查看更多>>摘要：The protein,azurin,has enabled the study of the tryptophan radical.Upon UV excitation of tyrosine-deficient apoazurin and in the presence of a Co(III) electron acceptor,the neutral radical(W48·) is formed.The lifetime of W48· in apoazurin is 41 s,which is shorter than the lifetime of several hours in Zn-substituted azurin.Molecular dynamics simulations revealed enhanced fluctuations of apoazurin which likely destabilize W48·.The photophysics of W48 was investigated to probe the precursor state for ET.The phosphorescence intensity was eliminated in the presence of an electron acceptor while the fluorescence was unchanged;this quenching of the phosphorescence is attributed to ET.The kinetics associated with W48· were examined with a model that incorporates intersystem crossing,ET,deprotonation,and decay of the cation radical.The estimated rate constants for ET(6 × 10~6 s~(-1)) and deprotonation(3 × 10~5 s~(-1)) are in agreement with a photoinduced mechanism where W48· is derived from the triplet state.The triplet as the precursor state for ET was supported by photolysis of apoazurin with 280 nm in the absence and presence of triplet-absorbing 405 nm light.Absorption bands from the neutral radical were observed only in the presence of blue light.
查看更多>>摘要：New enzyme functions exist within the increasing number of unannotated protein sequences.Novel enzyme discovery is necessary to expand the pathways that can be accessed by metabolic engineering for the biosynthesis of functional compounds.Accordingly,various machine learning models have been developed to predict enzymatic reactions.However,the ability to predict unknown reactions that are not included in the training data has not been clarified.In order to cover uncertain and unknown reactions,a wider range of reaction types must be demonstrated by the models.Here,we establish 16 expanded enzymatic reaction prediction models developed using various machine learning algorithms,including deep neural network.Improvements in prediction performances over that of our previous study indicate that the updated methods are more effective for the prediction of enzymatic reactions.Overall,the deep neural network model trained with combined substrate-enzyme-product information exhibits the highest prediction accuracy with Macro F1 scores up to 0.966 and with robust prediction of unknown enzymatic reactions that are not included in the training data.This model can predict more extensive enzymatic reactions in comparison to previously reported models.This study will facilitate the discovery of new enzymes for the production of useful substances.
查看更多>>摘要：Sequence-dependent binding between DNA and proteins in chromatin is an essential part of gene expression.Linker histone H1 is an important protein in the regulation of chromatin compartmentalization and compaction,and its binding with the nucleosome is sensitive to the DNA sequence.Although the interactions of H1 and DNA have been widely investigated,the mechanism of nucleosome conformation changes induced by the DNA-sequence-dependent binding with gH1(globular H1.0) remains largely unclear at the atomic level.In the present molecular dynamics simulations,both linker and dyad DNAs were mutated to investigate the conformational changes of the nucleosome induced by the sequence-dependent binding of gH1 based on the on-dyad binding mode.Our results indicate that gH1 is insensitive to the DNA sequence of the dyad DNA but presents an apparent preference to linker DNA with an AT-rich sequence.Moreover,this specific binding induces the entry/exit region of a nucleosome to a tight conformation and regulates the accessibility of core histones.Considering that the entry/exit region of the nucleosome is a crucial binding site for many functional proteins related to gene expression,the conformational change at this region could represent an important gene regulation signal.
查看更多>>摘要：Hsp70 molecular chaperones play central roles in maintaining a healthy cellular proteome.Hsp70s function by binding to short peptide sequences in incompletely folded client proteins,thus preventing them from misfolding and/or aggregating,and in many cases holding them in a state that is competent for subsequent processes like translocation across membranes.There is considerable interest in predicting the sites where Hsp70s may bind their clients,as the ability to do so sheds light on the cellular functions of the chaperone.In addition,the capacity of the Hsp70 chaperone family to bind to a broad array of clients and to identify accessible sequences that enable discrimination of those that are folded from those that are not fully folded,which is essential to their cellular roles,is a fascinating puzzle in molecular recognition.In this article we discuss efforts to harness computational modeling with input from experimental data to develop a predictive understanding of the promiscuous yet selective binding of Hsp70 molecular chaperones to accessible sequences within their client proteins.We trace how an increasing understanding of the complexities of Hsp70-client interactions has led computational modeling to new underlying assumptions and design features.We describe the trend from purely data-driven analysis toward increased reliance on physics-based modeling that deeply integrates structural information and sequence-based functional data with physics-based binding energies.Notably,new experimental insights are adding to our understanding of the molecular origins of"selective promiscuity"in substrate binding by Hsp70 chaperones and challenging the underlying assumptions and design used in earlier predictive models.Talcing the new experimental findings together with exciting progress in computational modeling of protein structures leads us to foresee a bright future for a predictive understanding of selective-yet-promiscuous binding exploited by Hsp70 molecular chaperones;the resulting new insights will also apply to substrate binding by other chaperones and by signaling proteins.
查看更多>>摘要：Substrate inhibition,whereby enzymatic activity decreases with excess substrate after reaching a maximum turnover rate,is among the most elusive phenomena in enzymatic catalysis.Here,based on a dynamic energy landscape model,we investigate the underlying mechanism by performing molecular simulations and frustration analysis for a model enzyme adenylate kinase(AdK),which catalyzes the phosphoryl transfer reaction ATP + AMP ←→ ADP + ADP.Intriguingly,these reveal a kinetic repartitioning mechanism of substrate inhibition,whereby excess substrate AMP suppresses the population of an energetically frustrated,but kinetically activated,catalytic pathway going through a substrate(ATP)-product(ADP) cobound complex with steric incompatibility.Such a frustrated pathway plays a crucial role in facilitating the bottleneck product ADP release,and its suppression by excess substrate AMP leads to a slow down of product release and overall turnover.The simulation results directly demonstrate that substrate inhibition arises from the rate-limiting product-release step,instead of the steps for populating the catalytically competent complex as often suggested in previous works.Furthermore,there is a tight interplay between the enzyme conformational equilibrium and the extent of substrate inhibition.Mutations biasing to more closed conformations tend to enhance substrate inhibition.We also characterized the key features of single-molecule enzyme kinetics with substrate inhibition effect.We propose that the above molecular mechanism of substrate inhibition may be relevant to other multisubstrate enzymes in which product release is the bottleneck step.
查看更多>>摘要：Binding to the host membrane is the initial infection step for animal viruses.Sendai virus(SeV),the model respirovirus studied here,utilizes sialic-acid-conjugated glycoproteins and glycolipids as receptors for binding.In a previous report studying single virus binding to supported lipid bilayers(SLBs),we found a puzzling mechanistic difference between the binding of SeV and influenza A virus(strain X31,IAV~(X31)).Both viruses use similar receptors and exhibit similar cooperative binding behavior,but whereas LAV*31 binding was altered by SLB cholesterol concentration,which can stabilize receptor nanoclusters,SeV was not.Here,we propose that differences in viral size distributions can explain this discrepancy;viral size could alter the number of virus-receptor interactions in the contact area and,therefore,the sensitivity to receptor nanoclusters.To test this,we compared the dependence of SeV binding on SLB cholesterol concentration between size-filtered and unfiltered SeV.At high receptor density,the unfiltered virus showed little dependence,but the size-filtered virus exhibited a linear cholesterol dependence,similar to IAV~(X31).However,at low receptor densities,the unfiltered virus did exhibit a cholesterol dependence,indicating that receptor nanoclusters enhance viral binding only when the number of potential virus-receptor interactions is small enough.We also studied the influence of viral size and receptor nanoclusters on viral mobility following binding.Whereas differences in viral size greatly influenced mobility,the effect of receptor nanoclusters on mobility was small.Together,our results highlight the mechanistic salience of both the distribution of viral sizes and the lateral distribution of receptors in a viral infection.
查看更多>>摘要：Nitric oxide synthase(NOS) is a homodimeric flavohemoprotein responsible for catalyzing the oxidation of l-arginine(L-Arg) to citrulline and nitric oxide.Electrons are supplied for the reaction via interdomain electron transfer between an N-terminal heme-containing oxygenase domain and a FMN-containing(sub)domain of a C-terminal reductase domain.Extensive attention has focused on elucidating how conformational dynamics regulate electron transfer between the domains.Here we investigate the impact of the interdomain FMN-heme interaction on the heme active site dynamics of inducible NOS(iNOS).Steady state linear and time-resolved two-dimensional infrared(2D IR) spectroscopy was applied to probe a CO ligand at the heme within the oxygenase domain for full-length and truncated or mutated constructs of human iNOS.Whereas the linear IR spectra of the CO ligand were identical among the constructs,2D IR spectroscopy revealed variation in the frequency dynamics.The wild-type constructs that can properly form the FMN/oxygenase docked state due to the presence of both the FMN and oxygenase domains showed slower dynamics than the oxygenase domain alone.Introduction of the mutation(E546N) predicted to perturb electrostatic interactions between the domains resulted in measured dynamics intermediate between those for the full-length and individual oxygenase domain,consistent with perturbation to the docked/undocked equilibrium.These results indicate that docking of the FMN domain to the oxygenase domain not only brings the FMN cofactor within electron transfer distance of the heme domain but also modulates the dynamics sensed by the CO ligand within the active site in a way expected to promote efficient electron transfer.
查看更多>>摘要：Recently,we presented a whole-cell kinetic model of the genetically minimal bacterium JCVI-syn3A that described the coupled metabolic and genetic information processes and predicted behaviors emerging from the interactions among these networks.JCVI-syn3A is a genetically reduced bacterial cell that has the fewest number and smallest fraction of genes of unclear function,with approximately 90 of its 452 protein-coding genes(that is less than 20%) unannotated.Further characterization of unclear JCVI-syn3A genes strengthens the robustness and predictive power of cell modeling efforts and can lead to a deeper understanding of biophysical processes and pathways at the cell scale.Here,we apply computational analyses to elucidate the functions of the products of several essential but previously uncharacterized genes involved in integral cellular processes,particularly those directly affecting cell growth,division,and morphology.We also suggest directed wet-lab experiments informed by our analyses to further understand these"missing puzzle pieces"that are an essential part of the mosaic of biological interactions present in JCVI-syn3A Our workflow leverages evolutionary sequence analysis,protein structure prediction,interactomics,and genome architecture to determine upgraded annotations.Additionally,we apply the structure prediction analysis component of our work to all 452 protein coding genes in JCVI-syn3A to expedite future functional annotation studies as well as the inverse mapping of the cell state to more physical models requiring all-atom or coarse-grained representations for all JCVI-syn3A proteins.
Carolina Correa GironAatto LaaksonenFernando L.Barroso da Silva
18页
查看更多>>摘要：Electrostatic intermolecular interactions are important in many aspects of biology.We have studied the main electrostatic features involved in the interaction of the receptor-binding domain(RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2(ACE2).As the principal computational tool,we have used the FORTE approach,capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions,here focusing on the RBD-ACE2 interactions.Both the wild-type and all critical variants are included in this study.From our large ensemble of extensive simulations,we obtain,as a function of pH,the binding affinities,charges of the proteins,their charge regulation capacities,and their dipole moments.In addition,we have calculated the pKas for all ionizable residues and mapped the electrostatic coupling between them.We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha,Beta,Gamma,Delta,and Omicron variants,as a linear correlation between the total charge of the RBD and the corresponding binding affinity.This"RBD charge rule"should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future.
查看更多>>摘要：Protein-protein interactions(PPIs) and protein-metabolite interactions play a key role in many biochemical processes,yet they are often viewed as being independent.However,the fact that small molecule drugs have been successful in inhibiting PPIs suggests a deeper relationship between protein pockets that bind small molecules and PPIs.We demonstrate that 2/3 of PPI interfaces,including antibody-epitope interfaces,contain at least one significant small molecule ligand binding pocket.In a representative library of 50 distinct protein-protein interactions involving hundreds of mutations,>75% of hot spot residues overlap with small molecule ligand binding pockets.Hence,ligand binding pockets play an essential role in PPIs.In representative cases,evolutionary unrelated monomers that are involved in different multimeric interactions yet share the same pocket are predicted to bind the same metabolites/drugs;these results are confirmed by examples in the PDB.Thus,the binding of a metabolite can shift the equilibrium between monomers and multimers.This implicit coupling of PPI equilibria,termed"metabolic entanglement",was successfully employed to suggest novel functional relationships among protein multimers that do not directly interact.Thus,the current work provides an approach to unify metabolomics and protein interactomics.
NSTL