Biology subjects

Hwang, W.

Publications and source records attributed to Hwang, W..

25 records · Page 2Linked to original sources

bioRxiv2020

Identification of SARS-CoV-2 induced pathways reveal drug repurposing strategies

The global outbreak of SARS-CoV-2 necessitates the rapid development of new therapies against COVID-19 infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein (SIP) network, based on disease signatures defined by COVID-19 multi-omic datasets(Bojkova et al., 2020; Gordon et al., 2020), and cross-examined these pathways against approved drugs. This analysis identified 200 drugs predicted to target SARS-CoV-2-induced pathways, 40 of which are already in COVID-19 clinical trials(Clinicaltrials.gov, 2020) testifying to the validity of the approach. Using artificial neural network analysis we classified these 200 drugs into 9 distinct pathways, within two overarching mechanisms of action (MoAs): viral replication (130) and immune response (70). A subset of drugs implicated in viral replication were tested in cellular assays and two (proguanil and sulfasalazine) were shown to inhibit replication. This unbiased and validated analysis opens new avenues for the rapid repurposing of approved drugs into clinical trials.

pharmacology and toxicology↗

bioRxiv2019

An interactive retrieval system for clinical trial studies with context-dependent protocol elements

A clinical trial protocol defines the procedures that should be performed during a clinical trial. Every clinical trial begins with the design of its protocol. While designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art retrieval systems only offer text-based searches for user-entered keywords. In this study, we present an interactive retrieval system with a context-dependent and protocol-element-selection function for successfully designing a clinical trial protocol. To do this, we first introduce a database for a protocol retrieval system constructed from individual protocol data extracted from 184,634 clinical trials and 13,210 frame structures of clinical trial protocols. The database contains various semantic information that enables the protocols to be filtered during the search operation. Based on the database, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips), which enables an interactive search by utilizing protocol elements. CLIPS provides the options to select the next element according to the previous element in the form of a connected tree, thus enabling an interactive search for combinations of protocol elements. The validation results show that our method achieves better performance than existing databases in predicting phenotypic features.

bioinformatics↗

bioRxiv2019

Reduction of insulin/IGF-1 receptor rejuvenates immunity via positive feedback circuit

Immunosenescence is considered an inevitable decline in immune function during aging. Here we show that genetic inhibition of the DAF-2/insulin/IGF-1 receptor drastically delays immunosenescence and rejuvenates immunity in C. elegans. We find that p38 mitogen-activated protein kinase 1 (PMK-1), a key determinant of immunosenescence, is dispensable for this rejuvenated immunity. Instead, we demonstrate that longevity-promoting DAF-16/FOXO and heat-shock transcription factor 1 (HSF-1) increase immunocompetence in old daf-2(-) animals. The upregulation of DAF-16/FOXO and HSF-1 decreases the expression of the zip-10/bZIP transcription factor, which in turn downregulates INS-7, an agonistic insulin-like peptide, resulting in further reduction of insulin/IGF-1 signaling (IIS). Thus, reduced IIS bypasses immunosenescence and rejuvenates immunity via the upregulation of anti-aging transcription factors that modulate an endocrine insulin-like peptide through a positive feedback mechanism. Because many functions of IIS are conserved across phyla, our study may lead to the development of strategies for human immune rejuvenation.

genetics↗

bioRxiv2018

Whole-Genome Genomics Correlates of Response To Anti-PD1 Therapy in Relapsed/Refractory Natural Killer/T Cell Lymphoma

AbstractThis study aims to identify recurrent genetic alterations in relapsed or refractory (RR) natural-killer/T-cell lymphoma (NKTL) patients who have achieved complete response (CR) with programmed cell death 1 (PD-1) blockade therapy. Seven of the eleven patients treated with pembrolizumab achieved CR while the remaining four had progressive disease (PD). Using whole genome sequencing (WGS), we found recurrent clonal structural rearrangements (SR) of the PD-L1 gene in four of the seven (57%) CR patients pretreated tumors. These PD-L1 SRs consist of inter-chromosomal translocations, tandem duplication and micro-inversion that disrupted the suppressive function of PD-L1 3UTR. Interestingly, recurrent JAK3-activating (p.A573V) mutations were also validated in two CR patients tumors that did not harbor the PD-L1 SR. Importantly, these mutations were absent in the four PD cases. With immunohistochemistry (IHC), PD-L1 positivity could not discriminate patients who archived CR (range: 6%-100%) from patients who had PD (range: 35%-90%). PD-1 blockade with pembrolizumab is a potent strategy for RR NKTL patients and genomic screening could potentially accompany PD-L1 IHC positivity to better select patients for anti-PD-1 therapy.

genomics↗

bioRxiv2017

Energetic costs, precision, and efficiency of a biological motor in cargo transport

Molecular motors play key roles in organizing the interior of cells. An efficient motor in cargo transport would travel with a high speed and a minimal error in transport time (or distance) while consuming minimal amount of energy. The travel distance and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation. Here, we reinterpret the uncertainty measure ([Q]) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small [Q]. Analyses on the motility data from several types of molecular motors show that [Q] is a nonmonotic function of ATP concentration and load (f). For kinesin-1, [Q] is locally minimized at [ATP] {approx} 200 M and f {approx} 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes, and the energetic cost to achieve the same precision as the wild-type increases significantly, which underscores the importance of molecular structure in transport properties. For the biological motors studied here, their value of [Q] is semi-optimized under the cellular condition ([ATP] {approx} 1 mM, f = 0 - 1 pN). We find that among the motors, kinesin-1 at single molecule level is the most efficient in cargo transport.

biophysics↗

bioRxiv2016

Quantifying the Heat Dissipation from Molecular Motor’s Transport Properties in Nonequilibrium Steady States

Theoretical analysis, which maps single molecule time trajectories of a molecular motor onto unicyclic Markov processes, allows us to evaluate the heat dissipated from the motor and to elucidate its dependence on the mean velocity and diffusivity. Unlike passive Brownian particles in equilibrium, the velocity and diffusion constant of molecular motors are closely inter-related to each other. In particular, our study makes it clear that the increase of diffusivity with the heat production is a natural outcome of active particles, which is reminiscent of the recent experimental premise that the diffusion of an exothermic enzyme is enhanced by the heat released from its own catalytic turnover. Compared with freely diffusing exothermic enzymes, kinesin-1 whose dynamics is confined on one-dimensional tracks is highly efficient in transforming conformational fluctuations into a locally directed motion, thus displaying a significantly higher enhancement in diffusivity with its turnover rate. Putting molecular motors and freely diffusing enzymes on an equal footing, our study offers thermodynamic basis to understand the heat enhanced self-diffusion of exothermic enzymes.

biophysics↗

bioRxiv2016

Decoding Single Molecule Time Traces with Dynamic Disorder

Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed. Here we report a new algorithm - Variational Bayes-double chain Markov model (VB-DCMM) - to analyze single molecule time trajectories that display dynamic disorder. The proposed analysis employing VB-DCMM allows us to detect the presence of dynamic disorder, if any, in each trajectory, identify the number of internal states, and estimate transition rates between the internal states as well as the rates of conformational transition within each internal state. Applying VB-DCMM algorithm to single molecule FRET data of H-DNA in 100 mM-Na+ solution, followed by data clustering, we show that at least 6 kinetic paths linking 4 distinct internal states are required to correctly interpret the duplex-triplex transitions of H-DNA.\n\nAuthor SummaryWe have developed a new algorithm to better decode single molecule data with dynamic disorder. Our new algorithm, which represents a substantial improvement over other methodologies, can detect the presence of dynamic disorder in each trajectory and quantify the kinetic characteristics of underlying energy landscape. As a model system, we applied our algorithm to the single molecule FRET time traces of H-DNA. While duplex-triplex transitions of H-DNA are conventionally interpreted in terms of two-state kinetics, slowly varying dynamic patterns corresponding to hidden internal states can also be identified from the individual time traces. Our algorithm reveals that at least 4 distinct internal states are required to correctly interpret the data.

biophysics↗