ABCC8 encodes SUR1, the regulatory subunit of the ATP-sensitive potassium channel, or KATP, in pancreatic beta cells. The channel helps control insulin secretion by responding to cellular energy and nucleotide signals. Loss-of-function variants can impair channel opening and cause persistent hyperinsulinemic hypoglycemia, whereas gain-of-function variants can limit insulin release and contribute to diabetes or neonatal diabetes. SUR1 is also the principal pharmacological target of sulfonylureas. Gliclazide binds to this subunit and promotes channel closure, depolarizing the beta-cell membrane, opening voltage-gated calcium channels and triggering insulin release. Because ABCC8 variants occur in several diabetes-related disorders, their consequences for gliclazide binding may be relevant to drug selection and response.

The researchers assembled a dataset of 18 missense variants associated with type 2 diabetes from ClinVar Miner and ClinVar, retaining variants with at least two review stars and multiple submitters. The set included substitutions distributed throughout SUR1, including the gain-of-function Arg1182Trp and numerous loss-of-function variants linked to hyperinsulinism, neonatal diabetes or type 2 diabetes. They obtained the human wild-type sequence from UniProt and the corresponding structural model from the AlphaFold Protein Structure Database, then used AlphaFold 3 to model each mutant. Quality assessment with QMEANDisCo and MolProbity indicated that the models were suitable for downstream analysis: mutant global scores were close to the wild-type value, and more than 95% of residues in every model occupied favored Ramachandran regions. The variant models nevertheless had higher clash scores than the wild-type model, revealing localized differences in atomic contacts that could influence ligand interactions.

Molecular docking was performed with HADDOCK, using a predicted binding pocket to guide placement of gliclazide, diazoxide and metformin. Metformin served as a negative control because it lacks the sulfonylurea pharmacophore, while diazoxide provided a reference for another SUR1 ligand with opposite functional effects on channel gating. Gliclazide ranked as the strongest binder throughout the wild-type and mutant models, with predicted binding free energies of roughly −7 to −8 kilocalories per mole. The strongest docking result was for Phe591Leu at −7.95 kcal/mol, while Arg526Cys, Asp1471Asn, Arg74Gln and Glu128Lys also yielded favorable complexes. Most docked poses shared an Arg1144 hydrogen bond with gliclazide, while the wild type also interacted with Tyr1293. Mutants differed in aromatic and sulfur-mediated contacts involving Trp1296, Phe591, Tyr1293 or His584, showing how residue substitution could alter the local interaction network without eliminating ligand recognition.

The researchers advanced selected complexes into 50-nanosecond all-atom molecular dynamics simulations under explicit-solvent, physiological ionic conditions. Root-mean-square deviation, a measure of structural displacement, generally rose during the first 10 nanoseconds and then approached a plateau, suggesting equilibration rather than continuous destabilization. The wild-type gliclazide complex had a mean RMSD of 0.64 ± 0.13 nanometers. Phe591Leu was more stable still at 0.32 ± 0.04 nm, and Arg74Gln and Arg526Cys also produced relatively consistent trajectories. Asp1471Asn was the clearest outlier, with a mean RMSD of 0.92 ± 0.30 nm and a late rise to approximately 1.6–1.8 nm near the end of the run. That pattern indicated the greatest departure from the initial bound conformation, even though the ligand remained spatially associated with the receptor.

Other trajectory measures supported the general stability of the protein–ligand complexes. Mean residue fluctuations ranged from 0.17 to 0.27 nanometers, and the largest peaks occurred mainly in flexible loops and terminal regions outside the defined ligand-binding pocket. The radius of gyration stabilized after an early reduction, indicating that the global fold remained compact without sustained expansion. The wild-type gliclazide complex had a mean radius of gyration of 4.30 ± 0.02 nanometers, while Phe591Leu was slightly more compact at 4.21 ± 0.02 nanometers. Solvent-accessible surface area also declined during equilibration and then leveled off, with Phe591Leu showing the lowest mean value at 721.79 ± 20.49 square nanometers. These findings suggest that mutations in the tested set did not broadly destabilize the receptor’s fold or dislodge gliclazide over the simulation interval.

Ligand positioning and hydrogen bonding further distinguished the complexes. The mean distance between the ligand and receptor centers of mass remained within a relatively narrow range for most gliclazide complexes, indicating persistent association. Phe591Leu showed the least variation in this distance, while Asp1471Asn had the smallest average separation but the least stable global structure, showing that close proximity alone does not guarantee an intact complex. Phe591Leu also formed the most persistent polar contacts, averaging 2.67 hydrogen bonds and reaching a maximum of six. The wild-type complex averaged only 0.51 hydrogen bonds, and Arg526Cys averaged 0.19. These observations suggest that the Phe591Leu substitution may reinforce the bound state through a combination of compact protein geometry, consistent ligand placement and stronger hydrogen-bonding, even though the exact contribution of each interaction requires experimental testing.

Binding free-energy calculations gave a more nuanced picture than the structural stability metrics. MM-PBSA estimated the most favorable energy for wild-type gliclazide at −21.86 ± 2.70 kcal/mol, compared with −10.00 ± 3.20 for wild-type diazoxide and −9.34 ± 2.17 for wild-type metformin. Among the mutants, Arg74Gln had the most favorable gliclazide estimate at −19.46 ± 3.33 kcal/mol, followed by Phe591Leu at −18.95 ± 4.93 and Asp1471Asn at −18.18 ± 3.09. Arg526Cys and Glu128Lys were less favorable at −16.86 ± 3.81 and −16.34 ± 2.46 kcal/mol. Thus, every tested variant retained predicted binding but showed a less favorable free energy than the wild type. Phe591Leu illustrates why stability and affinity are not interchangeable: it had the most stable dynamics and strongest hydrogen bonding, yet its estimated binding energy remained slightly weaker than that of the wild type.

The biological interpretation remains tentative because docking and molecular dynamics describe interactions with a folded receptor and do not reproduce the full life cycle of a human KATP channel. SUR1 channels are assembled with Kir6.2 core subunits, and the simulations assumed homomeric mutant assemblies rather than the heteromeric arrangements found in many patients with compound-heterozygous mutations. They also cannot directly model whether a mutant receptor reaches the cell surface. That limitation is particularly relevant to Asp1471Asn, which has been associated with congenital hyperinsulinism and may impair channel folding or trafficking. A receptor retained in the endoplasmic reticulum could be unavailable to gliclazide even if its isolated protein model binds the drug. Future work should therefore express wild-type and mutant SUR1/KATP channels in cells, quantify sulfonylurea sensitivity with electrophysiology and derive concentration–response relationships, while also examining clinical outcomes in affected individuals.

Overall, the study portrays gliclazide as a robust computational binder of the pathogenic ABCC8 variants tested, but not as a variant-independent drug in every biological setting. The preserved Arg1144 anchor and recurring contacts in the sulfonylurea pocket help explain why the ligand remained associated with most models, while Phe591Leu emerged as a particularly stable complex and Asp1471Asn as the most likely to disturb structural behavior. The central message is that ABCC8 single-nucleotide variants can fine-tune SUR1 dynamics and modify predicted gliclazide affinity without eliminating binding. Establishing whether those differences translate into altered insulin secretion, channel closure or treatment response will require direct functional measurements and clinical validation rather than reliance on molecular simulation alone.

Subject of Research: Molecular simulation of how pathogenic ABCC8 variants affect structural dynamics and gliclazide binding to SUR1

Article Title: Structural dynamics of pathogenic ABCC8 single-nucleotide variants and their interactions with gliclazide

Article References: Simatupang, S. T., Dermawan, D., Nadia, Tan, S., Yulandi, A., & Tjandrawinata, R. R. (2026). Structural dynamics of pathogenic ABCC8 single-nucleotide variants and their interactions with gliclazide. Pharmacia, 73, Article e185272. https://doi.org/10.3897/pharmacia.73.e185272

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e185272

Keywords: ABCC8, SUR1, gliclazide, type 2 diabetes, KATP channel, molecular dynamics, molecular docking, MM-PBSA, drug response, sulfonylurea receptor, insulin secretion, genetic variants

The triple combination is becoming increasingly common in the management of type 2 diabetes, and for good reason. Each drug attacks high blood sugar through a different biological route: metformin suppresses glucose production in the liver and improves insulin sensitivity, gliclazide prods the pancreas to release more insulin, and dapagliflozin forces the kidneys to flush excess glucose out through the urine. Combining them in a single pill improves patient compliance and delivers better glycaemic control than any one agent alone. But that therapeutic synergy creates an analytical headache, because a quality-control laboratory must be able to verify the exact amount of each ingredient in every batch before the tablets reach patients.

The difficulty lies in chemistry. Metformin is a small, strongly polar, highly hydrophilic molecule with a log P value of roughly minus 2.64, which means it barely interacts with the oily, hydrophobic surface of a reverse-phase column and tends to zip through unretained. Dapagliflozin and gliclazide, by contrast, are far more lipophilic, with log P values around 2 or higher, so they cling to the stationary phase much longer. On top of that, the dose disparity is enormous: commercial tablets contain 500 to 1000 milligrams of metformin, 40 to 80 milligrams of gliclazide, and a mere 5 to 10 milligrams of dapagliflozin, so any single method must accurately quantify compounds whose concentrations in solution differ by orders of magnitude.

Led by Rajendra Patel, with Nishith Teraiya and Anjali Prajapati, all of the K.B. Institute of Pharmaceutical Education and Research in Gandhinagar, the team systematically tuned every variable that governs chromatographic behavior. They tested water-methanol and water-acetonitrile mixtures in various ratios, but unbuffered systems produced broad, asymmetrical peaks with poor resolution. The breakthrough came from adding a volatile 20 millimolar ammonium acetate buffer adjusted to pH 3.0 with ortho-phosphoric acid. At that acidity, metformin remains fully protonated and water-loving, so it elutes first, while the more lipophilic dapagliflozin and gliclazide linger progressively longer on the hydrophobic C18 stationary phase, producing clean, well-resolved peaks.

The final recipe is elegantly simple. Separation occurs on a Kromasil C18 column, 250 millimeters long with a 4.6 millimeter internal diameter and 5 micrometer particles, using a mobile phase of the acetate buffer and acetonitrile mixed 35:65 by volume, pumped at a constant 0.8 milliliters per minute in isocratic mode. A UV detector set at 224 nanometers, a wavelength where the absorption spectra of all three drugs overlap acceptably, monitors the eluate. Under these conditions metformin appears at 2.47 minutes, dapagliflozin at 3.90 minutes, and gliclazide at 6.46 minutes. Because the solvent composition never changes during the run, the method avoids the complexity, variability, and extra solvent consumption of gradient elution, keeping both analysis time and operating costs low.

Validation followed the International Council for Harmonisation’s Q2 (R2) guidelines, the global benchmark for analytical procedures. Calibration curves were linear across 125 to 375 micrograms per milliliter for metformin, 2.5 to 7.5 for dapagliflozin, and 15 to 45 for gliclazide, with correlation coefficients all above 0.997. Recovery experiments, in which known amounts of standard drug were spiked into tablet samples at 80, 100, and 120 percent of target, yielded recoveries between 98 and 102 percent for every analyte, demonstrating negligible interference from tablet excipients. Precision testing, repeated within a single day and across three separate days, produced relative standard deviations consistently below 2 percent, the accepted threshold for repeatability in pharmaceutical analysis.

The robustness trials are particularly reassuring for routine laboratories. The researchers deliberately nudged the method’s settings, slightly altering mobile phase composition, flow rate, detection wavelength, buffer pH, and column temperature, and found that the separation held up every time, with peaks remaining symmetrical, well resolved, and statistically unchanged. Sample solutions stored for 48 hours at room temperature and at refrigerator temperature showed no degradation and no loss of assay value, meaning laboratories can prepare samples in advance without compromising results. Limits of detection and quantification, calculated from the regression statistics of the calibration lines, confirmed the method is sensitive enough for the low-dose dapagliflozin component.

The most dramatic evidence for the method’s stability-indicating power came from forced degradation studies, which regulators require to prove that an analytical method can spot decomposition before it spots nothing at all. The team exposed the drugs to 0.1 normal hydrochloric acid for one hour, 0.1 normal sodium hydroxide for two hours, 3 percent hydrogen peroxide for one hour, 40 degrees Celsius heat for one hour, and direct sunlight for two hours. Each stressor told a chemical story: gliclazide degraded most under acid, consistent with hydrolysis of its sulfonylurea linkage; dapagliflozin proved most vulnerable to light, its aromatic glucoside structure susceptible to photo-oxidation; and metformin, shielded by its highly polar biguanide scaffold, stayed comparatively stable even under heat. Crucially, in every case the degradation products eluted as separate peaks that never overlapped the three drug peaks.

Applied to a real commercial tablet containing 10 milligrams of dapagliflozin, 60 milligrams of gliclazide, and 500 milligrams of metformin, the method returned assay values of 101.52, 98.19, and 99.64 percent respectively, comfortably within pharmacopoeial expectations and confirming that the technique works outside the pristine world of pure standards. That real-world performance matters because regulators and manufacturers increasingly rely on such methods for batch release, shelf-life determination, and post-market surveillance. A method that is simultaneously accurate, robust, and stability-indicating gives quality-control chemists a single, streamlined workflow where they previously might have needed multiple runs or separate methods for each drug pair.

The broader significance extends past one formulation. As fixed-dose combinations multiply across modern pharmacotherapy, the analytical community faces growing pressure to verify ever more complex mixtures with fewer resources. This study demonstrates that careful exploitation of fundamental properties, lipophilicity, ionization state, and spectral overlap, can tame even a three-drug combination spanning a hundredfold dose range in a simple isocratic run. For the millions of patients taking triple antidiabetic therapy, the work represents an invisible but vital layer of assurance: every tablet’s contents can now be confirmed, and its chemical deterioration detected, in under seven minutes of chromatography.

Subject of Research: Development and validation of a stability-indicating RP-HPLC method for simultaneous quantification of dapagliflozin, gliclazide, and metformin in antidiabetic combination tablets

Article Title: Development of a robust stability-indicating RP-HPLC method for simultaneous estimation of triple antidiabetic combination containing dapagliflozin, gliclazide and metformin

Article References: Patel, R., Teraiya, N., & Prajapati, A. (2026). Development of a robust stability-indicating RP-HPLC method for simultaneous estimation of triple antidiabetic combination containing dapagliflozin, gliclazide and metformin. Discover Chemistry, 3(1), Article 518. https://doi.org/10.1007/s44371-026-00978-x

Image Credits: AI Generated

DOI: 10.1007/s44371-026-00978-x

Keywords: RP-HPLC, dapagliflozin, gliclazide, metformin, type 2 diabetes, stability-indicating method, forced degradation, pharmaceutical analysis, ICH Q2 (R2), chromatography, quality control, fixed-dose combination

A team at Guy’s and St Thomas’ NHS Foundation Trust in London set out to close this gap with a structured, age-adapted initiative known as the GOLD diabetes enhanced monitoring pathway, developed within the Geriatric Oncology Liaison Development clinic. Reporting their work in the European Geriatric Medicine journal, the researchers describe a quality improvement project conducted between February 2022 and June 2025, in which a multidisciplinary group of geriatricians, oncologists, diabetologists and clinical nurse specialists translated national guidance from the UK Chemotherapy Board and the Joint British Diabetes Societies for Inpatient Care into a practical, locally tailored system for older patients at intermediate risk of steroid-induced hyperglycaemia.

The pathway began with careful risk stratification. Patients were classified as low risk if they had an HbA1c below 48 mmol/mol and no history of diabetes, and were followed by their oncology team and general practitioner. High-risk patients, including those on insulin, those with HbA1c of 64 mmol/mol or above, glucose readings of 15 mmol/L or higher, pancreatic cancer, or a previous episode of steroid-induced hyperglycaemia, were referred directly to specialist diabetes services. The intermediate group, typically those with HbA1c between 48 and 63 mmol/mol or capillary glucose between 11 and 14.9 mmol/L, or patients with diabetes managed on oral agents who did not meet high-risk criteria, became the focus of the GOLD pathway.

Once enrolled, each patient received a capillary blood glucose meter and personalised education from a geriatric clinical nurse specialist, delivered face to face or by telephone within days of referral, because the interval between referral and the start of systemic anti-cancer therapy is often extremely short. Education covered the symptoms of high and low blood sugar, how to recognise diabetes emergencies, glucose targets, and practical demonstrations of the meter, all calibrated to each patient’s health literacy, cognition and physical abilities, with caregivers involved where necessary. During every treatment cycle, patients checked their glucose on the day of steroid administration and the following two days, before breakfast and before the evening meal, a schedule designed to capture the late-afternoon and evening peaks characteristic of steroid-induced hyperglycaemia.

Telephone follow-up by nurse specialists after each cycle formed the backbone of the monitoring system. The team reviewed all glucose readings, assessed food intake and treatment side effects, and applied decision-making algorithms for intervention. Hyperglycaemia was defined as at least two readings above 15 mmol/L, and hypoglycaemia as any reading below 4 mmol/L. When medication was required, the protocol favoured gliclazide, a sulphonylurea that directly stimulates insulin secretion and thereby counteracts the steroid-driven suppression of pancreatic beta-cell function. The team deliberately adopted a higher intervention threshold of 15 mmol/L, compared with the 12 mmol/L in national guidance, reflecting broader glycaemic targets for older people and a conscious effort to avoid hypoglycaemia and its consequences, particularly in patients with poor oral intake or renal impairment.

The implementation itself was iterative. The pathway was refined through seven Plan-Do-Study-Act cycles between 2022 and 2023, each incorporating feedback from healthcare professionals and addressing specific local barriers such as the feasibility of glucose measurement, intervention thresholds and the medication titration process. Risk criteria were sharpened over successive cycles, with the glucose range adjusted from 12–20 to 11–15 mmol/L and the HbA1c range expanded from 48–59 to 48–64 mmol/mol. Fortnightly multidisciplinary meetings were introduced from January 2023 to review complex cases, and the geriatric nursing team grew increasingly autonomous in managing intermediate-risk patients, reducing the burden on specialist diabetes services while retaining rapid access to expert advice.

In total, 126 patients were enrolled, with a median age of 74 years, 58% male, and 77% living with pre-existing diabetes. The most common tumour sites were the oesophagus, colon and breast, and 94% received chemotherapy as their primary systemic anti-cancer therapy, most commonly supported by dexamethasone at a median daily dose of 8 mg for the first four days of each cycle, chiefly for its anti-emetic and anti-allergic properties. Comprehensive geriatric assessment data, available for 81% of participants, revealed a largely pre-frail population with a median Clinical Frailty Scale score of 3, and identified malnutrition in 46% of the cohort, alongside social isolation, functional impairment and recent falls in smaller proportions. Personalised geriatric interventions, spanning physiotherapy, occupational therapy, dietary support and medication management, were implemented for the vast majority of those with identified impairments.

The results paint a picture of a pathway that is both feasible and safe. Clinical advice on diabetes management was provided to 89% of patients, and diabetes medication intervention was required in 32%, with gliclazide initiated or escalated in 92% of those cases. Women and patients with pre-existing diabetes were significantly more likely to need medication. Critically, only three hypoglycaemic events occurred, all asymptomatic and all managed without clinical consequences. Among 35 unplanned hospital admissions within a year, only two were related to hyperglycaemia, and there were no episodes of diabetic ketoacidosis or hyperosmolar hyperglycaemic syndrome, and no admissions for hypoglycaemia. During a median follow-up of 300 days, 41 patients died, but mortality was associated with metastatic disease, malnutrition and social isolation rather than with glycaemic control or diabetes intervention, suggesting that proactive metabolic monitoring did not add risk in this fragile population.

The pathway also influenced cancer treatment itself in measurable ways. Steroid regimens were modified for 24% of patients, almost always involving dose reductions driven by hyperglycaemia, and in 80% of those cases the adjustment was linked to the need for diabetes medication. While steroid reduction triggered treatment toxicity symptoms in four patients, leading to early discontinuation or dose reduction of the anti-cancer protocol in two, the overall signal was one of balance: oncologists could taper steroids with confidence knowing that a safety net existed for the metabolic consequences. Notably, secondary referrals to the diabetes team fell dramatically over the project period, from 36% of patients enrolled in 2022 to just 5% in 2025, evidence that the geriatric team’s growing expertise was absorbing demand that would otherwise have overwhelmed specialist services.

The authors are candid about limitations. The single-centre design, the predominance of pre-frail patients, the absence of a comparator group and the use of clinical rather than validated tools for some geriatric domains all constrain generalisability, and under-ascertainment of nocturnal or asymptomatic glycaemic excursions cannot be excluded with intermittent fingerstick testing. Even so, the team argues that the GOLD pathway offers a robust, patient-centred model for integrating geriatric, oncology and diabetes care, aligned with national and international recommendations for multidisciplinary management of older adults with complex needs. Future priorities include multi-centre validation, comparative and randomised designs to confirm effectiveness, integration of continuous glucose monitoring and digital health tools to reduce nursing workload, evaluation of patient-reported outcomes and cost-effectiveness, and incorporation of patient feedback to improve usability for those who struggle with glucometer technology. If those steps succeed, structured diabetes monitoring could become a standard component of geriatric oncology, ensuring that the steroids that help fight cancer no longer silently undermine the patients receiving them.

Subject of Research: A quality improvement project evaluating an age-adapted, multidisciplinary diabetes monitoring pathway for older adults with cancer undergoing steroid-based systemic anti-cancer therapy.

Article Title: Improving diabetes management in older adults with cancer: a quality improvement project to enhance monitoring during steroid-based systemic anti-cancer therapy

Article References: Liuu, E., Evans, R., Bassas-Letissier, N., Amaratunga, G., Compton, S., Georgiou, A., Kalsi, T., Liu, Y.-F., Maguire, J., Nottage, C., Rush, H. L., & Welch, C. (2026). Improving diabetes management in older adults with cancer: a quality improvement project to enhance monitoring during steroid-based systemic anti-cancer therapy. European Geriatric Medicine. https://doi.org/10.1007/s41999-026-01585-w

Image Credits: AI Generated

DOI: 10.1007/s41999-026-01585-w

Keywords: geriatric oncology, diabetes, steroid-induced hyperglycaemia, systemic anti-cancer therapy, quality improvement, multidisciplinary care, gliclazide, blood glucose monitoring, older adults, comprehensive geriatric assessment, hypoglycaemia, cancer treatment