 Hello everyone and welcome to the first webinar in the QMM best practice workshop of this year. Now to introduce today's speaker. Today's speaker is Professor Yanis Mavri. He is based at the University of Ljubljana, where he's a professor of pharmaceutical chemistry and also at the National Institute of Chemistry in Ljubljana, where he's head of the laboratory for computational biochemistry and drug design. So Yanis has a wide-ranging interest in a number of areas in theoretical and computational pharmacology as well as the application of these of these areas for drug design and things like carcinogenesis, namely, multi-scale simulations of enzyme reactions including force QMM as we will note out Yanis will be talking about today, the role of hydrogen bonding, nuclear quantum effects, transport phenomena and receptor triggering. Yanis has been a recipient of the Long-Term Human Frontier Science program fellowship as well as a Fulbright scholarship and he lectured at places like Gordon Research Conference and has held several visiting positions as research groups at universities in Canada and Netherlands and elsewhere in France. So first I would like to thank for this kind invitation. So it is it would be much more it would be much nicer to be I guess in Finland where yet it is located. So but we can do it also in this way. So today I'm going to talk about multi-scale simulation of quantum energy system and we will have applications to neurodegeneration. So I would say that Filihuzha of this talk will be protons and we all know that snow and ice is white because of the protons. So this photo is from Nepal a couple of years ago and that's Ahmadavnam. So this year I can only dream about this. Okay this is my group here. So the photo was taken a couple of years ago. So this is this is with all visitors and students and what we are doing is basically we try to understand function of biological macromolecules and application is drug design and since proteins are large molecules it's absolutely necessary to proceed with the hierarchical treatment that is called multi-scale modeling. So in December 2013 I was attending Nobel Prize lectures in Stockholm and I remember a sentence of Martin Karplus saying if I were 30 years younger I would be simulating the brain. Martin Karplus turned 90 last year. So I was quite happy to hear that since at that time they were ready to make first steps in this direction. So let's now define monominergic system. So it consists of neurons that basically secrete monamine neurotransmitters such as dopamine, noradrenaline and serotonin. So when they activate the receptor it's fine to decompose them and these are enzymes that think that monamine oxidizes cut the whole omethyl transferases then transporters like dopamine transport serotonin transporters and receptors. So these receptors are are actually sensors that feel over neurotransmitters. So the levels of monamines critically depend on the rate of reuptake and the rate of decomposition is of course controlled by enzymes and monamine oxidate oxidases are essential enzymes to maintain the level of monominergic neurotransmitters. So it would be fine to understand and to simulate the rates of those of this of those enzymes from first principles and in this case it's fine to understand what is the physics or chemistry behind that. So Pauline rationalized that the nature of enzyme catalysis is is basically is basically based on more favorable salvation of the transition state relative to the reactants. And if this is the case then the reaction would proceed faster. But he was more or less quiet about the nature of this of this solution. And then Argy Warsh recognized that that pre-organized electrostatics is the only relevant factor for enzyme catalysis. We can see Argy here in Bled in Slovenia. So pre-organized electrostatics simply means that polar and ionizable groups around the transition states are organized in a way that they stabilize transition state better than the reactants. So reversible work to reorganize or to organize those dipoles when going from reactants the transition state is lower than the corresponding value in in aqueous solution. So it's like that. So electrostatics is a long range interaction and it's somehow I would somehow this gives some evidence why enzymes have to be so large. So you cannot you cannot design efficient enzyme with five residues. Okay when the substrate starts to approach the enzyme it must first find the active site. So this searching is usually diffusion control sent in this cost this this this barrier here the search active site is 5.2k cal per mole and this corresponds to the rate constant of 10 or 10 on 9. So this is diffusion controlled reaction. Then they form Michaelis complex and in computation and zemology we would like to calculate the activation free energy. So this is the basis of computation energy or computation and zemology to calculate activation free energy for going from the from the Michaelis complex over the transition state to the to the well off of your products. So this was formulated more more than 100 years ago by Michaelis and Mod Menton. I don't know if you know but Mod Menton was empty by basic education. So most of the enzymes are not not very fast. So an average enzyme works excuse me it's k cat of 10 per second and so but there are some some enzymes that are very fast like acetylcholine esterase superoxide dismutase and so on. So most of those enzymes had to be fast in order to properly to properly catalyze the reaction. So the superoxide dismutase as catalyzes and stuff like that have to remove very fast reactive oxygen species. So this is important so 10 per second works and is the rate constant of the average enzyme. So then let's define catalysis. Catalysis is lowering of the activation energy relative to the reference reaction. So traditionally in zemology we have reaction in aqueous solution. So this is the reference reaction. So in the enzyme the barrier will be lower than the corresponding reaction aqueous solution and this difference is is the measure for catalysis. At this point it's worth to give you a warning of improper models so dynamic and other esoteric effects do not contribute to catalysis. So Judith Klinman that basically advocated these ideas change her mind. So I talked a couple of years ago with Sharon Hamer Schiffer her close co-worker and but it's interesting that up to my knowledge I did not publish anything in this direction. I mean that they were wrong. So for the criticism you can read these papers especially illustrative is this paper of Adrian Mulholland stating that transition state theory is perfectly valid. Okay now we have basically all the tools to proceed with monamine oxidases. These are this we are talking about two enzymes MAO A and MAO B. They appear in the gastrointestinal tract and in the central nervous systems. They metabolize serotonin, dopamine, tyramine you know. If you block those by one of the incubators and eat old cheese that contains tyramine you have very very good chance to end the emergency medicine department. So what it does it actually this reaction the reaction that it catalyzes is basically oxidative deamination of the of the amines. So before at the very end we obtain the aldehydes ammonia and peroxide and that that further gives rise to reactive oxygen species. So by definition whenever a molecule of biogenic amine is is metabolized by monamine oxidase you obtain a molecule of hydrogen peroxide so that's not very good since hydrogen peroxide is is is is basically causing neurodegeneration. All right Robert Villanella joined us as Marie-Keris Scholar and his knowledge of physical organic chemistry was sufficient to propose the mechanism he was using cluster model like Pachmishimon does it. So he included a few residues and he examined a few reaction mechanisms and basically he he came to the conclusion that the protein if this hydride if CH bond is cleaved in the form of hydride this is the most favorable barrier. So only 24 kK. So this radical and polar nucleophilic mechanisms were much much more expensive so much higher barrier so this is not a plausible reaction channel. Well we were still a little bit high 24 kK experimental value is 16 kK and this is one of the reasons why why small enzymes are not very efficient. Then so this is the message reaction proceeds like that we have we have methylene group vicinal to the neutral amino group and this is this is this hydride is means hydride is the tet so hydride ion means proton plus lone pair and flavin at the at this position and five here picks up hydride. So we finally we appeared on the cover page of the european journal for organic chemistry. We are very proud of that and then we have machinery to then we have machinery to to include full full dimension of the of the enzyme and the method of two issues empirical valence bond. So this is actually forceful that is able to model chemical reactions so bond breaking and bond making. So it's fine because it includes knowledge about the reference reaction so it could be even experimental value of the barrier or that gives rise to the experimental rate constant let's say an aqueous solution and we have basically one or two or four or three parameters and these parameters are transferable between aqueous solution and protein. So actually we are talking about description of the reactant and the product well and we have to we have to basically fit in this h12 that gives the barrier height and the gas phase shift that is basically the difference between these two terms here. So message is now we have computational inexpensive description of the of the reactor system that allows for for high quality thermal average. So Michapurk actually provided this this slide so if you have a SN2 reaction so to the major case this chlorine and bromine and carbon are in our lidar then I would say medium high medium high level of activity would require 20 hours for 1600 points so this is this is roughly 1.6 picosecond of molecular dynamics while empirical valence bond requires 0.1 second so it's a big big big difference. So by multiscay simulation in in conjunction with empirical valence bonds one obtains well convert free energy profiles and at this point it's worth to stress that's essential to have the same orientation of the reactive species for the enzyme reaction and reference reaction so this can be contrasted with the ab initia QMM simulation where they are typically far away from convergence still with the event of metodynamics there is there is some progress and criticism of ab initia QMM is that typically they do not have that reference reaction so within machinery we can afford very long simulations of nanoseconds so for monamine oxidizes the reaction the the simulation converge I would say at 1 nanosecond and since this is computationally affordable we can we can afford even 10 parlance so to have a measure of the error bar. Okay that's the reaction so again courtesy of maestrometopurg or that's the decomposition of serotonin you can see full dimensionality of the enzyme we have thermal averaging and this this CH will be cleaved and the hydrogen will be picked up will be picked up by by a flavin nitrogen atom and five so I'm proud since this reaction simulation of this reaction I performed with my own hands that was follow-up of learning Q5 okay here is the maestro and I love this when I was in at the University of Southern California I had wonderful view from my office to the Hollywood sign okay here are the results in the gas phase reaction will not proceed the barrier is 35 k cal and the reaction is okay in a solution the barrier goes down to 28 k cal while in the in the protein environment we have the barrier that is perfect comparable with the expert you see you see it's slightly exothermic and that's good since the enzyme reactions may not be too exothermic since you know this is one way how the how how they are controlled if the if the the population of products is increased too much the reaction goes back okay so with by subtracting the the barrier nique solution from that one in enzyme we can see that maob provides 10.4 k cal to catalysis we here we're talking about dopamine decomposition we simulated series of of the of the substrate by you by using maob mao a and you obtain reasonable very reasonable and nicely reasonable reasonable values of the barriers that nicely compare with the experiment so this serotonin that we published this last year is not yet in this table okay this last year we also simulated mao be irreversible inhibitions you know parkinson patients are usually taking one of those two irreversible inhibitors raster gelin this is israeli know how or seler gelin this was hungarian know how and we simulated reaction and actually proceeds basically by the same by the same mechanism as the as the as the enzyme catalyzes the reaction of the composition that this was mainly done by robert and tana tanda rich here and this was fine miraculously all right uh one of the strong two is in physical chemist in physical organic chemistry is is a hd kinetic isotope effect so this that means proton is or jitter on a no more twins but a rather cloud so this is this is this nuclear wave function and this can be done by on a grid and this is the mannik but very elegant way is part integration so instead of having one proton or some other atoms we have a necklace that is of let's say of protons 10 or 18 small bits will represent the proton and this force constants depend on the mass so proton is but jitter on is more localized than the proton so this is nicely implemented and i also increased to a q6 package so now let's let's try to understand that properly here are probability densities so uh classical classical probability densities is this blue one h is more delocalized and d is somehow in between and if you take minus kt ln probability density we obtain different barriers for h and for d and the difference is the measure of kinetic isotope effect so at this point it's worth to mention that tunneling is not a dynamical phenomenon and is perfectly compatible with the transition state theory so it can be calculated also by what the methodology know so concept of time is not necessary so we basically reproduce it this was nice work with ricordo and zen shuna and and this is not so so this fact that we basically reproduced the experimental value that has pretty pretty wide span gives additional evidence about validity of the transition state theory so this is not just blue sky research because recently pharmaceutical industry launched deuterated drugs because they are more stable so if you have deuterated whatever it is it is it is let's say 12 times 12.8 times more stable than its hydrogen anion and this is of course more favorable for the patients and it's it's not not necessary to administer a drug every five hours or so but maybe once a day so very similar results were obtained for other substrates and by quantization of of more atoms last year we managed to publish this paper and this one was for benzylamine benzylamine is the is the research is the research analog is this research substrate and you can see here we quantized much much more atoms so this is snapshot from the simulation here we quantized about more than 20 atoms and the results were again consistent with the expert okay does tunneling contribute to enzyme catharsis one would say you know if it's uh eight or twelve in our case then the rectum will be 12 times faster unfortunately the answer is no because the same the same isotope effect can be anticipated in the case of of the reaction in in the in aqueous solution so it's of course great challenge to experimentally prove or disprove this for the enzymes where this might be essential so kinetic isotope effect for most of the normal enzymes is in the range between three and eight of maybe you might know that exception is like oxygenase where it's 80 so but generated enzymes would work on average five times slower those who know some organic chemistry would realize if one would be slowly drinking heavy water you know and then slowly all deuterans all protons in human body would be replaced by deuterans and one would have slow and long life so five times 80 so four hundred years this story works perfectly for Echerichia coli but it does not work for higher organisms rodents do not survive if there is more than 30 percent of what of deto in their body and of course one can speculate that the concept of agonism and antagonism is gone and as first step in this direction we simulated what is the how the quantum nature of of the nuclear motion would affect just binding of ligands to the hydra to the histamine receptor so that's again work of more or less of rubric via nail art he came with with with so initially we're thinking to proceed with part integration but then they found this neutron diffraction study where they stated that in the n-h-o hydrogen bonds the n-d distance shrinks to point three relative to the n-h value and then n-o distance elongates and in hydrogen bonding community they call this uh they call this uh um uberude effect uh we consider this this as a constrain in in uh in quantum chemical calculations we just scaled n-d bonds and n-o-d bonds for with a factor with a factor 0.0.98 so robert came with this complicated scheme since it's necessary to transfer histamine from a solution to the receptor and we were basically able to to reproduce experimental change in in the affiliate so we repeated the exercise with much larger uh water environment and much larger part of the receptor and it basically came uh with the with the experimental value so for for for um progressively methylated uh histamine and two antagonists well at the at the beginning already in the in quite like promised that we're going to talk about neurodegeneration central nervous system weights two percent of the body mass but still it consumes 20 percent of the oxygen and clinically loss dead neurons are not replaced that's more or less not um there are some exceptions and clinically loss of neurons in central neural system is manifested as Alzheimer dementia or Parkinson's and there are basically two two mechanisms we and we also learned that monamine oxidases produce hydrogen peroxide so reactive reactive oxygen species can either attack fatty acids that are constituting the bilayer so the membrane and when membrane becomes leaky then this is the end with the with the cell or they are going to oxidize heavy metal ions like iron and copper they bind alpha-synthesine clean and they press this plaque is basically uh is basically blocking the vesicular transporter and neuron is progressing toward this homeostasis it's it's ill so MEO inhibition is of course an efficient strategy for provision prevention of neurodegeneration together with uh with uh Matitz Pavlin and Matej Repic and Robert we're basically collected the kinetic data of all processes relevant for neurodegeneration and so these these reactions are waiting for awaiting for computational treatment and side effect is when we are carefully searching the literature that monamine oxidase is blocked by hormones if one is smoking cigarettes so smoking is highly neuroprotective so drinking red wine is also neuroprotective so people in the tobacco industry of course love this research very much well uh dopamine is beside and they will be catalyzed the decomposition was also rapidly auto oxidized so the rate constant is so 0.14 per second and again aside product we have hydrogen peroxide and this is clinical manifestation is Parkinson and this this damages of the dopaminergic neurons are initially located in the Negro striatal pathway this is the part this is this red part here that is responsible for for movement uh we suggest the mechanism of dopamine decon that composition so this is all this is all uh quantum chemical work so it's necessary so the proposed mechanism is that OH minus iron in a clear solution is attacking neutral dopamine and this is the barrier and these are the costs first for for the this here nine point nine point fifty i 58 is the pk value of of dopamine and this is the the second term is the energy necessary for dopamine uh deprotonation and the first the second term here is is is free energy cost required to produce OH uh iron so hydroxide and the idea is that the rate constant so now we have analytical analytical analytical um analytical the expression of the activation energy as a function of ph and we see here at acidic ph reactive dopamine is not react is not reacting if you go to the physiological value and higher it becomes the this reaction becomes very very fast so this is this was published in front in mureka neuroscience two years ago so so dopamine is stored in the acidic vesicles work and last for for weeks while if it is here then it starts to decode okay uh like here so a large majority of the dopamine is stored in this vesicles and of course you can change this of course you can change this by modulating the the uh of dopamine and the vesicular transporters you can do that if you want to be more happy than necessary so you can play with those three two transporters with cocaine and unfathomance cocaine is going to block only dopamine transporter and is leaving the zikar transporter intact why while unfathomance are going to block also this monster here so like then i said and message is that if you sniff cocaine in terms of neurodegeneration you are pretty safe it's cardiovascular issues uh the other story i'm not going to address this here while unfathomance are highly problematic so we made a nice nice model so three differential equations so experimental data of pharmacokinetics were dopamine and unfathomance were plugged in you know as time dependent opening and closing of this mouse and uh so messages here in the synaptic gap so this is the measure of how much you're stoned if you sniff cocaine or you take or you take your your unfathomance you see the effect but still for for cocaine the story usually ends in half an hour while in the while in the cytosol is the measure of neurodegeneration and you see that basically it does not cocaine does not have any effect on the elevated level of of of dopamine there while unfathomance induce elevated levels and this is a measure of neurodegeneration at this point i would like to mention that we have enormous problems to to to publish that because you can imagine that in a medical journal to say that the cocaine is safe for neurodegeneration a good message so we have to understand the effect of point mutations monamin oxidizes so we are able to say which residues are contributing to to to to catalysis and with this machinery we are planning to proceed uh so we have tools to proceed with clinical neuroscience you know genomic medicine is these days producing enormous amounts of data and there are also applications in Europe psychiatry like Brunner syndrome this is the Dutch study so the idea of Brunner syndrome is that you have less active monamin oxidase a and already fetuses is exposed to to large to high levels of serotonin plasticity of the brain is changed and you end with with the with the stupid and very aggressive patients of the very end we would like to understand more serotonin and dopamine transporters challenges for future is multi-scale simulation of G protein coupled receptors that formally are electrically controlled enzymes and since we have this nice machinery to simulate the isotope effects would be fine to to properly understand the isotope effects catalyzed by so of the reactions catalyzed by cytocrats and so of course this macroscopic model of the synapse is a challenge for future so now we are at the end I would like to end those fine people without them definitely computational biochemistry and neuroscience would not be on the same level so at this point I would like to thank you for your for your careful listening and we have now time for questions and answers thank you very much Janice very interesting so I know that we have a very least already one question that was asked during the presentation about EVP are there free energy profiles or potential or potential energy here we are definitely talking about free energy profiles since we are using thermodynamic perturbation to slowly move systems from reactants over the transition state to the products so again we performed free energy perturbation with 51 windows and results start to converge one nanosecond and in order to have to estimate the error bar we we perform 10 parallel starting from 10 different starting structures perhaps it would be useful for the attendees if you can comment a little bit in more detail about how you perform the free energy perturbation calculation in that case so you want to go from reactant to product so how how do we do that okay yeah as you know as you know if you want to calculate free energy differences it is necessary it is necessary to thermodynamic thermodynamically couple those two states uh I remember early works of Hermann Berenson and Pierre Stratzma they were mutating sodium ion to neon so it was it was it was alchemic change here we are traveling from reactants to the to the products by using this empirical balance bond so get between between between these two states is used as the reaction coordinate the energy and we monitor it and basically we are we are we are the point the larger the the highest point on this pathway corresponds to the transition state so you can definitely take up take out snapshots you can analyze you can you can you can you can analyze so it's you obtain structural information so if you want to if you want to obtain more information about that you can even perform ab initio tmm calculations for selected snapshots is that enough I think so yes and maybe now it's so there's a couple of more questions which we forward to you the last question on the list is actually now a good one so how do you then analyze your reaction in in terms of which residues contribute to catalysis that's a question of Jack Glancy okay Jack Glancy touch more how can determine the residues contributing to catalysis that's relatively easy so we take the snapshots and then we basically calculate interaction energy between let's say active site or quantum region and each individual residue that you can do and you do it for the reactants and you do it for the transition state and if they if the differences are significant then those residues contribute to catalysis it's we have wonderful scripts for that alia prach that is probably attending this webinar would would provide you with the would provide you with the with the script so all this work was done with what what I was talking was mainly done by oakwist q5 except those part integration it was done by q6 okay that's great thank you very much so so jack who asked this question jack I will attempt to unmute you now so that perhaps you can follow up and and just confirm whether that's whether that's answered your question or indeed follow up with with anything else you want to ask us and thank you very much for your talk that was really really insightful and so I'll just further them to the question about determining which residues contribute to catalysis and clearly it's of importance and for quantum calculation speed to try and reduce how many how many residues we use so when you say we calculate the interaction energy between the transition states and the residues do you how many of those residues do you initially include in the quantum region before when you find the transition state if that makes sense uh look when we were making this residue by residue contribution we considered full dimensionality of the enzyme and you know we considered several several snapshots and this those snapshots so this empirical valence bond is on the level of molecular mechanics we can afford we can afford several snapshots and we can we can we can afford full dimensionality of the enzyme that would make it more difficult with the q with the ab initio q m m m still uh we uh if you have structures let's say snapshots of the of the transition state and the reactants uh then you can we know that the interaction between the transition state and the enzyme is more or less of electrostatic nature so you can always consider the reactive subs subsystem if you want to analyze it properly and you take the the enzyme is described on the level of atomic charges so you can insert them that to your to your ab initio calculation that's that's great thank you very much okay let's go now to the question of of christina rogatz considering the p-h sensitivity of dopamine auto oxidation in solutions shown by your needs is it any all catalyzed metabolism or also likely to be p-h sensitivity especially gives to the invoice the proton transfer yes it is um very good point christina i i probably have forgotten to to mention that p-h of dopamine is nine point four or so and uh at physiological p-h or at p-h at which the experiment was performed it's for it's first necessary to remove the proton and the reversible work for this is calculated as this 1.38 p-h minus p-k and this gives the strong p-h dependence of the enzyme catalyzed reaction as it was in the case of of dopamine auto oxidation that's right moreover you know p-h dependence p-h if you would like to to study this reaction at some other p-h values uh protonation states of the ionizer and residues may change and then that then life becomes a little bit more complicated that's not then it's not necessary then it's necessary to then it's necessary to uh to redo the calculation with the since this changes the proton environment the proton environment uh thanks very much that was very insightful yes my question was um really considering if you deem it likely that some of the residues within the MAOs might actually change ionizable properties with p-h changes and if that is realistic in a p-h range let's say between five and ten i mean it's it's it's perfectly possible to do it but still there are there it's it's not easy since the termination of protonation of p-k values of of uh of the of the protein is far from being easy i mean we we calculated protonation states of the of the of the ionizable residues of both MAO A and MAO B and still it's necessary to proceed with advanced uh uh with advanced uh with advanced methods that are only built in the worships molaris so currently q does not support that and uh i was trying to understand how these things work properly but worship actually implemented long event long event dipoles with double grid resolution so it's really really really complicated so uh one possibility is always to proceed with pro p-k-a that gives reasonable values and most of the computation enzymologists are using that these days but again q is not q is not supporting currently p-k-a calculations and i tried to persuade johan ochrist and his team to implement that but so far uh this was not implemented yet okay thank you very much in evb the reference reactions in water which consideration should be taken into account to build the action model in water how to select the atoms from the enzyme cofactor substrate to build them on all right and we we considered dopamine or any other biogenic amine and the luniflame flavin mine so this was there this was the this was the model and then was everything nicely solvated in a droplet of water so we used about the same parameters for non-bonding interaction especially scut off us in the enzyme reaction uh at this point i would like to emphasize that it is essential to have the same orientation so the same oiler angles in enzyme and in solution so in reality we perform first the simulation in the in the enzyme and then we keep these orientations and and we we we solvate we solvate the reactive system with with with with water when you are when you are when we are doing this reaction we must have the same mechanism and this really means that you have to apply soft position restraints for this at least for this reactive center in order at least for the substrate and lume flavin in order because in computation and zimology there is a big problem of that we cannot simultaneously simulate chemical and conformational coordinates since correlation times become very very long so people that are doing ab initio q m m m and zimology usually do not have such troubles because in 50 picoseconds they can they can usually simulate not much happens okay is is that about yeah it's pretty pretty clear the the the response so yeah i was thinking in in reactions where uh sonaminos is from the protein cam cam cam or to participate in the reaction so i think that you need to as you mentioned put constraints soft constraints on the on those amino acids to to to avoid the the the rupture of the of the catalytic site so it's clear your your your answer so thank you very much and very nice talk thank you now comes mohammed Assad hi the question was for the catalysis is there any role of polarization energy could you please comment on it thank you thank you all right uh let's make clear that the protein and water are used by using effectively polarized force so they charges or charge distribution does not change in during the reaction well empirical valence bond part is however polarizable so because all point charges all point charges or by which is described either aqueous or enzyme environment are included in the hamilton and this is a big difference between this empirical valence bond approach to simulate reactions and and previous attempts let's say by bill jorgensen who was you know you probably remember from from textbooks when he was simulating the s and two reaction were the charges of the of this material chloride chloride iron did not change with the fluctuations of water so so for now we have effectively polarized environment while reactive subsystem is polarized is that enough thank you very much and it was a really wonderful presentation joe as professor maury simulated the aqueous solution the aqueous reaction pcm and explicit representation of the solvent if so has he noticed any difference well this reaction we actually at least robert via nail on was when he was doing cluster model he was using this polarizable continuum model of that but when it came to to real catalysis that i was discussing about what was the catalytic effect of monamine oxidases we had explicit solvent rounds so it was the it was again a nice a nice ball filled with with water and reactive subsystem consisting of of lumiflavin and and dopamine was sitting in the center so it was different and of course explicit representation of solvent is necessary if you want to have to have quantitative if you want to have quantitative measure of of the catalytic effect that's that's great thank you professor maury it's we've just been running some calculations on our own aqueous our reactions and have noticed quite a large difference when you calculate them in pcm and explicit salvation models in terms of explicit favoring charge separated species much more than the pcm salvation models so that's all i was wondering about thank you very much i can ask one more question i don't see other ones coming in yes sure so when you compare so the point about having to compare to solution is a very important one yeah many qm studies indeed do not consider that they only look at the enzyme and then they check if something is optimized or not by checking if the barrier goes down but actually what happens is that they actually did they actually change the the binding free energy that is something that i did not see in your talks do you also consider the binding free energy of the substrate into the protein so that part of this of the reaction profile and furthermore does the free energy of the reaction between the free energy difference between the product and the and the reactants does that match experiments because you seem to compare mostly on on on rate limiting steps okay good question so uh uh we did not consider the entrance of the of the substrate from eq solution to the to the to the uh to the active site so this formation of the michaelis complex was not considered since this controls the overall rate constant only in the case when chemistry is that fast that the that that the the reaction activation energy is lower than 5.2 k k per mole so this would be relevant let's say for very fast enzymes like okay pulling ester or catalyzed or stuff like that okay so that means that in the solution you also start already with the encounter complex then if it's uh if it's not only molecular yeah yeah no i mean in the case of of a q solution if you have that means we are talking if you if you want to if i understand properly want to ask how was done in the reference reaction again we started with the with the with the configuration that was ready for the reaction and then we so this approaching of of of of the substrate and you know it's necessary to enter the active site and it's necessary to move a little bit the enzyme and so this is fast it does not cost much again this is relevant only for very very fast enzymes i i remember studies of acetylcholine esterase where people were trying to figure out uh so they if if this really costs less than five five five point five point two k cal and this for this slow enzymes like monamine oxidizes this is not relevant okay and the other question so the free energy of the reaction to consider that as well maybe i can this one on okay we calculated free energy of the reaction but only for this catalytic steps is immediately four you know subsequent so this is the rate limiting step but probably several steps follow that is called formation of peroxide the regeneration and so so reaction reaction reaction free energy though this is this difference between reactant and the products and probably product is somewhere here is is at least for monamine oxidase is not there are no experimental data okay for some enzymes they are and for that it's possible to proceed but still for this enzyme for this enzyme it would be fun to proceed also with consequent step that is called regeneration you know molyca oxygen enters hydrogen peroxide is formed but that's a little bit nastier chemistry because we are talking about open shell systems and we all know that that's not easy okay thanks jazz okay so i think that is that is all the questions we have so i would like to thank you very much on behalf of bio excel and behalf of all the attendees for this really interesting presentation and also it was great to have this question answer session at the end very very useful before we end the webinar completely i should just show that we have another webinar coming up namely next week Tuesday as part of the QM best practice workshop we have professor Carmen Rovira from the University of Barcelona giving talk about application of QM MD approaches for our carbide rejected enzymes and the information is there available on the at the link on the bio excel website with that thank you again very much for the professor and thank you all the attendees as well and i hope you have a good weekend thank you and thank you for the questions