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Computational Life Sciences, Bioinformatics and System Biology

Low resolution protein mapping and KB-R7943 drug-protein molecular interaction analysis of long-QT syndrome linked KCNH2 mutations

, , , , , , , ORCID Icon & ORCID Icon show all
Pages 183-193 | Received 09 Oct 2019, Accepted 25 Feb 2020, Published online: 12 Mar 2020

Figures & data

Table 1. Basic characteristics of KCNH2 missense variants analyzed in this study.

Table 2. Shows pathogenic predictions scores and amino acid changes of all three CA linked KCNH2 mutaions.

Figure 1. Molecular view of built KCNH2 model (a) cytosolic N-terminal PAS domain (b) voltage gated transmembrane domain (VAS) (c) cytosolic C-terminal domain.

Figure 1. Molecular view of built KCNH2 model (a) cytosolic N-terminal PAS domain (b) voltage gated transmembrane domain (VAS) (c) cytosolic C-terminal domain.

Figure 2. Shows the superpose simulation of both wild type KCNH2 against its mutated protein models, with description of the amino acid changes and their RMSD values at the position of the all mutations.

Figure 2. Shows the superpose simulation of both wild type KCNH2 against its mutated protein models, with description of the amino acid changes and their RMSD values at the position of the all mutations.

Figure 3. KCNH2 mutations site secondary structural elements at KCNH2 Wild and mutant models.

Figure 3. KCNH2 mutations site secondary structural elements at KCNH2 Wild and mutant models.

Figure 4. Illustration of the docking simulation combining all KB-R7943 with KCNH2 with (a) wild type protein model (b) mutant Thr613Meth protein model (c) mutant Ser641Phe protein model (d) mutant Gly648Ser protein model.

Figure 4. Illustration of the docking simulation combining all KB-R7943 with KCNH2 with (a) wild type protein model (b) mutant Thr613Meth protein model (c) mutant Ser641Phe protein model (d) mutant Gly648Ser protein model.

Table 3. Auto dock binding energies of KB-R7943 with KCNH2 wild and mutant forms.

Supplemental material

Supplemental Material

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