Supramolecular organization and dynamics of mannosylated phosphatidylinositol lipids in the mycobacterial plasma membrane.

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), a disease that claims ~1.6 million lives annually. The current treatment regime is long and expensive, and missed doses contribute to drug resistance. Therefore, development of new anti-TB drugs remains one of the highest public health priorities. Mtb has evolved a complex cell envelope that represents a formidable barrier to antibiotics. The Mtb cell envelop consists of four distinct layers enriched for Mtb specific lipids and glycans. Although the outer membrane, comprised of mycolic acid esters, has been extensively studied, less is known about the plasma membrane, which also plays a critical role in impacting antibiotic efficacy. The Mtb plasma membrane has a unique lipid composition, with mannosylated phosphatidylinositol lipids (phosphatidyl-myoinositol mannosides, PIMs) comprising more than 50% of the lipids. However, the role of PIMs in the structure and function of the membrane remains elusive. Here, we used multiscale molecular dynamics (MD) simulations to understand the structure-function relationship of the PIM lipid family and decipher how they self-organize to shape the biophysical properties of mycobacterial plasma membranes. We assess both symmetric and asymmetric assemblies of the Mtb plasma membrane and compare this with residue distributions of Mtb integral membrane protein structures. To further validate the model, we tested known anti-TB drugs and demonstrated that our models agree with experimental results. Thus, our work sheds new light on the organization of the mycobacterial plasma membrane. This paves the way for future studies on antibiotic development and understanding Mtb membrane protein function.

Pectin Nanoporous Structures Prepared via Salt-Induced Phase Separation and Ambient Azeotropic Evaporation Processes.

Polysaccharide nanoporous structures are suitable for various applications, ranging from biomedical scaffolds to adsorption materials, owing to their biocompatibility and large surface areas. Pectin, in particular, can create 3D nanoporous structures in aqueous solutions by binding with calcium cations and creating nanopores by phase separation; this process involves forming hydrogen bonds between alcohols and pectin chains in water and alcohol mixtures and the resulting penetration of alcohols into calcium-bound pectin gels. However, owing to the dehydration and condensation of polysaccharide chains during drying, it has proven to be challenging to maintain the 3D nanoporous structure without using a freeze-drying process or supercritical fluid. Herein, we report a facile method for creating polysaccharide-based xerogels, involving the co-evaporation of water with a nonsolvent (e.g., a low-molecular-weight hydrophobic alcohol such as isopropyl or n-propyl alcohol) at ambient conditions. Experiments and coarse-grained molecular dynamics simulations confirmed that salt-induced phase separation and hydrogen bonding between hydrophobic alcohols and pectin chains were the dominant processes in mixtures of pectin, water, and hydrophobic alcohols. Furthermore, the azeotropic evaporation of water and alcohol mixed in approximately 1:1 molar ratios was maintained during the natural drying process under ambient conditions, preventing the hydration and aggregation of the hydrophilic pectin chains. These results introduce a simple and convenient process to produce 3D polysaccharide xerogels under ambient conditions.

Structure, Dynamics, and Interactions of GPI-Anchored Human Glypican-1 with Heparan Sulfates in a Membrane.

Glypican-1 and its heparan sulfate (HS) chains play important roles in modulating many biological processes including growth factor signaling. Glypican-1 is bound to a membrane surface via a glycosylphosphatidylinositol (GPI)-anchor. In this study, we used all-atom molecular modeling and simulation to explore the structure, dynamics, and interactions of GPI-anchored glypican-1, three HS chains, membranes, and ions. The folded glypican-1 core structure is stable, but has substantial degrees of freedom in terms of movement and orientation with respect to the membrane due to the long unstructured C-terminal region linking the core to the GPI-anchor. With unique structural features depending on the extent of sulfation, high flexibility of HS chains can promote multi-site interactions with surrounding molecules near and above the membrane. This study is a first step toward all-atom molecular modeling and simulation of the glycocalyx, as well as its modulation of interactions between growth factors and their receptors.

CHARMM-GUI Membrane Builder for Lipid Nanoparticles with Ionizable Cationic Lipids and PEGylated Lipids.

A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, messenger RNA, and small interfering RNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies, albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder's capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol % PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus (KA) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and the head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for rational LNP design.

High-Speed Lateral Flow Strategy for a Fast Biosensing with an Improved Selectivity and Binding Affinity.

We report a high-speed lateral flow strategy for a fast biosensing with an improved selectivity and binding affinity even under harsh conditions. In this strategy, biosensors were fixed at a location away from the center of a round shape disk, and the disk was rotated to create the lateral flow of a target solution on the biosensors during the sensing measurements. Experimental results using the strategy showed high reaction speeds, high binding affinity, and low nonspecific adsorptions of target molecules to biosensors. Furthermore, binding affinity between target molecules and sensing molecules was enhanced even in harsh conditions such as low pH and low ionic strength conditions. These results show that the strategy can improve the performance of conventional biosensors by generating high-speed lateral flows on a biosensor surface. Therefore, our strategy can be utilized as a simple but powerful tool for versatile bio and medical applications.

CHARMM-GUI Multicomponent Assembler for modeling and simulation of complex multicomponent systems.

Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. In this work, we demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to study complex interactions between small molecules, biomacromolecules, polymers, and nanomaterials.

Anillin-related Mid1 as an adaptive and multimodal contractile ring anchoring protein: A simulation study.

Cytokinesis of animal and fungi cells depends crucially on the anillin scaffold proteins. Fission yeast anillin-related Mid1 anchors cytokinetic ring precursor nodes to the membrane. However, it is unclear if both of its Pleckstrin Homology (PH) and C2 C-terminal domains bind to the membrane as monomers or dimers, and if one domain plays a dominant role. We studied Mid1 membrane binding with all-atom molecular dynamics near a membrane with yeast-like lipid composition. In simulations with the full C terminal region started away from the membrane, Mid1 binds through the disordered L3 loop of C2 in a vertical orientation, with the PH away from the membrane. However, a configuration with both C2 and PH initially bound to the membrane remains associated with the membrane. Simulations of C2-PH dimers show extensive asymmetric membrane contacts. These multiple modes of binding may reflect Mid1's multiple interactions with membranes, node proteins, and ability to sustain mechanical forces.

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications.

Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.

CHARMM-GUI Multicomponent Assembler for Modeling and Simulation of Complex Multicomponent Systems.

Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. We demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to facilitate innovative studies of complex interactions between small (organic and inorganic) molecules, biomacromolecules, polymers, and nanomaterials.

Anillin Related Mid1 as an Adaptive and Multimodal Contractile Ring Anchoring Protein: A Simulation Study.

The organization of the cytokinetic ring at the cell equator of dividing animal and fungi cells depends crucially on the anillin scaffold proteins. In fission yeast, anillin related Mid1 binds to the plasma membrane and helps anchor and organize a medial broad band of cytokinetic nodes, which are the precursors of the contractile ring. Similar to other anillins, Mid1 contains a C terminal globular domain with two potential regions for membrane binding, the Pleckstrin Homology (PH) and C2 domains, and an N terminal intrinsically disordered region that is strongly regulated by phosphorylation. Previous studies have shown that both PH and C2 domains can associate with the membrane, preferring phosphatidylinositol-(4,5)-bisphosphate (PIP 2 ) lipids. However, it is unclear if they can simultaneously bind to the membrane in a way that allows dimerization or oligomerization of Mid1, and if one domain plays a dominant role. To elucidate Mid1's membrane binding mechanism, we used the available structural information of the C terminal region of Mid1 in all-atom molecular dynamics (MD) near a membrane with a lipid composition based on experimental measurements (including PIP 2 lipids). The disordered L3 loop of C2, as well as the PH domain, separately bind the membrane through charged lipid contacts. In simulations with the full C terminal region started away from the membrane, Mid1 binds through the L3 loop and is stabilized in a vertical orientation with the PH domain away from the membrane. However, a configuration with both C2 and PH initially bound to the membrane remains associated with the membrane. These multiple modes of binding may reflect Mid1's multiple interactions with membranes and other node proteins, and ability to sustain mechanical forces.

Structural basis for Y2 receptor-mediated neuropeptide Y and peptide YY signaling.

Neuropeptide Y (NPY) and its receptors are expressed in various human tissues including the brain where they regulate appetite and emotion. Upon NPY stimulation, the neuropeptide Y1 and Y2 receptors (Y1R and Y2R, respectively) activate GI signaling, but their physiological responses to food intake are different. In addition, deletion of the two N-terminal amino acids of peptide YY (PYY(3-36)), the endogenous form found in circulation, can stimulate Y2R but not Y1R, suggesting that Y1R and Y2R may have distinct ligand-binding modes. Here, we report the cryo-electron microscopy structures of the PYY(3-36)‒Y2R‒Gi and NPY‒Y2R‒Gi complexes. Using cell-based assays, molecular dynamics simulations, and structural analysis, we revealed the molecular basis of the exclusive binding of PYY(3-36) to Y2R. Furthermore, we demonstrated that Y2R favors G protein signaling over ß-arrestin signaling upon activation, whereas Y1R does not show a preference between these two pathways.

Suppression of Lung Cancer Malignancy by Micellized siRNA through Cell Cycle Arrest.

UBA6-specific E2 conjugation enzyme 1 (USE1) is frequently overexpressed in lung cancer patients. Moreover, the critical role of USE1 in the progression of human lung cancer is also indicated. As the next step, the authors aim to develop USE1-targeted therapeutic agents based on RNA interference (RNAi). In this study, a lipid-modified DNA carrier, namely U4T, which consists of four consecutive dodec-1-ynyluracil (U) nucleobases to increase the cell permeability of siRNA targeting of USE1 is introduced. The U4Ts aggregate to form micelles, and the USE1-silencing siRNA-incorporated soft spherical nucleic acid aggregate (siSNA) can be created simply through base-pairing with siRNA. Treatment with siSNA is effective in suppressing tumor growth in vivo as well as cell proliferation, migration, and invasion of lung cancer cells. Furthermore, siSNA inhibited tumor cell growth by inducing cell cycle arrest in the G1 phase and apoptosis. Thus, the anti-tumor efficacy of siSNA in lung cancer cell lines and that siSNA possesses effective cell-penetrating ability without using cationic transfection moieties are confirmed. Collectively, these results suggest that siSNA can be applied to the clinical application of RNAi-based therapeutics for lung cancer treatment.

Accurate Force Fields for Atomistic Simulations of Oxides, Hydroxides, and Organic Hybrid Materials up to the Micrometer Scale.

The simulation of metals, oxides, and hydroxides can accelerate the design of therapeutics, alloys, catalysts, cement-based materials, ceramics, bioinspired composites, and glasses. Here we introduce the INTERFACE force field (IFF) and surface models for α-Al2O3, α-Cr2O3, α-Fe2O3, NiO, CaO, MgO, ß-Ca(OH)2, ß-Mg(OH)2, and ß-Ni(OH)2. The force field parameters are nonbonded, including atomic charges for Coulomb interactions, Lennard-Jones (LJ) potentials for van der Waals interactions with 12-6 and 9-6 options, and harmonic bond stretching for hydroxide ions. The models outperform DFT calculations and earlier atomistic models (Pedone, ReaxFF, UFF, CLAYFF) up to 2 orders of magnitude in reliability, compatibility, and interpretability due to a quantitative representation of chemical bonding consistent with other compounds across the periodic table and curated experimental data for validation. The IFF models exhibit average deviations of 0.2% in lattice parameters, <10% in surface energies (to the extent known), and 6% in bulk moduli relative to experiments. The parameters and models can be used with existing parameters for solvents, inorganic compounds, organic compounds, biomolecules, and polymers in IFF, CHARMM, CVFF, AMBER, OPLS-AA, PCFF, and COMPASS, to simulate bulk oxides, hydroxides, electrolyte interfaces, and multiphase, biological, and organic hybrid materials at length scales from atoms to micrometers. The nonbonded character of the models also enables the analysis of mixed oxides, glasses, and certain chemical reactions, and well-performing nonbonded models for silica phases, SiO2, are introduced. Automated model building is available in the CHARMM-GUI Nanomaterial Modeler. We illustrate applications of the models to predict the structure of mixed oxides, and energy barriers of ion migration, as well as binding energies of water and organic molecules in outstanding agreement with experimental data and calculations at the CCSD(T) level. Examples of model building for hydrated, pH-sensitive oxide surfaces to simulate solid-electrolyte interfaces are discussed.

CHARMM-GUI Nanomaterial Modeler for Modeling and Simulation of Nanomaterial Systems.

Molecular modeling and simulation are invaluable tools for nanoscience that predict mechanical, physicochemical, and thermodynamic properties of nanomaterials and provide molecular-level insight into underlying mechanisms. However, building nanomaterial-containing systems remains challenging due to the lack of reliable and integrated cyberinfrastructures. Here we present Nanomaterial Modeler in CHARMM-GUI, a web-based cyberinfrastructure that provides an automated process to generate various nanomaterial models, associated topologies, and configuration files to perform state-of-the-art molecular dynamics simulations using most simulation packages. The nanomaterial models are based on the interface force field, one of the most reliable force fields (FFs). The transferability of nanomaterial models among the simulation programs was assessed by single-point energy calculations, which yielded 0.01% relative absolute energy differences for various surface models and equilibrium nanoparticle shapes. Three widely used Lennard-Jones (LJ) cutoff methods are employed to evaluate the compatibility of nanomaterial models with respect to conventional biomolecular FFs: simple truncation at r = 12 Å (12 cutoff), force-based switching over 10 to 12 Å (10-12 fsw), and LJ particle mesh Ewald with no cutoff (LJPME). The FF parameters with these LJ cutoff methods are extensively validated by reproducing structural, interfacial, and mechanical properties. We find that the computed density and surface energies are in good agreement with reported experimental results, although the simulation results increase in the following order: 10-12 fsw <12 cutoff < LJPME. Nanomaterials in which LJ interactions are a major component show relatively higher deviations (up to 4% in density and 8% in surface energy differences) compared with the experiment. Nanomaterial Modeler's capability is also demonstrated by generating complex systems of nanomaterial-biomolecule and nanomaterial-polymer interfaces with a combination of existing CHARMM-GUI modules. We hope that Nanomaterial Modeler can be used to carry out innovative nanomaterial modeling and simulations to acquire insight into the structure, dynamics, and underlying mechanisms of complex nanomaterial-containing systems.

Structural basis of neuropeptide Y signaling through Y1 receptor.

Neuropeptide Y (NPY) is highly abundant in the brain and involved in various physiological processes related to food intake and anxiety, as well as human diseases such as obesity and cancer. However, the molecular details of the interactions between NPY and its receptors are poorly understood. Here, we report a cryo-electron microscopy structure of the NPY-bound neuropeptide Y1 receptor (Y1R) in complex with Gi1 protein. The NPY C-terminal segment forming the extended conformation binds deep into the Y1R transmembrane core, where the amidated C-terminal residue Y36 of NPY is located at the base of the ligand-binding pocket. Furthermore, the helical region and two N-terminal residues of NPY interact with Y1R extracellular loops, contributing to the high affinity of NPY for Y1R. The structural analysis of NPY-bound Y1R and mutagenesis studies provide molecular insights into the activation mechanism of Y1R upon NPY binding.

CHARMM-GUI Membrane Builder for Lipid Nanoparticles with Ionizable Cationic Lipids and PEGylated Lipids.

A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, mRNA, and siRNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes a rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder's capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol% PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus (KA) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for a rational LNP design.

CHARMM-GUI Polymer Builder for Modeling and Simulation of Synthetic Polymers.

Molecular modeling and simulations are invaluable tools for polymer science and engineering, which predict physicochemical properties of polymers and provide molecular-level insight into the underlying mechanisms. However, building realistic polymer systems is challenging and requires considerable experience because of great variations in structures as well as length and time scales. This work describes Polymer Builder in CHARMM-GUI (http://www.charmm-gui.org/input/polymer), a web-based infrastructure that provides a generalized and automated process to build a relaxed polymer system. Polymer Builder not only provides versatile modeling methods to build complex polymer structures, but also generates realistic polymer melt and solution systems through the built-in coarse-grained model and all-atom replacement. The coarse-grained model parametrization is generalized and extensively validated with various experimental data and all-atom simulations. In addition, the capability of Polymer Builder for generating relaxed polymer systems is demonstrated by density calculations of 34 homopolymer melt systems, characteristic ratio calculations of 170 homopolymer melt systems, a morphology diagram of poly(styrene-b-methyl methacrylate) block copolymers, and self-assembly behavior of amphiphilic poly(ethylene oxide-b-ethylethane) block copolymers in water. We hope that Polymer Builder is useful to carry out innovative and novel polymer modeling and simulation research to acquire insight into structures, dynamics, and underlying mechanisms of complex polymer-containing systems.

Structure, Dynamics, Receptor Binding, and Antibody Binding of the Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein in a Viral Membrane.

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2) and is considered the major target for drug and vaccine development. We previously built fully glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of the receptor-binding domain (RBD) and different templates for the stalk region. In this work, multiple µs-long all-atom molecular dynamics simulations were performed to provide deeper insights into the structure and dynamics of S protein and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of the RBD and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody-glycan clash analysis instead of commonly used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibodies. Overall, our observations offer structural and dynamic insights into the SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 (ACE2) binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work, and performed all-atom molecular dynamics simulations to get insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes, and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.