Intramolecular Diels-Alder Reaction of a Biphenyl Group in a Strained meta-Quaterphenylene Acetylene.

At elevated temperatures, a strained, cyclic meta-quaterphenylene acetylene undergoes an intramolecular cyclization reaction to form benz[e]indeno[1,2,3-hi]acephenanthrylene. This reaction represents an example of a Diels-Alder reaction at the 2-, 1-, 1'-, and 2'-positions of a biphenyl derivative, a region analogous to the bay regions of perylene and other periacenes. The reaction proceeds cleanly with high conversion. Kinetics studies of a methylated derivative reveal that the ΔG‡ for the reaction is ∼40-41 kcal/mol, and computational models predict a similar value of Grel for the transition state of a concerted [4 + 2]-cycloaddition.

The Impacts of the Molecular Education and Research Consortium in Undergraduate Computational Chemistry on the Careers of Women in Computational Chemistry.

The Molecular Education and Research Consortium in Undergraduate Computational Chemistry (MERCURY) has supported a diverse group of faculty and students for over 20 years by providing computational resources as well as networking opportunities and professional support. The consortium comprises 38 faculty (42% women) at 34 different institutions, who have trained nearly 900 undergraduate students, more than two-thirds of whom identify as women and one-quarter identify as students of color. MERCURY provides a model for the support necessary for faculty to achieve professional advancement and career satisfaction. The range of experiences and expertise of the consortium members provides excellent networking opportunities that allow MERCURY faculty to support each other's teaching, research, and service needs, including generating meaningful scientific advancements and outcomes with undergraduate researchers as well as being leaders at the departmental, institutional, and national levels. While all MERCURY faculty benefit from these supports, the disproportionate number of women in the consortium, relative to their representation in computational sciences generally, produces a sizable impact on advancing women in the computational sciences. In this report, the women of MERCURY share how the consortium has benefited their careers and the careers of their students.

Undergraduate structural biology education: A shift from users to developers of computation and simulation tools.

The use of theory and simulation in undergraduate education in biochemistry, molecular biology, and structural biology is now common, but the skills students need and the curriculum instructors have to train their students are evolving. The global pandemic and the immediate switch to remote instruction forced instructors to reconsider how they can use computation to teach concepts previously approached with other instructional methods. In this review, we survey some of the curricula, materials, and resources for instructors who want to include theory, simulation, and computation in the undergraduate curriculum. There has been a notable progression from teaching students to use discipline-specific computational tools to developing interactive computational tools that promote active learning to having students write code themselves, such that they view computation as another tool for solving problems. We are moving toward a future where computational skills, including programming, data analysis, visualization, and simulation, will no longer be considered an optional bonus for students but a required skill for the 21st century STEM (Science, Technology, Engineering, and Mathematics) workforce; therefore, all physical and life science students should learn to program in the undergraduate curriculum.

Computational Models for Activated Human MEK1: Identification of Key Active Site Residues and Interactions.

MEK1 is a protein kinase in the MAPK cellular signaling pathway that is notable for its dual specificity and its potential as a drug target for a variety of cancer therapies. While much is known about the key role of MEK1 in signaling events, understanding of the structural features that sustain MEK1 function remains limited because of the absence of crystal or NMR structural insights into the phosphorylated and activated form of MEK1. In this work, homology modeling was used to overcome this limitation and generate computational models of the doubly phosphorylated active MEK1 conformation. A variety of models were generated using crystal structures of active protein kinases as homology model templates. These models were equilibrated using molecular dynamics simulations, and each model was validated against several known structural characteristics of activated kinases. The best model structures were used in docking studies with ATP and a small peptide sequence that represents the activation loop of ERK2 to identify the most important residues in stabilizing protein docking and phosphorylation. These results provide insights for the pursuit of structure-guided mutagenesis and drug design.

Communication: resolving the three-body contribution to the lattice energy of crystalline benzene: benchmark results from coupled-cluster theory.

Coupled-cluster theory including single, double, and perturbative triple excitations [CCSD(T)] has been applied to trimers that appear in crystalline benzene in order to resolve discrepancies in the literature about the magnitude of non-additive three-body contributions to the lattice energy. The present results indicate a non-additive three-body contribution of 0.89 kcal mol(-1), or 7.2% of the revised lattice energy of -12.3 kcal mol(-1). For the trimers for which we were able to compute CCSD(T) energies, we obtain a sizeable difference of 0.63 kcal mol(-1) between the CCSD(T) and MP2 three-body contributions to the lattice energy, confirming that three-body dispersion dominates over three-body induction. Taking this difference as an estimate of three-body dispersion for the closer trimers, and adding an Axilrod-Teller-Muto estimate of 0.13 kcal mol(-1) for long-range contributions yields an overall value of 0.76 kcal mol(-1) for three-body dispersion, a significantly smaller value than in several recent studies.

Impact of geometry optimization on base-base stacking interaction energies in the canonical A- and B-forms of DNA.

Base stacking is known to make an important contribution to the stability of DNA and RNA, and accordingly, significant efforts are ongoing to calculate stacking energies using ab initio quantum mechanical methods. To date, impressive improvements have been made in the model chemistries used to perform stacking energy calculations, including extensions that include robust treatments of electron correlation with extended basis sets, as required to treat interactions where dispersion makes a significant contribution. However, those efforts typically use rigid monomer geometries when calculating the interaction energies. To overcome this, in the present work, we describe a novel internal coordinate definition that allows the relative, intermolecular orientation of stacked base monomers to be constrained during geometry optimizations while allowing full optimization of the intramolecular degrees of freedom. Use of the novel reference frame to calculate the impact of full geometry optimization versus constraining the bases to be planar on base monomer stacking energies, combined with density-fitted, spin-component scaling MP2 treatment of electron correlation, shows that full optimization makes the average stacking energy more favorable by -3.4 and -1.5 kcal/mol for the canonical A and B conformations of the 16 5' to 3' base stacked monomers. Thus, treatment of geometry optimization impacts the stacking energies to an extent similar to or greater than the impact of current state of the art increases in the rigor of the model chemistry itself used to treat base stacking. Results also indicate that stacking favors the B-form of DNA, though the average difference versus the A-form decreases from -2.6 to -0.6 kcal/mol when the intramolecular geometry is allowed to fully relax. However, stacking involving cytosine is shown to favor the A-form of DNA, with that contribution generally larger in the fully optimized bases. The present results show the importance of allowing geometry optimization, as well as properly treating the appropriate model chemistry, in studies of nucleic acid base stacking.