ABSTRACT
Proteins' fuzziness are features for communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. Binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit, but it is unclear whether the limited experimental data available can be used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. With our designs, we provided a framework of explainable machine learning model to annotate atomic charges of calcium ions in calcium-binding proteins with domain knowledge in response to the chemical changes in an environment based on the limited size of scientific data in a genome space.
ABSTRACT
We aim to elucidate the molecular mechanism of the reciprocal relation of calmodulin's (CaM) target binding and its affinity for calcium ions (Ca2+), which is central to decoding CaM-dependent Ca2+ signaling in a cell. We employed stopped-flow experiments and coarse-grained molecular simulations that learn the coordination chemistry of Ca2+ in CaM from first-principle calculations. The associative memories as part of the coarse-grained force fields built on known protein structures further influence CaM's selection of its polymorphic target peptides in the simulations. We modeled the peptides from the Ca2+/CaM-binding domain of Ca2+/CaM-dependent kinase II (CaMKII), CaMKIIp (293-310) and selected distinctive mutations at the N-terminus. Our stopped-flow experiments have shown that the CaM's affinity for Ca2+ in the bound complex of Ca2+/CaM/CaMKIIp decreased significantly when Ca2+/CaM bound to the mutant peptide (296-AAA-298) compared to that bound to the wild-type peptide (296-RRK-298). The coarse-grained molecular simulations revealed that the 296-AAA-298 mutant peptide destabilized the structures of Ca2+-binding loops at the C-domain of CaM (c-CaM) due to both loss of electrostatic interactions and differences in polymorphic structures. We have leveraged a powerful coarse-grained approach to advance a residue-level understanding of the reciprocal relation in CaM, that could not be possibly achieved by other computational approaches.
Subject(s)
Calcium , Calmodulin , Calmodulin/chemistry , Amino Acid Sequence , Calcium/chemistry , Protein Binding , Computer Simulation , Binding SitesABSTRACT
A growing body of evidence suggests that only a few amino acids ("hot-spots") at the interface contribute most of the binding energy in transient protein-protein interactions. However, experimental protocols to identify these hot-spots are highly labor-intensive and expensive. Computational methods, including evolutionary couplings, have been proposed to predict the hot-spots, but they generally fail to provide details of the interacting amino acids. Here we showed that unbiased evolutionary methods followed by biased molecular dynamic simulations could achieve this goal and reveal critical elements of protein complexes. We applied the methodology to selected G-protein coupled receptors (GPCRs), known for their therapeutic properties. We used the structure-prior-assisted direct coupling analysis (SP-DCA) to predict the binding interfaces of A2aR/D2R, CB1R/D2R, A2aR/CB1R, 5HT2AR/D2R, and 5-HT2AR/mGluR2 receptor heterodimers, which all agreed with published data. In order to highlight details of the interactions, we performed molecular dynamic (MD) simulations using the newly developed AWSEM energy model. We found that these receptors interact primarily through critical residues at the C and N terminal domains and the third intracellular loop (ICL3). The MD simulations showed that these residues are energetically necessary for dimerization and revealed their native conformational state. We subsequently applied the methodology to the 5-HT2AR/5-HTR4R heterodimer, given its implication in drug addiction and neurodegenerative pathologies such as Alzheimer's disease (AD). Further, the SP-DCA analysis showed that 5-HT2AR and 5-HTR4R heterodimerize through the C-terminal domain of 5-HT2AR and ICL3 of 5-HT4R. However, elucidating the details of GPCR interactions would accelerate the discovery of druggable sites and improve our knowledge of the etiology of common diseases, including AD.
Subject(s)
Molecular Dynamics Simulation , Receptors, G-Protein-Coupled , Receptors, G-Protein-Coupled/metabolism , Cell Membrane/metabolism , Dimerization , Amino Acids/metabolismABSTRACT
Calmodulin (CaM) is a calcium-binding protein that transduces signals to downstream proteins through target binding upon calcium binding in a time-dependent manner. Understanding the target binding process that tunes CaM's affinity for the calcium ions (Ca2+), or vice versa, may provide insight into how Ca2+-CaM selects its target binding proteins. However, modeling of Ca2+-CaM in molecular simulations is challenging because of the gross structural changes in its central linker regions while the two lobes are relatively rigid due to tight binding of the Ca2+ to the calcium-binding loops where the loop forms a pentagonal bipyramidal coordination geometry with Ca2+. This feature that underlies the reciprocal relation between Ca2+ binding and target binding of CaM, however, has yet to be considered in the structural modeling. Here, we presented a coarse-grained model based on the Associative memory, Water mediated, Structure, and Energy Model (AWSEM) protein force field, to investigate the salient features of CaM. Particularly, we optimized the force field of CaM and that of Ca2+ ions by using its coordination chemistry in the calcium-binding loops to match with experimental observations. We presented a "community model" of CaM that is capable of sampling various conformations of CaM, incorporating various calcium-binding states, and carrying the memory of binding with various targets, which sets the foundation of the reciprocal relation of target binding and Ca2+ binding in future studies.
ABSTRACT
DNA double-strand breaks (DSBs) are among the most lethal types of DNA damage and frequently cause genome instability. Sequencing-based methods for mapping DSBs have been developed but they allow measurement only of relative frequencies of DSBs between loci, which limits our understanding of the physiological relevance of detected DSBs. Here we propose quantitative DSB sequencing (qDSB-Seq), a method providing both DSB frequencies per cell and their precise genomic coordinates. We induce spike-in DSBs by a site-specific endonuclease and use them to quantify detected DSBs (labeled, e.g., using i-BLESS). Utilizing qDSB-Seq, we determine numbers of DSBs induced by a radiomimetic drug and replication stress, and reveal two orders of magnitude differences in DSB frequencies. We also measure absolute frequencies of Top1-dependent DSBs at natural replication fork barriers. qDSB-Seq is compatible with various DSB labeling methods in different organisms and allows accurate comparisons of absolute DSB frequencies across samples.
Subject(s)
Computational Biology/methods , DNA Breaks, Double-Stranded , Whole Genome Sequencing/methods , Cell Line, Tumor , DNA Replication/genetics , DNA Topoisomerases, Type I/metabolism , Genome, Fungal/genetics , Genome, Human/genetics , Humans , Saccharomycetales/geneticsABSTRACT
Maintenance of genome stability is a key issue for cell fate that could be compromised by chromosome deletions and translocations caused by DNA double-strand breaks (DSBs). Thus development of precise and sensitive tools for DSBs labeling is of great importance for understanding mechanisms of DSB formation, their sensing and repair. Until now there has been no high resolution and specific DSB detection technique that would be applicable to any cells regardless of their size. Here, we present i-BLESS, a universal method for direct genome-wide DNA double-strand break labeling in cells immobilized in agarose beads. i-BLESS has three key advantages: it is the only unbiased method applicable to yeast, achieves a sensitivity of one break at a given position in 100,000 cells, and eliminates background noise while still allowing for fixation of samples. The method allows detection of ultra-rare breaks such as those forming spontaneously at G-quadruplexes.
ABSTRACT
Hematopoietic stem and progenitor cells (HSPCs) are vulnerable to endogenous damage and defects in DNA repair can limit their function. The 2 single-stranded DNA (ssDNA) binding proteins SSB1 and SSB2 are crucial regulators of the DNA damage response; however, their overlapping roles during normal physiology are incompletely understood. We generated mice in which both Ssb1 and Ssb2 were constitutively or conditionally deleted. Constitutive Ssb1/Ssb2 double knockout (DKO) caused early embryonic lethality, whereas conditional Ssb1/Ssb2 double knockout (cDKO) in adult mice resulted in acute lethality due to bone marrow failure and intestinal atrophy featuring stem and progenitor cell depletion, a phenotype unexpected from the previously reported single knockout models of Ssb1 or Ssb2 Mechanistically, cDKO HSPCs showed altered replication fork dynamics, massive accumulation of DNA damage, genome-wide double-strand breaks enriched at Ssb-binding regions and CpG islands, together with the accumulation of R-loops and cytosolic ssDNA. Transcriptional profiling of cDKO HSPCs revealed the activation of p53 and interferon (IFN) pathways, which enforced cell cycling in quiescent HSPCs, resulting in their apoptotic death. The rapid cell death phenotype was reproducible in in vitro cultured cDKO-hematopoietic stem cells, which were significantly rescued by nucleotide supplementation or after depletion of p53. Collectively, Ssb1 and Ssb2 control crucial aspects of HSPC function, including proliferation and survival in vivo by resolving replicative stress to maintain genomic stability.