Chen Can, Wang Jianlong
Laboratory of Environmental Technology, INET, Tsinghua University, Beijing, PR China.
Appl Microbiol Biotechnol. 2007 Mar;74(4):911-7. doi: 10.1007/s00253-006-0739-1. Epub 2006 Nov 30.
The influence of metal ionic characteristics on their biosorption capacity was analyzed using quantitative structure-activity relationships model. The waste biomass of Saccharomyces cerevisiae was used as biosorbent to adsorb 10 kinds of metal ions, and their maximum biosorption capacity (q (max)) was determined by the Langmuir isotherm model. The values of q (max) decreased in the following order (in millimole per gram): Pb(2+) (0.413) > Ag(+) (0.385) > Cr(3+) (0.247) > Cu(2+) (0.161) > Zn(2+) (0.148) > Cd(2+) (0.137) > Co(2+) (0.128) > Sr(2+) (0.114) > Ni(2+) (0.108) > Cs(+) (0.092). Twenty-two parameters of physiochemical characteristics of metal ions were selected and correlated with q (max), i.e., OX, AN, r (Angstroms), DeltaIP (eV), DeltaE (0) (V), X (m), |log K (OH)|, X(m)(2)(r), Z*(2)/r, AN/DeltaIP, sigma rho, AR, AW, IP, AR/AW, Z/r (2), Z/AR(2), Z/r, Z/AR, Z*(2)/r., Z*, N. The linear regression analysis showed that the covalent index [Formula: see text] was correlated well with q (max) for all metal ions tested in the following equation: q (max) = 0.029 + 0.061 (X(m)(2)r) (R (2) = 0.70). It suggested that the greater the covalent index value of metal ion was, the greater the potential to form covalent bonds with biological ligands, such as sulphydryl, amino, carboxyl, hydroxyl groups, etc. on the biomass surface, and the higher the metal ion biosorption capacity was. Classification of metal ions, for divalent ion or for soft-hard ion could improve the linear relationship (R (2) = 0.89). The equation could be used to predict the biosorption capacity of metal ions.
采用定量构效关系模型分析了金属离子特性对其生物吸附能力的影响。以酿酒酵母的废弃生物质作为生物吸附剂吸附10种金属离子,并用朗缪尔等温线模型测定其最大生物吸附量(q(max))。q(max)值按以下顺序降低(单位为毫摩尔/克):Pb(2+)(0.413)>Ag(+)(0.385)>Cr(3+)(0.247)>Cu(2+)(0.161)>Zn(2+)(0.148)>Cd(2+)(0.137)>Co(2+)(0.128)>Sr(2+)(0.114)>Ni(2+)(0.108)>Cs(+)(0.092)。选取了22个金属离子的理化特性参数并与q(max)进行关联,即OX、AN、r(埃)、DeltaIP(电子伏特)、DeltaE(0)(伏特)、X(m)、|log K(OH)|, X(m)(2)(r)、Z*(2)/r、AN/DeltaIP、sigma rho、AR、AW、IP、AR/AW、Z/r(2)、Z/AR(2)、Z/r, Z/AR、Z*(2)/r.、Z*、N。线性回归分析表明,共价指数[公式:见原文]与所有测试金属离子的q(max)具有良好的相关性,其关系式如下:q(max)=0.029 + 0.061(X(m)(2)r)(R(2)=0.70)。这表明金属离子的共价指数值越大,与生物质表面的巯基、氨基、羧基、羟基等生物配体形成共价键的潜力越大,金属离子的生物吸附能力越高。对金属离子进行分类,分为二价离子或软硬离子,可改善线性关系(R(2)=0.89)。该方程可用于预测金属离子的生物吸附能力。