Molecular Dynamic Simulations and the Quest for Calculating the G Protein-Coupled Receptor Response

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.

Problems Inherent Within Pharmacological and Biological Assays

This essay addresses inherent problems within most pharmacological and biological assays that all scientists should know. A basic scientific principle is that scientific theories are overturned by experimental evidence that doesn’t support the current theory, but this is only true if the experiments are not only accurate and repeatable, but also accurately represent the natural reactions that happen within the whole animal or organism. This is especially important in the biological and pharmacological sciences, because there are numerous variables that influence the experimental outcomes that receive little or no mention in the mainstream scientific literature. In order to develop new drugs, we need to increase our awareness of the critical variables that are seldom mentioned in most experimental assays. Many of these factors may be why assays are often difficult or impossible to reproduce. When we look at the bigger picture, it is a wonder that we place so much trust in our assays for the important roles that they play in everything from drug development to medicine and research. To step back and see this bigger picture, I will briefly discuss three general factors that often alter the outcomes of these assays.

Three Factors Complicating Most Pharmacological and Biological Assays

1) Confounding Effects:

An overlooked subject that greatly influences pharmacological and biological assays is desensitization or substrate inhibition. This is observed when higher doses of drugs, ligands or substrate molecules show a decrease in the response of the receptor or activity of an enzyme. Most receptor and enzymatic reactions display some negative feedback such as desensitization or substrate inhibition. However, this often goes unnoticed because many assays measure the cumulative response, which is the area under the actual dose-response curve (or the area under the kinetic reaction curve) for different drug, ligand or substrate concentrations. Assays measuring a cumulative response mask the underlying desensitization or substrate inhibition within these systems.

It is often, wrongly, thought that by keeping the drug or substrate molecules at lower levels the effects of desensitization or substrate inhibition will be reduced or prevented.  This isn’t accurate, because the phenomena of desensitization and substrate inhibition is inherent within the chemical equilibria of these systems. Many scientists and medical doctors aren’t aware of the ubiquity of drug desensitization or enzyme substrate inhibition, because many experimental assays aren’t capable of clearly demonstrating these phenomena. These issues present a large problem in drug development and the proper pharmaceutical treatment of patients.

Interpretation of assay results is perhaps another one of the most confounding factors. Our interpretations are largely model dependent. We tend to see what our models allow us to see. Models, such as curve fitting, often create confounding factors that are very much dependent on the assumptions underlying these models. Any two-dimensional curve can be fitted by an arbitrary polynomial to arbitrarily high powers; however, this type of fitting does little to elucidate the underlying biophysical mechanisms of these systems. Statistically we can get a good fit with a bad model. Statistics alone cannot determine the quality of our research. A good model should be like a good pair of glasses that helps us see more clearly the underlying biophysical and physicochemical mechanisms of our assays. Bad models blur our understanding and create confusion.

Current trends using extremely simplified simulations to model and understand the reactions of enzymes or receptors may be hindering our understanding of the underlying basic principles. It seems unlikely that such relatively small differences of 2-5 kcal/mole in binding energies of drugs, ligands or substrates will produce signal-specific wiggles against the background thermal noise in these much larger molecules. Because of our limitations, our current models cannot accommodate many of the other important molecules included within these complex systems, such as the solvent, lipid, other proteins, counter-ions, redox, energy, and cofactor molecules that are necessary components for the activation of these systems in their natural state. Because these complex systems are simplified and run in a vacuum, we’re stuck trying to make sense of rather meaningless wiggles. These observations often serve to obfuscate rather than clarify our understanding of the underlying biophysical principles.  

2) Past Histories:

In general, assays can be divided into those using whole organisms (in vivo) or isolated preparations (in vitro), but there’s also the more general and less controlled variables of past histories and current environmental conditions surrounding these assays, which applies to both in vivo and in vitro assays. Past histories include considerations such as how the animals were handled, caged, fed, type of bedding, etc., or how the isolated preparation was prepared, such as type and amounts of buffers used, fluctuations in temperatures (and the duration and order of these fluctuations), osmotic pressures, pH, solvents; exposures to atmospheric (oxidation) conditions at what stages of the preparation and for what length of time, etc. How pure were our preparations, chemicals, buffers, solvent(s), cofactors, etc? Did the type of containment vessels (glass/plastic) alter the preparations?

Past exposures to various exogenous (xenobiotics, pollutants) and endogenous (steroids, fatty acids) chemicals may induce metabolic pathways such as the Cytochromes P450 enzyme systems (CPYs) that handles many exogenous and endogenous molecules. These induced pathways can profoundly alter our assays in ways that we don’t currently see or understand fully.  

These factors are usually not reported in the scientific literature to the detailed extent that is necessarily suggested here. In some cases, scientists have recognized these confounding facts and tried to account for them, but in general we should all be aware of these serious problems in interpreting any experimental results. Only by recognizing these problems and the limitations that they place on our current assays can we make future progress toward a better scientific understanding of the experimentally observed responses of receptor and enzyme systems.

3) Assay Conditions:

In general, the more procedures that required to isolate any biological sample, the more errors accumulate such that easy replication becomes very difficult or impossible.

Very little or no attention is given to the REDOX (Reduction-Oxidation reactions) environment of receptors or enzymes when measuring their activities in vitro. In vitro, there is little or no regard to the possible effects of light, high oxygen (including REDOX status), electromagnetic gradients, etc. The processes of isolating receptor or enzyme molecules often exposes them to oxidation conditions that generally go unaccounted for the possible effects on their redox sensitive groups.

The requirements of cofactors for enzyme reactions has been previously discovered, but there may be additional requirements such as the requirement for an energy source from molecules such as ATP or GTP or membrane energy gradients. Additional molecules may be necessary to sustain and regenerate these energy molecules or gradients across membranes. There may also be requirements for essential regional molecules such as gases (CO2, H2S, NO, etc.) that may have far greater tissue concentrations in vivo than in our in vitro assays.

Another problem that may seem simple, but is quite complicated, is simply determining the pH-dependence of a receptor response, or an enzymatic reaction. Often these reactions are done at various pHs to find the optimum pH for that specific reaction under the conditions of specific temperature, pressure, osmotic pressure, etc. To complicate matters, the binding drug, ligand, or substrate molecules may have their own titratable groups that are pH-dependent that differ from the receptor or enzyme molecules, which often have multiple titratable groups that may also act to influence each other. Other problems arise because the receptor or enzyme molecules are often membrane bound in vivo whereas the assays are performed in vitro. Other significant problems, which are very difficult to accommodate into in vitro assays, is that biological membranes often separate regions with different pHs, counter-ion concentrations, osmolarities, etc. Even the simpler problems such as determining the proper buffer(s) to use, the concentration, temperature correction(s), unwanted effects on other molecules, such as solvent(s), cofactors, pH-detector(s), etc. are daunting.

In general, it is also very difficult to perform assays under strictly in vivo conditions. The confounding problems with using the whole organism entails many additional factors that affect the experimentally measured responses, which include the pharmacokinetic factors such as the ADME (Absorption, Distribution, Metabolism and Excretion).  Each of the ADME factors have multiple complexities that can confound experimental observations. Just considering the distribution factor alone is often complicated by a drug, ligand, or substrate molecule having to cross one or more membrane barriers, and by the differing tortuosity of the route to tissue-embedded groups of receptor or enzyme molecules. These barriers can greatly delay or alter the drug or substrate molecules from reaching their target receptors or enzymes. The surrounding microenvironments often determine the further metabolism and replenishment rates of the drug, ligand, or substrate molecules, which are also dependent on the lipid compositions of membranes as important considerations. The correct biochemical and biophysical tensions across these membranes are also vitally important to ensure that these assays accurately reflect their natural biological activities. The correct ionic, osmotic, electrochemical, and pH gradients are the most obviously important ones, but there are many others.

Assays that test experimental drugs for potential further drug development are perhaps one of the most critical components of the drug discovery process; yet they remain poorly characterized for this as well as for other biological purposes. This is a very general description of several problems with experimental assays that I’ve noticed over the four plus decades of my career covering experimental, computational and theoretical approaches to many scientific problems. Some of these problems may seem simple but continue to remain largely marginalized and go unnoticed. They need to be recognized and openly discussed so that further progress can be made.  Other problems are much more complex than current experimental techniques can handle, but knowledge of these problems may spur improved assays or at least make us aware of the many problems inherent within our current pharmacological and biological assays.

Richard G. Lanzara, MPH, Ph.D.

President and Principal Scientific Officer

Bio Balance, Inc.

Quintessence - Life's Essential Balance Between Stability, Novelty and Fateful Encounters

We’re two scientists trying to understand Life and Evolution. On a fundamental level, we may all wonder if Life is somehow hard-wired into the structural design of the universe. This naturally leads to the question of what is it that is hard-wired into this vast universe that produces Life? Are there yet unknown chemistries that we haven’t explored? Are there unknown physical laws that govern the flow of energies into Life’s multiple forms? We attempt to answer these questions and more about Life’s most basic principles. This book is meant to engage and catalyze the reader’s mind on a journey of discovery, wonder and awe as we explore and marvel at the wonders of Life and Evolution.