[SOUND]. Lecture Two, Part B. So when I ended the Part A of this lecture I had described to you how protein kinase A mediates epinephrine's flight or fright response. This line of reasoning is true for most receptor pathways in the G protein class. And so there are over 1,000 G protein-coupled receptors. They activate about four different classes of G protein subunits. Heterotrimeric G proteins which are consist of, of three subunits, an alpha beta, alpha and a beta gamma. They're essentially hetero, called heterotrimeric. But beta and gamma are always tightly bound to each other, so they are functionally heterodimers, if you want to call them that. So, the alpha subunit, defines both receptor specificity and often effector specificity or very often effector specificity. The effectors are enzymes, channels or sometimes even regulators of small G proteins. Occasionally but not always they produce intracellular second messengers such as cyclic NP the most classicly characterized one. IP3, inositol trisphosphate, another soluble second messenger. And a membrane bound second messenger DAG or diacylglycerol activates a variety of protein kinases. Such as protein kinase A, protein kinase C, protein kinase B, cAMK calcium calmodulin. CaM kinase II and these kinases in turn mediate various physiological factors such as transcription factors, metabolic enzymes, and so on. So this is pretty much a linear signaling pathway if you want to call it that, As you can see, the signal flows down a site coupled by chemical reaction. But even in this linear signalling pathway in its simplest form, there's almost always a feedback loop. When the protein kinases for later receptor to either most often inhibit them a situation called desensitization. Whereupon occupancy by the ligand of the receptor, the receptor gets turned off for further stimulus for a period of time. [BLANK_AUDIO] So in addition to these large G proteins, or heterotrimeric G proteins, there's a very big family of small GTPases which are about 21 to 28 kilodaltons in size. The typical large G protein is about oh, 90 kilodaltons in size, the alpha sub unit is somewhere at 40 to 45 kilodaltons. And the beta gamma another about 42 or so kilodaltons. So, the small GTPases are another class of signal transducers. Which also mm, allow for signals to flow from receptor to effectors by switch, when Which allows signals to flow when the trans signal transducers are activated when GTP is bound and inactivated when GDP is bound. In this little schematic I show you a typical cycle GTPase cycle, for the small G protein row. Which is il, involved in,cytoskeletal regulation. Many, many receptors couple to these small G protein pathways, not the GPCR's that couple with the heterotrimeric G proteins. It, although they are a class two, here the, GCPR's are called Serpentine receptors. So in addition to the GCPRs cell addition receptors such as integrin, cytokine receptors, blood factor receptors. All couple to the small G proteins in here, the example used is the RAS-GTPase we are very famous oncogene. And they're all coupled by regulating exchange factors for GEF one and nucleotide exchange factors. That allow the small G protein to be activated from the GDP bound state to the GTP bound state. And as I told you the GT bound. GTP bound state allows for signal to flow from the receptor to effectors. And then there are these proteins called GAPS or GTPs activating proteins that are involved with the active. Or in, yeah, in the active deactivation of the GTPases converting them back to the GDP bound state. And this sort of gives rise to a cycle. Since many, many GEFS and GAPS there are many GEFS, there are many GAPS there are many protein kinases. And all this mix and match stuff go on to produce an extensive network. So the regulation of GEFS and GAPS are a sort of an important point at which networking occurs. And I would, you know, we will discuss this more in the in the next lecture. Here let me move on from signal transduction or the basic process of signal transduction to start a focus on receptors. You can see that, because signal transduction pathways involve signal flow, they are major targets for drugs for a variety of diseases. Receptor ligands are widely used as drugs. That is because you just need to get the ligand into the blood stream and they can bind to the receptor at the outside of the cell surface. Er, Agonists receptors ligands er, that bind to the drug and initiate biological action are called agonists. Receptor ligands that bind specifically to the receptor, but do not initiate eh, action. But block the deleterious effect of natural ligand, are called antagonists, are called antagonists. And in between the agonists and antagonists, there is a class that can be called a partial agonist. Or a, or, or if you want to call it, this is also a partial act in antagonist. So this partial agonist or antagonist will specifically bind to the receptors, but they will not fully activate the receptor. So consequently by themselves, they produce a 30% or 50% of the activity and then set partial. But now, if used with a full agonist, they, in excess, they bind to the receptor, and suppress the activity of the full agonist. And so they might behave like partial antagonists. So these receptors can come in many, many classes and [INAUDIBLE] common drugs that are receptors ligands, the best known of these are insulin. Insulin advance to the insulin receptor which is an agonist drug used to treat Type 1 diabetes. There are of course very famous antagonist drugs such as Propranolol which is an antagonist for the beta-adrenergic receptors. It was among the first antihypers, hypertersives, hypertensives tends to be to lower blood pressure. And for the development of Propranolol, Jim Black shared a Nobel Prize back in the 80s. He also invented or designed and developed Cimitedine which is an H2 receptor antagonist that blocks acid secretions. These are small molecules and is used for a treatment of mm, sort of GI disorders. There is of course drugs against tyrosine kinase receptors. Mm, such as the antibody Trastuzumab that binds against the tyrosine kinase receptor ErB2. And this receptor is used, this drug is used to treat certain types of [INAUDIBLE]. So in book biochemistry and in pharmacology mathematical representation of drug action has been a major way in which drug action is studied and understand, understood. And, it's used for the development of drugs because you want to develop more potent than efficacious drugs. So basically, coming back to this sort of ligand receptor interaction, reaction one can indeed have ligand rerceptor interaction. Eh, reaction that contain both, activators and inhibitors. Which is the most common, kind of scenario, where the natural hormone or the neurotransmitter might be the activator. And the drug that is given exogenously might be the inhibitor. And then you can have reactions going in both directions. And the ligand receptor in the formation of the formation of the ligand receptor complex. Which is the sum total of the complex that transmit the information that is given by this equation down here. This type of equation can be used to determine the extent the physiology or the pathophysiological reaction. And also, both the extent and the action of drug ac, er, er, er, of drug action. From the 70s through the 90s, when ligand and drug binding receptors were most extensively studied. People conducted experiments using, they do actively labeled ligands that could a, a, who's binding to the receptor in whole cells. Or Isolated plasma membranes or tissues could be static. A typical experiment or the simplest of these kinds of experiments, were the ones shown on the left. Where one studied the bind, specific binding of radioactive ligand. It could be a receptor receptor agonist or an antagonist as, as a function of reading concentrations of the ligand. Or it could also be with one concentration of the radioactive ligand and multiple concentration of unlabeled drug. Two lower curves on the left panel might represent the differing concentration to the unlabeled drug for a fixed concentration of radioactive ligand. From these kinds of time course experiments, one can see that one reaches steady state. In this particular example, somewhere between say 15, 16 to 20 30 minutes, one can get steady-state binding activities. Which can be then plotted as receptor activities as a function of a drug or agonist concentration. And the panel in the middle shows such typical plot which is a semi-log plot. Where, where one can see a [UNKNOWN] dose response curve for, varying concentrations of ligand. And the curve in blue might represent agonist binding to the receptor. The curve in, with the green might represent a ligand binding being competed by an un-ligand drug. From the curve in the the, with the blue dots blue squares, one can see that one can see that you can calculate the concentration of the agonist. Where you get 50% occupancy or effect, 50% of the maximal. And this is e, typically called EC50. From the curve, from curves like the one with the green dots, one can similarly calculate out a an IC50 concentrations using. The, different conna, different concentrations of unlabeled ligand. Another way to sort of analyze these data is the, is the linear transformation shown on the right. Where bound or free ligand is plotted as a function of bound and this is called Scatchard Plot. The slope of this plot represents minus 1 KD, KD being dissociation constant. And so, this can be estimated from the plot and the intercept on the obsessor represents the B max or the maximum. Or the total number of receptors present in the sample for which the binding Experiment was done. So if one used a fixed amount of say plasma membrane or a certain number of cells, from this B max value. One would be able to calculate the total number of receptors per cell. The take home points for the Lecture 2 are as followings. Signalling pathways receive information from the outside of the cell and change cell physiology in response to this information. Indeed the change somethime tissue and organ physiology and organism physiology and all the processing and change information can be so represented mathematically. And this mathematical representation is very important not only for understanding biological function but also in drug development. Signaling pathways contain many components each of which receive and transmit signal with bi-directional specificity. Just to emphasize this point let me use the examples of GS and GQ. GS couples to GS couples to GS coupled class of GPCRs, and activates adenylyl cyclase in response to these receptor activation. GQ 11 proteins in contrast, couple to GQ 11 class of receptors and activate phospholipids C in desi, in co, in response to receptor activation. GS does not just activate cyclase, GQ does not activate phospholipid, GS does not activate phospholipid C. GQ does not activate cyclase. So there is specificity of the affected action and the specificity at receptor action. So this vital action specificity of many component inline. Allows for signalling pathways to emerge from, reactions of a component with an upstream and downstream partner. Information flow through signalling pathways can be studied mathematically using ordinary differential equations. So this has been done a long time. This is not something new for systems biology. This has been done for a long time in both biochemistry and pharmacology. And, and adapting the sort of biochemical and pharmacological lines of reasoning into systems biology, helps us build bigger and bigger systems. That can be computationally analyzed, to understand input-output relationships and how information is processed, as it flows through the systems. And of course receptors are immediate targets for drugs that are used to treat a variety of diseases. And understanding drug action requires understanding both receptor affinity or drug affinity for the receptor and efficacy of the drug. And these are routine and sort of mathematical representations and computations of the receptor function. This concludes Lecture 2. Thank you. [MUSIC]
