Novel Method for Structure–Activity Relationship of Aptamer Sequences for Human Prostate Cancer

Abstract

Prostate cancer (PCa) is one of the most common malignancies in men and seriously threatens men’s health. Developing aptamer probes for PCa cells is of great significance for early diagnosis and treatment of PCa. This paper reports a classification model for SELEX-based aptamers, which were obtained with PCa cell line PCa-3M-1E8 (highly metastatic tumor cell) as target cells and PCa cell line PCa-3M-2B4 (low metastatic tumor cell) as control cells. On the basis of the SELEX principle, 100 oligonucleotide sequences from the 3rd round of SELEX were defined as low affinity and specificity aptamers, and 100 sequences from the 11th round were set as high affinity and specificity aptamers. Seven molecular descriptors were used for the classification model, which were calculated from amino acid sequences translated from DNA aptamer sequences with DNAMAN software. The classification model based on binary logical regression analysis has prediction accuracies, sensitivity, and specificity of about 80% for both the training set and test set. Therefore, it is feasible to calculate molecular descriptors from amino acid sequence translated from DNA aptamer sequences and develop a classification model for PCa cell line PCa-3M-1E8.

Label-free electrochemical aptasensor for rapid detection of SARS-CoV-2 spike glycoprotein based on the composite of Cu(OH)2 nanorods arrays as a high-performance surface substrate

“…Recently, electrochemical sensors and biosensors have attracted a lot of attention due to their ability to detect selectively and sensitively a wide range of targets and in ​medical diagnosis and biomedical research, food control, environmental monitoring, forensics, drug discovery and etc. are of great importance [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] . Among the various biomolecules used to preparation of biosensing layers, aptamers have received much attention from researchers in recent years.…”

Prediction of Depuration Rate Constants for Polychlorinated Biphenyl Congeners

“…The SVM model was further evaluated with the statistical parameters ( q int 2 , r 2 , k , k ′, R 0 2 , R ′ 0 2 , and r m 2 ). − The value of the internal correlation coefficient q int 2 obtained from the training set with leave-one-out cross-validation procedure is 0.690 (>0.5); the value of the correlation coefficient r 2 for the test set is 0.883 (>0.6); the slopes k and k ′ of the regression lines through the origin are 0.983 and 1.003, respectively, within the range of 0.85–1.15; the values of the determination coefficients R 0 2 (0.845) and R ′ 0 2 (0.875) are close to those of r 2 (0.883) with ( r 2 – R 0 2 )/ r 2 = 0.044 and ( r 2 – R ′ 0 2 )/ r 2 = 0.009, both less than 0.1; and the value of the correlation coefficient r 0 2 (without an intercept for r 2 ) is 0.878 and that of the r m 2 = r 2 × [1 – ( r 2 – r 0 2 ) 1/2 ] is 0.820 (>0.5). These statistical parameters satisfy the criteria defined for an acceptable QSPR model. − Therefore, the SVM model in this paper is successful.…”