We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher‐order assemblies. These were more difficult to model, as their prediction mainly involved “ab‐initio” docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance “gap” was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template‐based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

In biological fluids, nanoparticles are always surrounded by proteins. As the protein is adsorbed on the surface, the extent of adsorption and the effect on the protein conformation and stability are dependent on the chemical nature, shape, and size of the nanoparticle (NP). We have carried out a detailed investigation on the interaction of bovine serum albumin (BSA) with polyethyleneimine-functionalized ZnO nanoparticles (ZnO-PEI). ZnO-PEI was synthesized using a wet chemical method with a core size of ~3-7 nm (from transmission electron microscopy). The interaction of BSA with ZnO-PEI was examined using a combination of calorimetric, spectroscopic, and computational techniques. The binding was studied by ITC (isothermal titration calorimetry), and the result revealed that the complexation is enthalpy-driven, indicating the possible involvement of electrostatic interaction. To investigate the nature of the interaction and the location of the binding site, a detailed domain-wise surface electrostatic potential calculation was performed using adaptive Poisson-Boltzmann software (APBS). The result shows that the protein surface can bind the nanoparticle. On binding ZnO-PEI, the protein gets destabilized to some extent, as displayed by CD (circular dichroism) and FTIR (Fourier transform infrared) spectroscopy. Chemical and thermal denaturation of BSA, when carried out in the presence of ZnO-PEI, also indicated a small perturbation in the protein structure. A comparison of the enthalpy and entropy components of binding with those derived for the interaction of BSA with ZnO nanoparticles explains the effect of hydrophilic cationic species attached on the NP surface. The effect of the NP surface modification on the structure and stability of BSA would find useful applications in nanobiotechnology.

Background: Osteoporosis is an important public health problem in older adults. It is more common in postmenopausal women and not only gives rise to morbidity but also markedly diminishes the quality of life in this population. There is lack of information about the risk factor of osteoporosis in developing countries. In this study we aimed to assess the risk factors for osteoporosis in postmenopausal women from selected BMD centers of two developing Asian countries (Iran and India).

AlphaFold2 has revolutionized protein structure prediction by leveraging sequence information to rapidly model protein folds with atomic-level accuracy. Nevertheless, previous work has shown that these predictions tend to be inaccurate for structurally heterogeneous proteins. To systematically assess factors that contribute to this inaccuracy, we tested AlphaFold2's performance on 98-fold-switching proteins, which assume at least two distinct-yet-stable secondary and tertiary structures. Topological similarities were quantified between five predicted and two experimentally determined structures of each fold-switching protein. Overall, 94% of AlphaFold2 predictions captured one experimentally determined conformation but not the other. Despite these biased results, AlphaFold2's estimated confidences were moderate-to-high for 74% of fold-switching residues, a result that contrasts with overall low confidences for intrinsically disordered proteins, which are also structurally heterogeneous. To investigate factors contributing to this disparity, we quantified sequence variation within the multiple sequence alignments used to generate AlphaFold2's predictions of fold-switching and intrinsically disordered proteins. Unlike intrinsically disordered regions, whose sequence alignments show low conservation, fold-switching regions had conservation rates statistically similar to canonical single-fold proteins. Furthermore, intrinsically disordered regions had systematically lower prediction confidences than either foldswitching or single-fold proteins, regardless of sequence conservation. AlphaFold2's high prediction confidences for fold switchers indicate that it uses sophisticated pattern recognition to search for one most probable conformer rather than protein biophysics to model a protein's structural ensemble. Thus, it is not surprising that its predictions often fail for proteins whose properties are not fully apparent from solved protein structures. Our results emphasize the need to look at protein structure as an ensemble and suggest that systematic examination of fold-switching sequences may reveal propensities for multiple stable secondary and tertiary structures.