UAM Cuajimalpa

Quantifying molecular similarity is crucial for drug discovery and for exploring chemical space. A similarity assessment always combines two independent ingredients: a molecular representation and a similarity coefficient. The most common pairing, binary substructure fingerprints scored with the Tanimoto coefficient, depends strongly on fingerprint bit density and, because it compares unweighted sets of substructure identifiers, is blind to the multiplicity of repeated fragments and frequently returns ranking ties that obscure meaningful chemical relationships. Here, we introduce the Mahalanobis Similarity Index (MSI), which pairs continuous Mol2Vec embeddings with a covariance-aware Mahalanobis distance (dM) and an associated Mahalanobis angle (θM) to give a statistically grounded assessment that is invariant under invertible linear reparametrization of the descriptor space. We evaluated MSI on five chemically distinct reference compounds: aspirin, a salicylate nonsteroidal anti-inflammatory drug (NSAID); aniline, an industrial aromatic amine; curcumin, a polyphenolic natural product; ibuprofen, a propionic-acid NSAID; and digitoxin, a cardiac glycoside. Relative to the Tanimoto coefficient computed on ECFP4 fingerprints, MSI improves the analysis in three specific respects: it promotes chemically reasonable analogs that the fingerprint deprioritises; it resolves ranking ties, recovering between 7 and 10 distinct scores among the 10 nearest neighbors where Tanimoto recovers only 3-7; and its geometry varies systematically with HOMO-LUMO energy gaps in the QM9 dataset, indicating that the embedding tracks electronic structure even though it was trained on structural context alone. Polar plots and three-dimensional similarity maps reveal anisotropy within the embedding space and define practical applicability domains for high-similarity retrieval. MSI retains discriminatory power in the regime where the Tanimoto coefficient saturates near zero, and sparse peripheral regions suggest scaffold-hopping opportunities. The dual radial-angular description supports hypothesis-driven reasoning about how structural modifications shift electronic properties. MSI is computationally efficient, chemically interpretable, and offers a practical way to navigate high-dimensional chemical space. Beyond drug discovery, it is applicable to materials science, toxicology, and chemical biology, wherever continuous molecular embeddings are used for property-driven screening.

Leucoagaricus gongylophorus is essential to the mutualistic relationship between leaf-cutting ants and their fungal gardens. Known for its ability to degrade complex plant polysaccharides, this fungus produces a range of CAZymes and FOLymes enzymes that have significant potential for biotechnological applications. We investigated the growth kinetics, enzymatic activities and quantitative secretome modulation of L. gongylophorus grown in submerged cultures containing glucose, carboxymethylcellulose (CMC), xylan or pectin as sole carbon sources. In the comparative analysis, glucose was the preferred carbon source for biomass accumulation reaching 8.6 g L-1 at day 35, whereas cultures grown on pectin showed limited growth. In the case of enzyme activity, pectin cultures had the highest values in endo-β-1,4-glucanase, pectinase and laccase activities, reaching up to 50.7 U L-1, 206.6 U L-1 and 97.3 U L-1, respectively. In addition, a quantitative proteomic analysis was performed across the different growth conditions and identified 290 proteins, of which 201 were assigned to the secretome. Presence-absence analysis revealed 93 proteins shared across substrates, including 43 consistently detected at both time points, while pectin cultures exhibiting a more diverse set of exclusive secreted proteins. A key difference between conditions was in protein abundance rather in terms of protein profiles, cellulolytic enzymes were preferentially enriched in CMC cultures, pectinolytic enzymes in pectin, and oxidative proteins in xylan-grown cultures. Based on our results, L. gongylophorus adapts to different polysaccharides primarily through quantitative regulation of a shared secretome, reflecting a finely tuned enzymatic strategy that is consistent with its mutualistic lifestyle.

We report the draft genome sequence of Scenedesmus bijugus var. obtusiusculus AT-UAM, a CO2-tolerant and lipid-producing microalga isolated from Cuatro Ciénegas, México. The strain shows potential for biotechnological applications due to its adaptability and high lipid accumulation.

The primary function of the CheY protein is to regulate flagellar motility in motile bacteria such as Escherichia coli and Thermotoga maritima. Although the general determinants of thermal stability in CheY from the hyperthermophilic bacterium T. maritima (TmY) have been proposed, the molecular mechanisms that enable this protein to remain structurally and functionally competent at elevated temperatures are not fully understood. Here, we investigated the thermal stability of TmY through all-atom molecular dynamics simulations, using three independent trajectories of 1 μs each at five different temperatures. Equivalent simulations were performed for its mesophilic homologue from E. coli (EcY) to enable a direct comparison under identical conditions. Our observations show that TmY preserves its native fold and global compactness across the entire temperature range, whereas EcY exhibits progressive destabilization and unfolds at high temperatures. Mechanistically, the enhanced thermal resistance of TmY is associated with an extensive network of salt bridges that interconnect secondary-structure elements and couple the N- and C-terminal domains. These electrostatic networks act as stabilizing scaffolds that restrain local flexibility, preserve domain communication, and maintain a tightly packed globular architecture under thermal stress, providing a molecular basis for the superior stability of TmY relative to its mesophilic counterpart.