A5100439355- Protein Structure and Dynamics
- Computational Drug Discovery Methods
- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Crystallography and molecular interactions
- Enzyme Structure and Function
- Machine Learning in Materials Science
- Scientific Computing and Data Management
- Distributed and Parallel Computing Systems
- RNA and protein synthesis mechanisms
- Microbial Natural Products and Biosynthesis
- Advanced Data Storage Technologies
- vaccines and immunoinformatics approaches
- Endoplasmic Reticulum Stress and Disease
- Power System Optimization and Stability
- Second Language Learning and Teaching
- Cardiac electrophysiology and arrhythmias
- Additive Manufacturing Materials and Processes
- Industrial Vision Systems and Defect Detection
- Smart Grid and Power Systems
- Optimal Power Flow Distribution
- Synthesis and biological activity
- Amino Acid Enzymes and Metabolism
- Power System Reliability and Maintenance
- Parallel Computing and Optimization Techniques
Guizhou University
2023-2025
Shandong University
2025
Fuyang Second People's Hospital
2025
Lawrence Livermore National Laboratory
2014-2024
Renmin University of China
2023
Wenzhou University
2023
Sichuan Normal University
2022
North China Electric Power University
2021
State Grid Corporation of China (China)
2019-2020
Medical University of South Carolina
2020
We present an extensive study of a novel class de novo designed tetrahedral M(4)L(6) (M = Ni, Zn) cage receptors, wherein internal decoration the cavities with urea anion-binding groups, via functionalization organic components L, led to selective encapsulation oxoanions EO(4)(n-) (E S, Se, Cr, Mo, W, n 2; E P, 3) from aqueous solutions, based on shape, size, and charge recognition. External tBu groups enhanced solubility cages in methanol thereby allowing for their thorough characterization...
Predicting accurate protein–ligand binding affinities is an important task in drug discovery but remains a challenge even with computationally expensive biophysics-based energy scoring methods and state-of-the-art deep learning approaches. Despite the recent advances application of convolutional graph neural network-based approaches, it unclear what relative advantages each approach are how they compare physics-based methodologies that have found more mainstream success virtual screening...
A high-throughput virtual screening pipeline has been extended from single energetically minimized structure Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring to ensemble-average MM/GBSA rescoring. The correlation coefficient (R2) of calculated and experimental binding free energies for a series antithrombin ligands improved 0.36 0.69 when switching the single-structure one. electrostatic interactions in both solute solvent are identified play an important role...
Significance Here we present an unprecedented multiscale simulation platform that enables modeling, hypothesis generation, and discovery across biologically relevant length time scales to predict mechanisms can be tested experimentally. We demonstrate our predictive simulation-experimental validation loop generates accurate insights into RAS-membrane biology. Evaluating over 100,000 correlated simulations, show RAS–lipid interactions are dynamic evolving, resulting in: 1) a reordering...
In this work we announce and evaluate a high throughput virtual screening pipeline for in-silico of compound databases using performance computing (HPC). Notable features are an automated receptor preparation scheme with unsupervised binding site identification. The includes receptor/target preparation, ligand VinaLC docking calculation, molecular mechanics/generalized Born surface area (MM/GBSA) rescoring the GB model by Onufriev co-workers [J. Chem. Theory Comput. 2007, 3, 156–169]....
Abstract A mixed parallel scheme that combines message passing interface (MPI) and multithreading was implemented in the AutoDock Vina molecular docking program. The resulting program, named VinaLC, tested on petascale high performance computing (HPC) machines at Lawrence Livermore National Laboratory. To exploit typical cluster‐type supercomputers, thousands of calculations were dispatched by master process to run simultaneously slave processes, where each calculation takes one node, within...
Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and source major economic liability for development. Thus, reliable in silico screening candidates possible ADRs would be advantageous. In this work, we introduce computational approach that predicts by combining the results molecular docking leverages known ADR information from DrugBank SIDER. We employed recently parallelized version AutoDock Vina (VinaLC) to dock 906 small...
We present a new approach to estimate the binding affinity from given three-dimensional poses of protein–ligand complexes. In this scheme, every atom pair makes an additive free-energy contribution. The sum these pairwise contributions then gives total free energy or logarithm dissociation constant. contribution is calculated by function implemented via neural network that takes properties two atoms and their distance as input. trained using portion PDBbind 2018 data set. model achieves good...
Interdependence across time and length scales is common in biology, where atomic interactions can impact larger-scale phenomenon. Such dependence especially true for a well-known cancer signaling pathway, the membrane-bound RAS protein binds an effector called RAF. To capture driving forces that bring RAF (represented as two domains, RBD CRD) together on plasma membrane, simulations with ability to calculate detail while having long large length- are needed. The Multiscale Machine-Learned...
Computational models can define the functional dynamics of complex systems in exceptional detail. However, many modeling studies face seemingly incommensurate requirements: to gain meaningful insights into some phenomena requires with high resolution (microscopic) detail that must nevertheless evolve over large (macroscopic) length- and time-scales. Multiscale has become increasingly important bridge this gap. Executing multiscale on current petascale computers levels parallelism...
Transient stability assessment (TSA) is of great importance in power system operation and control. One the usual tasks TSA to estimate critical clearing time (CCT) a given fault under network topology pre-fault flow. Data-driven methods try obtain models describing mapping between these factors CCT from large number samples. However, influence on hard be analyzed often ignored, which makes inaccurate unpractical. In this paper, novel data-driven model combining Mahalanobis kernel regression...
In previous research presentations, we have described the important features of chorismate → prephenate reaction using molecular dynamics (MD) and thermodynamic integration studies. This investigation in Escherichia coli water involves QM/MM procedures (SCCDFTB/MM two-dimensional coordinates to identify transition state structures water, enzyme, gas phase followed by B3LYP/6-31+G* single-point computations which allow determination activation energies E. enzyme). Computed 11.3 kcal/mol...
Biologists have observed that the presence of divalent metal is essential for binding hormone oxytocin (OT) to its cellular receptor. However, this interaction not understood on molecular level. Because conformation a key factor controlling ligand in biomolecule systems, we used ion mobility experiments and modeling probe oxytocin−zinc complex. Results show Zn2+ occupies an octahedral site interior OT peptide frees N-terminus creates structured hydrophobic exterior; both factors are conducive
A rapid response is necessary to contain emergent biological outbreaks before they can become pandemics. The novel coronavirus (SARS-CoV-2) that causes COVID-19 was first reported in December of 2019 Wuhan, China and reached most corners the globe less than two months. In just over a year since initial infections, infected almost 100 million people worldwide. Although similar SARS-CoV MERS-CoV, SARS-CoV-2 has resisted treatments are effective against other coronaviruses. Crystal structures...
The appeal of multiscale modeling approaches is predicated on the promise combinatorial synergy. However, this can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider molecular dynamics (MD) simulations that combine accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations sampling speed reductive, coarse-grained (CG) representations. AA-to-CG conversions relatively straightforward because deterministic...
The study investigates the role of foreign language enjoyment (FLE) and engagement in context English learning among Chinese students, emphasizing significance positive emotions enhancing academic success. Utilizing a sample 249 students majoring international trade, research employs scale to count their level assess various dimensions student engagement, including cognitive, emotional, behavioral, social engagement. By conducting regression analysis, findings reveal that FLE positively...
This study aimed to assess the predictive value of neutrophil-lymphocyte ratio (NLR), C-reactive protein/albumin (CAR), and serum amyloid A (SAA) in predicting acute exacerbations chronic obstructive pulmonary disease (AECOPD) complicated by respiratory failure (RF). retrospective was conducted on 198 patients with AECOPD Respiratory Department No. 2 People's Hospital Fuyang City from December 2022 May 2023. Patients were categorized into two groups: an experimental group presence RF (n =...
We have implemented the Martini force field within Lawrence Livermore National Laboratory’s molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition being ported GPU, entire integration step, including thermostat, barostat, and constraint solver, as well, which speeds up simulations 278-fold using one GPU vs central (CPU) core. A benchmark study performed with several test...
Hederagenin (He) is a novel triterpene template for the development of new antitumor compounds. In this study, 26 He–pyrazine derivatives were synthetized in an attempt to develop potent agents; they screened vitro cytotoxicity against tumor and non-tumor cell lines. The majority these showed much stronger cytotoxic activity than He. Remarkably, most was compound 9 (half maximal inhibitory concentration (IC50) 3.45 ± 0.59 μM), which exhibited similar activities A549 (human non-small-cell...
The advancement of machine learning techniques and the heterogeneous architectures most current supercomputers are propelling demand for large multiscale simulations that can automatically autonomously couple diverse components map them to relevant resources solve complex problems at multiple scales. Nevertheless, despite recent progress in workflow technologies, capabilities limited coupling two In first-ever demonstration using three scales resolution, we present a scalable generalizable...