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With the rise of deep learning models and the successful result showing in different domains (such as Computer vision and Natural language processing)researchers and laboratories of chem-informatics try to apply these techniques in drug design and discovery. recently,the application of Deep Learning in this area of research has made a good progress but it is in the early stage and we can’t say that the results lead us to rational drug design,which mean designing new drugs without in Vivo and human trials. in this project project, we apply different machine learning models on drug design and discovery datasets with multiple tasks (each dateset has a task or goal to achieve from the analysis) after the evaluation and comparison of our results and the benchmarks we found that the huge problem is the small amount of data.