RT Journal Article SR Electronic T1 Convert Your Favorite Protein Modeling Program Into A Mutation Predictor: “MODICT” JF bioRxiv FD Cold Spring Harbor Laboratory SP 038992 DO 10.1101/038992 A1 Ibrahim Tanyalcin A1 Katrien Stouffs A1 Dorien Daneels A1 Carla Al Assaf A1 Danny Coomans A1 Willy Lissens A1 Anna Jansen A1 Alexander Gheldof YR 2016 UL http://biorxiv.org/content/early/2016/02/06/038992.abstract AB Motivation: Predict whether a mutation is deleterious based on the custom 3D model of a protein.Methods: We have developed modiot, a mutation prediction tool which is based on per residue RMSD (root mean square deviation) values of superimposed 3D protein models. Our mathematical algorithm was tested for 42 described mutations in multiple genes including renin, beta-tubulin, biotinidase, sphingomyelin phosphodiesterase-1, phenylalanine hydroxylase and medium chain Acyl-Coa dehydrogenase. Moreover, modiot scores corresponded to experimentally verified residual enzyme activities in mutated biotinidase, phenylalanine hydroxylase and medium chain Acyl-CoA dehydrogenase. Several commercially available prediction algorithms were tested and results were compared. The modiot PERL package and the manual can be downloaded from https://github.com/MODICT/MODICT.Conclusion: We show here that modiot is capable tool for mutation effect prediction at the protein level, using superimposed 3D protein models instead of sequence based algorithms used by POLYPHEN and SIFT.