Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Does Rest Time before Ultrasonography Imaging Affect Quadriceps Femoris Muscle Thickness,Cross-Sectional Area and Echo Intensity Measurements?

In the work described here, our aim was to determine, in an elderly population, changes in muscle thickness (MT), cross-sectional area (CSA) and echo intensity (EI) of the quadriceps muscles at four time points (0, 5, 10 and 15 min; i.e., T0, T5, T10 and T15, respectively) after changing from a standing to supine position. Twenty-one elderly participants (14 men: 68.1 ± 4.6 y; 8 women: 66.8 ± 4.1 y) were evaluated at four time points. Rectus femoris CSA (RF_CSA), MT and EI of the quadriceps femoris (QF) muscles were assessed. EI significantly increased from T0 to T5, T10 and T15 (p < 0.001), whereas no differences were observed between T5 and T15 in the rectus femoris (RF_EI), vastus intermedius (VI_EI) and quadriceps femoris (QF_EI). No differences were observed between any time points in the RF_CSA and MT of QF muscles. In summary, these results suggest that periods >5 min are not necessary to obtain consistent MT and EI measurements of quadriceps femoris muscles in the elderly population.     

Variation of resting energy expenditure after the first chemotherapy cycle in acute leukemia patients

Changes in resting energy expenditure (REE) of cancer patients vary depending on type of tumor, treatment time point and kind of treatment. Little is known about REE of acute leukemia adult patients after treatment, especially with results related to body weight or fat free mass (FFM). This study aimed to assess changes in REE of acute leukemia adult patients before and after the first remission induction. Evaluation of REE was performed by indirect calorimetry and predicted REE was calculated by Harris-Benedict equation. Weight and height were measured and compared to a control group of healthy individuals. FFM was assessed by bioelectrical impedance for adjusting REE values. We evaluated 18 patients and 26 healthy individuals. At diagnosis, patients presented REE, REE/weight, and REE/FFM higher than the controls. Reductions of REE, REE/weight, and REE/FFM were also observed in patients after the first cycle of chemotherapy. The predicted REE for the patients group showed significant lower value compared with measured REE. Before the first cycle of chemotherapy REE was increased but undergoes a reduction after treatment, reaching values similar to the controls. For predictive Harris-Benedict equation, stress factors should be added to avoid underestimation of REE before and after chemotherapy.