Several autism spectrum disorders (ASD) exome studies suggest that coding single nucleotide variants (SNVs) play an important role on ASD etiology. Usually, the pathogenic effect of missense mutations is estimated through predictors that lose accuracy for those SNVs placed in intrinsically disordered regions of protein. Here, we used bioinformatics tools to investigate the effect of mutations described in ASD published exome studies (549 mutations) in protein disorder, considering post-translational modification, PEST and Molecular Recognition Features (MoRFs) motifs. Schizophrenia and type 2 diabetes (T2D) datasets were created for comparison purposes. The frequency of mutations predicted as disordered was comparable among the three datasets (38.1% in ASD, 35.7% in schizophrenia, 46.4% in T2D). However, the frequency of SNVs predicted to lead a gain or loss of functional sites or change intrinsic disorder tendencies was higher in ASD and schizophrenia than T2D (46.9%, 36.4%, and 23.1%, respectively). The results obtained by SIFT and PolyPhen-2 indicated that 38.9% and 34.4% of the mutations predicted, respectively, as tolerated and benign showed functional alterations in disorder properties. Given the frequency of mutations placed in IDRs and their functional impact, this study suggests that alterations in intrinsic disorder properties might play a role in ASD and schizophrenia etiologies. They should be taken into consideration when researching the pathogenicity of mutations in neurodevelopmental and psychiatric diseases. Finally, mutations with functional alterations in disorder properties must be potential targets for in vitro and in vivo functional studies.