Predicting protein flexibility with AlphaFold Ma, Puyi; Li, Da‐Wei; Brüschweiler, Rafael
Proteins, structure, function, and bioinformatics,
June 2023, 2023-06-00, 20230601, Volume:
91, Issue:
6
Journal Article
Peer reviewed
Open access
AlphaFold2 has revolutionized protein structure prediction from amino‐acid sequence. In addition to protein structures, high‐resolution dynamics information about various protein regions is important ...for understanding protein function. Although AlphaFold2 has neither been designed nor trained to predict protein dynamics, it is shown here how the information returned by AlphaFold2 can be used to predict dynamic protein regions at the individual residue level. The approach, which is termed cdsAF2, uses the 3D protein structure returned by AlphaFold2 to predict backbone NMR NH S2 order parameters using a local contact model that takes into account the contacts made by each peptide plane along the backbone with its environment. By combining for each residue AlphaFold2's pLDDT confidence score for the structure prediction accuracy with the predicted S2 value using the local contact model, an estimator is obtained that semi‐quantitatively captures many of the dynamics features observed in experimental backbone NMR NH S2 order parameter profiles. The method is demonstrated for a set nine proteins of different sizes and variable amounts of dynamics and disorder.
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR ...analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that are challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.
Kiwifruit (Actinidia spp.) is a climacteric fruit with high sensitivity to ethylene, influenced by multiple ethylene-responsive structural genes and transcription factors. However, the roles of other ...post-transcriptional regulators (e.g. miRNAs) necessary for ripening remain elusive.
High-throughput sequencing sRNAome, degradome and transcriptome methods were used to identify further contributors to ripening control in the kiwifruit (A. deliciosa cv ‘Hayward’).
Two NAM/ATAF/CUC domain transcription factors (AdNAC6 and AdNAC7), both predicted targets for miR164, showed significant upregulation by exogenous ethylene. Gene expression analysis and luciferase reporter assays indicated that Ade-miR164 and one of its precursor miRNAs (Ade-MIR164b) were repressed by ethylene treatment and negatively correlated with AdNAC6/7 expression. Subsequent analysis indicated that both AdNAC6 and AdNAC7 proteins are transcriptional activators and physically bind the promoters of AdACS1 (1-aminocyclopropane-1-carboxylate synthase), AdACO1 (1-aminocyclopropane-1-carboxylic acid oxidase), AdMAN1 (endo-β-mannanase) and AaTPS1 (terpene synthase). Moreover, subcellular analysis indicated that the location of the AdNAC6/7 proteins was influenced by Ade-miR164.
Multiple omics-based approaches revealed a novel regulatory link for fruit ripening that involved ethylene-miR164-NAC. The regulatory pathway for miR164-NAC is present in various fruit (e.g. Rosaceae fruit, citrus, grape), with implications for fruit ripening regulation.
NMR-Based Protein Potentials Li, Da-Wei; Brüschweiler, Rafael
Angewandte Chemie (International ed.),
September 10, 2010, Volume:
49, Issue:
38
Journal Article
Peer reviewed
Speed training: A highly efficient screening of new potentials against the parent molecular dynamics (MD) trajectories of trial proteins provides a greater than 105‐fold increase in the speed of the ...analysis by using a re‐weighting scheme guided by experimental NMR data for proteins, thereby improving the accuracy of computer simulations of proteins.
A method based on plasmon resonance Rayleigh scattering (PRRS) spectroscopy and dark‐field microscopy (DFM) was established for the real‐time monitoring of a click reaction at the single‐nanoparticle ...level. Click reactions on the surface of single gold nanoparticles (GNPs) result in interparticle coupling, which leads to a red‐shift of the λmax (Δλmax=43 nm) in the PRRS spectra and a color change of the single gold nanoparticles in DFM (from green to orange).
Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the ...coanalysis of up to three two-dimensional (2D) NMR spectra, namely, 13C–1H HSQC (heteronuclear single quantum coherence spectroscopy), 1H–1H TOCSY (total correlation spectroscopy), and 13C–1H HSQC-TOCSY, for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum, and the top metabolite hits are then validated against the TOCSY-type experiment(s) by superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR.
An ultrasensitive cysteine sensor is prepared by using a Nafion assembly of a CdS quantum dot–methyl viologen complex on a conductive ITO surface. It is effective in the readout of the ...photoelectrochemical response to cysteine with high sensitivity, good selectivity, and fast response.
Hydrogen sulfide (H2S) has emerged as an important gasotransmitter in diverse physiological processes, although many aspects of its roles remain unclear, partly owing to a lack of robust analytical ...methods. Herein we report a novel surface‐enhanced Raman scattering (SERS) nanosensor, 4‐acetamidobenzenesulfonyl azide‐functionalized gold nanoparticles (AuNPs/4‐AA), for detecting the endogenous H2S in living cells. The detection is accomplished with SERS spectrum changes of AuNPs/4‐AA resulting from the reaction of H2S with 4‐AA on AuNPs. The SERS nanosensor exhibits high selectivity toward H2S. Furthermore, AuNPs/4‐AA responds to H2S within 1 min with a 0.1 μM level of sensitivity. In particular, our SERS method can be utilized to monitor the endogenous H2S generated in living glioma cells, demonstrating its great promise in studies of pathophysiological pathways involving H2S.
Rapid, selective, and sensitive: The endogenous H2S in living cells can be detected rapidly, selectively, and sensitively using a surface‐enhanced Raman scattering (SERS) nanosensor, 4‐acetamidobenzenesulfonyl azide‐functionalized gold nanoparticles (AuNPs/4‐AA). Based on the rapid and specific reaction between H2S and 4‐AA, combined with the sensitive fingerprinting capability of SERS, the nanosensor can monitor the endogenous H2S generated in a variety of pathophysiological pathways.
Despite the promise of combination cancer therapy, it remains challenging to develop targeted strategies that are nontoxic to normal cells. Here we report a combination therapeutic strategy based on ...engineered DNAzyme molecular machines that can promote cancer apoptosis via dynamic inter‐ and intracellular regulation. To achieve external regulation of T‐cell/cancer cell interactions, we designed a DNAzyme‐based molecular machine with an aptamer and an i‐motif, as the MUC‐1‐selective aptamer allows the specific recognition of cancer cells. The i‐motif is folded under the tumor acidic microenvironment, shortening the intercellular distance. As a result, T‐cells are released by metal ion activated DNAzyme cleavage. To achieve internal regulation of mitochondria, we delivered another DNAzyme‐based molecular machine with mitochondria‐targeted peptides into cancer cells to induce mitochondria aggregation. Our strategy achieved an enhanced killing effect in zinc deficient cancer cells.
A combination therapeutic strategy based on engineered DNAzyme molecular machines was designed for promoting cancer apoptosis via dynamic inter‐ and intracellular regulation. Our strategy resulted in an enhanced killing effect, demonstrated using zinc deficient cancer cells, thus providing a promising next‐generation combination therapy for cancer.
The quantitative and predictive understanding how intrinsically disordered proteins (IDPs) interact with engineered nanoparticles has potentially important implications for new therapeutics as well ...as nanotoxicology. Based on a recently developed solution 15N NMR relaxation approach, the interactions between four representative IDPs with silica nanoparticles are reported at atomic detail. Each IDP possesses distinct binding modes, which can be quantitatively explained by the local amino‐acid residue composition using a “free residue interaction model”. The model was parameterized using the binding affinities of free proteinogenic amino acids along with long‐range effects, derived by site‐specific mutagenesis, that exponentially scale with distance along the primary sequence. The model, which is accessible through a web server, can be applied to predict the residue‐specific binding affinities of a large number of IDPs.
Binding of four different intrinsically disordered proteins to amorphous silica surfaces was quantitatively measured at atomic resolution by NMR and could be accurately explained by a universal free residue interaction model.
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