A5022718242- SARS-CoV-2 and COVID-19 Research
- Spectroscopy and Quantum Chemical Studies
- Machine Learning in Materials Science
- Immunotherapy and Immune Responses
- vaccines and immunoinformatics approaches
- Bone Tissue Engineering Materials
- Nonlinear Dynamics and Pattern Formation
- Venomous Animal Envenomation and Studies
- Evolution and Genetic Dynamics
- Evolutionary Game Theory and Cooperation
- Advanced Thermodynamics and Statistical Mechanics
- Quantum chaos and dynamical systems
- Calpain Protease Function and Regulation
- Protein Structure and Dynamics
- Nuclear Structure and Function
- Microbial Fuel Cells and Bioremediation
- Advancements in Transdermal Drug Delivery
- Graphene and Nanomaterials Applications
- Electrostatics and Colloid Interactions
- Quantum, superfluid, helium dynamics
- HIV Research and Treatment
- Advanced biosensing and bioanalysis techniques
- Advanced Nanomaterials in Catalysis
- interferon and immune responses
- COVID-19 Impact on Reproduction
Beijing University of Posts and Telecommunications
2021-2024
Shanghai Jiao Tong University
2020-2023
National Engineering Research Center for Nanotechnology
2020-2023
Massachusetts Institute of Technology
2018-2021
University of Arizona
2020
University of Maryland, College Park
2018-2020
Ragon Institute of MGH, MIT and Harvard
2018
Beijing Institute of Technology
2018
Nankai University
2015
Tsinghua University
2011
The main protease (Mpro) of SARS-CoV-2 is a key antiviral drug target. While most Mpro inhibitors have γ-lactam glutamine surrogate at the P1 position, we recently found that several hydrophobic moieties site, including calpain II and XII, which are also active against human cathepsin L, host important for viral entry. In this study, solved x-ray crystal structures in complex with XII three analogs GC-376 structure inhibitor confirmed S1 pocket can accommodate methionine side chain,...
Machine learning has the potential to revolutionize field of molecular simulation through development efficient and accurate models interatomic interactions. In particular, neural network can describe interactions at level accuracy quantum mechanics-based calculations, but with a fraction cost, enabling large systems over long timescales ab initio accuracy. However, implicit in construction potentials is an assumption locality, wherein atomic arrangements on scale about nanometer are used...
Significance Functional specificity in biology is mediated by two classes of mechanisms, “lock–key” interactions and multivalent weak cooperative (WCI). Despite growing evidence that WCI are widely prevalent higher organisms, little known about the selection forces drove its evolution repeated positive for mediating biological metazoa. We report evolved as number tasks organisms had to perform with functional became large (e.g., multicellular organisms). find confer enhanced robust...
Coulomb interactions play a major role in determining the thermodynamics, structure, and dynamics of condensed-phase systems, but often present significant challenges. Computer simulations usually use periodic boundary conditions to minimize corrections from finite cell boundaries long range generates contributions distant images simulation cell, calculated by Ewald sum techniques. This can add overhead computer hampers development intuitive local pictures simple analytic theory. In this...
Abstract We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic T Lymphocyte (CTL) epitopes derived from diverse pathogens, given Human Leukocyte Antigen (HLA) genotype. The was trained and tested on experimental data relative immunodominance CTL in Immunodeficiency Virus infection. method is more accurate than publicly available models. Our predicts that only fraction SARS-CoV-2 have been predicted to bind HLA molecules immunogenic. immunogenic across all...
Machine learning-based neural network potentials have the ability to provide ab initio-level predictions while reaching large length and time scales often limited empirical force fields. Traditionally, rely on a local description of atomic environments achieve this scalability. These descriptions result in short-range models that neglect long-range interactions necessary for processes like dielectric screening polar liquids. Several approaches including electrostatic within appeared...
We describe a physics-based learning model for predicting the immunogenicity of cytotoxic T lymphocyte (CTL) epitopes derived from diverse pathogens including SARS-CoV-2. The was trained and optimized on relative immunodominance CTL in human immunodeficiency virus infection. Its accuracy tested against experimental data patients with COVID-19. Our predicts that only some SARS-CoV-2 predicted to bind HLA molecules are immunogenic. immunogenic across all proteins provide broad population...
Rationale: Novel vaccine R&D is essential to interrupt the COVID-19 pandemic and other epidemics in future. Subunit vaccines have received tremendous attention for their low cost safety. To improve immunogenicity of subunit vaccines, we developed a novel adjuvant system. Methods: Here rationally designed CpG 1018 graphene oxide-based bi-adjuvant system deliver Receptor-Binding Domain (RBD) SARS-CoV-2 spike protein obtained complex nanovaccine (GCR). Furthermore, microneedle patch (MGCR)...
Abstract The main protease (M pro ) of SARS-CoV-2, the pathogen responsible for COVID-19 pandemic, is a key antiviral drug target. While most SARS-CoV-2 M inhibitors have γ-lactam glutamine surrogate at P1 position, we recently discovered several hydrophobic moieties site, including calpain II/XII, which are also active against human cathepsin L, host-protease that important viral entry. To determine binding mode these and establish structure-activity relationship, solved X-ray crystal...
The role that van der Waals (vdW) attractive forces play in the hydration and association of atomic hydrophobic solutes such as argon (Ar) water is reanalyzed using local molecular field (LMF) theory those interactions. In this problem, solute vdW can reduce or mask interactions measured by contact peak heights ArAr correlation function compared to reference results for purely repulsive core solutes. Nevertheless, both systems exhibit a characteristic inverse temperature behavior which...
The novel coronavirus disease (COVID-19) is breaking out and spreading rapidly around the world. There an urgent need for accurate rapid detection method to quickly find infected patients asymptomatic carriers in order prevent spread of severe acute respiratory syndrome [SARS-CoV-2]. In this paper, we designed a test strip which used principle double antigen sandwich. Fe<sub>3</sub>O<sub>4</sub> magnetic nanobeads are firstly coupled with specific antibodies, S protein new as coating capture...
The new coronavirus SARS-CoV-2 has become a global pandemic, which had huge impact on the lives of people around world and caused impacts losses economic development. To now, there is still no effective drug or therapy against coronavirus. A large number studies have shown that vaccines are ultimate weapon to eliminate major infectious diseases. development coronaviruses best way prevent infections. In this study, we developed vaccine by combining our self-developed nano adjuvant loaded with...
Significance HIV is a highly mutable pathogen that can mutate to evade vaccine-induced immune responses, thus negating the vaccine’s protective effects. If mutations responses incur fitness penalty for virus, other evolve partially compensate loss. Accounting such effects, we designed single long peptide immunogen comprised of parts proteins wherein would be difficult without penalties virus. This was expressed in adenovirus vectors, which are clinical development (e.g., COVID-19). Monkeys...
As periodic orbit theory works badly on computing the observable averages of dynamical systems with intermittency, we propose a scheme to cooperate cycle expansion and perturbation so that can deal intermittent compute more precisely. The assumes shortest unstable orbits build framework system provide quantities based them, while locally analyze structure systems. may be obtained precisely by combining two techniques together. Based integrability near marginal hyperbolicity in part away from...
The system has addressed the error of "Bad character(s) in field Abstract" for no reason. Please refer to manuscript full abstract.
The premelting layer on crystal surfaces significantly affects the stability, surface reactivity, and phase transition behaviors of crystals. Traditional methods for studying this layer—experimental techniques, classical simulations, even first-principle simulations—have significant limitations in accuracy scalability. To overcome these challenges, we employ molecular dynamic simulations based neural network potentials to investigate structural behavior ice. This approach matches...
Machine learning-based neural network potentials are revolutionizing molecular dynamics simulations enabling large system sizes and longer time scales with ab initio-level accuracy. Conventional potentials, however, rely on a local description of atomic interactions but can not predict properties where long-range become important. Several methodologies have been developed to embed the in potentials. Here, we explore transferability recently self-consistent field (SCFNN) by modeling...
LiNi 0.8 Co 0.1 Mn O 2 powders were synthesized from co-precipitated spherical metal hydroxide, Ni (OH) .The effects of the complexant (NH 4 OH) concentration in base solution on microstructure, crystalline structure and electrochemical properties product studied.The results scanning electron microscopy showed that particle morphology was more regular size tended to increase with improving NH OH.The as-prepared material had a good α-NaFeO hexagonal lamellar structure, as confirmed by X-ray...