Biology subjects

Miao, Y.

Publications and source records attributed to Miao, Y..

4 recordsLinked to original sources

bioRxiv2026

Gaussian accelerated Molecular Dynamics - Thermodynamic Integration (GaMD-TI): Improved alchemical free energy calculations with enhanced sampling

It is valuable to calculate alchemical free energy changes in drug discovery and development. Thermodynamics Integration (TI) has been widely used in computational chemistry for estimating free energy changes with alchemical transformations. However, TI based on usually short Molecular Dynamics (MD) simulations often suffers from insufficient conformational sampling. Here, we have integrated Gaussian accelerated MD and TI (GaMD-TI) to enhance the conformational sampling and improve accuracy of free energy calculations. GaMD-TI has been demonstrated in model systems of alchemical changes in the Valine dipeptide and mutation cycle of the Alanine <-> Valine <-> Isoleucine (AVI) residues. Simulations showed that when GaMD boost potentials followed near-Gaussian distribution, the free energy change could be reweighted accurately through generalized cumulant expansion to the second order. The total free energy change often exhibited faster convergence using Selective GaMD (SGaMD) than using conventional MD (cMD). Accuracy of the free energy estimates from SGaMD-TI simulations was similar to or higher than those from cMD-TI simulations, although the differences were subtle for these small model systems. Meanwhile, dihedral angles in the model systems underwent significantly more frequent conformational transitions in SGaMD than in cMD, indicating improved sampling. Future studies are planned on larger systems with more complicated alchemical changes, such as ligand binding to proteins/nucleic acids and mutations at biomolecular binding interfaces. GaMD-TI should be broadly applicable to alchemical free energy calculations and therapeutic design.

biochemistry↗

bioRxiv2018

Development of a novel signature of long noncoding RNAs as a prognostic biomarker for esophageal cancer

ObjectivesThis study aims to develop a lncRNA signature based on RNA-Seq data to predict overall survival in esophageal cancer patients.\n\nMethodsThe lncRNA expression profiles and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database on August 30, 2017. Differentially expressed lncRNAs were screened out between tumor tissues and adjacent normal tissues. The univariate and multivariate Cox regression models were used to develop a prognostic signature for all esophageal cancer patients. The receiver operating curve (ROC) was used to test the sensitivity and specificity of lncRNA signature. Survivals were compared via log-rank test. GO and KEGG enrichment analyses were used to explore the potential functions of prognostic lncRNAs.\n\nResultsWe identified two lncRNAs (RPL34-AS1 and GK3P) were significantly associated with the overall survival of the total 150 esophageal cancer patients. A novel two-lncRNA signature was constructed by Cox regression models. Signature low-risk cases showed better overall survival (median 625.560 days vs. 478.000 days, p = 0.002) than high-risk cases. Further analysis suggested that this two-lncRNA signature was independent of clinical characteristics. GO functional and KEGG pathway enrichment analyses revealed potential functional roles of the two prognostic lncRNAs in tumorigenesis.\n\nConclusionsOur findings suggest that the two-lncRNA signature may be a useful prognostic biomarker for predicting overall survival in esophageal cancer patients.

bioinformatics↗

bioRxiv2018

FT/FD-GRF5 repression loop directs growth to increase soybean yield

Major advances in crop yield are eternally needed to cope with population growth. To balance vegetative and reproductive growth plays an important role in agricultural yield. To extend vegetative phase can increase crop yield, however, this strategy risks loss of yield in the field as crops may not mature in time before winter come. Here, we identified a repression feedback loop between GmFTL/GmFDL and GmGRF5-1 (Glycine-max-Flowering-Locus-T/Glycine-max-FDL and Glycine-max-GROWTH-REGULATING-FACTOR5-1), which functions as a pivotal regulator in balancing vegetative and reproductive phases in soybean. GmFTL/GmFDL and GmGRF5-1 directly repress gene expression each other. Additionally, GmGRF5-1 enhances vegetative growth by directly enhancing expression of photosynthesis- and auxin synthesis-related genes. To modulate the loop, such as fine-tuning GmFTL expression to trade-off vegetative and reproductive growth, increases substantially soybean yield in the field. Our findings not only uncover the mechanism balancing vegetative and reproductive growth, but open a new window to improve crop yield.

plant biology↗

bioRxiv2018

Molecular mechanism of off-target effects in CRISPR-Cas9

CRISPR-Cas9 is the state-of-the-art technology for editing and manipulating nucleic acids. However, the occurrence of off-target mutations can limit its applicability. Here, all-atom enhanced molecular dynamics (MD) simulations - using Gaussian accelerated MD (GaMD) - are used to decipher the mechanism of off-target binding at the molecular level. GaMD reveals that base pair mismatches in the target DNA at specific distal sites with respect to the Protospacer Adjacent Motif (PAM) induce an extended opening of the RNA:DNA heteroduplex, which leads to newly discovered interactions between the unwound nucleic acids and the protein counterpart. The conserved interactions between the target DNA strand and the L2 loop of the catalytic HNH domain constitute a \"lock\" effectively decreasing the conformational freedom of the HNH domain and its activation for cleavage. Remarkably, depending on their position at PAM distal sites, DNA mismatches leading to off-target cleavages are unable to \"lock\" the HNH domain, thereby identifying the ability to \"lock\" HNH as a key determinant. Consistently, off-target sequences hampering the catalysis have been shown to \"trap\" somehow the HNH domain in an inactive \"conformational checkpoint\" state (Dagdas et al. Sci Adv, 2017). As such, this mechanism identifies the molecular basis underlying off-target cleavages and contributes in clarifying a long-lasting open issue of the CRISPR-Cas9 function. It also poses the foundation for designing novel and more specific Cas9 variants, which could be obtained by magnifying the \"locking\" interactions between HNH and the target DNA in the presence of any incorrect off-target sequence, thus preventing undesired cleavages.

biophysics↗