A Minima Hopping Study of All-Atom Protein Folding and Structure Prediction

Mutation-induced change in chignolin stability from π-turn to α-turn

A mutation from threonine to proline at the eighth residue in chignolin changes π-turn to α-turn.

Low-Energy Phases of Bi Monolayer Predicted by Structure Search in Two Dimensions

We employ an ab-initio structure search algorithm to explore the configurational space of bismuth in quasi-two dimensions. A confinement potential is introduced to restrict the movement of atoms within a predefined thickness to find the stable and metastable forms of monolayer Bi. In addition to the two known low-energy structures (puckered monoclinic and buckled hexagonal), our calculations predict three new phases: α, β, and γ. Each phase exhibits peculiar electronic properties, ranging from metallic (α and γ) to semiconducting (puckered monoclinic, buckled hexagonal, and β) monolayers. Topologically nontrivial features are predicted for buckled hexagonal and γ phases. We also remark on the role of 5d electrons on the electronic properties of Bi monolayer. We conclude that Bi provides a rich playground to study distortion-mediated metal-insulator phase transitions in quasi-2D.

Analysis of molecular dynamics simulations of 10-residue peptide, chignolin, using statistical mechanics: Relaxation mode analysis and three-dimensional reference interaction site model theory

Molecular dynamics simulation is a fruitful tool for investigating the structural stability, dynamics, and functions of biopolymers at an atomic level. In recent years, simulations can be performed on time scales of the order of milliseconds using special purpose systems. Since the most stable structure, as well as meta-stable structures and intermediate structures, is included in trajectories in long simulations, it is necessary to develop analysis methods for extracting them from trajectories of simulations. For these structures, methods for evaluating the stabilities, including the solvent effect, are also needed. We have developed relaxation mode analysis to investigate dynamics and kinetics of simulations based on statistical mechanics. We have also applied the three-dimensional reference interaction site model theory to investigate stabilities with solvent effects. In this paper, we review the results for designing amino-acid substitution of the 10-residue peptide, chignolin, to stabilize the misfolded structure using these developed analysis methods.

Analysis of Structural Stability of Chignolin

We discuss the stability of an entire protein and the influence of main chains and side chains of individual amino acids to investigate the protein-folding mechanism. For this purpose, we calculated the solvation free-energy contribution of individual atoms using the three-dimensional reference interaction site model with the atomic decomposition method. We generated structures of chignolin miniprotein by a molecular dynamics simulation and classified them into six types: native 1, native 2, misfolded 1, misfolded 2, intermediate, and unfolded states. The total energies of the native (-171.1 kcal/mol) and misfolded (-171.2 kcal/mol) states were almost the same and lower than those of the intermediate (-158.5 kcal/mol) and unfolded (-148.1 kcal/mol) states; however, their components were different. In the native state, the side-chain interaction between Thr6 and Thr8 is important for the formation of π-turn. On the other hand, the hydrogen bonds between the atoms of the main chains in the misfolded state become stronger than those in the intermediate state.

Adaptive Assembly: Maximizing the Potential of a Given Functional Peptide with a Tailor-Made Protein Scaffold

Protein engineering that exploits known functional peptides holds great promise for generating novel functional proteins. Here we propose a combinatorial approach, termed adaptive assembly, which provides a tailor-made protein scaffold for a given functional peptide. A combinatorial library was designed to create a tailor-made scaffold, which was generated from β hairpins derived from a 10-residue minimal protein "chignolin" and randomized amino acid sequences. We applied adaptive assembly to a peptide with low affinity for the Fc region of human immunoglobulin G, generating a 54-residue protein AF.p17 with a 40,600-fold enhanced affinity. The crystal structure of AF.p17 complexed with the Fc region revealed that the scaffold fixed the active conformation with a unique structure composed of a short α helix, β hairpins, and a loop-like structure. Adaptive assembly can take full advantage of known peptides as assets for generating novel functional proteins.

Comparison of volume and surface area nonpolar solvation free energy terms for implicit solvent simulations

Implicit solvent models for molecular dynamics simulations are often composed of polar and nonpolar terms. Typically, the nonpolar solvation free energy is approximated by the solvent-accessible-surface area times a constant factor. More sophisticated approaches incorporate an estimate of the attractive dispersion forces of the solvent and∕or a solvent-accessible volume cavitation term. In this work, we confirm that a single volume-based nonpolar term most closely fits the dispersion and cavitation forces obtained from benchmark explicit solvent simulations of fixed protein conformations. Next, we incorporated the volume term into molecular dynamics simulations and find the term is not universally suitable for folding up small proteins. We surmise that while mean-field cavitation terms such as volume and SASA often tilt the energy landscape towards native-like folds, they also may sporadically introduce bottlenecks into the folding pathway that hinder the progression towards the native state.

Tracing primordial protein evolution through structurally guided stepwise segment elongation

The understanding of how primordial proteins emerged has been a fundamental and longstanding issue in biology and biochemistry. For a better understanding of primordial protein evolution, we synthesized an artificial protein on the basis of an evolutionary hypothesis, segment-based elongation starting from an autonomously foldable short peptide. A 10-residue protein, chignolin, the smallest foldable polypeptide ever reported, was used as a structural support to facilitate higher structural organization and gain-of-function in the development of an artificial protein. Repetitive cycles of segment elongation and subsequent phage display selection successfully produced a 25-residue protein, termed AF.2A1, with nanomolar affinity against the Fc region of immunoglobulin G. AF.2A1 shows exquisite molecular recognition ability such that it can distinguish conformational differences of the same molecule. The structure determined by NMR measurements demonstrated that AF.2A1 forms a globular protein-like conformation with the chignolin-derived β-hairpin and a tryptophan-mediated hydrophobic core. Using sequence analysis and a mutation study, we discovered that the structural organization and gain-of-function emerged from the vicinity of the chignolin segment, revealing that the structural support served as the core in both structural and functional development. Here, we propose an evolutionary model for primordial proteins in which a foldable segment serves as the evolving core to facilitate structural and functional evolution. This study provides insights into primordial protein evolution and also presents a novel methodology for designing small sized proteins useful for industrial and pharmaceutical applications.

Low-energy polymeric phases of alanates

Low-energy structures of alanates are currently known to be described by patterns of isolated, nearly ideal tetrahedral [AlH4] anions and metal cations. We discover that the novel polymeric motif recently proposed for LiAlH4 plays a dominant role in a series of alanates, including LiAlH4, NaAlH4, KAlH4, Mg(AlH4)2, Ca(AlH4)2, and Sr(AlH4)2. In particular, most of the low-energy structures discovered for the whole series are characterized by networks of corner-sharing [AlH6] octahedra, forming wires and/or planes throughout the materials. Finally, for Mg(AlH4)2 and Sr(AlH4)2, we identify two polymeric phases to be lowest in energy at low temperatures.

Evolutionary-inspired probabilistic search for enhancing sampling of local minima in the protein energy surface

Background

Despite computational challenges, elucidating conformations that a protein system assumes under physiologic conditions for the purpose of biological activity is a central problem in computational structural biology. While these conformations are associated with low energies in the energy surface that underlies the protein conformational space, few existing conformational search algorithms focus on explicitly sampling low-energy local minima in the protein energy surface.

Methods

This work proposes a novel probabilistic search framework, PLOW, that explicitly samples low-energy local minima in the protein energy surface. The framework combines algorithmic ingredients from evolutionary computation and computational structural biology to effectively explore the subspace of local minima. A greedy local search maps a conformation sampled in conformational space to a nearby local minimum. A perturbation move jumps out of a local minimum to obtain a new starting conformation for the greedy local search. The process repeats in an iterative fashion, resulting in a trajectory-based exploration of the subspace of local minima.

Results and conclusions

The analysis of PLOW's performance shows that, by navigating only the subspace of local minima, PLOW is able to sample conformations near a protein's native structure, either more effectively or as well as state-of-the-art methods that focus on reproducing the native structure for a protein system. Analysis of the actual subspace of local minima shows that PLOW samples this subspace more effectively that a naive sampling approach. Additional theoretical analysis reveals that the perturbation function employed by PLOW is key to its ability to sample a diverse set of low-energy conformations. This analysis also suggests directions for further research and novel applications for the proposed framework.

Novel structural motifs in low energy phases of LiAlH4

We identify a class of novel low energy phases of the hydrogen storage material LiAlH4 by using the ab initio minima hopping crystal structure prediction method. These phases are, unlike previous predictions and known structures of similar materials, characterized by polymeric networks consisting of Al atoms interlinked with H atoms. The most stable structure is a layered ionic crystal with P21/c symmetry, and it has lower free energy than the previously reported structure over a wide range of temperatures. Furthermore, we carry out x-ray diffraction, phonon, and GW band-structure analysis in order to characterize this phase. Its experimental synthesis would have profound implications for the study of dehydrogenation and rehydrogenation processes and the stability problem of LiAlH4 for hydrogen storage applications.

Turn-directed folding dynamics of β-hairpin-forming de novo decapeptide Chignolin

Realistic mechanistic pictures of β-hairpin formation, offering valuable insights into some of the key early events in protein folding, are accessible through short designed polypeptides as they allow atomic-level scrutiny through simulations. Here, we present a detailed picture of the dynamics and mechanism of β-hairpin formation of Chignolin, a de novo decapeptide, using extensive, unbiased molecular dynamics simulations. The results provide clear evidence for turn-directed broken-zipper folding and reveal details of turn nucleation and cooperative progression of turn growth, hydrogen-bond formations, and eventual packing of the hydrophobic core. Further, we show that, rather than driving folding through hydrophobic collapse, cross-strand side-chain packing could in fact be rate-limiting as packing frustrations can delay formation of the native hydrophobic core prior to or during folding and even cause relatively long-living misfolded or partially folded states that may nucleate aggregative events in more complex situations. The results support the increasing evidence for turn-centric folding mechanisms for β-hairpin formation suggested recently for GB1 and Peptide 1 based on experiments and simulations but also point to the need for similar examinations of polypeptides with larger numbers of cross-strand hydrophobic residues.

High-pressure structures of disilane and their superconducting properties

A systematic ab initio search for low-enthalpy phases of disilane (Si2H6) at high pressures was performed based on the minima hopping method. We found a novel metallic phase of disilane with Cmcm symmetry, which is enthalpically more favorable than the recently proposed structures of disilane up to 280 GPa, but revealing compositional instability below 190 GPa. The Cmcm phase has a moderate electron-phonon coupling yielding a superconducting transition temperature T(c) of around 20 K at 100 GPa, decreasing to 13 K at 220 GPa. These values are significantly smaller than previously predicted T(c))s for disilane at equivalent pressure. This shows that similar but different crystalline structures of a material can result in dramatically different T(c)'s and stresses the need for a systematic search for a crystalline ground state.

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward.