AI-Based Homology Modelling of Fatty Acid Transport Protein 1 Using AlphaFold: Structural Elucidation and Molecular Dynamics Exploration.

Fatty acid transport protein 1 (FATP1) is an integral transmembrane protein that is involved in facilitating the translocation of long-chain fatty acids (LCFA) across the plasma membrane, thereby orchestrating the importation of LCFA into the cell. FATP1 also functions as an acyl-CoA ligase, catalyzing the ATP-dependent formation of fatty acyl-CoA using LCFA and VLCFA (very-long-chain fatty acids) as substrates. It is expressed in various types of tissues and is involved in the regulation of crucial signalling pathways, thus playing a vital role in numerous physiological and pathological conditions. Structural insight about FATP1 is, thus, extremely important for understanding the mechanism of action of this protein and developing efficient treatments against its anomalous expression and dysregulation, which are often associated with pathological conditions such as breast cancer. As of now, there has been no prior prediction or evaluation of the 3D configuration of the human FATP1 protein, hindering a comprehensive understanding of the distinct functional roles of its individual domains. In our pursuit to unravel the structure of the most commonly expressed isoforms of FATP1, we employed the cutting-edge ALPHAFOLD 2 model for an initial prediction of the entire protein's structure. This prediction was complemented by molecular dynamics simulations, focusing on the most promising model. We predicted the structure of FATP1 in silico and thoroughly refined and validated it using coarse and molecular dynamics in the absence of the complete crystal structure. Their relative dynamics revealed the different properties of the characteristic FATP1.

Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach

Purpose@#The integration of large-scale gene data and their functional analysis needs the effective application of various computational tools. Here we attempted to unravel the biological processes and cellular pathways in response to ionizing radiation using a systems biology approach. @*Materials and Methods@#Analysis of gene ontology shows that 80, 42, 25, and 35 genes have roles in the biological process, molecular function, the cellular process, and immune system pathways, respectively. Therefore, our study emphasizes gene/protein network analysis on various differentially expressed genes (DEGs) to reveal the interactions between those proteins and their functional contribution upon radiation exposure. @*Results@#A gene/protein interaction network was constructed, which comprises 79 interactors with 718 interactions and TP53, MAPK8, MAPK1, CASP3, MAPK14, ATM, NOTCH1, VEGFA, SIRT1, and PRKDC are the top 10 proteins in the network with high betweenness centrality values. Further, molecular complex detection was used to cluster these associated partners in the network, which produced three effective clusters based on the Molecular Complex Detection (MCODE) score. Interestingly, we found a high functional similarity from the associated genes/proteins in the network with known radiation response genes. @*Conclusion@#This network-based approach on DEGs of human lymphocytes upon response to ionizing radiation provides clues for an opportunity to improve therapeutic efficacy.

Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach

Purpose@#The integration of large-scale gene data and their functional analysis needs the effective application of various computational tools. Here we attempted to unravel the biological processes and cellular pathways in response to ionizing radiation using a systems biology approach. @*Materials and Methods@#Analysis of gene ontology shows that 80, 42, 25, and 35 genes have roles in the biological process, molecular function, the cellular process, and immune system pathways, respectively. Therefore, our study emphasizes gene/protein network analysis on various differentially expressed genes (DEGs) to reveal the interactions between those proteins and their functional contribution upon radiation exposure. @*Results@#A gene/protein interaction network was constructed, which comprises 79 interactors with 718 interactions and TP53, MAPK8, MAPK1, CASP3, MAPK14, ATM, NOTCH1, VEGFA, SIRT1, and PRKDC are the top 10 proteins in the network with high betweenness centrality values. Further, molecular complex detection was used to cluster these associated partners in the network, which produced three effective clusters based on the Molecular Complex Detection (MCODE) score. Interestingly, we found a high functional similarity from the associated genes/proteins in the network with known radiation response genes. @*Conclusion@#This network-based approach on DEGs of human lymphocytes upon response to ionizing radiation provides clues for an opportunity to improve therapeutic efficacy.

Exploring the Potential of Capsaicin Against Cancer Metastasis Based on TGF-ß Signaling Modulation Through Module-based Network Pharmacology Approachx.

BACKGROUND: Capsaicin is an active alkaloid /principal component of red pepper responsible for the pungency of chili pepper. Capsaicin by changing the intracellular redox homeostasis regulate a variety of signaling pathways ultimately producing a divergent cellular outcome. Several reports showed the potential of capsaicin against cancer metastasis, however unexplored molecular mechanism is still an active part of the research. Several growth factors have a critical role during cancer metastasis among them TGF- ß signaling play a vital role. METHODS: The present study aimed at analyzing capsaicin modulation of TGF-ß signaling using network pharmacology approach. The chemical and protein interaction data of capsaicin was curated and abstracted using STITCH4.0, PubChem and ChEMBL database. Further, the compiled data set was subjected to the pathway and functional enrichment analysis using Protein Analysis THrough Evolutionary Relationship (PANTHER) and, Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Meanwhile, the pattern of amino acid composition across the capsaicin targets was analyzed using the EMBOSS Pepstat tool. Capsaicin targets involved in TGF- ß were identified and their Protein-Protein Interaction (PPI) network constructed using STRING v10 and Cytoscape (v 3.2.1). From the above-constructed network, the clusters were mined using the MCODE clustering algorithm and finally binding affinity of capsaicin with its targets involved in TGF-ß signaling pathway was analyzed using Autodock Vina. RESULTS: The analysis explored capsaicin targets and, their associated functional and pathway annotations. Besides, the analysis also provides a detailed distinct pattern of amino acid composition across the capsaicin targets. The capsaicin targets described as MAPK14, JUN, SMAD3, MAPK3, MAPK1 and MYC involved in TGF-ß signaling pathway through pathway enrichment analysis. The binding mode analysis of capsaicin with its targets has shown high affinity with MAPK3, MAPK1, JUN and MYC. CONCLUSION: The study explores the potential of capsaicin as a potent modulator of TGF-ß signaling pathway during cancer metastasis and proposes new methodology and mechanism of action of capsaicin against TGF- ß signaling pathway.

Aqueous extract from Madhuca indica bark protects cells from oxidative stress caused by electron beam radiation: in vitro, in vivo and in silico approach.

In an endeavor to find the novel natural radioprotector to secure normal cells surrounding cancerous cell during radiation exposure, Madhuca indica (M. indica) aqueous stem bark extract was evaluated for radioprotective activity using in vitro, in vivo, and in silico models. M. indica extract exhibited concentration dependent protective effect on electron beam radiation (EBR) induced damage to pBR322 DNA; the highest protection was achieved at 150 µg concentrations. Similarly, M. indica extract (400 mg/kg) administrated to mice prior to irradiation protected DNA from the radiation damage, which was confirmed by inhibiting comet parameters. The study showed a significant increase in the levels of glutathione and superoxide dismutase levels. The study also revealed that administration of M. Indica at the different dose to mice significantly reduced EBR induced MDA, sialic acid and nitric acid levels. Further extract prevented histophatological changes of skin and liver. In contrast, protein-protein interaction studies were performed to find the hub protein, involved in radiation-induced DNA damage. Among 437 proteins that are found expressed during radiation, p53 was found to be a master protein regulating the whole pathway. Molecular interaction between p53 and M. indica extract was predicted by quantitative structure-activity relationship and ADMET properties. Biomolecules such as quercetin, myricetin, and 7-hydroxyflavone were found to be promising inhibitors of p53 protein and may help in the protection of EBR induced DNA damage during cancer treatment.

Natural radioprotectors and their impact on cancer drug discovery

Cancer is a complex multifaceted illness that affects different patients in discrete ways. For a number of cancers the use of chemotherapy has become standard practice. Chemotherapy is a use of cytostatic drugs to cure cancer. Cytostatic agents not only affect cancer cells but also affect the growth of normal cells; leading to side effects. Because of this, radiotherapy gained importance in treating cancer. Slaughtering of cancerous cells by radiotherapy depends on the radiosensitivity of the tumor cells. Efforts to improve the therapeutic ratio have resulted in the development of compounds that increase the radiosensitivity of tumor cells or protect the normal cells from the effects of radiation. Amifostine is the only chemical radioprotector approved by the US Food and Drug Administration (FDA), but due to its side effect and toxicity, use of this compound was also failed. Hence the use of herbal radioprotectors bearing pharmacological properties is concentrated due to their low toxicity and efficacy. Notably, in silico methods can expedite drug discovery process, to lessen the compounds with unfavorable pharmacological properties at an early stage of drug development. Hence a detailed perspective of these properties, in accordance with their prediction and measurement, are pivotal for a successful identification of radioprotectors by drug discovery process.