Hi All, As per the suggestion given in the modeller that changing random seed would helps in producing different models. On this note I have tried to generate 100 models from single template and using different random seeds. It was mainly performed to know how changing random seed influencing on conformational sampling ?. Following the experiment I had observed that there was notable fluctuations on the sidechain orientations. But when I aligned all the models against top model (DOPE SCORE) there was no variations on the backbone conformation and also in terms of RMSD. Following these observations I have a couple of questions for the modeller experts as follows: When modeller says changing random seed helps in finding different models, does it meant for sidechain orientations or backbone? Is it possible to produce models in modeller that will have more variations on the backbone and in terms of RMSD ? Thanking you in advance