The study of protein-protein interaction is of great biological significance, and the prediction of protein-protein interaction sites can promote the understanding of cell biological activity and will be helpful for drug development. However, uneven distribution between interaction and non-interaction sites is common because only a small number of protein interactions have been confirmed by experimental techniques, which greatly affects the predictive capability of computational methods. In this work, two imbalanced data processing strategies based on XGBoost algorithm were proposed to re-balance the original dataset from inherent relationship between positive and negative samples for the prediction of protein-protein interaction sites. Herein, a feature extraction method was applied to represent the protein interaction sites based on evolutionary conservatism of proteins, and the influence of overlapping regions of positive and negative samples was considered in prediction performance. Our method showed good prediction performance, such as prediction accuracy of 0.807 and MCC of 0.614, on an original dataset with 10,455 surface residues but only 2297 interface residues. Experimental results demonstrated the effectiveness of our XGBoost-based method.

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Heavy metal pollution is an important problem in current water treatments. Traditional methods for treating chromium-containing wastewater have limitations such as having complicated processes and causing secondary pollution. Therefore, seeking efficient and fast processing methods is an important research topic at present. Photocatalysis is an efficient method to remove Cr(VI) from aqueous solutions; however, conventional photocatalysts suffer from a low metal absorption capacity, high investment cost, and slow desorption of trivalent chromium from the catalyst surface. In this study, a novel composite gel was synthesized by chemically modifying thiourea onto sodium alginate, which was then mixed with biochar. The composite gel (T-BSA) can effectively remove 99.98% of Cr(VI) in aqueous solution through synergistic adsorption and photocatalytic reduction under UV light irradiation. The removal mechanism of Cr(VI) was analyzed by FT-IR, FESEM, UV-DRS and XPS. The results show that under acidic conditions, the amino group introduced by chemical modification can be protonated to adsorb Cr(VI) through electrostatic interaction. In addition, the biochar as a functional material has a large specific surface area and pore structure, which can provide active sites for the adsorption of Cr(VI), while the photo-reduced Cr(III) is released into the solution through electrostatic repulsion, regenerating the adsorption sites, thereby improving the removal performance of Cr(VI). Biochar significantly intensifies the Cr(VI) removal performance by providing a porous structure and transferring electrons during photoreduction. This study demonstrates that polysaccharide-derived materials can serve as efficient photocatalysts for wastewater treatment.