Author Archives: joaquinbarroso
Photosynthesis, the basis of life on Earth, is based on the capacity a living organism has of capturing solar energy and transform it into chemical energy through the synthesis of macromolecules like carbohydrates. Despite the fact that most of the molecular processes present in most photosynthetic organisms (plants, algae and even some bacteria) are well described, the mechanism of energy transference from the light harvesting molecules to the reaction centers are not entirely known. Therefore, in our lab we have set ourselves to study the possibility of some excitonic transference mechanisms between pigments (chlorophyll and its corresponding derivatives). It is widely known that the photophysical properties of chlorophylls and their derivatives stem from the electronic structure of the porphyrin and it is modulated by the presence of Mg but its not this ion the one that undergoes the main electronic transitions; also, we know that Mg almost never lies in the same plane as the porphyrin macrocycle because it bears a fifth coordination whether to another pigment or to a protein that keeps it in place (Figure 1).
During our calculations of the electronic structure of the pigments (Bacteriochlorophyll-a, BChl-a) present in the Fenna-Matthews-Olson complex of sulfur dependent bacteria we found that the Mg²⁺ ion at the center of one of these pigments could in fact create an intermolecular interaction with the C=C double bond in the phytol fragment which lied beneath the porphyrin ring.
This would be the first time that a dihapto coordination is suggested to occur in any chlorophyll and that on itself is interesting enough but we took it further and calculated the photophysical implications of having this fifth intramolecular dihapto coordination as opposed to a protein or none for that matter. Figure 3 shows that the calculated UV-Vis spectra (calculated with Time Dependent DFT at the CAM-B3LYP functional and the cc-pVDZ, 6-31G(d,p) and 6-31+G(d,p) basis sets). A red shift is observed for the planar configuration, respect to the five coordinated species (regardless of whether it is to histidine or to the C=C double bond in the phytyl moiety).
Before calculating the UV-Vis spectra, we had to unambiguously define the presence of this observed interaction. To that end we calculated to a first approximation the C-Mg Wiberg bond indexes at the CAM-B3LYP/cc-pVDZ level of theory. Both values were C(1)-Mg 0.022 and C(2)-Mg 0.032, which are indicative of weak interactions; but to take it even further we performed a non-covalent interactions analysis (NCI) under the Atoms in Molecules formalism, calculated at the M062X density which yielded the presence of the expected critical points for the η²Mg-(C=C) interaction. As a control calculation we performed the same calculation for Magnoscene just to unambiguously assign these kind of interactions (Fig 4, bottom).
This research is now available at the International Journal of Quantum Chemistry. A big shoutout and kudos to Gustavo “Gus” Mondragón for his work in this project during his masters; many more things come to him and our group in this and other research ventures.
I’ve lately reviewed a ton of papers whose titles begin with some version of “Computational studies of…“, “Theoretical studies of…” or even more subtly just subtitled “A theoretical/computational study” and even when I gotta confess this is probably something I’ve done once or twice myself, it got me thinking about the place and role of computational chemistry within chemistry itself.
As opposed to physicists, chemists are pressed to defend a utilitarian view of their work and possibly because of that view some computational chemists sometimes lose sight of their real contribution to a study, which is far from just performing a routine electronic structure calculation. I personally don’t like it when an experimental colleague comes asking for ‘some calculations’ without a clear question to be answered by them; Computational Chemistry is not an auxiliary science but a branch of physical chemistry in its own right, one that provides all the insight experiments -chemical or physical- sometimes cannot.
I’m no authority on authoring research papers but I encourage my students to think about the titles of their manuscripts in terms of what the manuscript most heavily relies on; whether it’s the phenomenon, the methodology or the object of the study, that should be further stressed on the title. Papers titled “Computational studies of…” usually are followed by ‘the object of study’ possibly overlooking the phenomenon observed throughout such studies. It is therefore a disservice to the science contained within the manuscript, just like experimental papers gain little from titles such as “Synthesis and Characterization of…“. It all comes down to finding a suitable narrative for our work, something that I constantly remind my students. It’s not about losing rigor or finding a way to oversell our results but instead to actually drive a point home. What did you do why and how. Anna Clemens, a professional scientific writer has a fantastic post on her blog about it and does it far better than I ever could. Also, when ranting on Twitter, the book Houston, we have a narrative was recommended to me, I will surely put it my to-read list.
While I’m on the topic of narratives in science, I’m sure Dr. Stuart Cantrill from Nature Chemistry wouldn’t mind if I share with you his deconstruction of an abstract. Let’s play a game and give this abstract a title in the comments section based on the information vested in it.
There’s an error message when opening some Gaussian16 output files in GaussView5 for which the message displayed is the following:
ConnectionGLOG::Parse_Gauss_Coord(). Failure reading oriented atomic coordinates. Line Number
We have shared some solutions to the GaussView handling of *chk and *.fchk files in teh past but never for *.log files, and this time Dr. Davor Šakić from the University of Zagreb in Croatia has brought to my attention a fix for this error. If “Dipole orientation” with subsequent orientation is removed, the file becomes again readable by GaussView5.
Here you can download a script to fix the file without any hassle. The usage from the command line is simply:
˜$ chmod 777 Fg16TOgv5 ˜$ ./Fg16TOgv5 name.log
The first line is to change and grant all permissions to the script (use at your discretion/own risk), which in turn will take the output file name.log and yield two more files: gv5_name.log and and name.arch; the latter archive allows for easy generation of SI files while the former is formatted for GaussView5.x.
Thanks to Dr. Šakić for his script and insight, we hope you find it useful and if indeed you do please credit him whenever its due, also, if you find this or other posts in the blog useful, please let us know by sharing, staring and commenting in all of them, your feedback is incredibly helpful in justifying to my bosses the time I spent curating this blog.
Thanks for reading.
Today’s science is published mostly in English, which means that non-English speakers must first tackle the language barrier before sharing their scientific ideas and results with the community; this blog is a proof that non-native-English speakers such as myself cannot outreach a large audience in another language.
For young scientists learning English is a must nowadays but it shouldn’t shy students away from learning science in their own native tongues. To that end, the noble effort by Dr. José Cerón-Carrasco from Universidad Católica San Antonio de Murcia, in Spain, of writing a DFT textbook in Spanish constitutes a remarkable resource for Spanish-speaking computational chemistry students because it is not only a clear and concise introduction to ab initio and DFT methods but because it was also self published and written directly in Spanish. His book “Introducción a los métodos DFT: Descifrando B3LYP sin morir en el intento” is now available in Amazon. Dr. Cerón-Carrasco was very kind to invite me to write a prologue for his book, I’m very thankful to him for this opportunity.
Así que para los estudiantes hispanoparlantes hay ahora un muy valioso recurso para aprender DFT sin morir en el intento gracias al esfuerzo y la mente del Dr. José Pedro Cerón Carrasco a quien le agradezco haberme compartido la primicia de su libro
¡Salud y olé!
We’ve expanded the scope of our research interests from quantum mechanical calculations to docking and MedChem for over a year now; it has been a very interesting ride and a very rich avenue of research to explore. Durbis Castillo has led -out of his own initiative- this project and today he presents us with a guest post on the nuances of his project. Bear in mind that the detail of the calculations and a small -very targeted- tutorial on MAESTRO will be provided later in further posts and that making all this decisions required a long process of trial and error, we can only thank Dr. Antonio Romo for his help in minimizing the time this process took.
HIV is a tricky virus, and even though many of the steps included in its lifecycle are druggable, the chemical machinery making it work has been quite elusive since research groups started studying it. Highly Active Antiretroviral Therapy (HAART) works thanks to the combination of several drugs targeting different proteins such as the HIV protease or reverse transcriptase.
In 1998 the elucidation of the gp120 envelope glycoprotein crystal structure introduced a new step in the drug discovery race: HIV entry. Since drugs targeting gp120 have not been widely explored or developed, we decided to use common methodologies like docking (rigid and fit-induced) and ADME predictions to address the following question: How can we easily discover a molecule that inhibits gp120 binding to the lymphocyte CD4 receptor without having to synthesize it first? The answer was to perform a virtual screening with a bottleneck methodology based on docking calculations.
Docking methodologies are often looked as insufficient, careless or even unscientific, since the algorithms they are founded upon are not as accurate or descriptive as the ones that support DFT or ab initio calculations, for example. But there is a huge advantage to simpler operations: less computational resources are required. Then, following Russia’s example when making tanks during the WWII, why not make thousands or millions of docking calculations to quickly explore an entire chemical space and find which molecules are more likely to bind the protein?
And this is exactly what we did. We built a piperazine-based dataset of 16.3 million compounds, all of them including fragments that are reported in the medicinal chemistry literature, thus having two main characteristics, synthetic accessibility and pharmacological activity. These 16.3 million compounds were thoroughly filtered through several docking steps, each one of them being more accurate and comprehensive than the previous one, abruptly eliminating poorly fitted molecules, leaving us with a total of 275 candidates that were redocked in a different crystal structure and a different program (consensus docking).
After analyzing the ADME properties of the candidates, with descriptors such as human oral absorption and possible metabolic reactions, as well as the Induced-Fit Docking score of these molecules, ten ligands were selected as the best ones inside the analyzed chemical space. You can see ligand 255 (figure 1) as an example of the molecules that obtained the best scores throughout the docking steps.
Many of the colleague researchers related to this kind of topics asked “Why didn’t you download a set of molecules from Zinc or Maybridge?” And the answer to this question includes three aspects: first we wanted to test a combinatorial approach to drug design, second, we wanted to test whether including a piperazine as the core of the set of molecules would immediately grant them activity and high potency, and finally, a built database will always confer a higher degree of novelty to the possible hits when compared to commercially available compounds whose synthesis has already been developed. However, this last point needs to be addressed by an organic chemist since none of the molecules from our database have ever been synthesized (any takers?).
Right now, we are trying to explore further through molecular dynamics simulations using Desmond and Amber. Other future goals for this project include screening large databases of commercial and novel compounds with gp120 and other proteins involved in the HIV lifecycle. Also, we remain open to collaborate with anyone interested in taking the challenge to synthesize our molecules, as well as performing the biochemical assays to get an idea of their activity.
More details on MD simulations and the path of our first virtual hits to follow. Anyone interested in reading my thesis work can contact me through my linkedin profile at https://www.linkedin.com/in/durbisjaviercp/. An article is under preparation and will soon be submitted, stay tuned!
2017 was a complicated year for various reasons here in Mexico (and some personal health issues) but nonetheless I’m very proud of the performance of everyone at the lab whose hard work and great skills keep pushing our research forward.
Four new members joined the team and have presented their work at the national meeting for CompChem for the first time. Also, for the first time, one of my students, Gustavo Mondragón, gave a talk at this meeting with great success about his research on the Fenna Matthews Olson complex of photosynthetic bacteria.
The opportunity to attend WATOC at Munich presented me the great chance to meet wonderful people from around the world and was even kindly and undeservingly invited to write the prologue for an introductory DFT book by Prof. Pedro Cerón from Spain. I hope to Jeep up with the collaborations abroad such as the one with the Mirkin group at Nortgwestern and the one with my dear friend Kunsagi-Mate Sándor at Pecsi Tudomanyegyetem (Hungary), among many others; I’m thankful for their trust in our capabilities.
Two members got their BSc degrees, Marco an Durbis, the latter also single handedly paved the way for us to develop a new research line on the in silico drug developing front; his relentless work has also been praised by the QSAR team at the Institute of Chemistry with which he has collaborated by performing toxicity calculations for the agrochemical industry as well as by designing educational courses aimed to the dissemination of our work and QSAR in general among regulatory offices and potential clients. We’re sad to see him go next fall but at the same time we’re glad to know his scientific skills will further develop.
I cannot thank the team enough: Alejandra Barrera, Gustavo Mondragón, Durbis Castillo, Fernando Uribe, Juan Guzman, Alberto Olmedo, Eduardo Cruz, Ricardo Loaiza and Marco Garcia; may 2018 be a great year for all of you.
And to all the readers thank you for your kind words, I’m glad this little space which is about to become nine years old is regarded as useful; to all of you I wish a great 2018!
One of the most popular posts in this blog has to do with calculating Fukui indexes, however, when dealing with a large number of molecules, our described methodology can become cumbersome since it requires to manually extract the population analysis from two or three different output files and then performing the arithmetic on them separately with a spreadsheet or something.
Our new team member Ricardo Loaiza has written a python script that takes the three aforementioned files and yields a .csv file with the calculated Fukui indexes, and it even points out which of the atoms exhibit the largest values so if you have a large molecule you don’t have to manually check for them. We have also a batch version which takes all the files in any given directory and performs the Fukui calculations for each, provided it can find file triads with the naming requirements described below.
Output files must be named filename.log (the N electrons reference state), filename_plus.log (the state with N+1 electrons) and filename_minus.log (the N-1 electrons state). Another restriction is that so far these scripts only work with NBO population analysis as provided by the NBO3.1 program available in the various versions of Gaussian. I imagine the listing is similar in NBO5.x and NBO6.x and so it should work if you do the population analysis with them.
The syntax for the single molecule version is:
python fukui.py filename.log filename_minus.log filename_plus.log
For the batch version is:
(Por Lote means In Batch in Spanish.)
These scripts are available via GitHub. We hope you find them useful, and you do please let us know whether here at the comments section or at our GitHub site.
We’ve covered some common errors when dealing with formatted checkpoint files (*.fchk) generated from Gaussian, specially when analyzed with the associated GaussView program. (see here and here for previous posts on the matter.)
Prof. Neal Zondlo from the University of Delaware kindly shared this solution with us when the following message shows up:
CConnectionGFCHK::Parse_GFCHK() Missing or bad data: Rbond Line Number 1234
The Rbond label has to do with the connectivity displayed by the visualizer and can be overridden by close examination of the input file. In the example provided by Prof. Zondlo he found the following line in the connectivity matrix of the input file:
2 9 0.0
which indicates a zero bond order between atoms 2 and 9, possibly due to their proximity. He changed the line to simply
So editing the connectivity of your atoms in the input can help preventing the Rbond message.
I hope this helps someone else.
A yearly tradition of this Comp.Chem. lab and many others throughout our nation is to attend the Mexican Meeting on Theoretical Physical Chemistry to share news, progress and also a few drinks and laughs. This year the RMFQT was held in Puebla and although unfortunately I was not able to attend this lab was proudly represented by its current members. Gustavo Mondragón gave a talk about his progress on his photosynthesis research linking to the previous work of María Eugenia Sandoval already presented in previous editions; kudos to Gustavo for performing remarkably and thanks to all those who gave us their valuable feedback and criticism. Also, five posters were presented successfully, I can only thank the entire team for representing our laboratory in such an admirable way, and a special mention to the junior members, I hope this was the first of many scientific events they attend and may you deeply enjoy each one of them.
Among the invited speakers, the RMFQT had the honor to welcome Prof. John Perdew (yes, the P in PBE); the team took the opportunity of getting a lovely picture with him.
Here is the official presentation of the newest members of our group:
Alejandra Barrera (hyperpolarizabilty calculations on hypothetical poly-calyx[n]arenes for the search of NLO materials)
Fernando Uribe (Interaction energy calculations for non-canonical nucleotides)
Juan Guzmán (Reaction mechanisms calculations for catalyzed organic reactions)
We thank the organizing committee for giving us the opportunity to actively participate in this edition of the RMFQT, we eagerly await for next year as every year.