4 research outputs found
Ligand Binding Swaps between Soft Internal Modes of ι,β-Tubulin and Alters Its Accessible Conformational Space
The dynamic instability
of the microtubule originates from the
conformational switching of its building block, that is, the Îą,
β-tubulin dimer. Ligands occupying the interface of the Îąâβ
dimer bias the switch toward the disintegration of the microtubule,
which in turn controls the cell division. A little loop of tubulin
is structurally encoded as a biophysical âgearâ that
works by changing its structural packing. The consequence of such
change propagates to the quaternary level to alter the global dynamics
and is reflected as a swapping between the relative contributions
of dominating internal modes. Simulation shows that there is an appreciable
separation between the conformational space accessed by the liganded
and unliganded systems; the clusters of conformations differ in their
intrinsic tendencies to âbendâ and âtwistâ.
The correlation between the altered breathing modes and conformational
space rationally hypothesizes a mechanism of straightâbent
interconversion of the system. In this mechanism, a ligand is understood
to bias the state of the âgearâ that detours the conformational
equilibrium away from its native preference. Thus, a fundamental biophysical
insight into the mechanism of the conformational switching of tubulin
is presented as a multiscale process that also shows promise to yield
newer concept of ligand design
Dynamic and Static Water Molecules Complement the TN16 Conformational Heterogeneity inside the Tubulin Cavity
TN16
is one of the most promising inhibitors of ι, β
dimer of tubulin that occupies the cavity in the β-subunit located
at the dimeric interface, known as the colchicine binding site. The
experimentally determined structure of the complex (Protein Data Bank
entry 3HKD) presents the conformation and position of the ligand based
on the âbest fitâ, keeping the controversy of other
significant binding modes open for further investigation. Computation
has already revealed that TN16 experiences fluctuations within the
binding pocket, but the insight from that previous report was limited
by the shorter windows of sampling and by the approximations on the
surrounding environment by implicit solvation. This article reports
that in most of the cases straightforward MMGBSA calculations of binding
energy revealed a gradual loss of stabilization that was inconsistent
with the structural observations, and thus, it indicated the lack
of consideration of stabilizing factors with appropriate weightage.
Consideration of the structurally packed water molecules in the space
between the ligand and receptor successfully eliminated such discrepancies
between the structure and stability, serving as the âlitmus
testâ of the importance of explicit consideration of such structurally
packed water in the calculations. Such consideration has further evidenced
a quasi-degenerate character of the different binding modes of TN16
that has rationalized the observed intrinsic fluctuations of TN16
within the pocket, which is likely to be the most critical insight
into its entropy-dominated binding. Quantum mechanical calculations
have revealed a relay of electron density from TN16 to the protein
via a water molecule in a concerted manner
Molecular Dynamics and Machine Learning Give Insights on the FlexibilityâActivity Relationships in Tyrosine Kinome
Tyrosine kinases are a subfamily of kinases with critical
roles
in cellular machinery. Dysregulation of their active or inactive forms
is associated with diseases like cancer. This study aimed to holistically
understand their flexibilityâactivity relationships, focusing
on pockets and fluctuations. We studied 43 different tyrosine kinases
by collecting 120 Îźs of molecular dynamics simulations, pocket
and residue fluctuation analysis, and a complementary machine learning
approach. We found that the inactive forms often have increased flexibility,
particularly at the DFG motif level. Noteworthy, thanks to these long
simulations combined with a decision tree, we identified a semiquantitative
fluctuation threshold of the DGF+3 residue over which the kinase has
a higher probability to be in the inactive form
Molecular Dynamics and Machine Learning Give Insights on the FlexibilityâActivity Relationships in Tyrosine Kinome
Tyrosine kinases are a subfamily of kinases with critical
roles
in cellular machinery. Dysregulation of their active or inactive forms
is associated with diseases like cancer. This study aimed to holistically
understand their flexibilityâactivity relationships, focusing
on pockets and fluctuations. We studied 43 different tyrosine kinases
by collecting 120 Îźs of molecular dynamics simulations, pocket
and residue fluctuation analysis, and a complementary machine learning
approach. We found that the inactive forms often have increased flexibility,
particularly at the DFG motif level. Noteworthy, thanks to these long
simulations combined with a decision tree, we identified a semiquantitative
fluctuation threshold of the DGF+3 residue over which the kinase has
a higher probability to be in the inactive form