Intrinsic structural dynamics dictate enzymatic activity and inhibition.

Enzymes are known to sample various conformations, many of which are critical for their biological function. However, structural characterizations of enzymes predominantly focus on the most populated conformation. As a result, single-point mutations often produce structures that are similar or essentially identical to those of the wild-type enzyme despite large changes in enzymatic activity. Here, we show for mutants of a histone deacetylase enzyme (HDAC8) that reduced enzymatic activities, reduced inhibitor affinities, and reduced residence times are all captured by the rate constants between intrinsically sampled conformations that, in turn, can be obtained independently by solution NMR spectroscopy. Thus, for the HDAC8 enzyme, the dynamic sampling of conformations dictates both enzymatic activity and inhibitor potency. Our analysis also dissects the functional role of the conformations sampled, where specific conformations distinct from those in available structures are responsible for substrate and inhibitor binding, catalysis, and product dissociation. Precise structures alone often do not adequately explain the effect of missense mutations on enzymatic activity and drug potency. Our findings not only assign functional roles to several conformational states of HDAC8 but they also underscore the paramount role of dynamics, which will have general implications for characterizing missense mutations and designing inhibitors.

Picosecond Dynamics of a Small Molecule in Its Bound State with an Intrinsically Disordered Protein.

Intrinsically disordered proteins (IDPs) are highly dynamic biomolecules that rapidly interconvert among many structural conformations. These dynamic biomolecules are involved in cancers, neurodegeneration, cardiovascular illnesses, and viral infections. Despite their enormous therapeutic potential, IDPs have generally been considered undruggable because of their lack of classical long-lived binding pockets for small molecules. Currently, only a few instances are known where small molecules have been observed to interact with IDPs, and this situation is further exacerbated by the limited sensitivity of experimental techniques to detect such binding events. Here, using experimental nuclear magnetic resonance (NMR) spectroscopy 19F transverse spin-relaxation measurements, we discovered that a small molecule, 5-fluoroindole, interacts with the disordered domains of non-structural protein 5A from hepatitis C virus with a Kd of 260 ± 110 µM. Our analysis also allowed us to determine the rotational correlation times (τc) for the free and bound states of 5-fluoroindole. In the free state, we observed a rotational correlation time of 27.0 ± 1.3 ps, whereas in the bound state, τc only increased to 46 ± 10 ps. Our findings imply that it is possible for small molecules to engage with IDPs in exceptionally dynamic ways, in sharp contrast to the rigid binding modes typically exhibited when small molecules bind to well-defined binding pockets within structured proteins.

Post-translational insertion of boron in proteins to probe and modulate function.

Boron is absent in proteins, yet is a micronutrient. It possesses unique bonding that could expand biological function including modes of Lewis acidity not available to typical elements of life. Here we show that post-translational Cß-Bγ bond formation provides mild, direct, site-selective access to the minimally sized residue boronoalanine (Bal) in proteins. Precise anchoring of boron within complex biomolecular systems allows dative bond-mediated, site-dependent protein Lewis acid-base-pairing (LABP) by Bal. Dynamic protein-LABP creates tunable inter- and intramolecular ligand-host interactions, while reactive protein-LABP reveals reactively accessible sites through migratory boron-to-oxygen Cß-Oγ covalent bond formation. These modes of dative bonding can also generate de novo function, such as control of thermo- and proteolytic stability in a target protein, or observation of transient structural features via chemical exchange. These results indicate that controlled insertion of boron facilitates stability modulation, structure determination, de novo binding activities and redox-responsive 'mutation'.

Confined placental mosaicism: placental size and function evaluated on magnetic resonance imaging.

OBJECTIVES: Evidence regarding placental function in pregnancies complicated by confined placental mosaicism (CPM) is conflicting. We aimed to compare placental function between CPM and non-CPM pregnancies prenatally and at birth. A secondary objective was to evaluate the relationship between placental function and chromosomal subtype of CPM. METHODS: This was a retrospective study of pregnancies with CPM and control pregnancies delivered at a tertiary hospital in Denmark between 2014 and 2017. Placental volume and placental transverse relaxation time (T2*) were estimated on magnetic resonance imaging (MRI), fetal weight and uterine artery pulsatility index (UtA-PI) were estimated on ultrasound and fetoplacental ratio was assessed on MRI and at birth. These estimates of placental function were adjusted for gestational age and compared between groups using the Wilcoxon rank-sum test. Within the group of CPM pregnancies, measures of placental function were compared between those at high risk (chromosome numbers 2, 3, 7, 13 and 16) and those at low risk (chromosome numbers 5, 18 and 45X). RESULTS: A total of 90 pregnancies were included, of which 12 had CPM and 78 were controls. MRI and ultrasound examinations were performed at a median gestational age of 32.6 weeks (interquartile range, 24.7-35.3 weeks). On MRI assessment, CPM placentae were characterized by a lower placental T2* Z-score (P = 0.004), a lower fetoplacental ratio (P = 0.03) and a higher UtA-PI Z-score (P = 0.03), compared with non-CPM placentae. At birth, the fetoplacental ratio was significantly lower (P = 0.02) and placental weight Z-score was higher (P = 0.01) in CPM pregnancies compared with non-CPM pregnancies. High-risk CPM pregnancies showed a reduced placental T2* Z-score (P = 0.003), lower birth-weight Z-score (P = 0.041), earlier gestational age at delivery (P = 0.019) and higher UtA-PI Z-score (P = 0.028) compared with low-risk CPM pregnancies. Low-risk CPM pregnancies did not differ in any of these parameters from non-CPM pregnancies. CONCLUSIONS: CPM pregnancies are characterized by an enlarged and dysfunctional placenta. Placental function was highly related to the chromosomal type of CPM; placental dysfunction was seen predominantly in high-risk CPM pregnancies in which chromosomes 2, 3, 7, 13 or 16 were involved. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Optimizing frequency sampling in CEST experiments.

For the past decade chemical exchange saturation transfer (CEST) experiments have been successfully applied to study exchange processes in biomolecules involving sparsely populated, transiently formed conformers. Initial implementations focused on extensive sampling of the CEST frequency domain, requiring significant measurement times. Here we show that the lengthy sampling schemes often used are not optimal and that reduced frequency sampling schedules can be developed without a priori knowledge of the exchange parameters, that only depend on the chosen B1 field, and, to a lesser extent, on the intrinsic transverse relaxation rates of ground state spins. The reduced sampling approach described here can be used synergistically with other methods for reducing measurement times such as those that excite multiple frequencies in the CEST dimension simultaneously, or make use of non-uniform sampling of indirectly detected time domains, to further decrease measurement times. The proposed approach is validated by analysis of simulated and experimental datasets.

Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks.

Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structure of the conformers that are involved. However, analysis of the NMR data that report on exchanging macromolecules often hinges on complex least-squares fitting procedures as well as human experience and intuition, which, in some cases, limits the widespread use of the methods. The applications of deep neural networks (DNNs) and artificial intelligence have increased significantly in the sciences, and recently, specifically, within the field of biomolecular NMR, where DNNs are now available for tasks such as the reconstruction of sparsely sampled spectra, peak picking, and virtual decoupling. Here we present a DNN for the analysis of chemical exchange saturation transfer (CEST) data reporting on two- or three-site chemical exchange involving sparse state lifetimes of between approximately 3-60 ms, the range most frequently observed via experiment. The work presented here focuses on the 1H CEST class of methods that are further complicated, in relation to applications to other nuclei, by anti-phase features. The developed DNNs accurately predict the chemical shifts of nuclei in the exchanging species directly from anti-phase 1HN CEST profiles, along with an uncertainty associated with the predictions. The performance of the DNN was quantitatively assessed using both synthetic and experimental anti-phase CEST profiles. The assessments show that the DNN accurately determines chemical shifts and their associated uncertainties. The DNNs developed here do not contain any parameters for the end-user to adjust and the method therefore allows for autonomous analysis of complex NMR data that report on conformational exchange.

Acoustic detection range of right whale upcalls identified in near-real time from a moored buoy and a Slocum glider.

The goal of this study was to characterize the detection range of a near real-time baleen whale detection system, the digital acoustic monitoring instrument/low-frequency detection and classification system (DMON/LFDCS), equipped on a Slocum glider and a moored buoy. As a reference, a hydrophone array was deployed alongside the glider and buoy at a shallow-water site southwest of Martha's Vineyard (Massachusetts, USA) over a four-week period in spring 2017. A call-by-call comparison between North Atlantic right whale upcalls localized with the array (n = 541) and those detected by the glider or buoy was used to estimate the detection function for each DMON/LFDCS platform. The probability of detection was influenced by range, ambient noise level, platform depth, detection process, review protocol, and calling rate. The conservative analysis of near real-time pitch tracks suggested that, under typical conditions, a 0.33 probability of detection of a single call occurred at 6.2 km for the buoy and 8.6-13.4 km for the glider (depending on glider depth), while a 0.10 probability of detection of a single call occurred at 14.4 m for the buoy and 22.6-27.5 km for the glider. Probability of detection is predicted to increase substantially at all ranges if more than one call is available for detection.

Virtual Homonuclear Decoupling in Direct Detection Nuclear Magnetic Resonance Experiments Using Deep Neural Networks.

Nuclear magnetic resonance (NMR) experiments are frequently complicated by the presence of homonuclear scalar couplings. For the growing body of biomolecular 13C-detected NMR methods, one-bond 13C-13C couplings significantly reduce sensitivity and resolution. The solution to this problem has typically been to perform virtual decoupling by recording multiple spectra and taking linear combinations. Here, we propose an alternative method of virtual decoupling using deep neural networks, which only requires a single spectrum and gives a significant boost in resolution while reducing the minimum effective phase cycles of the experiments by at least a factor of 2. We successfully apply this methodology to virtually decouple in-phase CON (13CO-15N) protein NMR spectra, 13C-13C correlation spectra of protein side chains, and 13Cα-detected protein 13Cα-13CO spectra where two large homonuclear couplings are present. The deep neural network approach effectively decouples spectra with a high degree of flexibility, including in cases where existing methods fail, and facilitates the use of simpler pulse sequences.

FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling.

In recent years, the transformative potential of deep neural networks (DNNs) for analysing and interpreting NMR data has clearly been recognised. However, most applications of DNNs in NMR to date either struggle to outperform existing methodologies or are limited in scope to a narrow range of data that closely resemble the data that the network was trained on. These limitations have prevented a widescale uptake of DNNs in NMR. Addressing this, we introduce FID-Net, a deep neural network architecture inspired by WaveNet, for performing analyses on time domain NMR data. We first demonstrate the effectiveness of this architecture in reconstructing non-uniformly sampled (NUS) biomolecular NMR spectra. It is shown that a single network is able to reconstruct a diverse range of 2D NUS spectra that have been obtained with arbitrary sampling schedules, with a range of sweep widths, and a variety of other acquisition parameters. The performance of the trained FID-Net in this case exceeds or matches existing methods currently used for the reconstruction of NUS NMR spectra. Secondly, we present a network based on the FID-Net architecture that can efficiently virtually decouple 13Cα-13Cß couplings in HNCA protein NMR spectra in a single shot analysis, while at the same time leaving glycine residues unmodulated. The ability for these DNNs to work effectively in a wide range of scenarios, without retraining, paves the way for their widespread usage in analysing NMR data.

Novel clinicopathological characteristics differentiate dementia with Lewy bodies from Parkinson's disease dementia.

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) known as Lewy body dementias have overlapping clinical and neuropathological features. Neuropathology in both includes combination of Lewy body and Alzheimer's disease (AD) pathology. Cerebral amyloid angiopathy (CAA), often seen in AD, is increasingly recognized for its association with dementia. AIMS: This study investigated clinical and neuropathological differences between DLB and PDD. METHODS: 52 PDD and 16 DLB cases from the Queen Square Brain Bank (QSBB) for Neurological disorders were included. Comprehensive clinical data of motor and cognitive features were obtained from medical records. Neuropathological assessment included examination of CAA, Lewy body and AD pathology. RESULTS: CAA was more common in DLB than in PDD (P = 0.003). The severity of CAA was greater in DLB than in PDD (P = 0.009), with significantly higher CAA scores in the parietal lobe (P = 0.043), and the occipital lobe (P = 0.008), in DLB than in PDD. The highest CAA scores were observed in cases with APOE ε4/4 and ε2/4. Survival analysis showed worse prognosis in DLB, as DLB reached each clinical milestone sooner than PDD. Absence of dyskinesia in DLB is linked to the significantly lower lifetime cumulative dose of levodopa in comparison with PDD. CONCLUSIONS: This is the first study which identified prominent concurrent CAA pathology as a pathological substrate of DLB. More prominent CAA and rapid disease progression as measured by clinical milestones distinguish DLB from PDD.

Risk factors for multi-joint disease in patients with glucocorticoid-induced osteonecrosis.

This study investigated risk factors for osteonecrosis involving multiple joints (MJON) among glucocorticoid-treated patients. The best predictor of MJON was cumulative oral glucocorticoid dose. Risk of MJON was 12-fold higher in patients who had a second risk factor for osteonecrosis. Further research is needed into strategies for prevention of MJON. INTRODUCTION: Osteonecrosis (ON) is a debilitating musculoskeletal condition in which bone cell death can lead to mechanical failure. When multiple joints are affected, pain and disability are compounded. Glucocorticoid treatment is one of the most common predisposing factors for ON. This study investigated risk factors for ON involving multiple joints (MJON) among glucocorticoid-treated patients. METHODS: Fifty-five adults with glucocorticoid-induced ON were prospectively enrolled. MJON was defined as ON in ≥ three joints. Route, dose, duration, and timing of glucocorticoid treatment were assessed. RESULTS: Mean age of enrolled subjects was 44 years, 58% were women. Half had underlying conditions associated with increased ON risk: systemic lupus erythematosus (29%), acute lymphoblastic leukemia (11%), HIV (9%), and alcohol use (4%). Mean daily oral dose of glucocorticoids was 29 mg. Average cumulative oral dose was 30 g over 5 years. The best predictor of MJON was cumulative oral glucocorticoid dose. For each increase of 1,000 mg, risk of MJON increased by 3.2% (95% CI 1.03, 1.67). Glucocorticoid exposure in the first 6 months of therapy, peak dose (oral or IV), and mean daily dose did not independently increase risk of MJON. The risk of MJON was 12-fold in patients who had a second risk factor (95% CI 3.2, 44.4). CONCLUSIONS: Among patients with glucocorticoid-induced ON, cumulative oral dose was the best predictor of multi-joint disease; initial doses of IV and oral glucocorticoids did not independently increase risk. Further research is needed to better define optimal strategies for prevention and treatment of MJON.

Effect of far infrared therapy on arteriovenous fistula maturation, survival and stenosis in hemodialysis patients, a randomized, controlled clinical trial: the FAITH on fistula trial.

BACKGROUND: An arteriovenous fistula (AVF) is the preferred vascular access for hemodialysis treatment. After creation many of the AVFs will never mature or if functioning will need an intervention within 1 year due to an AVF stenosis. Studies investigating possible therapies that improves the AVF maturation and survival are scarce. Far infrared therapy (FIR) has shown promising results. In minor single centre and industry supported trials FIR has shown improved AVF maturation and survival. There is a need of a randomized multicentre controlled trial to examine the effect of FIR on the AVF maturation and survival and to explore the possible AVF protective mechanism induced by the FIR treatment. METHODS: This investigator initiated, randomized, controlled, open-labeled, multicenter clinical trial will examine the effect of FIR on AVF maturation in patients with a newly created AVF (incident) and AVF patency rate after 1 year of treatment in patients with an existing AVF (prevalent) compared to a control group. The intervention group will receive FIR to the skin above their AVF three times a week for 1 year. The control group will be observed without any treatment. The primary outcome for incident AVFs is the time from surgically creation of the AVF to successful cannulation. The primary outcome for the prevalent AVFs is the difference in number of AVFs without intervention and still functioning in the treatment and control group after 12 months. Furthermore, the acute changes in inflammatory and vasodilating factors during FIR will be explored. Arterial stiffness as a marker of long term AVF patency will also be examined. DISCUSSION: FIR is a promising new treatment modality that may potentially lead to improved AVF maturation and survival. This randomized controlled open-labelled trial will investigate the effect of FIR and its possible mechanisms. TRIAL REGISTRATION: Clinicaltrialsgov NCT04011072 (7th of July 2019).

Potent non-hydroxamate inhibitors of histone deacetylase-8: Role and scope of an isoindolin-2-yl linker with an α-amino amide as the zinc-binding unit.

A series of potent inhibitors of histone deacetylase-8 (HDAC8) is described that contains an α-amino amide zinc-binding unit and a substituted isoindolinyl capping group. The presence of a 2,4-dichlorophenyl unit located in the acetate-release cavity was shown to confer a gain of approx. 4.3 kJ mol-1 in binding energy compared to a phenyl group, and the isoindoline linker has approx. 5.8 kJ mol-1 greater binding energy than the corresponding tetrahydroisoquinoline ring system. In a series of 5-substituted isoindolin-2-yl inhibitors, a 5-acetylamino derivative was found to be more potent than the 5-unsubstituted lead HDAC8 inhibitor (increase in binding energy of 2.0 kJ mol-1, ascribed to additional binding interactions within the Nε-acetyl-l-lysine binding tunnel in HDAC8, including hydrogen bonding to Asp101. Tolerance of a 5-substituent (capping group) on the isoindoline ring has been demonstrated, and which in some cases confers improved enzyme inhibition, the HDAC8 substrate-binding region providing a platform for additional interactions.

Near real-time marine mammal monitoring from gliders: Practical challenges, system development, and management implications.

In 2017, an endangered North Atlantic right whale mortality event in the Gulf of St. Lawrence, Canada, triggered the implementation of dynamic mitigation measures that required real-time information on whale distribution. Underwater glider-based acoustic monitoring offers a possible solution for collecting near real-time information but has many practical challenges including self-noise, energy restrictions, and computing capacity, as well as limited glider-to-shore data transfer bandwidth. This paper describes the development of a near real-time baleen whale acoustic monitoring glider system and its evaluation in the Gulf of St. Lawrence in 2018. Development focused on identifying and prioritizing important acoustic events and on sending contextual information to shore for human validation. The system performance was evaluated post-retrieval, then the trial was simulated using optimized parameters. Trial simulation evaluation revealed that the validated detections of right, fin, and blue whales produced by the system were all correct; the proportion of species occurrence missed varied depending on the timeframe considered. Glider-based near real-time monitoring can be an effective and reliable technique to inform dynamic mitigation strategies for species such as the North Atlantic right whale.

Interaction Between the a3 Region of Factor VIII and the TIL'E' Domains of the von Willebrand Factor.

The von Willebrand factor (VWF) and coagulation factor VIII (FVIII) are intricately involved in hemostasis. A tight, noncovalent complex between VWF and FVIII prolongs the half-life of FVIII in plasma, and failure to form this complex leads to rapid clearance of FVIII and bleeding diatheses such as hemophilia A and von Willebrand disease (VWD) type 2N. High-resolution insight into the complex between VWF and FVIII has so far been strikingly lacking. This is particularly the case for the flexible a3 region of FVIII, which is imperative for high-affinity binding. Here, a structural and biophysical characterization of the interaction between VWF and FVIII is presented with focus on two of the domains that have been proven pivotal for mediating the interaction, namely the a3 region of FVIII and the TIL'E' domains of VWF. Binding between the FVIII a3 region and VWF TIL'E' was here observed using NMR spectroscopy, where chemical shift changes were localized to two ß-sheet regions on the edge of TIL'E' upon FVIII a3 region binding. Isothermal titration calorimetry and NMR spectroscopy were used to characterize the interaction between FVIII and TIL'E' as well as mutants of TIL'E', which further highlights the importance of the ß-sheet region of TIL'E' for high-affinity binding. Overall, the results presented provide new insight into the role the FVIII a3 region plays for complex formation between VWF and FVIII and the ß-sheet region of TIL'E' is shown to be important for FVIII binding. Thus, the results pave the way for further high-resolution insights into this imperative complex.

Using Deep Neural Networks to Reconstruct Non-uniformly Sampled NMR Spectra.

Non-uniform and sparse sampling of multi-dimensional NMR spectra has over the last decade become an important tool to allow for fast acquisition of multi-dimensional NMR spectra with high resolution. The success of non-uniform sampling NMR hinge on both the development of algorithms to accurately reconstruct the sparsely sampled spectra and the design of sampling schedules that maximise the information contained in the sampled data. Traditionally, the reconstruction tools and algorithms have aimed at reconstructing the full spectrum and thus 'fill out the missing points' in the time-domain spectrum, although other techniques are based on multi-dimensional decomposition and extraction of multi-dimensional shapes. Also over the last decade, machine learning, deep neural networks, and artificial intelligence have seen new applications in an enormous range of sciences, including analysis of MRI spectra. As a proof-of-principle, it is shown here that simple deep neural networks can be trained to reconstruct sparsely sampled NMR spectra. For the reconstruction of two-dimensional NMR spectra, reconstruction using a deep neural network performs as well, if not better than, the currently and widely used techniques. It is therefore anticipated that deep neural networks provide a very valuable tool for the reconstruction of sparsely sampled NMR spectra in the future to come.

Intra-residue methyl-methyl correlations for valine and leucine residues in large proteins from a 3D-HMBC-HMQC experiment.

Methyl-TROSY based NMR experiments have over the last two decades become one of the most important means to characterise dynamics and functional mechanisms of large proteins and macromolecular machines in solution. The chemical shift assignment of methyl groups in large proteins is, however, still not trivial and it is typically performed using backbone-dependent experiments in a 'divide and conquer' approach, mutations, structure-based assignments or a combination of these. Structure-based assignment of methyl groups is an emerging strategy, which reduces the time and cost required as well as providing a method that is independent of a backbone assignment. One crucial step in available structure-based assignment protocols is linking the two prochiral methyl groups of leucine and valine residues. This has previously been achieved by recording NOESY spectra with short mixing times or by comparing NOESY spectra. Herein, we present a method based on through-bond scalar coupling transfers, a 3D-HMBC-HMQC experiment, to link the intra-residue methyl groups of leucine and valine. It is shown that the HMBC-HMQC method has several advantages over solely using NOESY spectra since a unique intra-residue cross-peak is observed. Moreover, overlap in the methyl-TROSY HMQC spectrum can easily be identified with the HMBC-HMQC experiment, thereby removing possible ambiguities in the assignment.

Review: Clinical, neuropathological and genetic features of Lewy body dementias.

Lewy body dementias are the second most common neurodegenerative dementias after Alzheimer's disease and include dementia with Lewy bodies and Parkinson's disease dementia. They share similar clinical and neuropathological features but differ in the time of dementia and parkinsonism onset. Although Lewy bodies are their main pathological hallmark, several studies have shown the emerging importance of Alzheimer's disease pathology. Clinical amyloid-ß imaging using Pittsburgh Compound B (PiB) supports neuropathological studies which found that amyloid-ß pathology is more common in dementia with Lewy bodies than in Parkinson's disease dementia. Nevertheless, other co-occurring pathologies, such as cerebral amyloid angiopathy, TDP-43 pathology and synaptic pathology may also influence the development of neurodegeneration and dementia. Recent genetic studies demonstrated an important role of APOE genotype and other genes such as GBA and SNCA which seem to be involved in the pathophysiology of Lewy body dementias. The aim of this article is to review the main clinical, neuropathological and genetic aspects of dementia with Lewy bodies and Parkinson's disease dementia. This is particularly relevant as future management for these two conditions may differ.

A Chemical Biology Approach to Understanding Molecular Recognition of Lipid†II by Nisin(1-12): Synthesis and NMR Ensemble Analysis of Nisin(1-12) and Analogues.

Natural products that target lipid II, such as the lantibiotic nisin, are strategically important in the development of new antibacterial agents to combat the rise of antimicrobial resistance. Understanding the structural factors that govern the highly selective molecular recognition of lipid II by the N-terminal region of nisin, nisin(1-12), is a crucial step in exploiting the potential of such compounds. In order to elucidate the relationships between amino acid sequence and conformation of this bicyclic peptide fragment, we have used solid-phase peptide synthesis to prepare two novel analogues of nisin(1-12) in which the dehydro residues have been replaced. We have carried out an NMR ensemble analysis of one of these analogues and of the wild-type nisin(1-12) peptide in order to compare the conformations of these two bicyclic peptides. Our analysis has shown the effects of residue mutation on ring conformation. We have also demonstrated that the individual rings of nisin(1-12) are pre-organised to an extent for binding to the pyrophosphate group of lipid II, with a high degree of flexibility exhibited in the central amide bond joining the two rings.