DeepUMQA: ultrafast shape recognition-based protein model quality assessment using deep learning.

MOTIVATION: Protein model quality assessment is a key component of protein structure prediction. In recent research, the voxelization feature was used to characterize the local structural information of residues, but it may be insufficient for describing residue-level topological information. Design features that can further reflect residue-level topology when combined with deep learning methods are therefore crucial to improve the performance of model quality assessment. RESULTS: We developed a deep-learning method, DeepUMQA, based on Ultrafast Shape Recognition (USR) for the residue-level single-model quality assessment. In the framework of the deep residual neural network, the residue-level USR feature was introduced to describe the topological relationship between the residue and overall structure by calculating the first moment of a set of residue distance sets and then combined with 1D, 2D and voxelization features to assess the quality of the model. Experimental results on the CASP13, CASP14 test datasets and CAMEO blind test show that USR could supplement the voxelization features to comprehensively characterize residue structure information and significantly improve model assessment accuracy. The performance of DeepUMQA ranks among the top during the state-of-the-art single-model quality assessment methods, including ProQ2, ProQ3, ProQ3D, Ornate, VoroMQA, ProteinGCN, ResNetQA, QDeep, GraphQA, ModFOLD6, ModFOLD7, ModFOLD8, QMEAN3, QMEANDisCo3 and DeepAccNet. AVAILABILITY AND IMPLEMENTATION: The DeepUMQA server is freely available at http://zhanglab-bioinf.com/DeepUMQA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Structural analogue-based protein structure domain assembly assisted by deep learning.

MOTIVATION: With the breakthrough of AlphaFold2, the protein structure prediction problem has made remarkable progress through deep learning end-to-end techniques, in which correct folds could be built for nearly all single-domain proteins. However, the full-chain modelling appears to be lower on average accuracy than that for the constituent domains and requires higher demand on computing hardware, indicating the performance of full-chain modelling still needs to be improved. In this study, we investigate whether the predicted accuracy of the full-chain model can be further improved by domain assembly assisted by deep learning. RESULTS: In this article, we developed a structural analogue-based protein structure domain assembly method assisted by deep learning, named SADA. In SADA, a multi-domain protein structure database was constructed for the full-chain analogue detection using individual domain models. Starting from the initial model constructed from the analogue, the domain assembly simulation was performed to generate the full-chain model through a two-stage differential evolution algorithm guided by the energy function with an inter-residue distance potential predicted by deep learning. SADA was compared with the state-of-the-art domain assembly methods on 356 benchmark proteins, and the average TM-score of SADA models is 8.1% and 27.0% higher than that of DEMO and AIDA, respectively. We also assembled 293 human multi-domain proteins, where the average TM-score of the full-chain model after the assembly by SADA is 1.1% higher than that of the model by AlphaFold2. To conclude, we find that the domains often interact in the similar way in the quaternary orientations if the domains have similar tertiary structures. Furthermore, homologous templates and structural analogues are complementary for multi-domain protein full-chain modelling. AVAILABILITY AND IMPLEMENTATION: http://zhanglab-bioinf.com/SADA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The additional nitrogen atom breaks the uranyl structure: a combined photoelectron spectroscopy and theoretical study of NUO2.

We report a joint photoelectron spectroscopic and relativistic quantum chemistry study on gaseous NUO2-. The electron affinity (EA) of the neutral NUO2 molecule is reported for the first time with a value of 2.602(28) eV. The U-O and U-N stretching vibrational modes for the ground state and the first excited state are observed for NUO2. The geometric and electronic structures of both the anions and the corresponding neutrals are investigated by relativistic quantum chemistry calculations to interpret the photoelectron spectra and to provide insights into the nature of the chemical bonding. Both the ground state of the anion and neutral are calculated to be planar structures with C2v symmetry. Unlike the "T"-shape structure of UO3 which has a quasi-linear O-U-O angle, both the ground-state geometries of the anion and neutral have O-U-O bond angles of around 90°. The significant contraction of the O-U-O bond angle indicates the strong interaction between the U and N atoms compared with the "additional" oxygen in UO3. The chemical bonding calculation indicates that multiple bonding of U(VI) can occur in NUO2- and NUO2, and the UVI-N bond is significantly more covalent than the U-O bond. The current experimental and theoretical results reveal the difference between the U-N and U-O bond in the unified molecular system, and expand our understanding of the bonding capacities of actinide elements with the nitrogen atom.

A sequential niche multimodal conformational sampling algorithm for protein structure prediction.

MOTIVATION: Massive local minima on the protein energy landscape often cause traditional conformational sampling algorithms to be easily trapped in local basin regions, because they find it difficult to overcome high-energy barriers. Also, the lowest energy conformation may not correspond to the native structure due to the inaccuracy of energy models. This study investigates whether these two problems can be alleviated by a sequential niche technique without loss of accuracy. RESULTS: A sequential niche multimodal conformational sampling algorithm for protein structure prediction (SNfold) is proposed in this study. In SNfold, a derating function is designed based on the knowledge learned from the previous sampling and used to construct a series of sampling-guided energy functions. These functions then help the sampling algorithm overcome high-energy barriers and avoid the re-sampling of the explored regions. In inaccurate protein energy models, the high-energy conformation that may correspond to the native structure can be sampled with successively updated sampling-guided energy functions. The proposed SNfold is tested on 300 benchmark proteins, 24 CASP13 and 19 CASP14 FM targets. Results show that SNfold correctly folds (TM-score ≥ 0.5) 231 out of 300 proteins. In particular, compared with Rosetta restrained by distance (Rosetta-dist), SNfold achieves higher average TM-score and improves the sampling efficiency by more than 100 times. On several CASP FM targets, SNfold also shows good performance compared with four state-of-the-art servers in CASP. As a plug-in conformational sampling algorithm, SNfold can be extended to other protein structure prediction methods. AVAILABILITY AND IMPLEMENTATION: The source code and executable versions are freely available at https://github.com/iobio-zjut/SNfold. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A de novo protein structure prediction by iterative partition sampling, topology adjustment and residue-level distance deviation optimization.

MOTIVATION: With the great progress of deep learning-based inter-residue contact/distance prediction, the discrete space formed by fragment assembly cannot satisfy the distance constraint well. Thus, the optimal solution of the continuous space may not be achieved. Designing an effective closed-loop continuous dihedral angle optimization strategy that complements the discrete fragment assembly is crucial to improve the performance of the distance-assisted fragment assembly method. RESULTS: In this article, we proposed a de novo protein structure prediction method called IPTDFold based on closed-loop iterative partition sampling, topology adjustment and residue-level distance deviation optimization. First, local dihedral angle crossover and mutation operators are designed to explore the conformational space extensively and achieve information exchange between the conformations in the population. Then, the dihedral angle rotation model of loop region with partial inter-residue distance constraints is constructed, and the rotation angle satisfying the constraints is obtained by differential evolution algorithm, so as to adjust the spatial position relationship between the secondary structures. Finally, the residue distance deviation is evaluated according to the difference between the conformation and the predicted distance, and the dihedral angle of the residue is optimized with biased probability. The final model is generated by iterating the above three steps. IPTDFold is tested on 462 benchmark proteins, 24 FM targets of CASP13 and 20 FM targets of CASP14. Results show that IPTDFold is significantly superior to the distance-assisted fragment assembly method Rosetta_D (Rosetta with distance). In particular, the prediction accuracy of IPTDFold does not decrease as the length of the protein increases. When using the same FastRelax protocol, the prediction accuracy of IPTDFold is significantly superior to that of trRosetta without orientation constraints, and is equivalent to that of the full version of trRosetta. AVAILABILITYAND IMPLEMENTATION: The source code and executable are freely available at https://github.com/iobio-zjut/IPTDFold. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MMpred: a distance-assisted multimodal conformation sampling for de novo protein structure prediction.

MOTIVATION: The mathematically optimal solution in computational protein folding simulations does not always correspond to the native structure, due to the imperfection of the energy force fields. There is therefore a need to search for more diverse suboptimal solutions in order to identify the states close to the native. We propose a novel multimodal optimization protocol to improve the conformation sampling efficiency and modeling accuracy of de novo protein structure folding simulations. RESULTS: A distance-assisted multimodal optimization sampling algorithm, MMpred, is proposed for de novo protein structure prediction. The protocol consists of three stages: The first is a modal exploration stage, in which a structural similarity evaluation model DMscore is designed to control the diversity of conformations, generating a population of diverse structures in different low-energy basins. The second is a modal maintaining stage, where an adaptive clustering algorithm MNDcluster is proposed to divide the populations and merge the modal by adjusting the annealing temperature to locate the promising basins. In the last stage of modal exploitation, a greedy search strategy is used to accelerate the convergence of the modal. Distance constraint information is used to construct the conformation scoring model to guide sampling. MMpred is tested on a large set of 320 non-redundant proteins, where MMpred obtains models with TM-score≥0.5 on 291 cases, which is 28% higher than that of Rosetta guided with the same set of distance constraints. In addition, on 320 benchmark proteins, the enhanced version of MMpred (E-MMpred) has 167 targets better than trRosetta when the best of five models are evaluated. The average TM-score of the best model of E-MMpred is 0.732, which is comparable to trRosetta (0.730). AVAILABILITY AND IMPLEMENTATION: The source code and executable are freely available at https://github.com/iobio-zjut/MMpred. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Probing the electronic structure and Au-C bonding in AuC2nH (n = 4-7) using photoelectron imaging spectroscopy and quantum chemical calculations.

We report a combined experimental and theoretical study on the structures and chemical bonding of AuC2nH (n = 4-7) using photoelectron imaging and quantum chemical calculations. All the ground states of anions and neutral AuC2nH have a linear geometry. The electron affinities (EAs) are measured to be 2.063(5), 2.157(5), 2.220(5), and 2.267(5) eV for AuC2nH, n = 4-7, respectively. The photoelectron imaging data of AuC8H- and AuC10H- reveal major vibrational progressions in the Au-C stretching modes. The ground state stretching frequencies of the titled neutral molecules are 226, 193, 177, and 128 cm-1, respectively. By comparing the experimental ß value and theoretical molecular orbital analysis, we confirm that the CAM-B3LYP method is more suitable for describing the properties of such unsaturated long chains organogold clusters. The experimental and CAM-B3LYP methods give a big picture of the trend in EAs of AuC2nH. This shows that the EA value becomes larger with an increase in the carbon chain length, and it also shows a slow increment for larger n. The NRT analysis shows that the change of the Au-C bond order is not obvious as the number of carbon atoms increases, and the covalent character dominates the Au-C chemical bonds in these neutral species. The current study provides a wealth of electronic structure information about long-chain AuC2nH- (n = 4-7) and their corresponding neutral counterparts.

CGLFold: a contact-assisted de novo protein structure prediction using global exploration and loop perturbation sampling algorithm.

MOTIVATION: Regions that connect secondary structure elements in a protein are known as loops, whose slight change will produce dramatic effect on the entire topology. This study investigates whether the accuracy of protein structure prediction can be improved using a loop-specific sampling strategy. RESULTS: A novel de novo protein structure prediction method that combines global exploration and loop perturbation is proposed in this study. In the global exploration phase, the fragment recombination and assembly are used to explore the massive conformational space and generate native-like topology. In the loop perturbation phase, a loop-specific local perturbation model is designed to improve the accuracy of the conformation and is solved by differential evolution algorithm. These two phases enable a cooperation between global exploration and local exploitation. The filtered contact information is used to construct the conformation selection model for guiding the sampling. The proposed CGLFold is tested on 145 benchmark proteins, 14 free modeling (FM) targets of CASP13 and 29 FM targets of CASP12. The experimental results show that the loop-specific local perturbation can increase the structure diversity and success rate of conformational update and gradually improve conformation accuracy. CGLFold obtains template modeling score ≥ 0.5 models on 95 standard test proteins, 7 FM targets of CASP13 and 9 FM targets of CASP12. AVAILABILITY AND IMPLEMENTATION: The source code and executable versions are freely available at https://github.com/iobio-zjut/CGLFold. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Thermally Activated Delayed Fluorescence from d10 -Metal Carbene Complexes through Intermolecular Charge Transfer and Multicolor Emission with a Monomer-Dimer Equilibrium.

A series of two-coordinate AuI and CuI complexes (3 a, 3 b and 5 a, 5 b) are reported as new organometallic thermally activated delayed fluorescence (TADF) emitters, which are based on the carbene-metal-carbazole model with a pyridine-fused 1,2,3-triazolylidene (PyTz) ligand. PyTz features low steric hindrance and a low-energy LUMO (LUMO=-1.47 eV) located over the π* orbitals of the whole ligand, which facilitates intermolecular charge transfer between a donor (carbazole) and an accepter (PyTz). These compounds exhibit efficient TADF with microsecond lifetimes. Temperature-dependent photoluminescence kinetics of 3 a supports a rather small energy gap between S1 and T1 (ΔE S 1 - T 1 =60 meV). Further experiments reveal that there are dual-emission properties from a monomer-dimer equilibrium in solution, exhibiting single-component multicolor emission from blue to orange, including white-light emission.

Polarization consistent basis sets using the projector augmented wave method: a renovation brought by PAW into Gaussian basis sets.

A recently introduced framework incorporating the Projector Augmented Wave method and Gauss-type function (GTF-PAW) [X.-G. Xiong and T. Yanai, J. Chem. Theory Comput., 2017, 13, 3236-3249] opens alternative possibilities for performing low-cost molecular computational chemistry calculations. In this work, we present our first attempt to expand the applicability of this method by developing a family of compact general contracted polarization consistent basis sets (PAW-Ln) as an optimized GTF basis in combination with PAW. The results show that PAW-Ln, despite having small numbers of primitives, can provide not only better performance than effective core potential (ECP) but also good accuracy and desirable systematic convergence compared to larger all-electron basis sets. This demonstrates that GTF-PAW using the PAW-Ln basis sets could be a better alternative to both conventional all-electron- and ECP-based approaches for routine DFT calculations.

Anion Photoelectron Spectroscopy and Theoretical Study of HAuCN and [HAuCN]-: Spin-Orbit Coupling and Low-Lying Excited States.

We report a study of the electronic structures and chemical bonding of gaseous [HAuCN]- and the corresponding neutral molecule using photoelectron spectroscopy and relativistic quantum chemistry calculations. The electron affinity of the neutral HAuCN is reported to be 4.75 eV for the first time. The low-lying excited states of neutral molecule are observed and assigned according to the calculations utilizing a sophisticated electron correlation method incorporating both the scalar and spin-orbit relativistic effects. Our theoretical calculations suggest the geometry will be distorted from linear structure to the bent during the process of detaching one electron from the anion. Various chemical bonding analyses based on theoretical calculations have been performed for the titled complexes, and the apparent covalent natures of interactions between gold and the studied ligands have been verified.

Underestimation-Assisted Global-Local Cooperative Differential Evolution and the Application to Protein Structure Prediction.

Various mutation strategies show distinct advantages in differential evolution (DE). The cooperation of multiple strategies in the evolutionary process may be effective. This paper presents an underestimation-assisted global and local cooperative DE to simultaneously enhance the effectiveness and efficiency. In the proposed algorithm, two phases, namely, the global exploration and the local exploitation, are performed in each generation. In the global phase, a set of trial vectors is produced for each target individual by employing multiple strategies with strong exploration capability. Afterward, an adaptive underestimation model with a self-adapted slope control parameter is proposed to evaluate these trial vectors, the best of which is selected as the candidate. In the local phase, the better-based strategies guided by individuals that are better than the target individual are designed. For each individual accepted in the global phase, multiple trial vectors are generated by using these strategies and filtered by the underestimation value. The cooperation between the global and local phases includes two aspects. First, both of them concentrate on generating better individuals for the next generation. Second, the global phase aims to locate promising regions quickly while the local phase serves as a local search for enhancing convergence. Moreover, a simple mechanism is designed to determine the parameter of DE adaptively in the searching process. Finally, the proposed approach is applied to predict the protein 3D structure. Experimental studies on classical benchmark functions, CEC test sets, and protein structure prediction problem show that the proposed approach is superior to the competitors.

Anion photoelectron spectroscopy and chemical bonding of ThO2- and ThO3.

We conducted a study of electronic structures and chemical bonding of gaseous ThO2- and ThO3- using velocity-map imaging and ab initio calculations. The electron affinity of neutral ThO2 molecule is reported for the first time with the value of 1.21(5) eV. We obtained a vibrationally resolved photoelectron spectroscopy of ThO2- and observed the symmetric stretching frequency of 824(40) cm-1 for neutral molecules. One hot band transition is observed in the spectrum of ThO2-, which allows the measurement of symmetric stretching mode for ThO2-. The ground state of ThO2- is 2A1 with C2v symmetry: the detachment of an electron from the singly occupied molecular orbital (SOMO) results in the ground state of ThO2. Kohn-Sham molecular orbital analyses reveal an σ and two weak π bonds for Th-O multiple bonds in ThO2. Global minimum search methodology combined with quantum chemical calculations are used to find the minima of ThO3 and ThO3-, and the adiabatic detachment energy of ThO3- is calculated to be 3.26 eV at the coupled cluster with singles and doubles plus perturbative triples level. Our theoretical calculations suggest that the ground state of ThO3 is 1A' with a symmetry of Cs, while the most stable ThO3- is 2A1 with C2v symmetry; thus, the transition from ThO3- to ThO3 undergoes a significant geometry reorganization. Molecular orbital analyses suggest that the SOMO of ThO3- is mainly participated by O 2p and O to Th back donation was found in HOMO-2 molecular orbital. This investigation will shed some light on the understanding of covalent bonding in Th-contained molecules.

Probing Chemical Bonding and Electronic Structures in ThO- by Anion Photoelectron Imaging and Theoretical Calculations.

Because of renewed research on thorium-based molten salt reactors, there is growing demand and interest in enhancing the knowledge of thorium chemistry both experimentally and theoretically. Compared with uranium, thorium has few chemical studies reported up to the present. Here we report the vibrationally resolved photoelectron imaging of the thorium monoxide anion. The electron affinity of ThO is first reported to be 0.707 ± 0.020 eV. Vibrational frequencies of the ThO molecule and its anion are determined from Franck-Condon simulation. Spectroscopic evidence is obtained for the two-electron transition in ThO-, indicating the strong electron correlation among the (7sσ)2(6dδ)1 electrons in ThO- and the (7sσ)2 electrons in ThO. These findings are explained by using quantum-chemical calculations including spin-orbit coupling, and the chemical bonding of gaseous ThO molecules is analyzed. The present work will enrich our understanding of bonding capacities with the 6d valence shell.

Norovirus outbreaks in Fengtai District, Beijing, China, 2014.

Norovirus (NoV) is the most common cause of non-bacterial acute gastroenteritis (AGE) outbreaks worldwide. Eight NoV outbreaks in the Fengtai District of Beijing City, China, were identified in 2014. Samples were collected from the eight outbreaks, and 73 out of 119 samples from cases and 10 out of 59 samples from the close contacts were positive for NoVs. The genotypes were determined by sequencing analysis. Six different GII genotypes, including GII.2, 4, 6, 7, 8, 14, and 17 were found, and GII.4 was not the local major epidemic genotype in the present study. Enhanced strain surveillance is necessary for future NoV epidemics.

Outbreak of febrile illness caused by coxsackievirus A4 in a nursery school in Beijing, China.

BACKGROUND: Coxsackievirus A4 (CV-A4) is classified as human enterovirus A according to its serotype. CV-A4, an etiological agent of hand, foot, and mouth disease, affects children worldwide and can circulate in closed environments such as schools and hospitals for long periods. FINDINGS: An outbreak of febrile illness at a nursery school in Beijing, China, was confirmed to be caused by CV-A4. Phylogenetic analysis of the complete genome of the isolated strain showed that the virus belongs to the same cluster as the predominant CV-A4 strain in China. This outbreak was controlled by effective measures. CONCLUSIONS: The early identification of the pathogen and timely intervention may be the most critical factors in controlling an outbreak caused by CV-A4 in a preschool.

Tetramethylpyrazine upregulates the aquaporin 8 expression of hepatocellular mitochondria in septic rats.

BACKGROUND: The sepsis-induced acute liver injury majorly depends on the dysfunction of mitochondria and the loss of cellular energy. Aquaporin 8 (AQP8) can modulate water transport and osmotic swelling of mitochondria in the inner mitochondrial membrane of the liver. In this study, we explore the effects of tetramethylpyrazine (TMP) on protecting the structure of hepatocyte mitochondria and modulating the expression of AQP8. MATERIALS AND METHODS: Forty-eight rats were randomly allocated to four groups: control group receiving sham procedure, septic group receiving cecal ligation and puncture (CLP), therapeutic group receiving 60 mg/kg of ligustrazine (TMP) intravenously from caudal vein immediately after CLP, and preventive group receiving 60 mg/kg/d of ligustrazine intravenously from caudal vein for 7 d before CLP. The mitochondrial ultrastructure of rat liver was observed. The protein expression of AQP8 was assayed by Western blot. Analysis of AQP8 messenger RNA (mRNA) expression level was performed by the reverse transcription-polymerase chain reaction. The mean fluorescence intensity (MFI) of rhodamine 123 (Rh 123) was measured by flow cytometry. The serum tumor necrosis factor alpha (TNF-α) level was determined by the enzyme-linked immunosorbent assay. RESULTS: The mitochondrial ultrastructure was markedly damaged in the septic group, whereas it was lightly damaged in the therapeutic and preventive groups. Compared with the control group, the AQP8 protein expression and MFI were significantly reduced, and the steady-state AQP8 mRNA and serum TNF-α levels were increased in the septic, therapeutic, and preventive groups. Compared with the septic group, the AQP8 protein expression and MFI were increased, and the steady-state AQP8 mRNA and serum TNF-α levels were decreased significantly in the therapeutic and preventive groups. There was no significant difference in morphologic characteristics, AQP8 protein level, AQP8 mRNA level, MFI, and serum TNF-α level between the therapeutic and the preventive groups. Linear positive correlation was observed between the AQP8 protein level and the MFI of Rh 123. Linear negative correlation was observed between the AQP8 protein level or the MFI of Rh 123 and serum TNF-α level. CONCLUSIONS: TMP has protective effect on hepatocellular mitochondria from damage in sepsis by ameliorating the expression of AQP8 protein in liver mitochondria. The protective effect of TMP on the liver mitochondria might not have a difference between using TMP before or after the occurrence of sepsis.

[Molecular epidemiological characteristics of HIV-1 B'/C strains in Beijing].

OBJECTIVE: To analyze the molecular epidemiological characteristic of HIV-1 B'/C strains prevalent in Beijing. METHODS: Plasma samples were collected from 200 newly diagnosed HIV-1 B'/C individuals reported during 2006 to 2010 in Beijing. The gag gene fragments were amplified from RNA template extracted from plasma with reverse transcription (RT) and nested polymerase chain reaction (PCR). And the sequences were analyzed by phylogenetic methods and Entropy analysis. RESULTS: A total of 159 sequences were successfully amplified from the gag genes of which 147 was CRF07_BC and 12 CRF08_BC. There were 3 main sub-clusters in CRF07_BC phylogenetic tree and they were named as sub-cluster IDU-Max (89 sequences), sub-cluster IDU-Min (22 sequences) and sub-cluster MSM (34 sequences) based on transmission.No international reference strain was closely related with these three sub-clusters except for one strain identified in Taiwan. All CRF07_BC recombinant strains were remarkable for their low interpatient diversity in gag genes (3.7%, 3.3% and 2.0% for isolates from IDU-Max, IDU-Min and MSM respectively).When compared with sub-cluster IDU-Max, there were 32 and 41 significantly different sites of nucleotide polymorphism compositions in sub-clusters IDU-Min and MSM. CONCLUSION: This is the first report of describing the existence of three main epidemic sub-clusters in CRF07_BC strains prevalent in Beijing. And IDU-Max sub-cluster is the dominant strain. The CRF07_BC in Beijing are less diverse than other strains and may be derived from a common ancestor.

A Comprehensive Review on Biotransformation, Interaction, and Health of Gut Microbiota and Bioactive Components.

BACKGROUND: The relationship between gut microbiota and bioactive components has become the research focus in the world. We attempted to clarify the relationship between biotransformation and metabolites of gut microbiota and bioactive components, and explore the metabolic pathway and mechanism of bioactive ingredients in vivo, which will provide an important theoretical basis for the clinical research of bioactive ingredients and rationality of drugs, and also provide an important reference for the development of new drugs with high bioavailability. METHODS: The related references of this review on microbiota and bioactive components were collected from both online and offline databases, such as ScienceDirect, PubMed, Elsevier, Willy, SciFinder, Google Scholar, Web of Science, Baidu Scholar, SciHub, Scopus, and CNKI. RESULTS: This review summarized the biotransformation of bioactive components under the action of gut microbiota, including flavonoids, terpenoids, phenylpropanoids, alkaloids, steroids, and other compounds. The interaction of bioactive components and gut microbiota is a key link for drug efficacy. Relevant research is crucial to clarify bioactive components and their mechanisms, which involve the complex interaction among bioactive components, gut microbiota, and intestinal epithelial cells. This review also summarized the individualized, precise, and targeted intervention of gut microbiota in the field of intestinal microorganisms from the aspects of dietary fiber, microecological agents, fecal microbiota transplantation, and postbiotics. It will provide an important reference for intestinal microecology in the field of nutrition and health for people. CONCLUSION: To sum up, the importance of human gut microbiota in the research of bioactive components metabolism and transformation has attracted the attention of scholars all over the world. It is believed that with the deepening of research, human gut microbiota will be more widely used in the pharmacodynamic basis, drug toxicity relationship, new drug discovery, drug absorption mechanism, and drug transport mechanism in the future.

DomBpred: Protein Domain Boundary Prediction Based on Domain-Residue Clustering Using Inter-Residue Distance.

Domain boundary prediction is one of the most important problems in the study of protein structure and function, especially for large proteins. At present, most domain boundary prediction methods have low accuracy and limitations in dealing with multi-domain proteins. In this study, we develop a sequence-based protein domain boundary prediction, named DomBpred. In DomBpred, the input sequence is first classified as either a single-domain protein or a multi-domain protein through a designed effective sequence metric based on a constructed single-domain sequence library. For the multi-domain protein, a domain-residue clustering algorithm inspired by Ising model is proposed to cluster the spatially close residues according inter-residue distance. The unclassified residues and the residues at the edge of the cluster are then tuned by the secondary structure to form potential cut points. Finally, a domain boundary scoring function is proposed to recursively evaluate the potential cut points to generate the domain boundary. DomBpred is tested on a large-scale test set of FUpred comprising 2549 proteins. Experimental results show that DomBpred better performs than the state-of-the-art methods in classifying whether protein sequences are composed by single or multiple domains, and the Matthew's correlation coefficient is 0.882. Moreover, on 849 multi-domain proteins, the domain boundary distance and normalised domain overlap scores of DomBpred are 0.523 and 0.824, respectively, which are 5.0% and 4.2% higher than those of the best comparison method, respectively. Comparison with other methods on the given test set shows that DomBpred outperforms most state-of-the-art sequence-based methods and even achieves better results than the top-level template-based method. The executable program is freely available at https://github.com/iobio-zjut/DomBpred and the online server at http://zhanglab-bioinf.com/DomBpred/.