Zhao Lab
GROUP FOR SOFT MATTER AND BIOPHYSICS RESEARCH
________________________________________________________________________________________________________________________
________________________________________________________________________________________________________________________

Research

We developed automated and efficient computational tools to address RNA structural challenges. 3dRNA builds the RNA tertiary structure from the smallest secondary elements (SSEs) by using sequences and secondary structure information (Scientific Reports, 2012; Nucleic Acids Research, 2017). 3dRNAscore is a novel all-heavy-atom knowledge-based statistical potential to evaluate the RNA predictions (Nucleic Acids Research, 2015). DIRECT (Direct Information REweighted by Contact Templates) incorporates a Restricted Boltzmann Machine (RBM) to augment the information on sequence co-variations with structural features in contact inference (BMC Bioinformatics, 2019; Chinese Physics B, 2020). RBind transforms the RNA tertiary structures into a network and calculates the degree values for short-range binding cavity and closeness values for the long-range allosteric effect to identify the binding sites (Bioinformatics, 2018; Comput Struct. Biotechnol. J., 2020). RPDescriptor calculates the pocket geometrical property quantitatively. It takes advantage of both the atom-level precision of the structure and the nucleotide-level tertiary interactions (BMC Bioinformatics, 2021). It turns out that our developed RNA structural computational tools are easy to use and increasingly being used to solve structure-related problems in the RNA community.

We developed the dynamical network and accelerated sampling technologies to study the protein-protein/protein-RNA binding dynamics, enhancing sample efficiency and magnifying the interaction changes. The strategy has been successfully applied to study the multi-body interactions in the complex biomolecular system (Scientific Reports, 2017; Chinese Physics B, 2020; RSC Advances, 2020; J. Theor. Comput. Chem., 2020).
    Immune system The CD4+ and CD8+ T cell dichotomy are essential for effective cellular immunity. Tcf1- and Lef1-deficient CD8+ T cells exhibit histone hyperacetylation, which can be ascribed to intrinsic histone deacetylase (HDAC) activity in Tcf1 and Lef1. Mutation of five conserved amino acids in the Tcf1 HDAC domain diminishes HDAC activity and the ability to suppress CD4+ lineage genes in CD8+ T cells. (Nature Immunology, 2016)
    The human immunodeficiency virus (HIV) is a retrovirus that progressively attacks the human immune system. It is known that the HIV viral protein Tat recruits the host elongation factor, positive transcription elongation factor b (P-TEFb), onto the nascent HIV viral transactivation response element (TAR) RNA to overcome the elongation pause for active transcription of the entire viral genome. We proposed a computational framework to quantify Tat mutation impact by analyzing the CDK9–Cyclin interface and ATP pocket reorganization dynamics. Our computational results on Tat mutants at residues P10, W11, and N12 explain some puzzling observations on these Tat mutants' latency (Phys.Chem.Chem.Phys., 2020. Cover paper).

We developed the Physics-based computational approaches and applied them for drug design (Chem J Chinese U, 2017; Chinese Physics B, 2017; Int. J. Pept. Res. Ther.,2019; Pathogens, 2021; Math. Biosci. Eng., 2021). First, we proposed one accurate for pocket detection and topology calculation. HKPocket database provides sequence, structure, hydrophilic-hydrophobic, critical interactions, and druggability information, including 1717 pockets from 255 kinases. The potential inhibitors can be selected and optimized by analyzing the sequence conservation, critical interactions, and hydrophobicity of identified drug pockets (BMC Bioinformatics, 2019).
    Then, we applied the developed tools for human diseases related study. HIV protein Tat serves as a mediator to bring host elongation protein P-TEFb onto the viral TAR RNA for active transcription. Thus, these two arms of Tat, so to speak, that grab onto the protein on the one hand and the RNA on the other hand, have long been the drug targets for removing Tat from the complex to inhibit HIV transcription. Two inhibitors, F07#13 and JB181, attack these two sides of Tat. The simulations indicate a far more complete removal of Tat from the complex and thus more efficient disintegration of the complex. Our computational work can thus aid new experimental approaches to exploit the synergetic effect of combined inhibitors in removing Tat from both sides for possibly more efficient Tat degradation, which can set HIV-infected cells into deep latency. (Biophysical Journal, 2021. Cover paper)