Skip to content
#protein folding Open access

Comprehensive analysis of non-synonymous single-nucleotide polymorphism of human TSC1 and TSC2 genes: An in silico approach

Sep 2026 · PLoS ONE · 75 references
Tuberous Sclerosis Complex Research

Abstract

Abstract Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by mutations in the TSC1 and TSC2 genes and is characterized by benign hamartoma formation in multiple organs. The TSC1–TSC2 complex regulates mTORC1 signaling in response to cellular growth conditions. This study aims to predict the structural stability and functional effects of non-synonymous single-nucleotide polymorphisms (nsSNPs) in human TSC1 and TSC2 using computational approaches. Twelve computational tools were assessed using receiver operating characteristic (ROC) analysis and applied to identify deleterious nsSNPs. Protein stability was predicted using I-Mutant 2.0 and MUpro, while evolutionary conservation was analyzed with ConSurf. NetPhos 3.1 identified potential PTM sites, and MutPred2.0 evaluated their functional impact. Project HOPE assessed mutation-induced physicochemical changes. Structural models were validated using multiple tools, visualized in ChimeraX 1.9, and further evaluated by molecular dynamics simulation to confirm wild-type and mutant stability. All twelve tools had AUC values above 0.90. A combined in silico analysis identified twelve high-risk nsSNPs in TSC1 and sixteen in TSC2, all reducing protein stability, located in conserved regions, and potentially disrupting phosphorylation sites. MutPred and Project HOPE confirmed their impact on protein function. Functional analysis showed TSC1 and TSC2 affect mTORC1 and PI3K–Akt pathways. RMSF and RMSD analyses revealed that TSC1 variants rs1846545280 (G236E), and rs2132135678 (V234E), and TSC2 variants rs45517223 (S758C), rs2151354925 (T836P), and rs45517365 (R1570W) had the largest structural fluctuations. Substitution with glutamic acid, a negatively charged and bulkier residue, may disrupt local folding of TSC1. Similarly, replacement of arginine with tyrosine at position 1570 may impair Rheb binding at the GAP domain of TSC2. These findings highlight potentially pathogenic nsSNPs in TSC1 and TSC2.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Google DeepMind Blog Nov 25, 2025

AlphaFold: Five years of impact

Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.

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