Commentary, J Pulm Med Vol: 5 Issue: 4
Molecular Dynamics at the Checkpoint
*Corresponding Author: Wolfgang Schreiner Department of Biosimulation and Bioinformatics, Medical University of Vienna, Austria Tel: +431 40400 66790 E-mail: [email protected]
Received: August 16, 2021; Accepted: August 30, 2021; Published: September 06, 2021
Citation: B Roither, Ch Oostenbrink, G Pfeiler, H Koelbl, W Schreiner (2021) Molecular Dynamics at the Checkpoint, J Pulm Med 5:4
Computational molecular dynamics and by big data analysis disclose molecular movement patterns relevant for drug development and function. Atoms in the contact zones of the PD-1 receptor move differently depending on the binding partner: the natural ligand, PD-L1, or the checkpoint inhibitors nivolumab and pembrolizumab, respectively. Computational analysis was performed by an interdisciplinary team from MedUni Vienna and the University of Natural Resources, Vienna. The natural ligand, PD-L1, not only binds but also activates PD-1, thereby inducing T-cell apoptosis. Cancer cells may, by expressing PD-L1, halt natural immune attack and thus survive. Checkpoint inhibitors are designed to just bind to PD-1, but without activating it. This functional difference is reflected by molecular movements analyzed in the papers by Roither being outlined here.
Keywords: Computational molecular dynamics
The Method of Molecular Dynamics
Molecular dynamics is a computational technique to compute atomic movements similar to a planetary system – but for thousands of atoms rather than nine planets. Atomic positions of all molecules (PD-1, PD-L1, nivolumab, pembrolizumab) are taken from the Protein Data Bank (PDP) [1-4] (Figure 1). Given positions, distances and forces between atoms are computed . Atomic velocities are assigned randomly, according to physiological temperature. The‚ flight trajectories are then computed along a very short interval of time (2 × 10-15 sec), yielding the next configuration, i.e. new positions, distances, forces and velocities. The next step of simulation may follow . The system can be watched just like in a movie. At intervals, positions are stored and represent a 'trajectory' for subsequent evaluation.
Refined Big Data Analysis
Advanced analysis is mandatory to extract anything meaningful from the vast amount of data. For evaluation, the software Visual Molecular Dynamics (VMD)  and programs coded in MATLAB  were used.
Similarity and Clusters
In a first step, configurations are compared and considered similar if their multidimensional distances  are small. Multidimensional distance may be defined across a whole molecule or with respect to some special part, such as an alpha helix, a beta sheet or a loop. Similar configurations may be grouped into clusters . In our system, the CC‘- loop of PD-1 (Figure 1) proved a most relevant region for clustering.
Clusters Relate to Function
Certain clusters regarding the configuration of the CC‘-loop occur with both, the natural ligand as well as the drugs as binding partner. Other clusters occur with specific partners only. For example, one specific configuration of the CC‘-loop is only seen with Pembrolizunab as ligand it is 'specific'for this drug. Conversely, with the natural ligand, the very same loop toggles between two configurations (clusters), (Figure 2). This may represent the molecular reason why the natural ligand is able to trigger PD-1 while the drug does not it just binds and blocks the checkpoint [13-15].
Molecular dynamics simulation offers detailed insight into basic mechanisms of molecular medicine and is a conerstone of in silico drug design. It reveals atomnistic explanations that cannot be povided experimentally, regarding biololecules and also drugs. Nivolumab and Pembrolizumab have already been evaluated regarding lung cancer. Modified drugs may be simulated to estimate their therapeutic potential prior to wet lab or even clinical studies. While the described article focuses on PD-1, other chekpoints and corresponding inhibitors may be tackled as well using the very same techniques opening a wide range of applications of Computational Molecular Medicine.
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