Skip to content

Structure-Guided Identification of 2-Arylbenzothiazole as disruptors for the Oncogenic MTDH-SND1 Protein-Protein Interaction.

Jul 2026 · Archives of Biochemistry and Biophysics · pp. 110949 · 0 citations · 35 references
Medicine

TL;DR

2-arylbenzothiazoles are established as a promising chemotype for MTDH-SND1 PPI inhibition and provide a validated computational-to-experimental framework for discovering and optimizing MTDH-directed therapeutics.

Abstract

The protein-protein interaction (PPI) between metadherin (MTDH) and staphylococcal nuclease and tudor domain-containing 1 (SND1) drives oncogenic signaling and tumor progression in multiple cancer types, yet remains an underexploited therapeutic target. Here, we report an integrated computational-experimental strategy to identify small-molecule disruptors of the MTDH-SND1 interface. A focused PubChem library of 4,149 2-arylbenzothiazoles was screened using a tiered workflow combining drug-likeness/PAINS filtering, hierarchical docking into the MTDH-binding groove on SND1 (PDB 4QMG), and MM/PBSA-based refinement. Top-ranked candidates were further evaluated by 1-μs molecular dynamics (MD) simulations and prioritized based on pose stability and interfacial engagement metrics. Four representative hits-L1 (2-(4-aminophenyl)benzothiazole), L2 (2-(4-amino-3-methylphenyl)-5-fluorobenzothiazole), L3 (YL-109), and L4 (2-(3,4,5-trimethoxyphenyl)benzothiazole)-were advanced for experimental validation. MD analyses indicated ligand-dependent modulation of PPI stability and conformational landscapes, while MM/PBSA decomposition suggested binding was driven predominantly by short-range hydrophobic packing within the interfacial groove. A quantitative split-luciferase complementation assay confirmed dose-dependent disruption of MTDH-SND1 in a cell-free format with low-micromolar potency (IC50: L1 10.72 ± 1.12 μM, L2 5.72 ± 0.92 μM, L3 11.77 ± 1.42 μM, L4 7.41 ± 1.01 μM) and in a cell-based reporter (IC50: L1 35.71 ± 2.80 μM, L2 16.44 ± 0.24 μM, L3 32.96 ± 2.58 μM, L4 21.93 ± 0.9 μM). Importantly, a linked-luciferase counterscreen (IC50 > 1,000 μM) supported minimal luciferase interference. MST analysis further confirmed direct binding of L1-L4 to purified SND1, yielding low-micromolar KD values. Together, these results establish 2-arylbenzothiazoles as a promising chemotype for MTDH-SND1 PPI inhibition and provide a validated computational-to-experimental framework for discovering and optimizing MTDH-directed therapeutics.

View source

Similar papers

Open access Sep 2026

Fragment-Based Discovery of BRD4-BD2 Selective Binders: Biophysical Validation and Structural Insights for Domain-Selective Inhibitor Design

BRD4, a member of the bromodomain and extra-terminal (BET) family of epigenetic readers, plays a central role in transcriptional regulation and is implicated in a wide spectrum of diseases. Although BRD4 inhibitors targeting both bromodomains have advanced into clinical studies, their development and therapeutic use ar...

Sriram Prakash Baskaran, Yashini Vidhya Subramani, S. Bairy et al. · 0 citations
Aug 2026

In silico evaluation of novel metabolites from Tricholoma pardinum: Insights into drug-likeness, toxicity and target interactions via molecular docking and dynamics.

Six previously uncharacterized metabolites isolated from the poisonous mushroom Tricholoma pardinum are investigated using an integrated in silico approach to evaluate their therapeutic potential, highlighting the potential of metabolites from T. pardinum as novel scaffolds for developing anticancer agents targeting PA...

A. Amin, H. M. Amin, A. R. Hamad et al. · 0 citations
Open access Aug 2026

In Silico Optimization of Dihydropteridine Derivatives Targeting PLK1 for Glioblastoma: An Integrated QSAR, Docking, and Molecular Dynamics Study

Computational findings support the prioritization of X14 for further experimental validation in glioblastoma therapy, and generally favorable ADMET profiles were observed, hepatotoxicity alerts were predicted for all compounds, which represents an important limitation supporting the prioritization of X14.

Youssef Briach, M. Er-rajy, Jamal Elkhabchi et al. · 0 citations
Open access Aug 2026

Structure-Based Virtual Screening and De Novo Design Guided by 3D-QSAR Triage for the Identification of Nanomolar STK3 Inhibitors

This study establishes a robust design paradigm for the rapid development of highly potent kinase inhibitors through structure-based computational strategies and indicates that 3D-QSAR modeling contributed as a complementary triage tool rather than a standalone driver of lead discovery.

Ahyoung Jang, Kewon Kim, Hyeonsoo Han et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.