A Structural Proteomics Exploration of Synphilin-1 and Alpha-Synuclein Interaction in Pathogenesis of Parkinson's Disease

Abstract

Pathological significance of interaction of Synphilin-1 with mutated alpha-synuclein is well known to have serious consequences in causing the formation of inclusion bodies that are linked to Parkinson's disease (PD). Information extracted so far pointed out that specific mutations, A53T, A30P, and E46K, in alpha-synuclein promote such interactions. However, a detailed structural study of this interaction is pending due to the unavailability of the complete structures of the large protein Synphilin-1 of chain length 919 residues and the mutated alpha-synuclein having all the reported specific mutations so far. In this study, a semi-automatic pipeline-based meta-predictor, AlphaLarge, is created to predict high-fidelity structures of large proteins like Synphilin-1 given the limitations of the existing protocols. AlphaLarge recruits a novel augmented AlphaFold model that uses a divide and conquer based strategy on the foundation of a self-sourced template dataset to choose the best structure model through their standard validations. The structure models were re-validated by a Protein Mediated Interaction Analysis (PMIA) formalism that uses the existing structurally relevant information of these proteins. For the training dataset, the new method, AlphaLarge, performed reasonably better than AlphaFold. Also, the new residue- and domain-based structural details of interactions of resultant best structure models of Synphilin-1 and both wild and mutated alpha-synuclein are extracted using PMIA. This result paves the way for better screening of target specific drugs to control the progression of PD, in particular, and research on any kind of pathophysiology involving large proteins of unknown structures, in general.

Keywords: Lewy bodies; Parkinson’s disease; Synphilin-1 and alpha-synuclein interaction; prediction of large protein structures; protein aggregates; protein–protein interaction.

Figure 1

Working parameters (participating residues, bonds, and binding energies) used in PMIA.

Figure 2

Creation of overlapping fragments A, B, and C following the divide and conquer strategy.

Figure 3

Flowchart depicting the working principle of AlphaLarge, where a, b and c shows the structure of fragments 1, 2 and 3 respectively.

Figure 4

Quality assessment of Syn-1 structure predicted by DAA and DTS method from Ramachandran plots obtained from the Swiss-PdbViewer.

Figure 5

(A) Surface filling model, (B) ribbon representation of DTS and DAA structures of Syn-1 (cyan overall with deep blue highlighting central coiled–coil region), and (C) zoomed version of (B) showing interactions with a-syn (wild type) (grey ribbon).

Figure 5

(A) Surface filling model, (B) ribbon representation of DTS and DAA structures of Syn-1 (cyan overall with deep blue highlighting central coiled–coil region), and (C) zoomed version of (B) showing interactions with a-syn (wild type) (grey ribbon).

Figure 6

Panels (A–C) show wild, mutated, and superimposed structures of wild (PDB ID: 1XQ8), and mutated a-Syn, respectively.

Figure 7

Syn-1 and a-Syn (mutated) complex structure: (A) Surface filling model of the AlphaLarge predicted structure of Syn-1 (cyan overall with deep blue highlighting central coiled coil region) and ribbon representation of mutated a-syn (N-terminal 1–65 in grey ribbon), (B) ribbon representation of the complex and (C) zoomed version of (B) showing interactions with mutated a-syn through C-terminal (green ribbon).