Implicit Water Model Research Articles

Theoretical Investigations of Hydrolysis Mechanisms of N(SiMe3)3.

Tris(trimethylsilyl)amine (N(SiMe3)3) is one of the most important intermediate products in the indirect synthesis of ammonia (NH3) from nitrogen (N2), which could be hydrolyzed to NH3 under mild conditions. Herein, the hydrolysis mechanism of N(SiMe3)3 has been systematically investigated using density functional theory (DFT) with explicit combined implicit water models. Under neutral conditions, the active barrier of the hydrolysis of N(SiMe3)3 is 17.6 kcal mol-1 in water solvent. The attacking of proton to N center and OH group to the Si atom from water is decoupled for the stabilization of OH group by solvent water molecules, which lower the hydrolysis energy barriers. Furthermore, under acid conditions, N(SiMe3)3 is easily coordinated with proton to form [NH(SiMe3)3]+, and the energy barrier of the hydrolysis reaction could be reduced to 11.5 kcal mol-1 of the first stage, making it being promoted according to the chemical equilibrium. Thus, the results provide an explanation for the possible mechanism of the quantitative conversion of N(SiMe3)3 to NH3 under mild conditions. The decoupled hydrolysis mechanism may play important role in other hydrolysis processes.

Thio ligand binding in dinitrosyl iron-sulfur complexes: Quantitative structure–activity relationships

Energies of the Fe–S coordination bonds D298Fe-S in dinitrosyl iron-sulfur complexes [Fe+(NO)2L2] (DNICs) have been determined from the DFT calculations at the TPSSH/def2-TZVP level of theory and implicit water model. The thio ligand (L) abstraction and exchange for H2O molecule were considered for 26 thiocarbonyl and thiolate DNICs. Quantitative structure–activity relationships have been examined between D298Fe-S and the reactivity indices (RI) of free L. The Fe–S bond energies and the energies of hydrolysis in DNICs linearly correlate with the partial electronic charge on S and properties derived from the energies of frontier MOs in L. Two-parameter linear regression models based on RI of only a free L were built to evaluate stability of DNICs in hydrolysis of L or substitution for other thio ligands. In particular, the predicted D298Fe-S of glutathione in DNIC qualitatively agree with the known experimental data on iron-sulfur-nitrosyl complexes.

PSPICA Force Field Extended for Proteins and Peptides.

Many coarse-grained (CG) molecular dynamics (MD) studies have been performed to investigate biological processes involving proteins and lipids. CG force fields (FFs) in these MD studies often use implicit or nonpolar water models to reduce computational costs. CG-MD using water models cannot properly describe electrostatic screening effects owing to the hydration of ionic segments and thus cannot appropriately describe molecular events involving water channels and pores through lipid membranes. To overcome this issue, we developed a protein model in the pSPICA FF, in which a polar CG water model showing the proper dielectric response was adopted. The developed CG model greatly improved the transfer free energy profiles of charged side chain analogues across the lipid membrane. Application studies on melittin-induced membrane pores and mechanosensitive channels in lipid membranes demonstrated that CG-MDs using the pSPICA FF correctly reproduced the structure and stability of the pores and channels. Furthermore, the adsorption behavior of the highly charged nona-arginine peptides on lipid membranes changed with salt concentration, indicating the pSPICA FF is also useful for simulating protein adsorption on membrane surfaces.

Highly robust quantum mechanics and umbrella sampling studies on inclusion complexes of curcumin and β-cyclodextrin

The poor aqueous solubility of curcumin (CUR) obstructs its wide utilization in nutraceuticals, cosmetics, and pharmaceutical companies. This study is dedicated to investigate the stability of CUR inside the hydrophobic pocket of β-cyclodextrin (β-CD), hydroxypropyl-β-CD (HP-β-CD), and 2,6-Di-O-methyl-β-CD (DM-β-CD). Initially, molecular mechanics (MM) calculations and subsequently quantum mechanical (QM) calculations were performed on inclusion complexes to strengthen the MM results. We performed microsecond timescale MD simulations to observe the structural dynamics of CUR inside the cavity of CDs. We elucidated the most stable binding orientations of CUR inside the cavity of CDs based on binding free energy obtained from the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) and umbrella sampling simulations. Furthermore, the two-layered ONIOM (B3LYP/6-311+G(2d,p):PM7) method with CPCM implicit water model was used to derive the complete energetics and thermodynamics of inclusion complexes at 1:1 stoichiometry. Each inclusion reaction was exothermic and spontaneous. The chemical reactivity and kinetic stability of inclusion complexes were described by HOMO-LUMO molecular orbital energies. In conclusion, our studies revealed that HP-β-CD had the highest binding affinity for CUR with the most negative complexation energy (−6520.69 kJ/mol) and Gibb's free energy change (−6448.20 kJ/mol). The atomic-level investigation of noncovalent interactions between CUR and the hydroxypropyl groups in HP-β-CD/CUR complex may be helpful to drive new derivatives of HP-β-CD with better host capacity. The computational strategy adopted here might serve as a benchmark for increasing the solubility of numerous clinically significant molecules.

Comparing the influence of explicit and implicit solvation models on site-specific thermodynamic stability of proteins.

Understanding the molecular basis for protein stability requires a thermodynamic analysis of protein folding. Thermodynamic analysis is often performed by sampling many atomistic conformations using molecular simulations that employ either explicit or implicit water models. However, it remains unclear to what extent thermodynamic results from different solvation models are reliable at the molecular level. In this study, we quantify the influence of both solvation models on folding stability at the individual backbone and side chain resolutions. We assess the residue-specific folding free energy components of a β-sheet protein and a helical protein using trajectories resulting from TIP3P explicit and generalized Born/surface area implicit solvent simulations of model proteins. We found that the thermodynamic discrepancy due to the implicit solvent mostly originates from charged side chains, followed by the under-stabilized hydrophobic ones. In contrast, the contributions of backbone residue in both proteins were comparable for explicit and implicit water models. Our study lays out the foundation for detailed thermodynamic assessment of solvation models in the context of protein simulation.

Solvent Model Benchmark for Molecular Dynamics of Glycosaminoglycans.

In computational studies of glycosaminoglycans (GAGs), a group of anionic, periodic linear polysaccharides, so far there has been very little discussion about the role of solvent models in the molecular dynamics simulations of these molecules. Predominantly, the TIP3P water model is commonly used as one of the most popular explicit water models in general. However, there are numerous alternative explicit and implicit water models that are neglected in the computational research of GAGs. Since solvent-mediated interactions are particularly important for GAG dynamic and structural properties, it would be of great interest for the GAG community to establish the solvent model that is suited the best in terms of the quality of theoretically obtained GAG parameters and, at the same time, would be reasonably demanding in terms of computational resources required. In this study, heparin (HP) was simulated using five implicit and six explicit solvent models with the aim to find out how different solvent models influence HP's molecular descriptors in the molecular dynamics simulations. Here, we initiate the search for the most appropriate solvent representation for GAG systems and we hope to encourage other groups to contribute to this highly relevant subject.

Different temperature- and pressure-effects on the water-mediated interactions between hydrophobic, hydrophilic, and hydrophobic-hydrophilic nanoscale surfaces.

Water-mediated interactions (WMIs) are responsible for diverse processes in aqueous solutions, including protein folding and nanoparticle aggregation. WMI may be affected by changes in temperature and pressure, and hence, they can alter chemical/physical processes that occur in aqueous environments. Traditionally, attention has been focused on hydrophobic interactions while, in comparison, the role of hydrophilic and hybrid (hydrophobic-hydrophilic) interactions have been mostly overlooked. Here, we study the role of T and P on the WMI between nanoscale (i) hydrophobic-hydrophobic, (ii) hydrophilic-hydrophilic, and (iii) hydrophilic-hydrophobic pairs of (hydroxylated/non-hydroxylated) graphene-based surfaces. We find that hydrophobic, hydrophilic, and hybrid interactions are all sensitive to P. However, while hydrophobic interactions [case (i)] are considerably sensitive to T-variations, hydrophilic [case (ii)] and hybrid interactions [case (iii)] are practically T-independent. An analysis of the entropic and enthalpic contributions to the potential of mean force for cases (i)-(iii) is also presented. Our results are important in understanding T- and P-induced protein denaturation and the interactions of biomolecules in solution, including protein aggregation and phase separation processes. From the computational point of view, the results presented here are relevant in the design of implicit water models for the study of molecular and colloidal/nanoparticle systems at different thermodynamic conditions.

Implicit water model within the Zimm-Bragg approach to analyze experimental data for heat and cold denaturation of proteins

Studies of biopolymer conformations essentially rely on theoretical models that are routinely used to process and analyze experimental data. While modern experiments allow study of single molecules in vivo, corresponding theories date back to the early 1950s and require an essential update to include the recent significant progress in the description of water. The Hamiltonian formulation of the Zimm-Bragg model we propose includes a simplified, yet explicit model of water-polypeptide interactions that transforms into the equivalent implicit description after performing the summation of solvent degrees of freedom in the partition function. Here we show that our model fits very well to the circular dichroism experimental data for both heat and cold denaturation and provides the energies of inter- and intra-molecular H-bonds, unavailable with other processing methods. The revealed delicate balance between these energies determines the conditions for the existence of cold denaturation and thus clarifies its absence in some proteins.

GalaxyWater-wKGB: Prediction of Water Positions on Protein Structure Using wKGB Statistical Potential.

Proteins fold and function in water, and protein-water interactions play important roles in protein structure and function. In computational studies on protein structure and interaction, the effect of water is considered either implicitly or explicitly. Implicit water models are frequently used in protein structure prediction and docking because they are computationally much more efficient than explicit water models, which are often employed in molecular dynamics (MD) simulations. However, implicit water models that treat water as a continuous solvent medium cannot account for specific atomistic protein-water interactions that are critical for structure formation and interactions with other molecules. Various methods for predicting water molecules that form specific atomistic interactions with proteins have been developed. Methods involving MD simulations or the integral equation theory tend to produce more accurate results at a higher computational cost than simple geometry- or energy-based methods. Here, we present a novel method for predicting water positions on a protein surface called GalaxyWater-wKGB, which is based on a statistical potential, a water knowledge-based potential based on the generalized Born model (wKGB). This method is accurate and rapid because it does not require conformational sampling or iterative computation owing to the effective statistical treatment employed to derive the potential. The statistical potential describes specific protein atom-water interactions more accurately than conventional potentials by considering the dependence on the degree of solvent accessibility of protein atoms as well as on protein atom-water distances and orientations. The introduction of solvent accessibility allows effective consideration of competing nonspecific protein-water and intraprotein interactions. When tested on high-resolution protein crystal structures, this method could recover similar or larger fractions of crystallographic water 180 times faster than the sophisticated integral equation theory, 3D-RISM. A web service of this water prediction method is freely available at http://galaxy.seoklab.org/wkgb.

Computational mechanistic study on molecular catalysis of water oxidation by cyclam ligand-based iron complex

The iron metal complexes containing cyclam-based macrocyclic ligands are active water oxidation catalysts, which can facilitate oxygen–oxygen bond formation during the water-splitting process. To understand the mechanism of the catalytic process, we explored this process by [Fe(cyclam)Cl2]Cl performing density functional theory-based first-principles calculations. We examined the energetics of the formation of the oxygen–oxygen bond through the investigation of complexes [FeV(cyclam)(O)2]+, and [FeV(cyclam)(OH)(O)]+2. The process of water nucleophilic addition by this FeV–(oxo) complexes was explored in detail. Our computational study confirms the formation of these species, which were reported earlier in experimental conditions. The transition states for various reactions of the catalytic cycle were obtained within the implicit water model. From these calculations, we find that the proton transfers to cis–oxo or hydroxide moiety require high activation energy during the formation of the oxygen–oxygen bond. Our calculations reveal that the oxygen–oxygen bond formation by the transfer of a proton to the explicit water molecule requires more activation free energy than the transfer of a proton to the cis–oxo or hydroxide of the FeV–oxo species. Overall [FeV(cyclam)(O)2]+ and [FeV(cyclam)(OH)(O)]+2 species with one explicit water molecule requires similar free energy. The Mulliken spin density data confirm the formation of the superoxide complexes. The activation free energy for the release of the oxygen molecule is lesser than that of the oxygen–oxygen bond formation. The natural bond orbital analysis for the complexes before and after the formation of the oxygen–oxygen bond formation shows that this bond formation happens through the interaction of antibonding orbital, π*(d2 −2 –2py) of Fe=O moiety, with the σ*–orbital of the hydroxide group of the water molecule.

A Fragmenting Protocol with Explicit Hydration for Calculation of Binding Enthalpies of Target-Ligand Complexes at a Quantum Mechanical Level.

Optimization of the enthalpy component of binding thermodynamics of drug candidates is a successful pathway of rational molecular design. However, the large size and missing hydration structure of target-ligand complexes often hinder such optimizations with quantum mechanical (QM) methods. At the same time, QM calculations are often necessitated for proper handling of electronic effects. To overcome the above problems, and help the QM design of new drugs, a protocol is introduced for atomic level determination of hydration structure and extraction of structures of target-ligand complex interfaces. The protocol is a combination of a previously published program MobyWat, an engine for assigning explicit water positions, and Fragmenter, a new tool for optimal fragmentation of protein targets. The protocol fostered a series of fast calculations of ligand binding enthalpies at the semi-empirical QM level. Ligands of diverse chemistry ranging from small aromatic compounds up to a large peptide helix of a molecular weight of 3000 targeting a leukemia protein were selected for systematic investigations. Comparison of various combinations of implicit and explicit water models demonstrated that the presence of accurately predicted explicit water molecules in the complex interface considerably improved the agreement with experimental results. A single scaling factor was derived for conversion of QM reaction heats into binding enthalpy values. The factor links molecular structure with binding thermodynamics via QM calculations. The new protocol and scaling factor will help automated optimization of binding enthalpy in future molecular design projects.

Multiscale analysis of the effect of surface charge pattern on a nanopore's rectification and selectivity properties: From all-atom model to Poisson-Nernst-Planck.

We report a multiscale modeling study for charged cylindrical nanopores using three modeling levels that include (1) an all-atom explicit-water model studied with molecular dynamics, and reduced models with implicit water containing (2) hard-sphere ions studied with the Local Equilibrium Monte Carlo simulation method (computing ionic correlations accurately), and (3) point ions studied with Poisson-Nernst-Planck theory (mean-field approximation). We show that reduced models are able to reproduce device functions (rectification and selectivity) for a wide variety of charge patterns, that is, reduced models are useful in understanding the mesoscale physics of the device (i.e., how the current is produced). We also analyze the relationship of the reduced implicit-water models with the explicit-water model and show that diffusion coefficients in the reduced models can be used as adjustable parameters with which the results of the explicit- and implicit-water models can be related. We find that the values of the diffusion coefficients are sensitive to the net charge of the pore but are relatively transferable to different voltages and charge patterns with the same total charge.

The effect of pH on the U(VI) sorption on graphene oxide (GO): A theoretical study

Environmental contamination of radioactive waste water has drawn major public concerns because of its serious hazard in chemical and dynamic bio-toxicities. In present work, the interaction mechanism of the important radionuclide uranium (U) and graphene oxide (GO) under aqueous conditions with varying pH levels was scrutinized by means of high-level density functional theory (DFT) together with the implicit water model. A closer look at the bonding structures and adsorption energies of 12 GO/uranyl complexes indicated that the main adsorption sites on GO were the oxygen-containing functional groups such as epoxy group, carboxyl group, and hydroxyl group. More importantly, high pH level was more favorable for the adsorption process of uranyl species on the graphene oxide due to the stronger electrostatic interaction between negatively charged O atom and uranyl ion. This conclusion was further verified by comprehensive analysis from density of state (DOS) and charge density difference. Compared to the other forms of graphene oxide, the GO containing bi-hydroxyl groups had the highest adsorption capacity towards the uranyl species. The present theoretical view point gave supplement to the experimental observations and the proposed intrinsic mechanisms may bring new insight into the environmental management of radioactive pollution.

A systematic Monte Carlo simulation study of the primitive model planar electrical double layer over an extended range of concentrations, electrode charges, cation diameters and valences

The purpose of this study is to provide data for the primitive model of the planar electrical double layer, where ions are modeled as charged hard spheres, the solvent as an implicit dielectric background (with dielectric constant ϵ = 78.5), and the electrode as a smooth, uniformly charged, hard wall. We use canonical and grand canonical Monte Carlo simulations to compute the concentration profiles, from which the electric field and electrostatic potential profiles are obtained by solving Poisson’s equation. We report data for an extended range of parameters including 1:1, 2:1, and 3:1 electrolytes at concentrations c = 0.0001 − 1 M near electrodes carrying surface charges up to σ = ±0.5 Cm−2. The anions are monovalent with a fixed diameter d− = 3 Å, while the charge and diameter of cations are varied in the range z+ = 1, 2, 3 and d+ = 1.5, 3, 6, and 9 Å (the temperature is 298.15 K). We provide all the raw data in the supplementary material.

Theoretical Studies on the Photochemistry of Pentose Aminooxazoline, a Hypothetical Intermediate Product in the Prebiotic Synthetic Scenario of RNA Nucleotides.

2-Aminooxazole is generally considered a prebiotic precursor of ribonucleotides on the early earth. Its pentose compound, pentose aminooxazoline, has been suggested to be a key intermediate in the prebiotic synthetic scenario. In this article, detailed mechanism of the photochemistry of pentose aminooxazoline has been studied by performing density functional theory and multireference complete active space self-consistent field calculations. Parallel to the "ring-puckering" process, which leads to ultrafast nonradiative deactivation, several other photodissociation channels are explored in detail. In addition, the influences of the pentose structure and solvation effects with both implicit and explicit water models have been uncovered for both neutral and protonated forms. The current theoretical results provide very important information not only for the photostability of RNA nucleotides but also for an in-depth understanding of the synthesis of other prebiotic nucleotides.

Protein NMR Structure Refinement based on Bayesian Inference

Nuclear Magnetic Resonance (NMR) spectroscopy is a tool to investigate threedimensional (3D) structures and dynamics of biomacromolecules at atomic resolution in solution or more natural environments such as living cells. Since NMR data are principally only spectra with peak signals, it is required to properly deduce structural information from the sparse experimental data with their imperfections and uncertainty, and to visualize 3D conformations by NMR structure calculation. In order to efficiently analyse the data, Rieping et al. proposed a new structure calculation method based on Bayes’ theorem. We implemented a similar approach into the program CYANA with some modifications. It allows us to handle automatic NOE cross peak assignments in unambiguous and ambiguous usages, and to create a prior distribution based on a physical force field with the generalized Born implicit water model. The sampling scheme for obtaining the posterior is performed by a hybrid Monte Carlo algorithm combined with Markov chain Monte Carlo (MCMC) by the Gibbs sampler, and molecular dynamics simulation (MD) for obtaining a canonical ensemble of conformations. Since it is not trivial to search the entire function space particularly for exploring the conformational prior due to the extraordinarily large conformation space of proteins, the replica exchange method is performed, in which several MCMC calculations with different temperatures run in parallel as replicas. It is shown with simulated data or randomly deleted experimental peaks that the new structure calculation method can provide accurate structures even with less peaks, especially compared with the conventional method. In particular, it dramatically improves in-cell structures of the proteins GB1 and TTHA1718 using exclusively information obtained in living Escherichia coli (E. coli) cells.

Molecular dynamics simulation study of nerve ion channel

Ion channels are naturally occurring proteins that form hole in membrane. They play multiple roles in many important biological processes. Deletion or alteration of these channels often leads to serious problems in the physiological processes as it controls the flow of ions through it. The proper maintenance of the flow of ions, in turn, is required for normal health. The role of ions channels are now a proved factor behind nerve impulse. Here we have analyzed the nerve ion channel protein, with PDB entry 1BL8, which is basically an ion channel protein in Streptomyces Lividans. The equilibrium energy as well as molecular dynamics simulation is performed first. The possibility of ligand binding is investigated. The change of channel structure is found to be dependent on ligand binding. Implicit water model of the protein is subjected to molecular dynamics simulation to find their energy minimized value. Simulation of the protein in the environment of water and ions has given us important results too.

Coarse-grained molecular dynamics simulation of self-assembly and surface adsorption of ionic surfactants using an implicit water model.

We perform coarse-grained molecular dynamics simulations for sodium dodecyl sulfate (SDS) surfactant using a modification of the Dry Martini force field (Arnarez et al. 2014) with implicit water. After inclusion of particle mesh Ewald (PME) electrostatics, an artificially high dielectric constant for water (ε(r) = 150), and reparameterization, we obtain structural and thermodynamic properties of SDS micelles that are close to those obtained from the standard Martini force field with explicit water, which in turn match those of atomistic simulations. The gains in computational efficiency obtained by removing explicit water allow direct simulations of the self-assembly of SDS in solution. We observe surfactant exchange among micelles and micelle fission and fusion and obtain realistic, equilibrated micelle size distributions at modest computational cost, as well as a transition to cylindrical micelles at high surfactant concentration or with added salt. We further apply this parametrized force field to study the adsorption of SDS onto hydrophobic surfaces and calculate the adsorption kinetics and equilibrium adsorption isotherm. The greatly increased speed of computation of surfactant self-assembly made possible by this Dry Martini method should allow future simulation of competitive adsorption of multiple surfactant species to surfaces, as well as simulation of micellar shape transitions.

Affinity of HIV-1 antibody 2G12 with monosaccharides: A theoretical study based on explicit and implicit water models

In order to develop potential ligands to HIV-1 antibody 2G12 toward HIV-1 vaccine, binding mechanisms of the antibody 2G12 with the glycan ligand of d-mannose and d-fructose were theoretically examined. d-Fructose, whose molecular structure is slightly different from d-mannose, has experimentally shown to have stronger binding affinity to the antibody than that of d-mannose. To clarify the nature of d-fructose's higher binding affinity over d-mannose, we studied interaction between the monosaccharides and the antibody using ab initio fragment molecular orbital (FMO) method considering solvation effect as implicit model (FMO-PCM) as well as explicit water model. The calculated binding free energies of the glycans were qualitatively well consistent with the experimentally reported order of their affinities with the antibody 2G12. In addition, the FMO-PCM calculation elucidated the advantages of d-fructose over d-mannose in the solvation energy as well as the entropic contribution term obtained by MD simulations. The effects of explicit water molecules observed in the X-ray crystal structure were also scrutinized by means of FMO methods. Significant pair interaction energies among d-fructose, amino acids, and water molecules were uncovered, which indicated contributions from the water molecules to the strong binding ability of d-fructose to the antibody 2G12. These FMO calculation results of explicit water model as well as implicit water model indicated that the strong binding of d-fructose over d-mannose was due to the solvation effects on the d-fructose interaction energy.

Structures and Free Energy Landscapes of the A53T Mutant-Type α-Synuclein Protein and Impact of A53T Mutation on the Structures of the Wild-Type α-Synuclein Protein with Dynamics

The A53T genetic missense mutation of the wild-type α-synuclein (αS) protein was initially identified in Greek and Italian families with familial Parkinson's disease. Detailed understanding of the structures and the changes induced in the wild-type αS structure by the A53T mutation, as well as establishing the direct relationships between the rapid conformational changes and free energy landscapes of these intrinsically disordered fibrillogenic proteins, helps to enhance our fundamental knowledge and to gain insights into the pathogenic mechanism of Parkinson's disease. We employed extensive parallel tempering molecular dynamics simulations along with thermodynamic calculations to determine the secondary and tertiary structural properties as well as the conformational free energy surfaces of the wild-type and A53T mutant-type αS proteins in an aqueous solution medium using both implicit and explicit water models. The confined aqueous volume effect in the simulations of disordered proteins using an explicit model for water is addressed for a model disordered protein. We also assessed the stabilities of the residual secondary structure component interconversions in αS based on free energy calculations at the atomic level with dynamics using our recently developed theoretical strategy. To the best of our knowledge, this study presents the first detailed comparison of the structural properties linked directly to the conformational free energy landscapes of the monomeric wild-type and A53T mutant-type α-synuclein proteins in an aqueous solution environment. Results demonstrate that the β-sheet structure is significantly more altered than the helical structure upon A53T mutation of the monomeric wild-type αS protein in aqueous solution. The β-sheet content close to the mutation site in the N-terminal region is more abundant while the non-amyloid-β component (NAC) and C-terminal regions show a decrease in β-sheet abundance upon A53T mutation. Obtained results utilizing our new theoretical strategy show that the residual secondary structure conversion stabilities resulting in α-helix formation are not significantly affected by the mutation. Interestingly, the residual secondary structure conversion stabilities show that secondary structure conversions resulting in β-sheet formation are influenced by the A53T mutation and the most stable residual transition yielding β-sheet occurs directly from the coil structure. Long-range interactions detected between the NAC region and the N- or C-terminal regions of the wild-type αS disappear upon A53T mutation. The A53T mutant-type αS structures are thermodynamically more stable than those of the wild-type αS protein structures in aqueous solution. Overall, the higher propensity of the A53T mutant-type αS protein to aggregate in comparison to the wild-type αS protein is related to the increased β-sheet formation and lack of strong intramolecular long-range interactions in the N-terminal region in comparison to its wild-type form. The specific residual secondary structure component stabilities reported herein provide information helpful for designing and synthesizing small organic molecules that can block the β-sheet forming residues, which are reactive toward aggregation.