Geometric deep learning methods and applications in 3D structure-based drug design.

3D structure-based drug design (SBDD) is considered a challenging and rational way for innovative drug discovery. Geometric deep learning is a promising approach that solves the accurate model training of 3D SBDD through building neural network models to learn non-Euclidean data, such as 3D molecular graphs and manifold data. Here, we summarize geometric deep learning methods and applications that contain 3D molecular representations, equivariant graph neural networks (EGNNs), and six generative model methods [diffusion model, flow-based model, generative adversarial networks (GANs), variational autoencoder (VAE), autoregressive models, and energy-based models]. Our review provides insights into geometric deep learning methods and advanced applications of 3D SBDD that will be of relevance for the drug discovery community.

Studying noncovalent or covalent bond problem between smoothened and cholesterol by molecular dynamics simulation and Markov state model.

Smoothened (SMO) is an attractive therapeutic target for the treatment and prevention of several malignant tumors of the nervous system. The crystal structure of SMO shows cholesterol interacts with residue Asp95 via the noncovalent bond. However, some studies indicate that cholesterol covalently binds to residue Asp95 of SMO. To study these contradictory results, we performed molecular dynamics (MD) simulations and Markov state model (MSM) on SMO in complex with noncovalent-bound and covalent-bound cholesterol. The MD simulated results showed that the noncovalent-bound cholesterol was extremely unstable around the position of residue Asp95 of SMO, while the covalent-bound cholesterol could keep the stable connection with residue Asp95 of SMO. The free energy landscape showed that noncovalent-bound cholesterol had more deep energy wells than covalent-bound cholesterol when it dynamically interacted with the extracellular domain of SMO crystal structure. The MSM results showed the noncovalent-bound cholesterol had more dynamic configuration transformation pathways than the covalent-bound cholesterol. These results theoretically revealed cholesterol should have a covalent bond with residue Asp95 if cholesterol could be stable in the near position of residue Asp95 of SMO. Our studies not only elucidate the covalent binding contradictory issue between cholesterol and residue Asp95 of SMO, but also supply helpful information for antagonists design of SMO.

Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents.

Repositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. Computational technologies such as machine learning methods have accelerated the process of drug repositioning in the last few decades years. The repositioning potential of type 2 diabetes mellitus (T2DM) drugs for various diseases such as cancer, neurodegenerative diseases, and cardiovascular diseases have been widely studied. Hence, the related summary about repurposing antidiabetic drugs is of great significance. In this review, we focus on the machine learning methods for the development of new T2DM drugs and give an overview of the repurposing potential of the existing antidiabetic agents.

Insights into the molecular mechanism of positive cooperativity between partial agonist MK-8666 and full allosteric agonist AP8 of hGPR40 by Gaussian accelerated molecular dynamics (GaMD) simulations.

Activation of human free fatty acid receptor 1 (FFAR1, also called hGPR40) enhances insulin secretion in a glucose-dependent manner. Hence, the development of selective agonist targeting hGPR40 has been proposed as a therapeutic strategy of type 2 diabetes mellitus. Some agonists targeting hGPR40 were reported. The radioligand-binding studies and the crystal structures reveal that there are multiple sites on GPR40, and there exists positive binding cooperativity between the partial agonist MK-8666 and full allosteric agonist (AgoPAM) AP8. In this work, we carried out long-time Gaussian accelerated molecular dynamics (GaMD) simulations on hGPR40 to shed light on the mechanism of the cooperativity between the two agonists at different sites. Our results reveal that the induced-fit conformational coupling is bidirectional between the two sites. The movements and rotations of TM3, TM4, TM5 and TM6 due to their inherent flexibility are crucial in coupling the conformational changes of the two agonists binding sites. These helices adopt similar conformational states upon alternative ligand or both ligands binding. The Leu1384.57, Leu1865.42 and Leu1905.46 play roles in coordinating the rearrangements of residues in the two pockets, which makes the movements of residues in the two sites like gear movements. These results provide detailed information at the atomic level about the conformational coupling between different sites of GPR40, and also provide the structural information for further design of new agonists of GPR40. In addition, these results suggest that it is necessary by considering the effect of other site bound in structure-based ligands discovery.

WADDAICA: A webserver for aiding protein drug design by artificial intelligence and classical algorithm.

Artificial intelligence can train the related known drug data into deep learning models for drug design, while classical algorithms can design drugs through established and predefined procedures. Both deep learning and classical algorithms have their merits for drug design. Here, the webserver WADDAICA is built to employ the advantage of deep learning model and classical algorithms for drug design. The WADDAICA mainly contains two modules. In the first module, WADDAICA provides deep learning models for scaffold hopping of compounds to modify or design new novel drugs. The deep learning model which is used in WADDAICA shows a good scoring power based on the PDBbind database. In the second module, WADDAICA supplies functions for modifying or designing new novel drugs by classical algorithms. WADDAICA shows better Pearson and Spearman correlations of binding affinity than Autodock Vina that is considered to have the best scoring power. Besides, WADDAICA supplies a friendly and convenient web interface for users to submit drug design jobs. We believe that WADDAICA is a useful and effective tool to help researchers to modify or design novel drugs by deep learning models and classical algorithms. WADDAICA is free and accessible at https://bqflab.github.io or https://heisenberg.ucam.edu:5000.

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.

Deep learning is an important branch of artificial intelligence that has been successfully applied into medicine and two-dimensional ligand design. The three-dimensional (3D) ligand generation in the 3D pocket of protein target is an interesting and challenging issue for drug design by deep learning. Here, the MolAICal software is introduced to supply a way for generating 3D drugs in the 3D pocket of protein targets by combining with merits of deep learning model and classical algorithm. The MolAICal software mainly contains two modules for 3D drug design. In the first module of MolAICal, it employs the genetic algorithm, deep learning model trained by FDA-approved drug fragments and Vinardo score fitting on the basis of PDBbind database for drug design. In the second module, it uses deep learning generative model trained by drug-like molecules of ZINC database and molecular docking invoked by Autodock Vina automatically. Besides, the Lipinski's rule of five, Pan-assay interference compounds (PAINS), synthetic accessibility (SA) and other user-defined rules are introduced for filtering out unwanted ligands in MolAICal. To show the drug design modules of MolAICal, the membrane protein glucagon receptor and non-membrane protein SARS-CoV-2 main protease are chosen as the investigative drug targets. The results show MolAICal can generate the various and novel ligands with good binding scores and appropriate XLOGP values. We believe that MolAICal can use the advantages of deep learning model and classical programming for designing 3D drugs in protein pocket. MolAICal is freely for any nonprofit purpose and accessible at https://molaical.github.io.

Revealing the Positive Binding Cooperativity Mechanism between the Orthosteric and the Allosteric Antagonists of CCR2 by Metadynamics and Gaussian Accelerated Molecular Dynamics Simulations.

CC chemokine receptor 2 (CCR2) and its endogenous CC chemokine ligands are associated with numerous inflammatory, neurodegenerative diseases, and cancer. CCR2 is becoming an attractive target in the treatment of autoimmune disease and neurodegenerative diseases. The orthosteric antagonist BMS-681 and allosteric antagonist CCR2-RA-[R] of CCR2 show positive binding cooperativity. We performed well-tempered metadynamics simulations and Gaussian accelerated MD simulations to reveal the influence of the orthosteric antagonist on the unbinding of allosteric antagonist of CCR2. We revealed different unbinding pathways of CCR2-RA-[R] in binary complex CCR2-VT5 and ternary complex CCR2-73R-VT5. The different unbinding pathways of CCR2-RA-[R] are due to the conformational dynamics of TM6. We obtained the significant conformational differences of the intracellular side of TM6 upon CCR2 binding to different ligands by GaMD simulation. The conformational dynamics of TM6 are consistent with the unbinding pathway analysis. GaMD simulations indicate that BMS-681 binding restricts the bend of intracellular side of TM6 by stabilizing the extracellular sides of TM6 and TM7. The charged residues Arg2065.43 of TM5 and Glu2917.39 of TM7 play key roles in stabling TM7 and TM6. TM6 and TM7 are crucial components in the orthosteric and allosteric binding sites. Our results illustrate the conformational details about the effect of the orthosteric antagonist on the allosteric antagonist of CCR2. The conformational dynamics of CCR2 upon binding to different ligands can provide a rational basis for development of allosteric ligands of CCR2.

Engineering viable foot-and-mouth disease viruses with increased acid stability facilitate the development of improved vaccines.

Foot-and-mouth disease virus (FMDV), the most acid-unstable virus among picornaviruses, tends to disassemble into pentamers at pH values slightly below neutrality. However, the structural integrity of intact virion is one of the most important factors that influence the induction of a protective antibody response. Thus, improving the acid stability of FMDV is required for the efficacy of vaccine preparations. According to the previous studies, a single substitution or double amino acid substitutions (VP1 N17D, VP2 H145Y, VP2 D86H, VP3 H142D, VP3 H142G, and VP1 N17D + VP2 H145Y) in the capsid were introduced into the full-length infectious clone of type O FMDV vaccine strain O/HN/CHN/93 to develop seed FMDV with improved acid stability. After the transfection into BSR/T7 cells of constructed plasmids, substitution VP1 N17D or VP2 D86H resulted in viable and genetically stable FMDVs, respectively. However, substitution VP2 H145Y or VP1 N17D + VP2 H145Y showed reverse mutation and additional mutations, and substitution VP3 H141G or VP3 H141D prevented viral viability. We found that substitution VP1 N17D or VP2 D86H could confer increased acid resistance, alkali stability, and thermostability on FMDV O/HN/CHN/93, whereas substitution VP1 N17D was observed to lead to a decreased replication ability in BHK-21 cells and mildly impaired virulence in suckling mice. In contrast, substitution VP2 D86H had no negative effect on viral infectivity. These results indicated that the mutant rD86H carrying substitution VP2 D86H firstly reported by us could be more adequate for the development of inactivated FMD vaccines with enhanced acid stability.

Computational Insight Into the Small Molecule Intervening PD-L1 Dimerization and the Potential Structure-Activity Relationship.

Recently, small-molecule compounds have been reported to block the PD-1/PD-L1 interaction by inducing the dimerization of PD-L1. All these inhibitors had a common scaffold and interacted with the cavity formed by two PD-L1 monomers. This special interactive mode provided clues for the structure-based drug design, however, also showed limitations for the discovery of small-molecule inhibitors with new scaffolds. In this study, we revealed the structure-activity relationship of the current small-molecule inhibitors targeting dimerization of PD-L1 by predicting their binding and unbinding mechanism via conventional molecular dynamics and metadynamics simulation. During the binding process, the representative inhibitors (BMS-8 and BMS-1166) tended to have a more stable binding mode with one PD-L1 monomer than the other and the small-molecule inducing PD-L1 dimerization was further stabilized by the non-polar interaction of Ile54, Tyr56, Met115, Ala121, and Tyr123 on both monomers and the water bridges involved in ALys124. The unbinding process prediction showed that the PD-L1 dimerization kept stable upon the dissociation of ligands. It's indicated that the formation and stability of the small-molecule inducing PD-L1 dimerization was the key factor for the inhibitory activities of these ligands. The contact analysis, R-group based quantitative structure-activity relationship (QSAR) analysis and molecular docking further suggested that each attachment point on the core scaffold of ligands had a specific preference for pharmacophore elements when improving the inhibitory activities by structural modifications. Taken together, the results in this study could guide the structural optimization and the further discovery of novel small-molecule inhibitors targeting PD-L1.

Deciphering the Allosteric Effect of Antagonist Vismodegib on Smoothened Receptor Deactivation Using Metadynamics Simulation.

The smoothened receptor (Smo) plays a key role in Hedgehog (Hh) signaling pathway and it has been regarded as an efficacious therapeutic target for basal cell carcinoma (BCC) and medulloblastoma (MB). Nevertheless, the resistance mutation and active mutants of Smo have put forward the requirement of finding more effective inhibitors. Herein, we performed metadynamics simulations on Smo bound with vismodegib (Smo-Vismod) and with cholesterol (Smo-CLR), respectively, to explore the inhibition mechanism of vismodegib. The simulation results indicated that vismodegib-induced shifts of TM5, TM6, and TM7, which permitted the extracellular extension of TM6 and extracellular loop3 (ECL3) to enter the extracellular cysteine-rich domain (CRD) groove. Therefore, an open CRD groove that has not been noticed previously was observed in Smo-Vismod complex. As a consequence, the occupied CRD groove prevents the binding of cholesterol. In addition, the HD and ECLs play crucial roles in the interaction of CRD and TMD. These results reveal that TM5, TM6, and TM7 play important roles in allosteric inhibition the activation of Smo and disrupting cholesterol binding by vismodegib binding. Our results are expected to contribute to understanding the allosteric inhibition mechanism of Smo by vismodegib. Moreover, the detailed conformational changes contribute to the development of novel Smo inhibitors against resistance mutation and active mutants of Smo.

Investigation of ECD conformational transition mechanism of GLP-1R by molecular dynamics simulations and Markov state model.

As a member of the class B G protein-coupled receptors (GPCRs), the glucagon-like peptide-1 (GLP-1) can regulate the blood glucose level by binding to the glucagon-like peptide-1 receptor (GLP-1R). Since the extracellular domain (ECD) of GLP-1R is considered as one of the binding sites of GLP-1, the open and closed states of ECD play an important role in the binding process of GLP-1. To investigate the transition path of GLP-1R ECD, the crystal structures of GLP-1R in its bound and unbound states (apo-state) are chosen to perform a total of 1.6 µs of molecular dynamics simulations. The simulated results show that the ECD of GLP-1R closes in the GLP-1 bound state and opens in the GLP-1 unbound state. To determine the critical role that GLP-1 played in regulating the open and closed states of the ECD, we applied the independent gradient model (IGM) to the simulation trajectories. We found that the "hand-like" N-terminal of the GLP-1R ECD plays an important role in the GLP-1 binding. In contrast, the apo-state GLP-1R ECD opens and exposes the two ligand binding domains of GLP-1 after 200 ns of simulations. To elucidate the open and closed mechanisms of GLP-1R ECD in the apo-state and GLP-1 bound state, the Markov state model (MSM) is performed on the MD simulation trajectories. Our results provide possible transition pathways from the closed state to open state of the apo-state GLP-1R ECD. Each pathway contains several intermediate states that correspond to different local minima in deep wells. The dynamical relationships and the most possible conversion pathway between two states are detailed through the MSM analysis. Our results profile the conformation transition mechanism of the GLP-1R ECD and will help in hypoglycemic peptide design of GLP-1R.

Engineering Responses to Amino Acid Substitutions in the VP0- and VP3-Coding Regions of PanAsia-1 Strains of Foot-and-Mouth Disease Virus Serotype O.

The presence of sequence divergence through adaptive mutations in the major capsid protein VP1, and also in VP0 (VP4 and VP2) and VP3, of foot-and-mouth disease virus (FMDV) is relevant to a broad range of viral characteristics. To explore the potential role of isolate-specific residues in the VP0 and VP3 coding regions of PanAsia-1 strains in genetic and phenotypic properties of FMDV, a series of recombinant full-length genomic clones were constructed using Cathay topotype infectious cDNA as the original backbone. The deleterious and compensatory effects of individual amino acid substitutions at positions 4008 and 3060 and in several different domains of VP2 illustrated that the chain-based spatial interaction patterns of VP1, VP2, and VP3 (VP1-3), as well as between the internal VP4 and the three external capsid proteins of FMDV, might contribute to the assembly of eventually viable viruses. The Y2079H site-directed mutants dramatically induced a decrease in plaque size on BHK-21 cells and viral pathogenicity in suckling mice. Remarkably, the 2079H-encoding viruses displayed a moderate increase in acid sensitivity correlated with NH4Cl resistance compared to the Y2079-encoding viruses. Interestingly, none of all the 16 rescued viruses were able to infect heparan sulfate-expressing CHO-K1 cells. However, viral infection in BHK-21 cells was facilitated by utilizing non-integrin-dependent, heparin-sensitive receptor(s) and replacements of four uncharged amino acids at position 3174 in VP3 of FMDV had no apparent influence on heparin affinity. These results provide particular insights into the correlation of evolutionary biology with genetic diversity in adapting populations of FMDV.IMPORTANCE The sequence variation within the capsid proteins occurs frequently in the infection of susceptible tissue cultures, reflecting the high levels of genetic diversity of FMDV. A systematic study for the functional significance of isolate-specific residues in VP0 and VP3 of FMDV PanAsia-1 strains suggested that the interaction of amino acid side chains between the N terminus of VP4 and several potential domains of VP1-3 had cascading effects on the viability and developmental characteristics of progeny viruses. Y2079H in VP0 of the indicated FMDVs could affect plaque size and pathogenicity, as well as acid sensitivity correlated with NH4Cl resistance, whereas there was no inevitable correlation in viral plaque and acid-sensitive phenotypes. The high affinity of non-integrin-dependent FMDVs for heparin might be explained by the differences in structures of heparan sulfate proteoglycans on the surfaces of different cell lines. These results may contribute to our understanding of the distinct phenotypic properties of FMDV in vitro and in vivo.

How Does Agonist and Antagonist Binding Lead to Different Conformational Ensemble Equilibria of the κ-Opioid Receptor: Insight from Long-Time Gaussian Accelerated Molecular Dynamics Simulation.

The opioid receptors belong to the class A seven transmembrane-spanning (7TM) G protein-coupled receptors (GPCRs). The κ-opioid receptor (KOR) is a subfamily of four opioid receptors. The endogenous peptide and a variety of selective agonists and antagonists of KOR have been developed. The structurally similar ligands at the same site cause completely opposite biological functions and induce different conformational changes. To shed light on the conformation ensembles and conformational dynamics in activation and deactivation processes of KOR, we performed all-atom, long-time Gaussian accelerated molecular dynamics simulation (GaMD) on KOR binding with agonist epoxymorphinan MP1104 and antagonist JDTic, respectively. Our results revealed different conformation ensembles of KOR binding with agonist and with antagonist. Agonist binding stabilizes the active state of key motifs including DYYNM motif and CWxP motif, and biases the conformation equilibria toward the active state. Antagonist binding will not destroy inactive conformation equilibria, by keeping the stable inactive state of these crucial motifs. We found that the inactive apo form of KOR is the most stable state, while the active apo form relaxes readily to inactive state. Our results also revealed a stable intermediate (I), which is attributed to the hydrophobic interactions between Tyr2465.58 and TM6, as well as the steric hindrance of them. Our results not only show the conformation equilibria bias of KOR by binding with agonist and antagonist, but also provide the structural information for the design and discovery of potential ligands with different functions.

Conformation Transition of Intracellular Part of Glucagon Receptor in Complex With Agonist Glucagon by Conventional and Accelerated Molecular Dynamics Simulations.

The inactive conformations of glucagon receptor (GCGR) are widely reported by crystal structures that support the precision structure for drug discovery of type 2 diabetes. The previous study shows that the intracellular part is open in the glucagon-bound GCGR (glu-GCGR) and closed in the apo-GCGR by accelerated molecular dynamics (aMD) simulations. However, the crystal structure of GCGR in complex with partial agonist shows that the intracellular part is closed in the inactive conformation. To understand the differences between the studies of aMD simulations and crystal structure, the 2,500 ns conventional molecular dynamics (cMD) simulations are performed on the simulated model of glu-GCGR. The result shows that the transmembrane helices (TMH) 6 of glu-GCGR is outward ~4 Å to drive the intracellular part of glu-GCGR open until ~390 ns cMD simulations. The (TMH) 6 of glu-GCGR becomes closed after ~490 ns cMD simulations, which are consistent with the crystal structure of GCGR in complex with the partial agonist. To further elucidate the activation mechanism of GCGR deeply, the simulated models of glu-GCGR, apo-GCGR, and antagonist-bound GCGR (ant-GCGR) are constructed to perform 10 of parallel 300 ns aMD simulations, respectively. The results show that both of glu-GCGR and apo-GCGR can generate the open conformations of the intracellular part. But the glu-GCGR has the higher percentage of open conformations than apo-GCGR. The ant-GCGR is restricted to generate the open conformations of the intracellular part by antagonist MK-0893. It indicates that the glu-GCGR, apo-GCGR, and ant-GCGR can be distinguished by the aMD simulated method. Free energy landscape shows that the open conformations of the intracellular part of GCGR are in intermediate state. Our results show that aMD simulations enhance the space samplings of open conformations of GCGR via adding extra boost potential. It indicates that the aMD simulations are an effective way for drug discovery of GCGR.

Computational studies on horseshoe shape pocket of human orexin receptor type 2 and boat conformation of suvorexant by molecular dynamics simulations.

The FDA approved drug suvorexant binds to the horseshoe shape pocket of OX2 R with the boat conformation. The horseshoe shape pocket plays an important role on the biological activity of OX2 R in the cell membrane. To study the binding mechanism between the horseshoe shape pocket of OX2 R and boat conformation of suvorexant, the crystal structures of wild type and N324A mutant of OX2 R in complex with antagonist suvorexant are chosen to perform molecular dynamics (MD) simulations, QM/MM, and MMGBSA calculations. By comparison with the wild type of OX2 R, the results show the 1,2,3-triazole and p-toluamide groups of suvorexant are changed in the N324A mutant of OX2 R during 200 ns MD simulations. The QM/MM and weak interaction analysis are employed to calculate the non-covalent bonds interaction between suvorexant and key residues in the wild type and N324A mutant of OX2 R. The MMGBSA calculations indicate the entropy energy is an important influence factor for suvorexant affinity in the distorted horseshoe shape pocket of OX2 R. Our results not only show the horseshoe shape pocket of OX2 R is the necessary conformation for the binding of antagonist suvorexant, but also give the important sites and structural features for antagonist design of OX2 R.

Influence of EGCG on α-synuclein (αS) aggregation and identification of their possible binding mode: A computational study using molecular dynamics simulation.

The accumulation of intrinsically disordered α-synuclein (αS) protein that can form ß-sheet-rich fibrils is linked to Parkinson's disease. (-)-Epigallocatechin-3-gallate (EGCG) is the most abundant active component in green tea and can inhibit the fibrillation of αS. The elucidation of this molecular mechanism will be helpful to understand the inhibition mechanism of EGCG to the fibrillation of αS and also to find more potential small molecules that can inhibit the aggregation of αS. In this work, to study the influence of EGCG on the structure of ß-sheet-rich fibrils of αS and identification of their possible binding mode, molecular dynamics simulations of pentamer and decamer aggregates of αS in complex with EGCG were performed. The obtained results indicate that EGCG can remodel the αS fibrils and break the initial ordered pattern by reducing the ß-sheet content. EGCG can also break the Greek conformation of αS by the disappeared H-bond in the secondary structure of turn. The results from our study can not only reveal the specific interaction between EGCG and ß-sheet-rich fibrils of αS, but also provide the useful guidance for the discovery of other potential inhibitors.

Molecular dynamics simulation, binding free energy calculation and unbinding pathway analysis on selectivity difference between FKBP51 and FKBP52: Insight into the molecular mechanism of isoform selectivity.

As co-chaperones of the 90-kDa heat shock protein(HSP90), FK506 binding protein 51 (FKBP51) and FK506 binding protein 52 (FKBP52) modulate the maturation of steroid hormone receptor through their specific FK1 domains (FKBP12-like domain 1). The inhibitors targeting FK1 domains are potential therapies for endocrine-related physiological disorders. However, the structural conservation of the FK1 domains between FKBP51 and FKBP52 make it difficult to obtain satisfactory selectivity in FK506-based drug design. Fortunately, a series of iFit ligands synthesized by Hausch et al exhibited excellent selectivity for FKBP51, providing new opportunity for design selective inhibitors. We performed molecular dynamics simulation, binding free energy calculation and unbinding pathway analysis to reveal selective mechanism for the inhibitor iFit4 binding with FKBP51 and FKBP52. The conformational stability evaluation of the "Phe67-in" and "Phe67-out" states implies that FKBP51 and FKBP52 have different preferences for "Phe67-in" and "Phe67-out" states, which we suggest as the determinant factor for the selectivity for FKBP51. The binding free energy calculations demonstrate that nonpolar interaction is favorable for the inhibitors binding, while the polar interaction and entropy contribution are adverse for the inhibitors binding. According to the results from binding free energy decomposition, the electrostatic difference of residue 85 causes the most significant thermodynamics effects on the binding of iFit4 to FKBP51 and FKBP52. Furthermore, the importance of substructure units on iFit4 were further evaluated by unbinding pathway analysis and residue-residue contact analysis between iFit4 and the proteins. The results will provide new clues for the design of selective inhibitors for FKBP51.

The pH stability of foot-and-mouth disease virus.

ᅟ: This review summarized the molecular determinants of the acid stability of FMDV in order to explore the uncoating mechanism of FMDV and improve the acid stability of vaccines. BACKGROUND: The foot-and-mouth disease virus (FMDV) capsid is highly acid labile and tends to dissociate into pentameric subunits at acidic condition to release viral RNA for initiating virus replication. However, the acid stability of virus capsid is greatly required for the maintenance of intact virion during the process of virus culture and vaccine production. The conflict between the acid lability in vivo and acid stability in vitro of FMDV capsid promotes the selection of a series of amino acid substitutions which can confer resistance to acid-induced FMDV inactivation. In order to explore the uncoating activity of FMDV and enhance the acid stability of vaccines, we summarized the available works about the pH stability of FMDV. In this review, we analyzed the intrinsic reasons for the acid instability of FMDV from the structural and functional aspects. We also listed all substitutions obtained by different research methods and showed them in the partial capsid of FMDV. We found that a quadrangle region in the viral capsid was the place where a great many pH-sensitive residues were distributed. As the uncoating event of FMDV is dependent on the pH-sensitive amino acid residues in the capsid, this most pH-sensitive position indicates a potential candidate location for RNA delivery triggered by the acid-induced coat disassociation. SHORT CONCLUSION: This review provided an overview of the pH stability of FMDV. The study of pH stability of FMDV not only contributes to the exploration of molecule and mechanism information for FMDV uncoating, but also enlightens the development of FMDV vaccines, including the traditionally inactivated vaccines and the new VLP (virus-like particle) vaccines.

Experimental and Theoretical Insights into the Inhibition Mechanism of Prion Fibrillation by Resveratrol and its Derivatives.

Resveratrol and its derivatives have been shown to display beneficial effects to neurodegenerative diseases. However, the molecular mechanism of resveratrol and its derivatives on prion conformational conversion is poorly understood. In this work, the interaction mechanism between prion and resveratrol as well as its derivatives was investigated using steady-state fluorescence quenching, Thioflavin T binding assay, Western blotting, and molecular dynamics simulation. Protein fluorescence quenching method and Thioflavin T assay revealed that resveratrol and its derivatives could interact with prion and interrupt prion fibril formation. Molecular dynamics simulation results indicated that resveratrol can stabilize the PrP127-147 peptide mainly through π-π stacking interactions between resveratrol and Tyr128. The hydrogen bonds interactions between resveratrol and the PrP127-147 peptide could further reduce the flexibility and the propensity to aggregate. The results of this study not only can provide useful information about the interaction mechanism between resveratrol and prion, but also can provide useful clues for further design of new inhibitors inhibiting prion aggregation.

Higher-Ordered Actin Structures Remodeled by Arabidopsis ACTIN-DEPOLYMERIZING FACTOR5 Are Important for Pollen Germination and Pollen Tube Growth.

Dynamics of the actin cytoskeleton are essential for pollen germination and pollen tube growth. ACTIN-DEPOLYMERIZING FACTORs (ADFs) typically contribute to actin turnover by severing/depolymerizing actin filaments. Recently, we demonstrated that Arabidopsis subclass III ADFs (ADF5 and ADF9) evolved F-actin-bundling function from conserved F-actin-depolymerizing function. However, little is known about the physiological function, the evolutional significance, and the actin-bundling mechanism of these neofunctionalized ADFs. Here, we report that loss of ADF5 function caused delayed pollen germination, retarded pollen tube growth, and increased sensitive to latrunculin B (LatB) treatment by affecting the generation and maintenance of actin bundles. Examination of actin filament dynamics in living cells revealed that the bundling frequency was significantly decreased in adf5 pollen tubes, consistent with its biochemical functions. Further biochemical and genetic complementation analyses demonstrated that both the N- and C-terminal actin-binding domains of ADF5 are required for its physiological and biochemical functions. Interestingly, while both are atypical actin-bundling ADFs, ADF5, but not ADF9, plays an important role in mature pollen physiological activities. Taken together, our results suggest that ADF5 has evolved the function of bundling actin filaments and plays an important role in the formation, organization, and maintenance of actin bundles during pollen germination and pollen tube growth.