series of computational validation analyses like pathway enrichment, gene expression, knockout mouse model, and variant pathogenicity predictions. Our findings have shown the absence of rare variants showing classical Mendelian inheritance in both families. However, interactome analysis of rare WES variants and GWAS loci has identified a total of 11 hub genes. The multidimensional computational analysis of hub genes has prioritized IL1R1 for family A and CD3E for family B as potential genes. These genes were connected to CeD pathogenesis pathways of T-cell selection, cytokine signaling, and adaptive immune response. Future multi-omics studies may uncover the roles of IL1R1 and CD3E in gluten sensitivity. The present investigation lays forth a novel approach integrating next-generation sequencing (NGS) of familial cases, GWAS, and computational analysis for solving the complex genetic architecture of CeD.
    Language English
    Publishing date 2022-02-14
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2711999-3
    ISSN 2296-2360
    ISSN 2296-2360
    DOI 10.3389/fped.2022.837957
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Identification of miRNA-mRNA-TFs regulatory network and crucial pathways involved in asthma through advanced systems biology approaches.

    Shaik, Noor Ahmad / Nasser, Khalidah / Mohammed, Arif / Mujalli, Abdulrahman / Obaid, Ahmad A / El-Harouni, Ashraf A / Elango, Ramu / Banaganapalli, Babajan

    PloS one

    2022  Volume 17, Issue 10, Page(s) e0271262

    Abstract: Asthma is a life-threatening and chronic inflammatory lung disease that is posing a true global health challenge. The genetic basis of the disease is fairly well examined. However, the molecular crosstalk between microRNAs (miRNAs), target genes, and ... ...

    Abstract Asthma is a life-threatening and chronic inflammatory lung disease that is posing a true global health challenge. The genetic basis of the disease is fairly well examined. However, the molecular crosstalk between microRNAs (miRNAs), target genes, and transcription factors (TFs) networks and their contribution to disease pathogenesis and progression is not well explored. Therefore, this study was aimed at dissecting the molecular network between mRNAs, miRNAs, and TFs using robust computational biology approaches. The transcriptomic data of bronchial epithelial cells of severe asthma patients and healthy controls was studied by different systems biology approaches like differentially expressed gene detection, functional enrichment, miRNA-target gene pairing, and mRNA-miRNA-TF molecular networking. We detected the differential expression of 1703 (673 up-and 1030 down-regulated) genes and 71 (41 up-and 30 down-regulated) miRNAs in the bronchial epithelial cells of asthma patients. The DEGs were found to be enriched in key pathways like IL-17 signaling (KEGG: 04657), Th1 and Th2 cell differentiation (KEGG: 04658), and the Th17 cell differentiation (KEGG: 04659) (p-values = 0.001). The results from miRNAs-target gene pairs-transcription factors (TFs) have detected the key roles of 3 miRs (miR-181a-2-3p; miR-203a-3p; miR-335-5p), 6 TFs (TFAM, FOXO1, GFI1, IRF2, SOX9, and HLF) and 32 miRNA target genes in eliciting autoimmune reactions in bronchial epithelial cells of the respiratory tract. Through systemic implementation of comprehensive system biology tools, this study has identified key miRNAs, TFs, and miRNA target gene pairs as potential tissue-based asthma biomarkers.
    MeSH term(s) Humans ; MicroRNAs/genetics ; MicroRNAs/metabolism ; RNA, Messenger/genetics ; Systems Biology ; Gene Regulatory Networks ; Interleukin-17/metabolism ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Computational Biology/methods ; Transcription Factors/genetics ; Transcription Factors/metabolism ; Asthma/genetics ; Biomarkers
    Chemical Substances MicroRNAs ; RNA, Messenger ; Interleukin-17 ; Transcription Factors ; Biomarkers
    Language English
    Publishing date 2022-10-20
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0271262
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Integrative weighted molecular network construction from transcriptomics and genome wide association data to identify shared genetic biomarkers for COPD and lung cancer.

    Banaganapalli, Babajan / Mallah, Bayan / Alghamdi, Kawthar Saad / Albaqami, Walaa F / Alshaer, Dalal Sameer / Alrayes, Nuha / Elango, Ramu / Shaik, Noor A

    PloS one

    2022  Volume 17, Issue 10, Page(s) e0274629

    Abstract: Chronic obstructive pulmonary disease (COPD) is a multifactorial progressive airflow obstruction in the lungs, accounting for high morbidity and mortality across the world. This study aims to identify potential COPD blood-based biomarkers by analyzing ... ...

    Abstract Chronic obstructive pulmonary disease (COPD) is a multifactorial progressive airflow obstruction in the lungs, accounting for high morbidity and mortality across the world. This study aims to identify potential COPD blood-based biomarkers by analyzing the dysregulated gene expression patterns in blood and lung tissues with the help of robust computational approaches. The microarray gene expression datasets from blood (136 COPD and 6 controls) and lung tissues (16 COPD and 19 controls) were analyzed to detect shared differentially expressed genes (DEGs). Then these DEGs were used to construct COPD protein network-clusters and functionally enrich them against gene ontology annotation terms. The hub genes in the COPD network clusters were then queried in GWAS catalog and in several cancer expression databases to explore their pathogenic roles in lung cancers. The comparison of blood and lung tissue datasets revealed 63 shared DEGs. Of these DEGs, 12 COPD hub gene-network clusters (SREK1, TMEM67, IRAK2, MECOM, ASB4, C1QTNF2, CDC42BPA, DPF3, DET1, CCDC74B, KHK, and DDX3Y) connected to dysregulations of protein degradation, inflammatory cytokine production, airway remodeling, and immune cell activity were prioritized with the help of protein interactome and functional enrichment analysis. Interestingly, IRAK2 and MECOM hub genes from these COPD network clusters are known for their involvement in different pulmonary diseases. Additional COPD hub genes like SREK1, TMEM67, CDC42BPA, DPF3, and ASB4 were identified as prognostic markers in lung cancer, which is reported in 1% of COPD patients. This study identified 12 gene network- clusters as potential blood based genetic biomarkers for COPD diagnosis and prognosis.
    MeSH term(s) Biomarkers ; Computational Biology ; Cytokines/metabolism ; DEAD-box RNA Helicases/genetics ; Gene Expression Profiling ; Gene Regulatory Networks ; Genetic Markers ; Genome-Wide Association Study ; Humans ; Lung Neoplasms/diagnosis ; Lung Neoplasms/genetics ; Minor Histocompatibility Antigens ; Pulmonary Disease, Chronic Obstructive/diagnosis ; Pulmonary Disease, Chronic Obstructive/genetics ; Pulmonary Disease, Chronic Obstructive/metabolism ; Serine-Arginine Splicing Factors/genetics ; Transcriptome
    Chemical Substances Biomarkers ; Cytokines ; Genetic Markers ; Minor Histocompatibility Antigens ; SREK1 protein, human ; Serine-Arginine Splicing Factors (170974-22-8) ; DDX3Y protein, human (EC 3.6.1.-) ; DEAD-box RNA Helicases (EC 3.6.4.13)
    Language English
    Publishing date 2022-10-04
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0274629
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Structural characterization and conformational dynamics of alpha-1 antitrypsin pathogenic variants causing alpha-1-antitrypsin deficiency.

    Shaik, Noor Ahmad / Saud Al-Saud, Najla Bint / Abdulhamid Aljuhani, Thamer / Jamil, Kaiser / Alnuman, Huda / Aljeaid, Deema / Sultana, Nasreen / El-Harouni, Ashraf AbdulRahman / Awan, Zuhier Ahmed / Elango, Ramu / Banaganapalli, Babajan

    Frontiers in molecular biosciences

    2022  Volume 9, Page(s) 1051511

    Abstract: Background: ...

    Abstract Background:
    Language English
    Publishing date 2022-11-24
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2814330-9
    ISSN 2296-889X
    ISSN 2296-889X
    DOI 10.3389/fmolb.2022.1051511
    Database MEDical Literature Analysis and Retrieval System OnLINE

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