3D-QSPR Method of Computational Technique Applied on Red Reactive Dyes by Using CoMFA Strategy

Abstract

Cellulose fiber is a tremendous natural resource that has broad application in various productions including the textile industry. The dyes, which are commonly used for cellulose printing, are “reactive dyes” because of their high wet fastness and brilliant colors. The interaction of various dyes with the cellulose fiber depends upon the physiochemical properties that are governed by specific features of the dye molecule. The binding pattern of the reactive dye with cellulose fiber is called the ligand-receptor concept. In the current study, the three dimensional quantitative structure property relationship (3D-QSPR) technique was applied to understand the red reactive dyes interactions with the cellulose by the Comparative Molecular Field Analysis (CoMFA) method. This method was successfully utilized to predict a reliable model. The predicted model gives satisfactory statistical results and in the light of these, it was further analyzed. Additionally, the graphical outcomes (contour maps) help us to understand the modification pattern and to correlate the structural changes with respect to the absorptivity. Furthermore, the final selected model has potential to assist in understanding the charachteristics of the external test set. The study could be helpful to design new reactive dyes with better affinity and selectivity for the cellulose fiber.

A strategy to enhance VOC of π-conjugated molecules based on thieno[2,3-b] indole for applications in bulk heterojunction organic solar cells using DFT, TD-DFT, and 3D-QSPR modeling studies

“…In this test, new values of R 2 and Q 2 were obtained for the random models, and the limit of the difference between the values ( R 2 ) of the original model and those ( R r 2 ) of the random model was measured by the indicator c R p 2 (eqn (14)). 71 …”

Support vector machine classification model for color fastness to ironing of vat dyes

“…28 The 2D-QSPR model has r 2 of 0.957, slightly less than that (r 2 ¼ 0.989) of the 3D-QSPR model. 43 But the LOO cross-validation correlation coefficient q int 2 is 0.937, which is far greater than that (q int 2 ¼ 0.509) of the model by Mahmood et al 43 Thus, the 2D-QSPR model is more stable than the 3D-QSPR model. 43 The results suggest that the molecular descriptors from dyes can be used for developing QSPR models for dyes.…”

“…43 But the LOO cross-validation correlation coefficient q int 2 is 0.937, which is far greater than that (q int 2 ¼ 0.509) of the model by Mahmood et al 43 Thus, the 2D-QSPR model is more stable than the 3D-QSPR model. 43 The results suggest that the molecular descriptors from dyes can be used for developing QSPR models for dyes. Although there may be systematic bias in the description of dye structures when only the molecular structures of dyes are taken into account, for structurally similar molecules these calculation errors are considered to be approximately constant throughout the series, and can be reduced or ignored when regression analysis is performed to develop 2D-QSPR models.…”

“…19 Mahmood et al develop a 3D-QSPR model for the absorptivity of 26 red reactive dyes with comparative molecular field analysis (CoMFA). 43 The 3D-QSPR model has a coefficient of determination of r 2 ¼ 0.989 and an internal correlation coefficient of q int 2 ¼ 0.509 by means of leave-one-out (LOO) cross-validation. To make a comparison between the 3D-QSPR 43 versus 2D-QSPR methods, we calculated molecular descriptors with the method stated above and built a 2D-QSPR model (equation ( 8)) for the absorptivity (e, the unit being dm 3 /mol/ cm  10 4 ) of the red reactive dyes: Here, r 2 is the coefficient of determination, SE is the standard error of the estimate, F is the Fischer ratio, P is the significance test, MATS4v denotes Moran autocorrelations of lag 4 weighted by van der Waals volume, L/Bw means length-to-breadth ratio by the WHIM approach, R7p expresses R maximal autocorrelation of lag 7 weighted by polarizability.…”

Quantitative structure-property relationship modeling of Grätzel solar cell dyes

“…An important assumption made here is that all molecules have similar mechanisms of interaction with the receptor. In addition to drug design, CoMFA methods have also been shown to be useful in other areas such as modeling the absorptivity of cellulose dyes used in fabrics and in the study of metallocene catalysts for ethylene polymerization . The application of CoMFA to photovoltaic dyes is based on the assumption that the steric and electrostatic fields can be correlated with a target property (such as PCE, J sc ) by modeling the dyes as “ligands” and the semiconductor layer as the “receptor.” While the electrostatic effects are crucial for the intramolecular charge transfer, steric (spatial arrangement of atoms) factors also influence the DSSC performance with respect to preventing, for example, undesirable aggregation between dye molecules …”