The emerging science that studies biological protein materials across scales from nano to macro
Imagine a material that is as strong as steel, yet can heal itself when damaged; a substance that can be both incredibly rigid and surprisingly flexible, all while being produced at room temperature with minimal energy. This isn't science fiction—it's the reality of biological protein materials found throughout nature, from the silk of a spiderweb to the bones in our body.
Biological materials operate across multiple scales simultaneously, with remarkable properties emerging from intricate hierarchical structures.
The power of materiomics can be understood through a musical analogy 1 . Just as diverse music is constructed from the same basic sound waves, biological materials are built from limited molecular building blocks. Function emerges from complex interplay across scales—from molecular notes to macroscopic symphonies.
Materiomics represents a fundamental shift in materials science, defined as "the study of the material properties of natural and synthetic materials by examining fundamental links between processes, structures and properties at multiple scales, from nano to macro" 7 .
This approach acknowledges that you can't truly understand a material by examining only its atomic composition or only its bulk properties.
Hierarchical organization is nature's secret weapon for creating multifunctional materials from limited building blocks.
This architecture enables emergent properties that aren't present in any individual component. Each scale contributes differently to overall material performance.
What makes biological materials so extraordinary is how they integrate multiple, often conflicting properties 7 . Consider:
Investigating osteogenesis imperfecta (brittle bone disease) through a multiscale computational approach 7 .
Began at the nanoscale, modeling how specific point mutations in collagen molecules affect mechanical interactions between individual proteins.
Traced how nanoscale changes propagate upward through hierarchical levels—from altered molecular adhesion to compromised fibril mechanics.
Used computational simulations to visualize stress distribution within collagen fibrils containing mutations compared to healthy tissue.
| Scale Level | Effect of Mutation | Functional Consequence |
|---|---|---|
| Molecular | Weakened intermolecular adhesion | Reduced stiffness at nanoscale |
| Fibrillar | Increased intermolecular spacing | Altered mineral deposition |
| Tissue | Formation of stress concentrations | Reduced strength and toughness |
| Clinical | Compromised structural integrity | Fragile bones, skeletal deformity |
This case study powerfully demonstrates that failure must be understood as a multiscale phenomenon 7 . A single-point mutation at the genetic level manifests as changed chemical properties at the molecular level, which alters nanomechanics, which modifies fibril assembly, and ultimately leads to catastrophic tissue failure.
The materiomics approach revealed that the best-performing materials don't necessarily come from the best individual components . It's their orchestration across scales that determines ultimate performance.
Essential technologies in materiomics that span computational, experimental, and analytical domains.
Multiscale simulation, finite element analysis, and molecular dynamics predict material behavior across scales before experimental validation.
Circular Dichroism (CD) spectroscopy, X-ray crystallography, and NMR determine secondary structure composition and protein folding.
Electron microscopy and atomic force microscopy visualize hierarchical structures from nano to micro scales.
Genetic algorithms, autonomous robotic platforms, and machine learning accelerate discovery of optimal material combinations.
| Discovery Method | Throughput (blends/day) | Key Finding | Performance Advantage |
|---|---|---|---|
| Traditional Approach | Dozens to hundreds | Often focuses on optimizing individual components | Limited by researcher intuition and time |
| Autonomous Platform | Up to 700 | Optimal blends may use underperforming components | Best blend performed 18% better than its best component |
Among structural analysis tools, the BeStSel (Beta Structure Selection) method represents a significant breakthrough 3 . This web server analyzes Circular Dichroism (CD) spectra to determine protein secondary structure with unprecedented detail.
Unlike earlier methods that struggled with β-structure variability, BeStSel distinguishes eight secondary structure components, including parallel β-structure and antiparallel β-sheets with different twist groups 3 . This precision enables researchers to connect subtle structural changes with mechanical performance.
Materiomics represents more than just a new field of study—it offers a new way of seeing the material world. By recognizing that function emerges from the interplay of structures across scales, this approach finally gives us the conceptual framework to understand nature's most sophisticated material designs.
Materiomics could lead to breakthroughs in treating not just osteogenesis imperfecta but countless other diseases rooted in structural failures 7 .
Perhaps most excitingly, materiomics teaches us that excellence often lies not in perfect components but in effective organization. The same principle that allows modest protein building blocks to form extraordinary biological materials might guide us in organizing our technologies, our communities, and our responses to complex challenges. In learning nature's structural language across scales, we may discover better ways to build everything from our bones to our future.
As this field advances, supported by increasingly sophisticated tools and cross-disciplinary collaborations, we're not just becoming better materials scientists—we're learning to speak nature's design language, potentially ushering in a new era of sustainable, adaptive, and intelligent materials.