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Proteins fold on relatively smooth free energy landscapes which are biased toward the native state, but even simple topologies which fold rapidly can experience roughness on their free energy landscape. The details of these interactions are difficult to elucidate experimentally. Closely related to the problem of deciphering the details of the free energy landscape is the problem of defining the interactions in the denatured state ensemble (DSE) which is populated under native conditions, that is, under conditions where the native state is stable. The DSE of many proteins deviates from random coil models, but quantifying and defining the energetics of the transiently populated interactions in this ensemble is extremely challenging. Characterization of the DSE of proteins which fold to compact structures is also relevant to studies of intrinsically disordered proteins (IDPs) since interactions in the dynamic ensemble populated by IDPs can modulate their behavior. Here we show how experimental thermodynamic and pKa measurements can be combined with computational thermodynamic integration to quantify interactions in the DSE. We show that non-native side chain interactions can stabilize native backbone structure in the DSE and demonstrate that that even rapidly folding proteins can form energetically significant non-native interactions in their DSE. As an example, we characterize a non-native salt bridge that stabilizes local native backbone structure in the DSE of a widely studied fast-folding protein, the villin headpiece helical domain. The combined computational experimental approach is applicable to other protein unfolded states and provides insight that is impossible to obtain with either method alone.

Islet amyloid polypeptide (IAPP), a 37 residue polypeptide, is the main protein component of islet amyloid deposits produced in the pancreas in Type 2 diabetes. Human IAPP contains five serine residues at positions 19, 20, 28, 29, and 34. Models of the IAPP amyloid fibril indicate a structure composed of two closely aligned columns of IAPP monomers with each monomer contributing to two intermolecular β-strands. Ser 19 and Ser 20 are in the partially ordered β-turn region, which links the two strands, whereas Ser 28, Ser 29, and Ser 34 are in the core region of the amyloid fibril. Ser 29 is involved in contacts between the two columns of monomers and is the part of the steric zipper interface. We undertook a study of individual serine substitutions with the hydrophobic isostere 2-aminobutyric acid (2-Abu) to examine the site-specific role of serine side chains in IAPP amyloid formation. All five variants formed amyloid. The Ser 19 to 2-Abu mutant accelerates amyloid formation by a factor of 3 to 4, while the Ser 29 to 2-Abu mutation modestly slows the rate of amyloid formation. 2-Abu replacements at the other sites had even smaller effects. The data demonstrate that the cross-column interactions made by residue 29 are not essential for amyloid formation and also show that cross-strand networks of hydrogen-bonded Ser side chains, so called Ser-ladders, are not required for IAPP amyloid formation. The effect of the Ser 19 to 2-Abu mutant suggests that residues in this region are important for amyloid formation by IAPP.

Intrinsically disordered proteins (IDPs) play important roles in biology, but little is known about the energetics of their inter-residue interactions. Methods that have been successfully applied to analyze the energetics of globular proteins are not applicable to the fluctuating partially ordered ensembles populated by IDPs. A combined computational experimental strategy is introduced for analyzing the energetic role of individual residues in the free state of IDPs. The approach combines experimental measurements of the binding of wild-type and mutant IDPs to their partners with alchemical free energy calculations of the structured complexes. These data allow quantitative information to be deduced about the free state via a thermodynamic cycle. The approach is validated by the analysis of the effects of mutations upon the binding free energy of the ovomucoid inhibitor third binding domain to its partners and is applied to the C-terminal domain of the measles virus nucleoprotein, a 125-residue IDP involved in the RNA transcription and replication of measles virus. The analysis reveals significant inter-residue interactions in the unbound IDP and suggests a biological role for them. The work demonstrates that advances in force fields and computational hardware have now led to the point where it is possible to develop methods, which integrate experimental and computational techniques to reveal insights that cannot be studied using either technique alone.

Rising temperature is a major threat to the normal growth and development of maize, resulting in low yield production and quality. The mechanism of maize in response to heat stress remains uncertain. In this study, a maize mutant Zmhsl-1 (heat sensitive leaves) with wilting and curling leaves under high temperatures was identified from maize Zheng 58 (Z58) mutant lines generated by ethyl methanesulfonate (EMS) mutagenesis. The Zmhsl-1 plants were more sensitive to increased temperature than Z58 in the field during growth season. The Zmhsl-1 plants had lower plant height, lower yield, and lower content of photosynthetic pigments. A bulked segregant analysis coupled with whole-genome sequencing (BSA-seq) enabled the identification of the corresponding gene, named ZmHSL, which encodes an endo-β-1,4-xylanase from the GH10 family. The loss-of-function of ZmHSL resulted in reduced lignin content in Zmhsl-1 plants, leading to defects in water transport and more severe leaf wilting with the increase in temperature. RNA-seq analysis revealed that the differentially expressed genes identified between Z58 and Zmhsl-1 plants are mainly related to heat stress-responsive genes and unfolded protein response genes. All these data indicated that ZmHSL plays a key role in lignin synthesis, and its defective mutation causes changes in the cell wall structure and gene expression patterns, which impedes water transport and confers higher sensitivity to high-temperature stress. [ABSTRACT FROM AUTHOR]

Ecological restoration is an important strategy for mitigating environmental degradation, and the effectiveness evaluation of ecological restoration is of profound significance for the scientific implementation of restoration projects. This study improved the Patch-generating Land Use Simulation (PLUS) model. It was used to simulate the land use patterns under multi-scenarios such as natural development (ND), economic priority (EP), and ecological restoration (ER) in 2030. An evaluation framework covering ecological "Restoration–Monitoring–Effectiveness" (RME) was proposed. Based on 30 m high-resolution remote-sensing data from 2000 to 2020, the land use distribution, landscape pattern changes, and ecosystem services under different scenarios were evaluated and predicted in the Yellow River Basin of Sichuan to verify the effectiveness of the evaluation framework. The results showed the following: (1) Under the ER scenario, the transfer of land use types in 2020–2030 was mainly characterized by an increase in the area of wetlands and a decrease in the area of built-up land. (2) There were obvious differences in land use and landscape patterns under different scenarios. Compared with the ND and EP scenarios, the growth of the construction rate was suppressed in the ER scenario, and the coverage of grassland and wetlands increased significantly. (3) The mean values of ecosystem services in the ER scenario were higher than those in the ND and EP scenarios. These findings clearly indicate that the RME evaluation system can accurately evaluate the ecological restoration effects under multi-scenarios in the future, providing a new perspective for ecological restoration evaluation in other regions. [ABSTRACT FROM AUTHOR]

The simultaneous detection of multiple stimuli, such as pressure and temperature, has long been a persistent challenge for developing electronic skin (e‐skin) to emulate the functionality of human skin. Meanwhile, the demand for integrated power supply units is an additional pressing concern to achieve its lightweightness and flexibility. Herein, we propose a self‐powered dual temperature–pressure (SPDM) sensor, which utilizes a compressible ionic gel electrolyte driven by the potential difference between MXene and Al electrodes. The SPDM sensor exhibits a rapid and timely response to changes in pressure‐induced deformation, while exhibiting a slow and hysteretic response to temperature variations. These distinct response characteristics enable the differentiation of current signals generated by different stimuli through machine learning, resulting in an impressive accuracy rate of 99.1%. Furthermore, the developed SPDM sensor exhibits a wide pressure detection range of 0–800 kPa and a broad temperature detection range of 5–75°C, encompassing the environmental conditions encountered in daily human life. The dual‐mode coupled strategy by machine learning provides an effective approach for temperature and pressure detection and discrimination, showcasing its potential applications in wearable electronics, intelligent robots, human–machine interactions, and so on. [ABSTRACT FROM AUTHOR]

The rational and predictable enhancement of protein stability is an important goal in protein design. Most efforts target the folded state, however stability is the free energy difference between the folded and unfolded states thus both are suitable targets. Strategies directed at the unfolded state usually seek to decrease chain entropy by introducing cross-links or by replacing glycines. Cross-linking has led to mixed results. Replacement of glycine with an l-amino acid, while reducing the entropy of the unfolded state, can introduce unfavorable steric interactions in the folded state, since glycine is often found in conformations that require a positive φ angle such as helical C-capping motifs or type I' and II″ β-turns. l-Amino acids are strongly disfavored in these conformations, but d-amino acids are not. However, there are few reported examples and conflicting results have been obtained when glycines are replaced with d-Ala. We critically examine the effect of Gly-to-d-Ala substitutions on protein stability using experimental approaches together with molecular dynamics simulations and free energy calculations. The data, together with a survey of high resolution structures, show that the vast majority of proteins can be stabilized by substitution of C-capping glycines with d-Ala. Sites suitable for substitutions can be identified via sequence alignment with a high degree of success. Steric clashes in the native state due to the new side chain are rarely observed, but are likely responsible for the destabilizing or null effect observed for the small subset of Gly-to-d-Ala substitutions which are not stabilizing. Changes in backbone solvation play less of a role. Favorable candidates for d-Ala substitution can be identified using a rapid algorithm based on molecular mechanics.

Glioma is the most common tumor of the central nervous system. In this review, we outline the immunobiological factors that interact with glioma cells and tumor microenvironment (TME), providing more potential targets for clinical inhibition of glioma development and more directions for glioma treatment.

The green construction evaluation system of the Xinyi expressway electromechanical installation, comprising 19 indicators, has been constructed using the IAHP, CRITIC, and grey clustering method. This system was developed based on the Xinyi expressway electromechanical installation project, which involved the use of the IAHP, CRITIC, and grey clustering method. The system was constructed from four aspects: comprehensive management level, resource saving and utilization, construction quality impact, and ecological environment impact. The green construction grade of the electromechanical installation of the selected five bidding sections is evaluated in a comprehensive manner, and the advantages and disadvantages of the selected bidding sections are analyzed using a radar chart method. The research findings indicate that the primary determinants of the green construction evaluation level of the project are the prefabrication rate of component parts, the vegetation restoration rate, and the utilization rate of environmental protection technology. Once the selected bidding section has achieved a higher grade in the green construction evaluation, the monitoring data of the electromechanical installation's green construction meets the requirements of the specification, and the level of green construction is close to the actual production of the project. This proves that the method is scientific and rational and provides a reference for the green construction evaluation of similar electromechanical installation projects in the future. [ABSTRACT FROM AUTHOR]

Maize is a major staple crop widely used as food, animal feed, and raw materials in industrial production. High‐density planting is a major factor contributing to the continuous increase of maize yield. However, high planting density usually triggers a shade avoidance response and causes increased plant height and ear height, resulting in lodging and yield loss. Reduced plant height and ear height, more erect leaf angle, reduced tassel branch number, earlier flowering, and strong root system architecture are five key morphological traits required for maize adaption to high‐density planting. In this review, we summarize recent advances in deciphering the genetic and molecular mechanisms of maize involved in response to high‐density planting. We also discuss some strategies for breeding advanced maize cultivars with superior performance under high‐density planting conditions. [ABSTRACT FROM AUTHOR]