stationary phase raises a handful of sensible questions. This page answers them in order, starting with the fundamentals and moving to applications.
This page was last updated on 2026-01-06 and is reviewed periodically as new material appears.
Developing an HPLC method begins with defining the purpose, such as quantifying a main component, measuring impurities, or confirming identity. Analysts select separation mode, column, mobile phase, detection, and sample preparation based on analyte properties and matrix. Experiments vary solvent strength, pH, buffer type, and temperature to achieve resolution between critical peaks. The goal is a robust method that produces reliable results across instruments and operators. Method development often involves trial runs and statistical optimization.
Validation demonstrates that a method is suitable for its intended use. Typical performance characteristics include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, and robustness. Regulators and standards organizations provide frameworks, but specific requirements depend on the application and jurisdiction. System suitability tests are run before sample analysis to confirm resolution, peak symmetry, retention time repeatability, and sensitivity. A validated method is not permanently fixed; changes may require partial or full revalidation.
Separation modes differ by the chemistry of the stationary phase and the composition of the mobile phase. Reversed-phase testing uses a nonpolar column and polar solvents, making it common for pharmaceutical, environmental, and food analytes. Normal-phase testing uses a polar column and nonpolar solvents for compounds that are poorly retained in reversed-phase systems. Ion-exchange and ion-pair methods separate charged species, while size-exclusion methods sort molecules by hydrodynamic volume. Gradient elution changes solvent strength over time to resolve complex mixtures, and isocratic elution holds solvent composition constant for simpler assays.
Key performance measures include retention time, peak area, peak height, resolution, tailing factor, and plate count. Retention time helps identify a peak under fixed conditions, but confirmation often requires a second method or detector. Peak area and height relate to concentration through calibration curves, which may be linear or nonlinear depending on the detector response. Resolution describes separation between adjacent peaks, while tailing factor and plate count describe peak shape and column efficiency. Performance checks verify these values before and during a run to confirm that the instrument is performing within limits.
| Property | Value | Notes |
|---|---|---|
| Validation parameter | Accuracy | Closeness of measured value to accepted reference value |
| Validation parameter | Precision | Agreement among repeated measurements under specified conditions |
| System suitability check | Resolution ≥ 1.5 | Baseline separation between critical peak pair |
| System suitability check | Tailing factor ≤ 2.0 | Common target for peak symmetry |
| Documentation | Validation report | Summarizes experiments, acceptance criteria, and conclusions |
HPLC testing separates dissolved compounds by passing a liquid sample through a column packed with stationary phase. A pump delivers mobile phase at controlled flow, and the sample components interact differently with stationary and mobile phases. Compounds that spend more time in mobile phase elute earlier; those retained by stationary phase elute later. Detectors record elution as peaks, and peak area or height relates to amount. This mechanism underpins quantitative analysis of mixtures.
Most routine HPLC testing uses reversed-phase columns, where the stationary phase is nonpolar and the mobile phase is a polar mixture such as water with an organic solvent. Analytes partition between the two phases according to polarity, size, and charge. Gradients that change solvent composition over time can separate compounds with broad retention ranges. Isocratic conditions keep solvent composition constant and suit simpler mixtures. The choice of column chemistry, pH, and temperature affects selectivity and peak shape.
Detection in HPLC testing commonly relies on ultraviolet-visible absorbance, fluorescence, refractive index, or mass spectrometry. UV detection is widely used because many organic compounds absorb light, but it requires a chromophore. Mass spectrometry provides mass-based identification and high sensitivity for trace analytes. Each detector has trade-offs in selectivity, cost, and compatibility with mobile phases. Quantification typically uses calibration curves prepared from reference standards. Results are reported as concentration, purity, or presence above a limit.
Method validation evaluates accuracy, precision, specificity, linearity, range, detection limit, quantitation limit, and robustness. Regulatory guidance for pharmaceuticals, foods, and environmental testing defines expected documentation and acceptance criteria. Verification confirms that a validated method works in a specific laboratory with its own instruments and reagents. Calibration curves use reference standards with known purity and traceability, while measurement uncertainty is estimated from validation data, control charts, and collaborative studies. The scope of validation depends on the method's intended use.
Routine quality control monitors retention time shifts, baseline noise, system pressure, and peak shape. Trends can reveal column aging, mobile phase preparation errors, detector drift, or sample degradation. Corrective actions may include replacing the column, preparing fresh mobile phase, or recalibrating the detector. Stability testing often uses HPLC to measure parent compound loss and degradation product formation. Open questions remain about how accelerated stability results extrapolate to long-term storage under varied conditions.
Quality control for HPLC testing combines scheduled checks, documented procedures, and review of results. Before sample analysis, system suitability testing confirms that the instrument, column, and method meet predefined criteria. Common criteria include resolution between critical peaks, retention time precision, peak tailing, and theoretical plate count. Failure triggers investigation before results are reported. Records link raw data, calculations, instrument logs, and analyst identity to each batch, supporting audits and repeat analysis.
AlphaKnot complements KnotProt, a database focused on experimentally determined protein structures and their topological features. KnotProt provides detailed descriptions of knots, slipknots, and related entanglements in experimentally characterized proteins, whereas AlphaKnot was developed primarily to examine the much larger population of structures generated by modern protein-structure prediction methods. AlphaKnot has been used to investigate the frequency and distribution of knots in protein families and to identify previously uncharacterized topological architectures. Large-scale analyses of AlphaFold structures have identified unusual knot types and proteins containing multiple knots, while comparison with experimentally determined structures has provided examples in which unusual predicted topologies were subsequently confirmed experimentally. The database can therefore be used both as a source of candidate knotted proteins for experimental investigation and as a computational tool for examining the relationship between protein sequence, structure, and topology.
The origins of alemtuzumab date back to Campath-1 which was derived from the rat antibodies raised against human lymphocyte proteins by Herman Waldmann and colleagues in 1983. The name Campath derives from the pathology department of Cambridge University. Initially, Campath-1 was not ideal for therapy because patients could, in theory, react against the foreign rat protein determinants of the antibody. To circumvent this problem, Greg Winter and his colleagues humanised Campath-1, by extracting the hypervariable loops that had specificity for CD52 and grafting them onto a human antibody framework. This became known as Campath-1H and serves as the basis for alemtuzumab. While alemtuzumab started life as a laboratory tool for understanding the immune system, within a short time it was clinically investigated for use to improve the success of bone marrow transplants and as a treatment for leukaemia, lymphoma, vasculitis, organ transplants, rheumatoid arthritis and multiple sclerosis.
The linear amino acid sequence of a protein is called the primary structure. The primary structure can be easily determined from the sequence of codons on the DNA gene that codes for it. In most proteins, the primary structure uniquely determines the 3-dimensional structure of a protein in its native environment. An exception is the misfolded prion protein involved in bovine spongiform encephalopathy. This structure is linked to the function of the protein. Additional structural information includes the secondary, tertiary and quaternary structure. A viable general solution to the prediction of the function of a protein remains an open problem. Most efforts have so far been directed towards heuristics that work most of the time.
Benazepril (Lotensin) Cilazapril (Inhibace) Enalapril (Vasotec/Renitec/Berlipril/Enap/Enalapril Profarma) Imidapril (Tanatril) Lisinopril (Listril/Lopril/Novatec/Prinivil/Zestril, Lisidigal) Moexipril (Univasc) Perindopril (Coversyl/Aceon/Perindo) Quinapril (Accupril) Ramipril (Altace/Prilace/Ramace/Ramiwin/Triatec/Tritace/Ramitac) Trandolapril (Mavik/Odrik/Gopten) Ceronapril (never marketed) Fosinopril (Fositen/Monopril) ACE inhibitor peptides can be derived from natural sources such as algae, fruit, seeds, dairy and animal products. A comprehensive resource on anti-hypertensive peptides is available in the form of a database. It contains around 1700 unique antihypertensive peptides. Arfalasin (HOE 409) is an angiotensin antagonist.
Sources: en.wikipedia.org
Biochemistry is the study of chemical processes within and relating to living organisms. Molecular biology is the branch of biology that seeks to understand the molecular basis of biological activity in and between cells. It is centered largely on the study of nucleic acids (such as DNA and RNA) and proteins. It examines the structure, function, and interactions of these macromolecules as they orchestrate processes such as replication, transcription, translation, protein synthesis, and complex biomolecular interactions. In 1953, the Miller–Urey experiment showed that organic compounds could be synthesized abiotically within a closed system mimicking the conditions of early Earth, thus suggesting that complex organic molecules could have arisen spontaneously in early Earth in the process of abiogenesis.
H3O+(aq) + OH−(aq) ⇌ H2O(liq) + H2O(liq) Due to this equilibrium, any increase in the concentration of hydronium is accompanied by a decrease in the concentration of hydroxide. Thus, an Arrhenius acid could also be said to be one that decreases hydroxide concentration, while an Arrhenius base increases it. In an acidic solution, the concentration of hydronium ions is greater than 10−7 moles per liter. Since pH is defined as the negative logarithm of the concentration of hydronium ions, acidic solutions thus have a pH of less than 7.
Caspases play the central role in the transduction of ER apoptotic signals. Caspases are proteins that are highly conserved, cysteine-dependent aspartate-specific proteases. There are two types of caspases: initiator caspases (caspases 2, 8, 9, 10, 11, and 12) and effector caspases (caspases 3, 6, and 7). The activation of initiator caspases requires binding to specific oligomeric activator protein. These active initiator caspases activate the effector caspases through proteolytic cleavage. The active effector caspases then proteolytically degrade a host of intracellular proteins to carry out the cell death program. There also exists a caspase-independent apoptotic pathway that is mediated by AIF (apoptosis-inducing factor).
Sources: en.wikipedia.org
the carboxylation of glutamate allows for better binding of calcium cations, Hydroxyproline, generated by hydroxylation of proline, is a major component of the connective tissue collagen. Hypusine in the translation initiation factor EIF5A, contains a modification of lysine. Some non-proteinogenic amino acids are not found in proteins. Examples include 2-aminoisobutyric acid and the neurotransmitter gamma-aminobutyric acid. Non-proteinogenic amino acids often occur as intermediates in the metabolic pathways for standard amino acids – for example, ornithine and citrulline occur in the urea cycle, part of amino acid catabolism (see below). A rare exception to the dominance of α-amino acids in biology is the β-amino acid beta alanine (3-aminopropanoic acid), which is used in plants and microorganisms in the synthesis of pantothenic acid (vitamin B5), a component of coenzyme A.
The cytochrome b5 reductase enzyme contains a typical oxidoreductase structure with a diaphorase binding domain complex for NADH and a FAD-binding domain. A three-stranded linker domain is present, as well as water-mediated hydrogen bonds, in order to biochemically connect the complex. Once cytochrome b5 reductase catalyzes electron transfer, the resulting reduced form of cytochrome b5 reduces the oxidized ferric ion of hemoglobin from Fe 3+ to Fe 2+. Mechanism: NADH + H+ + 2 ferricytochrome b5 -> NAD+ + 2 ferrocytochrome b5
Anne S. Ulrich (born December 31, 1966) is a German chemist. She is the director of the Institute of Biological Interfaces (IBG-2) and Chair of Biochemistry at the Karlsruhe Institute of Technology. She studied chemistry at the University of Oxford - continued her doctoral work in the laboratory of Anthony Watts - held subsequent research positions as an EMBO-Fellow with Hartmut Oschkinat at the European Molecular Biology Laboratory in Heidelberg and as a Liebig-Fellow with Felix Wieland at the University of Heidelberg - became Associate Professor at the University of Jena - until she moved her group in 2002 to the Karlsruhe Institute of Technology. Her research focuses on the structural and functional analysis of biomembranes by solid state NMR. The main systems of interest are:
Seven genes encode seven distinct 14-3-3 proteins in most mammals (See Human genes below) and 13–15 genes in many higher plants, though typically in fungi they are present only in pairs. Protists have at least one. Eukaryotes can tolerate the loss of a single 14-3-3 gene if multiple genes are expressed, but deletion of all 14-3-3s (as experimentally determined in yeast) results in death. 14-3-3 proteins are structurally similar to the Tetratrico Peptide Repeat (TPR) superfamily, which generally have 9 or 10 alpha helices, and usually form homo- and/or hetero-dimer interactions along their amino-termini helices. These proteins contain a number of known common modification domains, including regions for divalent cation interaction, phosphorylation & acetylation, and proteolytic cleavage, among others established and predicted. 14-3-3 binds to peptides. There are common recognition motifs for 14-3-3 proteins that contain a phosphorylated serine or threonine residue, although binding to non-phosphorylated ligands has also been reported. This interaction occurs along a so-called binding groove or cleft that is amphipathic in nature. To date, the crystal structures of six classes of these proteins have been resolved and deposited in the public domain.
Sources: en.wikipedia.org
It is a set of checks performed before or during an HPLC run to confirm the system works as expected. Parameters may include resolution, tailing factor, theoretical plates, and retention time precision. Failure can trigger maintenance, method adjustment, or repeat analysis.
Validation follows a planned protocol that tests accuracy, precision, specificity, linearity, range, detection limits, quantitation limits, and robustness. Results are compared against predefined acceptance criteria. The validation report supports regulatory filing or routine use.
Revalidation may be needed after changes to column chemistry, mobile phase, detection, sample preparation, or instrument type. It can also follow a pattern of out-of-specification results. The scope depends on whether the change affects method performance.
It measures the amounts and identities of compounds in liquid samples by separation and detection. Depending on the detector and reference standards, results can be qualitative or quantitative. The technique is used in fields such as pharmaceutical analysis, food safety, and environmental monitoring.