Out of some +1000 twitter accounts I follow about a quarter are related computational chemistry. The following public list isn’t comprehensive and prone to errors and contains researchers, programmers, students, journals, products and companies who gravitate around the use of in silico methods for the understanding and design of chemical and biochemical compounds.
Most organic chemistry deals with closed shell calculations, but every once in a while you want to calculate carbenes, free radicals or radical transition states coming from a homolytic bond break, which means your structure is now open shell. Closed shell systems are characterized by having doubly occupied molecular orbitals, that is to say the calculation is ‘restricted’: Two electrons with opposite spin occupy the same orbital.
As is the case of proteins, the functioning of DNA is highly dependent on its 3D structure and not just only on its sequence but the difference is that protein tertiary structure has an enormous variety whereas DNA is (almost) always a double helix with little variations. The canonical base pairs AT, CG stabilize the famous double helix but the same cannot be guaranteed when non-canonical -unnatural- base pairs (UBPs) are introduced.
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.
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. Inserting new unnatural base pairs in DNA works a lot like editing a computer’s code.
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.
The goal of any scientist is to generate new knowledge and then it would be a fair assumption that most scientists are inclined to share that knowledge with as many people as possible in a noble effort to improve the world in which we live; in fact, that is the very -underlying- reason why we publish articles of all our research, so every bit of knowledge generated in our labs goes not only on record but is available for testing and questioning.
In the past I’ve avoided this topic for various reasons. First, because I strongly believe that focusing on labels perpetuates them, and as scientists, we should always rise above them, for is science and not scientists what’s important. I remember my former PhD advisor, Prof.
Like everybody else, we are doing a brief recount of the achievements of this lab during 2016 if for no better reason because it helps me map my annual report. We published seven articles: A Mixed DFT-MD Methodology for the In Silico Development of Drug Releasing Macrocycles.
(Ah! Mathematicians, did you see what I did there?) There are a number of appalling videos on line in which iPhones are destroyed by various means.
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.