Design, synthesis, and biological evaluation of dinaciclib and CAN508 hybrids as CDK inhibitors.

The scaffolds of two known CDK inhibitors (CAN508 and dinaciclib) were the starting point for synthesizing two series of pyarazolo[1,5-a]pyrimidines to obtain potent inhibitors with proper selectivity. The study presented four promising compounds; 10d, 10e, 16a, and 16c based on cytotoxic studies. Compound 16a revealed superior activity in the preliminary anticancer screening with GI % = 79.02-99.13 against 15 cancer cell lines at 10 µM from NCI full panel 60 cancer cell lines and was then selected for further investigation. Furthermore, the four compounds revealed good safety profile toward the normal cell lines WI-38. These four compounds were subjected to CDK inhibitory activity against four different isoforms. All of them showed potent inhibition against CDK5/P25 and CDK9/CYCLINT. Compound 10d revealed the best activity against CDK5/P25 (IC50 = 0.063 µM) with proper selectivity index against CDK1 and CDK2. Compound 16c exhibited the highest inhibitory activity against CDK9/CYCLINT (IC50 = 0.074 µM) with good selectivity index against other isoforms. Finally, docking simulations were performed for compounds 10e and 16c accompanied by molecular dynamic simulations to understand their behavior in the active site of the two CDKs with respect to both CAN508 and dinaciclib.

A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan.

BACKGROUND: The number of COVID-19 infected patients has been soaring in the Middle East countries. The disease poses a significant threat, decisions about prioritizing care should be made in accordance with the proven risk factors for complications. OBJECTIVE: The present study provides the first bespoke prediction model in the Middle East to identify COVID-19 patients, who are at higher risk for complications. METHOD: A case-control study design was adopted to compare the characteristics of successfully recovered patients with those who had complications. Complications were defined as admission to the intensive care unit, mechanical ventilation, sepsis or septic shock, pneumonia or respiratory failure, and death. The prediction model was created through multivariable logistic regression. Overall statistical significance tests for the model were carried out. RESULTS: All COVID-19 infected hospitalized patients (n = 133) in Amman - Jordan were included in the study. Successfully recovered were 125 patients. The median age (IRQ) was 26 (10-40). Almost 30% were >40 years. Patients with complications were eight patients, age 63 (51.5-71.5). The prediction model identified the following variables as risk factors: diabetes (OR = 59.7; 95% CI: 3.5-1011.5, p = 0.005), fever (OR = 24.8; 95% CI: 1.4-447.3, p = 0.029), SHORTNESS OF BREATH (OR = 15.9; 95% CI: 1.3-189.7, p = 0.029), body mass index (OR = 0.74; 95% CI: 0.61-0.88, p = 0.001), abnormal Neutrophils (OR = 16.8; 95% CI: 1.0-292.0, p = 0.053). Prediction model was statistically significant, χ2(5) = 86.1, p < 0.0005. CONCLUSIONS: Unlike reports from China, the most influential variables that led to disease progression in Jordanian patients were diabetes, fever, shortness of breath, body mass index, and abnormal neutrophils. Similar to reports from the USA, smoking was not a leading factor for complications. Comorbidities and patient health status, rather than age, were the primary risk factors for complications. Treatment with Hydroxychloroquine showed no protective effect.