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Predicting Protein Dimer Structures Using MELD × MD.

ABSTRACT: It is challenging to predict the docked conformations of two proteins. Current methods are susceptible to errors from treating proteins as rigid bodies and from an inability to compute relative Boltzmann populations of different docked conformations. Here, we show that by using the ClusPro server as a front end to generate possible protein-protein contacts, and using Modeling Employing Limited Data (MELD) accelerated molecular dynamics (MELD × MD) as a back end for atomistic simulations, we can find 16/20 native dimer structures of small proteins as those having the lowest free energy, starting from good-bound-backbone structures. We show that atomistic MD free energies can be used to identify native protein dimer structures.

SUBMITTER: Brini E

PROVIDER: S-EPMC6690486 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Predicting Protein Dimer Structures Using MELD × MD.

Brini Emiliano E Kozakov Dima D Dill Ken A KA

Journal of chemical theory and computation 20190405 5

It is challenging to predict the docked conformations of two proteins. Current methods are susceptible to errors from treating proteins as rigid bodies and from an inability to compute relative Boltzmann populations of different docked conformations. Here, we show that by using the ClusPro server as a front end to generate possible protein-protein contacts, and using Modeling Employing Limited Data (MELD) accelerated molecular dynamics (MELD × MD) as a back end for atomistic simulations, we can ...[more]

PMID: 30908034

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Project description:BackgroundControversy exists regarding the best predictive model of liver transplant waiting list (WL) mortality. Models for end-stage liver disease-glomerular filtration rate assessment in liver disease (MELD-GRAIL) and MELD-GRAIL-Na were recently described to provide better prognostication, particularly in females. We evaluated the performance of these scores compared to MELD and MELD-Na.MethodsConsecutive patients with cirrhosis waitlisted for liver transplant from 1998 to 2017 were examined in this single-center study. The primary outcome was 90-d WL mortality. MELD, MELD-Na, MELD-GRAIL, and MELD-GRAIL-Na at the time of WL registration were compared. Model discrimination was assessed with area under the receiver operating characteristic curves and Harrell's C-index after fitting Cox models. Model calibration was examined with Grønnesby and Borgan's modification of the Hosmer-Lemeshow formula and by comparing predicted/observed outcomes across model strata.ResultsThe study population comprised 1108 patients with a median age of 53.5 (interquartile range 48-59) y and male predominance (74.9%). All models had excellent areas under the receiver operating characteristic curves for the primary outcome (MELD 0.89, MELD-Na 0.91, MELD-GRAIL 0.89, MELD-GRAIL-Na 0.89; all comparisons P > 0.05). Youden index cutoffs for 90-d mortality were as follows: MELD, 19; MELD-Na, 22; MELD-GRAIL, 18; and MELD-GRAIL-Na, 17. Variables associated with 90-d mortality on multivariable Cox regression were sodium, bilirubin, creatinine, and international normalized ratio. There were no differences in model discrimination using Harrell's C-index. All models were well calibrated; however, divergence between observed and predicted mortality was noted with scores ≥25.ConclusionThere were no demonstrable differences in discrimination or calibration of GRAIL-based models compared with MELD or MELD-Na in our cohort. This suggests that GRAIL-based models may not have meaningful improvements in discriminatory ability when applied to other settings.

Dataset Information

Predicting Protein Dimer Structures Using MELD × MD.

Publications

Predicting Protein Dimer Structures Using MELD × MD.

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