Preorientation of protein and RNA just before contacting

<div><p>Protein and RNA molecules interact and form complexes in many biological processes. However, it is still unclear how they can find the correct docking direction before forming complex. In this paper, we study preorientation of RNA and protein separated at a distance of 5–7 Å just before they form contacts and interact with each other only through pure electrostatic interaction when neglecting the influence of other molecules and complicated environment. Since geometric complementary has no meaning at such a distance, this is not a docking problem and so the conventional docking methods, like FTDock, are inapplicable. However, like the usual docking problem, we need to sample all the positions and orientations of RNA surrounding the protein to find the lowest energy orientations between RNA and protein. Therefore, we propose a long-range electrostatic docking-like method using Fast Fourier Transform-based sampling, LEDock, to study this problem. Our results show that the electrostatically induced orientations between RNA and protein at a distance of 5–7 Å are very different from the random ones and are much closer to those in their native complexes. Meanwhile, electrostatic funnels are found around the RNA-binding sites of the proteins in 62 out of 78 bound protein–RNA complexes. We also tried to use LEDock to find RNA-binding residues and it seems to perform slightly better than BindN Server for 23 unbound protein–RNA complexes.</p> </div

Additional file 1 of Association between the triglyceride-glucose index and impaired cardiovascular fitness in non-diabetic young population

Additional file1: Table S1. Definition of physical activity. Table S2. Definition of smoking status. Table S3. The measurement methods of laboratory indicators. Table S4.The weights used in the analysis of this study. Table S5. The collinearity assessment outcomes for Model 3. Table S6. Comprehensive details of the Survival Cohort Study Design for NHANES 1999-2004. Table S7. Baseline characteristics of the study population with accessible survival outcomes. Table S8. Hazard ratios for all-cause mortality and cardiovascular mortality according to TyG Index. Figure S1. The association between TyG index and CVF impairment. Figure S2. The association between TyG index and all-cause mortality. Figure S3 The association between TyG index and cardiovascular mortality. Figure S4. Sensitivity analysis 1. Figure S5. Sensitivity analysis 2.Don

Additional file 1 of The metabolic score for insulin resistance in the prediction of major adverse cardiovascular events in patients after coronary artery bypass surgery: a multicenter retrospective cohort study

Additional file 1: Table S1. Baseline characteristics between excluded and included participants. Table S2. Sensitivity analysis for the association between the METS-IR and MACE. Table S3. Subgroup and interaction between the METS-IR (Per SD) and non-fatal MI and across various subgroups