Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike protein and the membrane (M) protein, which may imply an enhanced ability to evade immune responses. In this study, an examination of co-mutations within the spike RBD and their potential correlation with mutations in the M protein was conducted. The EVmutation method was utilized to analyze the distribution of the mutations to elucidate the relationship between the mutations in the spike RBD and the alterations in the M protein. Additionally, the Sequence-to-Sequence Transformer Model (S2STM) was employed to establish mapping between the amino acid sequences of the spike RBD and M proteins, offering a novel and efficient approach for streamlined sequence analysis and the exploration of their interrelationship. Certain mutations in the spike RBD, G339D-S373P-S375F and Q493R-Q498R-Y505, are associated with a heightened propensity for inducing mutations at specific sites within the M protein, especially sites 3 and 19/63. These results shed light on the concept of mutational synergy between the spike RBD and M proteins, illuminating a potential mechanism that could be driving the evolution of SARS-CoV-2.

How to effectively plug the multi-scale fractured water channeling has always been the key to achieving efficient water flooding of fractured low-permeability oil reservoirs. In this paper, a new type of supramolecular–polymer composite gel is developed, which is suitable for plugging multi-scale fractured water channeling. The supramolecular–polymer composite gel is composed of a polymer (such as polyacrylamide), cross-linking agent (such as polyethyleneimine), supramolecular gel factor (such as cyclodextrin) and polarity regulator (such as ethyl alcohol). The mass fraction of polyacrylamide, polyethyleneimine, cyclodextrin and ethyl alcohol are 0.15%, 0.2%, 1% and 0.2%, respectively. At the initial state, the viscosity of the composite gelant system is less than 20 mPa·s. It has good injection performance in micro-scale fractures and can enter the deep part of a fractured reservoir. At 40 °C, the composite gelant system can form a gel with a double network structure after gelation. One of the networks is formed by the covalent interaction between polyacrylamide and polyethyleneimine, the other network is formed by the self-assembly of cyclodextrins under the action of the ethyl alcohol. The comprehensive performance of the composite gel is greatly improved. The strength of the composite gel is >5 × 104 mPa·s, and it has good plugging strength in large-scale fractures. The composite gel can be used as a conformance control agent for fractured low-permeability oilfields.

While undergoing structural deformation, DNA experiences changes in the interactions between its internal base pairs, presenting challenges to conventional elastic methods. To address this, we propose the Discrete Critical State (DCS) model in this paper. This model combines surface discrete frame theory with gauge theory and Landau phase transition theory to investigate DNA’s structural deformation, phase transitions, and chirality. Notably, the DCS model considers both the internal interactions within DNA and formulates an overall equation using unified physical and geometric parameters. By employing the discrete frame, we derive the evolution of physical quantities along the helical axis of DNA, including geodesic curvature, geodesic torsion, and others. Our findings indicate that B-DNA has a significantly lower free energy density compared to Z-DNA, which is in agreement with experimental observations. This research reveals that the direction of base pairs is primarily governed by the geodesic curve within the helical plane, aligning closely with the orientation of the base pairs. Moreover, the geodesic curve has a profound influence on the arrangement of base pairs at the microscopic level and effectively regulates the configuration and geometry of DNA through macroscopic-level free energy considerations.

The latent features extracted from the multiple sequence alignments (MSAs) of homologous protein families are useful for identifying residue-residue contacts, predicting mutation effects, shaping protein evolution, etc. Over the past three decades, a growing body of supervised and unsupervised machine learning methods have been applied to this field, yielding fruitful results. Here, we propose a novel self-supervised model, called encoder-transformation layer-decoder (ETLD) architecture, capable of capturing protein sequence latent features directly from MSAs. Compared to the typical autoencoder model, ETLD introduces a transformation layer with the ability to learn inter-site couplings, which can be used to parse out the two-dimensional residue-residue contacts map after a simple mathematical derivation or an additional supervised neural network. ETLD retains the process of encoding and decoding sequences, and the predicted probabilities of amino acids at each site can be further used to construct the mutation landscapes for mutation effects prediction, outperforming advanced models such as GEMME, DeepSequence and EVmutation in general. Overall, ETLD is a highly interpretable unsupervised model with great potential for improvement and can be further combined with supervised methods for more extensive and accurate predictions.

p38α mitogen-activated protein kinase (MAPK) undergoes autophosphorylation induced by the binding of TGFβ-activated kinase 1 binding protein 1 (TAB1) in myocardial ischemia. Investigation of the conformational transformations in p38α triggered by TAB1 binding is motivated by the need to find selective p38α activation inhibitors to treat myocardial ischemia. Herein, the conformational transformations of p38α were studied via all-atom accelerated molecular dynamics simulations and principal component analysis. With the binding of TAB1, the conformational changes of p38α auto-activation were characterized by the movement of the activation loop (A-loop) away from the αG helix toward the αF, αE helixes and L16-loop. In addition, a diverse intermediate state with an extensional and phosphorylated A-loop different from the transition intermediate state was explored. The conformational changes, including the A-loop alpha-structure breaking and the stronger hydrogen bond network formation, are accompanied by the extension of the A-loop and more intramolecular interactions in p38α. TAB1 correlates with other regions of p38α that are distal from the TAB1-binding site, including the A-loop, αC helix, and L16-loop, which regulates the intramolecular correlation of p38α. And, the phosphorylation further enhances the correlations between the A-loop and the other regions of p38α. The correlation results imply the regulation process of p38α conformational transformations. These findings will improve our understanding of the autophosphorylation of kinase and facilitate the development of selective inhibitors for the treatment of ischemic injury.

Lymphokine-activated killer T-cell-originated protein kinase (TOPK) is a potential target for cancer therapy. To explore the micromechanism, we proposed the N-terminal premodel (NTPM) of the TOPK monomer via homology modeling and molecular dynamic simulations and analyzed the conformational dynamics by Markov state model analysis. The electronegative insert (ENI) motif of the NTPM can be opened with a small probability under wild type, regulated by the so-called "N-C" interaction zone consisting of the N-terminal head, the coil between β3-strand and αC-helix, and the ENI motif. Glutamate substitution at threonine residue 9 or tyrosine residue 74 promotes the closed-open transition, revealing the details of phosphorylation. Allosteric effects induce functionally relevant structural changes, such as increased structural flexibility and active sites, which are thought to be necessary for further activation or binding. These findings provide rational structural templates for designing state-dependent inhibitors and give insight into the molecular regulatory mechanisms of TOPK monomers.

CD147 functions as the receptor of extracellular cyclophilin A (CypA) in various diseases, and CD147-CypA binding ulteriorly underlies the pathological process of various viral infections including HIV-1, SARS, and SARS-CoV-2. Although CyPA has been identified as a key intermediate pro-inflammatory factor, the mechanism by which CD147 cooperates with CypA in the development of the cytokine storm remains largely unknown, and the binding profile of CD147 with CypA remains to be elucidated as well. Here, we prepared three binding models of the CD147-CypA complex, including the active site of CypA severally binding to the groove bound by the Ig1 and Ig2 domains (model-0), P180-G181 (model-1), and P211 (model-2) of CD147, as well as introducing mutations P180A-G181A and P211A individually in each model. All systems were studied using accelerated molecular dynamics simulations and the molecular mechanics generalized Born surface area (MM/GBSA) method. For model-0, CypA bound to the ectodomain of CD147 with the highest binding affinity. Moreover, mutations P180A-G181A of CD147 in model-0 decreased the binding affinity and weakened the dynamic correlation between CD147 and CypA, which resulted in CypA shifting from the initial binding location. Other residue mutations of CD147 did not significantly affect the CD147-CypA binding, as reflected by the energy and structural analyses. Compared with surface plasmon resonance results and nuclear magnetic resonance shift signals, CypA should tend to reciprocally bind to the groove of CD147, and the binding process might be modulated by P180-G181 rather than P211. Besides, residue R201 of CD147 is critical for CD147-CypA binding and needs further experimental verification. These findings further our understanding of the recruitment between CD147 and CypA and its potential role in the development of inflammation and viral infection.

Inhibition of the cholesteryl ester transfer protein (CETP) has been considered as a promising way for the treatment of cardiovascular disease (CVD) for three decades. However, clinical trials of several CETP inhibitors with various potencies have been marginally successful at best, raising doubts on the target drugability of CETP. The in-depth understanding of the glycosylated CETP structure could be beneficial to more definitive descriptions of the CETP function and the underlying mechanism. In this work, large-scale molecular dynamics simulations were performed to thoroughly explore the mechanism of glycans modulating CETP. Here, the extensive simulation results intensely suggest that glycan88 tends to assist CETP in forming a continuous tunnel throughout interacting with the upper-right region of the N-barrel, while it also could prevent the formation of a continuous tunnel by swinging toward the right-rear of the N-barrel. Furthermore, glycan240 formed stable H-bonds with Helix-B and might further stabilize the central cavity of CETP. Furthermore, the nonspecific involvement of the hydroxyl groups from the various glycans with protein core interactions and the similar influence of different glycans trapped at similar regions on the protein structure suggest that physiological glycan may lead to a similar effect. This study would provide valuable insights into devising novel methods for CVD treatment targeting CETP and functional studies about glycosylation for other systems.

To date, many experiments have revealed that the functional balance between hemagglutinin (HA) and neuraminidase (NA) plays a crucial role in viral mobility, production, and transmission. However, whether and how HA and NA maintain balance at the sequence level needs further investigation. Here, we applied principal component analysis and hierarchical clustering analysis on thousands of HA and NA sequences of A/H1N1 and A/H3N2. We discovered significant coevolution between HA and NA at the sequence level, which is closely related to the type of host species and virus epidemic years. Furthermore, we propose a sequence-to-sequence transformer model (S2STM), which mainly consists of an encoder and a decoder that adopts a multi-head attention mechanism for establishing the mapping relationship between HA and NA sequences. The training results reveal that the S2STM can effectively realize the “translation” from HA to NA or vice versa, thereby building a relationship network between them. Our work combines unsupervised and supervised machine learning methods to identify the sequence matching between HA and NA, which will advance our understanding of IAVs’ evolution and also provide a novel idea for sequence analysis methods.

p38α is a key serine/threonine kinase that can enable atypical auto-activation through Zap70 phosphorylation and initiate T cell receptor signaling. The auto-activation plays an important role in autoimmune diseases. Although the classical activation mechanism of p38α has been studied in-depth, the atypical activation mechanism of Y323 phosphorylation-induced p38α auto-activation remains largely unexplained, especially the regulatory effects of phosphorylation on different sites (Y323 vs T180). From the X-ray experimental data, we identified the inactive and active states of p38α using principal component analysis. To understand the auto-activation process and the internal driving mechanism, a computational paradigm that couples the targeted molecular dynamics simulations, the String Method, and the umbrella sampling strategy were employed to generate the conformational landscape of p38α, including p38α T180-Y323, p38α T180-pY323, and p38α pT180-pY323 systems (pT180/pY323: phosphorylated T180/Y323). We explored that pY323 could change the conformational distribution and promote the conformational transition of p38α from the inactive state to the active state. Auto-activation of p38α is regulated by pY323 through destabilization of the hydrophobic core structure and aided by R173. This study will further explain the conformational transition of p38α induced by Y323 phosphorylation and provide insights into the universal molecular auto-activation mechanism of the p38 subfamily at the atomic level.

SARS-CoV-2 has recently caused an epidemic in humans and poses a huge threat to global public health. As a primary receptor of SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2) exists in different hosts that are in close contact with humans, especially cats and dogs. However, the underlying mechanism of how the spike receptor binding domain (RBD) of SARS-CoV-2 cooperates with human ACE2 (hACE2), cat ACE2 (cACE2) and dog ACE2 (dACE2) and the variation in binding remains largely unsolved. Therefore, we explored the binding behavior of the spike RBD with cACE2, dACE2 and hACE2 via all-atom molecular dynamics simulations. In accordance with the binding free energies and residue interactions, the spike RBD has respective binding specificities with cACE2, dACE2 and hACE2, and the binding affinities decrease in the order of hACE2, cACE2, dACE2, mainly due to changes in the amino acids Q24L, H34Y, and M82T in cACE2 or dACE2. Furthermore, alanine scanning analysis results validated some key residues of the spike RBD interact with ACE2 and provided clues to the variation of amino acid that could influence the transmissibility or immune responses of SARS-CoV-2. Decreasing dynamic correlations strengths of ACE2 with the RBD were found in all hACE2-RBD, cACE2-RBD and dACE2-RBD systems. The ACE2 protein shows variable motion modes across the zinc metallopeptidase domain, which induces different interactions between ACE2 and the RBD. Our studies reveal that the motion pattern of the zinc metallopeptidase domain is critical to the binding behavior of RBD with ACE2. These findings could aid our understanding of selective recognition involving various ACE2 with the SARS-CoV-2 spike and shed further light on the binding mechanisms.

The coronavirus 2019 (COVID‐19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has spread across the world and is responsible for over 1,686,267 deaths worldwide. Co‐infection with influenza A virus (IFV‐A) during the upcoming flu season may complicate diagnosis and treatment of COVID‐19. Little is known about epidemiology and outcomes of co‐infection. Data for 213 COVID‐19 patients treated at Tongji Hospital in Wuhan from January 28, 2020 to March 24, 2020 were retrospectively analyzed. Ninety‐seven of the patients (45.5%) tested positive for anti‐ IFV‐A immunoglobulin M antibodies. The clinical characteristics were described and analyzed for patients with SARS‐CoV‐2 infection only and patients with SARS‐CoV‐2/IFV‐A co‐infection. Patients with co‐infection showed similar patterns of symptoms and clinical outcomes to patients with SARS‐CoV‐2 infection only. However, an increased expression of serum cytokines (interleukin‐2R [IL‐2R], IL‐6, IL‐8, and tumor necrosis factor‐α) and cardiac troponin I, and higher incidence of lymphadenopathy were observed in patients with SARS‐CoV‐2 infection only. Male patients and patients aged less than 60 years in the SARS‐CoV‐2 infection group also had significantly higher computed tomography scores than patients in co‐infection group, indicating that co‐infection with IFV‐A had no effect on the disease outcome but alleviated inflammation in certain populations of COVID‐19 patients. The study will provide a reference for diagnosing and treating IFV‐A and SARS‐CoV‐2 co‐infection cases in the upcoming flu season.

The appropriate selection of initial receptor structure has been the "cornerstone" or foundation of successful structure-based virtual screening (SBVS), and plagued the structure-based design with a significant practical problem to determine the major physiological states or important transition states of receptors (e.g. proteins with multiple low-energy conformations and liganddependent conformational dynamics). It is well known that current SBVS methods lack the capacity to capture and characterize the intrinsic receptor flexibility with ideal cost-effectiveness. In recent years, cryoelectron microscopy (cryo-EM) has been routinely applied in the determination of biomolecular assemblies within the physiological state. In this work, we review the roles of cryo-EM and ensemble docking methods to present the intrinsically dynamic behavior of biomacromolecules, as well as the ever-improving estimation of ligand binding affinities and receptor-ligand thermodynamics. Finally, we also provide a viewpoint for further research works on modeling receptor dynamics.

Coronavirus Disease 2019 (COVID-19), caused by the novel coronavirus, has spread rapidly across China. Consequently, there is an urgent need to sort and develop novel agents for the prevention and treatment of viral infections. A rapid structure-based virtual screening is used for the evaluation of current commercial drugs, with structures of human angiotensin converting enzyme II (ACE2), and viral main protease, spike, envelope, membrane and nucleocapsid proteins. Our results reveal that the reported drugs Arbidol, Chloroquine and Remdesivir may hinder the entry and release of virions through the bindings with ACE2, spike and envelope proteins. Due to the similar binding patterns, NHC (β-d-N4-hydroxycytidine) and Triazavirin are also in prospects for clinical use. Main protease (3CLpro) is likely to be a feasible target of drug design. The screening results to target 3CL-pro reveal that Mitoguazone, Metformin, Biguanide Hydrochloride, Gallic acid, Caffeic acid, Sulfaguanidine and Acetylcysteine seem be possible inhibitors and have potential application in the clinical therapy of COVID-19.

Offering a new strategy for resurrecting PPARγ-targeted therapeutics to chemoprevention, by taking the conformational plasticity of the receptor into account in the virtual screening procedure.

Communicated by Ramaswamy H. Sarma

Develops a new distributed P2P trust model named NBRTrust(node behavior relation trust) for appraising the degree of confidence of nodes.The global trust model NBRTrust with the correlativities between nodes as factors was developed.A distributed network β-list was built in correlation with the communication histories of nodes to appraise locally the degree of confidence of nodes,then the behavioral correlativities between nodes were computed distributively.Defines the mathematical expression of the model and distributed computation,with the P2P communication model developed on the basis of NBRTrust model.Simulation results revealed that the NBRTrust model is more objective and effective than the simply local or global trust model,which is able to resist efficiently the fraudulent acts from a single or grouped malignant nodes.

The performance of structured peer-to-peer overlay networks depends on the routing protocols mainly. The current protocols we used usually maintain a O(logN) routing table and O(logN) routing hops. To get better routing speed with less scale routing table, using O(1) node finger to get O(N) route path, a new protocol named CSSP was presented. This protocol has three layers: cache-nodes layer, super-node layer, and successor-node layer. A short routing table was made to record “L” cache nodes, one super node and one successor node. Algorithms for maintaining the route table was presented in this paper. A selection algorithm was presented to select the super node who could cache all of the nodes. And the cache-nodes, super-node and successor-node ensure the high performance of the CSSP. Compared to chord, pastry and etc., the CSSP increases the performance in routing table maintaining, routing hops, fault-tolerance and the amount of trembled nodes while some nodes inject and eject the CSSP p2p system. The conclusion shows that the CSSP is an efficient route algorithm, but also some problems waiting for further study.

Performance of structured peer-to-peer overlay networks depends on the routing protocols. To get better routing speed with less scale routing table, using O (1) node finger to get O (N) route path, a new routing protocol named BCPP was presented. Structured by a bidirectional circle topology, this p2p network has a short routing table to record one super node, one successor node, one previous node and several cache nodes. Algorithms for maintaining the route table and a distributed selection algorithm for selecting super node were presented in this paper. The super node and bidirectional neighbor nodes ensure the high performance of the BCPP. Compared to some other structured p2p overlay routing protocols, the BCPP increases the performance in routing table maintaining, routing hops, fault-tolerance and the amount of trembled nodes while some nodes inject and eject the BCPP p2p system. The conclusions show that the BCPP is an efficient route algorithm, but also some problems waiting for further study.