Molecular basis of the selective activity of vitamin D analogues

More than 2,000 synthetic analogues of the biological active form of vitamin D, 1alpha,25-dihydroxyvitamin D(3) (1alpha,25(OH)(2)D(3)), are presently known. Basically, all of them interfere with the molecular switch of nuclear 1alpha,25(OH)(2)D(3) signaling, which is the complex of the vitamin D receptor (VDR), the retinoid X receptor (RXR), and a 1alpha,25(OH)(2)D(3) response element (VDRE). Central element of this molecular switch is the ligand-binding domain (LBD) of the VDR, which can be stabilized by a 1alpha,25(OH)(2)D(3) analogue either in its agonistic, antagonistic, or non-agonistic conformation. The positioning of helix 12 of the LBD is of most critical importance for these conformations. In each of the three conformations, the VDR performs different protein-protein interactions, which then result in a characteristic functional profile. Most 1alpha,25(OH)(2)D(3) analogues have been identified as agonists, a few are antagonists (e.g., ZK159222 and TEI-9647), and only Gemini and some of its derivatives act under restricted conditions as non-agonists. The functional profile of some 1alpha,25(OH)(2)D(3) analogues, such as EB1089 and Gemini, can be modulated by protein and DNA interaction partners of the VDR. This provides them with some selectivity for DNA-dependent and -independent signaling pathways and VDRE structures.     

Machine Learning Methods for Exploring Sequence Determinants of 3D Genome Organization

In higher eukaryotic cells, chromosomes are folded inside the nucleus. Recent advances in whole-genome mapping technologies have revealed the multiscale features of 3D genome organization that are intertwined with fundamental genome functions. However, DNA sequence determinants that modulate the formation of 3D genome organization remain poorly characterized. In the past few years, predicting 3D genome organization based on DNA sequence features has become an active area of research. Here, we review the recent progress in computational approaches to unraveling important sequence elements for 3D genome organization. In particular, we discuss the rapid development of machine learning-based methods that facilitate the connections between DNA sequence features and 3D genome architectures at different scales. While much progress has been made in developing predictive models for revealing important sequence features for 3D genome organization, new research is urgently needed to incorporate multi-omic data and enhance model interpretability, further advancing our understanding of gene regulation mechanisms through the lens of 3D genome organization.     

基于深度学习的蛋白质建模与设计

随着蛋白质序列及结构数据的大量累积,在获得了大量描述性信息之后如何有效利用海量数据,从已有数据中高效提取信息并且应用到下游任务当中就成为了研究者亟待解决的问题。蛋白质的设计可使新蛋白的研发不再受限于实验条件,这对药物靶点预测、新药研发和材料设计等领域具有重要意义。深度学习作为一种高效的数据特征提取方法,可以通过它对蛋白质数据进行建模,进而加入先验信息对蛋白质进行设计。故此基于深度学习的蛋白质设计就成为一个具有广阔前景的研究领域。文中主要阐述基于深度学习的蛋白质序列与结构数据的建模和设计方法。详述该方法的策略、原理、适用范围、应用实例。讨论了深度学习方法在本领域的应用前景及局限性,以期为相关研究提供参考。     

PET水解酶传统与智能分子设计研究进展

塑料由于其耐久性和耐降解性造成的环境污染日趋严重,而塑料废弃物的处理回收方法存在着缺陷。聚对苯二甲酸乙二醇酯（polyethylene terephthalate,PET）是应用最广泛的塑料类型之一,但在自然条件下很难被降解。近年来,虽然多种具有PET降解活性的酶被发现,但这些酶的催化活性和热稳定性难以支撑实际工业所需,因此提高PET水解酶的降解能力已成为研究热点而备受关注。脂肪酶、角质酶、IsPETase和IsMHETase是目前研究最为广泛的PET水解酶,就这几种酶的结构、活性特征进行了总结,重点阐述了传统蛋白质工程和人工智能分子设计在增强PET水解酶应用性能方面的研究进展。期望塑料降解酶可以进一步发展优化,为循环塑料经济做出有价值的贡献。     

Molecular basis of film formation from a soybean protein: comparison between the conformation of glycinin in aqueous solution and in films

Fourier transform infrared spectroscopy has been used to investigate the conformational changes of glycinin, a major storage protein of soybean seeds, upon film-forming. The results show that the secondary structure of glycinin is mainly composed of a β-sheet (48%) and unordered (49%) structures. The amide I band of glycinin in film-forming conditions, i.e. in alkaline media and in the presence of plasticizing agent, reveals the conversion of 18% of the secondary structure of the protein from the β-sheet (6%) and random coil (12%) to the -helical conformation due to the helicogenic effect of the ethylene glycol used as the plasticizing agent. Conformational changes also occur upon the film-forming process leading to the formation of intermolecular hydrogen-bonded β-sheet structures. Results obtained from other plant families indicate that, whatever the origin and conformation of protein, formation of films leads to the appearance of intermolecular hydrogen-bonded β-sheet structures, suggesting that this type of structure might be essential for the network formation in films. Thus, it is hypothesized that, in the film state, intermolecular hydrogen bonding between segments of β-sheet may act as junction zones in the film network. This study reveals for the first time that there is a close relationship between the conformation of proteins and the mechanical properties of films.     

Molecular basis for the reversible ADP-ribosylation of guanosine bases

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1D2DSimScore: A novel method for comparing contacts in biomacromolecules and their complexes

The biologically relevant structures of proteins and nucleic acids and their complexes are dynamic. They include a combination of regions ranging from rigid structural segments to structural switches to regions that are almost always disordered, which interact with each other in various ways. Comparing conformational changes and variation in contacts between different conformational states is essential to understand the biological functions of proteins, nucleic acids, and their complexes. Here, we describe a new computational tool, 1D2DSimScore, for comparing contacts and contact interfaces in all kinds of macromolecules and macromolecular complexes, including proteins, nucleic acids, and other molecules. 1D2DSimScore can be used to compare structural features of macromolecular models between alternative structures obtained in a particular experiment or to score various predictions against a defined “ideal” reference structure. Comparisons at the level of contacts are particularly useful for flexible molecules, for which comparisons in 3D that require rigid-body superpositions are difficult, and in biological systems where the formation of specific inter-residue contacts is more relevant for the biological function than the maintenance of a specific global 3D structure. Similarity/dissimilarity scores calculated by 1D2DSimScore can be used to complement scores describing 3D structural similarity measures calculated by the existing tools.     

Molecular basis of SARS-CoV-2 Omicron variant evasion from shared neutralizing antibody response

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Soft regions of protein surface are potent for stable dimer formation

Abstract

By having knowledge about the characteristics of protein interaction interfaces, we will be able to manipulate protein complexes for therapies. Dimer state is considered as the primary alphabet of the most proteins’ quaternary structure. The properties of binding interface between subunits and of noninterface region define the specificity and stability of the intended protein complex. Considering some topological properties and amino acids’ affinity for binding in interfaces of protein dimers, we construct the interface-specific recurrence plots. The data obtained from recurrence quantitative analysis, and accessibility-related metrics help us to classify the protein dimers into four distinct classes. Some mechanical properties of binding interfaces are computed for each predefined class of the dimers. The computed mechanical characteristics of binding patch region are compared with those of nonbinding region of proteins. Our observations indicate that the mechanical properties of protein binding sites have a decisive impact on determining the dimer stability. We introduce a new concept in analyzing protein structure by considering mechanical properties of protein structure. We conclude that the interface region between subunits of stable dimers is usually mechanically softer than the interface of unstable protein dimers. Abbreviations AAB average affinity for binding

ANM anisotropic network model

APC affinity propagation clustering

ASA accessible surface area

CCD inter residues distance

CSC complex stability code

DM distance matrix

ΔG_diss PISA-computed dissociation free energy

GNM Gaussian normal mode analysis

NMA normal mode analysis

PBP protein binding patch

PISA proteins, interfaces, structures and assemblies

rASA relative accessible area in respect to unfolded state of residues

RM recurrence matrix

rP relative protrusion

RP recurrence plot

RQA recurrence quantitative analysis

SEM standard error of mean

Communicated by Ramaswamy H. Sarma     

Molecular basis for activation of G protein-coupled receptor kinases

G protein‐coupled receptor (GPCR) kinases (GRKs) selectively recognize and are allosterically regulated by activated GPCRs, but the molecular basis for this interaction is not understood. Herein, we report crystal structures of GRK6 in which regions known to be critical for receptor phosphorylation have coalesced to stabilize the kinase domain in a closed state and to form a likely receptor docking site. The crux of this docking site is an extended N‐terminal helix that bridges the large and small lobes of the kinase domain and lies adjacent to a basic surface of the protein proposed to bind anionic phospholipids. Mutation of exposed, hydrophobic residues in the N‐terminal helix selectively inhibits receptor, but not peptide phosphorylation, suggesting that these residues interact directly with GPCRs. Our structural and biochemical results thus provide an explanation for how receptor recognition, phospholipid binding, and kinase activation are intimately coupled in GRKs.     

Protein language-model embeddings for fast,accurate, and alignment-free protein structure prediction

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Molecular basis for TPR domain-mediated regulation of protein phosphatase 5

Protein phosphatase 5 (Ppp5) is a serine/threonine protein phosphatase comprising a regulatory tetratricopeptide repeat (TPR) domain N-terminal to its phosphatase domain. Ppp5 functions in signalling pathways that control cellular responses to stress, glucocorticoids and DNA damage. Its phosphatase activity is suppressed by an autoinhibited conformation maintained by the TPR domain and a C-terminal subdomain. By interacting with the TPR domain, heat shock protein 90 (Hsp90) and fatty acids including arachidonic acid stimulate phosphatase activity. Here, we describe the structure of the autoinhibited state of Ppp5, revealing mechanisms of TPR-mediated phosphatase inhibition and Hsp90- and arachidonic acid-induced stimulation of phosphatase activity. The TPR domain engages with the catalytic channel of the phosphatase domain, restricting access to the catalytic site. This autoinhibited conformation of Ppp5 is stabilised by the C-terminal alphaJ helix that contacts a region of the Hsp90-binding groove on the TPR domain. Hsp90 activates Ppp5 by disrupting TPR-phosphatase domain interactions, permitting substrate access to the constitutively active phosphatase domain, whereas arachidonic acid prompts an alternate conformation of the TPR domain, destabilising the TPR-phosphatase domain interface.     

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

We describe AlphaFold, the protein structure prediction system that was entered by the group A7D in CASP13. Submissions were made by three free-modeling (FM) methods which combine the predictions of three neural networks. All three systems were guided by predictions of distances between pairs of residues produced by a neural network. Two systems assembled fragments produced by a generative neural network, one using scores from a network trained to regress GDT_TS. The third system shows that simple gradient descent on a properly constructed potential is able to perform on par with more expensive traditional search techniques and without requiring domain segmentation. In the CASP13 FM assessors' ranking by summed z-scores, this system scored highest with 68.3 vs 48.2 for the next closest group (an average GDT_TS of 61.4). The system produced high-accuracy structures (with GDT_TS scores of 70 or higher) for 11 out of 43 FM domains. Despite not explicitly using template information, the results in the template category were comparable to the best performing template-based methods.     

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ .     

Functional information in SWISS-PROT: the basis for large-scale characterisation of protein sequences

With the rapid growth of sequence databases, there is an increasing need for reliable functional characterisation and annotation of newly predicted proteins. To cope with such large data volumes, faster and more effective means of protein sequence characterisation and annotation are required. One promising approach is automatic large-scale functional characterisation and annotation, which is generated with limited human interaction. However, such an approach is heavily dependent on reliable data sources. The SWISS-PROT protein sequence database plays an essential role here owing to its high level of functional information.     

Structural basis for promoter DNA recognition by the response regulator OmpR

OmpR, a response regulator of the EnvZ/OmpR two-component system (TCS), controls the reciprocal regulation of two porin proteins, OmpF and OmpC, in bacteria. During signal transduction, OmpR (OmpR-FL) undergoes phosphorylation at its conserved Asp residue in the N-terminal receiver domain (OmpRn) and recognizes the promoter DNA from its C-terminal DNA-binding domain (OmpRc) to elicit an adaptive response. Apart from that, OmpR regulates many genes in Escherichia coli and is important for virulence in several pathogens. However, the molecular mechanism of the regulation and the structural basis of OmpR–DNA binding is still not fully clear. In this study, we presented the crystal structure of OmpRc in complex with the F1 region of the ompF promoter DNA from E. coli. Our structural analysis suggested that OmpRc binds to its cognate DNA as a homodimer, only in a head-to-tail orientation. Also, the OmpRc apo-form showed a unique domain-swapped crystal structure under different crystallization conditions. Biophysical experimental data, such as NMR, fluorescent polarization and thermal stability, showed that inactive OmpR-FL (unphosphorylated) could bind to promoter DNA with a weaker binding affinity as compared with active OmpR-FL (phosphorylated) or OmpRc, and also confirmed that phosphorylation may only enhance DNA binding. Furthermore, the dimerization interfaces in the OmpRc–DNA complex structure identified in this study provide an opportunity to understand the regulatory role of OmpR and explore the potential for this “druggable” target.     

A template-finding algorithm and a comprehensive benchmark for homology modeling of proteins

The first step in homology modeling is to identify a template protein for the target sequence. The template structure is used in later phases of the calculation to construct an atomically detailed model for the target. We have built from the Protein Data Bank (PDB) a large-scale learning set that includes tens of millions of pair matches that can be either a true template or a false one. Discriminatory learning (learning from positive and negative examples) is used to train a decision tree. Each branch of the tree is a mathematical programming model. The decision tree is tested on an independent set from PDB entries and on the sequences of CASP7. It provides significant enrichment of true templates (between 50 and 100%) when compared to PSI-BLAST. The model is further verified by building atomically detailed structures for each of the tentative true templates with modeller. The probability that a true match does not yield an acceptable structural model (within 6 A RMSD from the native structure) decays linearly as a function of the TM structural-alignment score.     

酶的定向进化及其应用

综述了生物催化剂（酶）分子定向进化的产生、原理、方法及应用,深入阐述酶分子定向进化过程中的相关问题,重点介绍了易错PCR（Error-prone PCR）和DNA改组（DNA shuffling）等几种典型的酶定向进化方法与成功实例,展望了生物定向进化研究的发展前景。     

Molecular basis of vanadium-mediated inhibition of hepatocellular preneoplasia during experimental hepatocarcinogenesis in rats

Carcinogen-induced early DNA lesions and metallothionein (MT) over-expression have been implicated in cell proliferation and thereby subsequent expression of premalignant phenotype of the cell. We have therefore investigated the chemopreventive potential of vanadium in a multi-biomarker approach, viz. 8-hydroxy-2'-deoxyguanosines (8-OHdGs), DNA single-strand breaks (SSBs), DNA-protein crosslinks (DPCs), chromosomal aberrations (CAs), in situ MT expression, and cell proliferation in rat liver preneoplasia. Hepatocarcinogenesis was induced in male Sprague-Dawley rats with a single, necrogenic, intraperitoneal (i.p.) injection of diethylnitrosamine (DEN) (200 mg/Kg body weight) at week 4 of the experimental protocol followed by promotion with phenobarbital (PB) (0.05% in basal diet), on and from week 8 and continued till 32 weeks in a long-term regimen. There was a significant and steady elevation of modified DNA bases 8-OHdGs (P < 0.0001; 90.69%) along with substantial increments of the extent of SSBs (P < 0.001) and CAs (P < 0.001) following DEN exposure. Supplementation of vanadium at a dose of 0.5 ppm abated the formations of 8-OHdGs (80.63%; P < 0.0001), SS-DNAs (P < 0.001) and SSBs/DNA unit (P < 0.01; 56.39%), DPCs (59.26%; P < 0.0001) and CAs (71.52%; P < 0.001) in preneoplastic rat liver studied at various time points. Low dose of vanadium treatment further reduced liver-MT immunoreactivity (P < 0.05) and BrdU-labeling index (P < 0.02) and a significant positive correlation (r = 0.92; r2 = 0.85; P = 0.0001) was noted between them. Continuous vanadium administration also decreased nodular incidence (66.67%) and nodule multiplicity (62.12%; P < 0.001) along with substantial improvement in the altered hepatocellular phenotype when compared to DEN + PB treatment alone. The study indicates that vanadium-mediated suppression of cell proliferation and resulting premalignant expression might be due to the observed reductions in hepatic 8-OHdGs, SSBs, DPCs, CAs, and MT immunoreactivity. Vanadium is chemopreventive for DEN-induced hepatocellular preneoplasia in rats.