Guizhao Liang

Comparative Molecular Dynamics Study of Human Islet Amyloid Polypeptide (IAPP) and Rat IAPP Oligomers

Human islet amyloid polypeptide (hIAPP or amylin) is a causative agent in pancreatic amyloid deposits found in patients with type 2 diabetes. The aggregation of full-length hIAPP(1-37) into small oligomeric species is increasingly believed to be responsible for cell dysfunction and death. However, rat IAPP (rIAPP(1-37)), which differs from hIAPP in only six of 37 residues, loses its aggregation ability to form toxic amyloid species. Atomic details of the effect of sequence on the structure and toxicity between the amyloidogenic, toxic hIAPP peptide and the nonamyloidogenic, nontoxic rIAPP peptide remain unclear. Here, we probe sequence-induced differences in structural stability, conformational dynamics, and driving forces between different hIAPP and rIAPP polymorphic forms from monomer to pentamer using molecular dynamics simulations. Simulations show that hIAPP forms from trimer to pentamer exhibit high structural stability with well-preserved in-register parallel β-sheet and the U-bend conformation. The hIAPP trimer appears to be a smallest minimal seed in solution. The stabilities of parallel hIAPP oligomers increase with the number of peptides. Conversely, replacement of hIAPP sequence by rIAPP sequence causes a significant loss of favorable interpeptide interactions in all rIAPP oligomers, destabilizing the C-terminal β-sheet, turn conformation, and overall stability. A less β-sheet-rich structure and a disturbed U-shaped topology exert a large energy penalty on the self-assemble of the rIAPP peptides into highly ordered, in-register β-sheet-rich protofibrils and fibrils, which explains the nonamyloidogenic activity of rIAPP. Moreover, the absence of interior water within the U-turn region in the well-packed higher-order hIAPP oligomers, not in the poorly packed rIAPP oligomers, also stabilizes peptide association. This work provides atomic details of the sequence-structure relationship between the amyloidogenic hIAPP and its analogues such as the nonamyloidogenic rIAPP and some mutants, which could help in the development of novel therapeutic agents to block the formation of toxic hIAPP oligomeric species for type 2 diabetes.

Molecular dynamics simulations of low-ordered alzheimer β-amyloid oligomers from dimer to hexamer on self-assembled monolayers.

Accumulation of small soluble oligomers of amyloid-β (Aβ) in the human brain is thought to play an important pathological role in Alzheimers disease. The interaction of these Aβ oligomers with cell membrane and other artificial surfaces is important for the understanding of Aβ aggregation and toxicity mechanisms. Here, we present a series of exploratory molecular dynamics (MD) simulations to study the early adsorption and conformational change of Aβ oligomers from dimer to hexamer on three different self-assembled monolayers (SAMs) terminated with CH(3), OH, and COOH groups. Within the time scale of MD simulations, the conformation, orientation, and adsorption of Aβ oligomers on the SAMs is determined by complex interplay among the size of Aβ oligomers, the surface chemistry of the SAMs, and the structure and dynamics of interfacial waters. Energetic analysis of Aβ adsorption on the SAMs reveals that Aβ adsorption on the SAMs is a net outcome of different competitions between dominant hydrophobic Aβ-CH(3)-SAM interactions and weak CH(3)-SAM-water interactions, between dominant electrostatic Aβ-COOH-SAM interactions and strong COOH-SAM-water interactions, and between comparable hydrophobic and electrostatic Aβ-OH-SAM interactions and strong OH-SAM-water interactions. Atomic force microscopy images also confirm that all of three SAMs can induce the adsorption and polymerization of Aβ oligomers. Structural analysis of Aβ oligomers on the SAMs shows a dramatic increase in structural stability and β-sheet content from dimer to trimer, suggesting that Aβ trimer could act as seeds for Aβ polymerization on the SAMs. This work provides atomic-level understanding of Aβ peptides at interface.

Structure-Thermodynamics-Antioxidant Activity Relationships of Selected Natural Phenolic Acids and Derivatives: An Experimental and Theoretical Evaluation

Phenolic acids and derivatives have potential biological functions, however, little is known about the structure-activity relationships and the underlying action mechanisms of these phenolic acids to date. Herein we investigate the structure-thermodynamics-antioxidant relationships of 20 natural phenolic acids and derivatives using DPPH• scavenging assay, density functional theory calculations at the B3LYP/6-311++G(d,p) levels of theory, and quantitative structure-activity relationship (QSAR) modeling. Three main working mechanisms (HAT, SETPT and SPLET) are explored in four micro-environments (gas-phase, benzene, water and ethanol). Computed thermodynamics parameters (BDE, IP, PDE, PA and ETE) are compared with the experimental radical scavenging activities against DPPH•. Available theoretical and experimental investigations have demonstrated that the extended delocalization and intra-molecular hydrogen bonds are the two main contributions to the stability of the radicals. The C = O or C = C in COOH, COOR, C = CCOOH and C = CCOOR groups, and orthodiphenolic functionalities are shown to favorably stabilize the specific radical species to enhance the radical scavenging activities, while the presence of the single OH in the ortho position of the COOH group disfavors the activities. HAT is the thermodynamically preferred mechanism in the gas phase and benzene, whereas SPLET in water and ethanol. Furthermore, our QSAR models robustly represent the structure-activity relationships of these explored compounds in polar media.

Engineering antimicrobial peptides with improved antimicrobial and hemolytic activities.

The rapid rise of antibiotic resistance in pathogens becomes a serious and growing threat to medicine and public health. Naturally occurring antimicrobial peptides (AMPs) are an important line of defense in the immune system against invading bacteria and microbial infection. In this work, we present a combined computational and experimental study of the biological activity and membrane interaction of the computationally designed Bac2A-based peptide library. We used the MARTINI coarse-grained molecular dynamics with adaptive biasing force method and the umbrella sampling technique to investigate the translocation of a total of 91 peptides with different amino acid substitutions through a mixed anionic POPE/POPG (3:1) bilayer and a neutral POPC bilayer, which mimic the bacterial inner membrane and the human red blood cell (hRBC) membrane, respectively. Potential of mean force (PMF, free energy profile) was obtained to measure the free energy barrier required to transfer the peptides from the bulk water phase to the water-membrane interface and to the bilayer interior. Different PMF profiles can indeed identify different membrane insertion scenarios by mapping out peptide-lipid energy landscapes, which are correlated with antimicrobial activity and hemolytic activity. Computationally designed peptides were further tested experimentally for their antimicrobial and hemolytic activities using bacteria growth inhibition assay and hemolysis assay. Comparison of PMF data with cell assay results reveals a good correlation of the peptides between predictive transmembrane activity and antimicrobial/hemolytic activity. Moreover, the most active mutants with the balanced substitutions of positively charged Arg and hydrophobic Trp residues at specific positions were discovered to achieve the improved antimicrobial activity while minimizing red blood cell lysis. Such substitutions provide more effective and cooperative interactions to distinguish the peptide interaction with different lipid bilayers. This work provides a useful computational tool to better understand the mechanism and energetics of membrane insertion of AMPs and to rationally design more effective AMPs.

Structural Polymorphism of Human Islet Amyloid Polypeptide (hIAPP) Oligomers Highlights the Importance of Interfacial Residue Interactions

A 37-residue of human islet amyloid polypeptide (hIAPP or amylin) is a main component of amyloid plaques found in the pancreas of ∼90% of type II diabetes patients. It is reported that hIAPP oligomers, rather than mature fibrils, are major toxic species responsible for pancreatic islet β-cell dysfunction and even cell death, but molecular structures of these oligomers remain elusive. In this work, on the basis of recent solid-state NMR and mass-per-length (MPL) data, we model a series of hIAPP oligomers with different β-layers (one, two, and three layers), symmetries (symmetry and asymmetry), and associated interfaces using molecular dynamics simulations. Three distinct interfaces formed by C-terminal β-sheet and C-terminal β-sheet (CC), N-terminal β-sheet and N-terminal β-sheet (NN), and C-terminal β-sheet and N-terminal β-sheet (CN) are identified to drive multiple cross-β-layers laterally associated together to form different amyloid organizations via different intermolecular interactions, in which the CC interface is dominated by polar interactions, the NN interface is dominated by hydrophobic interactions, and the CN interface is dominated by mixed polar and hydrophobic interactions. Overall, the structural stability of the proposed hIAPP oligomers is a result of delicate balance between maximization of favorable peptide-peptide interactions at the interfaces and optimization of solvation energy with globular structure. Different hIAPP oligomeric models indicate a general and intrinsic nature of amyloid polymorphism, driven by different interfacial side-chain interactions. The proposed models are compatible with recent experimental data in overall size, cross-section area, and molecular weight. A general hIAPP aggregation mechanism is proposed on the basis of our simulated models and experimental data.

Heterogeneous triangular structures of human islet amyloid polypeptide (amylin) with internal hydrophobic cavity and external wrapping morphology reveal the polymorphic nature of amyloid fibrils.

The misfolding and self-assembly of human islet amyloid polypeptide (hIAPP or amylin) into amyloid fibrils is pathologically linked to type II diabetes. The polymorphic nature of both hIAPP oligomers and fibrils has been implicated for the molecular origin of hIAPP toxicity to islet β-cells, but little is known about the polymorphic structure and dynamics of these hIAPP oligomers/fibrils at the atomic level. Here, we model the polymorphism of full length hIAPP(1-37) oligomers based on experimental data from solid-state NMR, mass per length, and electron microscopy using all-atom molecular dynamics simulation with explicit solvent. As an alternative to steric zipper structures mostly presented in the 2-fold symmetrical fibrils, the most striking structural feature of our proposed hIAPP oligomers is the presence of 3-fold symmetry along the fibril growth axis, in which three β-sheet-layers wind around a hydrophobic core with different periodicities. These 3-fold triangular hIAPP structures dramatically differ in the details of the β-layer assembly and core-forming sequence at the cross section, but all display a high structural stability with favorable layer-to-layer interactions. The 3-fold hIAPP structures can also serve as templates to present triple-stranded helical fibrils via peptide elongation, with different widths from 8.7 to 9.9 nm, twists from 2.8° to 11.8°, and pitches from 14.5 to 61.1 nm, in reasonable agreement with available biophysical data. Because similar 3-fold Aβ oligomers are also observed by both NMR experiments and our previous simulations, the 3-fold structure could be a general conformation to a broad range of amyloid oligomers and fibrils. Most importantly, unlike the conventional stacking sandwich model, the proposed wrapping-cord structures can readily accommodate more than three β-layers via a two dimension conformation search by rotating and translating the β-layers to adopt different favorable packings, which can greatly enrich the polymorphism of amyloid oligomers and fibrils.

Structural and Energetic Insight into the Cross-Seeding Amyloid Assemblies of Human IAPP and Rat IAPP

The misfolding and aggregation of human islet amyloid polypeptide (hIAPP or amylin) into small oligomers and large amyloid fibrils is believed to be responsible for the dysfunction and death of pancreatic β-cells in diabetes type II. However, rat IAPP (rIAPP), which differs from the hIAPP by only 6 of 37 residues, lacks the ability to form amyloid fibrils and to induce cell death. Little is known about the cross-sequence interactions and cross-seeding structures between hIAPP and rIAPP peptides. Herein using explicit-solvent molecular dynamics (MD) simulations, we modeled and simulated different heteroassemblies formed by the amyloidogenic hIAPP and the nonamyloidogenic rIAPP peptides. Simulations showed that the U-shaped hIAPP monomer and oligomers can interact with conformationally similar rIAPP to form stable complexes and to coassemble into heterogeneous structures. Stable heterointeractions between hIAPP and rIAPP were shown to arise from hydrophobic contacts and hydrogen bonds at the interface, particularly at N- and C-terminal β-sheet regions. Because of the enhanced interpeptide interactions at the interface, upon binding to hIAPP oligomers, the β-sheet population of rIAPP was greatly increased as compared to that of rIAPP alone. More importantly, the conformational energies of rIAPP monomers at the bound state were observed to be consistently higher than those of rIAPP monomers at the unbound state. However, rIAPP monomers enable one to adopt different conformations and follow different pathways for associating with hIAPP from the high energy of the bound state to the low energy of the unbound state, without encountering any large and abrupt energy barrier. In parallel, AFM study of cross-aggregation of hIAPP and rIAPP provided additional evidence that hIAPP can seed with rIAPP to form hybrid fibrils at all concentrations similar to pure hIAPP fibrils. This work demonstrates the existence of cross-interactions between the two different IAPP peptides, which provides an improved fundamental understanding of the cross-seeding of different amyloid sequences toward amyloid aggregation and toxicity mechanisms.

Comprehensive 3D-QSAR and binding mode of BACE-1 inhibitors using R-group search and molecular docking

The β-enzyme (BACE), which takes an active part in the processing of amyloid precursor protein, thereby leads to the production of amyloid-β (Aβ) in the brain, is a major therapeutic target against Alzheimers disease. The present study is aimed at studying 3D-QSAR of BACE-1 inhibitors and their binding mode. We build a 3D-QSAR model involving 99 training BACE-1 inhibitors based on Topomer CoMFA, and 26 molecules are employed to validate the external predictive power of the model obtained. The multiple correlation coefficients of fitting modeling, leave one out cross validation, and external validation are 0.966, 0.767 and 0.784, respectively. Topomer search is used as a tool for virtual screening in lead-like compounds of ZINC databases (2012); as a result, we successfully design 30 new molecules with higher activity than that of all training and test inhibitors. Besides, Surflex-dock is employed to explore binding mode of the inhibitors studied when acting with BACE-1 enzyme. The result shows that the inhibitors closely interact with the key sites related to ASP93, THR133, GLN134, ASP289, GLY291, THR292, THR293, ASN294, ARG296 and SER386 of BACE-1.

Membrane Interactions of hIAPP Monomer and Oligomer with Lipid Membranes by Molecular Dynamics Simulations

Interaction of human islet amyloid polypeptide (hIAPP) peptides with cell membrane is crucial for the understanding of amyloid toxicity associated with Type II diabetes (T2D). While it is known that the hIAPP-membrane interactions are considered to promote hIAPP aggregation into fibrils and induce membrane disruption, the membrane-induced conformation, orientation, aggregation, and adsorption behaviors of hIAPP peptides have not been well understood at the atomic level. Herein, we perform all-atom explicit-water molecular dynamics (MD) simulations to study the adsorption, orientation, and surface interaction of hIAPP aggregates with different sizes (monomer to tetramer) and conformations (monomer with α-helix and tetramer with β-sheet-rich U-turn) upon adsorption on the lipid bilayers composed of both pure zwitterionic POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) and mixed anionic POPC/POPE (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine) (3:1) lipids. MD simulation results show that hIAPP monomer with α-helical conformation and hIAPP pentamer with β-sheet conformation can adsorb on both POPC and POPC/POPE bilayers via a preferential orientation of N-terminal residues facing toward the bilayer surface. The hIAPP aggregates show stronger interactions with mixed POPC/POPE lipids than pure POPC lipids, consistent with experimental observation that hIAPP adsorption and fibrililation are enhanced on mixed lipid bilayers. While electrostatic interactions are main attractive forces to drive the hIAPP aggregates to adsorb on both bilayers, the introduction of the more hydrophilic head groups of POPE lipids further promote the formation of the interfacial hydrogen bonds. Complement to our previous studies of hIAPP aggregates in bulk solution, this computational work increases our knowledge about the mechanism of amyloid peptide-membrane interactions that is central to the understanding the progression of all amyloid diseases.

An Index for Characterization of Natural and Non-Natural Amino Acids for Peptidomimetics

Bioactive peptides and peptidomimetics play a pivotal role in the regulation of many biological processes such as cellular apoptosis, host defense, and biomineralization. In this work, we develop a novel structural matrix, Index of Natural and Non-natural Amino Acids (NNAAIndex), to systematically characterize a total of 155 physiochemical properties of 22 natural and 593 non-natural amino acids, followed by clustering the structural matrix into 6 representative property patterns including geometric characteristics, H-bond, connectivity, accessible surface area, integy moments index, and volume and shape. As a proof-of-principle, the NNAAIndex, combined with partial least squares regression or linear discriminant analysis, is used to develop different QSAR models for the design of new peptidomimetics using three different peptide datasets, i.e., 48 bitter-tasting dipeptides, 58 angiotensin-converting enzyme inhibitors, and 20 inorganic-binding peptides. A comparative analysis with other QSAR techniques demonstrates that the NNAAIndex method offers a stable and predictive modeling technique for in silico large-scale design of natural and non-natural peptides with desirable bioactivities for a wide range of applications.