Negative afterimages are perceptual phenomena that occur after physical stimuli disappear from sight. Their origin is linked to transient post-stimulus responses of visual neurons. The receptive fields (RFs) of these subcortical ON- and OFF-center neurons exhibit antagonistic interactions between central and surrounding visual space, resulting in selectivity for stimulus polarity and size. These two features are closely intertwined, yet their relationship to negative afterimage perception remains unknown. Here we tested whether size differentially affects the perception of bright and dark negative afterimages in humans of both sexes, and how this correlates with neural mechanisms in subcortical ON and OFF cells. Psychophysically, we found a size-dependent asymmetry whereby dark disks produce stronger and longer-lasting negative afterimages than bright disks of equal contrast at sizes >0.8°. Neurophysiological recordings from retinal and relay cells in female cat dorsal lateral geniculate nucleus showed that subcortical ON cells exhibited stronger sustained post-stimulus responses to dark disks, than OFF cells to bright disks, at sizes >1°. These sizes agree with the emergence of center-surround antagonism, revealing stronger suppression to opposite-polarity stimuli for OFF versus ON cells, particularly in dorsal lateral geniculate nucleus. Using a network-based retino-geniculate model, we confirmed stronger antagonism and temporal transience for OFF-cell post-stimulus rebound responses. A V1 population model demonstrated that both strength and duration asymmetries can be propagated to downstream cortical areas. Our results demonstrate how size-dependent antagonism impacts both the neuronal post-stimulus response and the resulting afterimage percepts, thereby supporting the idea of perceptual RFs reflecting the underlying neuronal RF organization of single cells.SIGNIFICANCE STATEMENT Visual illusions occur when sensory inputs and perceptual outcomes do not match, and provide a valuable tool to understand transformations from neural to perceptual responses. A classic example are negative afterimages that remain visible after a stimulus is removed from view. Such perceptions are linked to responses in early visual neurons, yet the details remain poorly understood. Combining human psychophysics, neurophysiological recordings in cats and retino-thalamo-cortical computational modeling, our study reveals how stimulus size and the receptive-field structure of subcortical ON and OFF cells contributes to the parallel asymmetries between neural and perceptual responses to bright versus dark afterimages. Thus, this work provides a deeper link from the underlying neural mechanisms to the resultant perceptual outcomes.

Humans are more sensitive to luminance decrements than increments, as evidenced by lower thresholds and shorter latencies for dark stimuli. This asymmetry is consistent with results of neurophysiological recordings in dorsal lateral geniculate nucleus (dLGN) and primary visual cortex (V1) of cat and monkey. Specifically, V1 population responses demonstrate that darks elicit higher levels of activation than brights, and the latency of OFF responses in dLGN and V1 is shorter than that of ON responses. The removal of a dark or bright disc often generates the perception of a negative afterimage, and here we ask whether there also exist asymmetries for negative afterimages elicited by dark and bright discs. If so, do the poststimulus responses of subcortical ON and OFF cells parallel such afterimage asymmetries? To test these hypotheses, we performed psychophysical experiments in humans and single-cell/S-potential recordings in cat dLGN. Psychophysically, we found that bright afterimages elicited by luminance decrements are stronger and last longer than dark afterimages elicited by luminance increments of equal sizes. Neurophysiologically, we found that ON cells responded to the removal of a dark disc with higher firing rates that were maintained for longer than OFF cells to the removal of a bright disc. The ON and OFF cell asymmetry was most pronounced at long stimulus durations in the dLGN. We conclude that subcortical response strength differences between ON and OFF channels parallel the asymmetries between bright and dark negative afterimages, further supporting a subcortical origin of bright and dark afterimage perception.SIGNIFICANCE STATEMENT Afterimages are physiological aftereffects following stimulation of the eye, the study of which helps us to understand how our visual brain generates visual perception in the absence of physical stimuli. We report, for the first time to our knowledge, asymmetries between bright and dark negative afterimages elicited by luminance decrements and increments, respectively. Bright afterimages are stronger and last longer than dark afterimages. Subcortical neuronal recordings of poststimulus responses of ON and OFF cells reveal similar asymmetries with respect to response strength and duration. Our results suggest that subcortical differences between ON and OFF channels help explain intensity and duration asymmetries between bright and dark afterimages, supporting the notion of a subcortical origin of bright and dark afterimages.

Ribonucleoprotein (RNP) granules are membraneless liquid condensates that dynamically form,dissolve, and mature into a gel-like state in response to a changing cellular environment. RNP condensation islargely governed by promiscuous attractive inter-chain interactions mediated by low-complexity domains(LCDs). Using an archetypal disordered RNP, fused in sarcoma (FUS), here we study how molecular crowdingimpacts the RNP liquid condensation. We observe that the liquid⁻liquid coexistence boundary of FUS islowered by polymer crowders, consistent with an excluded volume model. With increasing bulk crowderconcentration, the RNP partition increases and the diffusion rate decreases in the condensed phase.Furthermore, we show that RNP condensates undergo substantial hardening wherein protein-dense dropletstransition from viscous fluid to viscoelastic gel-like states in a crowder concentration-dependent manner.Utilizing two distinct LCDs that broadly represent commonly occurring sequence motifs driving RNP phasetransitions, we reveal that the impact of crowding is largely independent of LCD charge and sequence patterns.These results are consistent with a thermodynamic model of crowder-mediated depletion interaction, whichsuggests that inter-RNP attraction is enhanced by molecular crowding. The depletion force is likely to play akey role in tuning the physical properties of RNP condensates within the crowded cellular space.

In this work we studied the folding process of the hybrid-1 type human telomeric DNA G-quadruplex with solvent and K(+) ions explicitly modeled. Enabled by the powerful bias-exchange metadynamics and large-scale conventional molecular dynamic simulations, the free energy landscape of this G-DNA was obtained for the first time and four folding intermediates were identified, including a triplex and a basically formed quadruplex. The simulations also provided atomistic pictures for the structures and cation binding patterns of the intermediates. The results showed that the structure formation and cation binding are cooperative and mutually supporting each other. The syn/anti reorientation dynamics of the intermediates was also investigated. It was found that the nucleotides usually take correct syn/anti configurations when they form native and stable hydrogen bonds with the others, while fluctuating between two configurations when they do not. Misfolded intermediates with wrong syn/anti configurations were observed in the early intermediates but not in the later ones. Based on the simulations, we also discussed the roles of the non-native interactions. Besides, the formation process of the parallel conformation in the first two G-repeats and the associated reversal loop were studied. Based on the above results, we proposed a folding pathway for the hybrid-1 type G-quadruplex with atomistic details, which is new and more complete compared with previous ones. The knowledge gained for this type of G-DNA may provide a general insight for the folding of the other G-quadruplexes.

The catalytic cycle of the enzyme adenylate kinase involves large conformational motions between open and closed states. A previous single-molecule experiment showed that substrate binding tends to accelerate both the opening and the closing rates and that a single turnover event often involves multiple rounds of conformational switching. In this work, we showed that the repeated conformational transitions of adenylate kinase are essential for the relaxation of incorrectly bound substrates into the catalytically competent conformation by combining all-atom and coarse-grained molecular simulations. In addition, free energy calculations based on all-atom and coarse-grained models demonstrated that the enzyme with incorrectly bound substrates has much a lower free energy barrier for domain opening compared to that with the correct substrate conformation, which may explain the the acceleration of the domain opening rate by substrate binding. The results of this work provide mechanistic understanding to previous experimental observations and shed light onto the interplay between conformational dynamics and enzyme catalysis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses a spike protein (S-protein) to recognize the receptor protein ACE2 of human cells and initiate infection, during which the conformational transition of the S-protein from inactive (down) state to active (up) state is one of the key molecular events determining the infectivity but the underlying mechanism remains poorly understood. In this work, we investigated the activation pathways and free energy landscape of the S-protein of SARS-CoV-2 and compared with those of the closely related counterpart SARS-CoV using molecular dynamics simulations. Our results revealed a large difference between the activation pathways of the two S-proteins. The transition from inactive to an active state for the S-protein of SARS-CoV-2 is more cooperative, involving simultaneous disruptions of several key interfacial hydrogen bonds, and the transition encounters a much higher free energy barrier. In addition, the conformational equilibrium of the SARS-CoV-2 S-protein is more biased to the inactive state compared to that of the SARS-CoV S-protein, suggesting the transient feature of the active state before binding to the receptor protein of the host cell. The key interactions contributing to the difference of the activation pathways and free energy landscapes were discussed. The results provide insights into the molecular mechanism involved in the initial stage of the SARS-CoV-2 infection.

The knowledge of the tertiary structure of RNA loops is important for understanding their functions. In this work we develop an efficient approach named RNApps, specifically designed for predicting the tertiary structure of RNA loops, including hairpin loops, internal loops, and multi-way junction loops. It includes a probabilistic coarse-grained RNA model, an all-atom statistical energy function, a sequential Monte Carlo growth algorithm, and a simulated annealing procedure. The approach is tested with a dataset including nine RNA loops, a 23S ribosomal RNA, and a large dataset containing 876 RNAs. The performance is evaluated and compared with a homology modeling based predictor and an ab initio predictor. It is found that RNApps has comparable performance with the former one and outdoes the latter in terms of structure predictions. The approach holds great promise for accurate and efficient RNA tertiary structure prediction.

The 14-3-3σ proteins are a family of ubiquitous conserved eukaryotic regulatory molecules involved in the regulation of mitogenic signal transduction, apoptotic cell death, and cell cycle control. A lot of small-molecule inhibitors have been identified for 14-3-3 protein-protein interactions (PPIs). In this work, we carried out molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method to study the binding mechanism between a 14-3-3σ protein and its eight inhibitors. The ranking order of our calculated binding free energies is in agreement with the experimental results. We found that the binding free energies are mainly from interactions between the phosphate group of the inhibitors and the hydrophilic residues. To improve the binding free energy of Rx group, we designed the inhibitor R9 with group R9 = 4-hydroxypheny. However, we also found that the binding free energy of inhibitor R9 is smaller than that of inhibitor R1. By further using the steer molecular dynamics (SMD) simulations, we identified a new hydrogen bond between the inhibitor R8 and residue Arg64 in the pulling paths. The information obtained from this study may be valuable for future rational design of novel inhibitors, and provide better structural understanding of inhibitor binding to 14-3-3σ proteins.

Quality assessment is essential for the computational prediction and design of RNA tertiary structures. To date, several knowledge-based statistical potentials have been proposed and proved to be effective in identifying native and near-native RNA structures. All these potentials are based on the inverse Boltzmann formula, while differing in the choice of the geometrical descriptor, reference state, and training dataset. Via an approach that diverges completely from the conventional statistical potentials, our work explored the power of a 3D convolutional neural network (CNN)-based approach as a quality evaluator for RNA 3D structures, which used a 3D grid representation of the structure as input without extracting features manually. The RNA structures were evaluated by examining each nucleotide, so our method can also provide local quality assessment. Two sets of training samples were built. The first one included 1 million samples generated by high-temperature molecular dynamics (MD) simulations and the second one included 1 million samples generated by Monte Carlo (MC) structure prediction. Both MD and MC procedures were performed for a non-redundant set of 414 RNAs. For two training datasets (one including only MD training samples and the other including both MD and MC training samples), we trained two neural networks, named RNA3DCNN_MD and RNA3DCNN_MDMC, respectively. The former is suitable for assessing near-native structures, while the latter is suitable for assessing structures covering large structural space. We tested the performance of our method and made comparisons with four other traditional scoring functions. On two of three test datasets, our method performed similarly to the state-of-the-art traditional scoring function, and on the third test dataset, our method was far superior to other scoring functions. Our method can be downloaded from https://github.com/lijunRNA/RNA3DCNN.

Allosteric communication between distant parts of proteins controls many cellular functions, in which metal ions are widely utilized as effectors to trigger the allosteric cascade. Due to the involvement of strong coordination interactions, the energy landscape dictating the metal ion binding is intrinsically rugged. How metal ions achieve fast binding by overcoming the landscape ruggedness and thereby efficiently mediate protein allostery is elusive. By performing molecular dynamics simulations for the Ca2+ binding mediated allostery of the calmodulin (CaM) domains, each containing two Ca2+ binding helix-loop-helix motifs (EF-hands), we revealed the key role of water-bridged interactions in Ca2+ binding and protein allostery. The bridging water molecules between Ca2+ and binding residue reduces the ruggedness of ligand exchange landscape by acting as a lubricant, facilitating the Ca2+ coupled protein allostery. Calcium-induced rotation of the helices in the EF-hands, with the hydrophobic core serving as the pivot, leads to exposure of hydrophobic sites for target binding. Intriguingly, despite being structurally similar, the response of the two symmetrically arranged EF-hands upon Ca2+ binding is asymmetric. Breakage of symmetry is needed for efficient allosteric communication between the EF-hands. The key roles that water molecules play in driving allosteric transitions are likely to be general in other metal ion mediated protein allostery.

Many load-bearing tissues, such as muscles and cartilages, show high elasticity, toughness, and fast recovery. However, combining these mechanical properties in the same synthetic biomaterials is fundamentally challenging. Here, we show that strong, tough, and fast-recovery hydrogels can be engineered using cross-linkers involving cooperative dynamic interactions. We designed a histidine-rich decapeptide containing two tandem zinc binding motifs. Because of allosteric structural change-induced cooperative binding, this decapeptide had a higher thermodynamic stability, stronger binding strength, and faster binding rate than single binding motifs or isolated ligands. The engineered hybrid network hydrogels containing the peptide-zinc complex exhibit a break stress of ~3.0 MPa, toughness of ~4.0 MJ m-3, and fast recovery in seconds. We expect that they can function effectively as scaffolds for load-bearing tissue engineering and as building blocks for soft robotics. Our results provide a general route to tune the mechanical and dynamic properties of hydrogels at the molecular level.

Mussels can strongly adhere to hydrophilic minerals in sea habitats by secreting adhesive proteins. The adhesion ability of these proteins is often attributed to the presence of Dopa derived from posttranslational modification of Tyr, whereas the contribution of structural feature is overlooked. It remains largely unknown how adhesive proteins overcome the surface-bound water layer to establish underwater adhesion. Here, we use molecular dynamics simulations to probe the conformations of adhesive protein Pvfp-5β and its salt-tolerant underwater adhesion on superhydrophilic mica. Dopa and positively charged basic residues form pairs, in this intrinsically disordered protein, and these residue pairs can lead to firm surface binding. Our simulations further suggest that the unmodified Tyr shows similar functions on surface adhesion by forming pairing structure with a positively charged residue. We confirm the presence of these residue pairs and verify the strong binding ability of unmodified proteins using nuclear magnetic resonance spectroscopy and lap shear tests.

A variety of micro-tweezers techniques, such as optical tweezers, magnetic tweezers, and dielectrophoresis technique, have been applied intensively in precise characterization of micro/nanoparticles and bio-molecules. They have contributed remarkably in better understanding of working mechanisms of individual sub-cell organelles, proteins, and DNA. In this paper, we present a controllable electrostatic device embedded in a microchannel, which is capable of driving, trapping, and releasing charged micro-particles suspended in microfluid, demonstrating the basic concepts of electrostatic tweezers. Such a device is scalable to smaller size and offers an alternative to currently used micro-tweezers for application in sorting, selecting, manipulating, and analyzing individual micro/nanoparticles. Furthermore, the system offers the potential in being combined with dielectrophoresis and other techniques to create hybrid micro-manipulation systems.

Cancer stem cell (CSC) or tumor initiating cell (TIC) plays an important role in tumor progression and metastasis. Biophysical forces in tumor microenvironment have an important effect on tumor formation and development. In this study, the potential effect of matrix stiffness on the biological characteristics of human head and neck squamous cell carcinoma (HNSCC) TICs, especially the enrichment of HNSCC TICs, was investigated under three-dimensional (3D) culture conditions by means of alginate gel (ALG) beads with different matrix stiffnesses. ALG beads with soft (21 kPa), moderate (70 kPa) and hard (105 kPa) stiffness were generated by changing alginate concentration. It was found that significant HNSCC TIC enrichment was achieved in the ALG beads with moderate matrix stiffness (70 kPa). The gene expression of stemness markers Oct3/4 and Nanog, TIC markers CD44 and ABCG2 was enhanced in cells under this moderate (70 kPa) stiffness. HNSCC TIC proportion was also highly enriched under moderate matrix stiffness, accompanying with higher tumorigenicity, metastatic ability and drug resistance. And it was also found that the possible molecular mechanism underlying the regulated TIC properties by matrix stiffness under 3D culture conditions was significantly different from 2D culture condition. Therefore, the results achieved in this study indicated that 3D biophysical microenvironment had an important effect on TIC characteristics and alginate-based biomimetic scaffolds could be utilized as a proper platform to investigate the interaction between tumor cells and 3D microenvironment.

The interactions between chiral molecules and cell membranes have attracted more and more attention in recent decades, due to their importance in molecular science and medical applications. It is observed that some peptides composed of different chiral amino acids may have distinct interactions with a membrane. How does the membrane exhibit a selective behavior related to the chirality of the peptides? Microscopically, the interactions between the peptides and the membrane are poorly understood. In this work, we study the interactions between an amphipathic peptide (C6) and POPC membrane with simulations. The kinetics and thermodynamics of peptide enantiomers during the adsorption to the membrane are characterized with direct simulations and umbrella sampling. It is observed that there are slow kinetics for the peptide composed of D-type amino acids. Along the observed pathways, the free energy landscapes are determined with umbrella sampling techniques. A free-energy barrier for the peptide composed of D-amino acids is observed, which is consistent with the kinetic observations. The results indicate the concurrent adsorption and rotation of the peptide helix. The local interactions between the peptides and the membrane are examined in detail, including the contact interactions between the peptides and the membrane, and the distributions of the lipids around the peptide. There are observable differences of the local interactions for the cases related to different peptide enantiomers. These results further demonstrate the importance of the rotation of peptide helix during the adsorption. More interestingly, all these kinetic differences between peptide enantiomers can be explained based on the conformations of the residue Trp and interactions between Trp and lipid molecules. These results give us a molecular understanding of the mechanism of the chirality-dependent peptide-membrane interactions, and may provide clues to designing systems which are sensitive to the chirality of membranes.

Substrate inhibition, whereby enzymatic activity decreases with excess substrate after reaching a maximum turnover rate, is among the most elusive phenomena in enzymatic catalysis. Here, based on a dynamic energy landscape model, we investigate the underlying mechanism by performing molecular simulations and frustration analysis for a model enzyme adenylate kinase (AdK), which catalyzes the phosphoryl transfer reaction ATP + AMP ⇋ ADP + ADP. Intriguingly, these reveal a kinetic repartitioning mechanism of substrate inhibition, whereby excess substrate AMP suppresses the population of an energetically frustrated, but kinetically activated, catalytic pathway going through a substrate (ATP)-product (ADP) cobound complex with steric incompatibility. Such a frustrated pathway plays a crucial role in facilitating the bottleneck product ADP release, and its suppression by excess substrate AMP leads to a slow down of product release and overall turnover. The simulation results directly demonstrate that substrate inhibition arises from the rate-limiting product-release step, instead of the steps for populating the catalytically competent complex as often suggested in previous works. Furthermore, there is a tight interplay between the enzyme conformational equilibrium and the extent of substrate inhibition. Mutations biasing to more closed conformations tend to enhance substrate inhibition. We also characterized the key features of single-molecule enzyme kinetics with substrate inhibition effect. We propose that the above molecular mechanism of substrate inhibition may be relevant to other multisubstrate enzymes in which product release is the bottleneck step.

How RNA sequences fold to specific tertiary structures is one of the key problems for understanding their dynamics and functions. Here, we study the folding process of an H-type RNA pseudoknot by performing a large-scale all-atom MD simulation and bias-exchange metadynamics. The folding free energy landscapes are obtained and several folding intermediates are identified. It is suggested that the folding occurs via multiple mechanisms, including a step-wise mechanism starting either from the first helix or the second, and a cooperative mechanism with both helices forming simultaneously. Despite of the multiple mechanism nature, the ensemble folding kinetics estimated from a Markov state model is single-exponential. It is also found that the correlation between folding and binding of metal ions is significant, and the bound ions mediate long-range interactions in the intermediate structures. Non-native interactions are found to be dominant in the unfolded state and also present in some intermediates, possibly hinder the folding process of the RNA.

Gram-positive bacteria can resist large mechanical perturbations during their invasion and colonization by secreting various surface proteins with intramolecular isopeptide or ester bonds. Compared to isopeptide bonds, ester bonds are prone to hydrolysis. It remains elusive whether ester bonds can completely block mechanical extension similarly to isopeptide bonds, or whether ester bonds dissipate mechanical energy by bond rupture. Here, we show that an ester-bond containing stalk domain of Cpe0147 is inextensible even at forces > 2 nN. The ester bond locks the structure to a partially unfolded conformation, in which the ester bond remains largely water inaccessible. This allows the ester bond to withstand considerable mechanical forces and in turn prevent complete protein unfolding. However, the protecting effect might be reduced at non-physiological basic pHs or low calcium concentrations due to destabilizing the protein structures. Inspired by this design principle, we engineer a disulfide mutant resistant to mechanical unfolding under reducing conditions.

Force is increasingly recognized as an important element in controlling biological processes. Forces can deform native protein conformations leading to protein-specific effects. Protein-protein binding affinities may be decreased, or novel protein-protein interaction sites may be revealed, on mechanically stressing one or more components. Here we demonstrate that the calcium-binding affinity of the sixth domain of the actin-binding protein gelsolin (G6) can be enhanced by mechanical force. Our kinetic model suggests that the calcium-binding affinity of G6 increases exponentially with force, up to the point of G6 unfolding. This implies that gelsolin may be activated at lower calcium ion levels when subjected to tensile forces. The demonstration that cation-protein binding affinities can be force-dependent provides a new understanding of the complex behaviour of cation-regulated proteins in stressful cellular environments, such as those found in the cytoskeleton-rich leading edge and at cell adhesions.

Both grid-like firing fields and theta oscillation are hallmarks of grid cells in the mammalian brain. While bump attractor dynamics have generally been recognized as the substrate for grid firing fields, how theta oscillation arises and interacts with persistent activity in a cortical circuit remains obscure. Here, we report that the theta oscillation intrinsically emerges in a continuous attractor network composed of principal neurons and interneurons. Periodic bump attractors and the theta rhythm stably coexist in both cell types due to the division of labor among interneurons via structured synaptic connectivity between principal cells and interneurons. The slow dynamics of NMDAR-mediated synaptic currents support the persistency of bump attractors and restrict the oscillation frequency in the theta band. The spikes of neurons within bump attractors are phase locked to a proxy of local field potential. The current work provides a network-level mechanism that orchestrates the bump attractor dynamics and theta rhythmicity.