Dataset Information

MutS?'s Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning.

ABSTRACT: MutS? is a key component in the mismatch repair (MMR) pathway. This protein is responsible for initiating the signaling pathways for DNA repair or cell death. Herein we investigate this heterodimer's post-recognition, post-binding response to three types of DNA damage involving cytotoxic, anti-cancer agents-carboplatin, cisplatin, and FdU. Through a combination of supervised and unsupervised machine learning techniques along with more traditional structural and kinetic analysis applied to all-atom molecular dynamics (MD) calculations, we predict that MutS? has a distinct response to each of the three damage types. Via a binary classification tree (a supervised machine learning technique), we identify key hydrogen bond motifs unique to each type of damage and suggest residues for experimental mutation studies. Through a combination of a recently developed clustering (unsupervised learning) algorithm, RMSF calculations, PCA, and correlated motions we predict that each type of damage causes MutS? to explore a specific region of conformation space. Detailed analysis suggests a short range effect for carboplatin-primarily altering the structures and kinetics of residues within 10 angstroms of the damaged DNA-and distinct longer-range effects for cisplatin and FdU. In our simulations, we also observe that a key phenylalanine residue-known to stack with a mismatched or unmatched bases in MMR-stacks with the base complementary to the damaged base in 88.61% of MD frames containing carboplatinated DNA. Similarly, this Phe71 stacks with the base complementary to damage in 91.73% of frames with cisplatinated DNA. This residue, however, stacks with the damaged base itself in 62.18% of trajectory frames with FdU-substituted DNA and has no stacking interaction at all in 30.72% of these frames. Each drug investigated here induces a unique perturbation in the MutS? complex, indicating the possibility of a distinct signaling event and specific repair or death pathway (or set of pathways) for a given type of damage.

SUBMITTER: Melvin RL

PROVIDER: S-EPMC6959842 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MutS<i>α</i>'s Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning.

Melvin Ryan L RL Thompson William G WG Godwin Ryan C RC Gmeiner William H WH Salsbury Freddie R FR

Frontiers in physics 20170330

MutS<i>α</i> is a key component in the mismatch repair (MMR) pathway. This protein is responsible for initiating the signaling pathways for DNA repair or cell death. Herein we investigate this heterodimer's post-recognition, post-binding response to three types of DNA damage involving cytotoxic, anti-cancer agents-carboplatin, cisplatin, and FdU. Through a combination of supervised and unsupervised machine learning techniques along with more traditional structural and kinetic analysis applied to ...[more]

PMID: 31938712

Similar Datasets

Project description:Several studies suggest that physical activity improves cognitive functions and reduces cognitive decline, whereas others did not find any evidence of a neuroprotective effect. Furthermore, few cohort studies have analyzed the different physical activity types and particularly household activities. Our objective was to assess the association of two physical activity types with the decline in different cognitive domains in a large prospective cohort of community-dwelling older adults from the Three-city study. Physical activity (domestic/transportation activities and leisure/sport activities) was assessed with the Voorrips questionnaire, specific for older adults. Baseline sociodemographic and health history variables as well as cognitive performance data at baseline and during the 8-year follow-up (Mini-Mental State Examination, Benton Visual Retention Test, Trail Making Tests A and B, Isaac's Set Test and Free and Cued Selective Reminding Test) were also available. Associations between physical activity scores and cognitive decline in different domains were tested using minimally- and multi-adjusted linear mixed models. The analysis included 1697 participants without dementia at baseline and with at least one follow-up visit. At baseline, participants with higher sub-scores for the two physical activity types had better cognitive performances. Interaction with time showed that decline in some cognitive scores (Trail Making Test B and Isaac's Set Test) was significantly less pronounced in participants with higher household/transportation activity sub-scores. No significant effect over time was found for leisure/sport activities. This study shows that during an 8-year follow-up, executive functions and verbal fluency were better preserved in older adults who performed household/transportation activities at moderate to high level. Participation in domestic activities and using adapted transport means could allow older adults to maintain specific cognitive abilities.

Dataset Information

MutS?'s Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning.

Publications

MutS<i>α</i>'s Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets