Category Archives: Computational Chemistry

I’m putting a new blog out there


As if I didn’t have enough things to do I’m launching a new blog inspired by the #365papers hashtag on Twitter and the naturalproductman.wordpress.com blog. In it I’ll hopefully list, write a femto-review of all the papers I read. This new effort is even more daunting than the actual reading of the huge digital pile of papers I have in my Mendeley To-Be-Read folder, the fattest of them all. The papers therein wont be a comprehensive review of Comp.Chem. must-read papers but rather papers relevant to our lab’s research or curiosity.

Maybe I’ll include some papers brought to my attention by the group and they could do the review. The whole endeavor might flop in a few weeks but I want to give it a shot; we’ll see how it mutates and if it survives or not. So far I haven’t managed to review all papers read but maybe this post will prompt to do so if only to save some face. The domain of the new blog is compchemdigest.wordpress.com but I think it should have included the word MY at the beginning so as to convey the idea that it is only my own biased reading list. Anyway, if you’re interested share it and subscribe, those post will not be publicized.

Unnatural DNA and Synthetic Biology


Ever since I read the highly praised article by Floyd Romesberg in Nature back in 2013 I got really interested in synthetic biology. In said article, an unnatural base pair (UBP) was not only inserted into a DNA double strand in vivo  but the organism was even able to reproduce the UBPs present in subsequent generations.

Imagen1

Romesberg’s Nucleosides. No Hydrogen bonding is formed between them!

Inserting new unnatural base pairs in DNA works a lot like editing a computer’s code. Inserting a couple UBPs in vitro is like inserting a comment; it wont make a difference but its still there. If the DNA sequence containing the UBPs can be amplified by molecular biology techniques such as PCR it means that a polymerase enzyme is able to recognize it and place it in site, this is equivalent to inserting a ‘hello world’ section into a working code; it will compile but it’s pretty much useless. Inserting these UBPs in vivo means that the organism is able to thrive despite the large deformation in a short section of its genetic code, but having it replicated by the chemical machinery of the nucleus is an amazing feat that only a few molecules could allow.

The ultimate goal of synthetic biology would be to find a UBP which codes effectively and purposefully during translation of DNA.This last feat would be equivalent to inserting a working subroutine in a program with a specific purpose. But not only could the use of UBPs serve for the purposes of expanding the genetic code from a quaternary (base four) to a senary (base six) system: the field of DNA origami could also benefit from having an expansion in the chemical and structural possibilities of the famous double helix; marking and editing a sequence would also become easier by having distinctive sections with nucleotides other than A, T, C and G.

It is precisely in the concept of double helix that our research takes place since the available biochemical machinery for translation and replication can only work on a double helix, else, the repair mechanisms get activated or the DNA will just stop serving its purpose (i.e. the code wont compile).

My good friend, Dr. Rodrigo Galindo and I have worked on the simulation of Romesberg’s UBPs in order to understand the underlying structural, dynamical and electronic causes that made them so successful and to possibly design more efficient UBPs based on a set of general principles. A first paper has been accepted for publication in Phys.Chem.Chem.Phys. and we’re very excited for it; more on that in a future post.

Grimme’s Dispersion DFT-D3 in Gaussian #CompChem


I was just asked if it is possible to perform DFT-D3 calculations in Gaussian and my first answer was to use the following  keyword:

EmpiricalDispersion=GD3

which is available in G16 and G09 only in revision D, apparently.

There are also some overlays that can be used to invoke the use dispersion in various scenarios:

IOp(3/74=x) Exchange and Correlation Potentials

-77

-76

-60

-59

DSD-PBEP86 (double hybrid, DFT-D3).

PW6B95-D3.

B2PLYP-D3 (double hybrid, DFT-D3).

B97-D (DFT-D3).

IOp(3/76=x) Mixing of HF and DFT.

-33 PW6B95 and PW6B95-D3 coefficients.

IOp(3/124=x) Empirical dispersion term.

30

40

50

Force dispersion type 3 (Grimme DFT-D3).

Force dispersion type 4 (Grimme DFT-D3(BJ)).

Force dispersion type 5 (Grimme D3, PM7 version).

 

The D3 correction method of Grimme defines the van der Waals energy like:

$\displaystyle E_{\rm disp} = -\frac{1}{2} \sum_{i=1}^{N_{at}} \sum_{j=1}^{N_{at...
...{6ij}} {r_{ij,{L}}^6} +f_{d,8}(r_{ij,L})\,\frac{C_{8ij}} {r_{ij,L}^8} \right ),$

where coefficients $ C_{6ij}$ are adjusted depending on the geometry of atoms i and j. The damping D3 function for is:

$\displaystyle f_{d,n}(r_{ij}) = \frac{s_n}{1+6(r_{ij}/(s_{R,n}R_{0ij}))^{-\alpha_{n}}},$

where the values of s are adjustable parameters fit for the exchange-correlation functionals used in each calculation.

Mexican Phys.Chem. Meeting XVth edition 


For the fifth year in a row my research group has participated in this traditional meeting on theoretical and computational chemistry, now at the beautiful city of Merida in southeastern Mexico.

Several distinguished international guests included Profs. Jose Luis Mendoza (Florida State University), Adrián Roitberg (University of Florida), Vincent Ortiz (Auburn University) and Paul Ayers (McMaster U. Canada); Their contributions rounded up nicely those of household names like Drs. Alberto Vela, Gabriel Merino (CINVESTAV) (the latter was also the main organizer), Jesus Hernández-Trujillo (UNAM), Jose Luis Gazquez (UAM-I), Óscar Jimenez (Guanajuato), and so many others who were also present.

My students presented four posters summarized below:

1) Maru Sandoval and Gustavo Mondragón on Photosynthesis, particularly the search for exciton transference mechanisms in both natural and theoretical arrangements of photosynthetic pigments. Some very exciting results have been observed; their publication is really near.


2) Raúl Torres and Gustavo Mondragón presented their work on arsenic removing calixarenes, published earlier this year, and the extension of said work to As(III) acids. Graphene oxide is now considered in our simulations as per the experimental work of our colleagues, Prof. Reyes Sierra and Prof. Eddie Lopez-Honorato.


3) Marco Diaz, Guillermo Caballero, Gustavo Mondragón and Raúl Torres had this poster on the calculation of sigma holes as descriptors for predicting pka values in organic acids. Their +1600 calculations project has found the best levels of theory (and ruled out some like B3LYP, of course) with some nice correlations. Yet, much work is still to be done but we’re on the right track.


4) Durbis Castillo presented his work on molecular docking and dynamics of a large library of HIV-1 entry inhibitors for which he uses the suite MAESTRO as a continuation of another project of ours. His enormous library is now in the hundredths of thousands and although we’re facing some technical difficulties, Durbis is thriving in his search. This is our first serious attempt towards a more mature drug discovery project; a manuscript should be ready in the first part of next year.


This guys and the rest of the lab who weren’t present are the ones who make our research flourish and they’ve all earned a day or two at the beach!

Here’s to fifteen more years of RMFQT!

Tribology – New paper in JPC A


Tribology isn’t exactly an area with which us chemists are most familiar, yet chemistry has a great impact on this branch of physics of high industrial importance. Tribology is basically the science which studies the causes and consequences of friction between surfaces. 

The plastic bag industry requires the use of chemical additives to reduce the electrostatic adherence between sheets of plastic. My good old friend Dr. Armando Gama has studied through Dissipative Particle Dynamics (DPD) coarse-grained simulations the friction coefficients of having two slightly different molecules: erukamide and behenamide, which only differ in the presence of a double bond between carbon atoms 12 and 13 (Fig1).

picture1

Fig 1

In order to study the electronic aspects that give rise to different tribological effects in these very similar molecules, four chains of each kind were bounded to a frozen graphene surface (four bonds apart to prevent steric crowding) and were optimized at the B97D/6-31G(d,p) level of theory.

 

 

Double bonds in erukamide pile together through pi-pi stacking interactions (Fig2) which are absent in behenamide which is why these last ones are able to slide better between each other (Fig3). Interaction energies calculated for the inner chains at the same level of theory are 44.21 and 34.46 kcal/mol for erukamide and behenamide, respectively. As per the suggestion of a referee we extended the calculations to a 2D system by placing seven molecules on graphene, which once again was kept at the optimized geometry of its isolated state, at four bonds of separation in order to prevent steric crowding (Fig 4).

picture4

Fig 4

This calculations clearly represent a limit case with a high density covering of the surface, but they nevertheless reflect the observed trend that behenamide works better than erukamide in reducing the static friction coefficient between sheets.

The paper is now available at JPC-A. Thanks to Dr. Gama for this great opportunity to work with his team, I know it wont be the last.

New paper in PCCP: CCl3 reduced to CH3 through σ-holes #CompChem


I found it surprising that the trichloromethyl group could be chemically reduced into a methyl group quite rapidly in the presence of thiophenol, but once again a failed reaction in the lab gave us the opportunity to learn some nuances about the chemical reactivity of organic compounds. Even more surprising was the fact that this reduction occured through a mechanism in which chlorine atoms behave as electrophiles and not as nucleophiles.

We proposed the mechanism shown in figure 1 to be consistent with the 1H-NMR kinetic experiment (Figure 2) which shows the presence of the intermediary sulfides and leads to the observed phenyl-disulfide as the only isolable byproduct. The proposed mechanism invokes the presence of σ-holes on chlorine atoms to justify the attack of thiophenolate towards the chlorine atom leaving a carbanion behind during the first step. The NMR spectra were recorded at 195K which implies that the energy barriers had to be very low; the first step has a ~3kcal/mol energy barrier at this temperature.

 

fig1-blog

Figure 1 – Calculated mechanism BMK/6-31G(d,p) sigma holes are observed on Cl atoms

fig2-blog

1H NMR of the chemical reduction of the trichloromethyl group. Sulfide 4 is the only observed byproduct

To calculate these energy barriers we employed the BMK functional as implemented in Gaussian09. This functional came highly recommended to this purpose and I gotta say it delivered! The optimized geometries of all transition states and intermediaries were then taken to an MP2 single point upon which the maximum electrostatic potential on each atom (Vmax) was calculated with MultiWFN. In figure 3 we can observe the position and Vmax value of σ-holes on chlorine atoms as suggested by the mapping of electrostatic potential on the electron density of various compounds.

We later ran the same MP2 calculations on other CCl3 groups and found that the binding to an electron withdrawing group is necessary for a σ-hole to be present. (This fact was already present in the literature, of course, but reproducing it served us to validate our methodology.)

fig3-blog

Figure 3 – Sigma holes found on other CCl3 containing compounds

We are pleased to have this work published in PhysChemChemPhys. Thanks to Dr. Moisés Romero for letting us into his laboratory and to Guillermo Caballero for his hard work both in the lab and behind the computer; Guillermo is now bound to Cambridge to get his PhD, we wish him every success possible in his new job and hope to see him again in a few years, I’m sure he will make a good job at his new laboratory.

Quick note on WFN(X) files and MP2 calculations #G09 #CompChem


A few weeks back we wrote about using WFN(X) files with MultiWFN in order to find σ-holes in halogen atoms by calculating the maximum potential on a given surface. We later found out that using a chk file to generate a wfn(x) file using the guess=(read,only) keyword didn’t retrieve the MP2 wavefunction but rather the HF wavefunction! Luckily we realized this problem very quickly and were able to fix it. We tried to generate the wfn(x) file with the following keywords at the route section

#p guess=(read,only) density=current

but we kept retrieving the HF values, which we noticed by running the corresponding HF calculation and noticing that every value extracted from the WFN file was exactly the same.

So, if you want a WFN(X) file for post processing an MP2 (or any other post-HartreFock calculation for that matter) ask for it from the beginning of your calculation in the same job. I still don’t know how to work around this or but will be happy to report it whenever I do.

PS. A sincere apology to all subscribers for getting a notification to this post when it wasn’t still finished.

A New Graduate Student


With pleasure I announce that last week our very own Gustavo “Gus” Mondragón became the fifth undergraduate student from my lab to defend his BSc thesis and it has to be said that he did it admirably so.

Gus has been working with us for about a year now and during this time he not only worked on his thesis calculating excited states for bacteriochlorophyl pigments but also helped us finishing some series of calculations on calix[n]arene complexes of Arsenic (V) acids, which granted him the possibility to apear as a co-author of the manuscript recently published in JIPH. Back in that study he calculated the interaction energies between a family of calix macrocycles and arsenic acid derivatives in order to develop a suitable extracting agent.

For his BSc thesis, Gus reproduced the UV-Vis absorption spectra of bacteriochlorophyll-a pigments found in the Fenna-Matthews-Olson complex of photosynthetic purple bacteria using Time Dependent Density Functional Theory (TD-DFT) with various levels of theory, with PBEPBE yielding the best results among the tried set. These calculations were performed at the crystallographic conformation and at the optimized structure, also, in vacuo results were compared to those in implicit solvent (SMD, MeOH). He will now move towards his masters where he will further continue our research on photosynthesis.

Thank you, Gustavo, for your hard work and your sense of humor. Congratulations on this step and may many more successes come your way.

 

New paper in Tetrahedron #CompChem “Why U don’t React?”


Literature in synthetic chemistry is full of reactions that do occur but very little or no attention is payed to those that do not proceed. The question here is what can we learn from reactions that are not taking place even when our chemical intuition tells us they’re feasible? Is there valuable knowledge that can be acquired by studying the ‘anti-driving force’ that inhibits a reaction? This is the focus of a new manuscript recently published by our research group in Tetrahedron (DOI: 10.1016/j.tet.2016.05.058) which was the basis of Guillermo Caballero’s BSc thesis.

fig1

 

It is well known in organic chemistry that if a molecular structure has the possibility to be aromatic it can somehow undergo an aromatization process to achieve this more stable state. During some experimental efforts Guillermo Caballero found two compounds that could be easily regarded as non-aromatic tautomers of a substituted pyridine but which were not transformed into the aromatic compound by any means explored; whether by treatment with strong bases, or through thermal or photochemical reaction conditions.

fig2

These results led us to investigate the causes that inhibits these aromatization reactions to occur and here is where computational chemistry took over. As a first approach we proposed two plausible reaction mechanisms for the aromatization process and evaluated them with DFT transition state calculations at the M05-2x/6-31+G(d,p)//B3LYP/6-31+G(d,p) levels of theory. The results showed that despite the aromatic tautomers are indeed more stable than their corresponding non-aromatic ones, a high activation free energy is needed to reach the transition states. Thus, the barrier heights are the first reason why aromatization is being inhibited; there just isn’t enough thermal energy in the environment for the transformation to occur.

fig3

But this is only the proximal cause, we went then to search for the distal causes (i.e. the reasons behind the high energy of the barriers). The second part of the work was then the calculation of the delocalization energies and frontier molecular orbitals for the non-aromatic tautomers at the HF/cc-pVQZ level of theory to get insights for the large barrier heights. The energies showed a strong electron delocalization of the nitrogen’s lone pair to the oxygen atom in the carbonyl group. Such delocalization promoted the formation of an electron corridor formed with frontier and close-to-frontier molecular orbitals, resembling an extended push-pull effect. The hydrogen atoms that could promote the aromatization process are shown to be chemically inaccessible.

fig4

Further calculations for a series of analogous compounds showed that the dimethyl amino moiety plays a crucial role avoiding the aromatization process to occur. When this group was changed for a nitro group, theoretical calculations yielded a decrease in the barrier high, enough for the reaction to proceed. Electronically, the bonding electron corridor is interrupted due to a pull-pull effect that was assessed through the delocalization energies.

The identity of the compounds under study was assessed through 1H, 13C-NMR and 2D NMR experiments HMBC, HMQC so we had to dive head long into experimental techniques to back our calculations.

The “art” of finding Transition States Part 2


Last week we posted some insights on finding Transitions States in Gaussian 09 in order to evaluate a given reaction mechanism. A stepwise methodology is tried to achieve and this time we’ll wrap the post with two flow charts trying to synthesize the information given. It must be stressed that knowledge about the chemistry of the reaction is of paramount importance since G09 cannot guess the structure connecting two minima on its own but rather needs our help from our chemical intuition. So, without further ado here is the remainder of Guillermo’s post.

 

METHOD 3. QST3. For this method, you provide the coordinates of your reagents, products and TS (in that order) and G09 uses the QST3 method to find the first order saddle point. As for QST2 the numbering scheme must match for all the atoms in your three sets of coordinates, again, use the connection editor to verify it. Here is an example of the input file.

link 0
--blank line--
#p b3lyp/6-31G(d,p) opt=(qst3,calcfc) geom=connectivity freq=noraman
--blank line--
Charge Multiplicity
Coordinates of reagents
--blank line—
Charge Multiplicity
Coordinates of products
--blank line--
Charge Multiplicity
Coordinates of TS
--blank line---

As I previously mentioned, it happens that you find a first order saddle point but does not correspond to the TS you want, you find an imaginary vibration that is not the one for the bond you are forming or breaking. For these cases, I suggest you to take that TS structure and manually modify the region that is causing you trouble, then use method 2.

METHOD 4. When the previous methods fail to yield your desired TS, the brute force way is to acquire the potential energy surface (PES) and visually locate your possible TS. The task is to perform a rigid PES scan, for this, the molecular structure must be defined using z-matrix. Here is an example of the input file.

link 0
--blank line--
#p b3lyp/6-31G(d,p) scan test geom=connectivity
--blank line--
Charge Multiplicity
Z-matrix of reagents (or products)
--blank line--

In the Z-matrix section you must specify which variables (B, A or D) you want to modify. First, locate the variables you want to modify (distance B, angle A, or dihedral angle D). Then modify those lines within the Z-matrix, here is an example.

B1       1.41     3          0.05
A1       104.5   2          1.0

What you are specifying with this is that the variable B1 (a distance) is going to be stepped 3 times by 0.05. Then variable A1 (an angle) is going to be stepped 2 times by 1.0. Thus, a total of 12 energy evaluations will be performed. At the end of the calculation open the .log file in gaussview and in Results choose the Scan… option. This will open a 3D surface where you should locate the saddle point, this is an educated guess, so take the structure you think corresponds to your TS and use it for method 2.

I have not fully explored this method so I encourage you to go to Gaussian.com and thoroughly review it.

Once you have found your TS structure and via the imaginary vibration confirmed that is the one you are looking for the next step is to verify that your TS connects both your reagents and products in the potential energy surface. For this, an Intrinsic Reaction Coordinate (IRC) calculation must be performed. Here is an example of the input file for the IRC.

link 0
--blank line--
#p b3lyp/6-31G(d,p) irc=calcfc geom=connectivity
--blank line--
Charge Multiplicity
Coordinates of TS
--blank line--

With this input, you ask for an IRC calculation, the default numbers of steps are 20 for each side of your TS in the PES; you must specify the coordinates of your TS or take them from the .chk file of your optimization. In addition, an initial force constant calculation must be made. It often occurs that the calculation fails in the correction step, thus, for complicated cases I hardly suggest to use irc=calcall, this will consume very long time (even days) but there is a 95% guaranty. If the number of points is insufficient you can put more within the route section, here is such an example for a complicated case.

link 0
--blank line--
#p b3lyp/6-31G(d,p) irc=(calcall,maxpoints=80) geom=connectivity
--blank line--
Charge Multiplicity
Coordinates of TS
--blank line--

With this route section, you are asking to perform an IRC calculation with 80 points on each side of the PES, calculating the force constants at every point. For an even complicated case try adding the scf=qc keyword in the route section, quadratic convergence often works better for IRC calculations.

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