The heterogeneous ribonucleoprotein A18 (hnRNP A18) is upregulated in hypoxic regions of various solid tumors and promotes tumor growth via the coordination of mRNA transcripts associated with pro-survival genes. Thus, hnRNP A18 represents an important therapeutic target in tumor cells. Presented here is the first X-ray crystal structure to be reported for the RNA-recognition motif of hnRNP A18. By comparing this structure with those of homologous RNA-binding proteins (i.e. hnRNP A1), three residues on one face of an antiparallel β-sheet (Arg48, Phe50 and Phe52) and one residue in an unstructured loop (Arg41) were identified as likely to be involved in protein-nucleic acid interactions. This structure helps to serve as a foundation for biophysical studies of this RNA-binding protein and structure-based drug-design efforts for targeting hnRNP A18 in cancer, such as malignant melanoma, where hnRNP A18 levels are elevated and contribute to disease progression.

S100A1 is a member of the S100 family of Ca-binding proteins and regulates several cellular processes, including those involved in Ca signaling and cardiac and skeletal muscle function. In Alzheimer's disease, brain S100A1 is overexpressed and gives rise to disease pathologies, making it a potential therapeutic target. The 2.25 Å resolution crystal structure of Ca-S100A1 is solved here and is compared with the structures of other S100 proteins, most notably S100B, which is a highly homologous S100-family member that is implicated in the progression of malignant melanoma. The observed structural differences in S100A1 versus S100B provide insights regarding target protein-binding specificity and for targeting these two S100 proteins in human diseases using structure-based drug-design approaches.

Structure-based drug discovery is under way to identify and develop small-molecule S100B inhibitors (SBiXs). Such inhibitors have therapeutic potential for treating malignant melanoma, since high levels of S100B downregulate wild-type p53 tumor suppressor function in this cancer. Computational and X-ray crystallographic studies of two S100B-SBiX complexes are described, and both compounds (apomorphine hydrochloride and ethidium bromide) occupy an area of the S100B hydrophobic cleft which is termed site 3. These data also reveal novel protein-inhibitor interactions which can be used in future drug-design studies to improve SBiX affinity and specificity. Of particular interest, apomorphine hydrochloride showed S100B-dependent killing in melanoma cell assays, although the efficacy exceeds its affinity for S100B and implicates possible off-target contributions. Because there are no structural data available for compounds occupying site 3 alone, these studies contribute towards the structure-based approach to targeting S100B by including interactions with residues in site 3 of S100B.

Background: Point-of-care transthoracic echocardiography (POC-TTE) is essential in shock management, allowing for stroke volume (SV) and cardiac output (CO) estimation using left ventricular outflow tract diameter (LVOTD) and left ventricular velocity time integral (VTI). Since LVOTD is difficult to obtain and error-prone, the body surface area (BSA) or a modified BSA (mBSA) is sometimes used as a surrogate (LVOTD BSA , LVOTD mBSA). Currently, no models of LVOTD based on patient characteristics exist nor have BSA-based alternatives been validated. Methods: Focused rapid echocardiographic evaluations (FREEs) performed in intensive care unit patients over a 3year period were reviewed. The age, sex, height, and weight were recorded. Human expert measurement of LVOTD (LVOTD HEM) was performed. An epsilon-support vector regression was used to derive a computer model of the predicted LVOTD (LVOTD CM). Training, testing, and validation were completed. Pearson coefficient and Bland-Altman were used to assess correlation and agreement. Results: Two hundred eighty-seven TTEs with ideal images of the LVOT were identified. LVOTD CM was the best method of SV measurement, with a correlation of 0.87. LVOTD mBSA and LVOTD BSA had correlations of 0.71 and 0.49 respectively. Root mean square error for LVOTD CM , LVOTD mBSA , and LVOTD BSA respectively were 13.3, 37.0, and 26.4. Bland-Altman for LVOTD CM demonstrated a bias of 5.2. LVOTD CM model was used in a separate validation set of 116 ideal images yielding a linear correlation of 0.83 between SV HEM and SV CM. Bland Altman analysis for SV CM had a bias of 2.3 with limits of agreement (LOAs) of − 24 and 29, a percent error (PE) of 34% and a root mean square error (RMSE) of 13.9. Conclusions: A computer model may allow for SV and CO measurement when the LVOTD cannot be assessed. Further study is needed to assess the accuracy of the model in various patient populations and in comparison to the gold standard pulmonary artery catheter. The LVOTD CM is more accurate with less error compared to BSA-based methods, however there is still a percentage error of 33%. BSA should not be used as a surrogate measure of LVOTD. Once validated and improved this model may improve feasibility and allow hemodynamic monitoring via POC-TTE once it is validated.

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