Structural Biology and Molecular Applications Research

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pink fractal protein

Fractal design that looks like the molecular structure of a protein.

Credit: iStock

Progress in cancer research is often driven by technological progress, which allows researchers to address questions that were until then inaccessible. Research in structural biology and molecular applications allows for the development of methods and technologies that lead to discoveries in a variety of areas in cancer biology. The scope of this research include four broad areas: structural and biophysical biology; molecular applications; bioinformatics, computational biology, data science, citizen science methods, and systems biology; and bioengineering and biotechnology.  The development, testing, and early validation of wet lab technologies, computer-based methods and data science, and device and systems development are all enabled by research in structural biology and molecular applications.

Research in this area is supported and directed by the Structural Biology and Molecular Applications Branch.

Structural and Biophysical Biology

chemical molecular formula

The structural formula of a molecule.

Credit: iStock

This area of research focuses on:

  • Determining the 3-D structure(s) (morphology/arrangement) of biomolecules and molecular assemblies associated with cancer development and progression
  • Structure and assembly of cellular organelles and extracellular molecular assemblies associated with cancer development and progression
  • Structural and/or biophysical studies on activators and inhibitors of molecular pathways associated with cancer development and progression
  • Molecular (including chemical and biophysical) basis of enzyme catalysis and regulation in molecular pathways associated with cancer development and progression

Molecular Applications

This research area supports new approaches and methods for characterizing and perturbing genomes, epigenomes, proteomes, glycomes, and metabolomes, as well as methods for other high-throughput molecular characterizations.  Development of new and early-stage application of high-throughput molecular approaches is also supported, including:

  • Understanding the composition and organization of genomes, transcriptomes, proteomes, and metabolomes, as well as their variations in cancer initiation and development
  • Identifying and characterizing functional units of genomes and their roles in carcinogenesis/tumorigenesis
  • Methodologies for selecting and preparing cancer-related protein samples, including tissue sampling, cell sorting, laser dissection, and extraction of molecular components of cells, including proteins, molecular complexes, and metabolites
  • Novel methods for extracting and characterizing DNA and RNA to facilitate the study of genes and their transcripts associated in carcinogenesis

Bioinformatics

Studies focused on developing and/or using bioinformatics methods and software tools for data management and analysis investigate a variety of topics, including:

  • Developing computational methods for automated experimental design and execution, data collection, processing, storage, organization, integration, visualization, and analysis that are related to cancer biology, including those focused on using an understanding of the biology to guide drug discovery
  • Assessing data quality, data annotation, curation, and mining, including the development of new ontologies, standards, common data elements for data integration, organization, and interpretation
  • Developing methods associated with processing and managing big data, such as data compression, data reduction, data wrangling, and data provenance tools to handle high-throughput genomics and other types of big data
  • Developing new computational methods and platforms for research collaboration and research training

Computational Biology, Data Science, and Citizen Science

Adopting computational, mathematical, or statistical modeling methods to help understand biological processes and cancer development is a critical field of research. Examples include:

  • Mathematical, statistical, and computational modeling or simulation of genetic controls, cellular processes, and signaling networks related to carcinogenesis/tumorigenesis. This includes computational models that cross biological scale as well as those that focus primarily on modeling biological processes or on clarifying underlying biological mechanisms
  • Modeling tumor cell population dynamics and evolution in cancer development and progression
  • Development or early application of new computational, mathematical, and statistical approaches to model and understand cancer processes
  • Developing and exploring theoretical biological concepts in cancer biology

Systems Biology

Research focused on developing systems or integrative biological approaches to understanding basic cancer biology and related cellular and molecular processes. This includes studies aimed at integrating computational and experimental biological approaches to understanding the underlying mechanisms and processes of cancer initiation and development.

Bioengineering and Biotechnology

Research in this area involves technology development, instrumentation development, bioengineering, nanotechnology, and the use of molecular and cellular imaging.  Some examples include:

  • Developing new technologies focused on biological systems in cancer biology, including nanotechnology
  • Development and early applications of single-cell technologies designed to study cancer processes
  • Synthetic biology and cell engineering, including the design and construction of artificial or man-made biological components and systems designed to study and understand cancer biology
  • Improving understanding of cell and molecular interactions with nanotechnology, particles, surfaces, or materials, as related to cancer biology.
  • Using imaging technologies, including electron and x-ray microscopy, crystallography, immunocytochemistry, and optical and fluorescence microscopy for the cellular and molecular characterization of cancer cells, especially to identify and measure molecular interactions
  • Posted: August 8, 2016

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