Actin filaments form a size-dependent diffusion barrier around centrosomes.

The centrosome, a non-membranous organelle, constrains various soluble molecules locally to execute its functions. As the centrosome is surrounded by various dense components, we hypothesized that it may be bordered by a putative diffusion barrier. After quantitatively measuring the trapping kinetics of soluble proteins of varying size at centrosomes by a chemically inducible diffusion trapping assay, we find that centrosomes are highly accessible to soluble molecules with a Stokes radius of less than 5.8 nm, whereas larger molecules rarely reach centrosomes, indicating the existence of a size-dependent diffusion barrier at centrosomes. The permeability of this barrier is tightly regulated by branched actin filaments outside of centrosomes and it decreases during anaphase when branched actin temporally increases. The actin-based diffusion barrier gates microtubule nucleation by interfering with γ-tubulin ring complex recruitment. We propose that actin filaments spatiotemporally constrain protein complexes at centrosomes in a size-dependent manner.

DR-SIP: protocols for higher order structure modeling with distance restraints- and cyclic symmetry-imposed packing.

MOTIVATION: Quaternary structure determination for transmembrane/soluble proteins requires a reliable computational protocol that leverages observed distance restraints and/or cyclic symmetry (Cn symmetry) found in most homo-oligomeric transmembrane proteins. RESULTS: We survey 118 X-ray crystallographically solved structures of homo-oligomeric transmembrane proteins (HoTPs) and find that ∼97% are Cn symmetric. Given the prevalence of Cn symmetric HoTPs and the benefits of incorporating geometry restraints in aiding quaternary structure determination, we introduce two new filters, the distance-restraints (DR) and the Symmetry-Imposed Packing (SIP) filters. SIP relies on a new method that can rebuild the closest ideal Cn symmetric complex from docking poses containing a homo-dimer without prior knowledge of the number (n) of monomers. Using only the geometrical filter, SIP, near-native poses of 7 HoTPs in their monomeric states can be correctly identified in the top-10 for 71% of all cases, or 29% among 31 HoTP structures obtained through homology modeling, while ZDOCK alone returns 14 and 3%, respectively. When the n is given, the optional n-mer filter is applied with SIP and returns the near-native poses for 76% of the test set within the top-10, outperforming M-ZDOCK's 55% and Sam's 47%. While applying only SIP to three HoTPs that comes with distance restraints, we found the near-native poses were ranked 1st, 1st and 10th among 54 000 possible decoys. The results are further improved to 1st, 1st and 3rd when both DR and SIP filters are used. By applying only DR, a soluble system with distance restraints is recovered at the 1st-ranked pose. AVAILABILITY AND IMPLEMENTATION: https://github.com/capslockwizard/drsip. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Resolution-exchanged structural modeling and simulations jointly unravel that subunit rolling underlies the mechanism of programmed ribosomal frameshifting.

MOTIVATION: Programmed ribosomal frameshifting (PRF) is widely used by viruses and bacteria to produce different proteins from a single mRNA template. How steric hindrance of a PRF-stimulatory mRNA structure transiently modifies the conformational dynamics of the ribosome, and thereby allows tRNA slippage, remains elusive. RESULTS: Here, we leverage linear response theories and resolution-exchanged simulations to construct a structural/dynamics model that connects and rationalizes existing structural, single-molecule and mutagenesis data by resolution-exchanged structural modelling and simulations. Our combined theoretical techniques provide a temporal and spatial description of PRF with unprecedented mechanistic details. We discover that ribosomal unfolding of the PRF-stimulating pseudoknot exerts resistant forces on the mRNA entrance of the ribosome, and thereby drives 30S subunit rolling. Such motion distorts tRNAs, leads to tRNA slippage, and in turn serves as a delicate control of cis-element's unwinding forces over PRF. AVAILABILITY AND IMPLEMENTATION: All the simulation scripts and computational implementations of our methods/analyses (including linear response theory) are included in the bioStructureM suite, provided through GitHub at https://github.com/Yuan-Yu/bioStructureM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DynOmics: dynamics of structural proteome and beyond.

DynOmics (dynomics.pitt.edu) is a portal developed to leverage rapidly growing structural proteomics data by efficiently and accurately evaluating the dynamics of structurally resolved systems, from individual molecules to large complexes and assemblies, in the context of their physiological environment. At the core of the portal is a newly developed server, ENM 1.0, which permits users to efficiently generate information on the collective dynamics of any structure in PDB format, user-uploaded or database-retrieved. ENM 1.0 integrates two widely used elastic network models (ENMs)-the Gaussian Network Model (GNM) and the Anisotropic Network Model (ANM), extended to take account of molecular environment. It enables users to assess potentially functional sites, signal transduction or allosteric communication mechanisms, and protein-protein and protein-DNA interaction poses, in addition to delivering ensembles of accessible conformers reconstructed at atomic details based on the global modes of motions predicted by the ANM. The 'environment' is defined in a flexible manner, from lipid bilayer and crystal contacts, to substrate or ligands bound to a protein, or surrounding subunits in a multimeric structure or assembly. User-friendly interactive features permit users to easily visualize how the environment alter the intrinsic dynamics of the query systems. ENM 1.0 can be accessed at http://enm.pitt.edu/ or http://dyn.life.nthu.edu.tw/oENM/.

iGNM 2.0: the Gaussian network model database for biomolecular structural dynamics.

Gaussian network model (GNM) is a simple yet powerful model for investigating the dynamics of proteins and their complexes. GNM analysis became a broadly used method for assessing the conformational dynamics of biomolecular structures with the development of a user-friendly interface and database, iGNM, in 2005. We present here an updated version, iGNM 2.0 http://gnmdb.csb.pitt.edu/, which covers more than 95% of the structures currently available in the Protein Data Bank (PDB). Advanced search and visualization capabilities, both 2D and 3D, permit users to retrieve information on inter-residue and inter-domain cross-correlations, cooperative modes of motion, the location of hinge sites and energy localization spots. The ability of iGNM 2.0 to provide structural dynamics data on the large majority of PDB structures and, in particular, on their biological assemblies makes it a useful resource for establishing the bridge between structure, dynamics and function.

Blocking the interaction between S100A9 and RAGE V domain using CHAPS molecule: A novel route to drug development against cell proliferation.

Human S100A9 (Calgranulin B) is a Ca(2+)-binding protein, from the S100 family, that often presents as a homodimer in myeloid cells. It becomes an important mediator during inflammation once calcium binds to its EF-hand motifs. Human RAGE protein (receptor for advanced glycation end products) is one of the target-proteins. RAGE binds to a hydrophobic surface on S100A9. Interactions between these proteins trigger signal transduction cascades, promoting cell growth, proliferation, and tumorigenesis. Here, we present the solution structure of mutant S100A9 (C3S) homodimer, determined by multi-dimensional NMR experiments. We further characterize the solution interactions between mS100A9 and the RAGE V domain via NMR spectroscopy. CHAPS is a zwitterionic and non-denaturing molecule widely used for protein solubilizing and stabilization. We found out that CHAPS and RAGE V domain would interact with mS100A9 by using (1)H-(15)N HSQC NMR titrations. Therefore, using the HADDOCK program, we superimpose two binary complex models mS100A9-RAGE V domain and mS100A9-CHAPS and demonstrate that CHAPS molecules could play a crucial role in blocking the interaction between mS100A9 and the RAGE V domain. WST-1 assay results also support the conclusion that CHAPS inhibits the bioactivity of mS100A9. This report will help to inform new drug development against cell proliferation.

Ligand-induced protein responses and mechanical signal propagation described by linear response theories.

In this study, a general linear response theory (LRT) is formulated to describe time-dependent and -independent protein conformational changes upon CO binding with myoglobin. Using the theory, we are able to monitor protein relaxation in two stages. The slower relaxation is found to occur from 4.4 to 81.2 picoseconds and the time constants characterized for a couple of aromatic residues agree with those observed by UV Resonance Raman (UVRR) spectrometry and time resolved x-ray crystallography. The faster "early responses", triggered as early as 400 femtoseconds, can be best described by the theory when impulse forces are used. The newly formulated theory describes the mechanical propagation following ligand-binding as a function of time, space and types of the perturbation forces. The "disseminators", defined as the residues that propagate signals throughout the molecule the fastest among all the residues in protein when perturbed, are found evolutionarily conserved and the mutations of which have been shown to largely change the CO rebinding kinetics in myoglobin.

Structural insights into the interaction of human S100B and basic fibroblast growth factor (FGF2): Effects on FGFR1 receptor signaling.

S100B is a calcium sensing protein belonging to the S100 protein family with intracellular and extracellular roles. It is one of the EF hand homodimeric proteins, which is known to interact with various protein targets to regulate varied biological functions. Extracellular S100B has been recently reported to interact with FGF2 in a RAGE-independent manner. However, the recognition mechanism of S100B-FGF2 interaction at the molecular level remains unclear. In this study, the critical residues on S100B-FGF2 interface were mapped by combined information derived from NMR spectroscopy and site directed mutagenesis experiments. Utilizing NMR titration data, we generated the structural models of S100B-FGF2 complex from the computational docking program, HADDOCK which were further proved stable during 15ns unrestrained molecular dynamics (MD) simulations. Isothermal titration calorimetry studies indicated S100B interaction with FGF2 is an entropically favored process implying dominant role of hydrophobic contacts at the protein-protein interface. Residue level information of S100B interaction with FGF2 was useful to understand the varied target recognition ability of S100B and further explained its role in effecting extracellular signaling diversity. Mechanistic insights into the S100B-FGF2 complex interface and cell-based assay studies involving mutants led us to conclude the novel role of S100B in FGF2 mediated FGFR1 receptor inactivation.

Molecular binding sites are located near the interface of intrinsic dynamics domains (IDDs).

We provide evidence supporting that protein-protein and protein-ligand docking poses are functions of protein shape and intrinsic dynamics. Over sets of 68 protein-protein complexes and 240 nonhomologous enzymes, we recognize common predispositions for binding sites to have minimal vibrations and angular momenta, while two interacting proteins orient so as to maximize the angle between their rotation/bending axes (>65°). The findings are then used to define quantitative criteria to filter out docking decoys less likely to be the near-native poses; hence, the chances to find near-native hits can be doubled. With the novel approach to partition a protein into "domains" of robust but disparate intrinsic dynamics, 90% of catalytic residues in enzymes can be found within the first 50% of the residues closest to the interface of these dynamics domains. The results suggest an anisotropic rather than isotropic distribution of catalytic residues near the mass centers of enzymes.

The N-terminal substrate-recognition domain of a LonC protease exhibits structural and functional similarity to cytosolic chaperones.

The Lon protease is ubiquitous in nature. Its proteolytic activity is associated with diverse cellular functions ranging from maintaining proteostasis under normal and stress conditions to regulating cell metabolism. Although Lon was originally identified as an ATP-dependent protease with fused AAA+ (ATPases associated with diverse cellular activities) and protease domains, analyses have recently identified LonC as a class of Lon-like proteases with no intrinsic ATPase activity. In contrast to the canonical ATP-dependent Lon present in eukaryotic organelles and prokaryotes, LonC contains an AAA-like domain that lacks the conserved ATPase motifs. Moreover, the LonC AAA-like domain is inserted with a large domain predicted to be largely α-helical; intriguingly, this unique Lon-insertion domain (LID) was disordered in the recently determined full-length crystal structure of Meiothermus taiwanensis LonC (MtaLonC). Here, the crystal structure of the N-terminal AAA-like α/ß subdomain of MtaLonC containing an intact LID, which forms a large α-helical hairpin protruding from the AAA-like domain, is reported. The structure of the LID is remarkably similar to the tentacle-like prong of the periplasmic chaperone Skp. It is shown that the LID of LonC is involved both in Skp-like chaperone activity and in recognition of unfolded protein substrates. The structure allows the construction of a complete model of LonC with six helical hairpin extensions defining a basket-like structure atop the AAA ring and encircling the entry portal to the barrel-like degradation chamber of Lon.

Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods.

Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in, if not determine, viable mechanisms of biological function. In recent years, machine learning frameworks have proven uniquely useful in structural biology, and recent studies further provide evidence to the utility and/or necessity of considering intrinsic dynamics for increasing their predictive ability. Efficient quantification of dynamics-based attributes by recently developed physics-based theories and models such as elastic network models provides a unique opportunity to generate data on dynamics for training ML models towards inferring mechanisms of protein function, assessing pathogenicity, or estimating binding affinities.

Full-Privacy Secured Search Engine Empowered by Efficient Genome-Mapping Algorithms.

Since the 90s, keyword-based search engines have been the only option for people to locate relevant web content through a simple query comprising one to a few keywords. These engines, whether free or paid, retained users' search queries and preferences, often to deliver targeted ads. Additionally, user-uploaded articles for plagiarism detection can further be stored as part of service providers' expanding databases for profit. Essentially, users could not search without exposing their queries to these providers. We present a new solution here: a method for searching the internet using a full article as a query without disclosing the content. Our Sapiens Aperio Veritas Engine (S.A.V.E.) uses an encoding scheme and an FM-index search, borrowed from next-generation human genome sequencing. Each word in a user's query is transformed into one of 12 "amino acids" to create a pseudo-biological sequence (PBS) on the user's device. Plagiarism checks are done by users submitting their locally created PBSs to our cloud service. This detects identical content in our database, which includes all English and Chinese Wikipedia articles and Open Access journals up to April 2021. PBSs, longer than 12 "amino acids", show accurate results with less than 0.8% false positives. Performance-wise, S.A.V.E. runs at a similar genome-mapping speed as Bowtie and is >5 orders faster than BLAST. With both standard and private modes, S.A.V.E. offers a revolutionary, privacy-first search and plagiarism check system. We believe this sets an exciting precedent for future search engines prioritizing user confidentiality. S.A.V.E. can be accessed at https://dyn.life.nthu.edu.tw/SAVE/.

Simulation-predicted and -explained inheritance model of pathogenicity confirmed by transgenic mice models.

Variants in the gap junction beta-2 (GJB2) gene are the most common cause of hereditary hearing impairment. However, how GJB2 variants lead to local physicochemical and structural changes in the hexameric ion channels of connexin 26 (Cx26), resulting in hearing impairment, remains elusive. In this study, using molecular dynamics (MD) simulations, we showed that detached inner-wall N-terminal "plugs" aggregated to reduce the channel ion flow in a highly prevalent V37I variant in humans. To examine the predictive ability of the computational platform, an artificial mutant, V37M, of which the effect was previously unknown in hearing loss, was created. Microsecond simulations showed that homo-hexameric V37M Cx26 hemichannels had an abnormal affinity between the inner edge and N-termini to block the narrower side of the cone-shaped Cx26, while the most stable hetero-hexameric channels did not. From the perspective of the conformational energetics of WT and variant Cx26 hexamers, we propose that unaffected carriers could result from a conformational predominance of the WT and pore-shrinkage-incapable hetero-hexamers, while mice with homozygous variants can only harbor an unstable and dysfunctional N-termini-blocking V37M homo-hexamer. Consistent with these predictions, homozygous V37M transgenic mice exhibited apparent hearing loss, but not their heterozygous counterparts, indicating a recessive inheritance mode. Reduced channel conductivity was found in Gjb2V37M/V37M outer sulcus and Claudius cells but not in Gjb2WT/WT cells. We view that the current computational platform could serve as an assessment tool for the pathogenesis and inheritance of GJB2-related hearing impairments and other diseases caused by connexin dysfunction.

Helical structure motifs made searchable for functional peptide design.

The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for Helicobacter pylori. We also show how the database can be used to design a new antimicrobial peptide that shows better Candida albicans clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/ .

Models with energy penalty on interresidue rotation address insufficiencies of conventional elastic network models.

In this study, I present a new elastic network model, to our knowledge, that addresses insufficiencies of two conventional models-the Gaussian network model (GNM) and the anisotropic network model (ANM). It has been shown previously that the GNM is not rotation-invariant due to its energy, which penalizes rigid-body rotation (external rotation). As a result, GNM models are found contaminated with rigid-body rotation, especially in the most collective ones. A new model (EPIRM) is proposed to remove such external component in modes. The extracted internal motions result from a potential that penalizes interresidue stretching and rotation in a protein. The new model is shown to pertinently describe crystallographic temperature factors (B-factors) and protein open↔closed transitions. Also, the capability of separating internal and external motions in GNM slow modes permits reexamining important mechanochemical properties in enzyme active sites. The results suggest that catalytic residues stay closer to rigid-body rotation axes than their immediate backbone neighbors. I show that the cumulative density of states for EPIRM and ANM follow different power laws as functions of low-mode frequencies. When using a cutoff distance of 7.5 Å, The cumulative density of states of EPIRM scales faster than that of all-atom normal mode analysis and slower than that of simple lattices.

An Effective and Safe Enkephalin Analog for Antinociception.

Opioids account for 69,000 overdose deaths per annum worldwide and cause serious side effects. Safer analgesics are urgently needed. The endogenous opioid peptide Leu-Enkephalin (Leu-ENK) is ineffective when introduced peripherally due to poor stability and limited membrane permeability. We developed a focused library of Leu-ENK analogs containing small hydrophobic modifications. N-pivaloyl analog KK-103 showed the highest binding affinity to the delta opioid receptor (68% relative to Leu-ENK) and an extended plasma half-life of 37 h. In the murine hot-plate model, subcutaneous KK-103 showed 10-fold improved anticonception (142%MPE·h) compared to Leu-ENK (14%MPE·h). In the formalin model, KK-103 reduced the licking and biting time to ~50% relative to the vehicle group. KK-103 was shown to act through the opioid receptors in the central nervous system. In contrast to morphine, KK-103 was longer-lasting and did not induce breathing depression, physical dependence, and tolerance, showing potential as a safe and effective analgesic.

ZHX2 promotes HIF1α oncogenic signaling in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and highly lethal disease, which warrants the critical need to identify new therapeutic targets. We show that Zinc Fingers and Homeoboxes 2 (ZHX2) is amplified or overexpressed in TNBC cell lines and patients. Functionally, depletion of ZHX2 inhibited TNBC cell growth and invasion in vitro, orthotopic tumor growth, and spontaneous lung metastasis in vivo. Mechanistically, ZHX2 bound with hypoxia-inducible factor (HIF) family members and positively regulated HIF1α activity in TNBC. Integrated ChIP-seq and gene expression profiling demonstrated that ZHX2 co-occupied with HIF1α on transcriptionally active promoters marked by H3K4me3 and H3K27ac, thereby promoting gene expression. Among the identified ZHX2 and HIF1α coregulated genes, overexpression of AP2B1, COX20, KDM3A, or PTGES3L could partially rescue TNBC cell growth defect by ZHX2 depletion, suggested that these downstream targets contribute to the oncogenic role of ZHX2 in an accumulative fashion. Furthermore, multiple residues (R491, R581, and R674) on ZHX2 are important in regulating its phenotype, which correspond with their roles on controlling ZHX2 transcriptional activity in TNBC cells. These studies establish that ZHX2 activates oncogenic HIF1α signaling, therefore serving as a potential therapeutic target for TNBC.

Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics.

MOTIVATION: To efficiently analyze the 'native ensemble of conformations' accessible to proteins near their folded state and to extract essential information from observed distributions of conformations, reliable mathematical methods and computational tools are needed. RESULT: Examination of 24 pairs of structures determined by both NMR and X-ray reveals that the differences in the dynamics of the same protein resolved by the two techniques can be tracked to the most robust low frequency modes elucidated by principal component analysis (PCA) of NMR models. The active sites of enzymes are found to be highly constrained in these PCA modes. Furthermore, the residues predicted to be highly immobile are shown to be evolutionarily conserved, lending support to a PCA-based identification of potential functional sites. An online tool, PCA_NEST, is designed to derive the principal modes of conformational changes from structural ensembles resolved by experiments or generated by computations. AVAILABILITY: http://ignm.ccbb.pitt.edu/oPCA_Online.htm

An Efficient Timer and Sizer of Biomacromolecular Motions.

Life ticks as fast as how proteins move. Computationally expensive molecular dynamics simulation has been the only theoretical tool to gauge the time and sizes of these motions, though barely to their slowest ends. Here, we convert a computationally cheap elastic network model (ENM) into a molecular timer and sizer to gauge the slowest functional motions of structured biomolecules. Quasi-harmonic analysis, fluctuation profile matching, and the Wiener-Khintchine theorem are used to define the "time periods," t, for anharmonic principal components (PCs), which are validated by nuclear magnetic resonance (NMR) order parameters. The PCs with their respective "time periods" are mapped to the eigenvalues (λENM) of the corresponding ENM modes. Thus, the power laws t(ns) = 56.1λENM-1.6 and σ2(Å2) = 32.7λENM-3.0 can be established allowing the characterization of the timescales of NMR-resolved conformers, crystallographic anisotropic displacement parameters, and important ribosomal motions, as well as motional sizes of the latter.

Insights into equilibrium dynamics of proteins from comparison of NMR and X-ray data with computational predictions.

For a representative set of 64 nonhomologous proteins, each containing a structure solved by NMR and X-ray crystallography, we analyzed the variations in atomic coordinates between NMR models, the temperature (B) factors measured by X-ray crystallography, and the fluctuation dynamics predicted by the Gaussian network model (GNM). The NMR and X-ray data exhibited a correlation of 0.49. The GNM results, on the other hand, yielded a correlation of 0.59 with X-ray data and a distinctively better correlation (0.75) with NMR data. The higher correlation between GNM and NMR data, compared to that between GNM and X-ray B factors, is shown to arise from the differences in the spectrum of modes accessible in solution and in the crystal environment. Mainly, large-amplitude motions sampled in solution are restricted, if not inaccessible, in the crystalline environment of X-rays. Combined GNM and NMR analysis emerges as a useful tool for assessing protein dynamics.