Convergent loss of chemoreceptors across independent origins of slave-making in ants

The evolution of an obligate parasitic lifestyle often leads to the reduction of morphological and physiological traits, which may be accompanied by loss of genes and functions. Slave-maker ants are social parasites that exploit the work force of closely related ant species for social behaviours such as brood care and foraging. Recent divergence between these social parasites and their hosts enables comparative studies of gene family evolution. We sequenced the genomes of eight ant species, representing three independent origins of ant slavery. During the evolution of eusociality, chemoreceptor genes multiplied due to the importance of chemical communication in societies. We investigated evolutionary patterns of chemoreceptors in relation to slave-making in ants. We found that slave-maker ant genomes harboured only half as many gustatory receptors as their hosts, potentially mirroring the outsourcing of foraging tasks to host workers. In addition, parasites had fewer odorant receptors and their loss shows patterns of convergence across origins of parasitism, representing a rare case of convergent molecular evolution. This convergent loss of specific odorant receptors suggests that selective deprivation of receptors is adaptive. The 9-exon odorant receptor subfamily, previously linked to social evolution in insects, was significantly enriched for convergent loss across the three origins of slavery in our study, indicating that the transition to social parasitism in ants is accompanied by the loss of receptors that are likely important for mediating eusocial behaviour. Overall, gene loss in slave-maker ants suggests that a switch to a parasitic lifestyle accompanies relaxed selection on chemical perception.

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

We describe the structure and optimization of the Open Force Field 1.0.0 small molecule force field, code-named Parsley. Parsley uses the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism in which parameter types are assigned directly by chemical perception, in contrast to traditional atom type-based approaches. This method provides a natural means to incorporate increasingly diverse chemistry without needlessly increasing force field complexity. In this work, we present essentially a full optimization of the valence parameters in the force field. The optimization was carried out with the ForceBalance tool and was informed by reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These data were computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. Tests of the resulting force field against compounds and data types outside the training set show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields. <br>

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

We describe the structure and optimization of the Open Force Field 1.0.0 small molecule force field, code-named Parsley. Parsley uses the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism in which parameter types are assigned directly by chemical perception, in contrast to traditional atom type-based approaches. This method provides a natural means to incorporate increasingly diverse chemistry without needlessly increasing force field complexity. In this work, we present essentially a full optimization of the valence parameters in the force field. The optimization was carried out with the ForceBalance tool and was informed by reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These data were computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. Tests of the resulting force field against compounds and data types outside the training set show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields. <br>

Development and Benchmarking of Open Force Field v1.0.0, the Parsley Small Molecule Force Field

We describe the structure and optimization of the Open Force Field 1.0.0 small molecule force field, code-named Parsley. Parsley uses the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism in which parameter types are assigned directly by chemical perception, in contrast to traditional atom type-based approaches. This method provides a natural means to incorporate increasingly diverse chemistry without needlessly increasing force field complexity. In this work, we present essentially a full optimization of the valence parameters in the force field. The optimization was carried out with the ForceBalance tool and was informed by reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These data were computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. Tests of the resulting force field against compounds and data types outside the training set show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields. <br>

ChemPer: An Open Source Tool for Automatically Generating SMIRKS Patterns

<div>Force fields are used in a variety of research fields including computer-aided drug design, biomaterials, and polymer chemistry. However, force fields also continue to limit the accuracy of predictions of physical properties. Current parameterization of these force fields involves a huge amount of human effort -- often years of work -- and depends heavily on the chemical intuition of those involved. The Open Force Field Initiative is working to replace this tedious process with an automated machinery to learn parameters and chemical perception. Our new SMIRKS-based force field format, SMIRNOFF, allows all parameter types to be defined independently. This allows for easier extension compared to the traditional atom type-based force fields where the chemical perception of all parameter types is intertwined. </div><div>We will need to be capable of programmatically learning SMIRKS patterns in order to fully automate force field parameterization. In this work, we present ChemPer -- a new tool for generating SMIRKS patterns based on clustered fragments (i.e. bonds, angles, or torsions) which should be assigned the same force field parameter. We demonstrate the utility of ChemPer by clustering fragments based on a reference force field, and then regenerating those parameters starting with a simple set of alkanes, ethers, and alcohols. Next, we create SMIRKS patterns for a protein SMIRNOFF which match the parameters from AMBER99. We conclude with a discussion of other potential applications and expansions to ChemPer. </div>

ChemPer: An Open Source Tool for Automatically Generating SMIRKS Patterns

<div>Force fields are used in a variety of research fields including computer-aided drug design, biomaterials, and polymer chemistry. However, force fields also continue to limit the accuracy of predictions of physical properties. Current parameterization of these force fields involves a huge amount of human effort -- often years of work -- and depends heavily on the chemical intuition of those involved. The Open Force Field Initiative is working to replace this tedious process with an automated machinery to learn parameters and chemical perception. Our new SMIRKS-based force field format, SMIRNOFF, allows all parameter types to be defined independently. This allows for easier extension compared to the traditional atom type-based force fields where the chemical perception of all parameter types is intertwined. </div><div>We will need to be capable of programmatically learning SMIRKS patterns in order to fully automate force field parameterization. In this work, we present ChemPer -- a new tool for generating SMIRKS patterns based on clustered fragments (i.e. bonds, angles, or torsions) which should be assigned the same force field parameter. We demonstrate the utility of ChemPer by clustering fragments based on a reference force field, and then regenerating those parameters starting with a simple set of alkanes, ethers, and alcohols. Next, we create SMIRKS patterns for a protein SMIRNOFF which match the parameters from AMBER99. We conclude with a discussion of other potential applications and expansions to ChemPer. </div>

Perception of aversive stimuli of different gustatory modalities in an haematophagous insect, Rhodnius prolixus

Sensory aversion is an essential link for avoiding potential dangers. Here, we studied the chemical perception of aversive compounds of different gustatory modalities (salty and bitter) in the haematophagous kissing bug, Rhodnius prolixus. Over a walking arena, insects preferred a substrate embedded with 0.3 M NaCl or KCl rather than with distilled water. Same salts were avoided when prepared at 1 M. When NaCl and KCl were confronted, no preferences were evinced by insects. A pre-exposure to amiloride interfered with the repellency of NaCl and KCl equally, suggesting that amiloride-sensitive receptors are involved in the detection of both salts. Discriminative experiments were then performed to determine if R. prolixus can distinguish between these salts. An aversive operant conditioning involving either NaCl or KCl modulated the repellency of the conditioned salt, but also of the novel salt. A chemical pre-exposure to the salts did not to modify their repellency levels. When we crossed gustatory modalities by confronting NaCl to caffeine (i.e. a bitter stimulus) no innate preferences were evinced. Aversive operant conditionings with either NaCl or Caf rendered unspecific changes in the repellency of both compounds. A chemical pre-exposure to Caf modulated the response to Caf but not to NaCl, suggesting the existence of two independent neural pathways for the detection of salts and bitter compounds. Overall results suggest that R. prolixus cannot distinguish between NaCl and KCl but can distinguish between NaCl and Caf and generalizes the response between these two aversive stimuli of different gustatory modality.Summary statementKissing-bugs use contact chemo-perception to avoid aversive substrates. They can sensory distinguish between salty (sodium chloride) and bitter (caffeine) tastes, but not between different salts (sodium and potassium chloride).