Dissecting contact potentials for proteins: relative contributions of individual amino acids

Amyloid Fibril Design: Limiting Structural Polymorphism in Alzheimer's Aβ Protofilaments

Nanoscale fibrils formed by amyloid peptides have a polymorphic character, adopting several types of molecular structures in similar growth conditions. As shown by experimental (e.g., solid-state NMR) and computational studies, amyloid fibril polymorphism hinders both the structural characterization of Alzheimer's Aβ amyloid protofilaments and fibrils at a molecular level, as well as the possible applications (e.g., development of drugs or biomarkers) that rely on similar, controlled molecular arrangements of the Aβ peptides in amyloid fibril structures. We have explored the use of several contact potentials for the efficient identification of minimal sequence mutations that could enhance the stability of specific fibril structures while simultaneously destabilizing competing topologies, controlling thus the amount of structural polymorphism in a rational way. We found that different types of contact potentials, while having only partial accuracy on their own, lead to similar results regarding ranking the compatibility of wild-type (WT) and mutated amyloid sequences with different fibril morphologies. This approach allows exhaustive screening and assessment of possible mutations and the identification of minimal consensus mutations that could stabilize fibrils with the desired topology at the expense of other topology types, a prediction that is further validated using atomistic molecular dynamics with explicit water molecules. We apply this two-step multiscale (i.e., residue and atomistic-level) approach to predict and validate mutations that could bias either parallel or antiparallel packing in the core Alzheimer's Aβ_9-40 amyloid fibril models based on solid-state NMR experiments. Besides shedding new light on the molecular origins of structural polymorphism in WT Aβ fibrils, our study could also lead to efficient tools for assisting future experimental approaches for amyloid fibril determination, and for the development of biomarkers or drugs aimed at interfering with the stability of amyloid fibrils, as well as for the future design of amyloid fibrils with a controlled (e.g., reduced) level of structural polymorphism.

SARAH Domain-Mediated MST2-RASSF Dimeric Interactions

RASSF enzymes act as key apoptosis activators and tumor suppressors, being downregulated in many human cancers, although their exact regulatory roles remain unknown. A key downstream event in the RASSF pathway is the regulation of MST kinases, which are main effectors of RASSF-induced apoptosis. The regulation of MST1/2 includes both homo- and heterodimerization, mediated by helical SARAH domains, though the underlying molecular interaction mechanism is unclear. Here, we study the interactions between RASSF1A, RASSF5, and MST2 SARAH domains by using both atomistic molecular simulation techniques and experiments. We construct and study models of MST2 homodimers and MST2-RASSF SARAH heterodimers, and we identify the factors that control their high molecular stability. In addition, we also analyze both computationally and experimentally the interactions of MST2 SARAH domains with a series of synthetic peptides particularly designed to bind to it, and hope that our approach can be used to address some of the challenging problems in designing new anti-cancer drugs.

We model the conformational changes and protein-protein interactions of enzymes involved in signaling along the Hippo pathway—a key molecular mechanism that controls the process of programmed cell death in eukaryotic cells, including cells affected by cancer. Combining modern computational modeling techniques with experimental information from X-ray crystallography and systems biology studies, can unveil detailed molecular interactions and lead to novel drugs. Here, we study the atomistic mechanisms and interactions between MST2 and RASSF-type kinases, through their respective SARAH domains—highly conserved, long, terminal α-helices, which play essential roles in the activation of MST kinases and, therefore, in modulating apoptosis. In spite of their key roles in mediating cell signaling pathways, there is little structural information available for the RASSF SARAH domains and their dimerization with the MST2 SARAH domains. In particular, the RASSF1A crystal structure is not available yet. Here, we model, refine and validate atomistic structural models of dimers of the RASSF1A and MST2 SARAH domains, studying the interaction and the dynamic behavior of these molecular complexes using homology modeling, docking and full atomistic molecular dynamics simulations. Experimentally, we validate our approach by designing a novel peptide that can disrupt effectively MST2 homo and hetero SARAH dimers.

Structure and dynamics of the fibronectin-III domains of Aplysia californica cell adhesion molecules

Due to their homophilic and heterophilic binding properties, cell adhesion molecules (CAMs) such as integrin, cadherin and the immunoglobulin superfamily CAMs are of primary importance in cell-cell and cell-substrate interactions, signalling pathways and other crucial biological processes. We study the molecular structures and conformational dynamics of the two fibronectin type III (Fn-III) extracellular domains of the Aplysia californica CAM (apCAM) protein, by constructing and probing an atomically-detailed structural model based on apCAM's homology with other CAMs. The stability and dynamic properties of the Fn-III domains, individually and in tandem, are probed and analysed using all-atom explicit-solvent molecular dynamics (MD) simulations and normal mode analysis of their corresponding elastic network models. The refined structural model of the Fn-III tandem of apCAM reveals a specific pattern of amino acid interactions that controls the stability of the β-sheet rich structure and could affect apCAM's response to physical or chemical changes of its environment. It also exposes the important role of several specific charged residues in modulating the structural properties of the linker segment connecting the two Fn-III domains, as well as of the inter-domain interface.

Breakout character of islet amyloid polypeptide hydrophobic mutations at the onset of type-2 diabetes

Toxic fibrillar aggregates of islet amyloid polypeptide (IAPP) appear as the physical outcome of a peptidic phase transition signaling the onset of type-2 diabetes mellitus in different mammalian species. In particular, experimentally verified mutations on the amyloidogenic segment 20-29 in humans, cats, and rats are highly correlated with the molecular aggregation propensities. Through a microcanonical analysis of the aggregation of IAPP_{20-29} isoforms, we show that a minimalist one-bead hydrophobic-polar continuum model for protein interactions properly quantifies those propensities from free-energy barriers. Our results highlight the central role of sequence-dependent hydrophobic mutations on hot spots for stabilization, and thus for the engineering, of such biological peptides.

Conformational dynamics and aggregation behavior of piezoelectric diphenylalanine peptides in an external electric field

Aromatic peptides including diphenylalanine (FF) have the capacity to self-assemble into ordered, biocompatible nanostructures with piezoelectric properties relevant to a variety of biomedical applications. Electric fields are commonly applied to align FF nanotubes, yet little is known about the effect of the electric field on the assembly process. Using all-atom molecular dynamics with explicit water molecules, we examine the response of FF monomers to the application of a constant external electric field over a range of intensities. We probe the aggregation mechanism of FF peptides, and find that the presence of even relatively weak fields can accelerate ordered aggregation, primarily by facilitating the alignment of individual molecular dipole moments. This is modulated by the conformational response of individual FF peptides (e.g., backbone stretching) and by the cooperative alignment of neighboring FF and water molecules. These observations may facilitate future studies on the controlled formation of nanostructured aggregates of piezoelectric peptides and the understanding of their electro-mechanical properties.

Alzheimer Aβ peptide interactions with lipid membranes: fibrils, oligomers and polymorphic amyloid channels

Fibrillar aggregates of misfolded amyloid proteins are involved in a variety of diseases such as Alzheimer disease (AD), type 2 diabetes, Parkinson, Huntington and prion-related diseases. In the case of AD amyloid β (Aβ) peptides, the toxicity of amyloid oligomers and larger fibrillar aggregates is related to perturbing the biological function of the adjacent cellular membrane. We used atomistic molecular dynamics (MD) simulations of Aβ_9–40 fibrillar oligomers modeled as protofilament segments, including lipid bilayers and explicit water molecules, to probe the first steps in the mechanism of Aβ-membrane interactions. Our study identified the electrostatic interaction between charged peptide residues and the lipid headgroups as the principal driving force that can modulate the further penetration of the C-termini of amyloid fibrils or fibrillar oligomers into the hydrophobic region of lipid membranes. These findings advance our understanding of the detailed molecular mechanisms and the effects related to Aβ-membrane interactions, and suggest a polymorphic structural character of amyloid ion channels embedded in lipid bilayers. While inter-peptide hydrogen bonds leading to the formation of β-strands may still play a stabilizing role in amyloid channel structures, these may also present a significant helical content in peptide regions (e.g., termini) that are subject to direct interactions with lipids rather than with neighboring Aβ peptides.

Scale-free behaviour of amino acid pair interactions in folded proteins

The protein structure is a cumulative result of interactions between amino acid residues interacting with each other through space and/or chemical bonds. Despite the large number of high resolution protein structures, the "protein structure code" has not been fully identified. Our manuscript presents a novel approach to protein structure analysis in order to identify rules for spatial packing of amino acid pairs in proteins. We have investigated 8706 high resolution non-redundant protein chains and quantified amino acid pair interactions in terms of solvent accessibility, spatial and sequence distance, secondary structure, and sequence length. The number of pairs found in a particular environment is stored in a cell in an 8 dimensional data tensor. When plotting the cell population against the number of cells that have the same population size, a scale free organization is found. When analyzing which amino acid paired residues contributed to the cells with a population above 50, pairs of Ala, Ile, Leu and Val dominate the results. This result is statistically highly significant. We postulate that such pairs form "structural stability points" in the protein structure. Our data shows that they are in buried α-helices or β-strands, in a spatial distance of 3.8-4.3Å and in a sequence distance >4 residues. We speculate that the scale free organization of the amino acid pair interactions in the 8D protein structure combined with the clear dominance of pairs of Ala, Ile, Leu and Val is important for understanding the very nature of the protein structure formation. Our observations suggest that protein structures should be considered as having a higher dimensional organization.

Conformational dynamics of human IAPP monomers

We study the conformational dynamics of the human Islet Amyloid Polypeptide (hIAPP) molecule - a 37 residue-long peptide associated to type 2 diabetes - using molecular dynamics (MD) simulations. We identify partially structured conformational states of the hIAPP monomer, categorized by both end-to-end distance and secondary structure, as suggested by previous experimental and computational studies. The MD trajectories of hIAPP are analyzed using data-driven methods, in particular principal component analysis, in order to identify preferred conformational states of the amylin monomer and to discuss their relative stability as compared to corresponding states in the amylin dimer. These potential hIAPP conformational states could be further tested and described experimentally, or in conjunction with modern computational analysis tools such as Markov state-based methods for extracting kinetics and thermodynamics from atomistic MD trajectories.

Molecular interactions of Alzheimer's Aβ protofilaments with lipid membranes

Amyloid fibrils and peptide oligomers play central roles in the pathology of Alzheimer's disease, type 2 diabetes, Parkinson's disease, Huntington's disease, and prion-related disease. Here, we investigate the molecular interactions between preformed amyloid β (Aβ) molecular protofilaments and lipid bilayer membranes, in the presence of explicit water molecules, using computational models and all-atom molecular dynamics. These interactions play an important role in the stability and function of both Aβ fibrils and the adjacent cellular membrane. Taking advantage of the symmetry-related and directional properties of the protofilaments, we build models that cover several relative protofilament-membrane orientations. Our molecular dynamics simulations reveal the relative contributions of different structural elements to the dynamics and stability of Aβ protofilament segments near membranes, and the first steps in the mechanism of fibril-membrane interactions. During this process, we observe a significant alteration of the side-chain contact pattern in protofilaments, although a fraction of the characteristic β-sheet content is preserved. As a major driving force, we identify the electrostatic interactions between Aβ charged side chains, including E22, D23, and K28, and lipid headgroups. Together with hydrogen bonding with atoms from lipid headgroups, these interactions can facilitate the penetration of hydrophobic C-terminal amino acids through the lipid headgroup region, which can finally lead both to further loss of the initial fibril structure and to local membrane-thinning effects. Our results may guide new experiments that could test the extent to which the structural features of water-formed amyloid fibrils are preserved, lost, or reshaped by membrane-mediated interactions.

Are Peptides Good Two-State Folders?

The folding kinetics of proteins is frequently single-exponential, as basins of folded and unfolded conformations are well separated by a high barrier. However, for relatively short peptides, a two-state character of folding is rather the exception than the rule. In this work, we use a Zwanzig-type model of protein conformational dynamics to study the dependence of folding kinetics on the protein chain length, M. The analysis is focused on the gap in the eigenvalue spectrum of the rate matrix that describes the protein's conformational dynamics. When there is a large gap between the two smallest in magnitude nonzero eigenvalues, the corresponding relaxation times have qualitatively different physical interpretations. The longest of these two times characterizes the interbasin equilibration (i.e., folding), whereas the second time characterizes the intrabasin relaxation. We derive approximate analytical solutions for the two eigenvalues that show how they depend on M. From these solutions, we infer that there is a large gap between the two, and thus, the kinetics is essentially single-exponential when M is large enough such that 2(M+1) is much larger than M(2).

Extending the PRIME model for protein aggregation to all 20 amino acids

We extend PRIME, an intermediate-resolution protein model previously used in simulations of the aggregation of polyalanine and polyglutamine, to the description of the geometry and energetics of peptides containing all 20 amino acid residues. The 20 amino acid side chains are classified into 14 groups according to their hydrophobicity, polarity, size, charge, and potential for side chain hydrogen bonding. The parameters for extended PRIME, called PRIME 20, include hydrogen-bonding energies, side chain interaction range and energy, and excluded volume. The parameters are obtained by applying a perceptron-learning algorithm and a modified stochastic learning algorithm that optimizes the energy gap between 711 known native states from the PDB and decoy structures generated by gapless threading. The number of independent pair interaction parameters is chosen to be small enough to be physically meaningful yet large enough to give reasonably accurate results in discriminating decoys from native structures. The most physically meaningful results are obtained with 19 energy parameters.

Explicit orientation dependence in empirical potentials and its significance to side-chain modeling

Protein structure modeling and prediction have important applications throughout the biological sciences, from the design of pharmaceuticals to the elucidation of enzyme mechanisms. At the core of most protein modeling is an energy function, the minimum of which represents the free energy "cost" for forming a correct protein structure. The most commonly used energy functions are knowledge-based statistical potential functions; that is, they are empirically derived from statistical analysis of a set of high-resolution protein structures. When that kind of potential function is constructed, the anisotropic orientation dependence between the interacting groups is a critical component for accurately representing key molecular interactions, such as those involved in protein side-chain packing. In the literature, however, many potential functions are limited in their ability to describe orientation dependence. In all-atom potentials, they typically ignore heterogeneous chemical-bond connectivity. In coarse-grained potentials, such as (semi)-residue-based potentials, the simplified representation of residues often reduces the sensitivity of the potential to side-chain orientation. Recently, in an effort to maximally capture the orientation dependence in side-chain interactions, a new type of all-atom statistical potential was developed: OPUS-PSP (potential derived from side-chain packing). The key feature of this potential is its explicit description of orientation dependence in molecular interactions, which is achieved with a basis set of 19 rigid-body blocks extracted from the chemical structures of 20 amino acid residues. This basis set is specifically designed to maximally capture the essential elements of orientation dependence in molecular packing interactions. The potential is constructed from the orientation-specific packing statistics of pairs of those blocks in a nonredundant structural database. On decoy set tests, OPUS-PSP significantly outperforms most of the existing knowledge-based potentials in terms of both its ability to recognize native structures and its consistency in achieving high Z scores across decoy sets. The application of OPUS-PSP to conformational modeling of side chains has led to another method, called OPUS-Rota. In terms of combined speed and accuracy, OPUS-Rota outperforms all of the other methods in modeling side-chain conformation. In this Account, we briefly outline the basic scheme of the OPUS-PSP potential and its application to side-chain modeling via OPUS-Rota. Future perspectives on the modeling of orientation dependence are also discussed. The computer programs for OPUS-PSP and OPUS-Rota can be downloaded at http://sigler.bioch.bcm.tmc.edu/MaLab . They are free for academic users.

Orientational distributions of contact clusters in proteins closely resemble those of an icosahedron

The orientational geometry of residue packing in proteins was studied in the past by superimposing clusters of neighboring residues with several simple lattices (Bagci et al., Proteins 2003;53:56-67; Raghunathan et al., Protein Sci 1997;6:2072-2083). In this work, instead of a lattice we use the regular polyhedron, the icosahedron, as the model to describe the orientational distribution of contacts in clusters derived from a high-resolution protein dataset (522 protein structures with high resolution < 1.5 A). We find that the order parameter (orientation function) measuring the angular overlap of directions in coordination clusters with directions of the icosahedron is 0.91, which is a significant improvement in comparison with the value 0.82 for the order parameter with the face-centered cubic (fcc) lattice. Close packing tendencies and patterns of residue packing in proteins are considered in detail and a theoretical description of these packing regularities is proposed.