Cavity-based free energy analysis of osmolyte effects on protein denaturation.

Experimental measurements of the thermal effects of the same osmolytes on two different globular proteins, C-reactive protein (CRP) and tumor necrosis factor alpha (TNFα), have shown that quantifying the change in the denaturing temperature leads to some results that are unique to each protein. In order to find osmolyte-dependent parameters that can be applied more consistently from protein to protein, this work considers, instead, the overall free energy change associated with that denaturation using coarse-grained models. This is enabled by using theoretical fluid equations that take into account the exclusion of water and osmolyte from the volume occupied by the protein in both its native and denatured forms. Assuming ideal geometric models of the two protein states whose sizes are based on the protein's surface area in each form, and taking into account the density of the aqueous osmolyte solution, the free energy change due to the change in geometry can be calculated. The overall change in free energy of the system is found from that quantity and other protein- and osmolyte-specific parameters, which are determined using the experimental concentration and temperature results. We find that these fitted parameters accurately reproduce experimental results and also show consistent patterns from protein to protein. We also consider two different model geometries of the denatured protein and find little impact on the use of one or the other. Defining the effects of the osmolyte in terms of free energy also allows for prediction of overall phase change behavior, including cold denaturation.

Evaluation of consensus scoring methods for AutoDock Vina, smina and idock.

We investigated the application of consensus scoring using the freely available and open source structure-based virtual screening docking programs AutoDock Vina, smina and idock. These individual programs and several simple consensus scoring methods were tested for their ability to identify hits against 20 DUD-E benchmark targets using the AUC and EF1 metrics. We found that all of the consensus scoring methods, however normalized, fared worse, on average, than simply using the output from a single program, smina. Additionally, the effect of a significant increase in the run time of all three programs was tested to find if a longer run time yielded improved results. Our results indicated that a longer run time than the default had little impact on the performance of these three programs or on consensus scoring methods based on their output. Thus, we have found that using the smina program alone at default settings is the best approach for researchers that do not have access to a suite of commercial docking software packages.

Identification of potential Zika virus NS2B-NS3 protease inhibitors via docking, molecular dynamics and consensus scoring-based virtual screening.

The Zika virus has recently become a subject of acute interest after the discovery of the link between viral infection and microcephaly in infants. Though a number of treatments are under active investigation, there are currently no approved treatments for the disease. To address this critical need, we screened more than 7 million compounds targeting the NS2B-NS3 protease in an attempt to identify promising inhibitor candidates. Starting with commercially and freely available compounds, we identified six hits utilizing an exhaustive consensus screening protocol, followed by molecular dynamics simulation and binding energy estimation using MM/GBSA and MM/PBSA methods. These compounds feature a variety of cores and functionalities, and all are predicted to have good pharmacokinetic profiles, making them promising candidates for screening assays. Graphical abstract Virtual screen of potential Zika virus NS2B-NS3 protease inhibitors.