INTRODUCTION Root-knot nematodes (RKNs; Meloidogyne spp.) are sedentary endoparasitic worms that can infect a variety of plant species globally. This causes annual crop losses of about $70 billion (Caboni et al., 2012). The four most significant crop-damaging species of root knot nematode are M. incognita, M. arenaria, M. hapla, and M. javanica, which are among the top 10 most economically devastating plant-parasitic nematodes (Jones et al., 2013). Banana yields are reduced by 20–30% as a result of M. incognita (Liu et al., 2005). Besides having a brief biological cycle, they also produce root lesions, which helps in secondary pathogen invasion (Caboni et al., 2016). Conventionally nematode management was mostly accomplished through the application of nematicides (Caboni et al., 2016). However, numerous synthetic nematicides have lost their effectiveness over time, and their use has been connected to a variety of harmful effects, including soil and groundwater contamination, as well as animal, farmer, and consumer health concerns (López-Lima et al., 2013). Beneficial bacteria and fungi limit the population dynamics of plant parasitic nematodes (PPN) in soils, halting their growth either by trapping or releasing toxins, or by interacting with tiny compounds produced as secondary metabolites by hostile bacteria. Some of the microorganisms associated in nematode suppression are Bacillus subtilis, B. velezensis, B. amyloliquefaciens, Pseudomonas fluorescens, and Pasteuria penetrans (Davies et al., 2015; Silva et al., 2019). Secondary metabolites produced by bacterial endophytes have been found to have antinemicactivity against a range of plant parasitic nematodes (Yadav et al., 2021). Cefazolin is a secondary metabolite released by B. velenzensis which is having antifungal activity (Nayana et al., 2022). Furthermore, recent bioinformatics advances have led to the identification of nematode target sites and their interactions with biomolecules produced by various plant growth-promoting rhizobacteria. Thus, availability of annotated protein sequence of root knot and lesion nematode has allowed researchers to look into the most important proteins that play a vital role in the nematode's survival and invasion to host as potential therapeutic targets. An in-silico approach aids in the screening of secondary metabolites produced by bacterial endophytes to elucidate their inhibitory activity towards PPN (Terstappen and Reggiani, 2001). Further, Molecular docking facilitates virtual screening of diverse novel small molecules in short time for facilitating the structure-based drug design and to reduce the screening time (Amaro and Mulholland, 2018). Thus, based on the advances in the field of molecular docking, molecular simulation and release kinetics, novel biomolecules from bacterial origin could be identified for the management of plant parasitic nematodes infecting banana. MATERIALS AND METHODS Selection and molecular modelling of protein targets. Based on literature review, the potential protein targets of root knot nematode Meloidogyne incognita, were identified as cytochrome c oxidase subunit 1 (COX1) (Aditi Kundu et al., 2021), calreticulin (CRT) (Li et al., 2015; Jaouannet et al., 2013), venom allergen proteins (VAP) (Li et al., 2021 and Wilbers et al., 2018) and β-1,4 -endoglucanase (Smant et al., 1998). The Uni Prot database was utilised to retrieve the protein target sequences of the root knot nematode M. incognita. The chosen virulent protein targets for root knot nematode were lacking experimentally and computationally solved structures. SWISS-MODEL software was used to produce homology modelling for COX 1, endoglucanase, CRT and VAP (Waterhouse et al., 2018). The protein targets CRT,COX 1, endoglucanase, and VAP were blasted against Protein Data Bank (PDB) and followed homology modelling methodology. The parameters like Global Mean Quality Estimation (GMQE) score around 1, sequence identity percentage (30-50 %), and maximal query coverage were used to ensure the excellent quality of modelled structures. Model Validation of protein targets. From the Structural Analysis and Verification of protein (SAVES) server, the PROCHECK programme (https://saves.mbi.ucla.edu/) was used for analysing energy and stereo-chemical property of the modelled protein structures. Ramachandran plot was built for each target using the PROCHECK tool to find whether the residues are in the energetically favoured region. Energy minimisation along with the loop building for residues in the disallowed regions of Ramachandran plot was executed with the help of SWISS-PDB Viewer (Guex et al., 1997) Preparation of the Ligand. Structures of the ligands 10-acetyl-9,10-dihydroacridin valeric acid and formic acidwere all obtained in SDF format from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) (Kim et al.,2016). The commercial nematicide carbofuran 3G was used as a positive check. For the conversion of SDF to PDB file format Open Babel software was used (O'Boyle et al., 2011). Molecular docking analysis. To accomplish molecular docking, PyRx 0.8's AutoDock vina module was used (Dallakyan and Olson, 2015). The “make macromolecule” option in PyRx programme was used to prepare the structure of proteins. For the energy minimization of ligands conjugate gradient, first-order derivatives of an optimization procedure with 200 steps, and commercial molecular mechanics parameters-Unified Force Field (UFF)-were used. To determine binding site pockets for the targets, the Computed Atlas Topography of Proteins CASTp 3.0 server was used (Tian et al., 2018). AutoDock4 and autogrid4 parameter files were used for docking and grid configuration respectively. BIOVIA Discovery studio client 2021 (https://www.3ds.com/products-services/biovia/) was used to visualise interactions of docked conformations of protein-ligand complexes. To distinguish between the receptor, ligand, and interacting atoms, different colours were assigned to them (Design, 2014). RESULTS AND DISCUSSION Modelling of protein targets. Modelling for CRT was done using SWISS-MODEL software with the template protein (PDB ID-6ENY) of 66.05 percent identity,91 percent query coverage, and a GMQE (Global Model Quality Estimation) score of 0.75. Template protein for COX1 (PDB ID-3ABM) had 64.86 percent identity, 99 percent query coverage, and a GMQE score of 0.77, β- 1,4 -endoglucanase was modelled using template structure with (PDB ID-5IHS) had 49.17 percent identity,59 percent query coverage and 0.47 GMQE score, while VAP had 34.76 percent identity, 64 percent coverage, and a GMQE score of 0.45 with template protein (PDB ID-6ANY) (Fig.1). Model validation. Based on Ramachandran plot, the models were validated and was revealed that COX1 had 94.5 percent of the residues in the most preferred region (Fig. 2). The allowable percentage of CRT residues was found to be 87.3 percent (Fig. 3). 85.7 percent of residues of the target β-1,4-endoglucanase was found to be in allowed region(Fig. 4). Similarly, for the target VAP 82.3 percent of residues were found in most preferred region (Fig. 5). Molecular docking of biomolecules with theprotein targets of M. incognita. Virtual screening methods such as molecular docking contributed significantly to the discovery of a potential new small molecule with a broad range of mode of action. To use the advantage of molecular docking so that to find a molecule with the highest binding affinity against M. incognita protein target, we investigated the biomolecules, for their potential nematicidal activity against the potential effector and virulent protein targets of M. incognita. Docking studies were used to investigate the binding affinity of modelled protein structures with the compounds. The binding affinity of 10-acetyl-9,10-dihydroacridin with the target COX 1 was -9.4 kcal/mol (H-bonds: 0), binding affinity of calreticulin was -6.7 kcal/mol, β-1,4-endoglucanase had -4.6 kcal/mol as binding affinity (H-bonds: LYS 285, ALA 286) and VAP has a binding affinity of -8.3 kcal/mol. (H-bonds: TYR 172) exhibiting intermolecular interactions towards the binding pocket that provides stability to the complex (Fig. 6, Table 1 and 2). Carbofuran is a nematode-control agent used commercially by farmers. Hence, it was utilised to compare the affinity values as a positive check. The binding energy value of carbofuran found with the targets for COX 1 -4.2 kcal/mol (H-bonds: GLU 1), for β- 1,4 -endoglucanase -5.8 kcal/mol (H-bonds: LYS 241), for CRT–5.8 kcal/mol (H-bonds: ASN 166) and -6.6 kcal/mol for the target VAP (H-bonds: GLN 145, GLU 88). Two types of hydrogen bonds were found one with backbone and other with side chain. Other than hydrogen bonds there were other interactions also which are known as weak interaction like van der Waals interactions, pi-pi stacked interactions, alkyl, and pi-alkyl interactions (Fig. 7, Table 1 and 2). Among the selected protein targets of M. incognita, 10-acetyl-9,10-dihydroacridin exhibited the highest binding energy in relation to target sites COX-1, VAP, β-1,4- endoglucanase, CRT than the commercial nematicide carbofuran 3G.The maximum binding affinity (-9.4 kcal/mol) for the 10-acetyl-9,10-dihydroacridin with the protein target cytochrome c oxidase subunit-1 might inhibit the oxidative phosphorylation pathway and ultimately will cause mortality of nematodes while for the same target carbofuran shows binding energy of (-7.5 kcal/mol) which is less than 10-acetyl-9,10-dihydroacridin (Aditi Kundu et al., 2021). Likewise, maximum binding energy (-7.1 kcal/mol) of 10-acetyl-9,10-dihydroacridin with VAP may blocks these proteins which are involved in the establishment of persistent infections of nematodes in plants (Li et al., 2021). Further the maximum binding (-4.5 kcal/mol) of β- 1,4 -endoglucanase with ligand 10-acetyl-9,10-dihydroacridincould restrict the nematode access into plant tissues by inhibiting the nematode's ability to hydrolyse β-1,4 linkage in cellulose polymer (Smant et al., 1998). Subsequently 10-acetyl-9,10-dihydroacridinalso had the maximum binding energy (-6.7 kcal/mol) with protein target calreticulin. It indicated that binding of 10-acetyl-9,10-dihydroacridin with CRT might have blocked Ca2+ multifunctional protein and thus suppressed pathogenesis, reproduction, parasitism and aided in blocking evasion from immunity of host against root knot nematode (Li et al., 2015). However, no reports on the nematicidal action of 10-acetyl-9,10-dihydroacridin have been found. in comparison to carbofuran 3G, 10-acetyl-9,10-dihydroacridin showed maximum binding affinity and this suggests the possibility of 10-acetyl-9,10-dihydroacridin to have a nematicidal property better than the nematicidecarbofuran 3G which is commercially available. As a result, the current study is unique in that 10-acetyl-9,10-dihydroacridin can be used to create a formulation for the control of the banana root knot nematode.