Time-Resolved Ultraviolet Photodissociation Mass Spectrometry Probes the Mutation-Induced Alterations in Protein Stability and Unfolding Dynamics.

How mutations impact protein stability and structure dynamics is crucial for understanding the pathological process and rational drug design. Herein, we establish a time-resolved native mass spectrometry (TR-nMS) platform via a rapid-mixing capillary apparatus for monitoring the acid-initiated protein unfolding process. The molecular details in protein structure unfolding are further profiled by a 193 nm ultraviolet photodissociation (UVPD) analysis of the structure-informative photofragments. Compared with the wild-type dihydrofolate reductase (WT-DHFR), the M42T/H114R mutant (MT-DHFR) exhibits a significant stability decrease in TR-nMS characterization. UVPD comparisons of the unfolding intermediates and original DHFR forms indicate the special stabilization effect of cofactor NADPH on DHFR structure, and the M42T/H114R mutations lead to a significant decrease in NADPH-DHFR interactions, thus promoting the structure unfolding. Our study paves the way for probing the mutation-induced subtle changes in the stability and structure dynamics of drug targets.

Aqueous alkaline phosphate facilitates the non-exchangeable deuteration of peptides and proteins.

The incorporation of deuterium into peptides and proteins holds broad applications across various fields, such as drug development and structural characterization. Nevertheless, current methods for peptide/protein deuteration often target exchangeable labile sites or require harsh conditions for stable modification. In this study, we present a late-stage approach utilizing an alkaline phosphate solution to achieve deuteration of non-exchangeable backbone sites of peptides and proteins. The specific deuteration regions are identified through ultraviolet photodissociation (UVPD) and mass spectrometry analysis. This deuteration strategy demonstrates site and structure selectivity, with a notable affinity for labeling the α-helix regions of myoglobin. The deuterium method is particularly suitable for peptides and proteins that remain stable under high pH conditions.

Pituitary MRI Radiomics Improves Diagnostic Performance of Growth Hormone Deficiency in Children Short Stature: A Multicenter Radiomics Study.

RATIONALE AND OBJECTIVES: To develop an efficient machine-learning model using pituitary MRI radiomics and clinical data to differentiate growth hormone deficiency (GHD) from idiopathic short stature (ISS), making the diagnostic process more acceptable to patients and their families. MATERIALS AND METHODS: A retrospective cohort of 297 GHD and 300 ISS children (4-12 years) were enrolled as training and validation cohorts (8:2 ratio). An external cohort from another institution (49 GHD and 51 ISS) was employed as the testing cohort. Radiomics features extracted from the anterior pituitary gland on sagittal T1-weighted image (1.5 T or 3.0 T) were used to develop a radiomics model after feature selection. Hematological biomarkers were selected to create a clinical model and combine with the optimal radiomics features to create a clinical-radiomics model. The area under the receive operating characteristic curve (AUC) and Delong test compared the diagnostic performance of the previously mentioned three models across different validation and testing cohorts. RESULTS: 17 radiomics features were selected for the radiomics model, and total protein, total cholesterol, free triiodothyronine, and triglyceride were utilized for the clinical model. In the training and validation cohorts, the diagnostic performance of the clinical-radiomics model (AUC=0.820 and 0.801) was comparable to the radiomics model (AUC=0.812 and 0.779, both P >0.05), both outperforming the clinical model (AUC=0.575 and 0.593, P <0.001). In the testing cohort, the clinical-radiomics model exhibited the highest AUC of 0.762 than the clinical and radiomics model (AUC=0.604 and 0.741, respectively, P <0.05). In addition, the clinical and radiomics models demonstrated similar diagnostic performance in the testing cohort (P >0.05). CONCLUSION: Integrating radiomics features from conventional pituitary MRI with clinical indicators offers a minimally invasive approach for identifying GHD and shows robustness in a multicenter setting.

Probing the functional hotspots inside protein hydrophobic pockets by in situ photochemical trifluoromethylation and mass spectrometry.

Due to the complex high-order structures and interactions of proteins within an aqueous solution, a majority of chemical functionalizations happen on the hydrophilic sites of protein external surfaces which are naturally exposed to the solution. However, the hydrophobic pockets inside proteins are crucial for ligand binding and function as catalytic centers and transporting tunnels. Herein, we describe a reagent pre-organization and in situ photochemical trifluoromethylation strategy to profile the functional sites inside the hydrophobic pockets of native proteins. Unbiased mass spectrometry profiling was applied for the characterization of trifluoromethylated sites with high sensitivity. Native proteins including myoglobin, trypsin, haloalkane dehalogenase, and human serum albumin have been engaged in this mild photochemical process and substantial hydrophobic site-specific and structure-selective trifluoromethylation substitutes are obtained without significant interference to their bioactivity and structures. Sodium triflinate is the only reagent required to functionalize the unprotected proteins with wide pH-range tolerance and high biocompatibility. This "in-pocket" activation model provides a general strategy to modify the potential binding pockets and gain essential structural insights into the functional hotspots inside protein hydrophobic pockets.

Development and validation of a nomogram for preoperative prediction of immature teratoma in children with teratoma: a retrospective, multicenter, diagnostic study.

Background: Teratomas are the most common germ cell tumors in children, and histologically classified as mature teratomas (MTs) and immature teratomas (ITs). Preoperative IT identification can affect the surgical approach, the type of procedure, and future possible reproductive health. However, there is no complete diagnostic criterion for ITs nowadays. We aimed to establish and validate a nomogram based on clinical and computed tomography (CT) features for preoperative prediction of ITs in children. Methods: We retrospectively reviewed 519 teratoma patients from hospital I for training (n=364) and validation (n=155), and 113 patients from hospital II for external validation. Univariate and multivariate logistic regression analyses were performed on the training set to screen risk factors, including alpha-fetoprotein (AFP), age, gender, tumor site, size, tumor composition, calcification and fat. Then, a nomogram was established based on identified risk factors and validated on the validation set. The performance of the nomogram was evaluated in terms of discrimination, calibration and the clinical usefulness. Results: Multivariate logistic regression showed that tumor composition, AFP, age, calcification and fat were independent risk factors for preoperative prediction of IT. The area under the receiver operating characteristic (ROC) curves (AUCs) for the nomogram on the training set, internal and external validation set were 0.92 (0.88-0.96), 0.91 (0.84-0.97) and 0.92 (0.86-0.97), respectively. The model demonstrated sensitivity of 80%, specificity of 90% at the cut-off value of 0.262. Whatever the set, the calibration curve indicated good calibration. Decision curve analysis (DCA) curves demonstrated that the nomogram had greater net benefits than either the treat-all tactics or the treat-none tactics within a large scope of threshold. Conclusions: The nomogram established based on clinical and CT findings had the favorable accuracy for the preoperative prediction of IT, and may help in clinical decision-making and risk stratification.