ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules

One of the grand challenges in modern theoretical chemistry is designing and implementing approximations that expedite ab initio methods without loss of accuracy. Machine learning (ML) methods are emerging as a powerful approach to constructing various forms of transferable atomistic potentials. They have been successfully applied in a variety of applications in chemistry, biology, catalysis, and solid-state physics. However, these models are heavily dependent on the quality and quantity of data used in their fitting. Fitting highly flexible ML potentials, such as neural networks, comes at a cost: a vast amount of reference data is required to properly train these models. We address this need by providing access to a large computational DFT database, which consists of more than 20 M off equilibrium conformations for 57,462 small organic molecules. We believe it will become a new standard benchmark for comparison of current and future methods in the ML potential community

Steered Molecular Dynamic Simulations Reveal Marfan Syndrome Mutations Disrupt Fibrillin-1 cbEGF Domain Mechanosensitive Balcium Binding

Marfan syndrome (MFS) is a highly variable genetic connective tissue disorder caused by mutations in the calcium binding extracellular matrix glycoprotein fibrillin-1. Patients with the most severe form of MFS (neonatal MFS; nMFS) tend to have mutations that cluster in an internal region of fibrillin-1 called the neonatal region. This region is predominantly composed of eight calcium-binding epidermal growth factor-like (cbEGF) domains, each of which binds one calcium ion and is stabilized by three highly conserved disulfide bonds. Crucially, calcium plays a fundamental role in stabilizing cbEGF domains. Perturbed calcium binding caused by cbEGF domain mutations is thus thought to be a central driver of MFS pathophysiology. Using steered molecular dynamics (SMD) simulations, we demonstrate that cbEGF domain calcium binding decreases under mechanical stress (i.e. cbEGF domains are mechanosensitive). We further demonstrate the disulfide bonds in cbEGF domains uniquely orchestrate protein unfolding by showing that MFS disulfide bond mutations markedly disrupt normal mechanosensitive calcium binding dynamics. These results point to a potential mechanosensitive mechanism for fibrillin-1 in regulating extracellular transforming growth factor beta (TGFB) bioavailability and microfibril integrity. Such mechanosensitive smart features may represent novel mechanisms for mechanical hemostasis regulation in extracellular matrix that are pathologically activated in MFS

Analysis of State-Specific Vibrations Coupled to the Unidirectional Energy Transfer in Conjugated Dendrimers

The nonadiabatic excited-state molecular dynamics (NA-ESMD) method and excited-state instantaneous normal modes (ES-INMs) analyses have been applied to describe the state-specific vibrations that participate in the unidirectional energy transfer between the coupled chromophores in a branched dendrimeric molecule. Our molecule is composed of two-, three-, and four-ring linear poly(phenyleneethynylene) (PPE) units linked through meta-substitutions. After an initial laser excitation, an ultrafast sequential S3 → S 2 → S1 electronic energy transfer from the shortest to longest segment takes place. During each Sn → Sn-1 (n = 3, 2) transition, ES-INM(Sn) and ES-INM(Sn-1) analyses have been performed on Sn and Sn-1 states, respectively. Our results reveal a unique vibrational mode localized on the Sn state that significantly matches with the corresponding nonadiabatic coupling vector dn,(n-1). This mode also corresponds to the highest frequency ES-INM(Sn) and it is seen mainly during the electronic transitions. Furthermore, its absence as a unique ES-INM(S n-1) reveals that state-specific vibrations play the main role in the efficiency of the unidirectional Sn → Sn-1 electronic and vibrational energy funneling in light-harvesting dendrimers.Fil: Soler, Miguel A.. Universidad Nacional de Quilmes; ArgentinaFil: Roitberg, Adrián E.. University of Florida; Estados UnidosFil: Nelson, Tammie. Los Alamos National High Magnetic Field Laboratory; Estados UnidosFil: Tretiak, Sergei. Los Alamos National High Magnetic Field Laboratory; Estados UnidosFil: Fernández Alberti, Sebastián. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Submaximal Oviposition Rates in a Mymarid Parasitoid: Choosiness Should Not Be Ignored

Cronin and Strong (1993a, b) examined the oviposition behavior of Anagarus delicatus Dozier (Hymenoptera: Mymaridae), an egg parasitoid of the leafhopper Prokelisia marginate Van Duzee (Homoptera: Delphacidae). They reported oviposition rates that were lower than predicted if the rate of egg-laying was maximized. Cronin and Strong (1993a) considered, and subsequently rejected, several “rules of thumb” (Stephens and Krebs 1986) as explanations for the observed patterns of patch departure. They observed that hosts on leaves experience density-independent mortality due to leaf senescence. Based on that, they advanced the hypothesis that submaximal oviposition rates in A. delicatus are best explained as risk-spreading by the parasitoid. (That is, by laying a small number of eggs on many leaves, the parasitoid increases the probability that some of her offspring will survive; Cronin and Strong 1993a.) An alternative hypothesis (Rosenheim and Mangel 1994) suggests that by distributing the eggs among several leaves, A. delicatus avoids self-superparasitism. Here, we take a somewhat different approach than those provided above to explain an additional observation of Cronin and Strong (1993a): female wasps rejected most of the hosts that they had probed. In so doing, we argue that rate maximization was an inappropriate prediction for A. delicatus, and in light of the life history parameters of this species, egg limitation is more suitable. Furthermore, egg limitation, when combined with one of the proposed explanations for the distribution of eggs, can explain the high rejection level of potential hosts