INTRODUCTION:

The messenger ribonucleic acid(mRNA) carries all genetic information from DNA to the cytoplasmic site where protein-making machinery can work to form functional protein. Pre-mRNA undergoes cognate alternative splicing (AS) to form proteome diversity with a limited number of genes¹.

To ensure, the transcription correctly take place or not, eukaryotic cell developed various quality control mechanisms from which NMD is one of the finest studied among all eukaryotic mRNA surveillance mechanism. Nonsense-mediated mRNA decay (NMD)is a cytoplasmic event used by eukaryotes to identify aberrant transcripts having Pre-termination codon (PTCs) and degrade them^2-4. It is an evolutionary conserved translation-dependent mechanism that prevents truncated proteins from having a negative effect on the cells^5-7. NMD downregulates the abnormal transcriptome that affects a broad spectrum of cellular function and maintains cellular homeostasis^8-10. It allows cells to eliminate abnormal potentially harmful transcripts early in their biogenesis but the mechanism of target mRNA selection for NMD is still unknown^11-13. It is largely restricted to newly synthesised mRNA having PTCs. The PTCs are the result of an error in nucleic acid metabolism which mostly arises either due to mutation, defect in splicing, or during the transcription process^14-16. PTC can lead to the formation of C-terminal truncated protein having negative or damaging effects on the cell by associating with diseases such as β-thalassemia, cystic fibrosis, cancer, etc.¹⁷. It is located at >50-55 nucleotides upstream of the exon-exon junction at the upstream region of pre-mRNA^18-20. NMD initiates once the translating ribosome arrives at a PTC, at this moment the eukaryotic release factors 1 (eRF1) and eukaryotic release factors 3 (eRF3) interact with the core NMD factor up-frameshift protein 1 (UPF1), hence inducing premature translation termination. Following this, SMG1 with its regulators, SMG8 and SMG9, interacts with eRF1, eRF3, and UPF1 forming a “SURF” complex^21-23. For the UPF1-SMG1 interaction, ATP-dependent RNA helicase DEAH box polypeptide34 (DHX34) acts as a scaffold protein^24,25. UPF2 and UPF3B interact with UPF1, the SURF complex is transformed into a decay-inducing complex (DECID).

NMD in TUMORIGENESIS:

Tumor cells take advantage of NMD pathway to agitate uncontrolled growth by somatic mutation in tumour suppressor gene. The tumour suppressor genes (WT1, TP53, RB& BRAC1/2) have more tendency to get nonsense mutation than oncogenes, to promote tumorigenesis^26-28. It has been found from cancer patients that tumour suppressor genes are enriched with PTCs to trigger NMD activity. This incorporation is done by introducing PTC bearing allele in the tumour suppressor gene by making heterozygous deletion(haploinsufficiency). Phosphorylation or dephosphorylation of NMD-associated proteins (UPF1, UPF2, UPF3B, SMG1-5-6-7) results in upregulation of NMD expression which are benefited by tumour cells for growth and progressions^29-31. Lindeboom et.al discovered the role of haploinsufficiency in tumour suppressor gene promoting cancer growth. The cancer cells make use of NMD activity to suppress tumour by inducing mutation in one allele combined with deletion of the other allele or by selecting NMD-resistant mutation in alleles producing dominant negative proteins^32,33. In a study of colorectal cancer (CRC), two subgroups were investigated i.e., CRC with microsatellite instability (CRC MSI) and CRC with stable microsatellite sequence (CRC MSS). Due to instability in simple sequence repeat (SSRs), CRC MSI acquires more levels of PTC-mRNA. It is also found that some important NMD factors like UPF1/2 and SMG1/6/7 show upregulated expression in CRCs with MSI that facilitate CRC MSI tumours to survive. In contrast, the HSP110DE9 chaperon mutant has a dominant negative effect on MSICRC resulting in the development of cancer^34,35. Under different circumstances, if the PTC-bearing tumour suppressor gene produces an aberrant protein rather than a negative one, it is also targeted by NMD and leads to cancer development. The E.cadherin(CDH1) gene is an important tumour suppressor gene. Patients with reduced expression in the CDH1 gene caused by NMD-insensitive mutation in the gene have a propensity to develop hereditary diffuse gastric cancer (HDGC) but the resistant mutation of the CDH1 gene can function normally with truncated E.cadherin^36-38. SMG1, an important kinase involved in the NMD pathway, is a member of the phosphatidylinositol 3-kinase-related kinase (PIKK) family^39-41. SMG1 phosphorylates specific proteins, such as UPF1, which is essential for initiating NMD, triggering the degradation of defective mRNAs and preventing the production of abnormal proteins^42,43. Additionally, SMG1 has been discovered to play a significant role in cancer biology⁴⁴.In the NMD pathway, a crucial step involves the phosphorylation of the UPF1 protein by SMG1. UPF1 is a key component that initiates the degradation of defective mRNA. Phosphorylation is a process that entails adding a phosphate group to a protein, altering its function and activity. When SMG1 phosphorylates UPF1, it activates UPF1, thereby initiating the NMD process and leading to the breakdown of faulty mRNA. Due to its central role in the NMD pathway, SMG1 is an attractive target for the development of small molecule inhibitors. Inhibiting SMG1 may offer the potential to modulate the NMD pathway, potentially providing therapeutic benefits such as stabilizing specific mRNAs, which could be advantageous in diseases where NMD is dysregulated.

MATERIALS AND METHODS:

Protein Structure Preparation:

The crystal structure of the target Protein human SMG1 was retrieved from the Protein Data Bank (PDB) (PDB ID:6L53). Protein structure was prepared using Autodock tools 1.5.7 to remove water molecules, heteroatoms, and other non-protein entities. Hydrogen atoms were added, and protonation states were assigned. The grid box was defined around the SMG1 protein, considering for blind docking method and the grid parameters were saved as .gpf file.

SELECTION OF LIGANDS AND PREPARATION OF LIGAND LIBRARY:

Based on literature survey we have selected and prepared a library of 100 FDA approved anti-cancer drugs. Chemical structures of these 100 cancer drugs were obtained from the PubChem database in SDF format. Before proceed to molecular docking step, optimization of these ligands were done using AutoDock tools.

LIGAND PREPARATION:

Employed Open Babel and AutoDock tools for ligand preparation. Ligand structures were first converted from SDF to PDB format using OpenBabel software to make them compatible for Autodock tools. These PDB files of the ligands were then processed using the Autodock tolls 1.5.7. 3D structures of these ligands were then saved in PDBQT format.

MOLECULAR DOCKING:

In computational drug designing molecular docking is a widely used method that helps to identify potential drug candidates against various disease targets. This advanced computational method can save a significant amount of energy, time, and costs in the drug discovery process by screening large libraries of potential drug compounds in a very short span of time. In our study, we have screened a library of 100 bioactive anti cancer drugs against human SMG1 using Autodock 4.2 program^45-60. Based on the binding energy score, we have shortlisted top eleven ligands with lowest binding energy score (<10.0Kcal/mol).

RESULTS AND DISCUSSION:

The Autodock program performs molecular docking of hundred anti-cancer drugs against the SMG1 protein. Following the molecular docking study of all the ligands, the docking scores for all the ligands are evaluated. The top five compounds with the lowest binding energy scores are selected for further analysis (Table 1). Then analysis of the docking score and different types of molecular interaction between the ligands and protein were done. After carefully evaluating the docking output, we found that Nilotinib displayed the highest binding affinity towards SMG1, making it one of the most promising candidates for further analysis. We have generated a 2D plot using discovery studio vizualizer to illustrate the different bonded and non-bonded molecular interactions between the human SMG1 protein and the anticancer drugs showing top binding affinity. The molecular interactions between the protein and the top five selected ligands with high binding affinity are displayed in both 3D and 2D plots (Figures 1-3).

The lowest binding energy is shown by Nilotinib which is -11.25 kcal/mol among all the conformations and ligands. It shows three Vanderwaals bonds with residues LEU 486; ASN 488 and GLN 485. The carbon hydrogen bonds with residue ASP 495 and SER 554 were observed. It shows Pi Sigma bond with residue LEU 561 and a Pi Alkyl bond with residues CYS 489; PRO 559; VAL 560; ILE 558; LEU 555; ILE 612; LYS 608; VAL 611 (Figure 1).

Figure 1: 2D and 3D representation of molecular interaction between the SMG1 and Nilotinib (CID 644241): (A)docked complex of SMG1 protein and nilotinib; (B) close view of pocket with nilotinib in the stick model structure colored by atom types; (C) 2D representation of different types of interactions with nilotinib including van der Waals, conventional hydrogen bond, carbon hydrogen bond, Pi–sigma, and alkyl; (D) hydrophobicity surface representation of the overall structure SMG1; and (E) Surface representation of the complex showing residues involved in hydrogen bond donor acceptor.

The second lowest binding energy score is of Tazemetostat which is found to be -11.00 kcal/mol. VAL 1342; SER 1343; THR 637; LEU 641; THR 637; ASP 676 and GLN 1344 formed vanderwaals interaction with SMG1. A conventional hydrogen bonding was observed with residue PHE 639 and ALA 640 as well as HIS 671; HIS 677; SER 1345 formed carbon hydrogen bonds. Along this Pi cation bonds were found with residue ARG 674 and Pi Alkyl bonds with residue LEU 642 and LEU 1346 (Figure 2).

Figure 2: 2D and 3D representation of molecular interaction between the SMG1 and Tazemetostat (CID 66558664): (A)docked complex of SMG1 protein and tazemetostat; (B) close view of pocket with tazemetostat in the stick model structure colored by atom types; (C) 2D representation of different types of interactions with tazemetostat including van der Waals, conventional hydrogen bond, carbon hydrogen bond, Pi–sigma, and alkyl; (D) hydrophobicity surface representation of the overall structure SMG1; and (E) Surface representation of the complex showing residues involved in hydrogen bond donor acceptor.

The third lowest binding energy score is shown by Avapritinib which is -10.95kcal/mol. It shows vanderwaals interactions with avapritinib with residues GLU 21122; LEU 2342; VAL 2208, ASP 2209. The conventional hydrogen bonding was observed with residues HIS 2192 and TYR 2152 while carbon hydrogen bonding was also observed with VAL 2113; VAL 2119; GLN 2206; SER 2194. Along this Pi-Pi stacked residue TYR 2150; TYR 2193 and Pi Alkyl bonding with PRO 2110; VAL 2351 residue was found (Figure 3).

Figure 3: 2D and 3D representation of molecular interaction between the SMG1 and Avapritinib (CID 118023034): (A)docked complex of SMG1 protein and Avapritinib; (B) close view of pocket with Avapritinib in the stick model structure colored by atom types; (C) 2D representation of different types of interactions with Avapritinib including van der Waals, conventional hydrogen bond, carbon hydrogen bond, Pi–sigma, and alkyl; (D) hydrophobicity surface representation of the overall structure SMG1; and (E) Surface representation of the complex showing residues involved in hydrogen bond donor acceptor.

Acalabrutinib-SMG1 complex showed the minimum binding energy of -10.78 kcal/mol among all the conformations and ligands. It shows Van der waals interactions with residues VAL 1342; THR 637; GLN 1344; CYS 672; LEU 1346; THR 2185; GLN 2183; GLU 2184; ASN 2181. A conventional Hydrogen bonding was done by HIS 677; SER 1345 residues. SER 1343 was interacting with ligand using the carbon hydrogen bond while ARG 2182; ARG 674 and HIS 671 residues are forming Pi Alkyl bond.

The binding affinity of Tucatinib was -10.69 kcal/mol. A sum total of six types of bond formation was observed. THR 2347; ARG 2182; LYS 719; GLN 1309 and GLU 2184 form vanderwaals bond with SMG1. The conventional hydrogen bonds residue was found to be ASN 712 andcarbon-hydrogen bond residue was HIS 677. Along with Pi sigma bond residues GLN 2183; ILE 716, THR 2185 and Pi-Cation ARG 2312; ARG 2187 were observed.

CONCLUSION:

The human SMG1 protein has been shown to be crucial for the normal functioning of the NMD pathway, and it can be a highly potent drug target for modulating this pathway. In the present study, the protein-ligand binding mechanism of anti-cancer compounds in the active site of SMG1 protein has been elucidated using a molecular docking study. Based on docking results, we selected eleven ligands with minimum binding energy score (< -10.00 Kcal/mol) towards SMG1. These eleven anticancer drugs are Nilotinib, Tazemetostat, Avapritinib, Acalabrutinib, Tucatinib, Osimertinib, Vandetanib, Apalutamide, Adagrasib,Dacomitinib and Tepotinib and we considered them as potential inhibitors against SMG1. Molecular docking analysis revealed that Nilotinib molecule has lowest binding energy as compared to the all other compounds. The binding mode of these ligands with the target protein and the molecular interactions between protein and ligands were found to be reasonably good. Among these top eleven ligands, Nilotinib has been shown to be the best binder of SMG1, while other ten selected compounds also shows high binding affinity towards SMG1 protein. All these ligands are reported anticancer compounds used in cancer treatment and are also commercially available for further in vivo/in vitro validations. These eleven drugs are predicted to have a strong binding affinity for SMG1, and therefore, binding of these molecules with SMG1 can interfere with the normal functioning of the NMD pathway. The information generated from this present study may be utilized in the future for the development of anti-cancer therapeutics by targeting NMD pathway.

STATEMENTS AND DECLARATIONS:

FUNDING:

Authors would like to thank the Vice Chancellor, Centurion University of Technology and Management, Odisha for providing financial support to GKP (grant approval letter no: CUTM/VC Office/45 to GKP).

COMPETING INTERESTS:

The authors declare that they have no conflict of interest.

ETHICAL APPROVAL AND CONSENT TO PARTICIPATE:

No ethical approval is required.

CONSENT TO PUBLISH:

Not applicable.

HUMAN AND ANIMAL RIGHTS:

No animals were used in the study.

AVAILABILITY OF DATA AND MATERIALS:

Not applicable.

CREDIT AUTHORSHIP CONTRIBUTION STATEMENT:

All the authors have substantial contribution for the preparation of the manuscript. GKP and AS: conceptualized and conceived the idea. SM, GKP, AS, RD, AB, AKP: data curation and writing. All the authors have read and approved the final manuscript before submission.

CONFLICT OF INTEREST:

The authors declare that they have no conflict of interest.

ACKNOWLEDGEMENTS:

Authors thank the administration and management of Centurion University of Technology and Management, Odisha, India for their heartfelt support. We apologize to all colleagues whose work could not be included owing to space limitations.

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Received on 01.03.2025 Revised on 05.07.2025

Accepted on 07.09.2025 Published on 05.06.2026

Available online from June 06, 2026

Research J. Pharmacy and Technology. 2026;19(6):2409-2415.

DOI: 10.52711/0974-360X.2026.00344

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

Sl. No	Name of compounds	Binding Affinity (Kcal/Mol)	Types of molecular interactions between protein and ligands
1.	Nilotinib	-11.25	Vanderwaals interaction: LEU 486; ASN 488 and GLN 485 Carbon hydrogen bonds: ASP 495 and SER 554 Pi Sigma bond: LEU 561 Pi Alkyl bond: CYS 489; PRO 559; VAL 560; ILE 558; LEU 555; ILE 612; LYS 608; VAL 611.
2.	Tazemetostat	-11.00	Van der waals interaction: VAL 1342; SER 1343; THR 637; LEU 641; THR 637; ASP 676 and GLN 1344. Conventional hydrogen bonding: PHE 639 and ALA 640 Carbon hydrogen bonds: HIS 671; HIS 677; SER 1345 Pi Alkyl bonds: LEU 642 and LEU 1346 Pi cation bonds: ARG 674
3.	Avapritinib	-10.95	Van der waals interactions: GLU 21122; LEU 2342; VAL 2208, ASP 2209 Conventional hydrogen bonding: HIS 2192 and TYR 2152 Carbon hydrogen bonding: VAL 2113; VAL 2119; GLN 2206; SER 2194 Pi Alkyl bonding: PRO 2110; VAL 2351 Pi-Pi stacked: TYR 2150; TYR 2193
4.	Acalabrutinib	-10.78	Van der waals interactions: VAL 1342; THR 637; GLN 1344; CYS 672; LEU 1346; THR 2185; GLN 2183; GLU 2184; ASN 2181. Conventional Hydrogen bonding: HIS 677; SER 1345 Carbon hydrogen bonding: SER 1343 Pi Alkyl bonding: ARG 2182; ARG 674; HIS 671
5.	Tucatinib	-10.69	Van der waals interactions: LYS 719; GLN 1309; THR 2347; GLN 2184; ARG2182. Conventional Hydrogen bonding: ASN712 Carbon hydrogen bonding: HIS 677 Pi-sigma: THR2185; RGLN 2183; ILE716