Structural Biology Overview

Principles

Definition

Structural biology is a field of research dedicated to determining the three-dimensional atomic and molecular structures of biological macromolecules, primarily proteins and nucleic acids, and investigating the relationship between their structure, dynamics, and function. This interdisciplinary field integrates principles and techniques from molecular biology, biochemistry, and biophysics to understand biological processes at a fundamental level, which is essential for comprehending disease mechanisms and advancing the development of drugs and vaccines.

Ontological type

Core Techniques

Structure–Function Relationships

Biomedical Applications

Key developments

Key Figures

Experimental Foundations era

David A. Case[1] is a pivotal figure in structural biology during the Experimental Foundations era, with ties to Harvard University[3] and the University of California, San Francisco[4]. His key contribution in this era, as evidenced by the 1984 paper A new force field for molecular mechanical simulation of nucleic acids and proteins[6], was the development of a practical biomolecular force field that enabled more accurate modeling of macromolecular structure and dynamics. Peter A. Kollman[2] is likewise linked to the University of California, San Francisco[4] and the University of California, Berkeley[5] in this era. His contributions, highlighted by co-authorship of the 1984 force field paper A new force field for molecular mechanical simulation of nucleic acids and proteins[6], helped establish a computational framework that supported experimental structure elucidation and functional interpretation during this era.

Standardized Structural Workflows era

Janet M. Thornton [1] was active across The University of Texas Southwestern Medical Center [3] and Columbia University [4] during the Standardized Structural Workflows era. Her key contribution was PROCHECK: a program to check the stereochemical quality of protein structures [7], a foundational tool that anchored automated validation and quality control within reproducible structure-determination pipelines. Alex Bateman [2] was active at Heidelberg University [5] and University College London [6] in this era. His contributions centered on establishing the Pfam protein families database, with key papers The Pfam Protein Families Database [10] (2000), The Pfam protein families database [8] (2002), and The Pfam protein families database [9] (2004), which standardized protein family classification and enabled scalable annotation and comparative analyses across genomes within automated, reproducible workflows.

Integrative Predictive Biology era

Johannes Söding [1], associated with the Weizmann Institute of Science [3] and Seoul National University [4] in this era, helped advance computational strategies for protein analysis. His 2011 works on Clustal Omega [7] and HHblits [8] established fast, scalable MSAs and rapid sequence searching, providing essential infrastructure for end-to-end structure prediction in Integrative Predictive Biology. Julie Thompson [2], affiliated with the University of Puerto Rico at Carolina [5] and Duke University [6], contributed to this era through the Clustal Omega work [7], enabling rapid, scalable generation of high-quality MSAs that supported benchmarking and predictive modeling. Together, these contributions underscore how cross-institutional collaboration and fast sequence-analysis tools catalyzed open benchmarking resources and integrative modeling frameworks in this era.