Disulfide bonds are covalently bonded sulfur atoms from cysteine pairs in protein structures. Due to the importance of disulfide bonds in protein folding and structural stability, artificial ...disulfide bonds are often engineered by cysteine mutation to enhance protein structural stability. To facilitate the experimental design, we implemented a method based on neural networks to predict amino acid pairs for cysteine mutations to form engineered disulfide bonds. The designed neural network was trained with high-resolution structures curated from the Protein Data Bank. The testing results reveal that the proposed method recognizes 99% of natural disulfide bonds. In the test with engineered disulfide bonds, the algorithm achieves similar accuracy levels with other state-of-the-art algorithms in published dataset and better performance for two comprehensively studied proteins with 70% accuracy, demonstrating potential applications in protein engineering. The neural network framework allows exploiting the full features in distance space, and therefore improves accuracy of the disulfide bond engineering site prediction. The source code and a web server are available at http://liulab.csrc.ac.cn/ssbondpre.
The cannabinoid receptor 1 (CB1) is the principal target of the psychoactive constituent of marijuana, the partial agonist Δ9-tetrahydrocannabinol (Δ9-THC). Here we report two agonist-bound crystal ...structures of human CB1 in complex with a tetrahydrocannabinol (AM11542) and a hexahydrocannabinol (AM841) at 2.80 Å and 2.95 Å resolution, respectively. The two CB1-agonist complexes reveal important conformational changes in the overall structure, relative to the antagonist-bound state, including a 53% reduction in the volume of the ligand-binding pocket and an increase in the surface area of the G-protein-binding region. In addition, a 'twin toggle switch' of Phe2003.36 and Trp3566.48 (superscripts denote Ballesteros-Weinstein numbering) is experimentally observed and appears to be essential for receptor activation. The structures reveal important insights into the activation mechanism of CB1 and provide a molecular basis for predicting the binding modes of Δ9-THC, and endogenous and synthetic cannabinoids. The plasticity of the binding pocket of CB1 seems to be a common feature among certain class A G-protein-coupled receptors. These findings should inspire the design of chemically diverse ligands with distinct pharmacological properties.
Within a short period of time, COVID-19 grew into a world-wide pandemic. Transmission by pre-symptomatic and asymptomatic viral carriers rendered intervention and containment of the disease extremely ...challenging. Based on reported infection case studies, we construct an epidemiological model that focuses on transmission around the symptom onset. The model is calibrated against incubation period and pairwise transmission statistics during the initial outbreaks of the pandemic outside Wuhan with minimal non-pharmaceutical interventions. Mathematical treatment of the model yields explicit expressions for the size of latent and pre-symptomatic subpopulations during the exponential growth phase, with the local epidemic growth rate as input. We then explore reduction of the basic reproduction number R
through specific transmission control measures such as contact tracing, testing, social distancing, wearing masks and sheltering in place. When these measures are implemented in combination, their effects on R
multiply. We also compare our model behaviour to the first wave of the COVID-19 spreading in various affected regions and highlight generic and less generic features of the pandemic development.
In the past 10 years, the world has witnessed the revolutionary development of X-ray free electron lasers (XFELs) and their applications in many scientific disciplinaries ....
Amino acids form protein 3D structures in unique manners such that the folded structure is stable and functional under physiological conditions. Non-specific and non-covalent interactions between ...amino acids exhibit neighborhood preferences. Based on structural information from the protein data bank, a statistical energy function was derived to quantify amino acid neighborhood preferences. The neighborhood of one amino acid is defined by its contacting residues, and the energy function is determined by the neighboring residue types and relative positions. The neighborhood preference of amino acids was exploited to facilitate structural quality assessment, which was implemented in the neighborhood preference program NEPRE. The source codes are available via https://github.com/LiuLab-CSRC/NePre.
Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described ...from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino acid. Such distributions can reveal relation between ions and amino acids, so it is desirable to carry out a systematic survey of 'ion-amino acid' pairing interaction and share the information with a publicly available database.
The survey in the Protein Data Bank (PDB) revealed that approximately 40% of molecules records contain at least one ion. To reduce the bias resulted from protein redundancy, the statistics were extracted from a non-redundant dataset by excluding the proteins with similar sequences. Based on the structures of protein molecules and the location of ions, the statistical distributions of ions around each proteinogenic amino acid type were investigated and further summarized in a database. To systematically quantify the interactions between ions and each amino acid, the positions of ions were mapped to the coordinate system centered at each neighboring amino acid. It was found that the distribution of ions follows the expected rules governed by the physicochemical interactions in general. Large variations were observed, reflecting the preference in 'ion-amino acid' interactions. The analysis program is written in the Python programming language. The statistical results and program are available from the online database: ion distribution in protein molecules (IDPM) at http://liulab.csrc.ac.cn/idpm/ .
The spatial distribution of ions around amino acids is documented and analyzed. The statistics can be useful for identifying ion types for a given site in biomolecules, and can be potentially used in ion position prediction for given structures.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
High-accuracy ab initio folding has remained an elusive objective despite decades of effort. To explore the folding landscape of villin headpiece subdomain HP35, we conducted two sets of replica ...exchange molecular dynamics for 200 ns each and three sets of conventional microsecond-long molecular dynamics simulations, using AMBER FF03 force field and a generalized-Born solvation model. The protein folded consistently to the native state; the lowest${\rm C}_{\alpha}\text{-}{\rm rmsd}$from the x-ray structure was 0.46 Å, and the${\rm C}_{\alpha}\text{-}{\rm rmsd}$of the center of the most populated cluster was 1.78 Å at 300 K. ab initio simulations have previously not reached this level. The folding landscape of HP35 can be partitioned into the native, denatured, and two intermediate-state regions. The native state is separated from the major folding intermediate state by a small barrier, whereas a large barrier exists between the major folding intermediate and the denatured states. The melting temperature$T_{{\rm m}}=339\ {\rm K}$extracted from the heat-capacity profile was in close agreement with the experimentally derived$T_{{\rm m}}=342\ {\rm K}$. A comprehensive picture of the kinetics and thermodynamics of HP35 folding emerges when the results from replica exchange and conventional molecular dynamics simulations are combined.
Lipidic cubic phase (LCP) crystallization has proven successful for high-resolution structure determination of challenging membrane proteins. Here we present a technique for extruding gel-like LCP ...with embedded membrane protein microcrystals, providing a continuously renewed source of material for serial femtosecond crystallography. Data collected from sub-10-μm-sized crystals produced with less than 0.5 mg of purified protein yield structural insights regarding cyclopamine binding to the Smoothened receptor.
Serial crystallography is a powerful technique in structure determination using many small crystals at X‐ray free‐electron laser or synchrotron radiation facilities. The large diffraction data ...volumes require high‐throughput software to preprocess the raw images for subsequent analysis. ClickX is a program designated for serial crystallography data preprocessing, capable of rapid data sorting for online feedback and peak‐finding refinement by parameter optimization. The graphical user interface (GUI) provides convenient access to various operations such as pattern visualization, statistics plotting and parameter tuning. A batch job module is implemented to facilitate large‐data‐volume processing. A two‐step geometry calibration for single‐panel detectors is also integrated into the GUI, where the beam center and detector tilting angles are optimized using an ellipse center shifting method first, then all six parameters, including the photon energy and detector distance, are refined together using a residual minimization method. Implemented in Python, ClickX has good portability and extensibility, so that it can be installed, configured and used on any computing platform that provides a Python interface or common data file format. ClickX has been tested in online analysis at the Pohang Accelerator Laboratory X‐ray Free‐Electron Laser, Korea, and the Linac Coherent Light Source, USA. It has also been applied in post‐experimental data analysis. The source code is available via https://github.com/LiuLab‐CSRC/ClickX under a GNU General Public License.
A Python‐based program for serial crystallography experimental data preprocessing is developed for both online and offline analysis. Enhanced features include a graphical user interface, batch job execution and fast parameter optimizations.
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