Biology subjects

Sagar, A.

Publications and source records attributed to Sagar, A..

4 recordsLinked to original sources

bioRxiv2017

Dynamic Optimization with Particle Swarms (DOPS): A meta-heuristic for parameter estimation in biochemical models

BackgroundMathematical modeling is a powerful tool to analyze, and ultimately design biochemical networks. However, the estimation of the parameters that appear in biochemical models is a significant challenge. Parameter estimation typically involves expensive function evaluations and noisy data, making it difficult to quickly obtain optimal solutions. Further, biochemical models often have many local extrema which further complicates parameter estimation. Toward these challenges, we developed Dynamic Optimization with Particle Swarms (DOPS), a novel hybrid meta-heuristic that combined multi-swarm particle swarm optimization with dynamically dimensioned search (DDS). DOPS uses a multi-swarm particle swarm optimization technique to generate candidate solution vectors, the best of which is then greedily updated using dynamically dimensioned search.\n\nResultsWe tested DOPS using classic optimization test functions, biochemical benchmark problems and real-world biochemical models. We performed [Formula] trials with [Formula] function evaluations per trial, and compared the performance of DOPS with other commonly used meta-heuristics such as differential evolution (DE), simulated annealing (SA) and dynamically dimensioned search (DDS). On average, DOPS outperformed other common meta-heuristics on the optimization test functions, benchmark problems and a real-world model of the human coagulation cascade.\n\nConclusionsDOPS is a promising meta-heuristic approach for the estimation of biochemical model parameters in relatively few function evaluations. DOPS source code is available for download under a MIT license at http://www.varnerlab.org.

systems biology↗

bioRxiv2017

Atypical domain communication and domain functions of a Hsp110 chaperone

Hsp110s are well recognized nucleotide exchange factors (NEFs) of Hsp70s, in addition they are implicated in various aspects of cellular proteostasis as discrete chaperones with yet enigmatic molecular mechanism. Stark similarity in domain organization and structure between Hsp110s and Hsp70s, is easily discernible although the nature of domain communication and domain functions of Hsp110s are still puzzling. Here, we report atypical domain communication of yeast Hsp110, Sse1 using single molecule FRET, small angle X-ray scattering measurements (SAXS) and Molecular Dynamic simulations. Our data show that Sse1 lacks typical domain movements as exhibited by Hsp70s, albeit it undergoes unique structural alteration upon nucleotide and substrate binding. Hsp70-like domain-movements can be artificially salvaged in chimeric constructs of Hsp110-Hsp70 although such salvaging proves detrimental for the NEF activity of the protein. Furthermore, we show that substrate binding domain (SBD) of Hsp110, chaperones self, as well as foreign nucleotide binding domains (NBD). Interestingly, the substrate binding specificity of Hsp110 is largely determined by its NBD rather than SBD, the latter being the foremost substrate binding region for Hsp70s.

biochemistry↗

bioRxiv2017

Molecular mechanism of cell-cell adhesion mediated by cadherin-23

Adherin-junctions are traditionally described by the homophilic-interactions of classical cadherin-proteins at the extracellular region. However, the role of long-chain non-classical cadherins like cadherin-23(Cdh23) is not explored as yet even though it is implicated in tissue-morphogenesis, cancer, and force-sensing in neuronal tissues. Here, we identified a novel antiparallel-binding interface of Cdh23 homodimer in solution by combining biophysical and computational methods, in-vitro cell-binding, and mutational modifications. The dimer consists of two electrostatic-based interfaces extended up to two terminal domains, atypical to classical-cadherins known so far, and forms the strongest interactions in cadherin-family as measured using single-molecule force-spectroscopy. We further identified single point-mutation, E78K, that completely disrupts this binding. Interestingly, the mutation, S77L, found in skin cancers falls within the binding interface of the antiparallel-dimer. Overall, we provide the molecular architecture of Cdh23 at the cell-cell junctions which are likely to have far-reaching applications in the fields of mechanobiology and cancer.

biophysics↗

bioRxiv2017

An Effective Model Of The Retinoic Acid Induced HL-60 Differentiation Program

In this study, we present an effective model All-Trans Retinoic Acid (ATRA)-induced differentiation of HL-60 cells. The model describes reinforcing feedback between an ATRA-inducible signalsome complex involving many proteins including Vav1, a guanine nucleotide exchange factor, and the activation of the mitogen activated protein kinase (MAPK) cascade. We decomposed the effective model into three modules; a signal initiation module that sensed and transformed an ATRA signal into program activation signals; a signal integration module that controlled the expression of upstream transcription factors; and a phenotype module which encoded the expression of functional differentiation markers from the ATRA-inducible transcription factors. We identified an ensemble of effective model parameters using measurements taken from ATRA-induced HL-60 cells. Using these parameters, model analysis predicted that MAPK activation was bistable as a function of ATRA exposure. Conformational experiments supported ATRA-induced bistability. Additionally, the model captured intermediate and phenotypic gene expression data. Knockout analysis suggested Gfi-1 and PPAR$[gamma] were critical to the ATRA-induced differentiation program. These findings, combined with other literature evidence, suggested that reinforcing feedback is central to hyperactive signaling in a diversity of cell fate programs.

systems biology↗