As scientists, we occasionally need to step back and scrutinize important issues within developing scientific fields. Molecular dynamics simulations of various G protein-coupled receptors (GPCRs) have attempted to find the key conformations of these receptors that describe the activation and modulation of their experimentally observed responses. Although this quest has been pursued for over half a century, most current articles on this subject stress that simulations have made great progress, but that much more needs to be done to accurately model drug-receptor interactions.
Although thousands of crystal structures have been deposited in databanks, such as the Protein Data Bank (PDB), with consistently better resolutions, the conditions that led to their successful crystallization are vastly different from their in vivo environments. This naturally raises questions about the relevance of these structures for our understanding of their natural functioning states. These artificially produced crystal structures are far different than the GPCR’s transmembrane embedded, pH-dependent and REDOX (Reduction (RED) and Oxidation (OX)) sensitive states in vivo. After decades of work, we’re not much closer to discovering GPCR’s natural modes of activation that necessarily include these pH-dependent and REDOX sensitive states for these fascinating proteins.
If one critically examines the dogma that has crept into the field of molecular simulations, then one must begin to question some of that dogma. For instance, the dogma surrounding the essential disulfide bond (linking together two cysteine amino acids by their thiol or sulfhydryl groups) found in many GPCRs, suggests that those studying the molecular dynamics of these proteins may have forgotten some of their biochemistry concerning the stability of disulfide bonds in vivo. Many of these disulfide bonds are easily broken and reformed under natural conditions. In addition, many GPCRs such as rhodopsin contain an odd number of extracellular cysteines so that there may always exist at least one free cysteine that remains reactive. A free cysteine also accounts for the pH-dependence and REDOX properties experimentally associated with many GPCRs.
There have been relatively few attempts to model these extracellular cysteines in their free acid (SH) and base (S-) states. The complexities of cysteine sulfhydryl chemistries in vivo add multiple layers of complexity and confusion when ascertaining the functions of GPCRs. Even the seemly simple treatment by Dithiothreitol (DTT) to liberate the two cysteine thiols, or sulfhydryls, from a disulfide bond, may also block their subsequent reactions with other drugs or ligands in binding or activation assays. In addition, once the sulfhydryl groups are free, their pKa, which determines when the free thiol, or SH, group becomes deprotonated, may vary over a very wide range depending on the polarization of neighboring groups and the surrounding membrane charges. These free thiols, or sulfhydryls, are also sensitive to oxidation under normal atmospheric conditions, which greatly complicates the experimental study of receptors under normal laboratory conditions.
Least we become too confident that our simulations are completely accurate and predictive, many molecular dynamic simulations are done with the hope of discovering unique conformational changes, or “mechanistic hypotheses”, for receptor activation, but this approach may be digging a much deeper hole than initially intended. The almost endless search for better, more meaningful simulations with more powerful computers, stretches the horizon of drug discovery into vastly more complex simulations with lipids, water, counter-ions and other proteins necessary for receptor activation. These endless cycles of refinement and simulation don’t provide us with a good model for the necessary molecular switch between an off and on state for receptor activation. We’re usually happy if we can see clear conformational differences between the agonist and antagonist binding with their targeted receptor molecules, but what about the partial agonists, allosteric modulators, inverse agonists, rapid desensitization and tachyphylaxis? These present enormous challenges to our present simulation methods. Many laboratory experiments are and were previously done with chiral mixtures of enantiomers, whereas, the molecular dynamic simulations usually use only one enantiomer that is considered the most active. What are the implications comparing these mixtures used for laboratory experiments versus molecular dynamic simulations using only one enantiomer?
Similar criticisms can be made about QSAR (Quantitative Structure-Activity Relationship) studies of biological molecules, because they assume that the observed structure and properties that are modeled will help to predict the molecular behaviors. The idea that structure and its accompanying properties can predict function is appealing, but fraught with difficulties. We’re tempted by our ability to make molecular and protein structures with properties such as charges. We examine these charge patterns to see what we can learn about their reactive properties and then make inferences about how they react with another molecule, but in the environment of a cell, these charges may be fleeting or nonexistent if they are surrounded by a sea of catalytic molecules such as enzymes that can add or remove groups such as a phosphate or a plethora of many other functional groups.
We know the structures and properties of buildings and cars, but their functions depend upon many other variables such as their surrounding environments and the people who occupy those buildings and cars. Similarly, biological proteins and molecules are embedded within a cellular milieu with many other molecules that act as cofactors, energy providers, anchors, etc. These exist in a range of environments that have varying charges, fields, lipophilicities, gradients, etc. The whole is much greater than the sum of its parts when it comes to understanding the functioning of biological molecules.
However, as hard-nosed scientists, we should ask the toughest questions, which suggests that we should ask what molecular mechanisms might function as a distinct on and off switch for the GPCRs? We know that something like a chemical, net shift must drive receptors from their inactive to active states. Current debates center around conformational selection versus conformational induced fit. The presence of constitutively active receptors due to receptor overexpression suggests that conformational selection may be the preferred mechanism for receptor activation. Alas, this doesn’t tell us what that active conformation is. Because the net binding energies of many drugs, or ligands, are similar in magnitude to the background thermal noise at normal temperatures, “mechanistic hypotheses” don’t describe a clean off and on switch. The primary criticism being that there are no distinct boundaries between the on and off states that determine the extent of movements of any residue, helix, beta sheet, or loop that are necessary to select the active conformational state.
A better model for the molecular on and off switch would be something such as a distinct change from an acid to base state that would also be accompanied by an electrostatic change within the receptor. This would also be consistent with the experimental observations that many GPCRs show an increase in their activities at higher pH levels. There’s an ongoing need to critically analyze and incorporate much more of the available and reliable experimental data into our molecular dynamic simulations.
With the enormous scientific talent out there, we can and will explore more productive models for receptor activation. Having any model that provides some possible insights into the functions of GPCRs, may be pleasing, but we must not abandon many years of previous experimental observations that have been repeatedly checked and verified.
We may not be making more timely progress because the biochemists and enzymologists aren’t communicating enough with the pharmacologists and biophysicists and those who perform theoretical simulations. By combining our collective expertise and maintaining a skeptical, but open mind, we will greatly enhance our understanding of how our sensory and drug-targeted receptors function.
Richard G. Lanzara, MPH, Ph.D.