On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Helix-to-sheet transition of the Aβ42 peptide revealed using an enhanced sampling strategy and Markov state model

The self-assembly of Aβ peptides into toxic oligomers and fibrils is the primary cause of Alzheimer's disease. Moreover, the conformational transition from helix to sheet is considered a crucial step in the aggregation of Aβ peptides. However, the structural details of this process still remain unclear due to the heterogeneity and transient nature of the Aβ peptides. In this study, we developed an enhanced sampling strategy that combines artificial neural networks (ANN) with metadynamics to explore the conformational space of the Aβ42 peptides. The strategy consists of two parts: applying ANN to optimize CVs and conducting metadynamics based on the resulting CVs to sample conformations. The results showed that this strategy achieved better sampling performance in terms of the distribution of sampled conformations. The sampling efficiency is increased by 10-fold compared to our previous Hamiltonian Exchange Molecular Dynamics (MD) and by 1000-fold compared to ordinary MD. Based on the sampled conformations, we constructed a Markov state model to understand the detailed transition process. The intermediate states in this process are identified, and the connecting paths are analyzed. The conformational transitions in D23-K28 and M35-V40 are proven to be crucial for aggregation. These results are helpful in clarifying the mechanism and process of Aβ42 peptide aggregation. D23-K28 and M35-V40 can be identified as potential targets for screening and designing inhibitors of Aβ peptide aggregation.

CoVAMPnet: Comparative Markov State Analysis for Studying Effects of Drug Candidates on Disordered Biomolecules

Computational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here, we developed a comparative Markov state analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered Aβ42 peptide involved in Alzheimer's disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of Aβ42 by interacting nonspecifically with charged residues. SPA impacted Aβ42 more than TMP, protecting α-helices and suppressing the formation of aggregation-prone β-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on Aβ42 and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target biomolecules other than Aβ peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules.

Importance of Inter-residue Contacts for Understanding Protein Folding and Unfolding Rates, Remote Homology, and Drug Design

Inter-residue interactions in protein structures provide valuable insights into protein folding and stability. Understanding these interactions can be helpful in many crucial applications, including rational design of therapeutic small molecules and biologics, locating functional protein sites, and predicting protein-protein and protein-ligand interactions. The process of developing machine learning models incorporating inter-residue interactions has been improved recently. This review highlights the theoretical models incorporating inter-residue interactions in predicting folding and unfolding rates of proteins. Utilizing contact maps to depict inter-residue interactions aids researchers in developing computer models for detecting remote homologs and interface residues within protein-protein complexes which, in turn, enhances our knowledge of the relationship between sequence and structure of proteins. Further, the application of contact maps derived from inter-residue interactions is highlighted in the field of drug discovery. Overall, this review presents an extensive assessment of the significant models that use inter-residue interactions to investigate folding rates, unfolding rates, remote homology, and drug development, providing potential future advancements in constructing efficient computational models in structural biology.

Hexadecanoic acid analogs as potential CviR-mediated quorum sensing inhibitors in Chromobacterium violaceum: an in silico study

Chromobacterium violaceum is a Gram-negative, rod-shaped and opportunistic human pathogen. C. violaceum is resistant to various antibiotics due to the production of quorum sensing (QS)-controlled virulence factor and biofilm formation. Hence, we need to find alternative strategies to overcome the antimicrobial resistance and biofilm formation in Gram-negative bacteria. QS is a mechanism in which bacteria's ability to regulate the virulence factors and biofilm formations leads to disease progression. Previously, hexadecanoic acid was identified as a CviR-mediated quorum-sensing inhibitor. In this study, we aimed to discover potential analogs of hexadecanoic acid as a CviR-mediated quorum-sensing inhibitor against C. violaceum by using ADME/T prediction, density functional theory, molecular docking, molecular dynamics and free energy binding calculations. ADME/T properties predicted for analogs were acceptable for human oral absorption and feasibility. The highest occupied molecular orbitals and lowest unoccupied molecular orbitals gap energies predicted and found oleic acid with -0.3748 energies. Docosatrienoic acid exhibited the highest binding affinity -8.15 Kcal/mol and strong and stable interactions with the amino acid residues on the active site of the CviR protein. These compounds on MD simulations for 100 ns show strong hydrogen-bonding interactions with the protein and remain stable inside the active site. Our results suggest hexadecanoic acid analogs could serve as anti-QS and anti-biofilm molecules for treating C. violaceum infections. However, further validation and investigation of these inhibitors against CviR are needed to claim their candidacy for clinical trials.Communicated by Ramaswamy H. Sarma.

Biophysical Properties of the Fibril Structure of the Toxic Conformer of Amyloid-β42: Characterization by Atomic Force Microscopy in Liquid and Molecular Docking

Alzheimer's disease is associated with the aggregation of the misfolded neuronal peptide, amyloid-β42 (Aβ42). Evidence has suggested that several reasons are responsible for the toxicity caused by the aggregation of Aβ42, including the conformational restriction of Aβ42. In this study, one of the toxic conformers of Aβ42, which contains a Glu-to-Pro substitution (E22P-Aβ42), was explored using atomic force microscopy and molecular docking to study the aggregation dynamics. We proposed a systematic model of fibril formation to better understand the molecular basis of conformational transitions in the Aβ42 species. Our results demonstrated the formation of amorphous aggregates in E22P-Aβ42 that are stem-based, network-like structures, while the formation of mature fibrils occurred in the less toxic conformer of Aβ42, E22-Aβ42, that are sphere-like flexible structures. A comparison was made between the biophysical properties of E22P-Aβ42 and E22-Aβ42 that revealed that E22P-Aβ42 had greater stiffness, dihedral angle, number of β sheets involved, and elasticity, compared with E22-Aβ42. These findings will have considerable implications toward our understanding of the structural basis of the toxicity caused by conformational diversity in Aβ42 species.

Structural analysis of human G-protein-coupled receptor 17 ligand binding sites

The human G protein coupled membrane receptor (GPR17), the sensor of brain damage, is identified as a biomarker for many neurological diseases. In human brain tissue, GPR17 exist in two isoforms, long and short. While cryo-electron microscopy technology has provided the structure of the long isoform of GPR17 with Gi complex, the structure of the short isoform and its activation mechanism remains unclear. Recently, we theoretically modeled the structure of the short isoform of GPR17 with Gi signaling protein and identified novel ligands. In the present work, we demonstrated the presence of two distinct ligand binding sites in the short isoform of GPR17. The molecular docking of GPR17 with endogenous (UDP) and synthetic ligands (T0510.3657, MDL29950) found the presence of two distinct binding pockets. Our observations revealed that endogenous ligand UDP can bind stronger in two different binding pockets as evidenced by glide and autodock vina scores, whereas the other two ligand's binding with GPR17 has less docking score. The analysis of receptor-UDP interactions shows complexes' stability in the lipid environment by 100 ns atomic molecular dynamics simulations. The amino acid residues VAL83, ARG87, and PHE111 constitute ligand binding site 1, whereas site 2 constitutes ASN67, ARG129, and LYS232. Root mean square fluctuation analysis showed the residues 83, 87, and 232 with higher fluctuations during molecular dynamics simulation in both binding pockets. Our findings imply that the residues of GPR17's two binding sites are crucial, and their interaction with UDP reveals the protein's hidden signaling and communication properties. Furthermore, this finding may assist in the development of targeted therapies for the treatment of neurological diseases.

In Silico and In Vitro Studies of Benzothiazole-Isothioureas Derivatives as a Multitarget Compound for Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Inhibiting acetylcholinesterase (AChE), amyloid beta (Aβ1-42) aggregation and avoiding the oxidative stress could prevent the progression of AD. Benzothiazole groups have shown neuroprotective activity whereas isothioureas groups act as AChE inhibitors and antioxidants. Therefore, 22 benzothiazole-isothiourea derivatives (3a-v) were evaluated by docking simulations as inhibitors of AChE and Aβ1-42 aggregation. In silico studies showed that 3f, 3r and 3t had a delta G (ΔG) value better than curcumin and galantamine on Aβ1-42 and AChE, respectively. The physicochemical and pharmacokinetics predictions showed that only 3t does not violate Lipinski's rule of five, though it has moderated cytotoxicity activity. Then, 3f, 3r and 3t were synthetized and chemically characterized for their in vitro evaluation including their antioxidant activity and their cytotoxicity in PC12 cells. 3r was able to inhibit AChE, avoid Aβ1-42 aggregation and exhibit antioxidant activity; nevertheless, it showed cytotoxic against PC12 cells. Compound 3t showed the best anti-Aβ1-42 aggregation and inhibitory AChE activity and, despite that predictor, showed that it could be cytotoxic; in vitro with PC12 cell was negative. Therefore, 3t could be employed as a scaffold to develop new molecules with multitarget activity for AD and, due to physicochemical and pharmacokinetics predictions, it could be administered in vivo using liposomes due to is not able to cross the BBB.

Cholic acid inhibits amyloid fibrillation: Interplay of protonation and deprotonation

Amyloidopathies are the consequence of misfolding with subsequent aggregation affecting people worldwide. Irrespective of speedy advancement in the field of therapeutics no agent for treating amyloidopathies has been discovered and thus targeting amyloid fibrillation process via repositioning of small molecules can be fruitful. According to previous reports potential amyloid inhibitors possess unique features like, hydrophobicity, aromaticity, charge etc. Herein, we have explored the effect of Cholic acid (CA) on amyloid fibrillation irrespective of the charge (determined by Zetasizer) using four proteins Human Serum Albumin, Bovine Serum Albumin, Human Insulin and Beta-lactoglobulin (HSA, BSA, HI and BLG) employing biophysical, imaging and computational techniques. ThT results revealed that CA in both protonated and deprotonated form is potent to curb HSA, BSA, BLG aggregation ~50% and HI aggregation ~96% in a dose dependent manner (in accord with CD, ANS and Congo red assay). Interestingly, CA treated samples displayed reduced cytotoxicity (Hemolytic assay) with altered morphology (TEM) and mechanism behind inhibition may be the interaction of CA with proteins via hydrophobic interactions and hydrogen bonding (supported by molecular docking results). This study proved CA (irrespective of the pH) a potential inhibitor of amyloidosis thus can be helpful in generalizing and repurposing the related drugs/compounds for their anti-aggregation behavior as an implication towards treating amyloidopathies.

Conformation-Dependent Influences of Hydrophobic Amino Acids in Two In-Register Parallel β-Sheet Amyloids, an α-Synuclein Amyloid and a Local Structural Model of PrPSc

Prions are unconventional pathogens that encode the pathogenic information in conformations of the constituent abnormal isoform of prion protein (PrP^Sc), independently of the nucleotide genome. Therefore, conformational diversity of PrP^Sc underlies the existence of many prion strains and species barriers of prions, although the conformational information is extremely limited. Interestingly, differences between polymorphic or species-specific residues responsible for the species/strain barriers are often caused by conservative replacements between hydrophobic amino acids. This implies that subtle differences among hydrophobic amino acids are significant for PrP^Sc structures. Here we analyzed the influence of different hydrophobic residues on the structures of an in-register parallel β-sheet amyloid of α-synuclein (αSyn) using molecular dynamics (MD) simulation and applied the knowledge from the αSyn amyloid to modeling a local structure of human PrP^Sc encompassing residues 107-143. We found that mutations equivalent to polymorphisms that cause transmission barriers substantially affect the stabilities of the local structures; for example, the G127V mutation, which makes the host resistant to various human prion diseases, greatly destabilized the local structure of the model amyloid. Our study indicates that subtle differences among hydrophobic side chains can considerably affect the interaction network, including hydrogen bonds, and demonstrates specifically how and in what structures hydrophobic residues can exert unique effects on in-register parallel β-sheet amyloids.

Aggregation-Prone Structural Ensembles of Transthyretin Collected With Regression Analysis for NMR Chemical Shift

Monomer dissociation and subsequent misfolding of the transthyretin (TTR) is one of the most critical causative factors of TTR amyloidosis. TTR amyloidosis causes several human diseases, such as senile systemic amyloidosis and familial amyloid cardiomyopathy/polyneuropathy; therefore, it is important to understand the molecular details of the structural deformation and aggregation mechanisms of TTR. However, such molecular characteristics are still elusive because of the complicated structural heterogeneity of TTR and its highly sensitive nature to various environmental factors. Several nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) studies of TTR variants have recently reported evidence of transient aggregation-prone structural states of TTR. According to these studies, the stability of the DAGH β-sheet, one of the two main β-sheets in TTR, is a crucial determinant of the TTR amyloidosis mechanism. In addition, its conformational perturbation and possible involvement of nearby structural motifs facilitates TTR aggregation. This study proposes aggregation-prone structural ensembles of TTR obtained by MD simulation with enhanced sampling and a multiple linear regression approach. This method provides plausible structural models that are composed of ensemble structures consistent with NMR chemical shift data. This study validated the ensemble models with experimental data obtained from circular dichroism (CD) spectroscopy and NMR order parameter analysis. In addition, our results suggest that the structural deformation of the DAGH β-sheet and the AB loop regions may correlate with the manifestation of the aggregation-prone conformational states of TTR. In summary, our method employing MD techniques to extend the structural ensembles from NMR experimental data analysis may provide new opportunities to investigate various transient yet important structural states of amyloidogenic proteins.

An Overview of Several Inhibitors for Alzheimer's Disease: Characterization and Failure

Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.

Molecular dynamics study of conformation transition from helix to sheet of Aβ42 peptide

Aβ42 peptides can form helix and sheet structure under different conditions. The conformational conversion is closely associated with Aβ peptides aggregation and their neurotoxicity. But the transition from helix to sheet is not be clearly understood. In this study we performed microsecond timescale MD simulations of Aβ42 peptide to investigate the conformation transition from α-helix to β-sheet. Markov state model (MSM) was built to facilitate identification of crucial intermediate states and possible transition pathway. Based on the analysis, we found that the region Y10-A21 in the middle of Aβ42 peptide plays an initial role in this transition. MSM model revealed that the collapse of helical structure in this region might trigger the formation of sheet structure. Moreover, we further simulated the aggregation of Aβ42 peptides with different conformations. We found that the Aβ42 peptides forming sheet structure have higher aggregation potential compared with peptides with helix structure. These results demonstrate that we can prevent the aggregation of Aβ42 peptides by stabilizing the helix structure in the region of Y10-A21. In addition, this study provides new insight into better understanding the conformational transition and aggregation of Aβ42 peptides.

Exploring the Early Stages of the Amyloid Aβ(1-42) Peptide Aggregation Process: An NMR Study

Alzheimer’s disease (AD) is a neurodegenerative pathology characterized by the presence of neurofibrillary tangles and amyloid plaques, the latter mainly composed of Aβ(1–40) and Aβ(1–42) peptides. The control of the Aβ aggregation process as a therapeutic strategy for AD has prompted the interest to investigate the conformation of the Aβ peptides, taking advantage of computational and experimental techniques. Mixtures composed of systematically different proportions of HFIP and water have been used to monitor, by NMR, the conformational transition of the Aβ(1–42) from soluble α-helical structure to β-sheet aggregates. In the previous studies, 50/50 HFIP/water proportion emerged as the solution condition where the first evident Aβ(1–42) conformational changes occur. In the hypothesis that this solvent reproduces the best condition to catch transitional helical-β-sheet Aβ(1–42) conformations, in this study, we report an extensive NMR conformational analysis of Aβ(1–42) in 50/50 HFIP/water v/v. Aβ(1–42) structure was solved by us, giving evidence that the evolution of Aβ(1–42) peptide from helical to the β-sheet may follow unexpected routes. Molecular dynamics simulations confirm that the structural model we calculated represents a starting condition for amyloid fibrils formation.

Computational Analysis of the Interactions between the S100B Extracellular Chaperone and Its Amyloid β Peptide Client

S100B is an astrocytic extracellular Ca²⁺-binding protein implicated in Alzheimer’s disease, whose role as a holdase-type chaperone delaying Aβ₄₂ aggregation and toxicity was recently uncovered. Here, we employ computational biology approaches to dissect the structural details and dynamics of the interaction between S100B and Aβ₄₂. Driven by previous structural data, we used the Aβ_25–35 segment, which recapitulates key aspects of S100B activity, as a starting guide for the analysis. We used Haddock to establish a preferred binding mode, which was studied with the full length Aβ using long (1 μs) molecular dynamics (MD) simulations to investigate the structural dynamics and obtain representative interaction complexes. From the analysis, Aβ-Lys28 emerged as a key candidate for stabilizing interactions with the S100B binding cleft, in particular involving a triad composed of Met79, Thr82 and Glu86. Binding constant calculations concluded that coulombic interactions, presumably implicating the Lys28(Aβ)/Glu86(S100B) pair, are very relevant for the holdase-type chaperone activity. To confirm this experimentally, we examined the inhibitory effect of S100B over Aβ aggregation at high ionic strength. In agreement with the computational predictions, we observed that electrostatic perturbation of the Aβ-S100B interaction decreases anti-aggregation activity. Altogether, these findings unveil features relevant in the definition of selectivity of the S100B chaperone, with implications in Alzheimer’s disease.

Insights in the structural understanding of amyloidogenicity and mutation-led conformational dynamics of amyloid beta (Aβ) through molecular dynamics simulations and principal component analysis

Abnormal protein aggregation in the nervous tissue leads to several neurodegenerative disorders like Alzheimer's disease (AD). In AD, accumulation of the amyloid beta (Aβ) peptide is proposed to be an early important event in pathogenesis. Significant research efforts are devoted so as to understand the Aβ misfolding and aggregation. Molecular dynamics (MD) simulations complement experiments and provide structural information at the atomic level with dynamics without facing the same experimental limitations. Artificial missense mutations are employed experimentally and computationally for providing insights into the structure-function relationships of amyloid-β in relation to the pathologies of AD. Present work describes the MD simulations for 100 ns so as to probe the structural and conformational dynamics of Aβ1-42 assemblies and its mutants. Essential dynamics analysis with respect to conformational deviation of C_α was evaluated to identify the largest residual fluctuation of C_α. Conformational stability of all Aβ mutants was analyzed by computing RMSD, deciphering the convergence is reached in the last 20 ns in all replicas. To highlight the low frequency mode of motion corresponding to the highest amplitude, atomic displacements seen in trajectory, distance pair principal component analysis (dpPCA) was performed, which adumbrated mutations strongly affect the conformational dynamics of investigated model when compared with wild type. Dynamic cross correlation matrix (DCCM) also suggests the conserved interactions of wild Aβ and imply mutations in β3-β4 loop region induce deformity and residual fluctuations as observed from simulation. Present study indicate the mutational energy landscape which induces deformation leading to fibrillation.Communicated by Ramaswamy H. Sarma.

A Novel Nanosystem Realizing Curcumin Delivery Based on Fe3O4@Carbon Dots Nanocomposite for Alzheimer's Disease Therapy

Alzheimer’s disease (AD) is the most common neurodegenerative disease, which seriously affects human health but lacks effective treatment methods. Amyloid β (Aβ) aggregates are considered a possible target for AD treatment. Evidence is increasingly showing that curcumin (CUR) can partly protect cells from Aβ-mediated neurotoxicity by inhibiting Aβ aggregation. However, the efficiency of targeted cellular uptake and bioavailability of CUR is very low due to its poor stability and water-solubility. In order to better improve the cell uptake efficiency and bioavailability of CUR and reduce the cytotoxicity of high-dose CUR, a novel CUR delivery system for AD therapy has been constructed based on the employment of the Fe₃O₄@carbon dots nanocomposite (Fe₃O₄@CDs) as the carrier. CUR-Fe₃O₄@CDs have a strong affinity toward Aβ and effectively inhibit extracellular Aβ fibrillation. In addition, CUR-Fe₃O₄@CDs can inhibit the production of reactive oxygen species (ROS) mediated by Aβ fibrils and the corresponding neurotoxicity in PC12 cells. More importantly, it can restore nerve damage and maintained neuronal morphology. These results indicate that the application of CUR-Fe₃O₄@CDs provides a promising platform for the treatment of AD.