Publications

2025

1. ProtSci

   PLD-Tree: Persistent Laplacian Decision Tree for Protein-Protein Binding Free Energy Prediction

   X. Xu, C. Wang, G.W. Wei, and 1 more author

   Protein Sciences 2025
2. CIS

   Dimensionality reduction for k-means clustering of large-scale influenza mutation datasets

   E. Walden, J. Chen, and G.W. Wei

   Communication in Information and Systems 2025

2024

1. CBM

   Integration of persistent Laplacian and pre-trained transformer for protein

   J. Wee, J. Chen, K. Xia, and 1 more author

   Computers in Biology and Medicine 2024
2. SIAM Rev

   Graph Combinatorial and Hodge Laplacians: Similarity and Difference

   E. Ribando-Gros, R. Wang, J. Chen, and 2 more authors

   SIAM Review 2024

2023

1. JCP

   A Cartesian FMM-accelerated Galerkin boundary integral Poisson-Boltzmann solver

   Jiahui Chen, Johannes Tausch, and Weihua Geng

   Journal of Computational Physics 2023

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   The Poisson-Boltzmann model is an effective and popular approach for modeling solvated biomolecules in continuum solvent with dissolved electrolytes. In this paper, we report our recent work in developing a Galerkin boundary integral method for solving the linear Poisson-Boltzmann (PB) equation. The solver has combined advantages in accuracy, efficiency, and memory usage as it applies a well-posed boundary integral formulation to circumvent many numerical difficulties associated with the PB equation and uses an Cartesian Fast Multipole Method (FMM) to accelerate the GMRES iteration. In addition, special numerical treatments such as adaptive FMM order, block diagonal preconditioners, Galerkin discretization, and Duffy’s transformation are combined to improve the performance of the solver, which is validated on benchmark Kirkwood’s sphere and a series of testing proteins.

2. arXiv

   persistent topological Laplacian analysis of SARS-CoV-2 variants

   Xiaoqi Wei, Jiahui Chen, and Guo-Wei Wei

   arXiv preprint arXiv:2301.10865 2023
3. CBM

   Topological deep learning based deep mutational scanning

   J. Chen, D.R. Woldring, F. Huang, and 2 more authors

   Computers in Biology and Medicine 2023
4. JCBC

   Persistent topological Laplacian analysis of SARS-CoV-2 variants

   X. Wei, J. Chen, and G.W. Wei

   Journal of Computational Biophysics and Chemistry 2023
5. Small

   Shape Anisotropy Governed High Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs

   S. Nigam, J. Mohapatra, A. Makela, and 19 more authors

   Small 2023

2022

1. ChemRev

   Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2

   Kaifu Gao, Rui Wang, Jiahui Chen, and 6 more authors

   Chemical Reviews 2022

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   Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein–protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

2. ACS ID

   Emerging vaccine-breakthrough SARS-CoV-2 variants

   Rui Wang, Jiahui Chen, Yuta Hozumi, and 2 more authors

   ACS infectious diseases 2022
3. CJIM

   Omicron variant (B. 1.1. 529): infectivity, vaccine breakthrough, and antibody resistance

   Jiahui Chen, Rui Wang, Nancy Benovich Gilby, and 1 more author

   Journal of chemical information and modeling 2022
4. JPCL

   Omicron BA. 2 (b. 1.1. 529.2): High potential for becoming the next dominant variant

   Jiahui Chen, and Guo-Wei Wei

   The journal of physical chemistry letters 2022
5. arXiv

   Graph and Hodge Laplacians: Similarity and Difference

   Emily Ribando-Gros, Rui Wang, Jiahui Chen, and 2 more authors

   arXiv preprint arXiv:2204.12218 2022
6. arXiv

   Mathematical artificial intelligence design of mutation-proof COVID-19 monoclonal antibodies

   Jiahui Chen, and Guo-Wei Wei

   arXiv preprint arXiv:2204.09471 2022
7. arXiv

   Persistent Laplacian projected Omicron BA. 4 and BA. 5 to become new dominating variants

   Jiahui Chen, Yuchi Qiu, Rui Wang, and 1 more author

   Computers in Biology and Medicine 2022
8. CIS

   Computing electrostatic binding energy with the TABI Poisson–Boltzmann solver

   Leighton Wilson, Jingzhen Hu, Jiahui Chen, and 2 more authors

   Communications in Information and Systems 2022
9. JCIM

   Emerging dominant SARS-CoV-2 variants

   Jiahui Chen, Rui Wang, Yuta Hozumi, and 4 more authors

   Journal of Chemical Information and Modeling 2022

2021

1. DCDS–B

   Evolutionary de Rham-Hodge method

   Jiahui Chen, Rundong Zhao, Yiying Tong, and 1 more author

   Discrete and Continuous Dynamical Systems Series B 2021

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   The de Rham-Hodge theory is a landmark of the 20th Century’s mathematics and has had a great impact on mathematics, physics, computer science, and engineering. This work introduces an evolutionary de Rham-Hodge method to provide a unified paradigm for the multiscale geometric and topological analysis of evolving manifolds constructed from a filtration, which induces a family of evolutionary de Rham complexes. While the present method can be easily applied to close manifolds, the emphasis is given to more challenging compact manifolds with 2-manifold boundaries, which require appropriate analysis and treatment of boundary conditions on differential forms to maintain proper topological properties. Three sets of unique evolutionary Hodge Laplacians are proposed to generate three sets of topology-preserving singular spectra, for which the multiplicities of zero eigenvalues correspond to exactly the persistent Betti numbers of dimensions 0, 1, and 2. Additionally, three sets of non-zero eigenvalues further reveal both topological persistence and geometric progression during the manifold evolution. Extensive numerical experiments are carried out via the discrete exterior calculus to demonstrate the potential of the proposed paradigm for data representation and shape analysis. To demonstrate the utility of the proposed method, application is considered to the protein B-factor predictions of a few challenging cases for which other existing models do not work well.

2. JCBC

   Computing protein pKas using the TABI Poisson-Boltzmann solver

   Jiahui Chen, Jingzhen Hu, Yongjia Xu, and 2 more authors

   Journal of Computational Biophysics and Chemistry 2021
3. CPC

   Cyclically parallelized treecode for fast computations of electrostatic interactions on molecular surfaces

   Jiahui Chen, Weihua Geng, and Daniel R Reynolds

   Computer Physics Communications 2021

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   We study the parallelization of a flexible order Cartesian treecode algorithm for evaluating electrostatic potentials of charged particle systems in which particles are located on the molecular surfaces of biomolecules such as proteins. When the well-separated condition is satisfied, the treecode algorithm uses a far-field Taylor expansion to compute O(NlogN) particle–cluster interactions to replace the O(N^2) particle–particle interactions. The algorithm is implemented using the Message Passing Interface (MPI) standard by creating identical tree structures in the memory of each task for concurrent computing. We design a cyclic order scheme to uniformly distribute spatially-closed target particles to all available tasks, which significantly improves parallel load balancing. We also investigate the parallel efficiency subject to treecode parameters such as Taylor expansion order p, maximum particles per leaf N0, and maximum acceptance criterion theta. This cyclically parallelized treecode can solve interactions among up to tens of millions of particles. However, if the problem size exceeds the memory limit of each task, a scalable domain decomposition (DD) parallelized treecode using an orthogonal recursive bisection (ORB) tree can be used instead In addition to efficiently computing the N-body problem of charged particles, our approach can potentially accelerate GMRES iterations for solving the boundary integral Poisson–Boltzmann equation.

4. FDS

   HERMES: Persistent spectral graph software

   Rui Wang, Rundong Zhao, Emily Ribando-Gros, and 3 more authors

   Fondations of data science (Springfield, Mo.) 2021
5. ChemSci

   Prediction and mitigation of mutation threats to COVID-19 vaccines and antibody therapies

   Jiahui Chen, Kaifu Gao, Rui Wang, and 1 more author

   Chemical Science 2021

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   Antibody therapeutics and vaccines are among our last resort to end the raging COVID-19 pandemic. They, however, are prone to over 5000 mutations on the spike (S) protein uncovered by a Mutation Tracker based on over 200 000 genome isolates. It is imperative to understand how mutations will impact vaccines and antibodies in development. In this work, we first study the mechanism, frequency, and ratio of mutations on the S protein which is the common target of most COVID-19 vaccines and antibody therapies. Additionally, we build a library of 56 antibody structures and analyze their 2D and 3D characteristics. Moreover, we predict the mutation-induced binding free energy (BFE) changes for the complexes of S protein and antibodies or ACE2. By integrating genetics, biophysics, deep learning, and algebraic topology, we reveal that most of the 462 mutations on the receptor-binding domain (RBD) will weaken the binding of S protein and antibodies and disrupt the efficacy and reliability of antibody therapies and vaccines. A list of 31 antibody disrupting mutants is identified, while many other disruptive mutations are detailed as well. We also unveil that about 65% of the existing RBD mutations, including those variants recently found in the United Kingdom (UK) and South Africa, will strengthen the binding between the S protein and human angiotensin-converting enzyme 2 (ACE2), resulting in more infectious COVID-19 variants. We discover the disparity between the extreme values of RBD mutation-induced BFE strengthening and weakening of the bindings with antibodies and angiotensin-converting enzyme 2 (ACE2), suggesting that SARS-CoV-2 is at an advanced stage of evolution for human infection, while the human immune system is able to produce optimized antibodies. This discovery, unfortunately, implies the vulnerability of current vaccines and antibody drugs to new mutations. Our predictions were validated by comparison with more than 1400 deep mutations on the S protein RBD. Our results show the urgent need to develop new mutation-resistant vaccines and antibodies and to prepare for seasonal vaccinations.

6. CommBio

   Analysis of SARS-CoV-2 mutations in the United States suggests presence of four substrains and novel variants

   Rui Wang, Jiahui Chen, Kaifu Gao, and 3 more authors

   Communications biology 2021
7. AppSci

   Modeling the Effects of Calcium Overload on Mitochondrial Ultrastructural Remodeling

   Jasiel O Strubbe-Rivera, Jiahui Chen, Benjamin A West, and 3 more authors

   Applied Sciences 2021
8. CIS

   SARS-CoV-2 becoming more infectious as revealed by algebraic topology and deep learning

   Jiahui Chen, Rui Wang, and Guo-Wei Wei

   Communications in Information and Systems 2021
9. Genomics

   Vaccine-escape and fast-growing mutations in the United Kingdom, the United States, Singapore, Spain, India, and other COVID-19-devastated countries

   Rui Wang, Jiahui Chen, Kaifu Gao, and 1 more author

   Genomics 2021
10. JMB

    Revealing the threat of emerging SARS-CoV-2 mutations to antibody therapies

    Jiahui Chen, Kaifu Gao, Rui Wang, and 1 more author

    Journal of molecular biology 2021
11. arXiv

    Review of the mechanisms of SARS-CoV-2 evolution and transmission

    Jiahui Chen, Rui Wang, and Guo-Wei Wei

    ArXiv 2021
12. CJCP

    MLIMC: Machine learning-based implicit-solvent Monte Carlo

    Jiahui Chen, Weihua Geng, and Guo-Wei Wei

    Chinese Journal of Chemical Physics 2021
13. JPCL

    Mechanisms of SARS-CoV-2 evolution revealing vaccine-resistant mutations in Europe and America

    Rui Wang, Jiahui Chen, and Guo-Wei Wei

    The journal of physical chemistry letters 2021
14. JMC

    Perspectives on SARS-CoV-2 main protease inhibitors

    Kaifu Gao, Rui Wang, Jiahui Chen, and 3 more authors

    Journal of Medicinal Chemistry 2021

2020

1. ACS

   Repositioning of 8565 existing drugs for COVID-19

   Kaifu Gao, Duc Duy Nguyen, Jiahui Chen, and 2 more authors

   The journal of physical chemistry letters 2020
2. JMB

   Mutations strengthened SARS-CoV-2 infectivity

   Jiahui Chen, Rui Wang, Menglun Wang, and 1 more author

   Journal of Molecular Biology 2020
3. AR of Biophy.

   Review of COVID-19 antibody therapies

   Jiahui Chen, Kaifu Gao, Rui Wang, and 2 more authors

   Annual Review of Biophysics 2020
4. MathBio

   The de Rham–Hodge Analysis and Modeling of Biomolecules

   Rundong Zhao, Menglun Wang, Jiahui Chen, and 2 more authors

   Bulletin of Mathematical Biology 2020
5. JPhysChem

   Decoding asymptomatic COVID-19 infection and transmission

   Rui Wang, Jiahui Chen, Yuta Hozumi, and 2 more authors

   The journal of physical chemistry letters 2020
6. ChemSci

   Unveiling the molecular mechanism of SARS-CoV-2 main protease inhibition from 137 crystal structures using algebraic topology and deep learning

   Duc Duy Nguyen, Kaifu Gao, Jiahui Chen, and 2 more authors

   Chemical Science 2020

2019

1. SMU

   PARALLEL MULTIPOLE EXPANSION ALGORITHMS AND THEIR BIOLOGY APPLICATIONS

   Jiahui Chen

   2019

2018

1. ProtSci

   Improvements to the APBS biomolecular solvation software suite

   Elizabeth Jurrus, Dave Engel, Keith Star, and 8 more authors

   Protein Science 2018
2. JCP

   On preconditioning the treecode-accelerated boundary integral (TABI) Poisson–Boltzmann solver

   Jiahui Chen, and Weihua Geng

   Journal of Computational Physics 2018

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   We recently developed a treecode-accelerated boundary integral (TABI) solver for solving Poisson–Boltzmann (PB) equation [1]. The solver has combined advantages in accuracy, efficiency, memory, and parallelization as it applies a well-posed boundary integral formulation to circumvent many numerical difficulties associated with the PB equation and uses an O(NlogN) treecode to accelerate the GMRES iterative solver. However, as observed in our previous work, occasionally when the mesh generator produces low quality triangles, the number of GMRES iterations required to solve the discretized boundary integral equations Ax=b could be large. To address this issue, we design a preconditioning scheme using preconditioner matrix M such that M^-1A has much improved condition while M^-1z can be rapidly computed for any vector z. In this scheme, the matrix M carries the interactions between boundary elements on the same leaf only in the tree structure thus is block diagonal with many computational advantages. The sizes of the blocks in M are conveniently controlled by the treecode parameter N0, the maximum number of particles per leaf. The numerical results show that this new preconditioning scheme improves the TABI solver with significantly reduced iteration numbers and better accuracy, particularly for protein sets on which TABI solver previously converges slowly. In addition, this preconditioning scheme potentially can improve the condition number of various multipole method accelerated boundary elements solvers in scattering, fluids, elasticity, etc.

2015

1. Parallel computing of the adaptive n-body treecode algorithm for solving boundary integral Poisson-Boltzmann equation

   Jiahui Chen, and Weihua Geng

   In International Conference on High Performance Computing and Applications 2015