A computational approach for positive genetic identification and relatedness detection from low-coverage shotgun sequencing data.

Several methods exist for detecting genetic relatedness or identity by comparing DNA information. These methods generally require genotype calls, either single-nucleotide polymorphisms or short tandem repeats, at the sites used for comparison. For some DNA samples, like those obtained from bone fragments or single rootless hairs, there is often not enough DNA present to generate genotype calls that are accurate and complete enough for these comparisons. Here, we describe IBDGem, a fast and robust computational procedure for detecting genomic regions of identity-by-descent by comparing low-coverage shotgun sequence data against genotype calls from a known query individual. At less than 1× genome coverage, IBDGem reliably detects segments of relatedness and can make high-confidence identity detections with as little as 0.01× genome coverage.

Heterogeneous Dielectric Implicit Membrane Model for the Calculation of MMPBSA Binding Free Energies.

Membrane-bound protein receptors are a primary biological drug target, but the computational analysis of membrane proteins has been limited. In order to improve molecular mechanics Poisson-Boltzmann surface area (MMPBSA) binding free energy calculations for membrane protein-ligand systems, we have optimized a new heterogeneous dielectric implicit membrane model, with respect to free energy simulations in explicit membrane and explicit water, and implemented it into the Amber software suite. This new model supersedes our previous uniform, single dielectric implicit membrane model by allowing the dielectric constant to vary with depth within the membrane. We calculated MMPBSA binding free energies for the human purinergic platelet receptor (P2Y12R) and two of the muscarinic acetylcholine receptors (M2R and M3R) bound to various antagonist ligands using both membrane models, and we found that the heterogeneous dielectric membrane model has a stronger correlation with experimental binding affinities compared to the older model under otherwise identical conditions. This improved membrane model increases the utility of MMPBSA calculations for the rational design and improvement of future drug candidates.

Linking mechanochemistry with the green chemistry principles: Review article.

The need to explore contemporary alternatives for industrial production has driven the development of innovative techniques that address critical limitations linked to traditional batch mechanochemistry. One particularly promising strategy involves the integration of flow processes with mechanochemistry. Three noteworthy technologies in this domain are single-screw extrusion (SSE) and twin-screw extrusion (TSE) and Impact (Induction) in Continuous-flow Heated Mechanochemistry (ICHeM). These technologies go beyond the industrial production of polymers, extending to the synthesis of active pharmaceutical ingredients, the fabrication of (nano)materials, and the extraction of high-added value products through the valorisation of biomass and waste materials. In accordance with the principles of green chemistry, ball milling processes are generally considered greener compared to conventional solvothermal processes. In fact, ball milling processes require less solvent, enhance reaction rates and reaction conversion by increasing surface area and substituting thermal energy with mechanochemical energy, among others. Special attention will be given to the types of products, reactants, size of the milling balls and reaction conditions, selecting 60 articles after applying a screening methodology during the period 2020-2022. This paper aims to compile and analyze the cutting edge of research in utilizing mechanochemistry for green chemistry applications.