Recent advances in protein conformation sampling by combining machine learning with molecular simulation

The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational biology.One of the most cutting-edge and important applications of ML is its integration with molecular simulations to improve the sampling efficiency of the vast conformational space of large biomolecules.This review focuses on recent studies that utilize ML-based techniques in the exploration of protein conformational landscape.We first highlight the recent development of ML-aided enhanced sampling methods,including heuristic algorithms and neural networks that are designed to refine the selection of reaction coordinates for the construction of bias potential,or facilitate the exploration of the unsampled region of the energy landscape.Further,we review the development of autoencoder based methods that combine molecular simulations and deep learning to expand the search for protein conformations.Lastly,we discuss the cutting-edge methodologies for the one-shot generation of protein conformations with precise Boltzmann weights.Collectively,this review demonstrates the promising potential of machine learning in revolutionizing our insight into the complex conformational ensembles of proteins.

Amyloid-β peptide aggregation and the influence of carbon nanoparticles

Soluble peptides or proteins can self-aggregate into insoluble, ordered amyloid fibrils under appropriate conditions. These amyloid aggregates are the hallmarks of several human diseases ranging from neurodegenerative disorders to sys- temic amyloidoses. In this review, we first introduce the common structural features of amyloid fibrils and the amyloid fibrillation kinetics determined from experimental studies. Then, we discuss the structural models of Alzheimer＇s amyloid- β （Aβ） fibrils derived from solid-state nuclear magnetic resonance spectroscopy. On the computational side, molecular dynamics simulations can provide atomic details of structures and the underlying oligomerization mechanisms. We finally summarize recent progress in atomistic simulation studies on the oligomerization of β （including full-length Af and its fragments） and the influence of carbon nanoparticles.

Bending energy of a vesicle to which a small spherical particle adhere:An analytical study

On the basis of Helfrich＇s bending energy model, we show that the adsorption process of a small spherical particle to a closed vesicle can be analytically studied by retaining the leading terms in an expansion of the shape equation. Our general derivation predicts the optimal binding sites on a vesicle, where the local membrane shape of the binding site could be non-axisymmetric before the continuous adhesion transition takes place. Our derivation avoids directly solving the shape equation and depends on an integration of the contact-line condition. The results are verified by several examples of independent numerical solutions.

Structural and dynamical mechanisms of a naturally occurring variant of the human prion protein in preventing prion conversion

Prion diseases are associated with the misfolding of the normal helical cellular form of prion protein (PrPC) into the β-sheet-rich scrapie form (PrPSc) and the subsequent aggregation of PrPSc into amyloid fibrils. Recent studies demonstrated that a naturally occurring variant V127 of human PrPC is intrinsically resistant to prion conversion and aggregation, and can completely prevent prion diseases. However, the underlying molecular mechanism remains elusive. Herein we perform multiple microsecond molecular dynamics simulations on both wildtype (WT) and V127 variant of human PrPC to understand at atomic level the protective effect of V127 variant. Our simulations show that G127V mutation not only increases the rigidity of the S2–H2 loop between strand-2 (S2) and helix-2 (H2), but also allosterically enhances the stability of the H2 C-terminal region. Interestingly, previous studies reported that animals with rigid S2–H2 loop usually do not develop prion diseases, and the increase in H2 C-terminal stability can prevent misfolding and oligomerization of prion protein. The allosteric paths from G/V127 to H2 C-terminal region are identified using dynamical network analyses. Moreover, community network analyses illustrate that G127V mutation enhances the global correlations and intra-molecular interactions of PrP, thus stabilizing the overall PrPC structure and inhibiting its conversion into PrPSc. This study provides mechanistic understanding of human V127 variant in preventing prion conversion which may be helpful for the rational design of potent anti-prion compounds.

Interplay of Strain and Magnetism in FeSe Monolayers

Superconductivity and its relationship with strain remains elusive in the monolayer FeSe superconductor. Based on first-principles calculations and model studies, we investigate the magnetic properties of FeSe and FeTe monolayers and find that tensile strain induces changes to magnetic phases for both materials. Furthermore, we reveal that electron doping will decrease the difference of effective magnetic interactions between the a and b directions in an FeSe monolayer and hence suppress its nematicity. We suggest that the overall effect of tensile strain combined with electron doping hinders the appearance of both magnetic and nematic orders in an FeSe monolayer,which paves the way for the emergence of superconductivity.

Metastable oxygen vacancy ordering state and improved memristive behavior in TiO2 crystals

Oxygen vacancy is one of the pivotal factors for tuning/creating various oxide properties.Understanding the behavior of oxygen vacancies is of paramount importance.In this study,we identify a metastable oxygen vacancy ordering state other than the well-known Magnéli phases in TiO2 crystals from both experimental and theoretical studies.The oxygen vacancy ordering is found to be a zigzag chain along the[001]direction in the(110)plane occurring in a wide temperature range of 200–500℃.This metastable ordering state leads to a first-order phase transition accompanied by significant enhancement of dielectric permittivity and a memristive effect featuring a low driving electric field.Our results can improve oxide properties by engineering oxygen vacancies.

Intrinsic anomalous spin Hall effect

Charge-spin interconversion in magnetic materials is investigated by using the first-principles calculations.In addition to the conventional spin Hall effect(SHE) that requires mutual orthogonality of the charge current,spin-flow direction,and spin polarization,the recently proposed anomalous SHE(ASHE) is confirmed in Mn2Au and WTe2.The interaction of the order parameter with conduction electrons leads to sizeable non-zero spin Berry curvatures that give rise to anomalous spin Hall conductivity(ASHC).Our calculations show that the ASHE is intrinsic and originates from the order-parameter-controlled spin-orbit interaction,which generates an extra anomalous effective field.A useful relationship among the order parameter,the spin Berry curvature,and the ASHC is revealed.Our findings provide a new avenue for generating and detecting arbitrary types of spin currents.