Comparative analysis of the applicability of prediction software to microcystin toxicity evaluation

Application of software for toxicity analysis of cyanobacterial toxin remains poorly explored compared to such approach in other areas. Predictive software has been extensively used in the discovery of new drugs and assessment of cosmetics safety. Cosmopolitan microcystin variants have well-defined chemical structures, and their toxicity has been measured through in vivo and in vitro experiments. Toxic effects of unexplored variants are estimated using toxicity values from MC-LR, currently recognized as the most toxic and extensively studied microcystin. In silico software facilitates the acquisition of toxicity information for molecules with elucidated chemical structures expeditiously, reproducibly, and at reduced cost, thereby reducing the number of animals required for analyses. The objective of this study was to compare six prediction simulators to determine which ones generate useful information regarding microcystin toxicity. Two-dimensional chemical structures of four microcystin variants (MC-LR, MC-RR, MC-YR, and MC-HarHar) were used in selected software (ADMET Predictor®, ADMETlab, admetSAR, SwissADME, T.E.S.T., and ECOSAR) to obtain predictions on microcystin parameters. After assessing the applicability domain of each software, ADMET Predictor®, admetSAR, SwissADME, and T.E.S.T. were found adequate for predicting lipophilicity, permeability, intestinal absorption, transport proteins, and environmental biodegradation. ADMET Predictor®, admetSAR, and T.E.S.T. yielded similar results despite having fewer than 35 available models, and thus were found to be more consistent for microcystins than SwissADME, that showed the most discrepant results. Conversely, ADMET Predictor® demonstrated over 70 models with valid predictions. Our findings indicate that in silico prediction software with valid applicability domains is promising for generating information regarding toxicity differentiation of microcystin variants.