Protein engineering in Brazil: a biophysical perspective

Abstract

Protein engineering has become an increasingly interdisciplinary field, integrating molecular biology, structural biology, biophysics, computational modeling, and artificial intelligence to modify protein structure, stability, dynamics, molecular recognition, and catalytic activity. This systematic review examines the historical development and scientific contributions of protein engineering research associated with Brazilian institutions between 1988 and June 2026. A total of 792 peer-reviewed articles were identified in PubMed through eight thematic search strategies covering protein and enzyme engineering, directed evolution, rational and computational design, recombinant protein expression, therapeutic proteins, structural biology, and artificial intelligence-assisted engineering. The reviewed literature reveals a transition from early residue-level mutagenesis and conventional biochemical assays to increasingly integrated experimental and computational approaches. Advances in X-ray crystallography, nuclear magnetic resonance (NMR), circular dichroism (CD), mass spectrometry, small-angle X-ray scattering (SAXS), calorimetry, molecular dynamics, and structural bioinformatics enabled the quantitative investigation of protein folding, stability, conformational landscapes, molecular interactions, and catalytic mechanisms. More recently, machine learning, protein language models, AlphaFold-derived structures, and generative approaches have expanded the capacity to predict mutations and design proteins, peptides, antibodies, and enzymes with predefined properties. Overall, protein engineering in Brazil has evolved into a mature and diverse field with applications in health, infectious diseases, agriculture, biotechnology, bioenergy, biomaterials, environmental remediation, and industrial biocatalysis. The findings indicate that biophysics has moved beyond a predominantly descriptive role and has become central to the design and validation of engineered proteins. Future progress will depend on the convergence of experimental biophysics, multiscale simulations, artificial intelligence, high-throughput validation, and stronger national and international research networks.