Predicting pathogenic variants in the IHH gene associated with bone development abnormalities: a bioinformatics approach

Abstract Bone development abnormalities are challenging disorders with significant physical and emotional impacts. These abnormalities can stem from genetic or lifestyle factors, with genetic causes presenting ongoing research challenges. This study investigates the Indian hedgehog (Ihh) gene, which is known to be involved in bone formation issues. We analyzed non-synonymous single nucleotide polymorphisms (nsSNPs) in the Ihh gene retrieved from the dbSNP database for their deleterious nature and functional impact using various programs, including PolyPhen-2.0, FATHMM, Panther, SIFT, Provean, Mutation Assessor, and SNPS&GO. The stability of the protein structure was evaluated using Dynamut and I-Mutant 3.0. Out of 436 nsSNPs analyzed, 103 mutations were found to destabilize the protein. Special attention was given to mutations located in domain regions critical for protein function. Native and mutant protein models were predicted using SWISSMODEL, validated with PROCHECK, and compared for RMSD values using PyMOL. Functional impacts were assessed through docking studies with the binding partner using PatchDock. Significant changes in interaction energies and docking scores were observed, suggesting potential effects on protein function. This computational study indicates that these nsSNPs may contribute to bone-related disorders and suggests that the Ihh protein could be a potential drug target for further investigation and improved disease management.

Authors

Institutions

Publication Details

Journal
Discover Biotechnology
Published
2025-04-14
DOI
https://doi.org/10.1007/s44340-025-00016-z
Primary Topic
Genetic Syndromes and Imprinting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting pathogenic variants in the IHH gene associated with bone development abnormalities: a bioinformatics approach

Kumari Namrata, Vignesh Hariharan, Swetha Sunkar, Manoharan Athista et al.
Discover Biotechnology
Genetic Syndromes and Imprinting
article

Predicting pathogenic variants in the IHH gene associated with bone development abnormalities: a bioinformatics approach

Kumari Namrata, Vignesh Hariharan, Swetha Sunkar, Manoharan Athista, C. Valli Nachiyar, G. Pavankumar
article en

Abstract

Abstract Bone development abnormalities are challenging disorders with significant physical and emotional impacts. These abnormalities can stem from genetic or lifestyle factors, with genetic causes presenting ongoing research challenges. This study investigates the Indian hedgehog (Ihh) gene, which is known to be involved in bone formation issues. We analyzed non-synonymous single nucleotide polymorphisms (nsSNPs) in the Ihh gene retrieved from the dbSNP database for their deleterious nature and functional impact using various programs, including PolyPhen-2.0, FATHMM, Panther, SIFT, Provean, Mutation Assessor, and SNPS&GO. The stability of the protein structure was evaluated using Dynamut and I-Mutant 3.0. Out of 436 nsSNPs analyzed, 103 mutations were found to destabilize the protein. Special attention was given to mutations located in domain regions critical for protein function. Native and mutant protein models were predicted using SWISSMODEL, validated with PROCHECK, and compared for RMSD values using PyMOL. Functional impacts were assessed through docking studies with the binding partner using PatchDock. Significant changes in interaction energies and docking scores were observed, suggesting potential effects on protein function. This computational study indicates that these nsSNPs may contribute to bone-related disorders and suggests that the Ihh protein could be a potential drug target for further investigation and improved disease management.

Discover BiotechnologyVol. 2(1)
Meenakshi Academy of Higher Education and Research (IN), Sathyabama Institute of Science and Technology (IN)
Openalex Percentile: Top 91%
Genetic Syndromes and Imprinting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.