1Manoj K. Sain

2Bersha Kumari

3Karan Yogi

4Sagar Mahawar

1Arya Institute of Engineering And Technology,
2Arya Institute of Engineering, Technology and Management
3 Sandapani International School
4Govt. Senior Sec, School


Drug design is an expensive, time-consuming, and often unsuccessful process. To avoid this liability, FDA-approved drugs are rapidly repurposed using computational drug repositioning techniques to predict their potential therapeutic benefits in treating various diseases. To find FDA-approved anti-AD drugs, this computational study used methods such as protein modelling, shape-based screening, molecular docking, pharmacogenomics, and molecular dynamics simulation. Using the homology model, the predicted structure of the MADD protein was generated and characterized. Use of various IT tools. The drugs were filtered based on their structural similarity, and donepezil and galantamine were included as standard drugs. The primary and secondary structural features of the protein were calculated using ProtParam and SOPMA, respectively, which revealed that the protein was composed of random coil (41.71%), helix (36.23%), extended fibres (14.06%), and b exists. Consists of. Sales (8.00%). The three-dimensional structure of P. falciparum PABP was not yet available in the PDB. Therefore, homology models of these proteins were developed using the SWISS-MODEL, PHYRE2, and I-TASSER web servers. The models were visualized using RASMOL and their reliability was checked using PROCHECK, Verify3D, and QMEAN. 92.64% of the residues in the predicted model have a mean 3D-1D score. 0.2, indicating that the predicted model matches the sequence. Protein-protein and residue-residue interaction networks were generated from STRING and RING servers, respectively. The 3D ligand server was used to analyse the binding sites of the modelled PABP. This planned structure of P. falciparum PABP will contribute significantly to a better understanding of the protein's function in translation regulation in the parasite and could also provide targets for new therapeutic candidates


Biocomputing, Bioinformatics, Computational-biology, DNA, Data-Science, Algorithms, Input, Output, Domain knowledge, Functional Genomics

Paper Details
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