Y-Linked Copy Number Polymorphism of Target of Rapamycin Is Associated with Sexual Size Dimorphism in Seed Beetles.

The Y chromosome is theorized to facilitate evolution of sexual dimorphism by accumulating sexually antagonistic loci, but empirical support is scarce. Due to the lack of recombination, Y chromosomes are prone to degenerative processes, which poses a constraint on their adaptive potential. Yet, in the seed beetle, Callosobruchus maculatus segregating Y linked variation affects male body size and thereby sexual size dimorphism (SSD). Here, we assemble C. maculatus sex chromosome sequences and identify molecular differences associated with Y-linked SSD variation. The assembled Y chromosome is largely euchromatic and contains over 400 genes, many of which are ampliconic with a mixed autosomal and X chromosome ancestry. Functional annotation suggests that the Y chromosome plays important roles in males beyond primary reproductive functions. Crucially, we find that, besides an autosomal copy of the gene target of rapamycin (TOR), males carry an additional TOR copy on the Y chromosome. TOR is a conserved regulator of growth across taxa, and our results suggest that a Y-linked TOR provides a male specific opportunity to alter body size. A comparison of Y haplotypes associated with male size difference uncovers a copy number variation for TOR, where the haplotype associated with decreased male size, and thereby increased sexual dimorphism, has two additional TOR copies. This suggests that sexual conflict over growth has been mitigated by autosome to Y translocation of TOR followed by gene duplications. Our results reveal that despite of suppressed recombination, the Y chromosome can harbor adaptive potential as a male-limited supergene.

Leveraging Language Model Multitasking To Predict C-H Borylation Selectivity.

C-H borylation is a high-value transformation in the synthesis of lead candidates for the pharmaceutical industry because a wide array of downstream coupling reactions is available. However, predicting its regioselectivity, especially in drug-like molecules that may contain multiple heterocycles, is not a trivial task. Using a data set of borylation reactions from Reaxys, we explored how a language model originally trained on USPTO_500_MT, a broad-scope set of patent data, can be used to predict the C-H borylation reaction product in different modes: product generation and site reactivity classification. Our fine-tuned T5Chem multitask language model can generate the correct product in 79% of cases. It can also classify the reactive aromatic C-H bonds with 95% accuracy and 88% positive predictive value, exceeding purpose-developed graph-based neural networks.

Tautomer Standardization in Chemical Databases: Deriving Business Rules from Quantum Chemistry.

Databases of small, potentially bioactive molecules are ubiquitous across the industry and academia. Designed such that each unique compound should appear only once, the multiplicity of ways in which many compounds can be represented means that these databases require methods for standardizing the representation of chemistry. This is commonly achieved through the use of "Chemistry Business Rules", sets of predefined rules that describe the "house style" of the database in question. At Syngenta, the historical approach to the design of chemistry business rules has been to focus on consistency of representation, with chemical relevance given secondary consideration. In this work, we overturn that convention. Through the use of quantum chemistry calculations, we define a set of chemistry business rules for tautomer standardization that reproduces gas-phase energetic preferences. We go on to show that, compared to our historic approach, this method yields tautomers that are in better agreement with those observed experimentally in condensed phases and that are better suited for use in predictive models.

Understanding the apparent stator-rotor connections in the rotary ATPase family using coarse-grained computer modeling.

Advances in structural biology, such as cryo-electron microscopy (cryo-EM) have allowed for a number of sophisticated protein complexes to be characterized. However, often only a static snapshot of a protein complex is visualized despite the fact that conformational change is frequently inherent to biological function, as is the case for molecular motors. Computer simulations provide valuable insights into the different conformations available to a particular system that are not accessible using conventional structural techniques. For larger proteins and protein complexes, where a fully atomistic description would be computationally prohibitive, coarse-grained simulation techniques such as Elastic Network Modeling (ENM) are often employed, whereby each atom or group of atoms is linked by a set of springs whose properties can be customized according to the system of interest. Here we compare ENM with a recently proposed continuum model known as Fluctuating Finite Element Analysis (FFEA), which represents the biomolecule as a viscoelastic solid subject to thermal fluctuations. These two complementary computational techniques are used to answer a critical question in the rotary ATPase family; implicit within these motors is the need for a rotor axle and proton pump to rotate freely of the motor domain and stator structures. However, current single particle cryo-EM reconstructions have shown an apparent connection between the stators and rotor axle or pump region, hindering rotation. Both modeling approaches show a possible role for this connection and how it would significantly constrain the mobility of the rotary ATPase family.

QSRR Modeling for Metabolite Standards Analyzed by Two Different Chromatographic Columns Using Multiple Linear Regression.

Modified quantitative structure retention relationships (QSRRs) are proposed and applied to describe two retention data sets: A set of 94 metabolites studied by a hydrophilic interaction chromatography system under organic content gradient conditions and a set of tryptophan and its major metabolites analyzed by a reversed-phase chromatographic system under isocratic as well as pH and/or simultaneous pH and organic content gradient conditions. According to the proposed modification, an additional descriptor is added to a conventional QSRR expression, which is the analyte retention time, tR(R), measured under the same elution conditions, but in a second chromatographic column considered as a reference one. The 94 metabolites were studied on an Amide column using a Bare Silica column as a reference. For the second dataset, a Kinetex EVO C18 and a Gemini-NX column were used, where each of them was served as a reference column of the other. We found in all cases a significant improvement of the performance of the QSRR models when the descriptor tR(R) was considered.