Genomes with Superfamily and G3D Structural Annotations

Nor Zalina^*
*Correspondence: Nor Zalina, Department of Advanced Bioprocess, University of Technology Malaysia, Johor, Malaysia, Email:

Introduction

Structural annotation of genomes plays a crucial role in understanding the functional and evolutionary aspects of genes and their products. Superfamily and G3D are two widely used databases and tools for structural annotations, providing valuable information on protein domains, families, and their threedimensional (3D) structures. This article explores the significance of structural annotations in genomics research, focusing on the applications and features of Superfamily and G3D. It discusses their capabilities in identifying conserved domains, predicting protein functions, elucidating evolutionary relationships, and facilitating drug discovery efforts. Genomic sequencing efforts have provided vast amounts of DNA sequence information, but understanding the functions and mechanisms of genes requires knowledge beyond the sequence alone. Structural annotations of genomes provide insights into the three-dimensional structures and functional domains of proteins encoded by genes. Superfamily and G3D are powerful tools that utilize protein structure and domain information to enhance our understanding of genomic data.

Description

Superfamily identifying evolutionarily related protein domains: Superfamily is a database and classification system that identifies evolutionarily related protein domains across diverse organisms. It uses hidden Markov models (HMMs) to detect and classify protein domains based on their shared evolutionary history. Superfamily allows researchers to identify conserved structural motifs, predict protein functions, and explore evolutionary relationships.

Domain architecture: Superfamily provides information about the architecture and organization of protein domains within a gene or protein sequence. By analyzing the arrangement and combination of domains, researchers can infer the functional and regulatory characteristics of proteins. Superfamily assigns functional annotations to protein domains based on known protein structures and their associated functions. This information aids in predicting the functional properties of uncharacterized proteins and provides insights into their potential roles in cellular processes. Superfamily's classification system enables the exploration of evolutionary relationships between protein domains across different organisms. By identifying orthologous and paralogous relationships, researchers can study the diversification and adaptation of protein families throughout evolution [1].

3D structure visualization: G3D allows researchers to visualize protein structures and explore their three-dimensional conformation. This feature aids in understanding the spatial arrangement of protein domains, their interactions, and the potential functional implications. G3D provides information on known ligand binding sites within protein structures. This data is essential for understanding protein function, identifying potential drug targets, and facilitating structurebased drug discovery efforts, incorporates computational methods for protein structure prediction, including homology modeling and ab initio methods. These tools enable researchers to generate structural models for proteins with unknown structures, providing insights into their potential functions and interactions [2-5].

Conclusion

Integration with Genomic Data: Integrating structural annotations with genomic data, such as gene expression profiles and regulatory elements, will provide a more comprehensive understanding of the functional landscape of genomes. Efforts to merge different types of genomic data will enable a holistic analysis of gene regulation and protein function, Advances in computational methods for protein structure prediction and function annotation are crucial for enhancing the accuracy of structural annotations. Integration of machine learning approaches and experimental data will contribute to more reliable predictions. Structural annotations of genomes using databases and tools such as Superfamily and G3D play a vital role in understanding the functional and evolutionary aspects of genes. These resources provide insights into conserved domains, protein functions, evolutionary relationships, and potential drug targets. As genomic data continues to grow, improving the accuracy and completeness of structural annotations and integrating them with other genomic information will enhance our understanding of the complexity and functionality of genomes, paving the way for advancements in fields such as medicine, biotechnology, and evolutionary biology.

References

1. Bratteler, M., C. Lexer and Alex Widmer. "Genetic architecture of traits associated with serpentine adaptation of Silene vulgaris." J Evol Biol 19 (2006): 1149-1156.

Google Scholar, Crossref, Indexed at

2. Cervera, Maria-Teresa, Véronique Storme, Bart Ivens and Jaqueline Gusmao, et al. "Dense genetic linkage maps of three Populus species  based on AFLP and microsatellite markers." Genetics 158 (2001): 787-809.

Google Scholar, Indexed at

3. Cervino, Alessandra CL, Ariel Darvasi, Mohammad Fallahi and Christopher C. Mader, et al. "An integrated in silico gene mapping strategy in inbred mice." Genetics 175 (2007): 321-333.

Google Scholar, Crossref, Indexed at

4. Chakravarti, Aravinda, Laura K. Lasher and Jillian E. Reefer. "A maximum likelihood method for estimating genome length using genetic linkage data." Genetics 128 (1991): 175-182.

Google Scholar, Crossref, Indexed at

5. Cheng, Ju-Chien, Chien-Ling Huang, Chung-Ching Lin and  Chi-Ching Chen, et al. "Rapid detection and identification of clinically important bacteria by high-resolution melting analysis after broad-range ribosomal RNA real-time PCR." Clin Chem 52 (2006): 1997-2004.

Google Scholar, Crossref, Indexed at