The structural effects of mutations can aid in differential phenotype prediction of beta-myosin heavy chain (Myosin-7) missense variants

Abstract

Motivation: High-throughput sequencing platforms are increasingly used to screen patients with genetic disease for pathogenic mutations, but prediction of the effects of mutations remains challenging. Previously we developed SAAPdap (Single Amino Acid Polymorphism Data Analysis Pipeline) and SAAPpred (Single Amino Acid Polymorphism Predictor) that use a combination of rule-based structural measures to predict whether a missense genetic variant is pathogenic. Here we investigate whether the same methodology can be used to develop a differential phenotype predictor, which, once a mutation has been predicted as pathogenic, is able to distinguish between phenotypes -in this case the two major clinical phenotypes (hypertrophic cardiomyopathy, HCM, and dilated cardiomyopathy, DCM) associated with mutations in the beta-myosin heavy chain (MYH7) gene product (Myosin-7). Results: A random forest predictor trained on rule-based structural analyses together with structural clustering data gave a Matthews' correlation coefficient (MCC) of 0.53 (accuracy, 75%). A post hoc removal of machine learning models that performed particularly badly, increased the performance (MCC=0.61, Acc=79%). This proof of concept suggests that methods used for pathogenicity prediction can be extended for use in differential phenotype prediction.

Allosteric modulation of cardiac myosin dynamics by omecamtiv mecarbil

“…Increased preferential connections were also observed for the β3 and β4 strands and part of Loop 1 in most of the cases. Interestingly, mapping the mutations known to be associated with dilated cardiomyopathy (DCM) [ 28 ] onto the Δζ profiles (yellow points in Fig 8 ), shows that some of them are in regions preferentially connected to OM. In particular, I201T (Loop 1) and A223T (G helix) are found in functional regions with consistently negative Δζ values.…”

Computational and biophysical determination of pathogenicity of variants of unknown significance in cardiac thin filament

“…This algorithm was designed to be easily accessed, to be widely used, and to enable rapid predictions but cannot predict effects of splice variants, insertion or deletion mutations, as well as mutations that affect the function of neighboring proteins within a complex. Similarly, the SAAPdap method utilizes structural analysis as well as machine learning to predict the gain or loss of function due to a mutation within a protein ( 43 ). This method is highly focused on the local structural environment and therefore is more accurate than the PolyPhen-2 algorithm.…”

Allosteric Modulation of Cardiac Myosin Dynamics by Omecamtiv Mecarbil

“…Indeed, small molecule activators of myosin have been previously proposed as possible drugs to counteract the effect of dilated cardiomyopathy (DCM) mutations, since these are usually associated with a decrease of the power output of the cardiac muscle [4]. Comparing the distribution of the currently known DCM mutations [28] with the regions preferentially connected to the OM-binding site can give information on the mutants that are most likely to be directly affected by OM binding (yellow dots in Fig 8). Mutations I201T [51] (Loop1) and A223T [52] (G helix) are particularly interesting since a) they are located in regions with high preferential connection and b) they are far from the OM binding site, so they are less likely to directly interfere with the drug binding.…”

“…Indeed, the Apo simulations showed either a reduced (smaller |z| values compared to the OM ones) or no preferential connection (z = 0) to these regions (S14 Fig). The most pronounced increases in preferential connection were observed for the G helix, the β5 strand and Switch 2 in the ATP binding site (Fig 8B), which consistently showed negative Δz values for all the OMbinding site fragments (S13 Fig). Increased preferential connections were also observed for the β3 and β4 strands and part of Loop 1 in most of the cases. Interestingly, mapping the mutations known to be associated with dilated cardiomyopathy (DCM) [28] onto the Δz profiles (yellow points in Fig 8), shows that some of them are in regions preferentially connected to OM. In particular, I201T (Loop 1) and A223T (G helix) are found in functional regions with consistently negative Δz values.…”