Thermostable microbial α-amylases: production, characterization, molecular basis, and industrial applications — a review

1 Introduction

Industrial bioprocessing increasingly relies on biocatalysis to achieve exquisite substrate selectivity, high atom economy, and reduced environmental burdens compared to conventional chemical transformations (Mondal et al., 2022). In starch-processing sectors, endo-acting α-amylases (EC 3.2.1.1) represent the premier biocatalysts responsible for initial liquefaction, random internal bond cleavage, and viscosity reduction of macromolecular glucan polymers (Shukla and Singh, 2023).

Although enzymatic transformations avoid mineral acid corrosion and unwanted toxic degradation byproducts (such as hydroxymethylfurfural), industrial starch conversion remains a thermally demanding operation (Liaqat et al., 2024). Native starch granules require sustained thermal input at 95–105 °C to overcome crystalline hydrogen-bonding networks during gelatinization. Consequently, industrial liquefaction is conducted under severe thermal, hydrodynamic, and mechanical shear regimes, demanding robust biocatalysts (Isabel and Premalatha, 2025; Saha and Mazumdar, 2019) that retain conformational stability under conditions that rapidly denature conventional mesophilic enzymes (e.g., fungal Aspergillus oryzae α-amylase, which denatures rapidly above 50–55 °C) and psychrotolerant variants (which retain high catalytic flexibility at 5–20 °C), recognizing that exact boundaries vary with assay duration and substrate microenvironment (Ahmad et al., 2022). Thermostable microbial α-amylases—predominantly isolated from thermophilic bacteria (e.g., Bacillus licheniformis, Geobacillus stearothermophilus) and hyperthermophilic archaea (e.g., Pyrococcus furiosus)—sustain catalytic activity at 70–100 °C, offering critical bioprocess advantages: accelerated mass transfer, decreased slurry viscosity, reduced cooling and reheating energy costs, and intrinsic protection against microbial contamination without chemical biocides (Adetiloye et al., 2025). Microbial production hosts are overwhelmingly favored over plant or animal tissues due to rapid fermentation kinetics, unconstrained seasonal availability, high secretion titers, and ease of genetic engineering to boost thermal stability.

From an economic perspective, the global industrial enzyme market was valued at approximately USD 6.4 billion in 2022 and is projected to expand at a CAGR of 6.1% to reach USD 10.2 billion by 2030 (Hossain et al., 2024). Carbohydrases constitute the single largest product segment (~45% of total market revenue), within which microbial α-amylases represent a major economic sector valued at approximately USD 2.1 billion in 2022, forecast to surpass USD 3.6 billion by 2030, driven primarily by expanding bioethanol distillation, removal of starch-based pasting adhesives and fiber conditioning in leather processing, viscosity modification in paper manufacturing, textile desizing, detergent formulation, and food processing demands (Ramos Neyra et al., 2026).

Despite extensive literature on amylases, substantial disconnects remain between laboratory characterization practices and industrial operational realities. Specifically, the field lacks an integrated synthesis reconciling thermodynamic stability criteria, structural drivers of calcium independence, and the quantitative trade-offs of bioprocess scale-up. This review addresses three central organizing questions: (1) What sequence, structural, and thermodynamic determinants govern true thermal persistence versus transient thermoactivity in GH13 and related families? (2) How do bioprocess parameters in submerged and solid-state systems quantitatively dictate enzyme titer and downstream recovery economics? and (3) What protein engineering and formulation strategies bridge the gap between idealized bench-scale kinetics and high-dry-solids industrial biocatalysis?

A structured literature search was conducted using Scopus, Web of Science, PubMed, and Google Scholar for studies on microbial α-amylases, with emphasis on thermostability, microbial sources, production, purification, characterization, molecular features, engineering, and industrial applications. Search terms included “thermostable α-amylase,” “microbial α-amylase,” “thermophilic α-amylase,” “amylase production,” “α-amylase purification,” “amylase thermostability,” “α-amylase protein engineering,” and “thermostable amylase and industrial applications.” The search covered 2000-2026, with the final search conducted in (2026). Studies reporting microbial α-amylase production, thermostability, fermentation, purification, characterization, molecular features, engineering, or applications were included, while unrelated, duplicate, or insufficiently documented studies were excluded. Original research articles were prioritized for experimental evidence, whereas reviews were used for background and established concepts. Microorganisms in Table 1 and 2 were selected as representative examples based on the availability of reported thermal characteristics and purification information, respectively. 185 records were identified, 156 remained after duplicate removal, 128 underwent full-text assessment, and 85 studies were finally included in the manuscript.

Table 1. Comparative biochemical and operational profile of representative thermostable microbial α-amylases.

T_opt represents the temperature at which maximum enzyme activity was reported and should not be considered independently as evidence of thermostability. Thermal half-life (t_1/2), residual activity after heat treatment, and other stability measurements provide more direct evidence of thermal stability.

Table 2. Downstream purification strategies and recovery profiles of microbial α-amylases.

2 Operational definition and thermodynamic criteria of thermostability

In industrial enzymology, a rigorous distinction must be established between ‘thermoactivity’ and true ‘thermostability’ (Jaiswal and Jaiswal, 2024). Thermoactivity refers to the instantaneous catalytic reaction rate measured across an ascending temperature gradient, culminating in an apparent temperature optimum (T_opt) during short assay intervals (typically 10–15 min). Because higher temperatures exponentially accelerate catalytic turnover according to the Arrhenius relationship (Ea ≈ 30–50 kJ/mol), an enzyme may display an apparent T_opt of 60–70 °C purely as a transient kinetic phenomenon immediately preceding acute thermal denaturation (Vieille and Zeikus, 2001).

Conversely, thermostability represents the thermodynamic and kinetic resistance of the enzyme’s folded native tertiary structure (N) against irreversible thermal denaturation into an unfolded, inactive state (U) over prolonged operational intervals:

N ⇌ U → I (irreversibly inactivated state).

In this review, an α-amylase is operationally defined as ‘thermostable’ only if it satisfies a dual criterion:

• Optimal catalytic activity at T_opt ≥ 60 °C under standard assay conditions, and
• An operational thermal half-life (t_1/2) of at least 30 min (preferably ≥ 60 min) at or above 60 °C, retaining ≥ 50% residual catalytic activity in the absence of substrate stabilization or exogenous protective additives.

Enzymes are accordingly categorized along an operational thermal continuum:

• Psychrotolerant: T_opt 10–30 °C; rapid inactivation (t_1/2 < 5 min) at >40 °C.
• Mesophilic: T_opt 35–50 °C; stable at 30–45 °C; rapid inactivation (t_1/2 < 10 min) at >55 °C.
• Moderately Thermophilic/Thermotolerant: T_opt 55–65 °C; t_1/2 ≥ 30 min at 60 °C.
• Thermostable: Topt 65–85 °C; t_1/2 ≥ 60 min at 70–80 °C.
• Hyperthermostable: T_opt ≥ 90 °C; t_1/2 ≥ 60 min at ≥ 90 °C (frequently extending beyond 100 °C in hyperthermophilic archaea).

Hyperthermostable enzymes are commonly associated with thermophilic and hyperthermophilic microorganisms and can remain functional at temperatures at which most mesophilic proteins undergo rapid inactivation. Some hyperthermozymes have optimum temperatures exceeding 100 °C, illustrating that high-temperature functionality results from a complex interplay between protein structure, molecular interactions, conformational dynamics and environmental factors rather than from a single stabilizing mechanism (Unsworth et al., 2007).

3 Classification and functional diversity of starch-degrading amylases

Starch-degrading enzymes can be classified using three complementary systems: (i) reaction mechanism and cleavage mode, (ii) sequence- and structure-based CAZy families, and (iii) Enzyme Commission (EC) classification (Figure 1). Endo-acting enzymes cleave internal α-1,4-glucosidic bonds and rapidly reduce starch viscosity, whereas exo-acting enzymes progressively release smaller products from non-reducing chain ends. Debranching enzymes specifically hydrolize α-1,6 branch linkages, while glucosyltransferases catalyze transfer rather than net hydrolysis of glucosyl residues (Soghomonyan et al., 2024).

3.1 CAZy and EC classification

α-Amylase activity is primarily associated with GH13, the major α-amylase family (Shukla and Singh, 2023), and is also reported in GH57 and GH119. GH126 is sometimes included among α-amylase-related families, although unequivocal α-amylase specificity remains insufficiently established. GH13 enzymes generally possess a (β/α)₈ TIM-barrel and a retaining catalytic mechanism, whereas GH57 enzymes contain a modified (β/α)₇ barrel (Park et al., 2018).

Functionally, the major starch-active enzymes include:

• Hydrolases: α-amylase (EC 3.2.1.1), β-amylase (EC 3.2.1.2), glucoamylase (EC 3.2.1.3), pullulanase (EC 3.2.1.41), and isoamylase (EC 3.2.1.68).
• Glucosyltransferases: cyclodextrin glycosyltransferase/CGTase (EC 2.4.1.19) and amylomaltase (EC 2.4.1.25) (Mondal et al., 2022).

Although α-, β-, and glucoamylases occur across different biological groups, their distribution is not uniform. β-Amylases are particularly associated with plants, α-amylases are widespread among animals and microorganisms, and microbial diversity provides the broadest range of thermostable and industrially relevant α-amylases. Thus, biological distribution alone does not define catalytic properties; evolutionary adaptation, protein structure, and ecological niche are critical determinants of enzyme stability and industrial performance.

3.2 α-Amylase (EC 3.2.1.1)

α-Amylase is predominantly an endo-acting α-1,4-glucan hydrolase that randomly cleaves internal α-1,4-glycosidic bonds through a retaining double-displacement mechanism (Roy and Mukherjee, 2013). Classical GH13 α-amylases contain conserved catalytic Asp and Glu residues within the TIM-barrel catalytic domain (Kikani and Singh, 2011). Hydrolysis produces soluble dextrins and maltooligosaccharides, including maltose, maltotriose and higher oligomers (Figure 2), while α-1,6 branch points remain largely intact as α-limit dextrins (Rebholz et al., 2021).

3.3 Calcium dependence and calcium-independent α-amylases

Many classical GH13 α-amylases contain a structural Ca²⁺-binding site, often near the interface of Domains A and B, which can enhance conformational stability and thermal resistance. However, calcium dependence is not universal. Several microbial and extremophilic α-amylases retain activity and stability with little or no requirement for added Ca²⁺, indicating that intrinsic structural features can compensate for reduced metal dependence. Therefore, calcium-independent behavior should be described as a structural and biochemical variation among α-amylases rather than a universal paradox (Ali et al., 2025).

3.4 Other major amylolytic enzymes

β-Amylase and glucoamylase are included here primarily to provide a functional comparison with α-amylase within the broader starch-conversion system.

• β-Amylase (EC 3.2.1.2; GH14) is an exo-acting inverting enzyme that releases β-maltose from non-reducing chain ends and produces β-limit dextrins (Miłek and Lamkiewicz, 2022).
• Glucoamylase (EC 3.2.1.3; GH15) is an exo-acting enzyme that sequentially releases glucose from starch and related α-glucans, hydrolizing α-1,4 bonds and, more slowly, certain α-1,6 linkages. These enzymes complement α-amylase during starch liquefaction and saccharification (Saeed et al., 2021). The term “γ-amylase” has historically been used for glucoamylase but is less consistently used in contemporary enzyme classification and should therefore be avoided or explicitly qualified.

Their complementary catalytic activities have stimulated extensive research into microbial enzyme sources, production strategies, biochemical properties, catalytic mechanisms, and molecular engineering, particularly for the development of thermostable α-amylases.

4 Microbial sources of thermostable α-amylases

While early commercial preparations utilized plant grains (malted barley) or animal tissues, modern industrial biotechnology relies almost exclusively on microbial fermentation, utilizing low-cost agricultural residues (such as wheat bran, cassava bagasse, and fruit peels) as cost-effective carbon feedstocks and isolation matrices rather than biological enzyme producers. This preference is dictated not merely by microbial growth kinetics, but by a multi-factorial economic matrix encompassing volumetric enzyme titer (U/L/h), high extracellular secretion efficiency (>80% partition into broth), reduced batch cycle times, substrate conversion efficiency on agro-industrial residues, and lower contamination risks when operating at thermophilic regimes (El-Sayed et al., 2024). Furthermore, the high genetic plasticity of microorganisms enables significant yield optimization through strain improvement and targeted mutagenesis (Khelil et al., 2022). From an industrial standpoint, microbial platforms can be engineered to produce enzymes with enhanced thermostability. Utilising these enzymes at elevated temperatures offers critical advantages, including reduced risk of contamination and accelerated reaction rates, reducing overall process energy consumption by eliminating the need to cool hot gelatinized starch slurries (95–105 °C) to mesophilic temperatures prior to liquefaction, while simultaneously decreasing mash viscosity and mechanical mixing energy demands (Ali et al., 2025). While Bacillus species (e.g., B. licheniformis, B. stearothermophilus, B. amyloliquefaciens) and actinomycetes (e.g., Streptomyces, Laceyella) dominate commercial production due to their robust secretion systems (Arfah et al., 2024), hyperthermophilic Archaea (e.g., Pyrococcus furiosus, Thermococcus kodakarensis) and thermophilic filamentous fungi (e.g., Thermomyces lanuginosus, Myceliophthora thermophila) represent vital reservoirs of extreme thermostability and raw-starch-degrading capability (Unsworth et al., 2007).

These organisms are favored for their innate ability to secrete large quantities of enzymes directly into their environment, thereby simplifying downstream processing and reducing production costs (Vala et al., 2025). A few microbial sources producing thermostable amylase are highlighted in Table 1.

4.1 Thermophiles: strategies for survival and adaptations

Thermophiles survive high temperatures through multiple structural and molecular adaptations, as no single factor ensures their stability. Because extracellular enzymes function outside the cellular envelope—deprived of intracellular molecular chaperones (e.g., GroEL/ES), compatible solutes, and repair machinery—their thermal persistence must be intrinsically hardwired into their tertiary and quaternary structures. Key adaptations are included in Figure 3.

These combined adaptations enable thermophiles to maintain structural integrity and functional activity under extreme thermal conditions (Ahmad et al., 2022).

5 Starch: the natural substrate of amylases

Starch is a major dietary polysaccharide and an important industrial feedstock for the production of glucose syrups, fructose, maltodextrins, and cyclodextrins, with starch-derived sugars also serving as substrates for ethanol production (Burhanoğlu et al., 2020). Although starch is synthesized by many plants, industrial starch is primarily obtained from maize, cassava (tapioca), potato, and wheat. Its physicochemical and processing properties, including shear and thermal behavior and susceptibility to retrogradation, vary substantially with botanical origin, amylose-to-amylopectin ratio, granular structure, processing history, and chemical or physical modification (Souza and Magalhães, 2010).

Starch consists primarily of two α-glucans: amylose and amylopectin. Amylose is predominantly a linear polymer of α-1,4-linked glucose residues, whereas amylopectin has α-1,4-linked glucan chains interconnected through α-1,6 branch points (Padia et al., 2025). This molecular organization strongly influences starch granule architecture, accessibility, and susceptibility to enzymatic hydrolysis. α-Amylase predominantly hydrolyzes internal α-1,4-glycosidic bonds within amylose and amylopectin chains, whereas α-1,6 branch points generally remain intact.

Starch granules are commonly classified as A-, B-, or C-type according to their X-ray diffraction patterns and associated crystalline packing arrangements, rather than solely according to their botanical source (Figure 4). A-type starch typically exhibits a relatively compact crystalline arrangement and is commonly associated with cereal starches. B-type starch has a more open crystalline organization and is frequently observed in tubers and some high-amylose starches. C-type starch represents a combination of A- and B-type diffraction characteristics within the same granule and is commonly found in several legume starches (Ahmed et al., 2022; Guo et al., 2020; Punia et al., 2020).

Studies indicate that the efficiency of enzymatic hydrolysis of raw and gelatinized starches from corn, potato, rice, and cassava is strongly influenced by structural features such as granule morphology, crystallinity, molecular organization, and substrate accessibility (He and Wei, 2017). During hydrolysis, α-amylase converts starch into dextrins and maltooligosaccharides, with the final product profile depending on the enzyme source and specificity, substrate structure, and reaction conditions. For industrial applications, thermostability, pH tolerance, catalytic efficiency, and substrate specificity are therefore important determinants of enzyme performance (Sharma et al., 2025).

6 Fermentation strategies and bioprocess optimization for amylase production

6.1 Submerged and solid-state fermentation

α-Amylase is commercially produced mainly through submerged fermentation (SmF) and solid-state fermentation (SSF). In SmF, microorganisms are cultivated in a liquid nutrient medium, and extracellular enzymes can be recovered from the fermentation broth. SmF generally allows better monitoring and control of parameters such as pH, temperature, aeration, agitation, and oxygen transfer, although the extent of control and process performance depend on the microorganism, bioreactor configuration, and production scale (Hashemi et al., 2013). However, SmF may require larger process volumes, higher water consumption, and increased energy input for aeration, agitation, and downstream processing.

In contrast, SSF uses moist solid substrates with limited free water, including agricultural residues such as bran and bagasse. It can be particularly suitable for certain microorganisms, especially filamentous fungi and some bacteria, and may enable the use of low-cost agro-industrial substrates while generating less wastewater. However, SSF also presents important limitations, including difficulties in controlling moisture, temperature, pH, aeration, and substrate homogeneity. Heat and mass transfer limitations, localized overheating, and challenges in scaling up and extracting the enzyme from solid matrices may also affect process performance (Figure 5).

Although SSF can provide high product concentrations and, in some cases, improved productivity, higher volumetric productivity should not be considered a universal advantage over SmF. Comparative performance depends on the microorganism, substrate composition, moisture content, fermentation conditions, enzyme extraction efficiency, and the basis used to calculate production volume. Therefore, SmF and SSF should be evaluated using comparable production metrics and according to the requirements of the specific enzyme-production process (Kannan and Kanagaraj, 2019).

6.2 Optimization of fermentation media

Traditional one-factor-at-a-time (OFAT) optimization has historically been used to examine the individual effects of variables such as pH, temperature, carbon and nitrogen sources, and inoculum size while keeping other factors constant (Abdel-Fattah et al., 2013). Although OFAT can provide preliminary information on suitable operating ranges, its application is limited because it cannot evaluate interactions among variables and may therefore overlook factors whose effects depend on the levels of other process variables (Figure 6) table. For this reason, OFAT should primarily be considered an exploratory approach rather than a comprehensive optimization strategy. Previous studies have used OFAT to establish preliminary culture conditions or select suitable substrates before applying statistical designs; however, the extent of improvement varies among microorganisms and production systems (Sachdev et al., 2016; Saha and Mazumdar, 2019; Suthar et al., 2024).

Statistical design approaches provide a more systematic framework for fermentation optimization. Plackett–Burman Design (PBD) is commonly used as an initial screening tool to evaluate the main effects of a large number of variables with a relatively limited number of experimental trials (Ojha et al. 2020). However, PBD primarily estimates main effects, and interactions between variables may be confounded with these effects. Therefore, significant factors identified through PBD should be interpreted cautiously, particularly when strong interactions are expected (Saeed et al., 2021).

Following factor screening, Response Surface Methodology (RSM) can be used to investigate interaction effects and optimize the levels of selected variables. Designs such as the Central Composite Design (CCD) allow the development of second-order polynomial models describing linear, quadratic, and interaction effects on enzyme production. However, the sequence of OFAT, PBD, and RSM is not universally required; the most appropriate strategy depends on the number of variables, prior knowledge of the process, and the likelihood of significant interactions. Accordingly, PBD followed by RSM represents a commonly used and systematic approach, while other factorial or screening designs may be more appropriate in specific production systems (Rafanomezantsoa et al., 2023).

7 Activity assays, purification, and biochemical characterization of α-amylase

7.1 Methods for determination of α-amylase activity

Several methods are available for determining α-amylase activity, including the iodine–starch, DNS, dextrinizing, and Nelson–Somogyi assays. These methods differ in their analytical principles and, consequently, in their suitability for specific enzyme preparations and experimental objectives. Assay conditions, including substrate concentration, temperature, incubation time, and pH, should be optimized for the enzyme under investigation rather than treated as universally applicable.

The iodine–starch assay is based on the loss of color resulting from the hydrolysis of intact starch. Iodine forms a blue-colored complex primarily with longer starch chains, and enzymatic hydrolysis reduces this color intensity as starch is converted into shorter dextrins. This method is rapid and useful for monitoring starch disappearance or screening amylolytic activity; however, it does not directly quantify reducing sugars and may be influenced by starch type, chain length, and the composition of hydrolysis products (Gupta et al., 2003).

The DNS assay estimates reducing sugars released during starch hydrolysis. Following incubation of the enzyme with the substrate under enzyme-specific assay conditions, the DNS reagent is added to terminate the reaction and develop a colored product that is measured spectrophotometrically, commonly at 540 nm (Sundarram and Murthy, 2014). This method was first standardized by Lorenz Miller (1959) and is widely used because of its simplicity and sensitivity, but it measures total reducing sugars and therefore does not distinguish among glucose, maltose, and other reducing oligosaccharides. In addition, the assay may be affected by interfering reducing compounds present in crude enzyme preparations.

The dextrinizing activity assay measures the reduction in iodine-binding capacity of residual starch following enzymatic hydrolysis. The enzyme–substrate reaction is performed under conditions appropriate for the enzyme being studied, followed by the addition of iodine and spectrophotometric measurement of residual starch, commonly around 600 nm (Siva Sakthi et al., 2012). Incubation temperature and duration are therefore enzyme-specific, particularly for thermostable α-amylases, and should not be generalized across different preparations. This method is useful for assessing endo-acting starch depolymerization but, like the iodine–starch assay, does not directly determine the amount or identity of released hydrolysis products.

The Nelson–Somogyi method quantifies reducing sugars released during starch hydrolysis through the reduction of copper ions followed by color development with Nelson’s arsenomolybdate reagent (McCleary and McGeough, 2015). It can provide sensitive estimation of reducing sugar formation and is useful when comparing hydrolytic activity. However, the method is relatively time-consuming, involves multiple reaction and heating steps, and may be affected by other reducing substances in complex samples. The use of arsenomolybdate reagent also limits its convenience compared with simpler colorimetric methods.

Overall, no single assay provides a complete measure of α-amylase performance. Iodine-based and dextrinizing assays primarily reflect starch depolymerization, whereas DNS and Nelson–Somogyi assays measure reducing sugar formation. Therefore, assay selection should depend on the analytical objective, enzyme characteristics, substrate, and sample composition, and direct comparison of activity values obtained using different assay methods should be made cautiously.

7.2 Purification of α-amylase

Purification of α-amylase is an important downstream processing step that should balance the required enzyme quality with recovery yield, scalability, and process cost. Following fermentation, extracellular α-amylases are commonly recovered from the culture broth by removing cells and insoluble material through centrifugation or filtration (Finore et al., 2011). The degree of purification required depends on the intended application. Crude or partially purified preparations may be suitable for certain bulk applications; however, applications such as food processing and detergents may require greater batch-to-batch consistency and appropriate control or removal of unwanted proteases, pigments, odor-producing compounds, microbial contaminants, and other impurities. Therefore, the target purity should be defined according to application-specific quality and safety requirements (Pandey et al., 2000).

Purification strategies exploit differences in protein solubility, molecular size, charge, and hydrophobicity. Ammonium sulphate precipitation is commonly used for initial concentration and partial purification, followed by dialysis or other desalting methods to remove salts and low-molecular-weight impurities (Sudan et al., 2018). Further purification may involve ion-exchange, size-exclusion, hydrophobic interaction, or affinity chromatography. Ion-exchange chromatography separates proteins based on their net charge and includes cation-exchange and anion-exchange chromatography. Cation exchangers bind positively charged proteins, whereas anion exchangers bind negatively charged proteins. The choice depends on the enzyme’s isoelectric point and buffer pH, and bound proteins are typically eluted by changing salt concentration or pH. Membrane-based methods, aqueous two-phase systems, and other selective separation approaches may also be used depending on the physicochemical properties of the enzyme and the required product specifications (Gopinath et al., 2017; Vyas et al., 2019).

Importantly, higher purification does not necessarily indicate a more efficient downstream process. Each additional purification step may increase purification fold and specific activity but can also result in enzyme or activity losses, longer processing time, and increased operational costs (Arfah et al., 2024). High-resolution chromatographic methods are particularly useful for biochemical and structural characterization but may be less economical for large-scale bulk enzyme production. In contrast, precipitation and membrane-based approaches generally involve fewer processing steps and may offer better scalability, although with lower final purity. Therefore, purification strategies should be evaluated comparatively using purification fold, recovery yield, specific activity, enzyme stability, processing cost, scalability, and application-specific purity requirements, rather than purification fold alone (Alonazi et al., 2021).

Recent downstream-processing approaches aim to minimize the number of unit operations while maintaining adequate enzyme recovery and quality. Automated and programmable purification systems can improve process reproducibility and control; however, their cost-effectiveness depends on the production scale and intended application (Paul et al., 2015). SDS-PAGE is commonly used to provide an approximate assessment of protein purity and molecular mass. However, the presence of a single visible band does not confirm absolute enzyme homogeneity or protein identity. Additional analytical approaches may be required when definitive confirmation of enzyme identity or homogeneity is necessary (Abdulaal, 2018).

Overall, the most appropriate purification strategy is not necessarily the one that achieves the highest purity, but rather the one that provides an optimal balance between enzyme quality, recovery, stability, scalability, and cost. The purification strategies and recovery profiles reported for different microbial α-amylases are comparatively summarized in Table 2, while the general downstream purification workflow is illustrated in Figure 7.

7.3 Biochemical characterization of α-amylase

Characterization of α-amylase is a crucial step to evaluate its suitability for industrial and biotechnological applications. It primarily involves assessing the biochemical properties of the enzyme, catalytic efficiency, and stability under various conditions (Soy et al., 2021). Key characterization parameters include optimum temperature and thermal stability, as thermophilic amylases typically exhibit activity over a broad temperature range (approximately 45-90 °C), making them suitable for high-temperature industrial processes (Figure 8). Similarly, optimal pH and pH stability are determined, with most bacterial amylases showing activity under neutral to alkaline conditions, whereas fungal amylases often prefer slightly acidic pH ranges (Shukla and Singh, 2015a).

Further characterization involves studying the effect of metal ions, inhibitors, and chelating agents, as α-amylase is a calcium metalloenzyme and its activity and stability are often influenced by ions such as Ca²⁺, Na⁺, and other cofactors. The substrate specificity of the enzyme is also evaluated using various starch sources and polysaccharides to determine its catalytic preferences. In addition, enzyme kinetics, including Km and Vmax, are determined to understand substrate affinity and catalytic efficiency. These parameters are preferably estimated by fitting the experimental data directly to the non-linear Michaelis–Menten equation. Although Lineweaver–Burk plots may be useful for graphical visualization, their linear transformation can disproportionately weight measurements obtained at low substrate concentrations and amplify experimental errors, potentially biasing estimates of kinetic parameters.These parameters are typically calculated using Michaelis-Menten and Lineweaver-Burk plots (Sharma et al., 2025).

Enzyme activity during characterization is commonly measured using the dinitrosalicylic acid (DNS) assay, which quantifies reducing sugars released during starch hydrolysis. Advanced characterization may include analysis of thermodynamic stability, structural features, and molecular weight determination using techniques such as SDS-PAGE and protein modeling. Additionally, modern approaches such as enzyme immobilization and protein engineering can be used to improve enzyme stability, reusability, and catalytic performance, whereas metagenomics facilitates the discovery of novel amylase genes and the identification of previously uncultured microbial sources with potentially desirable catalytic and stability properties (Mondal et al., 2022).

Overall, comprehensive enzyme characterization provides essential insights into enzyme behavior under process conditions and guides the selection or engineering of amylases for efficient industrial applications.

8 Molecular engineering and structural basis of thermostability

8.1 Engineered microbial α-amylases with enhanced thermostability

Industrial processes often operate under harsh conditions, such as elevated temperatures, extreme pH, and oxidative environments, requiring robust, stable enzymes. Consequently, key properties including thermostability, pH tolerance, substrate and product specificity, and resistance to oxidative stress are highly desirable for industrial applications (Mondal et al., 2022). As enzymes of significant industrial importance, α-amylases have been extensively investigated with respect to their classification, amino acid sequences, and structural characteristics (Witasari et al., 2025). This comprehensive understanding has enabled the development of both native and recombinant α-amylases with improved functional properties. Through various protein engineering and molecular modification approaches, researchers have successfully enhanced enzyme stability and performance, thereby expanding their applicability across diverse industrial processes (Lim and Oslan, 2021).

Recombinant DNA technology has been extensively utilised to enhance α-amylase production by selecting and expressing efficient amylase-encoding genes. In this approach, the gene of interest is cloned into a suitable expression vector and introduced into a host microorganism, typically a bacterial system, to achieve high levels of recombinant mRNA expression and enzyme overproduction (Farooq et al., 2021).

A highly thermostable amylase gene derived from Pyrococcus sp., which exhibits approximately 40% sequence similarity to previously reported amylases, has been successfully cloned and expressed in Escherichia coli. Similarly, a novel thermostable amylase gene from Bacillus licheniformis NH1 was heterologously expressed in E. coli BL21, producing a recombinant enzyme that demonstrated notable stability under surfactant, chelating agent, and oxidizing conditions (Kikani and Singh, 2022).

The cloning and heterologous expression of thermostable α-amylase genes from thermophilic bacteria into Escherichia coli BL21 (DE3) have been widely reported. For instance, the maltogenic α-amylase gene (AmyYSP) from Bacillus stercoris YSP18 exhibited calcium independence, high substrate affinity, remarkable thermostability, and acid tolerance (Sharma et al., 2025). Similarly, the α-amylase gene (AmyK2) from Bacillus subtilis k2cm was successfully expressed in E. coli, producing a Ca²⁺-independent enzyme with significant thermal stability. Furthermore, immobilization of the purified enzyme on coconut coir enhanced its operational stability and reusability (Mondal et al., 2024).

8.2 Structural characteristics of amylases

The CAZy (Carbohydrate-Active Enzymes) database, established in 1998, provides an online, regularly updated classification of enzymes based on sequence, structure, and functional specificity in carbohydrate synthesis, modification, and degradation. It categorizes enzymes into five major groups: glycosyl hydrolases (GHs), glycosyl transferases (GTs), polysaccharide lyases (PLs), carbohydrate esterases (CEs), and auxiliary activities (AAs), which include redox enzymes (Cantarel et al., 2009).

Among 189 glycoside hydrolase families, four are associated with α-amylases: GH13 (largest and most abundant with a (β/α)₈ barrel), GH57 ((β/α)₇ barrel), GH119 (related to GH57), and GH126 ((α/α)₆ barrel). GH13, GH57, and GH119 follow an α-retaining double-displacement mechanism involving aspartate and glutamate residues, whereas GH126 follows an inverting single-displacement mechanism (Van Der Maarel et al., 2002).

The GH13 family is highly diverse, comprising numerous subfamilies. In addition to intrinsic structural factors, Ca²⁺ plays a crucial role in enhancing the thermal stability of α-amylases by promoting proper folding and increasing resistance to thermal denaturation. The binding of Ca²⁺ ions raises the energy barrier to protein unfolding and contributes to structural rigidity, partly by stabilizing hydrophobic interactions. Structural studies have revealed multiple Ca²⁺-binding sites in α-amylases, often associated with improved stability. However, variations exist, as some amylases remain calcium-independent despite possessing conserved structural domains (Kikani and Singh, 2022).

Advances in protein engineering, particularly structure-based approaches, have improved enzyme properties such as thermostability. Strategies such as loop modification and targeted mutations have successfully enhanced the stability of bacterial α-amylases, improved their industrial efficiency, and reduced process costs (Yang et al., 2013). In family GH13, α-amylases have 4–7 conserved sequence regions (CSRs) that are mostly located on the β-strands of the (β/α)8-barrel catalytic domain. These CSRs include the catalytic triad: an aspartic acid (nucleophile), a glutamic acid (proton donor), and another aspartic acid (transition-state stabilizer) (Møller and Svensson, 2016).

8.3 Structural features and mechanism of action of α-amylase

α-Amylase is a single polypeptide enzyme organized into three distinct domains:

• Domain A: The catalytic core, characterized by an N-terminal (β/α)₈ or TIM barrel structure, consisting of eight β-strands surrounded by eight α-helices.
• Domain B: A β-rich region forming part of the substrate-binding cleft, contributing to variations in size, structure, and substrate specificity among α-amylases.
• Domain C: The C-terminal domain, primarily involved in structural stability.

In some maltogenic amylases, an additional Domain D is present after the C-domain, although its exact function is not yet clearly understood (Figure 9). The catalytic triad is specifically found on strand β4 (Asp), β5 (Glu), and β7 (Asp) of the barrel. These residues are highly conserved and are essential for the catalytic activity of the enzyme (Janeček and Blesák, 2011).

9 Industrial and biomedical applications of amylases

Amylase has wide-ranging applications across industries such as paper, detergents, biofuels, textiles, confectionery, bakery, and pharmaceuticals, utilizing both native and engineered forms. Depending on process requirements, both ambient-active and thermostable amylases are employed. Figure 10 highlights key applications of amylase.

9.1 Food industry

Amylases are widely recognized as key industrial enzymes with extensive applications in the food industry, primarily due to their ability to hydrolize starch into simpler sugars such as glucose, maltose, and dextrins (Farooq et al., 2021). Their importance has increased significantly in recent years, driven by growing demand for processed foods and beverages, as well as for sustainable production processes. The global expansion of the food sector, particularly in bakery and ready-to-drink beverages, has further accelerated demand for microbial amylases, which are preferred for their high catalytic efficiency and cost-effectiveness. These enzymes not only enhance food quality and digestibility but also play a critical role in improving process efficiency across various food applications (Samanta, 2022).

9.1.1 Baking industry

In the baking industry, amylases play a crucial role as flour improvers by catalysing the hydrolysis of starch into fermentable sugars, thereby enhancing yeast metabolism during dough fermentation. This enzymatic activity promotes efficient gas production, resulting in increased loaf volume, improved crumb structure, and a desirable crust color. Furthermore, amylases contribute significantly to the retardation of bread staling by limiting starch retrogradation, thereby extending the shelf life of bakery products (Sundarram and Murthy, 2014). The incorporation of thermostable amylases ensures sustained enzymatic activity even under high-temperature baking conditions, improving process consistency and product quality. With the continued growth of the global bakery sector, the use of amylases has expanded significantly, underscoring their importance in modern baking technology (Rebholz et al., 2021).

9.1.2 Brewing and fermentation industry

Amylases play a pivotal role in both brewing and baking industries due to their ability to convert starch into fermentable sugars. In brewing and fermentation processes, these enzymes facilitate the breakdown of cereal starch during mashing, where α-amylase hydrolyzes starch into dextrins, and β-amylase further converts these intermediates into maltose. These sugars serve as essential substrates for yeast fermentation, leading to alcohol production. Efficient enzymatic activity is therefore crucial for enhancing fermentation efficiency, increasing alcohol yield, and improving flavor development in beverages (Ramos Neyra et al., 2026).

9.1.3 Starch processing and sweetener production

One of the most significant applications of amylases in the food industry is starch processing to produce sweeteners such as glucose syrup, maltose syrup, and high-fructose corn syrup. This process relies on enzymatic hydrolysis of starch, beginning with liquefaction by α-amylase, which breaks down starch into dextrins, followed by saccharification using glucoamylase to produce glucose (Vala et al., 2025). The inclusion of debranching enzymes, such as pullulanase, further enhances hydrolysis efficiency by cleaving α-1,6 glycosidic linkages, thereby ensuring a more complete conversion of starch. Compared to conventional chemical methods, this enzymatic approach offers greater specificity, improved energy efficiency, and enhanced environmental sustainability. The sweeteners produced through this process are widely utilised in beverages, confectionery, and various processed foods, underscoring the critical importance of amylases in modern food processing industries (Ashok et al., 2024).

9.1.4 Confectionery industry

In the confectionery industry, amylases are widely used to regulate key product attributes, such as sweetness, viscosity, and texture, through controlled hydrolysis of starch. This enzymatic process facilitates the production of sugars and syrups with specific functional properties required for various confectionery formulations. These applications demonstrate that amylases are not only essential for basic starch conversion but also contribute significantly to the development of value-added functional ingredients in modern confectionery products (Liu et al., 2026).

9.1.5 Fruit juice processing

Amylases are widely used in fruit juice processing to hydrolize residual starch, which can contribute to turbidity and increased viscosity, thereby improving product clarity and quality. The enzymatic degradation of starch enhances filtration efficiency, improves product stability, and produces a clearer, more visually appealing juice, ultimately improving consumer acceptance (Hossain et al., 2024). Thermostable α-amylases may offer an advantage when starch hydrolysis is integrated with elevated-temperature processing or when the enzyme is required to tolerate temperature fluctuations during processing. Their higher thermal stability can reduce the need for strict temperature control and may allow enzymatic treatment to be performed at temperatures that improve substrate solubility and reduce viscosity. However, the practical benefit of thermostability depends on the specific juice matrix and processing conditions, including temperature, pH, residence time, and the sequence of enzymatic and thermal treatments.

9.1.6 Infant and weaning foods

Amylases are widely used in the preparation of infant and weaning foods, particularly in cereal-based formulations, where they play a crucial role in reducing viscosity through enzymatic hydrolysis of starch (Chakravarthi and Kapoor, 2003). This reduction in viscosity allows the preparation of semi-solid foods that are easier for infants to consume and digest, without the need for excessive dilution. Importantly, this process helps maintain high nutritional and energy density, ensuring that the caloric value of the food is preserved. Such applications are particularly significant in the development of nutrient-rich formulations to address infant nutrition and malnutrition challenges (Gopaldas et al., 1988). Overall, the incorporation of amylases enhances both the functional and nutritional quality of weaning foods, making them more suitable for infant feeding.

9.1.7 Processed and functional foods

The application of amylases in processed and ready-to-eat foods has increased substantially in response to the growing demand for convenience foods. These enzymes play a vital role in modifying starch properties, thereby improving texture, consistency, and overall product stability across a wide range of food products, including soups, sauces, and beverages (Devi et al., 2025). Beyond their conventional role in starch hydrolysis, amylases are increasingly utilised in the production of functional food ingredients. Through controlled enzymatic processes, they can facilitate the formation of modified starch products and oligosaccharides, including isomaltooligosaccharides, cyclodextrins, and resistant starch. Some of these products may have potential prebiotic or other gut-related functional effects; however, these effects depend on their specific molecular structure, degree of polymerization, dosage, selective utilisation by the gut microbiota, and supporting evidence of a health benefit. Therefore, the formation of these products alone does not establish a prebiotic or gut-health effect, which requires appropriate biological and, where relevant, clinical evidence. These developments highlight the expanding role of amylases from traditional processing aids to biocatalysts for developing novel functional food ingredients (Liu et al., 2026).

9.2 Detergent industry

Amylases are essential enzymes in the detergent industry, widely used to effectively remove starch-based stains from fabrics. Starch residues from food sources such as sauces, gravies, and processed products are often resistant to conventional detergents; however, amylases hydrolize these complex polysaccharides into smaller, water-soluble sugars, thereby enhancing stain removal efficiency (Roy et al., 2012). The performance of amylases in detergent formulations largely depends on their stability and activity under harsh washing conditions, including alkaline pH, elevated temperatures, and the presence of surfactants and other chemical additives. Evaluation of washing efficiency has shown that incorporating amylases into commercial detergents significantly improves cleaning performance compared with detergents alone (Shukla and Singh, 2023). This enhancement is attributed to the synergistic interaction between enzymes and detergent components, where amylases degrade starch stains, facilitating their subsequent removal by surfactants.

In recent years, considerable attention has been directed toward alkaliphilic and detergent-compatible α-amylases because they can retain activity under the alkaline conditions and in the presence of surfactants and other detergent components. Thermostable amylases are particularly advantageous in formulations or cleaning processes involving elevated temperatures, whereas efficient low-temperature washing requires enzymes with sufficient catalytic activity and stability at low or moderate temperatures. Therefore, enzymes exhibiting broad temperature tolerance may offer greater flexibility across different washing conditions. The use of suitable detergent enzymes can improve the removal of starch-based stains under milder washing conditions and may contribute to reduced energy consumption when effective cleaning is achieved at lower temperatures. Additionally, enzymatic detergents may reduce reliance on some harsh chemical components and contribute to more sustainable cleaning formulations, although their environmental benefit depends on the overall detergent composition and life-cycle performance (Chandrasekar et al., 2024).

9.3 Fuel alcohol (bioethanol) industry

Ethanol is a widely used biofuel, with starch serving as a major substrate due to its abundance and low cost. Its conversion involves liquefaction by α-amylase to produce dextrins, followed by saccharification into fermentable sugars, which are then converted into ethanol by microorganisms such as Saccharomyces cerevisiae (Ashok et al., 2024). This process is industrially significant, particularly in countries like Brazil. Advances such as protoplast fusion between Saccharomyces fibuligera and S. cerevisiae have enabled direct starch-to-ethanol conversion, eliminating the need for separate saccharification. Additionally, bacteria such as Bacillus licheniformis and engineered strains of E. coli and Bacillus subtilis contribute to efficient starch hydrolysis through amylase production, thereby enhancing overall process efficiency (Ali et al., 2025).

9.4 Textile industry

Amylases are widely used in the textile industry for desizing, a process that removes starch-based sizing agents applied to yarn during weaving. Starch is commonly used due to its low cost, availability, and ease of removal. During finishing, α-amylases selectively hydrolize starch without damaging fabric fibers, thereby improving fabric quality and preventing thread breakage. Amylases, particularly from Bacillus species, have long been employed for efficient desizing processes (Arfah et al., 2024).

9.5 Paper industry

In the pulp and paper industry, α-amylases are used to modify starch during paper coating and sizing processes. Native starch often has high viscosity, which can limit its handling and application; controlled enzymatic hydrolysis reduces viscosity while retaining sufficient film-forming properties for paper processing. This modification can improve coating uniformity and paper surface properties, while starch-based sizing contributes to paper strength and durability (Jaiswal and Jaiswal, 2024).

Although some paper-sizing operations are performed at moderate temperatures (approximately 45–60 °C), thermostable α-amylases can offer additional process flexibility where starch preparation, hydrolysis, or continuous processing involves elevated or fluctuating temperatures. Their improved thermal stability may allow enzymatic viscosity reduction to be integrated with hot starch-processing steps and can reduce the risk of rapid enzyme inactivation during temperature variations. However, because paper-processing conditions vary among processes, the advantage of thermostable amylases depends on the actual operating temperature, residence time, starch characteristics, and required degree of hydrolysis. Thus, enzyme selection should be based on process-specific requirements rather than assuming that either mesophilic or thermostable α-amylases are universally preferable.

9.6 Clinical and medicinal applications

With advancements in biotechnology, the applications of amylases have expanded into clinical and medicinal fields. Historically, amylases were among the first enzymes used therapeutically, with fungal amylase introduced as early as 1894 for the treatment of digestive disorders. In modern pharmaceutical research, starch-based biodegradable polymers are widely explored for controlled drug delivery due to their biocompatibility. Amylases play a significant role in this area by regulating drug release from starch-based hydrogels and cross-linked amylose systems, enabling controlled and targeted delivery (Gupta et al., 2003).

Additionally, amylases are indirectly involved in therapeutic strategies through the identification of amylase inhibitors, which can reduce starch digestion and absorption, thereby contributing to the management of conditions such as obesity. Furthermore, amylases are utilised in diagnostic and analytical applications, including the development of biosensors and methods for detecting oligosaccharides. These diverse applications (Table 3) highlight the expanding role of amylases in modern medicine and pharmaceutical sciences (Far et al., 2020).

Table 3. Commercially available α-amylases and their major applications.

10 Discussion: controversies, research gaps, and future perspectives

10.1 Divergent views on optimization and screening strategies

A key concern in the amylase literature is not simply the choice between OFAT and statistical optimization, but the comparability and reliability of optimization outcomes generated using different experimental strategies. Studies based on OFAT may identify favorable conditions within a limited experimental range but can overlook interaction-dependent effects, whereas statistically designed approaches can evaluate multiple variables simultaneously and provide information on interaction and quadratic effects. Consequently, reported improvements in α-amylase production should be interpreted in the context of the experimental design, response metric, and validation of the predicted optimum rather than by comparing reported yields alone. As discussed in Section 5.2, statistical screening and optimization designs provide a more systematic basis for multivariable optimization; however, their effectiveness also depends on appropriate factor selection, model adequacy, and independent experimental validation of the predicted conditions. Thus, the apparent superiority of one optimization strategy should be assessed critically according to the objectives and complexity of the fermentation system rather than treated as universally applicable (Rafanomezantsoa et al., 2023; Rao et al., 2013; Saeed et al., 2021).

Similarly, opinions differ on whether crude or partially purified amylase preparations are sufficient for industrial use: for bulk applications such as detergents and starch liquefaction, many authors consider crude extracts adequate and more cost-effective, while others emphasize that extensive purification and characterization remain indispensable whenever reproducibility, specificity, or regulatory compliance (e.g., pharmaceutical or diagnostic use) is required (Sudan et al., 2018).

10.2 Calcium dependence and structure–stability relationships

Another area of ongoing debate concerns the structural basis of thermostability. Calcium ions are widely reported to stabilise the (β/α)₈ barrel of GH13 α-amylases by raising the energy barrier to unfolding (Kikani and Singh, 2022), yet several thermostable and industrially important amylases have been shown to be fully calcium-independent despite possessing the conserved calcium-binding architecture (Kikani and Singh, 2011, Kikani and Singh, 2012; Mondal et al., 2024). This apparent contradiction indicates that thermostability in this enzyme family is not governed by a single universal mechanism, but instead arises from a combination of factors — ionic and hydrophobic interactions, disulphide bridges, compact hydrophobic cores, and reduced surface loop flexibility — whose relative contribution varies across taxa and even across strains within the same species. Determining which of these factors dominate in a given amylase remains an open question in structural biology with direct implications for rational protein engineering.

10.3 Current research gaps

Despite decades of investigation, several gaps constrain the translation of thermostable microbial amylases from laboratory discovery to industrial deployment.

• Limited industrial-grade strains. Although a large number of amylase-producing microorganisms have been isolated and characterized, only a small subset combines high yield, thermostability, broad pH tolerance, and genetic tractability sufficient for large-scale production (Vala et al., 2025).
• Cost of downstream processing. Purification remains the most expensive stage of enzyme manufacture, and while modern approaches (aqueous two-phase systems, integrated biorefinery-style processing) aim to reduce the number of steps, a generalizable, low-cost purification platform applicable across amylase sources has not yet emerged (Sudan et al., 2018).
• Under-characterised extremophile diversity. Many thermophiles, halophiles, and psychrophiles capable of amylase production remain difficult to culture under laboratory conditions, restricting access to potentially valuable amylases and biasing the literature toward a relatively narrow set of readily culturable Bacillus and Geobacillus species (El-Sayed et al., 2024).
• Incomplete structure–function datasets. For several reported thermostable amylases, biochemical characterization (thermostability, kinetics) is available without matching structural or genomic data, limiting mechanistic interpretation and engineering efforts.
• Substrate-specific inconsistency. Because assay conditions (temperature, substrate source, raw versus gelatinized starch) vary considerably between studies, comparing reported activities and stabilities across the literature is difficult, complicating the identification of genuinely superior candidate enzymes (Sharma et al., 2025).

10.4 Future perspectives

Amylases remain among the most important industrial enzymes; however, despite extensive research and the identification of numerous microbial sources, only a limited number of strains meet industrial requirements. This has led to a continuous search for novel microorganisms capable of producing efficient and robust amylases suitable for large-scale applications. Beyond their established roles in food, detergent, and starch industries, amylases are increasingly used in sectors such as textile, paper and pulp, and biofuel production. In particular, the growing demand for sustainable energy has heightened interest in bioethanol production from starch-rich biomass, necessitating the development of efficient amylases that digest raw starch.

With the global shift toward environmentally sustainable processes, enzyme-based technologies are increasingly replacing conventional chemical methods due to their eco-friendliness and reduced energy and water consumption. However, successful industrial application requires cost-effective large-scale production and a deeper understanding of enzyme structure--function relationships to enhance stability and performance under harsh conditions. Despite significant advancements, gaps remain in optimising amylase properties for diverse industrial needs.

Future research is therefore focused on exploring microbial diversity, particularly extremophiles from unique environments, as potential sources of novel amylases with enhanced stability and functionality. Since many extremophiles are difficult to culture, modern approaches such as enzyme engineering, recombinant DNA technology, and heterologous expression in mesophilic hosts are being employed to harness their potential. Current efforts also emphasize the development of thermo-tolerant and pH-stable amylases, as well as cost optimization and genetic modifications to achieve desired industrial traits. Overall, amylases are expected to expand into emerging areas such as biopharmaceuticals, further broadening their industrial and scientific significance.

Looking forward, three directions appear particularly likely to shape the field. First, bioprospecting in underexplored extreme environments — geothermal springs, deep-sea vents, saline lakes, and cold deserts — combined with culture-independent (metagenomic) approaches, is expected to expand the catalog of naturally thermostable and multi-stress-tolerant amylases beyond the well-studied Bacillus/Geobacillus groups. Second, structure-guided and computational protein engineering (rational mutagenesis, directed evolution, and increasingly, machine-learning-assisted structure prediction) is likely to accelerate the design of amylases with tailored thermostability, pH optima, and product specificity, reducing reliance on trial-and-error screening. Third, integration of amylase production into circular-economy and biorefinery frameworks — using agro-industrial residues as fermentation feedstocks and coupling enzyme production with downstream valorization streams — is expected to improve the economic viability of thermostable amylases for large-scale, sustainable industrial use, including emerging biopharmaceutical and biosensor applications.

11 Conclusion

Thermostable microbial α-amylases occupy a central position among industrial enzymes because of their capacity to combine high catalytic efficiency with functional stability under the elevated temperatures, extreme pH values, and chemically demanding conditions typical of large-scale bioprocessing. This review has traced the classification and mechanism of amylolytic enzymes, the microbial and environmental sources from which thermostable variants are recovered, the fermentation and optimization strategies used to enhance their yield, the assays and downstream techniques used for their purification and characterization, the structural and molecular determinants of their thermostability, and the breadth of their application across the food, detergent, biofuel, textile, paper, and biomedical sectors. Taken together, the evidence indicates that while substantial progress has been made in isolating and engineering robust amylases, the field remains constrained by inconsistent characterization practices, the high cost of downstream processing, and the comparatively narrow taxonomic base from which most industrially relevant amylases have so far been drawn. Addressing these constraints through broader bioprospecting, structure-guided engineering, and economically integrated production strategies will be essential to fully realize the biotechnological potential of thermostable amylases.

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Footnotes

Edited by: Hichem Tahraoui, University of Medea, Algeria

Reviewed by: Hitarth B. Bhatt, Charotar University of Science and Technology, India

Piyush kant Rai, AKS University, India

Sobroney Heng, Merced, United States