Improving AlphaFold modeling using implicit information from experimental density maps

Machine learning prediction algorithms such as AlphaFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including experimental information, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt based on experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We find that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for crystallographic and electron cryo-microscopy map interpretation.

Densities, Viscosities and Excess Properties for Dimethyl Sulfoxide with Diethylene Glycol and Methyldiethanolamine at Different Temperatures

Densities and viscosities of the binary systems dimethylsulfoxide with diethylene glycol and methyldiethanolamine were measured at temperatures ranging from 293.15 to 313.15 K, at atmospheric pressure and over the entire composition range. The experimental density data was correlated as a function of composition using Belda’s and Herraez’s equations, and as a function of temperature and composition using the models of Emmerling et al. and Gonzalez-Olmos-Iglesias. The viscosity results were fitted to the Grunberg-Nissan, Heric-Brewer, Wilson, Noda, and Ishida and Eyring-NRTL equations. The values of viscosity deviation (), excess molar volume (VE), partial molar volumes ( and ) and apparent molar volume ( and ) were determined. The excess functions of the binary systems were fitted to the polynomial equations. The values of thermodynamic functions of activation of viscous flow were calculated and discussed.

Using Volumetric Method the Study of Molecular Interactions of NSAID (DP) in Water and Water + 1M Urea at Different Temperatures

Understanding possible interactions of drugs and the factors that command such interactions could be helpful to control their disadvantageous effects upon human health. In this study, volumetric properties for the solution of diclofenac potassium (DP), a non-steroidal anti-inflammatory drug (NSAID), were investigated for the first time to look into its molecular interactions at four different temperatures varying from 298.15 K to 313.15 K at 5 K intervals in water as well as aqueous hydrotropic agent urea (1M) solutions. Experimental density data obtained using a pycnometer have been taken to estimate apparent molar properties, i.e., limiting apparent molar volume (〖V_ɸ〗^0), apparent molar volume (V_ɸ), limiting apparent molar expansibility (〖E_ɸ〗^0) and apparent molar expansibility (E_ɸ). The results obtained were discussed in terms of solute-solvent and solute-solute interactions in the studied systems. The obtained results from volumetric data were explored in terms of the existence of solute-solvent interactions in aqueous systems of drug solutions.

Synthesis and Characterisation of Structural and Electrical Properties of CuMn2O4 Spinel Compound

CuMn2O4 was synthesized by the solid-state method. MnO2 and CuO were used as precursors. The optimum temperature of synthesis was 850°C. XRD results showed that the prepared compound had a cubic structure with Fd3 ̅m space group. The lattice constant and unit cell volume were a=8.359Å and V=584.14A°3 respectively. The grain size was calculated by the Debye-Scherrer method and was 33.49 nm for CuMn2O4 annealed at 850°C. The experimental density was calculated and compared to the theoretical density. The results were ρt= 5.399 gr/cm3 and ρE = 5.24 gr/cm3. The electrical properties of the compound showed that it behaves like a semiconductor, and the activation energy of the compound was 0.1535 eV. KEYWORDS Activation energy, copper manganite (CuMO), mixed oxide, solid-state reaction, spinel