Category Archives: Computational Chemistry
As far as population analysis methods goes, the Quantum Theory of Atoms in Molecules (QTAIM) a.k.a Atoms in Molecules (AIM) has become a popular option for defining atomic properties in molecular systems, however, its calculation is a bit tricky and maybe not as straightforward as Mulliken’s or NBO.
Personally I find AIM a philosophical question since, after the introduction of the molecule concept by Stanislao Cannizzaro in 1860 (although previously developed by Amadeo Avogadro who was dead at the time of the Karlsruhe congress), the questions of whether or not an atom retains its identity when bound to others? where does an atom end and the next begins? What are the connections between atoms in a molecule? are truly interesting and far deeper than we usually consider because it takes a big mental leap to think about how matter is organized to give rise to substances. Particularly I’m very interested with the concept of a Molecular Graph which in turn is concerned with the way we “draw lines” to form conceptual molecules. Perhaps in a different post we can go into the detail of the method, which is based in the Laplacian operator of the electron density, but today, I just want to collect the basic steps in getting the most basic AIM answers for any given molecule. Recently, my good friend Pezhman Zarabadi-Poor and I have used rather extensively the following procedure. We hope to have a couple of manuscripts published later on. Therefore, I’ve asked Pezhman to write a sort of guest post on how to run AIMALL, which is our selected program for the integration algorithm.
The first thing we need is a WFN or WFX file, which contains the wavefunction in a Fortran unformatted file on which the Laplacian integration is to be performed. This is achieved in Gaussian09 by incluiding the keyword output=wfn or output=wfx in the route section and adding a name for this file at the bottom line of the input file, e.g.
(NOTE: WFX is an eXtended version of WFN; particularly necessary when using pseudopotentials or ECP’s)
Analyzing this file requires the use of a third party software such as AIMALL suite of programs, of which the standard version is free of charge upon registration to their website.
OpenAIMStudio (the accompanying graphical interface) and select the AIMQB program from the run menu as shown in figure 1.
Select your WFN/WFX file on which the calculation is to be run. (Figure 2)
You can control several options for the integration of the Laplacian of the electron density as well as other features. If your molecules are simple enough, you may go through with a successful and meaningful calculation using the default settings. After the calculation is finished, several result files are obtained. We’ll work in this tutorial only with *.mpgviz (which contains information about the molecular graph, MG) and *.sum (which contains all of needed numerical data).
Visualization of the MG yields different kinds of critical points, such as: 1) Nuclear Attractor Critical Points (NACP); 2) Bond Critical Points (BCP); 3) Ring CP’s (RCP); and 4) Cage CP’s (CCP).
Of the above, BCP are the ones that indicate the presence of a chemical bond between two atoms, although this conclusion is not without controversy as pointed out by Foroutan-Njead in his paper: C. Foroutan-Nejad, S. Shahbazian and R. Marek, Chemistry – A European Journal, 2014, 20, 10140-10152. However, at a first approximation, BCP’s can help us to explore chemical interactions.
Now, let’s go back to visualizing those MGs (in our examples we’ve used methane and ethylene and acetylene). We open the corresponding *.mpgviz file in AIMStudio and export the image from the file menu and using the save as picture option (figure 3).
The labeled atoms are NACP’s while the green dots correspond to BCP’s. Multiplicity of a bond cannot be discerned within the MG; in order to find out whether a bond is a single, double or triple bond we have to look into the *.sum file, in which we’ll take a look at the bond orders between pairs of atoms in the section labeled “Diatomic Electron Pair Contributions and Delocalization Data” (Figure 4).
Delocalization indexes, DI’s, show the approximate number of electrons shared between two atoms. From the above examples we get the following DI(C,C) values: 1.93 for C2H4 and 2.87 for C2H2; on the other hand, DI(C,H) values are 0.98 for CH4, 0.97 in C2H4 and 0.96 in C2H2. These are our usual bond orders.
This is the first part of a crash tutorial on AIM, in my opinion this is the very basics anyone needs to get started with this interesting and widespread method. Thanks to all who asked about QTAIM, now you have your long answer.
Thanks a lot to my good friend Dr Pezhman Zarabadi-Poor for providing this contribution to the blog, we hope you all find it helpful. Please share and comment.
Well, I only contributed with the theoretical section by doing electronic structure calculations, so it isn’t really a paper we can ascribe to this particular lab, however it is really nice to see my name in JACS along such a prominent researcher as Prof. Chad Mirkin from Northwestern University, in a work closely related to my area of research interest as macrocyclic recognition agents.
In this manuscript, a calixarene is allosterically opened and closed reversibly by coordinating different kinds of ligands to a platinum center linked to the macrocycle. (This approach has been referred to as the weak link approach.) I recently visited Northwestern and had a great time with José Mendez-Arroyo, the first author, who showed me around and opened the possibility for further work between our research groups.
Closed, semi-open and fully open conformations; selectivity is modulated through cavity size. (Ligands: Green = Chloride; Blue = Cyanide)
Here at UNAM we calculated the interaction energies for the two guests that were successfully inserted into the cavity: N-methyl-pyridinium (Eint = 57.4 kcal/mol) and Pyridine-N-oxide (Eint = +200.0 kcal/mol). Below you can see the electrostatic potential mapped onto the electron density isosurface for one of the adducts. Relative orientation of the hosts within the cavity follows the expected (anti-) alignment of mutual dipole moments. At this level of theory, we could easily be inclined to assert that the most stable interaction is indeed the one from the semi-open compound and that this in turn is due to the fact that host and guest are packed closer together but there is also an orbital issue: Pyridine Oxide is a better electron acceptor than N-Me-pyridinium and when we take a closer look to the (Natural Bonding) orbitals interacting it becomes evident that a closer location does not necessarily yields a stronger interaction when the electron accepting power of the ligand is weaker (which is, in my opinion, both logic and at the same time a bit counterintuitive, yet fascinating, nonetheless).
All calculations were performed at the B97D/LANL2DZ level of theory with the use of Gaussian09 and NBO3.1 as provided within the former. Computing time at UNAM’s supercomputer known as ‘Miztli‘ is fully acknowledged.
The full citation follows:
A Multi-State, Allosterically-Regulated Molecular Receptor With Switchable Selectivity
Jose Mendez-Arroyo †, Joaquín Barroso-Flores §,Alejo M. Lifschitz †, Amy A. Sarjeant †, Charlotte L. Stern †, and Chad A. Mirkin *†
Thanks to José Mendez-Arroyo for contacting me and giving me the opportunity to collaborate with his research; I’m sure this is the first of many joint projects that will mutually benefit our groups.
Just as last year, the “Dolphin Summer Internship Program” (Programa Delfín) has started and this time it coincided with #RealTimeChem week. Four students from various cities (and accents) around Mexico have come to our lab in Toluca in order to spend about 7 weeks of research in the field of molecular modeling and within our research of molecular recognition in biochemistry. Karen, Cynthia, Jesús and Marco have started their training today as they arrived to CCIQS so we went over the (very) basics of quantum chemistry, the (very) basics of Linux and the basics of Gaussian09. (I should really think about developing some web tutorials or something because this impromptu training is very exhausting!)
Their academic backgrounds are mostly centered around pharmaceutics and biochemistry although their ages range from the second to the fourth year of college education. Computational chemistry is pretty unknown to all of them; I’ll do my best to change that, while at the same time I make them aware of its power as a research tool and as a research field in itself.
Here is to a very productive summer! I hope we manage to get enough data for a paper and, more importantly, that they all get a good experience out of their time here, make new friends and learn something new that enriches their skills in this increasingly competitive world.
A couple of weeks ago I posted a solution for a common error regarding .fchk files that will display the error below when opened with GaussView5.0. As I expected, this error has to do with the use of diffuse functions in the basis set and is related to a change of format between Gaussian versions.
CConnectionGFCHK::Parse_GFCHK() Missing or bad data: Alpha Orbital Energies Line Number 1234
Although the method described in the previous post works just fine, the following update is a better approach. Due to a change of spelling between G03 and G09 (which has been corrected for G09 but not available for GV versions prior to 5.0.9) one must change “independent” for “independant“
To make the change directly from the terminal the following command is needed:
sed -i 's/independent/independant/g' file.fchk
Alternatively you can redirect the output to a new file
sed -e 's/independent/independant/g' file.fchk > newfile.fchk
if you want to keep the old version and work with a new one.
Of course this edition can be performed manually with any text editor available (for example if you work in Windows) but solutions from the terminal always seem easier and a lot more fun to me.
Thanks to Dr. Fernando Cortés for sharing his insight into this issue.
I’ve found the following error regarding the opening of .fchk files in GaussView5.0.
CConnectionGFCHK::Parse_GFCHK() Missing or bad data: Alpha Orbital Energies Line Number 1234
The error is prevented to a first approximation (i.e. it at least will allow GV to open and visualize the file but other issues may arise) by opening the file and modifying the number of basis functions to equal the number of independent functions (which is lower)
FILE HEADER FOpt RM062X 6-311++G(d,p) Number of atoms I 75 Info1-9 I N= 9 163 163 0 0 0 110 2 18 -502 Charge I 0 Multiplicity I 1 Number of electrons I 314 Number of alpha electrons I 157 Number of beta electrons I 157 Number of basis functions I 1199 Number of independent functions I 1199 Number of point charges in /Mol/ I 0 Number of translation vectors I 0 Atomic numbers I N= 75 ... ... ... ...
Once both numbers match you can open the file normally and work with it. My guess is this will continue to happen with highly polarized basis sets but I need to run some tests.
So many things have happened since I last updated this blog but I will come to write on them when appropriate. Right now I’d like to share an invitation by Prof. Ponnadurai Ramasami from the University of Mauritius to the upcoming Virtual Conference on Computational Chemistry from the 1st to the 31st of August. Deadlines can be consulted here and the most important is the abstract submission on June 30th. This conference is part of the official celebrations of the International Year of Crystallography so talks involving experimental determination of electron densities will be well suited.
I participated in the latest edition and I must say it was a very enriching opportunity to learn from so many other researchers from across the world without leaving my desk. I already know what my talk will be about, now that we are so close to finish and submit a paper on the absence of reactivity for an anti-aromatic set of molecules. (I think I’ll call it “The reactivity of molecules that never existed [but that maybe should have.].) All talks are sent either as pdf, powerpoint presentations, youtube videos, etc. and Q&A are done over e-mail.
So this is a calling to other computational chemists out there who want to participate in this virtual conference. Kudos to Prof. Ponnadurai Ramasami and lets hope we can crystallize his visit to Mexico during 2014 the International Year of Crystallography (pun intended) and here’s to me going sometime to Mauritius!
I always get very happy to have a new paper out there! I find it exciting but most of all liberating since it makes you feel like your work is going somewhere but most of all that it is making its way ‘out there'; there is a strong feeling of validation, I guess.
Two very different families of calix[n]arenes (Fig 1) were tested as drug carriers for a very small molecule with a huge potential as a chemotherapeutic agent against Leukemia, namely, 3-phenyl-1H-benzofuro[3,2-c]pyrazole a.k.a. GTP which has proven to be an effective in vitro Tyrosine Kinase III inhibitor. Having such a low molecular weight it is expected to have a very high excretion rate therefore the use of a carrier could increase its retention time and hence its activity. This time we considered n = 4, 5, 6 and 8 for the size of the cavities and R = -SO3H and -OEt as functional groups on the upper rim as to evaluate only a polar coordinating group and a non-polar non-coordinating one since GTP offers two H-bond acceptor sites and one H-bond donor one along the π electron density that could form π – π stacking interactions between the aromatic groups on GTP and the walls of the calixarene.
Once again calculations were carried out at the B97D/6-31G(d,p) level of theory along with molecular dynamics simulations for over 100 ns of production runs. NBO Deletion interaction energies were computed in order to discern which hosts formed the most stable complexes.
You may find a link to the ScienceDirect website for downloading the paper from this link. Last, but certainly not least, I’d like to thank all coauthors for their contributions and patience in getting this study published: Dr. Rodrigo Galindo-Murillo; Alberto Olmedo-Romero; Eduardo Cruz-Flores; Dr. Petronela M. Petrar and Prof. Dr. Kunsági-Máté Sándor. Thanks a lot for everything!
Once again as every year we celebrate our internal symposium here at CCIQS, and like every year, my students presented some of their progress with their research projects. This time, three students, from three different levels, present posters regarding some of the data they’ve obtained.
María Eugenia ‘Maru’ Sandoval presented a poster regarding the molecular dynamics simulations performed for the drug Imatinb and a family of calix- and thia-calix[n]arenes as published here and reported in this blog here. ‘Maru’ is now a first year grad student at the National University, UNAM, after spending a year working for a pharmaceutical company. Her research in the realm of photosynthesis has only begun recently, that is why we had to rely on some other data.
Luis Enrique Aguilar is researching cation-π interactions within the aromatic cavities of calix[n]arenes in order to find suitable leads among these, our favorite macrocyles, for designing extraction agents of heavy (toxic) metals. Luis Enrique is an undergrad student here at the State University who should finish this year and has shown some interest (threatened us) in writing his dissertation thesis in our research group.
Monserrat Enriquez is a PhD student at CINVESTAV under the joint supervision of Dr. Eddie López-Honorato and myself (Dr. Eddie is her principal advisor), her research project involves both theoretical calculations and synthesis of the leads for extraction agents for several Arsenic species. For the time being, Monserrat is here with us, far from her home on the north side of the country, for this semester in which we have to finish with the theoretical section of her work. Besides her research concerning calixarenes she is also running calculations on the interactions between graphene oxide and the aforementioned As species. We are very excited about working with such a complex yet simple material that has such an exciting electronic structure.
This symposium is always interesting and important in bringing our research projects closer to all the comunity of this center. And since symposium comes from the Greek meaning ‘drinking together‘, then lets raise our glasses and toast for the data to come!
Happy new year to all my readers!
Having a new paper published is always a matter of happiness for this computational chemist but this time I’m excedingly excited about anouncing the publishing of a paper in the Journal of Chemical Theory and Computation, which is my highest ranked publication so far! It also establishes the consolidation of our research group at CCIQS as a solid and competitive group within the field of theoretical and computational chemistry. The title of our paper is “In Silico design of monomolecular drug carriers for the tyrosine kinase inhibitor drug Imatinib based on calix- and thiacalix[n]arene host molecules. A DFT and Molecular Dynamics study“.
In this article we aimed towards finding a suitable (thia-) calix[n]arene based drug delivery agent for the drug Imatinib (Gleevec by Novartis), which is a broadly used powerful Tyrosine Kinase III inhibitor used in the treatment of Chronic Myeloid Leukaemia and, to a lesser extent, Gastrointestinal Stromal Tumors; although Imatinib (IMB) exhibits a bioavailability close to 90% most of it is excreted, becomes bound to serum proteins or gets accumulated in other tissues such as the heart causing several undesired side effects which ultimately limit its use. By using a molecular capsule we can increase the molecular weight of the drug thus increasing its retention, and at the same time we can prevent Imatinib to bind, in its active form, to undesired proteins.
We suggested 36 different calix and thia-calix[n]arenes (CX) as possible candidates; IMB-CX complexes were manually docked and then optimized at the B97D/6-31G(d,p) level of theory; Stephan Grimme’s B97D functional was selected for its inclusion of dispersion terms, so important in describing π-π interactions. Intermolecular interaction energies were calculated under the Natural Bond Order approximation; a stable complex was needed but a too stable complex would never deliver its drug payload! This brings us to the next part of the study. A monomolecular drug delivery agent must be able to form a stable complex with the drug but it must also be able to release it. Molecular Dynamics simulations (+100 ns) and umbrella sampling methods were used to analyse the release of the drug into the aqueous media.
Potential Mean Force profiles for the four most stable complexes for position N1 and N2 from the QM simulations are shown below (Red, complexes in the N1 position, blue, N2 position). These plots, derived from the MD simulations give us an idea of the final destination of the drug respect of the calixarene carrier. In the next image, the three preferred structures (rotaxane-like; inside; released) for the final outcome of the delivery process are shown. The stability of the complexes was also assessed by calculating the values of ΔG binding through the use of the Poisson equations.
Thanks to my co-authors Maria Eugenia Sandoval-Salinas and Dr. Rodrigo Galindo-Murillo for their enormous contributions to this work; without their hard work and commitment to the project this paper wouldn’t have been possible.
Theoretical evaluation of a reaction mechanism is all about finding the right transition states (TS) but there are no guarantees within the available methods to actually find the one we need. Chemical intuition in the proposal of a mechanism is paramount. Let’s remember that a TS is a critical point on a Potential Energy Surface (PES) that is a minimum in every dimension but one. For a PES with more than two degrees of freedom, a hyper-surface, envisioning the location of a TS is a bit tricky, in the case of a three dimensional PES (two degrees of freedom) the saddle point constitutes the location of the TS as depicted in figure 1 by a section of a revolution hyperboloid.
The following procedure considers gas phase calculations. Nevertheless, the use of the SCRF keyword activates the implicit solvent calculation of choice in order to evaluate to some degree the solvent influence on the reaction energetics at different temperatures with the use of the temperature keyword.
The first step consists of a high level optimization of all minimums involved, such as reagents, products and intermediates, with a subsequent frequency analysis that includes no imaginary eigenvalues.
In order to find the structures of the transition states we use in Gaussian the Synchronous Transit-guided Quasi-Newton method  through the keywords QST2 or QST3. In the former case, coordinates for the reagents and products are needed as input; for the latter keyword, coordinates for the TS structure guess is needed also.
#p opt=(qst2,redundant) m062x/6-31++G(d,p) freq=noraman Temperature=373.15 SCRF=(Solvent=Water)
Title card for reagents
Cartesian Coordinates for reagents
Title card for products
Cartesian Coordinates for products
#p opt=(qst3,redundant) m062x/6-31++G(d,p) freq=noraman Temperature=373.15 SCRF=(Solvent=Water)
Title Card for reagents
Cartesian Coordinates for reagents
Title card for products
Cartesian Coordinates for products
Title card for TS
Cartesian Coordinates for TS
NOTE: It is fundamental that the numbering order is kept constant throughout the molecular specifications of all two, or three, input structures. Hence, I recommend to build a set of molecules, save their structure, and then modified the coordinates on the same file to produce the following structure, that way the number for every atom will remain the same for every step.
As I wrote above, there are no guarantees of finding the right TS so many attempts are probably needed. Once we have the optimized structures for all the species involved in our mechanistic proposal we can plot their energies very simply with MS Excel the way we’ve previously described in this blog (reblogged from eutactic.wordpress.com)
Once we’ve succeeded in finding the structure of our TS we may run an Internal Reaction Coordinate (IRC) calculation. This calculation will connect the TS structure to those of the products and the reagents. Initial constant forces are required and these are commonly retrieved from the TS calculation checkpoint file through the RCFC keyword.
#p m062x/6-31++G(d,p) IRC=(Maxpoints=50,RCFC,phase=(2,1))Temperature=373.15 SCRF=(Solvent=Water) geom=allcheck
Finally, the IRC path can be visualized with GaussView from the Results menu. A successful IRC will link both structures along a single reaction coordinate proving that both reagents and products are linked by the obtained TS.
Hat tip to Howard Diaz who has become quite skillful in calculating these mechanisms as proven by his recent poster at the XII RMFQT a couple of weeks back. And as usual thanks to everyone who reads, comments, likes, recommends, rates and shares my silly little posts.