Recent developments in molecular modeling tools and applications related to pharmaceutical and biomedical research

Molecular Modelling in Bioactive Peptide Discovery and Characterisation

Molecular modelling is a vital tool in the discovery and characterisation of bioactive peptides, providing insights into their structural properties and interactions with biological targets. Many models predicting bioactive peptide function or structure rely on their intrinsic properties, including the influence of amino acid composition, sequence, and chain length, which impact stability, folding, aggregation, and target interaction. Homology modelling predicts peptide structures based on known templates. Peptide-protein interactions can be explored using molecular docking techniques, but there are challenges related to the inherent flexibility of peptides, which can be addressed by more computationally intensive approaches that consider their movement over time, called molecular dynamics (MD). Virtual screening of many peptides, usually against a single target, enables rapid identification of potential bioactive peptides from large libraries, typically using docking approaches. The integration of artificial intelligence (AI) has transformed peptide discovery by leveraging large amounts of data. AlphaFold is a general protein structure prediction tool based on deep learning that has greatly improved the predictions of peptide conformations and interactions, in addition to providing estimates of model accuracy at each residue which greatly guide interpretation. Peptide function and structure prediction are being further enhanced using Protein Language Models (PLMs), which are large deep-learning-derived statistical models that learn computer representations useful to identify fundamental patterns of proteins. Recent methodological developments are discussed in the context of canonical peptides, as well as those with modifications and cyclisations. In designing potential peptide therapeutics, the main outstanding challenge for these methods is the incorporation of diverse non-canonical amino acids and cyclisations.

First separation of commendamide enantiomers

N-(3-hydroxyacyl)glycines are compounds of remarkable interest due to their biogenic origin and bioactivity and as precursors of the corresponding 3-acyloxy derivatives which represent an important class of bioactive products of bacterial origin. Commendamide [N-(3-hydroxypalmitoyl)glycine] (1) is a gut microbiota-derived bioactive metabolite that is structurally like endogenous long-chain N-acyl-amino acids belonging to the endocannabinoidome, a complex lipid signaling system involved in several aspects of mammalian physiology and pathology. Thanks to this structural similarity, this compound and its analogues, like the N-(3-hydroxymyristoyl)glycine 2, exert a remarkable bioactivity in mammals, for instance, through activation of G-protein-coupled receptors (GPCRs). N-(3-Hydroxyacyl)glycines are chiral and the availability of their pure enantiomers may bring light to possible enantioselective pathways within the biological processes which these compounds are involved in. A sustainable synthesis of rac-1 and its analogues was recently reported, but asymmetric synthesis and enantioseparation methods to access their pure or enriched enantiomers were not reported so far. In this paper, we report the first direct separation of commendamide enantiomers by using enantioselective high-performance liquid chromatography (HPLC) with polysaccharide-based chiral columns, aqueous-organic mixtures as mobile phases and either electrospray ionization mass spectrometry (ESI-MS) or UV detection. Optimal enantioseparation was obtained by using an amylose tris(3,5-dimethylphenylcarbamate)-based chiral column and acetonitrile/water 60:40 (v/v) (0.1 % acetic acid) as mobile phase. By adopting the same method, the enantioseparation of the analogue 2 was also performed. The molecular bases of the higher retention and selectivity observed for the N-(3-hydroxyacyl)glycine 1 compared to the analogue 2 were explored by computational analysis.

Imaging CDK4/6 Broaden Options of Breast Cancer Diagnostics with Positron Emission Tomography

This study developed a novel PET radiotracer to screen breast cancer patients sensitive to CDK4/6 inhibitors, guiding personalized treatment. Two CDK4/6-targeting precursors were synthesized and evaluated in vitro and in vivo. Three breast cancer cell lines─MCF-7, MDA-MB-231, and MDA-MB-468─were selected based on decreasing sensitivity to palbociclib. Compared to [68Ga]Ga-DOTA-Hexa-CDKi, [68Ga]Ga-DOTA-Bua-CDKi clearly identified cell lines with high sensitivity to palbociclib. PET/CT imaging showed significantly higher uptake of [68Ga]Ga-DOTA-Bua-CDKi (8.40 ± 0.85%ID/g) in MCF-7 tumors 60 min after tracer injection, with significant differences in tumor uptake among the three models (P < 0.05). Blocking assays demonstrated specific tumor uptake of [68Ga]Ga-DOTA-Bua-CDKi. Biosafety tests validated its safety as a diagnostic agent. [68Ga]Ga-DOTA-Bua-CDKi showed highly specific targeting of CDK4/6 and effective contrast imaging in tumor models. To our knowledge, [68Ga]Ga-DOTA-Bua-CDKi is one of the first radiotracers to assess CDK inhibitor sensitivity, offering promise for evaluating patient responses to CDK4/6 inhibitors.

Approaches for Inclusion Complexes of Ezetimibe with Cyclodextrins: Strategies for Solubility Enhancement and Interaction Analysis via Molecular Docking

This study aimed to improve the solubility of ezetimibe (EZT), which has low aqueous solubility, by preparing complexes using β-cyclodextrin (β-CD) derivatives. Phase solubility studies and Job's plot confirmed a high apparent stability constant for EZT with β-CD and even higher constants with its derivatives, establishing a 1:1 stoichiometric ratio. The composites were prepared using spray drying over a range of molar ratios, and their physicochemical properties were evaluated using techniques such as scanning electron microscopy (SEM), powder X-ray diffraction (PXRD), and Fourier transform infrared spectroscopy (FT-IR). Saturation solubility and in vitro dissolution tests revealed that solubility increased with higher CD molar ratios. EZT/RM-β-CD inclusion complexes (ICs) and EZT/DM-β-CD ICs exhibited a similar solubility, which was greater than that of EZT/HP-β-CD ICs and EZT/SBE-β-CD ICs (where RM, DM, HP, and SEB represent H, CH3, -CH2-CHOH-CH3 and -(CH2)4-SO3Na synthetic derivatives, respectively). Most complexes, except for EZT/SBE-β-CD at 1:2 or higher ratios, showed superior solubility compared with EZT powder and commercial products. Molecular docking simulations confirmed EZT inclusion within the CD, revealing hydrogen bonds and binding energies that aligned with solubility trends. These findings suggest that EZT complexes with β-CD derivatives significantly improve solubility, highlighting their potential for developing more effective oral solid formulations for hyperlipidemia treatment.

Trace Element Chromium-D-Phenylalanine Complex: Anti-Inflammatory and Antioxidant Insights from In Vivo and In Silico Studies

The biological significance of trace elements such as chromium extends beyond basic cellular functions, influencing key processes like inflammation and oxidative stress. In this study, we explore the anti-inflammatory and antioxidant potential of a trace element complex, Chromium-D-phenylalanine (Cr(D-Phe)₃), through in vivo and in silico approaches. Anti-inflammatory activity was assessed using a carrageenan-induced paw oedema model in rats, coupled with histopathological and biochemical analyses. The antioxidant effects of Cr(D-Phe)₃ were evaluated by measuring reduced glutathione (GSH), lipid peroxidation (LPO), and tumour necrosis factor-alpha (TNF-α) as a marker of inflammation. Furthermore, molecular docking and dynamics simulations were conducted to elucidate the compound's binding affinity and stability with cyclooxygenase enzymes. Cr(D-Phe)₃ exhibited significant anti-inflammatory activity, with the 40 μg/kg dose achieving 34.40% (p < 0.001) oedema inhibition, comparable to diclofenac sodium (42.40%). Treatment with Cr(D-Phe)₃ restored GSH levels (+ 62.10%, p < 0.001), reduced LPO (24.72%, p < 0.001), and lowered TNF-α (31.73%, p < 0.001) in carrageenan injected rats, demonstrating potent antioxidant and anti-inflammatory effects. Molecular docking revealed strong binding affinities between Cr(D-Phe)₃ and COX enzymes, suggesting its potential mechanism of action in modulating inflammatory pathways. This study highlights the potential of Cr(D-Phe)₃ as a chromium-based trace element complex with anti-inflammatory and antioxidant properties. These findings warrant further preclinical investigations to elucidate its full pharmacological potential and applications in managing inflammatory conditions.

The future of plant lectinology: Advanced technologies and computational tools

Lectins play crucial roles in many biological processes and serve as tools in fields ranging from agriculture to biomedicine. While classical methods for lectin discovery and characterization were foundational for the field, they often lack sensitivity and throughput, limiting the detection of less abundant or weakly binding lectins, such as the stress-inducible or monovalent lectins. This review focuses on recent advancements in plant lectin research, particularly novel technologies that complement traditional approaches. Techniques such as glycan microarrays allow rapid assessment of lectin specificity across a diverse range of glycans by evaluating interactions with immobilized glycans on solid surfaces. Phage display libraries enable the identification of carbohydrate-mimetic peptides and the development of ligands for lectins by presenting diverse peptide libraries on bacteriophages. Genomic and transcriptomic analyses facilitate the exploration of the lectome in various plant species by scanning entire datasets to identify genes that contain lectin motifs-specific conserved amino acid sequences involved in carbohydrate recognition-and lectin domains, the larger structural regions that facilitate and stabilize these interactions. Additionally, computational methods-including molecular docking, molecular dynamics simulations, and machine learning pipelines-support predictions of lectin structures and binding properties, underpinning experimental efforts. These advanced techniques bring increased efficiency, accuracy, and a broader scope to lectin studies, with potential impacts across multiple fields. However, challenges such as data complexity and the need for experimental validation for computational methods remain. The future of lectin research will depend on the integration of these methods and the strengthening of interdisciplinarity to unlock the full potential of lectins.

A Review on the Analysis of Chiral Molecules as Disease Biomarkers by LC/MS

The chiral compounds may be biomarker candidates in human metabolism, which indicates the health status of humans. There are many applications in LC/MS that show that chiral small molecules are promising biomarkers for human diseases. Both clinical and commercial analyses of chiral metabolites are necessary due to the enantiomeric ratios of chiral molecules in biological samples may show both human health status and diseases. This review provides current and advanced LC/MS techniques for the separation and analysis of chiral molecules as disease biomarkers. In particular, sample preparation and chromatographic analysis of potential chiral biomarkers in biological samples are presented. The preparation and applications of several chiral columns used in enantiomeric separation of chiral metabolites/biomarkers by advanced LC/MS techniques are discussed. The improvement of these analyses will enable both the discovery of new chiral biomarkers and the prognosis of human diseases.

Molecular modeling study to unravel complexation of daclatasvir and its enantiomer by β-cyclodextrins. Computational analysis using quantum mechanics and molecular dynamics

A computational study was performed to unravel mechanisms underlying capillary electrophoresis enantioseparations of daclatasvir and its (R,R,R,R)-enantiomer with native and methylated β-cyclodextrins (β-CDs) as chiral selectors. Considering the enantioseparation results as benchmark, the structures of β-CD and seven methylated β-CDs were optimized by quantum mechanics, and their topography and computed molecular properties were compared. Furthermore, the electron charge density distribution of the macrocycles was also evaluated by calculating the molecular electrostatic potential of pivotal regions of native and methylated β-CDs. The function of hydrogen bonds in the complexation process of daclatasvir and the CDs was derived from quantum mechanics analysis and confirmed by molecular dynamics, as orthogonal computational techniques. The presence of a round-shaped cavity in the CDs used as chiral selector appeared as a necessary requirement for the enantioseparation of daclatasvir and its (R,R,R,R)-enantiomer. In this regard, it was confirmed that the round shape of the CDs is sustained by hydrogen bonds formed between adjacent glucopyranose units and blocking rotation of the linking glycosidic bonds. The presence of hydroxy groups at the 6-position of the glucopyranose units and the concurrent absence of hydroxy groups at the 2-position were evidenced as important factors for enantioseparation of daclatasvir and its enantiomer by methylated β-CDs.

A journey in unraveling the enantiorecognition mechanism of 3,5-dinitrobenzoyl-amino acids with two Cinchona alkaloid-based chiral stationary phases: The power of molecular dynamic simulations

BACKGROUND

Innovations in computer hardware and software capabilities have paved the way for advances in molecular modelling techniques and methods, leading to an unprecedented expansion of their potential applications. In contrast to the docking technique, which usually identifies the most stable selector-selectand (SO-SA) complex for each enantiomer, the molecular dynamics (MD) technique enables the consideration of a distribution of the SO-SA complexes based on their energy profile. This approach provides a more truthful representation of the processes occurring within the column. However, benchmark procedures and focused guidelines for computational treatment of enantioselectivity at the molecular level are still missing.

RESULTS

Twenty-eight molecular dynamics simulations were performed to study the enantiorecognition mechanisms of seven N-3,5-dinitrobenzoylated α- and β-amino acids (DNB-AAs), occurring with the two quinine- and quinidine-based (QN-AX and QD-AX) chiral stationary phases (CSPs), under polar-ionic conditions. The MD protocol was optimized in terms of box size, simulation run time, and frame recording frequency. Subsequently, all the trajectories were analyzed by calculating both the type and amount of the interactions engaged by the selectands (SAs) with the two chiral selectors (SOs), as well as the conformational and interaction energy profiles of the formed SA-SO associates. All the MDs were in strict agreement with the experimental enantiomeric elution order and allowed to establish (i) that salt-bridge and H-bond interactions play a pivotal role in the enantiorecognition mechanisms, and (ii) that the π-cation and π-π interactions are the discriminant chemical features between the two SOs in ruling the chiral recognition mechanism.

SIGNIFICANCE

The results of this work clearly demonstrate the high contribution given by MD simulations in the comprehension of the enantiorecognition mechanism with Cinchona alkaloid-based CSPs. However, from this research endeavor it clearly emerged that the MD protocol optimization is crucial for the quality of the produced results.

The critical role of residues Phe120 and Val161 of (2 R,3 R)‑2,3‑butanediol dehydrogenase from Neisseria gonorrhoeae as probed by molecular docking and site-directed mutagenesis

NAD+-dependent (2 R,3 R)‑2,3‑butanediol dehydrogenase (BDH) from Neisseria gonorrhoeae (NgBDH) is a representative member of the medium-chain dehydrogenase/reductase (MDR) superfamily. To date, little information is available on the substrate binding sites and catalytic residues of BDHs from this superfamily. In this work, according to molecular docking studies, we found that conserved residues Phe120 and Val161 form strong hydrophobic interactions with both (2 R,3 R)‑2,3‑butanediol (RR-BD) and meso-2,3‑butanediol (meso-BD) and that mutations of these residues to alanine or threonine impair substrate binding. To further evaluate the roles of these two residues, Phe120 and Val161 were mutated to alanine or threonine. Kinetic analysis revealed that, relative to those of wild type, the apparent KM values of the Phe120Ala mutant for RR-BD and meso-BD increased 36- and 369-fold, respectively; the catalytic efficiencies of this mutant with RR-BD and meso-BD decreased approximately 586- and 3528-fold, respectively; and the apparent KM values of the Val161Ala mutant for RR-BD and meso-BD increased 4- and 37-fold, respectively, the catalytic efficiencies of this mutant with RR-BD and meso-BD decreased approximately 3- and 28-fold, respectively. Additionally, the Val161Thr mutant slightly decreased catalytic efficiencies (twofold with RR-BD; 7.3-fold with meso-BD) due to an increase in KM (sixfold for RR-BD; 24-fold for meso-BD) and a slight increase (2.8-fold with RR-BD; 3.3-fold with meso-BD) in kcat. These findings validate the critical roles of Phe120 and Val161 of NgBDH in substrate binding and catalysis. Overall, the current study provides a better understanding of the substrate binding and catalysis of BDHs within the MDR superfamily.

Update on chiral recognition mechanisms in separation science

The stereospecific analysis of chiral molecules is an important issue in many scientific fields. In separation sciences, this is achieved via the formation of transient diastereomeric complexes between a chiral selector and the selectand enantiomers driven by molecular interactions including electrostatic, ion-dipole, dipole-dipole, van der Waals or π-π interactions as well as hydrogen or halogen bonds depending on the nature of selector and selectand. Nuclear magnetic resonance spectroscopy and molecular modeling methods are currently the most frequently applied techniques to understand the selector-selectand interactions at a molecular level and to draw conclusions on the chiral separation mechanism. The present short review summarizes some of the recent achievements for the understanding of the chiral recognition of the most important chiral selectors combining separation techniques with molecular modeling and/or spectroscopic techniques dating between 2020 and early 2024. The selectors include polysaccharide derivatives, cyclodextrins, macrocyclic glycopeptides, proteins, donor-acceptor type selectors, ion-exchangers, crown ethers, and molecular micelles. The application of chiral ionic liquids and chiral deep eutectic solvents, as well as further selectors, are also briefly addressed. A compilation of all published literature on chiral selectors has not been attempted.