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2.
Sci Total Environ ; 923: 171315, 2024 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-38431177

RESUMO

Development of microalgal-bacterial granular sludge (MBGS) from saline-adapted microalgae is a promising approach for efficient mariculture wastewater treatment, whereas the elusive mechanisms governing granulation have impeded its widespread adoption. In this study, spherical and regular MBGS were successfully developed from mixed culture of pure Spirulina platensis and Chlorella sp. GY-H4 at 10 mg/L Fe2+ concentration. The addition of Fe2+ was proven to induce the formation of Fe-precipitates which served as nucleation sites for microbial attachment and granulation initiation. Additionally, Fe2+ increased the prevalence of exopolysaccharide-producing cyanobacteria, i.e. Synechocystis and Leptolyngbya, facilitating microbial cell adhesion. Furthermore, it stimulated the secretion of extracellular proteins (particularly tryptophan and aromatic proteins), which acted as structural backbone for the development of spherical granule form microalgal flocs. Lastly, it fostered the accumulation of exogenous heterotrophic functional genera, resulting in the efficient removal of DOC (98 %), PO43--P (98 %) and NH4+-N (87 %). Nevertheless, inadequate Fe2+ hindered microalgal floc transformation into granules, excessive Fe2+ expanded the anaerobic zone within the granules, almost halved protein content in the TB-EPS, and inhibited the functional genes expression, ultimately leading to an irregular granular morphology and diminished nutrient removal. This research provides valuable insights into the mechanisms by which Fe2+ promotes the granulation of salt-tolerant microalgae, offering guidance for the establishment and stable operation of MBGS systems in mariculture wastewater treatment.


Assuntos
Chlorella , Microalgas , Purificação da Água , Águas Residuárias , Microalgas/metabolismo , Esgotos/química , Proteínas/metabolismo , Bactérias , Purificação da Água/métodos , Ferro/metabolismo , Biomassa , Nitrogênio/metabolismo
3.
ACS Sens ; 9(3): 1239-1251, 2024 Mar 22.
Artigo em Inglês | MEDLINE | ID: mdl-38436286

RESUMO

Extracellular vesicles (EVs) are nanometric lipid vesicles that shuttle cargo between cells. Their analysis could shed light on health and disease conditions, but EVs must first be preserved, extracted, and often preconcentrated. Here we first compare plasma preservation agents, and second, using both plasma and cell supernatant, four EV extraction methods, including (i) ultracentrifugation (UC), (ii) size-exclusion chromatography (SEC), (iii) centrifugal filtration (LoDF), and (iv) accousto-sorting (AcS). We benchmarked them by characterizing the integrity, size distribution, concentration, purity, and expression profiles for nine proteins of EVs, as well as the overall throughput, time-to-result, and cost. We found that the difference between ethylenediaminetetraacetic acid (EDTA) and citrate anticoagulants varies with the extraction method. In our hands, ultracentrifugation produced a high yield of EVs with low contamination; SEC is low-cost, fast, and easy to implement, but the purity of EVs is lower; LoDF and AcS are both compatible with process automation, small volume requirement, and rapid processing times. When using plasma, LoDF was susceptible to clogging and sample contamination, while AcS featured high purity but a lower yield of extraction. Analysis of protein profiles suggests that the extraction methods extract different subpopulations of EVs. Our study highlights the strengths and weaknesses of sample preprocessing methods, and the variability in concentration, purity, and EV expression profiles of the extracted EVs. Preanalytical parameters such as collection or preprocessing protocols must be considered as part of the entire process in order to address EV diversity and their use as clinically actionable indicators.


Assuntos
Vesículas Extracelulares , Vesículas Extracelulares/metabolismo , Cromatografia em Gel , Proteínas/análise , Ultracentrifugação/métodos
4.
Anal Chem ; 96(12): 4960-4968, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38436624

RESUMO

The emergence of complex biological modalities in the biopharmaceutical industry entails a significant expansion of the current analytical toolbox to address the need to deploy meaningful and reliable assays at an unprecedented pace. Size exclusion chromatography (SEC) is an industry standard technique for protein separation and analysis. Some constraints of traditional SEC stem from its restricted ability to resolve complex mixtures and notoriously long run times while also requiring multiple offline separation conditions on different pore size columns to cover a wider molecular size distribution. Two-dimensional liquid chromatography (2D-LC) is becoming an important tool not only to increase peak capacity but also to tune selectivity in a single online method. Herein, an online 2D-LC framework in which both dimensions utilize SEC columns with different pore sizes is introduced with a goal to increase throughput for biomolecule separation and characterization. In addition to improving the separation of closely related species, this online 2D SEC-SEC approach also facilitated the rapid analysis of protein-based mixtures of a wide molecular size range in a single online experimental run bypassing time-consuming deployment of different offline SEC methods. By coupling the second dimension with multiangle light scattering (MALS) and differential refractive index (dRI) detectors, absolute molecular weights of the separated species were obtained without the use of calibration curves. As illustrated in this report for protein mixtures and vaccine processes, this workflow can be used in scenarios where rapid development and deployment of SEC assays are warranted, enabling bioprocess monitoring, purity assessment, and characterization.


Assuntos
Produtos Biológicos , Refratometria , Fluxo de Trabalho , Cromatografia em Gel , Proteínas/análise
5.
J Chem Theory Comput ; 20(6): 2618-2629, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38447049

RESUMO

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and ß2-adrenergic receptor (ß2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.


Assuntos
Simulação de Dinâmica Molecular , Proteínas , Conformação Proteica , Proteínas/química , Solventes/química , Lipídeos
6.
Biomed Pharmacother ; 173: 116393, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38461684

RESUMO

Urinary extracellular vesicles (uEVs) play important roles in physiologic condition and various renal/urological disorders. However, their roles in kidney stone disease remain unclear. This study aimed to examine modulatory effects of large and small uEVs derived from normal human urine on calcium oxalate (CaOx) crystals (the main component in kidney stones). After isolation, large uEVs, small uEVs and total urinary proteins (TUPs) with equal (protein equivalent) concentration were added into various crystal assays to compare with the control (without uEVs or TUPs). TUPs strongly inhibited CaOx crystallization, growth, aggregation and crystal-cell adhesion. Large uEVs had lesser degree of inhibition against crystallization, growth and crystal-cell adhesion, and comparable degree of aggregation inhibition compared with TUPs. Small uEVs had comparable inhibitory effects as of TUPs for all these crystal assays. However, TUPs and large uEVs slightly promoted CaOx invasion through extracellular matrix, whereas small uEVs did not affect this. Matching of the proteins reported in six uEVs datasets with those in the kidney stone modulator (StoneMod) database revealed that uEVs contained 18 known CaOx stone modulators (mainly inhibitors). These findings suggest that uEVs derived from normal human urine serve as CaOx stone inhibitors to prevent healthy individuals from kidney stone formation.


Assuntos
Oxalato de Cálcio , Cálculos Renais , Pirenos , Humanos , Oxalato de Cálcio/metabolismo , Cristalização , Cálculos Renais/metabolismo , Proteínas , Matriz Extracelular/metabolismo
7.
J Chem Theory Comput ; 20(6): 2643-2654, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38465868

RESUMO

It is well-known that proline (Pro) cis-trans isomerization plays a decisive role in the folding and stabilization of proteins. The conformational coupling between isomerization states of different Pro residues in proteins during conformational adaptation processes is not well understood. In the present work, we investigate the coupled cis-trans isomerization of three Pro residues using bradykinin (BK), a partially unstructured nonapeptide hormone, as a model system. We use a recently developed enhanced-sampling molecular dynamics method (ω-bias potential replica exchange molecular dynamics; ωBP-REMD) that allows us to exhaustively sample all combinations of Pro isomer states and obtain converged probability densities of all eight state combinations within 885 ns ωBP-REMD simulations. In agreement with experiment, the all-trans state is seen to be the preferred isomer of zwitterionic aqueous BK. In about a third of its structures, this state presents the characteristic C-terminal ß-turn conformation; however, other isomer combinations also contribute significantly to the structural ensemble. Unbiased probabilities can be projected onto the peptide bond dihedral angles of the three Pro residues. This unveils the interdependence of the individual Pro isomerization states, i.e., a possible coupling of the different Pro isomers. The cis/trans equilibrium of a Pro residue can change by up to 2.5 kcal·mol-1, depending on the isomerization state of other Pro residues. For example, for Pro7, the simulations indicate that its cis state becomes favored compared to its trans state when Pro2 is switched from the trans state to the cis state. Our findings demonstrate the efficiency of the ωBP-REMD methodology and suggest that the coupling of Pro isomerization states may play an even more decisive role in larger folded proteins subject to more conformational restraints.


Assuntos
Bradicinina , Prolina , Conformação Proteica , Prolina/química , Termodinâmica , Proteínas
8.
Anal Chem ; 96(12): 4868-4875, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38466774

RESUMO

Protein film electrochemistry is a technique in which an enzyme is immobilized on an electrode in a configuration that allows following the changes in turnover frequency as a response to changes in the experimental conditions. Insights into the reactivity of the enzyme can be obtained by quantitatively modeling such responses. As a consequence, the more the technique allows flexibility in changing conditions, the more useful it becomes. The most commonly used setup, based on the rotating disc electrode, allows easy stepwise increases in the concentration of nongaseous substrates, or exposure to constant concentration of dissolved gas, but does not permit to easily decrease the concentration of nongaseous substrates, or to change the concentration of dissolved gas in a stepwise fashion. To overcome the limitation by mass transport of the substrate toward the electrode when working with fast enzymes, we have designed another kind of electrochemical cell based on the wall-tube electrode (WTE). We demonstrate here that by using a system combining two syringe pumps, a commercial mixer, and the WTE, it is possible to change the concentration of species in a stepwise fashion in all directions, opening new possibilities to study redox enzymes. As a proof of concept, this device was applied to the study of the electrochemical response of the cytochrome c nitrite reductase of Desulfovibrio desulfuricans.


Assuntos
Proteínas , Eletroquímica/métodos , Oxirredução , Eletrodos
9.
ACS Nano ; 18(12): 8649-8662, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38471029

RESUMO

There has been much interest in integrating various inorganic nanoparticles (nanoscale colloids) in biology and medicine. However, buildup of a protein corona around the nanoparticles in biological media, driven by nonspecific interactions, remains a major hurdle for the translation of nanomedicine into clinical applications. In this study, we investigate the interactions between gold nanoparticles and serum proteins using a series of dihydrolipoic acid (DHLA)-based ligands. We employed gel electrophoresis combined with UV-vis absorption and dynamic light scattering to correlate protein adsorption with the nature and size of the ligand used. For instance, we found that AuNPs capped with DHLA alone promote nonspecific protein adsorption. In comparison, capping AuNPs with polyethylene glycol- or zwitterion-appended DHLA essentially prevents corona formation, regardless of ligand charge and size. Our results highlight the crucial role of surface chemistry and core material in protein corona formation and offer valuable information for the design of colloidal nanomaterials for biological applications.


Assuntos
Nanopartículas Metálicas , Nanopartículas , Coroa de Proteína , Ouro , Ligantes , Proteínas
10.
PLoS Comput Biol ; 20(3): e1011939, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38484014

RESUMO

Post-translational modifications (PTMs) of proteins play a vital role in their function and stability. These modifications influence protein folding, signaling, protein-protein interactions, enzyme activity, binding affinity, aggregation, degradation, and much more. To date, over 400 types of PTMs have been described, representing chemical diversity well beyond the genetically encoded amino acids. Such modifications pose a challenge to the successful design of proteins, but also represent a major opportunity to diversify the protein engineering toolbox. To this end, we first trained artificial neural networks (ANNs) to predict eighteen of the most abundant PTMs, including protein glycosylation, phosphorylation, methylation, and deamidation. In a second step, these models were implemented inside the computational protein modeling suite Rosetta, which allows flexible combination with existing protocols to model the modified sites and understand their impact on protein stability as well as function. Lastly, we developed a new design protocol that either maximizes or minimizes the predicted probability of a particular site being modified. We find that this combination of ANN prediction and structure-based design can enable the modification of existing, as well as the introduction of novel, PTMs. The potential applications of our work include, but are not limited to, glycan masking of epitopes, strengthening protein-protein interactions through phosphorylation, as well as protecting proteins from deamidation liabilities. These applications are especially important for the design of new protein therapeutics where PTMs can drastically change the therapeutic properties of a protein. Our work adds novel tools to Rosetta's protein engineering toolbox that allow for the rational design of PTMs.


Assuntos
Processamento de Proteína Pós-Traducional , Proteínas , Proteínas/química , Fosforilação , Glicosilação , Aprendizado de Máquina
11.
Langmuir ; 40(12): 6587-6594, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38486393

RESUMO

The coupling between different vibrational modes in proteins is essential for chemical dynamics and biological functions and is linked to the propagation of conformational changes and pathways of allosteric communication. However, little is known about the influence of intermolecular protein-H2O coupling on the vibrational coupling between amide A (NH) and amide I (C═O) bands. Here, we investigate the NH/CO coupling strength in various peptides with different secondary structures at the lipid cell membrane/H2O interface using femtosecond time-resolved sum frequency generation vibrational spectroscopy (SFG-VS) in which a femtosecond infrared pump is used to excite the amide A band, and SFG-VS is used to probe transient spectral evolution in the amide A and amide I bands. Our results reveal that the NH/CO coupling strength strongly depends on the bandwidth of the amide I mode and the coupling of proteins with water molecules. A large extent of protein-water coupling significantly reduces the delocalization of the amide I mode along the peptide chain and impedes the NH/CO coupling strength. A large NH/CO coupling strength is found to show a strong correlation with the high energy transfer rate found in the light-harvesting proteins of green sulfur bacteria, which may understand the mechanism of energy transfer through a molecular system and assist in controlling vibrational energy transfer by engineering the molecular structures to achieve high energy transfer efficiency.


Assuntos
Amidas , Água , Amidas/química , Água/química , Espectrofotometria Infravermelho/métodos , Proteínas/química , Peptídeos/química , Vibração
12.
Proc Natl Acad Sci U S A ; 121(12): e2315707121, 2024 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-38489388

RESUMO

KCTD10 belongs to the KCTD (potassiumchannel tetramerization domain) family, many members of which are associated with neuropsychiatric disorders. However, the biological function underlying the association with brain disorders remains to be explored. Here, we reveal that Kctd10 is highly expressed in neuronal progenitors and layer V neurons throughout brain development. Kctd10 deficiency triggers abnormal proliferation and differentiation of neuronal progenitors, reduced deep-layer (especially layer V) neurons, increased upper-layer neurons, and lowered brain size. Mechanistically, we screened and identified a unique KCTD10-interacting protein, KCTD13, associated with neurodevelopmental disorders. KCTD10 mediated the ubiquitination-dependent degradation of KCTD13 and KCTD10 ablation resulted in a considerable increase of KCTD13 expression in the developing cortex. KCTD13 overexpression in neuronal progenitors led to reduced proliferation and abnormal cell distribution, mirroring KCTD10 deficiency. Notably, mice with brain-specific Kctd10 knockout exhibited obvious motor deficits. This study uncovers the physiological function of KCTD10 and provides unique insights into the pathogenesis of neurodevelopmental disorders.


Assuntos
Encefalopatias , Transtornos do Neurodesenvolvimento , Canais de Potássio de Abertura Dependente da Tensão da Membrana , Animais , Camundongos , Proteínas/metabolismo , Encéfalo/metabolismo , Neurônios/metabolismo , Transtornos do Neurodesenvolvimento/genética , Encefalopatias/genética , Neurogênese/genética , Canais de Potássio de Abertura Dependente da Tensão da Membrana/metabolismo
13.
Protein Sci ; 33(4): e4922, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38501482

RESUMO

The present work describes an update to the protein covalent geometry and atomic radii parameters in the Xplor-NIH biomolecular structure determination package. In combination with an improved treatment of selected non-bonded interactions between atoms three bonds apart, such as those involving methyl hydrogens, and a previously developed term that affects the system's gyration volume, the new parameters are tested using structure calculations on 30 proteins with restraints derived from nuclear magnetic resonance data. Using modern structure validation criteria, including several formally adopted by the Protein Data Bank, and a clear measure of structural accuracy, the results show superior performance relative to previous Xplor-NIH implementations. Additionally, the Xplor-NIH structures compare favorably against originally determined NMR models.


Assuntos
Proteínas , Software , Proteínas/química , Espectroscopia de Ressonância Magnética/métodos , Ressonância Magnética Nuclear Biomolecular/métodos , Conformação Proteica
14.
J Vis Exp ; (205)2024 Mar 08.
Artigo em Inglês | MEDLINE | ID: mdl-38526130

RESUMO

Protocols for robotic protein crystallization using the Crystallization Facility at Harwell and in situ room temperature data collection from crystallization plates at Diamond Light Source beamline VMXi are described. This approach enables high-quality room-temperature crystal structures to be determined from multiple crystals in a straightforward manner and provides very rapid feedback on the results of crystallization trials as well as enabling serial crystallography. The value of room temperature structures in understanding protein structure, ligand binding, and dynamics is becoming increasingly recognized in the structural biology community. This pipeline is accessible to users from all over the world with several available modes of access. Crystallization experiments that are set up can be imaged and viewed remotely with crystals identified automatically using a machine learning tool. Data are measured in a queue-based system with up to 60° rotation datasets from user-selected crystals in a plate. Data from all the crystals within a particular well or sample group are automatically merged using xia2.multiplex with the outputs straightforwardly accessed via a web browser interface.


Assuntos
Proteínas , Síncrotrons , Cristalização/métodos , Cristalografia por Raios X , Temperatura , Proteínas/química , Coleta de Dados
15.
J Vis Exp ; (205)2024 Mar 08.
Artigo em Inglês | MEDLINE | ID: mdl-38526125

RESUMO

Single-use laboratory plastics exacerbate the pollution crisis and contribute to consumable costs. In extracellular vesicle (EV) isolation, polycarbonate ultracentrifuge (UC) tubes are used to endure the associated high centrifugal forces. EV proteomics is an advancing field and validated re-use protocols for these tubes are lacking. Re-using consumables for low-yield protein isolation protocols and downstream proteomics requires reagent compatibility with mass spectroscopy acquisitions, such as the absence of centrifuge tube-derived synthetic polymer contamination, and sufficient removal of residual proteins. This protocol describes and validates a method for cleaning polycarbonate UC tubes for re-use in EV proteomics experiments. The cleaning process involves immediate submersion of UC tubes in H2O to prevent protein drying, washing in 0.1% sodium dodecyl sulfate (SDS) detergent, rinsing in hot tap water, demineralized water, and 70% ethanol. To validate the UC tube re-use protocol for downstream EV proteomics, used tubes were obtained following an experiment isolating EVs from cardiovascular tissue using differential UC and density gradient separation. Tubes were cleaned and the experimental process was repeated without EV samples comparing blank never-used UC tubes to cleaned UC tubes. The pseudo-EV pellets obtained from the isolation procedures were lysed and prepared for liquid chromatography-tandem mass spectrometry using a commercial protein sample preparation kit with modifications for low-abundance protein samples. Following cleaning, the number of identified proteins was reduced by 98% in the pseudo-pellet versus the previous EV isolation sample from the same tube. Comparing a cleaned tube against a blank tube, both samples contained a very small number of proteins (≤20) with 86% similarity. The absence of polymer peaks in the chromatograms of the cleaned tubes was confirmed. Ultimately, the validation of a UC tube cleaning protocol suitable for the enrichment of EVs will reduce the waste produced by EV laboratories and lower the experimental costs.


Assuntos
Vesículas Extracelulares , Cimento de Policarboxilato , Proteômica , Proteômica/métodos , Vesículas Extracelulares/metabolismo , Proteínas/metabolismo , Polímeros/análise , Água/metabolismo
16.
J Chem Inf Model ; 64(6): 1806-1815, 2024 Mar 25.
Artigo em Inglês | MEDLINE | ID: mdl-38458968

RESUMO

Predicting the protein-nucleic acid (PNA) binding affinity solely from their sequences is of paramount importance for the experimental design and analysis of PNA interactions (PNAIs). A large number of currently developed models for binding affinity prediction are limited to specific PNAIs while also relying on the sequence and structural information of the PNA complexes for both training and testing, and also as inputs. As the PNA complex structures available are scarce, this significantly limits the diversity and generalizability due to the small training data set. Additionally, a majority of the tools predict a single parameter, such as binding affinity or free energy changes upon mutations, rendering a model less versatile for usage. Hence, we propose DeePNAP, a machine learning-based model built from a vast and heterogeneous data set with 14,401 entries (from both eukaryotes and prokaryotes) from the ProNAB database, consisting of wild-type and mutant PNA complex binding parameters. Our model precisely predicts the binding affinity and free energy changes due to the mutation(s) of PNAIs exclusively from their sequences. While other similar tools extract features from both sequence and structure information, DeePNAP employs sequence-based features to yield high correlation coefficients between the predicted and experimental values with low root mean squared errors for PNA complexes in predicting KD and ΔΔG, implying the generalizability of DeePNAP. Additionally, we have also developed a web interface hosting DeePNAP that can serve as a powerful tool to rapidly predict binding affinities for a myriad of PNAIs with high precision toward developing a deeper understanding of their implications in various biological systems. Web interface: http://14.139.174.41:8080/.


Assuntos
Aprendizado Profundo , Ácidos Nucleicos , Ligação Proteica , Proteínas/química , Mutação
17.
Comput Biol Med ; 172: 108227, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38460308

RESUMO

Accurately predicting protein-ATP binding residues is critical for protein function annotation and drug discovery. Computational methods dedicated to the prediction of binding residues based on protein sequence information have exhibited notable advancements in predictive accuracy. Nevertheless, these methods continue to grapple with several formidable challenges, including limited means of extracting more discriminative features and inadequate algorithms for integrating protein and residue information. To address the problems, we propose ATP-Deep, a novel protein-ATP binding residues predictor. ATP-Deep harnesses the capabilities of unsupervised pre-trained language models and incorporates domain-specific evolutionary context information from homologous sequences. It further refines the embedding at the residue level through integration with corresponding protein-level information and employs a contextual-based co-attention mechanism to adeptly fuse multiple sources of features. The performance evaluation results on the benchmark datasets reveal that ATP-Deep achieves an AUC of 0.954 and 0.951, respectively, surpassing the performance of the state-of-the-art model. These findings underscore the effectiveness of assimilating protein-level information and deploying a contextual-based co-attention mechanism grounded in context to bolster the prediction performance of protein-ATP binding residues.


Assuntos
Algoritmos , Proteínas , Ligação Proteica , Proteínas/química , Sequência de Aminoácidos , Trifosfato de Adenosina
18.
J Chem Inf Model ; 64(6): 1907-1918, 2024 Mar 25.
Artigo em Inglês | MEDLINE | ID: mdl-38470995

RESUMO

The protein-ligand binding free energy is a central quantity in structure-based computational drug discovery efforts. Although popular alchemical methods provide sound statistical means of computing the binding free energy of a large breadth of systems, they are generally too costly to be applied at the same frequency as end point or ligand-based methods. By contrast, these data-driven approaches are typically fast enough to address thousands of systems but with reduced transferability to unseen systems. We introduce DrΔG-Net (or simply Dragnet), an equivariant graph neural network that can blend ligand-based and protein-ligand data-driven approaches. It is based on a 3D fingerprint representation of the ligand alone and in complex with the protein target. Dragnet is a global scoring function to predict the binding affinity of arbitrary protein-ligand complexes, but can be easily tuned via transfer learning to specific systems or end points, performing similarly to common 2D ligand-based approaches in these tasks. Dragnet is evaluated on a total of 28 validation proteins with a set of congeneric ligands derived from the Binding DB and one custom set extracted from the ChEMBL Database. In general, a handful of experimental binding affinities are sufficient to optimize the scoring function for a particular protein and ligand scaffold. When not available, predictions from physics-based methods such as absolute free energy perturbation can be used for the transfer learning tuning of Dragnet. Furthermore, we use our data to illustrate the present limitations of data-driven modeling of binding free energy predictions.


Assuntos
Redes Neurais de Computação , Proteínas , Ligantes , Proteínas/química , Entropia , Ligação Proteica
19.
Biomed Mater ; 19(3)2024 Mar 25.
Artigo em Inglês | MEDLINE | ID: mdl-38471163

RESUMO

Exosomes, typically 30-150 nm in size, are lipid-bilayered small-membrane vesicles originating in endosomes. Exosome biogenesis is regulated by the coordination of various mechanisms whereby different cargoes (e.g. proteins, nucleic acids, and lipids) are sorted into exosomes. These components endow exosomes with bioregulatory functions related to signal transmission and intercellular communication. Exosomes exhibit substantial potential as drug-delivery nanoplatforms owing to their excellent biocompatibility and low immunogenicity. Proteins, miRNA, siRNA, mRNA, and drugs have been successfully loaded into exosomes, and these exosome-based delivery systems show satisfactory therapeutic effects in different disease models. To enable targeted drug delivery, genetic engineering and chemical modification of the lipid bilayer of exosomes are performed. Stimuli-responsive delivery nanoplatforms designed with appropriate modifications based on various stimuli allow precise control of on-demand drug delivery and can be utilized in clinical treatment. In this review, we summarize the general properties, isolation methods, characterization, biological functions, and the potential role of exosomes in therapeutic delivery systems. Moreover, the effective combination of the intrinsic advantages of exosomes and advanced bioengineering, materials science, and clinical translational technologies are required to accelerate the development of exosome-based delivery nanoplatforms.


Assuntos
Exossomos , MicroRNAs , Exossomos/química , MicroRNAs/metabolismo , Sistemas de Liberação de Medicamentos/métodos , Proteínas/metabolismo , RNA Interferente Pequeno
20.
J Chem Inf Model ; 64(6): 2112-2124, 2024 Mar 25.
Artigo em Inglês | MEDLINE | ID: mdl-38483249

RESUMO

Cyclic peptides have emerged as a highly promising class of therapeutic molecules owing to their favorable pharmacokinetic properties, including stability and permeability. Currently, many clinically approved cyclic peptides are derived from natural products or their derivatives, and the development of molecular docking techniques for cyclic peptide discovery holds great promise for expanding the applications and potential of this class of molecules. Given the availability of numerous docking programs, there is a pressing need for a systematic evaluation of their performance, specifically on protein-cyclic peptide systems. In this study, we constructed an extensive benchmark data set called CPSet, consisting of 493 protein-cyclic peptide complexes. Based on this data set, we conducted a comprehensive evaluation of 10 docking programs, including Rosetta, AutoDock CrankPep, and eight protein-small molecule docking programs (i.e., AutoDock, AudoDock Vina, Glide, GOLD, LeDock, rDock, MOE, and Surflex). The evaluation encompassed the assessment of the sampling power, docking power, and scoring power of these programs. The results revealed that all of the tested protein-small molecule docking programs successfully sampled the binding conformations when using the crystal conformations as the initial structures. Among them, rDock exhibited outstanding performance, achieving a remarkable 94.3% top-100 sampling success rate. However, few programs achieved successful predictions of the binding conformations using tLEaP-generated conformations as the initial structures. Within this scheme, AutoDock CrankPep yielded the highest top-100 sampling success rate of 29.6%. Rosetta's scoring function outperformed the others in selecting optimal conformations, resulting in an impressive top-1 docking success rate of 87.6%. Nevertheless, all the tested scoring functions displayed limited performance in predicting binding affinity, with MOE@Affinity dG exhibiting the highest Pearson's correlation coefficient of 0.378. It is therefore suggested to use an appropriate combination of different docking programs for given tasks in real applications. We expect that this work will offer valuable insights into selecting the appropriate docking programs for protein-cyclic peptide complexes.


Assuntos
Peptídeos Cíclicos , Proteínas , Peptídeos Cíclicos/metabolismo , Simulação de Acoplamento Molecular , Ligação Proteica , Proteínas/química , Conformação Molecular , Ligantes
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