Automated Author ProfileKulshrestha, Sudeepti
Kulshrestha, Sudeepti
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.9 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Aspergillosis is a major causative factor for morbidity in those with impaired immune systems, often caused by Aspergillus fumigatus. The diagnosis and treatment are difficult due to the diversity of individuals and risk factors and still pose a challenge for medical professionals. To understand the pathogenicity of any organism, it is critical to identify the significant metabolic pathways that are involved. Our work focused on developing kinetic models of critical pathways crucial for the survival of A. fumigatus using COPASI. While focusing on the folate biosynthesis, ergosterol biosynthesis and glycolytic pathway; sensitivity, time-course and steady-state analysis were performed to find the proteins/enzymes that are essential in the pathway and can be considered as potential drug targets. For further analysis of the interaction of drug targets identified, a protein–protein interaction (PPI) network was built, and hub nodes were identified using the Cytohubba package from Cytoscape. Based on the findings, dihydropteroate-synthase, dihydrofolate-reductase, 4-amino-4-deoxychorismate synthase, HMG-CoA-reductase, PG-isomerase and hexokinase could act as potential drug targets. Further, molecular docking and MM-GBSA analysis were performed with ligands chosen from DrugBank, and PubChem, and validated by experimental evidence and existing literature based on results from kinetic modeling and PPI network analysis. Based on docking scores and MM-GBSA results, molecular simulations were carried out for 1AJ2-dapsone, 1DIS-sulfamethazine, 1T02-lovastatin and 70YL-3-bromopyruvic acid complexes, which validated our findings. Our study provides a deeper insight into the mechanisms of A. fumigatus’s metabolism to reveal dapsone, sulfamethazine, lovastatin and 3-bromopyruvic acid as potential drugs for the treatment of Aspergillosis. Communicated by Ramaswamy H. Sarma
Authors
- Narad, Priyanka ;
- Kulshrestha, Sudeepti ;
- Chikara, Aryan ;
- Gupta, Vinayak ;
- Kakrania, Mahi ;
- Saxena, Ritika ;
- Gupta, Payal ;
- Gupta, Lovely ;
- Vijayaraghavan, Pooja ;
- Sengupta, Abhishek
Aspergillosis is a major causative factor for morbidity in those with impaired immune systems, often caused by Aspergillus fumigatus. The diagnosis and treatment are difficult due to the diversity of individuals and risk factors and still pose a challenge for medical professionals. To understand the pathogenicity of any organism, it is critical to identify the significant metabolic pathways that are involved. Our work focused on developing kinetic models of critical pathways crucial for the survival of A. fumigatus using COPASI. While focusing on the folate biosynthesis, ergosterol biosynthesis and glycolytic pathway; sensitivity, time-course and steady-state analysis were performed to find the proteins/enzymes that are essential in the pathway and can be considered as potential drug targets. For further analysis of the interaction of drug targets identified, a protein–protein interaction (PPI) network was built, and hub nodes were identified using the Cytohubba package from Cytoscape. Based on the findings, dihydropteroate-synthase, dihydrofolate-reductase, 4-amino-4-deoxychorismate synthase, HMG-CoA-reductase, PG-isomerase and hexokinase could act as potential drug targets. Further, molecular docking and MM-GBSA analysis were performed with ligands chosen from DrugBank, and PubChem, and validated by experimental evidence and existing literature based on results from kinetic modeling and PPI network analysis. Based on docking scores and MM-GBSA results, molecular simulations were carried out for 1AJ2-dapsone, 1DIS-sulfamethazine, 1T02-lovastatin and 70YL-3-bromopyruvic acid complexes, which validated our findings. Our study provides a deeper insight into the mechanisms of A. fumigatus’s metabolism to reveal dapsone, sulfamethazine, lovastatin and 3-bromopyruvic acid as potential drugs for the treatment of Aspergillosis. Communicated by Ramaswamy H. Sarma
Authors
- Narad, Priyanka ;
- Kulshrestha, Sudeepti ;
- Chikara, Aryan ;
- Gupta, Vinayak ;
- Kakrania, Mahi ;
- Saxena, Ritika ;
- Gupta, Payal ;
- Gupta, Lovely ;
- Vijayaraghavan, Pooja ;
- Sengupta, Abhishek