ArticlePloS one2020
Comparative MD simulations and advanced analytics based studies on wild-type and hot-spot mutant A59G HRas.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Article
- Insight into structural dynamics involved in activation mechanism of full length KRAS wild type and P-loop mutants.Heliyon · 2024Article
- Markov State Models: To Optimize or Not to Optimize.Journal of chemical theory and computation · 2024Article
- Studying early structural changes in SOS1 mediated KRAS activation mechanism.Current research in structural biology · 2024Article
- Mechanism-Based Redesign of GAP to Activate Oncogenic Ras.Journal of the American Chemical Society · 2023Article
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Authors and funding
3 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
The Ras family of proteins is known to play an important role in cellular signal transduction. The oncoprotein Ras is also found to be mutated in ~90% of the pancreatic cancers, of which G12V, G13V, A59G and Q61L are the known hot-spot mutants. These ubiquitous proteins fall in the family of G-proteins, and hence switches between active GTP bound and inactive GDP bound states, which is hindered in most of its oncogenic mutant counterparts. Moreover, Ras being a GTPase has an intrinsic property to hydrolyze GTP to GDP, which is obstructed due to mutations and lends the mutants stuck in constitutively active state leading to oncogenic behavior. In this regard, the present study aims to understand the dynamics involved in the hot-spot mutant A59G-Ras using long 10μs classical MD simulations (5μs for each of the wild-type and mutant systems) and comparing the same with its wild-type counterpart. Advanced analytics using Markov State Model (MSM) based approach has been deployed to comparatively understand the transition path for the wild-type and mutant systems. Roles of crucial residues like Tyr32, Gln61 and Tyr64 have also been established using multivariate PCA analyses. Furthermore, this multivariate PCA analysis also provides crucial features which may be used as reaction coordinates for biased simulations for further studies. The absence of formation of pre-hydrolysis network is also reported for the mutant conformation, using the distance-based analyses (between crucial residues) of the conserved regions. The implications of this study strengthen the hypothesis that the disruption of the pre-hydrolysis network in the mutant A59G ensemble might lead to permanently active oncogenic conformation in the mutant conformers.
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