Application of Amino Acid Analysis in Protein: a Comprehensive Overview

Amino acid compositional analysis stands as a cornerstone methodology across diverse scientific disciplines, including biochemistry, biomedicine, nutritional science, and biopharmaceutical development. By systematically characterizing amino acid composition, sequence architecture, and post-translational modifications, this approach unravels structure-function relationships in proteins while providing critical insights into metabolic regulation and physiological homeostasis. Its applications span fundamental and applied domains: in basic research, it elucidates protein folding dynamics and enzymatic mechanisms; in clinical diagnostics, it identifies biomarkers for inherited and metabolic disorders; in food science, it verifies protein authenticity and nutritional quality; in therapeutic development, it optimizes biologic stability and efficacy; and in industrial biotechnology, it facilitates enzyme engineering for sustainable production processes. These multifaceted applications highlight the technique's pivotal role in driving innovation across health, nutrition, and bioengineering sectors through precision-focused solutions.

NMR spectrum and LC-MS/MS method for amino acid quantification (D'eon JC et al., 2023).

Fundamental research

Protein Structure-Function Elucidation

Amino acid analysis serves as a cornerstone for decoding the relationship between protein architecture and biological activity. The sequence and spatial organization of amino acids dictate protein functionality, with analytical techniques enabling:

• Primary Structure Determination: Sequencing identifies linear amino acid arrangements, forming the basis for predicting secondary (α-helices/β-sheets) and tertiary (3D folding) conformations. For example, by analyzing the spatial distribution and composition pattern of amino acids in the primary structure of SARS-CoV-2 and SARS-CoV virus proteins, combined with Hurst index (quantitative sequence self-similarity) and Shannon entropy (evaluation site variability), this study reveals the three-dimensional conformational differences of key structural proteins (envelope, spike, etc.) under the high similarity of their genomes. Although the sequence homology is high, the amino acid distribution of SARS-CoV-2 significantly enhances the interaction with human host factors, and its structural plasticity (which can not be detected by traditional alignment) is related to the change of virus-host interaction network and pathogenic evolution by integrating Hurst- entropy index analysis. Fourteen conservative and variant regions of protein group were identified, which provided molecular basis for pedigree-specific adaptation of Covid-19 (Rout RK et al., 2022).
• PTM Mapping: Identification of phosphorylation, glycosylation, and other PTMs clarifies their roles in modulating protein activity, stability, and interactions. For example, by comparing the rodent models of O-ZSF1 (hyperglycemia/hypertension/diabetes) and L-ZSF1, this study reveals the metabolic characteristics of heart failure (HFpEF) with preserved ejection fraction: the blood sugar of O-ZSF1 rats is 39% higher than that of the control group, and the decrease of urinary creatinine indicates high renal filtration, and the urine lysine, cysteine and their glycation end products (such as CML and CEL) are significantly increased, reflecting the enhancement of non-enzymatic glycation. Arginine methylation and lysine/cysteine glycosylation modifications (such as Nε- carboxyethyl lysine) are strongly related to HFpEF markers. These urine-detectable modified metabolites may serve as noninvasive biomarkers of vascular oxidative stress and protein homeostasis, providing new targets for early diagnosis and pathological mechanism analysis of HFpEF (Baskal S et al., 2022).

Metabolic Pathway Investigation

Amino acids function as pivotal intermediates in cellular metabolism, with their quantification offering insights into regulatory networks:

• Metabolomic Profiling: Tracking temporal variations in amino acid pools reveals dynamic shifts in pathway flux under physiological or pathological conditions. For example, The amino acid level of HIV patients is generally decreased, which indicates that protein's anabolism is weakened and its gastrointestinal absorption is potential. However, the increase of amino acid metabolism (such as kynurenine, leucine and isoleucine) in patients with tuberculosis reflects the acceleration of protein decomposition and the increase of energy demand, and its pattern is similar to that of diabetes/insulin resistance (such as the decrease of glycine and the increase of branched-chain amino acids). When HIV/TB is co-infected, amino acid metabolism shows mixed characteristics: TB-driven catabolism partially counteracts HIV-related synthetic inhibition, but abnormal uric acid pathway in dogs may aggravate immunosuppression. (Pretorius C et al., 2024).

Amino acid metabolism pathways influenced by infection states (Pretorius C et al., 2024).

Medical diagnosis

Metabolic Disorder Identification

Dysregulation of amino acid metabolism is implicated in various inherited metabolic disorders, advanced metabolomic techniques enable precise diagnostic applications:

• Neonatal Screening: Blood-based amino acid profiling facilitates early detection of hereditary metabolic conditions, allowing prompt intervention in newborns. For example, this study analyzes the metabolic characteristics of 116 children with NICCD (64 cases were diagnosed by screening and 52 cases were missed diagnosis), and develops and optimizes the neonatal screening strategy. Based on the non-derivative MS/MS technique, the ROC curve shows that citrulline (cut-off value is 17.57 μmol/L, AUC=0.970) combined with glycine, phenylalanine, ornithine and C8 acyl carnitine can significantly improve the identification of missed cases (combined AUC=0.996), and the true positive rate of verification set is 91.67%, and the specificity is 96.48%. Studies have confirmed that the combined detection of multiple metabolic markers can effectively improve the sensitivity and specificity of NICCD screening, make up for the limitations of traditional single indicators (such as citrulline ≥30 μmol/L), and provide reliable biochemical basis for optimizing neonatal screening (Wang P et al., 2025).
• Urinary Biomarker Detection: Aberrant amino acid byproducts in urine serve as diagnostic indicators, enhancing the accuracy of metabolic disease confirmation. For example, urine glutamine/glutamic acid affects the proliferation by regulating the glnA gene (encoding glutamine synthetase) of Escherichia coli. Urea regulates the selection of glnA promoter (lack of urea activates glnAp2, while rich urea dominates glnAp1) and inhibits its mRNA translation. High concentrations of amino acids activate transcription and inhibitory amino acids block translation; Ntr cascade intervention at low concentration. Urine composition dynamically regulates bacterial adaptability and provides a new target for the treatment of urinary tract infection (Urs K et al., 2024).

Oncological Applications

Malignant transformations are characterized by altered amino acid utilization, offering diagnostic and therapeutic insights:

• Cancer Biomarkers: Elevated levels of glutamine and serine in tumor microenvironments correlate with malignancy, positioning these metabolites as potential diagnostic markers. For example, breast cancer cells rely on LAT1 and ASCT2 transporters to absorb leucine and glutamine to maintain proliferation. It was found that BenSer, an ASCT2 inhibitor, could double inhibit the activity of LAT1/ASCT2, block the intake of amino acids, significantly reduce the viability of MCF-7, HCC1806 and interfere with the cell cycle. Compared with LAT1 inhibitor BCH, BenSer is more effective, suggesting that it has multiple targets (such as additional inhibition of four amino acid transporters) (van Geldermalsen M et al., 2018).
• Immunogenic Monitoring: Decoding Neoepitope Signatures and MHC-TCR Interactions to Guide Tumor Immunotherapy. For example, amino acid analysis reveals the mechanism of tumor immune escape by analyzing the amino acid motif produced by mutation and its spatial distribution: if the mutant motif is homologous to human or microbial protein, it may activate TCR recognition; On the contrary, rare motifs lack homologous TCR to form immune blind spots. Analyzing the position of mutant residues in MHC binding groove (such as MHC-I position 2/9) can evaluate the degree of epitope exposure, and only 25-30% of mutant sites (such as glioma and lung squamous cell carcinoma) can be effectively identified. Screening mutations with high frequency exposure and TCR homology can guide the design of new antigen vaccine, break through the bottleneck of immune escape and improve the efficiency of targeted therapy (Homan EJ et al., 2023).

Food science

Amino acids, the fundamental components of proteins, serve as critical indicators for assessing the nutritional and functional attributes of food products. Their analysis provides essential insights into dietary value and product integrity, supporting both consumer health and industry standards.

Nutritional Assessment

• Essential Amino Acid Profiling: Quantification of indispensable amino acids (e.g., lysine, methionine) enables evaluation of protein completeness, a key determinant of food nutritional quality. For example, amino acid analysis reveals the functional characteristics of bee pollen and honey by analyzing their differences in amino acid composition: the total amino acid content of bee pollen (≈150 mg/g) is significantly higher than that of honey (≈15 mg/g), and it is rich in nonessential amino acids (such as glycine and GABA), while the proline (Pro) in honey decreases with storage, which can be used as a sign of maturity. The proportion of essential amino acids (such as threonine and phenylalanine) is similar, but the nutritional indexes such as EAAI, BV and PER of certain honey (such as CL3) are better, suggesting its high nutritional value. The deficiency of isoleucine and lysine exposes some nutritional shortcomings of honey (Sommano SR et al., 2020).
• Amino Acid Score (AAS): This metric compares a food's amino acid composition with human physiological requirements, offering a standardized measure of its capacity to meet dietary needs. For example, amino acid analysis reveals the nutritional and functional characteristics of China yellow waxy corn samples by analyzing the differences in amino acid composition: Inner Mongolia sample 1-1 has the highest protein content (40.26 mg/g), and sample 1-2 has the best digestibility. Essential amino acids (such as leucine and glutamic acid) dominate tissue repair and metabolism, while non-essential amino acids (such as glycine and alanine) regulate immunity and protein synthesis, and phenylalanine has antioxidant activity. Principal component analysis (PCA) combined with comprehensive evaluation of spectral data showed that sample 1-2 was the best nutritional variety because of its high bioavailability of essential amino acids, excellent spectral matching and good digestion efficiency (Li Z et al., 2022).

Quality Assurance and Control

• Adulteration Identification: Deviations in amino acid patterns, such as unexpected plant protein signatures in dairy products, help detect fraudulent alterations in food composition. For example, amino acid fingerprint analysis constructs the quantitative amino acid spectrum of skim milk powder (NFDM/SMP) by microwave-assisted hydrolysis and UHPLC-UV technology, and establishes the characteristic distribution threshold of real products by combining statistical models, which can accurately identify adulteration. This method can effectively distinguish protein addition from plant sources (such as peas and soybeans) and animal sources (such as whey and fish glue), with low detection limit and strong specificity (the interference of wheat protein and melamine can be ignored). The verification shows that its accuracy is more than 95%, especially sensitive to the adulteration of arginine and whey. It provides a non-destructive and highly sensitive quality control tool for the dairy industry and helps to supervise compliance and security traceability (Bhandari SD et al., 2022).
• Process Optimization: Monitoring amino acid stability during thermal processing or fermentation ensures minimal nutrient loss, guiding technological refinements for enhanced product quality. For example, the amino acid analysis quantitatively measured the dynamic changes of 17 kinds of amino acids in two fermentation processes (natural fermentation SF vs inoculation fermentation SC) by UHPLC, revealing that adding yeast (Saccharomyces cerevisiae) in SC method can increase the proportion of essential amino acids (63.4% vs 61.8%) and shorten the fermentation period by 3-4 days. At the initial stage of fermentation (0-2 days), the amino acid content is low due to proteolysis, and SC method can quickly accumulate flavor precursors (such as essential amino acids) by accelerating proteolysis, thus improving the flavor and aroma potential of cocoa beans (Balcázar-Zumaeta CR et al., 2024).

Applications in Indaustry Standards

By aligning amino acid profiles with regulatory benchmarks, manufacturers validate label claims (e.g., "high-protein" designations) and ensure compliance with safety protocols. Furthermore, tracking amino acid degradation products aids in identifying unsafe processing conditions or spoilage.

Drug development

Amino Acid Profiling in Pharmacological Innovation

Amino acid characterization serves as a cornerstone in modern drug discovery, offering critical insights into therapeutic target engagement and metabolic fate. This analytical approach facilitates both mechanistic elucidation and safety optimization across drug development pipelines.

Target Identification and Mechanistic Studies

• Peptide-Drug Conjugation: Mechanistic Insights into Receptor-DNA-Enzyme Interactions for Precision Therapeutics. For example, amino acid analysis can guide the accurate design of drug-peptide conjugates by analyzing peptide sequence and functional sites: in the development of receptor antagonists, the key sequences of peptide segments (such as the C-terminal tetrapeptide information region of CCK) and modification sites are defined to optimize the receptor binding ability of benzodiazepine conjugates; In the coupling of anti-tumor drugs, the coupling site of peptide carrier and chemotherapy drugs was determined to verify its DNA targeting binding efficiency; Anti-viral mimetic peptides were screened for highly effective HIV protease inhibitors by structure-activity analysis. This analysis provides a structural basis for drug-peptide interaction optimization, targeted delivery and activity enhancement, and promotes the development of precision therapeutic drugs (Gattu R et al., 2023).

Metabolic Pathway Profiling

• Biotransformation Mapping: the identification of amino acid-derived metabolites reveals the drug treatment route, which is helpful to predict and design drugs. For example, amino acid analysis can guide prodrug design to improve the permeability of biofilm by analyzing the physical and chemical characteristics of drugs (such as lipophilic/hydrophilic imbalance). To solve the problem of poor oral absorption of acyclovir, amino acid or fatty acid ester derivatives were designed to enhance water solubility, and intestinal peptide transporter PEPT1 (such as L- pentyl prodrug 1a) was used to improve absorption efficiency. Ganciclovir (GCV) optimizes corneal/retinal permeability through amino acid coupling. Dipeptide carrier (such as Phe-Gly) was delivered through PEPT1, and the regulation of amino acid side chain modification on drug bioavailability was verified (Vale N et al., 2018).

Industrial biotechnology

Amino acid characterization serves as a pivotal tool in advancing biotechnological processes, driving efficiency in microbial production systems and enabling the design of novel functional materials.

Microbial Production System Enhancement

• Metabolic Pathway Tuning: Monitoring shifts in amino acid profiles during fermentation allows precise adjustment of culture parameters (e.g., pH, nutrient feed) to maximize target compound synthesis. For example, in liquor fermentation, amino acids (such as serine) drive fungal community differentiation in the early stage of fermentation: in group B, zygotic yeast is dominant, and its metabolism is efficient to produce ethanol and flavor substances (isoamyl alcohol, etc.), while in group A, Pichia pastoris dominates amino acid metabolism. Metabolic analysis showed that the difference between the two groups focused on the carbon/amino acid metabolic pathway, and the interaction between group B amino acids and fungi was stronger, which shaped the flavor of wine body by activating yeast metabolism (such as higher alcohol synthesis) (Wei J et al., 2023).
• Enzyme engineering: optimizing amino acid residue network and enhancing industrial biology in noncovalent interactions. For example, it is revealed that the stability of GH10 xylanase in acidic environment (pH 2.0) depends on the surface amino acid network and non-covalent interaction: the key sites are concentrated in the two areas behind the enzyme activity center, and the structural rigidity is maintained through electrostatic repulsion regulation, π-π stacking and ionic bond/hydrogen bond cooperation. The mutation experiment confirmed that the optimization of key residues (such as Xyn10RE) can improve the thermal stability by more than 6 times, reflecting the acid-heat interaction characteristics. Five selected acid-tolerant GH10 xylanases (Xyn10C/RE/TC/BS/PC) have high catalytic activity at 70–90 C, providing key targets for industrial enzymatic design (Xia Y et al., 2024).

Functional Biopolymer Engineering

• Thermal Degradation Dynamics: Mapping Amino Acid Pyrolysis Kinetics and Structural Correlations for Sustainable Biomass Valorization. For example, by analyzing the pyrolysis behavior of 18 kinds of amino acids, it is revealed that their thermal stability is related to their structures: cyclic side chains (such as phenylalanine) and hydrophobic amino acids (such as alanine) are more stable at 160–240 C, and their degradation conforms to the first-order reaction kinetics (activation energy 88.5–137.44 kJ/mol). In pyrolysis, amino acids are preferentially cyclized to diketopiperazine (DKP), and the yield is far beyond the free state. The distribution of bound amino acids (glycine, proline, etc.) in straw aerosol further clarified the nitrogen transformation path. By analyzing the pyrolysis behavior of 18 kinds of amino acids, it is revealed that their thermal stability is related to their structures: cyclic side chains (such as phenylalanine) and hydrophobic amino acids (such as alanine) are more stable at 160–240 C, and their degradation conforms to the first-order reaction kinetics (activation energy 88.5–137.44 kJ/mol). In pyrolysis, amino acids are preferentially cyclized to diketopiperazine (DKP), and the yield is far beyond the free state. The distribution of bound amino acids (glycine, proline, etc.) in straw aerosol further clarified the nitrogen transformation path (Zhu RG et al., 2024).

Environmental sciences

Amino acid profiling has emerged as a versatile bioindicator for environmental pollution monitoring, enabling the quantification of contaminants and evaluation of ecological impacts through metabolic fingerprint analysis. In aquatic ecosystems, amino acid composition analysis provides quantitative insights into water quality degradation, with elevated levels of specific amino acids correlating with organic pollutant loads and microbial activity. For terrestrial environments, soil amino acid alteration patterns serve as sensitive indicators of fertility depletion and contamination, reflecting anthropogenic impacts such as industrial emissions and agricultural runoff.

• Water Quality Assessment: By quantifying free amino acids and peptide hydrolysates, researchers can establish contamination gradients and identify pollution sources affecting aquatic habitats. For example, amino acid analysis revealed that the organic nitrogen (which accounts for 92.53% of the total nitrogen in sediments) was mainly protein amino acids, which was an important source of nitrogen/carbon pollution by quantifying the carbon-nitrogen ratio of total hydrolyzed amino acids (THAAs-C accounted for 14.92% of organic carbon and THAAs-N accounted for 49.59% of organic nitrogen) in sediments. Combined with the degradation index (DI), it is found that the positive DI value (fresh organic matter) of surface sediments in the lower reaches of Ziya River is significantly positively correlated with THAA, indicating that the dynamic amino acid composition reflects the degradation degree of organic matter; high THAA level (such as heavily polluted river) indicates high degradation potential and pollution input (Zhao Y et al., 2016).

If you want to know more about amino acid analysis, please refer to "Amino Acid Analysis: a Comprehensive Overview".

If you want to know more about amino acid analysis methods, please refer to "Amino Acid Analysis Methods".

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