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Yeast As a Chassis for Developing Functional Assays to Study Human P53
Published on: August 4, 2019
Most Probable Druggable Pockets in Mutant p53-Arg175His Clusters Extracted from Gaussian Accelerated Molecular
Morad Mustafa1, Mohammed Gharaibeh2
1Department of Chemistry, School of Science, The University of Jordan, Amman, 11942, Jordan. morad.mustafa@gmail.com.
Abstract:
p53, a tumor suppressor protein, is essential for preventing cancer development. Enhancing our understanding of the human p53 function and its modifications in carcinogenesis will aid in developing more highly effective strategies for cancer prevention and treatment. In this study, we have modeled five human p53 forms, namely, inactive, distal-active, proximal-active, distal-Arg175His mutant, and proximal-Arg175His mutant forms. These forms have been investigated using Gaussian accelerated molecular dynamics (GaMD) simulations in OPC water model at physiological temperature and pH. Our observations, obtained throughout [Formula: see text] of production run, are in good agreement with the relevant results in the classical molecular dynamics (MD) studies. Therefore, GaMD method is more economic and efficient method than the classical MD method for studying biomolecular systems. The featured dynamics of the five human p53-DBD forms include noticeable conformational changes of L1 and [Formula: see text]-[Formula: see text] loops as well as [Formula: see text]-[Formula: see text] and [Formula: see text]-[Formula: see text] turns. We have identified two clusters that represent two distinct conformational states in each p53-DBD form. The free-energy profiles of these clusters demonstrate the flexibility of the protein to undergo a conformational transition between the two clusters. We have predicted two out of seven possible druggability pockets on the clusters of the Arg175His forms. These two druggability pockets are near the mutation site and are expected to be actual pockets, which will be helpful for the compound clinical progression studies.
Insights
Gaussian accelerated molecular dynamics (GaMD) simulations reveal distinct conformational states and druggable pockets in human p53 tumor suppressor protein. This enhanced understanding aids cancer prevention and treatment strategies.
Area of Science:
- Biophysics
- Computational Biology
- Cancer Research
Background:
- The tumor suppressor protein p53 is critical for preventing cancer.
- Understanding p53's function and modifications in carcinogenesis is key for developing effective cancer therapies.
Purpose of the Study:
- To model and investigate five human p53 forms using molecular dynamics.
- To explore the conformational dynamics and identify potential druggability pockets of p53.
Main Methods:
- Gaussian accelerated molecular dynamics (GaMD) simulations were employed.
- Five human p53 forms were simulated in an OPC water model at physiological conditions.
- Analysis focused on conformational changes, distinct states, and free-energy profiles.
Main Results:
- GaMD simulations revealed significant conformational changes in p53 loops and turns.
- Two distinct conformational states were identified for each p53 form, indicating protein flexibility.
- Two potential druggability pockets were predicted near the Arg175His mutation site.
Conclusions:
- GaMD is an efficient alternative to classical MD for biomolecular simulations.
- The identified conformational flexibility and druggable pockets offer new avenues for cancer drug development.
- Further studies on these pockets could advance clinical progression for p53-related cancers.
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