Scan-Find-Scan-Model: Discrete Site-Targeted Suppressor Design Strategy for Amyloid-β

Abstract

Alzheimer’s disease is undoubtedly the most well-studied neurodegenerative disease. Consequently, the amyloid-β (Aβ) protein ranks at the top in terms of getting attention from the scientific community for structural property-based characterization. Even after decades of extensive research, there is existing volatility in terms of understanding and hence the effective tackling procedures against the disease that arises due to the lack of knowledge of both specific target- and site-specific drugs. Here, we develop a multidimensional approach based on the characterization of the common static-dynamic-thermodynamic trait of the monomeric protein, which efficiently identifies a small target sequence that contains an inherent tendency to misfold and consequently aggregate. The robustness of the identification of the target sequence comes with an abundance of a priori knowledge about the length and sequence of the target and hence guides toward effective designing of the target-specific drug with a very low probability of bottleneck and failure. Based on the target sequence information, we further identified a specific mutant that showed the maximum potential to act as a destabilizer of the monomeric protein as well as enormous success as an aggregation suppressor. We eventually tested the drug efficacy by estimating the extent of modulation of binding affinity existing within the fibrillar form of the Aβ protein due to a single-point mutation and hence provided a proof of concept of the entire protocol.

The Molecular Mechanism of PSMα3 Aggregation: A New View

“…However, that possibility can be ruled out as the above-mentioned combination is reported to display a bias toward the generation of helical conformations 51 and has been effectively proven to maintain substantial helical states for multiple small peptides. 52,53 This observation directed us to look deeper into the more detailed differentiating features between simulation and experiment which turned out to be the choice of solutions used in the experimental works as they generally involve structure-inducing components as an ingredient of the solution condition, hexafluoroisopropanol 3,14,23 or trifluoroethanol, 6 both of which have a strong bias toward the generation or retention of α-helical conformations. 54,55 Hence, our simulated inference of low helicity is supposedly not such a contradictory outcome given the observation that even after using the helicity-inducing solvent, the maximum limit of helicity achieved in the experiment is very moderate (∼39%).…”

“…In addition to the lack of charge and lack of salt bridge forming ability, the unique potential of proline to act as a robust and persistent effective aggregation suppressor could also originate from the reduced flexibility of the backbone due to the unique structure of the side chain which wraps around the backbone via the formation of covalent bond, the inability of the sequence to accommodate a bulky side chain, and the lack in number of backbone hydrogen bond forming partners. 52,53 The observed lack of helicity across all the phases poses a question regarding the necessity of a new view of PSMα3 aggregation: Is this just an intrinsically disordered peptide initially getting assembled to a stable aggregated state via a native-like aggregation pathway 1 maintaining a substantial β propensity, which fails to reach a regular cross-β arrangement due to a high barrier against further structural reorganization and only attains cross-α fibrillar state 17,23 as an aftermath of imposed environmental effect, whether a specific experimental solvent condition 3 or biological membrane? 23…”

“…One obvious reason could be the choice of combination of parameters (CHARMM27/TIP3P) used in the simulations to describe the atomistic details of the peptide and water molecules. However, that possibility can be ruled out as the above-mentioned combination is reported to display a bias toward the generation of helical conformations and has been effectively proven to maintain substantial helical states for multiple small peptides. , This observation directed us to look deeper into the more detailed differentiating features between simulation and experiment which turned out to be the choice of solutions used in the experimental works as they generally involve structure-inducing components as an ingredient of the solution condition, hexafluoroisopropanol ,, or trifluoroethanol, both of which have a strong bias toward the generation or retention of α-helical conformations. , Hence, our simulated inference of low helicity is supposedly not such a contradictory outcome given the observation that even after using the helicity-inducing solvent, the maximum limit of helicity achieved in the experiment is very moderate (∼39%) . One can logically expect that the experimentally observed helicity content would go down a great deal further if only an aqueous environment was used in the experiment, which is a technical challenge for experimentalists due to the low solubility of the PSMα3 peptide in pure water.…”

“…Though, theoretically, all the designed variants can act as potential aggregation suppressors, the proline mutant appears as the best candidate as it consistently shows lower aggregability at all concentrations due to modulation of two out of three operative forces (charge and salt bridge) and requires a single point mutation which is experimentally feasible. In addition to the lack of charge and lack of salt bridge forming ability, the unique potential of proline to act as a robust and persistent effective aggregation suppressor could also originate from the reduced flexibility of the backbone due to the unique structure of the side chain which wraps around the backbone via the formation of covalent bond, the inability of the sequence to accommodate a bulky side chain, and the lack in number of backbone hydrogen bond forming partners. , …”