Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its use in biomedical engineering for biopolymer materials has only recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: (A) Computer-aided design (CAD/CAM) utilizes specialized software to design and model biopolymers for various biomedical applications. This technology allows researchers to create precise three-dimensional models of biopolymers, taking into account their chemical, structural, and functional properties. These models can be used to enhance the structure of biopolymers and improve their effectiveness in specific medical applications. (B) Finite element analysis, a computational technique used to analyze and solve problems in engineering and physics. This approach divides the physical domain into small finite elements with simple geometric shapes. This computational technique enables the study and understanding of the mechanical and structural behavior of biopolymers in biomedical environments. (C) Molecular dynamics (MD) simulations involve using advanced computational techniques to study the behavior of biopolymers at the molecular and atomic levels. These simulations are fundamental for better understanding biological processes at the molecular level. Studying the wide-ranging uses of MD simulations in biopolymers involves examining the structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton’s equations of motion for all-atom systems, producing spatial trajectories for each atom. This provides valuable insights into properties such as water absorption on biopolymer surfaces and interactions with solid surfaces, which are crucial for assessing biomaterials. This review provides a comprehensive overview of the various applications of MD simulations in biopolymers. Additionally, it highlights the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.

Bone is a highly organized tissue in which each structural level influences the macroscopic and microscopic mechanical behavior. In particular, the quantity, quality, and distribution of the different bone components, i.e. collagen matrix and hydroxyapatite crystals, are associated with bone strength or fragility. Common spectroscopic techniques used to assess bone composition have resolutions limited to the micrometer range. In this study, our aims were two-fold: i) to develop and validate the AFM-IR methodology for skeletal tissues and ii) to apply the methodology to sheep cancellous bone with the objective to obtain novel findings on the composition and structure of trabecular packets.To develop the methodology, we assessed spatial and temporal reproducibility using a known homogeneous material (polymethylmethacrylate, PMMA). We verified that the major peak positions were similar and not shifted when compared to traditional Fourier Transform Infrared imaging (FTIRI). When AFM-IR was applied to sheep cancellous bone, the mineral-to-matrix ratio increased and the acid phosphate substitution ratio decreased as a function of tissue maturity. The resolution of the technique enabled visualization of different stages of the bone maturation process, particularly newly-formed osteoid prior to mineralization. We also observed alternating patterns of IR parameters in line and imaging measurements, suggesting the apposition of layers of alternating structure and / or composition that were not visible with traditional spectroscopic methods. In conclusion, nanoscale IR spectroscopy demonstrates novel compositional and structural changes within trabecular packets in cancellous bone. Based on these results, AFM-IR is a valuable tool to investigate cancellous bone at the nanoscale and, more generally, to analyze small dynamic areas that are invisible to traditional spectroscopic methods.