Biology subjects

Schuler, J.

Publications and source records attributed to Schuler, J..

4 recordsLinked to original sources

bioRxiv2024

Characterization of radiations-inducedgenomic structural variations in Arabidopsis thaliana

DNA, is assaulted by endogenous and exogenous agents that lead to the formation of damage. In order to maintain genome integrity DNA repair pathways must be efficiently activated to prevent mutations and deleterious chromosomal rearrangements. Conversely, genome flexibility is also necessary to allow genetic diversity and evolution. The antagonist interaction between maintenance of genome integrity and flexibility determines genome shape and organization. Therefore, it is of great interest to understand how the whole linear genome structure behaves upon formation and repair of DNA damage. For this, we used long reads sequencing technology to identify and to characterize genomic structural variations (SV) of wild-type Arabidopsis thaliana somatic cells exposed either to UV-B, to UV-C or to protons irradiations. We found that genomic regions located in heterochromatin a more prone to form SVs than those located in euchromatin, highlighting that genome stability and flexibility differs along the chromosome. This holds true in Arabidopsis plants deficient for the expression of master regulators of the DNA Damage Response (DDR), ATM and ATR, suggesting that independent and alternative surveillance processes exist to maintain integrity in genic regions. Finally, the analysis of the radiations-induced deleted regions allowed determining that exposure UV-B, UV-C and protons induced the Microhomology-mediated end joining mechanism (MMEJ) and that both ATM and ATR repress this repair pathway.

plant biology↗

bioRxiv2020

Evaluating Performance of Drug Repurposing Technologies

Drug repurposing technologies are growing in number and maturing. However, comparison to each other and to reality is hindered due to lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross platform comparability, enabling us to continuously strive towards optimal repurposing by decreasing time and cost of drug discovery and development.

bioinformatics↗

bioRxiv2019

Fingerprinting CANDO: Increased Accuracy with Structure and Ligand Based Shotgun Drug Repurposing

We have upgraded our Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun drug repurposing to include ligand-based, data fusion, and decision tree pipelines. The first version of CANDO implemented a structure-based pipeline that modeled interactions between compounds and proteins on a large scale, generating compoundproteome interaction signatures used to infer similarity of drug behavior; the new pipelines accomplish this by incorporating molecular fingerprints and the Tanimoto coefficient. We obtain improved benchmarking performance with the new pipelines across all three evaluation metrics used: average indication accuracy, pairwise accuracy, and coverage. The best performing pipeline achieves an average indication accuracy of 19.0% at the top10 cutoff, compared to 11.7% for v1, and 2.2% for a random control. Our results demonstrate that the CANDO drug recovery accuracy is substantially improved by integrating multiple pipelines, thereby enhancing our ability to generate putative therapeutic repurposing candidates, and increasing drug discovery efficiency.

bioinformatics↗

bioRxiv2019

Exploration of interaction scoring criteria in the CANDO platform

BackgroundDrug discovery is an arduous process that requires many years and billions of dollars before approval for patient use. However, there are a number of drugs and human ingestibles approved for a variety of indications/diseases that can be potentially repurposed as new treatments for others, decreasing the time and cost required.\n\nMethodsCANDO (Computational Analysis of Novel Drug Opportunities) is a platform for shotgun, multitarget drug discovery and repurposing. The CANDO platform scores interactions between 46,784 proteins structures and 3,733 human use compounds using a bioinformatic docking protocol to generate compound-proteome interaction signatures that are then compared to identify candidates for repurposing. Benchmarking of the platform is accomplished by comparing the compound-proteome interaction signatures and determining whether signatures corresponding to pairs of drugs approved for the same indication fall within particular cutoffs.\n\nResultsWe have altered the scoring function of bioinformatic docking protocol in the newest version of our platform (v1.5) to use the best OBscore for each compound-protein interaction, resulting in an increased benchmarking accuracy from 11.7% in v1 to 12.8% in v1.5 for the top10 cutoff, the most stringent one used, and correspondingly from 24.9% to 31.2% for the top100 cutoff.\n\nConclusionsThe change in the interaction scoring and other bug fixes in CANDO v1.5 have resulted in improved benchmarking performance, making the platform more effective at predicting novel, therapeutic drug-indication pairs.

bioinformatics↗