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Advances in precision molecular imaging promise to transform our ability to detect, diagnose and treat disease. Here, we describe the engineering and validation of a new cystine knot peptide (knottin) that selectively recognizes human integrin αvβ 6 with single-digit nanomolar affinity. We solve its 3D structure by NMR and x-ray crystallography and validate leads with 3 different radiolabels in pre-clinical models of cancer. We evaluate the lead tracer’s safety, biodistribution and pharmacokinetics in healthy human volunteers, and show its ability to detect multiple cancers (pancreatic, cervical and lung) in patients at two study locations. Additionally, we demonstrate that the knottin PET tracers can also detect fibrotic lung disease in idiopathic pulmonary fibrosis patients. Our results indicate that these cystine knot PET tracers may have potential utility in multiple disease states that are associated with upregulation of integrin α v β 6 . Knottin is a cystine knot peptide. Here, the authors develop a knottin-based tracer for positron emission tomography and demonstrate its ability to detect cancer and idiopathic pulmonary fibrosis through selective binding to integrin αvβ 6 .

Background Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments. Results To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments. Conclusions Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap.

Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.

Staphylococcus epidermidis is the leading causative agent for hospital-acquired infections, especially device-related infections, due to its ability to form biofilms. The accumulation-associated protein (Aap) of S. epidermidis is primarily responsible for biofilm formation and consists of two domains, A and B. It was found that the A domain is responsible for the attachment to the abiotic/biotic surface, whereas the B domain is responsible for the accumulation of bacteria during biofilm formation. One of the parts of the A domain is the Aap lectin, which is a carbohydrate-binding domain having 222 amino acids in its structure. Here we report the near complete backbone chemical shift assignments for the lectin domain, as well as its predicted secondary structure. This data will provide a platform for future NMR studies to explore the role of lectin in biofilm formation.

Staphylococcus epidermidis is the leading causative agent for hospital-acquired infections, especially device-related infections, due to its ability to form biofilms. The accumulation-associated protein (Aap) of S. epidermidis is primarily responsible for biofilm formation and consists of two domains, A and B. It was found that the A domain is responsible for the attachment to the abiotic/biotic surface, whereas the B domain is responsible for the accumulation of bacteria during biofilm formation. One of the parts of the A domain is the Aap lectin, which is a carbohydrate-binding domain having 222 amino acids in its structure. Here we report the near complete backbone chemical shift assignments for the lectin domain, as well as its predicted secondary structure. This data will provide a platform for future NMR studies to explore the role of lectin in biofilm formation.

Abstract Advances in precision molecular imaging promise to transform our ability to detect, diagnose and treat disease. Here, we describe the engineering and validation of a new cystine knot peptide (knottin) that selectively recognizes human integrin αvβ 6 with single-digit nanomolar affinity. We solve its 3D structure by NMR and x-ray crystallography and validate leads with 3 different radiolabels in pre-clinical models of cancer. We evaluate the lead tracer’s safety, biodistribution and pharmacokinetics in healthy human volunteers, and show its ability to detect multiple cancers (pancreatic, cervical and lung) in patients at two study locations. Additionally, we demonstrate that the knottin PET tracers can also detect fibrotic lung disease in idiopathic pulmonary fibrosis patients. Our results indicate that these cystine knot PET tracers may have potential utility in multiple disease states that are associated with upregulation of integrin α v β 6 .

Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.

Advances in precision molecular imaging promise to transform our ability to detect, diagnose and treat disease. Here, we describe the engineering and validation of a new cystine knot peptide (knottin) that selectively recognizes human integrin αvβ with single-digit nanomolar affinity. We solve its 3D structure by NMR and x-ray crystallography and validate leads with 3 different radiolabels in pre-clinical models of cancer. We evaluate the lead tracer's safety, biodistribution and pharmacokinetics in healthy human volunteers, and show its ability to detect multiple cancers (pancreatic, cervical and lung) in patients at two study locations. Additionally, we demonstrate that the knottin PET tracers can also detect fibrotic lung disease in idiopathic pulmonary fibrosis patients. Our results indicate that these cystine knot PET tracers may have potential utility in multiple disease states that are associated with upregulation of integrin α β .