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1.
Anal Chem ; 93(36): 12312-12319, 2021 09 14.
Artigo em Inglês | MEDLINE | ID: mdl-34469131

RESUMO

Direct infusion shotgun proteome analysis (DISPA) is a new paradigm for expedited mass spectrometry-based proteomics, but the original data analysis workflow was onerous. Here, we introduce CsoDIAq, a user-friendly software package for the identification and quantification of peptides and proteins from DISPA data. In addition to establishing a complete and automated analysis workflow with a graphical user interface, CsoDIAq introduces algorithmic concepts to spectrum-spectrum matching to improve peptide identification speed and sensitivity. These include spectra pooling to reduce search time complexity and a new spectrum-spectrum match score called match count and cosine, which improves target discrimination in a target-decoy analysis. Fragment mass tolerance correction also increased the number of peptide identifications. Finally, we adapt CsoDIAq to standard LC-MS DIA and show that it outperforms other spectrum-spectrum matching software.


Assuntos
Proteoma , Software , Algoritmos , Cromatografia Líquida , Bases de Dados de Proteínas , Proteômica
2.
Molecules ; 26(16)2021 Aug 16.
Artigo em Inglês | MEDLINE | ID: mdl-34443534

RESUMO

Thrombosis is a disease that seriously endangers human health, with a high rate of mortality and disability. However, current treatments with thrombolytic drugs (such as recombinant tissue-plasminogen activator) and the oral anticoagulants (such as dabigatran and rivaroxaban) are reported to have a tendency of major or life-threatening bleeding, such as intracranial hemorrhage or massive gastrointestinal bleed with non-specific antidotes. In contrast, lumbrokinase is very specific to fibrin as a substrate and does not cause excessive bleeding. It can dissolve the fibrin by itself or convert plasminogen to plasmin by inducing endogenous t-PA activity to dissolve fibrin clots. Therefore, searching for potentially new therapeutic molecules from earthworms is significant. In this study, we first collected a strong fibrinolytic extract (PvQ) from the total protein of the Pheretima vulgaris with AKTA pure protein purification systems; its fibrinolytic bioactivity was verified by the fibrin plate assay and zebrafish thrombotic model of vascular damage. Furthermore, according to the cell culture model of human umbilical vein endothelial cells (HUVECs), the PvQ was proven to exhibit the ability to promote the secretion of tissue-type plasminogen activator (t-PA), which further illustrated that it has an indirect thrombolytic effect. Subsequently, extensive chromatographic techniques were applied to reveal the material basis of the extract. Fortunately, six novel earthworm fibrinolytic enzymes were obtained from the PvQ, and the primary sequences of those functional proteins were determined by LC-MS/MStranscriptome cross-identification and the Edman degradation assay. The secondary structures of these six fibrinolytic enzymes were determined by circular dichroism spectroscopy and the three-dimensional structures of these proteases were predicted by MODELLER 9.23 based on multi-template modelling. In addition, those six genes encoding blood clot-dissolving proteins were cloned from P. vulgaris by RT-PCR amplification, which further determined the accuracy of proteins primary sequences identifications and laid the foundation for subsequent heterologous expression.


Assuntos
Fibrinolíticos/isolamento & purificação , Fibrinolíticos/farmacologia , Oligoquetos/química , Peptídeo Hidrolases/farmacologia , Trombose/patologia , Sequência de Aminoácidos , Animais , Sequência de Bases , Sobrevivência Celular/efeitos dos fármacos , Bases de Dados de Proteínas , Eritrócitos/efeitos dos fármacos , Fibrinólise/efeitos dos fármacos , Fibrinolíticos/química , Células Endoteliais da Veia Umbilical Humana/citologia , Células Endoteliais da Veia Umbilical Humana/efeitos dos fármacos , Humanos , Modelos Moleculares , Peptídeo Hidrolases/química , Peptídeo Hidrolases/genética , Estrutura Secundária de Proteína , Estrutura Terciária de Proteína , Ativador de Plasminogênio Tecidual/metabolismo , Peixe-Zebra
3.
Int J Mol Sci ; 22(16)2021 Aug 12.
Artigo em Inglês | MEDLINE | ID: mdl-34445370

RESUMO

The PDB database provides more than 150,000 entries for biological macromolecular structures [...].


Assuntos
Proteínas/química , Bases de Dados de Proteínas , Humanos , Modelos Moleculares , Conformação Proteica
4.
Int J Mol Sci ; 22(16)2021 Aug 17.
Artigo em Inglês | MEDLINE | ID: mdl-34445537

RESUMO

Protein Blocks (PBs) are a widely used structural alphabet describing local protein backbone conformation in terms of 16 possible conformational states, adopted by five consecutive amino acids. The representation of complex protein 3D structures as 1D PB sequences was previously successfully applied to protein structure alignment and protein structure prediction. In the current study, we present a new model, PYTHIA (predicting any conformation at high accuracy), for the prediction of the protein local conformations in terms of PBs directly from the amino acid sequence. PYTHIA is based on a deep residual inception-inside-inception neural network with convolutional block attention modules, predicting 1 of 16 PB classes from evolutionary information combined to physicochemical properties of individual amino acids. PYTHIA clearly outperforms the LOCUSTRA reference method for all PB classes and demonstrates great performance for PB prediction on particularly challenging proteins from the CASP14 free modelling category.


Assuntos
Algoritmos , Aprendizado Profundo , Redes Neurais de Computação , Conformação Proteica , Proteínas/química , Análise de Sequência de Proteína/métodos , Software , Bases de Dados de Proteínas , Humanos , Modelos Moleculares
5.
Phys Chem Chem Phys ; 23(32): 17656-17662, 2021 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-34373871

RESUMO

In this manuscript the ability of selenium carbohydrates to undergo chalcogen bonding (ChB) interactions with protein residues has been studied at the RI-MP2/def2-TZVP level of theory. An inspection of the Protein Data Bank (PDB) revealed SeA (A = O, C and S) intermolecular contacts involving Se-pyranose ligands and ASP, TYR, SER and MET residues. Theoretical models were built to analyse the strength and directionality of the interaction together with "Atoms in Molecules" (AIM), Natural Bonding Orbital (NBO) and Non Covalent Interactions plot (NCIplot) analyses, which further assisted in the characterization of the ChBs described herein. We expect that the results from this study will be useful to expand the current knowledge regarding biological ChBs as well as to increase the visibility of the interaction among the carbohydrate chemistry community.


Assuntos
Lectinas/metabolismo , Monossacarídeos/metabolismo , Compostos Organosselênicos/metabolismo , Agaricales/química , Aspergillus oryzae/química , Bases de Dados de Proteínas , Escherichia coli/química , Proteínas de Escherichia coli/química , Proteínas de Escherichia coli/metabolismo , Proteínas Fúngicas/química , Proteínas Fúngicas/metabolismo , Ligação de Hidrogênio , Lectinas/química , Modelos Moleculares , Monossacarídeos/química , Compostos Organosselênicos/química , Ligação Proteica , Selênio/química , Eletricidade Estática , Termodinâmica
6.
Adv Protein Chem Struct Biol ; 127: 161-216, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34340767

RESUMO

With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through different tools sheds light on the particulars of the disease and our body's reactions to it, thus, aiding our understanding of the human health. Most useful of these tools is artificial intelligence and deep learning (DL). The artificially created neural networks in DL algorithms help extract viable data from the datasets, and further, to recognize patters in these complex datasets. Therefore, as a part of machine learning, DL helps us face all the various challenges that come forth during protein prediction, protein identification and their quantification. Proteomics is the study of such proteins, their structures, features, properties and so on. As a form of data science, Proteomics has helped us progress excellently in the field of genomics technologies. One of the major techniques used in proteomics studies is mass spectrometry (MS). However, MS is efficient with analysis of large datasets only with the added help of informatics approaches for data analysis and interpretation; these mainly include machine learning and deep learning algorithms. In this chapter, we will discuss in detail the applications of deep learning and various algorithms of machine learning in proteomics.


Assuntos
Bases de Dados de Proteínas , Aprendizado Profundo , Proteoma/metabolismo , Proteômica , Humanos
7.
Adv Protein Chem Struct Biol ; 127: 217-248, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34340768

RESUMO

Protein structure characterization is fundamental to understand protein properties, such as folding process and protein resistance to thermal stress, up to unveiling organism pathologies (e.g., prion disease). In this chapter, we provide an overview on how the spectral properties of the networks reconstructed from the Protein Contact Map (PCM) can be used to generate informative observables. As a specific case study, we apply two different network approaches to an example protein dataset, for the aim of discriminating protein folding state, and for the reconstruction of protein 3D structure.


Assuntos
Bases de Dados de Proteínas , Dobramento de Proteína , Mapas de Interação de Proteínas , Proteínas/química , Proteínas/metabolismo , Animais , Humanos , Domínios Proteicos , Estabilidade Proteica
8.
Molecules ; 26(16)2021 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-34443345

RESUMO

Protein glycosylation that mediates interactions among viral proteins, host receptors, and immune molecules is an important consideration for predicting viral antigenicity. Viral spike proteins, the proteins responsible for host cell invasion, are especially important to be examined. However, there is a lack of consensus within the field of glycoproteomics regarding identification strategy and false discovery rate (FDR) calculation that impedes our examinations. As a case study in the overlap between software, here as a case study, we examine recently published SARS-CoV-2 glycoprotein datasets with four glycoproteomics identification software with their recommended protocols: GlycReSoft, Byonic, pGlyco2, and MSFragger-Glyco. These software use different Target-Decoy Analysis (TDA) forms to estimate FDR and have different database-oriented search methods with varying degrees of quantification capabilities. Instead of an ideal overlap between software, we observed different sets of identifications with the intersection. When clustering by glycopeptide identifications, we see higher degrees of relatedness within software than within glycosites. Taking the consensus between results yields a conservative and non-informative conclusion as we lose identifications in the desire for caution; these non-consensus identifications are often lower abundance and, therefore, more susceptible to nuanced changes. We conclude that present glycoproteomics softwares are not directly comparable, and that methods are needed to assess their overall results and FDR estimation performance. Once such tools are developed, it will be possible to improve FDR methods and quantify complex glycoproteomes with acceptable confidence, rather than potentially misleading broad strokes.


Assuntos
Algoritmos , Glicopeptídeos/análise , Glicoproteínas/análise , COVID-19/metabolismo , Bases de Dados de Proteínas , Glicopeptídeos/química , Glicoproteínas/química , Glicosilação , Humanos , Proteômica/métodos , Proteômica/normas , SARS-CoV-2/metabolismo , Software , Glicoproteína da Espícula de Coronavírus/análise , Glicoproteína da Espícula de Coronavírus/química , Espectrometria de Massas em Tandem/métodos , Proteínas Virais de Fusão/análise , Proteínas Virais de Fusão/química
9.
Commun Biol ; 4(1): 934, 2021 08 03.
Artigo em Inglês | MEDLINE | ID: mdl-34345007

RESUMO

We describe an analytical method for the identification, mapping and relative quantitation of glycopeptides from SARS-CoV-2 Spike protein. The method may be executed using a LC-TOF mass spectrometer, requires no specialized knowledge of glycan analysis and exploits the differential resolving power of reverse phase HPLC. While this separation technique resolves peptides with high efficiency, glycans are resolved poorly, if at all. Consequently, glycopeptides consisting of the same peptide bearing different glycan structures will all possess very similar retention times and co-elute. Rather than a disadvantage, we show that shared retention time can be used to map multiple glycan species to the same peptide and location. In combination with MSMS and pseudo MS3, we have constructed a detailed mass-retention time database for Spike glycopeptides. This database allows any accurate mass LC-MS laboratory to reliably identify and quantify Spike glycopeptides from a single overnight elastase digest in less than 90 minutes.


Assuntos
Glicopeptídeos/química , Espectrometria de Massas/métodos , Glicoproteína da Espícula de Coronavírus/química , Bases de Dados de Proteínas , Fatores de Tempo
10.
Int J Mol Sci ; 22(15)2021 Aug 03.
Artigo em Inglês | MEDLINE | ID: mdl-34361104

RESUMO

Most non-communicable diseases are associated with dysfunction of proteins or protein complexes. The relationship between sequence and structure has been analyzed for a long time, and the analysis of the sequences organization in domains and motifs remains an actual research area. Here, we propose a mathematical method for revealing the hierarchical organization of protein sequences. The method is based on the pentapeptide as a unit of protein sequences. Employing the frequency of occurrence of pentapeptides in sequences of natural proteins and a special mathematical approach, this method revealed a hierarchical structure in the protein sequence. The method was applied to 24,647 non-homologous protein sequences with sizes ranging from 50 to 400 residues from the NRDB90 database. Statistical analysis of the branching points of the graphs revealed 11 characteristic values of y (the width of the inscribed function), showing the relationship of these multiple fragments of the sequences. Several examples illustrate how fragments of the protein spatial structure correspond to the elements of the hierarchical structure of the protein sequence. This methodology provides a promising basis for a mathematically-based classification of the elements of the spatial organization of proteins. Elements of the hierarchical structure of different levels of the hierarchy can be used to solve biotechnological and medical problems.


Assuntos
Algoritmos , Bases de Dados de Proteínas , Conformação Proteica , Proteínas/química , Humanos , Modelos Moleculares
11.
Int J Mol Sci ; 22(15)2021 Aug 03.
Artigo em Inglês | MEDLINE | ID: mdl-34361108

RESUMO

Alfalfa has emerged as one of the most important forage crops, owing to its wide adaptation and high biomass production worldwide. In the last decade, the emergence of bacterial stem blight (caused by Pseudomonas syringae pv. syringae ALF3) in alfalfa has caused around 50% yield losses in the United States. Studies are being conducted to decipher the roles of the key genes and pathways regulating the disease, but due to the sparse knowledge about the infection mechanisms of Pseudomonas, the development of resistant cultivars is hampered. The database alfaNET is an attempt to assist researchers by providing comprehensive Pseudomonas proteome annotations, as well as a host-pathogen interactome tool, which predicts the interactions between host and pathogen based on orthology. alfaNET is a user-friendly and efficient tool and includes other features such as subcellular localization annotations of pathogen proteins, gene ontology (GO) annotations, network visualization, and effector protein prediction. Users can also browse and search the database using particular keywords or proteins with a specific length. Additionally, the BLAST search tool enables the user to perform a homology sequence search against the alfalfa and Pseudomonas proteomes. With the successful implementation of these attributes, alfaNET will be a beneficial resource to the research community engaged in implementing molecular strategies to mitigate the disease. alfaNET is freely available for public use at http://bioinfo.usu.edu/alfanet/.


Assuntos
Proteínas de Bactérias/metabolismo , Bases de Dados de Proteínas , Interações Hospedeiro-Patógeno , Medicago sativa/metabolismo , Doenças das Plantas/imunologia , Mapas de Interação de Proteínas , Pseudomonas syringae/patogenicidade , Medicago sativa/imunologia , Medicago sativa/microbiologia , Doenças das Plantas/microbiologia
12.
Acta Crystallogr D Struct Biol ; 77(Pt 8): 1040-1049, 2021 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-34342277

RESUMO

The ß-link is a composite protein motif consisting of a G1ß ß-bulge and a type II ß-turn, and is generally found at the end of two adjacent strands of antiparallel ß-sheet. The 1,2-positions of the ß-bulge are also the 3,4-positions of the ß-turn, with the result that the N-terminal portion of the polypeptide chain is orientated at right angles to the ß-sheet. Here, it is reported that the ß-link is frequently found in certain protein folds of the SCOPe structural classification at specific locations where it connects a ß-sheet to another area of a protein. It is found at locations where it connects one ß-sheet to another in the ß-sandwich and related structures, and in small (four-, five- or six-stranded) ß-barrels, where it connects two ß-strands through the polypeptide chain that crosses an open end of the barrel. It is not found in larger (eight-stranded or more) ß-barrels that are straightforward ß-meanders. In some cases it initiates a connection between a single ß-sheet and an α-helix. The ß-link also provides a framework for catalysis in serine proteases, where the catalytic serine is part of a conserved ß-link, and in cysteine proteases, including Mpro of human SARS-CoV-2, in which two residues of the active site are located in a conserved ß-link.


Assuntos
Estrutura Secundária de Proteína , Serina Proteases/química , Motivos de Aminoácidos , Animais , Domínio Catalítico , Proteases 3C de Coronavírus/química , Proteases 3C de Coronavírus/metabolismo , Cisteína Proteases/química , Cisteína Proteases/metabolismo , Bases de Dados de Proteínas , Humanos , Ligação de Hidrogênio , Modelos Moleculares , SARS-CoV-2/química , SARS-CoV-2/enzimologia , Serina Proteases/metabolismo , Homologia Estrutural de Proteína
14.
Nat Commun ; 12(1): 5011, 2021 08 18.
Artigo em Inglês | MEDLINE | ID: mdl-34408149

RESUMO

Sequence-based contact prediction has shown considerable promise in assisting non-homologous structure modeling, but it often requires many homologous sequences and a sufficient number of correct contacts to achieve correct folds. Here, we developed a method, C-QUARK, that integrates multiple deep-learning and coevolution-based contact-maps to guide the replica-exchange Monte Carlo fragment assembly simulations. The method was tested on 247 non-redundant proteins, where C-QUARK could fold 75% of the cases with TM-scores (template-modeling scores) ≥0.5, which was 2.6 times more than that achieved by QUARK. For the 59 cases that had either low contact accuracy or few homologous sequences, C-QUARK correctly folded 6 times more proteins than other contact-based folding methods. C-QUARK was also tested on 64 free-modeling targets from the 13th CASP (critical assessment of protein structure prediction) experiment and had an average GDT_TS (global distance test) score that was 5% higher than the best CASP predictors. These data demonstrate, in a robust manner, the progress in modeling non-homologous protein structures using low-accuracy and sparse contact-map predictions.


Assuntos
Biologia Computacional/métodos , Proteínas/química , Bases de Dados de Proteínas , Modelos Moleculares , Método de Monte Carlo , Conformação Proteica , Dobramento de Proteína , Proteínas/genética , Software
15.
Biomolecules ; 11(6)2021 06 11.
Artigo em Inglês | MEDLINE | ID: mdl-34208298

RESUMO

Lysine succinylation is an important post-translational modification, whose abnormalities are closely related to the occurrence and development of many diseases. Therefore, exploring effective methods to identify succinylation sites is helpful for disease treatment and research of related drugs. However, most existing computational methods for the prediction of succinylation sites are still based on machine learning. With the increasing volume of data and complexity of feature representations, it is necessary to explore effective deep learning methods to recognize succinylation sites. In this paper, we propose a multilane dense convolutional attention network, MDCAN-Lys. MDCAN-Lys extracts sequence information, physicochemical properties of amino acids, and structural properties of proteins using a three-way network, and it constructs feature space. For each sub-network, MDCAN-Lys uses the cascading model of dense convolutional block and convolutional block attention module to capture feature information at different levels and improve the abstraction ability of the network. The experimental results of 10-fold cross-validation and independent testing show that MDCAN-Lys can recognize more succinylation sites, which is consistent with the conclusion of the case study. Thus, it is worthwhile to explore deep learning-based methods for the recognition of succinylation sites.


Assuntos
Previsões/métodos , Lisina/química , Processamento de Proteína Pós-Traducional/fisiologia , Ácido Succínico/química , Algoritmos , Sequência de Aminoácidos/genética , Aminoácidos/química , Animais , Biologia Computacional/métodos , Bases de Dados de Proteínas , Humanos , Aprendizado de Máquina , Proteínas/química
16.
Nat Methods ; 18(7): 806-815, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-34211188

RESUMO

Co-fractionation mass spectrometry (CF-MS) has emerged as a powerful technique for interactome mapping. However, there is little consensus on optimal strategies for the design of CF-MS experiments or their computational analysis. Here, we reanalyzed a total of 206 CF-MS experiments to generate a uniformly processed resource containing over 11 million measurements of protein abundance. We used this resource to benchmark experimental designs for CF-MS studies and systematically optimize computational approaches to network inference. We then applied this optimized methodology to reconstruct a draft-quality human interactome by CF-MS and predict over 700,000 protein-protein interactions across 27 eukaryotic species or clades. Our work defines new resources to illuminate proteome organization over evolutionary timescales and establishes best practices for the design and analysis of CF-MS studies.


Assuntos
Espectrometria de Massas/métodos , Mapeamento de Interação de Proteínas/métodos , Proteoma/análise , Animais , Evolução Biológica , Fracionamento Químico , Bases de Dados de Proteínas , Humanos , Camundongos , Plasmodium berghei/química , Plasmodium berghei/metabolismo , Proteômica/métodos
17.
Nat Commun ; 12(1): 4242, 2021 07 13.
Artigo em Inglês | MEDLINE | ID: mdl-34257289

RESUMO

Humankind is generating digital data at an exponential rate. These data are typically stored using electronic, magnetic or optical devices, which require large physical spaces and cannot last for a very long time. Here we report the use of peptide sequences for data storage, which can be durable and of high storage density. With the selection of suitable constitutive amino acids, designs of address codes and error-correction schemes to protect the order and integrity of the stored data, optimization of the analytical protocol and development of a software to effectively recover peptide sequences from the tandem mass spectra, we demonstrated the feasibility of this method by successfully storing and retrieving a text file and the music file Silent Night with 40 and 511 18-mer peptides respectively. This method for the first time links data storage with the peptide synthesis industry and proteomics techniques, and is expected to stimulate the development of relevant fields.


Assuntos
Bases de Dados de Proteínas , Software , Algoritmos , Animais , Humanos , Proteômica/métodos
18.
Science ; 373(6557): 871-876, 2021 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-34282049

RESUMO

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.


Assuntos
Aprendizado Profundo , Conformação Proteica , Dobramento de Proteína , Proteínas/química , Proteínas ADAM/química , Sequência de Aminoácidos , Simulação por Computador , Microscopia Crioeletrônica , Cristalografia por Raios X , Bases de Dados de Proteínas , Proteínas de Membrana/química , Modelos Moleculares , Complexos Multiproteicos/química , Redes Neurais de Computação , Subunidades Proteicas/química , Proteínas/fisiologia , Receptores Acoplados a Proteínas G/química , Esfingosina N-Aciltransferase/química
19.
Molecules ; 26(13)2021 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-34206860

RESUMO

In this paper, a combination of modification of the source and regulation of the process was used to control the degradation of PBDEs by plants and microorganisms. First, the key proteins that can degrade PBDEs in plants and microorganisms were searched in the PDB (Protein Data Bank), and a molecular docking method was used to characterize the binding ability of PBDEs to two key proteins. Next, the synergistic binding ability of PBDEs to the two key proteins was evaluated based on the queuing integral method. Based on this, three groups of three-dimensional quantitative structure-activity relationship (3D-QSAR) models of plant-microbial synergistic degradation were constructed. A total of 30 PBDE derivatives were designed using BDE-3 as the template molecule. Among them, the effect on the synergistic degradation of six PBDE derivatives, including BDE-3-4, was significantly improved (increased by more than 20%) and the environment-friendly and functional evaluation parameters were improved. Subsequently, studies on the synergistic degradation of PBDEs and their derivatives by plants and microorganisms, based on the molecular docking method, found that the addition of lipophilic groups by modification is beneficial to enhance the efficiency of synergistic degradation of PBDEs by plants and microorganisms. Further, while docking PBDEs, the number of amino acids was increased and the binding bond length was decreased compared to the template molecules, i.e., PBDE derivatives could be naturally degraded more efficiently. Finally, molecular dynamics simulation by the Taguchi orthogonal experiment and a full factorial experimental design were used to simulate the effects of various regulatory schemes on the synergistic degradation of PBDEs by plants and microorganisms. It was found that optimal regulation occurred when the appropriate amount of carbon dioxide was supplied to the plant and microbial systems. This paper aims to provide theoretical support for enhancing the synergistic degradation of PBDEs by plants and microorganisms in e-waste dismantling sites and their surrounding polluted areas, as well as, realize the research and development of green alternatives to PBDE flame retardants.


Assuntos
Retardadores de Chama/análise , Éteres Difenil Halogenados/química , Plantas/metabolismo , Poluentes do Solo/química , Solo/química , Dióxido de Carbono/química , Dióxido de Carbono/metabolismo , Bases de Dados de Proteínas , Éteres Difenil Halogenados/análise , Modelos Moleculares , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Relação Quantitativa Estrutura-Atividade , Microbiologia do Solo
20.
Molecules ; 26(13)2021 Jun 24.
Artigo em Inglês | MEDLINE | ID: mdl-34202892

RESUMO

Computational analysis of protein-ligand interactions is of crucial importance for drug discovery. Assessment of ligand binding energy allows us to have a glimpse of the potential of a small organic molecule to be a ligand to the binding site of a protein target. Available scoring functions, such as in docking programs, all rely on equations that sum each type of protein-ligand interactions in order to predict the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. Electrostatic interactions constitute one of the most important part of total interactions between macromolecules. Unlike dispersion forces, they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In this study, complexes of HIV-1 protease with inhibitor molecules (JE-2147 and darunavir) were analyzed by using charge densities from the transferable aspherical-atom University at Buffalo Databank (UBDB). Moreover, we analyzed the electrostatic interaction energy for an ensemble of structures, using molecular dynamic simulations to highlight the main features of electrostatic interactions important for binding affinity.


Assuntos
Bases de Dados de Proteínas , Inibidores da Protease de HIV/química , Protease de HIV/química , HIV-1/enzimologia , Simulação de Dinâmica Molecular
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