Search Results (22)

Background/Objectives: Chloroquine (CQ) and hydroxychloroquine (HCQ) have been the subject of debate in the treatment of COVID-19 due to the lack of conclusive evidence regarding their efficacy and safety. Our study aims to investigate the molecular interaction between the enantiomers of CQ and HCQ with angiotensin-converting enzyme 2 (ACE2), focusing on the binding mechanism, affinity, and selectivity. Methods: We used in silico methods, including molecular docking, molecular dynamics, and binding free energy calculations using the MM-PBSA method, to evaluate the interaction between the enantiomers of CQ and HCQ with ACE2. Results: We identified three main interaction sites on ACE2 (α, β, and γ) with distinct characteristics based on the pocket size, hydrophilic/hydrophobic characteristics, and affinity energy. We observed that protonation states and ionic strength significantly influence the binding affinity and specificity. In particular, the selectivity of the β-site, characterized by its smaller size and hydrophilic residues, is preferential for species with the (R) configuration, whereas the α and γ binding sites, with a larger size and amphiphilic residues, have greater affinity for the (S) enantiomer of CQ and HCQ. Furthermore, ionic strength can affect ligand binding by modulating electrostatic interactions, molecular conformation, solvation, and the stability of the complex. Conclusions: Our findings reveal that protonation states and the ionic strength substantially impact the binding affinity and specificity, regulated by spatial and polar–electrostatic complementarity, as well as hydrophobic contributions. These results suggest that understanding the interaction between CQ and HCQ enantiomers with ACE2 could be useful for the design of novel therapies against COVID-19. Full article

This study employs molecular dynamics simulations to investigate counterion effects (Li⁺, Na⁺, K⁺) on the interfacial aggregation of mixed short-chain fluorocarbon, Perfluorohexanoic acid (PFH_XA), and Sodium dodecyl sulfate (SDS) surfactants. Motivated by the need for greener surfactant alternatives and a fundamental understanding of molecular interactions governing their behavior, we demonstrate that counterion hydration radius critically modulates system organization. K⁺ ions induce superior monolayer condensation and interfacial performance compared to Li⁺ and Na⁺ counterparts, as evidenced by threefold analysis: (1) RMSD/MSD-confirmed equilibrium attainment ensures data reliability; (2) 1D/2D density profiles and surface tension measurements reveal K⁺-enhanced packing density (lower solvent-accessible surface area versus Na⁺ and Li⁺ systems); (3) Electrostatic potential analysis identifies synergistic complementarity between SDS’s hydrophobic stabilization via dodecyl chain interactions and PFH_XA’s charge uniformity, optimizing molecular-level charge screening. Radial distribution function analysis demonstrates K⁺’s stronger affinity for SDS head groups, with preferential sulfate coordination reducing surfactant-water hydration interactions. This behavior correlates with hydrogen-bond population reduction, attributed to SDS groups functioning as multidentate ligands—their tetrahedral oxygen arrangement facilitates cooperative hydrogen-bond networks, while counterion-specific charge screening competitively modulates bond formation. The resultant interfacial restructuring enables ordered molecular arrangements with lower system curvature than those observed in Li⁺ and Na⁺-containing systems. These findings elucidate counterion-mediated interfacial modulation mechanisms and establish K⁺ as an optimal candidate for enhancing PFH_XA/SDS mixture performance through hydration-radius screening. The work provides molecular-level guidelines for designing eco-friendly surfactant systems with tailored interfacial properties. Full article

The optical detection of thioacetamide was investigated using a metalated porphyrin, Mn(III)-5,10,15,20-tetrakis-(3,4-dimethoxyphenyl)-21H,23H-porphyrin chloride (Mn-3,4-diMeOPP), a gold colloid solution (AuNPs), and a complex formed between them (Mn-3,4-diMeOPP–AuNPs) in order to select the most sensitive material and to achieve complementarity between methods. Mn-3,4-diMeOPP, AuNPs, and their complex were synthesized and characterized by means of UV–Vis, FT-IR spectrometry, and AFM investigations. It could be concluded that Mn-3,4-diMeOPP could detect/quantify thioacetamide (TAA) in the range 3.13 × 10⁻⁸ M–7.67 × 10⁻⁷ M in a linear fashion, with a 99.85% confidence coefficient. The gold colloidal particles alone could detect TAA in an extremely narrow concentration domain of 2–9.8 × 10⁻⁷ M, slightly complementary with that of Mn-3,4-diMeOPP. The complex between Mn-3,4-diMeOPP and gold colloid proved to be able to quantify TAA in the trace domain with concentrations of 1.99 × 10⁻⁸ M–1.76 × 10⁻⁷ M in a polynomial fashion, with the method being more difficult. A potential mechanism for TAA detection based on Mn-3,4-diMeOPP is discussed based on computational modeling. The distorted porphyrin conformation and its electronic configuration favor the generation of a grid of electrostatic interactions between porphyrin and TAA. Full article

P21-activated kinase 4 (PAK4) plays a crucial role in the proliferation and metastasis of various cancers. However, developing selective PAK4 inhibitors remains challenging due to the high homology within the PAK family. Therefore, developing highly selective PAK4 inhibitors is critical to overcoming the limitations of existing inhibitors. We analyzed the structural differences in the binding pockets of PAK1 and PAK4 by combining cross-docking and molecular dynamics simulations to identify key binding regions and unique structural features of PAK4. We then performed screening using shape and protein conformation ensembles, followed by a re-evaluation of the docking results with deep-learning-driven GNINA to identify the candidate molecule, STOCK7S-56165. Based on this, we applied a fragment-replacement strategy under electrostatic-surface-matching conditions to obtain Compd 26. This optimization significantly improved electrostatic interactions and reduced binding energy, highlighting its potential for selectivity. Our findings provide a novel approach for developing selective PAK4 inhibitors and lay the theoretical foundation for future anticancer drug design. Full article

(1) Background: Electrostatics plays a capital role in protein–protein and protein–ligand interactions. Implicit solvent models are widely used to describe electrostatics and complementarity at interfaces. Electrostatic complementarity at the interface is not trivial, involving surface potentials rather than the charges of surfacial contacting atoms. (2) Results: The program bluues_cplx, here used in conjunction with the software NanoShaper to compute molecular surfaces, has been used to compute the electrostatic properties of 756 protein–protein and 189 protein–ligand complexes along with the corresponding isolated molecules. (3) Methods: The software we make available here uses Generalized Born (GB) radii, computed by a molecular surface integral, to output several descriptors of electrostatics at protein (and in general, molecular) interfaces. We illustrate the usage of the software by analyzing a dataset of protein–protein and protein–ligand complexes, thus extending and refining previous analyses of electrostatic complementarity at protein interfaces. (4) Conclusions: The complete analysis of a molecular complex is performed in tens of seconds on a PC, and the results include the list of surfacial contacting atoms, their charges and Pearson correlation coefficient, the list of contacting surface points with the electrostatic potential (computed for the isolated molecules) and Pearson correlation coefficient, the electrostatic and hydrophobic free energy with different contributions for the isolated molecules, their complex and the difference for all terms. The software is readily usable for any molecular complex in solution. Full article

Thirty-four binary systems of nitrofurantoin with pyridine derivatives were analyzed by combining virtual (molecular complementarity prediction and hydrogen bond propensity calculations) and experimental (liquid-assisted grinding) screening methods. A new modification of the hydrogen bond propensity calculation method (the integrated hydrogen bond propensity calculation method) with significantly improved virtual screening efficiency was proposed. Novel cocrystals of nitrofurantoin with 3-aminopyridine and 2-(1H-Imidazol-2-yl)pyridine were discovered. The crystal structures of the new cocrystals were determined from single-crystal X-ray diffraction data, and the hydrogen bond patterns were studied in conjunction with the Molecular Electrostatic Potential maps of the components. The nitrofurantoin cocrystal with 3-aminopyridine was found to exist in two polymorphic modifications. The origins of the different stability of the polymorphic forms were rationalized both in terms of total lattice enthalpy and free energy derived from periodic DFT-D3 calculations and in terms of the non-covalent interaction energy distribution in crystal. Full article

Introduction. Glioblastoma (GBM) is the most aggressive primary brain tumor in adults. Despite a growing understanding of glioblastoma pathology, the prognosis remains poor. Methods. In this study, we used a previously extensively benchmarked algorithm to retrieve immune receptor (IR) recombination reads from GBM exome files available from the cancer genome atlas. The T-cell receptor complementarity determining region-3 (CDR3) amino acid sequences that represent the IR recombination reads were assessed and used for the generation of chemical complementarity scores (CSs) that represent potential binding interactions with cancer testis antigens (CTAs), which is an approach particularly suited to a big data setting. Results. The electrostatic CSs representing the TRA and TRB CDR3s and the CTAs, SPAG9, GAGE12E, and GAGE12F, indicated that an increased electrostatic CS was associated with worse disease-free survival (DFS). We also assessed the RNA expression of immune marker genes, which indicated that a high-level expression of SPHK2 and CIITA genes also correlated with high CSs and worse DFS. Furthermore, apoptosis-related gene expression was revealed to be lower when the TCR CDR3-CTA electrostatic CSs were high. Conclusion. Adaptive IR recombination reads from exome files have the potential to aid in GBM prognoses and may provide opportunities to detect unproductive immune responses. Full article

Enterocytozoon hepatopenaei (EHP) causes slow growth syndrome in shrimp, resulting in huge economic losses for the global shrimp industry. Despite worldwide reports, there are no effective therapeutics for controlling EHP infections. In this study, five potential druggable targets of EHP, namely, aquaporin (AQP), cytidine triphosphate (CTP) synthase, thymidine kinase (TK), methionine aminopeptidase2 (MetAP2), and dihydrofolate reductase (DHFR), were identified via functional classification of the whole EHP proteome. The three-dimensional structures of the proteins were constructed using the artificial-intelligence-based program AlphaFold 2. Following the prediction of druggable sites, the ZINC15 and ChEMBL databases were screened against targets using docking-based virtual screening. Molecules with affinity scores ≥ 7.5 and numbers of interactions ≥ 9 were initially selected and subsequently enriched based on their ADMET properties and electrostatic complementarities. Five compounds were finally selected against each target based on their complex stabilities and binding energies. The compounds CHEMBL3703838, CHEMBL2132563, and CHEMBL133039 were selected against AQP; CHEMBL1091856, CHEMBL1162979, and CHEMBL525202 against CTP synthase; CHEMBL4078273, CHEMBL1683320, and CHEMBL3674540 against TK; CHEMBL340488, CHEMBL1966988, and ZINC000828645375 against DHFR; and CHEMBL3913373, ZINC000016682972, and CHEMBL3142997 against MetAP2.The compounds exhibited high stabilities and low binding free energies, indicating their abilities to suppress EHP infections; however, further validation is necessary for determining their efficacy. Full article

The recent outbreak of Monkeypox virus requires the development of a vaccine specifically directed against this virus as quickly as possible. We propose here a new strategy based on a two-step analysis combining (i) the search for binding domains of viral proteins to gangliosides present in lipid rafts of host cells, and (ii) B epitope predictions. Based on previous studies of HIV and SARS-CoV-2 proteins, we show that the Monkeypox virus cell surface-binding protein E8L possesses a ganglioside-binding motif consisting of several subsites forming a ring structure. The binding of the E8L protein to a cluster of gangliosides GM1 mimicking a lipid raft domain is driven by both shape and electrostatic surface potential complementarities. An induced-fit mechanism unmasks selected amino acid side chains of the motif without significantly affecting the secondary structure of the protein. The ganglioside-binding motif overlaps three potential linear B epitopes that are well exposed on the unbound E8L surface that faces the host cell membrane. This situation is ideal for generating neutralizing antibodies. We thus suggest using these three sequences derived from the E8L protein as immunogens in a vaccine formulation (recombinant protein, synthetic peptides or genetically based) specific for Monkeypox virus. This lipid raft/ganglioside-based strategy could be used for developing therapeutic and vaccine responses to future virus outbreaks, in parallel to existing solutions. Full article

Protein-protein interactions often involve a complex system of intermolecular interactions between residues and atoms at the binding site. A comprehensive exploration of these interactions can help reveal key residues involved in protein-protein recognition that are not obvious using other protein analysis techniques. This paper presents and extends DiffBond, a novel method for identifying and classifying intermolecular bonds while applying standard definitions of bonds in chemical literature to explain protein interactions. DiffBond predicted intermolecular bonds from four protein complexes: Barnase-Barstar, Rap1a-raf, SMAD2-SMAD4, and a subset of complexes formed from three-finger toxins and nAChRs. Based on validation through manual literature search and through comparison of two protein complexes from the SKEMPI dataset, DiffBond was able to identify intermolecular ionic bonds and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. DiffBond predictions on bond existence were also strongly correlated with observations of Gibbs free energy change and electrostatic complementarity in mutational experiments. DiffBond can be a powerful tool for predicting and characterizing influential residues in protein-protein interactions, and its predictions can support research in mutational experiments and drug design. Full article

Early-stage pancreatic cancer remains challenging to detect, leading to a poor five-year patient survival rate. This obstacle necessitates the development of early detection approaches based on novel technologies and materials. In this work, the presence of a specific pancreatic cancer-derived miRNA (pre-miR-132) is detected using the fluorescence properties of biocompatible nitrogen-doped graphene quantum dots (NGQDs) synthesized using a bottom-up approach from a single glucosamine precursor. The sensor platform is comprised of slightly positively charged (1.14 $\pm$ 0.36 mV) NGQDs bound via $\pi -\pi$ stacking and/or electrostatic interactions to the negatively charged (−22.4 $\pm$ 6.00 mV) bait ssDNA; together, they form a complex with a 20 nm average size. The NGQDs’ fluorescence distinguishes specific single-stranded DNA sequences due to bait–target complementarity, discriminating them from random control sequences with sensitivity in the micromolar range. Furthermore, this targetability can also detect the stem and loop portions of pre-miR-132, adding to the practicality of the biosensor. This non-invasive approach allows cancer-specific miRNA detection to facilitate early diagnosis of various forms of cancer. Full article

Despite the recent promising results of MDMA (3,4-methylenedioxy-methamphetamine) as a psychotherapeutic agent and its history of misuse, little is known about its molecular mode of action. MDMA enhances monoaminergic neurotransmission in the brain and its valuable psychoactive effects are associated to a dual action on the 5-HT transporter (SERT). This drug inhibits the reuptake of 5-HT (serotonin) and reverses its flow, acting as a substrate for the SERT, which possesses a central binding site (S1) for antidepressants as well as an allosteric (S2) one. Previously, we characterized the spatial binding requirements for MDMA at S1. Here, we propose a structure-based mechanistic model of MDMA occupation and translocation across both binding sites, applying ensemble binding space analyses, electrostatic complementarity, and Monte Carlo energy perturbation theory. Computed results were correlated with experimental data (r = 0.93 and 0.86 for S1 and S2, respectively). Simulations on all hSERT available structures with Gibbs free energy estimations (ΔG) revealed a favourable and pervasive dual binding mode for MDMA at S2, i.e., adopting either a 5-HT or an escitalopram-like orientation. Intermediate ligand conformations were identified within the allosteric site and between the two sites, outlining an internalization pathway for MDMA. Among the strongest and more frequent interactions were salt bridges with Glu494 and Asp328, a H-bond with Thr497, a π-π with Phe556, and a cation-π with Arg104. Similitudes and differences with the allosteric binding of 5-HT and antidepressants suggest that MDMA may have a distinctive chemotype. Thus, our models may provide a framework for future virtual screening studies and pharmaceutical design and to develop hSERT allosteric compounds with a unique psychoactive MDMA-like profile. Full article

The persistency of COVID-19 in the world and the continuous rise of its variants demand new treatments to complement vaccines. Computational chemistry can assist in the identification of moieties able to lead to new drugs to fight the disease. Fullerenes and carbon nanomaterials can interact with proteins and are considered promising antiviral agents. Here, we propose the possibility to repurpose fullerenes to clog the active site of the SARS-CoV-2 protease, M^pro. Through the use of docking, molecular dynamics, and energy decomposition techniques, it is shown that C₆₀ has a substantial binding energy to the main protease of the SARS-CoV-2 virus, M^pro, higher than masitinib, a known inhibitor of the protein. Furthermore, we suggest the use of C₇₀ as an innovative scaffold for the inhibition of SARS-CoV-2 M^pro. At odds with masitinib, both C₆₀ and C₇₀ interact more strongly with SARS-CoV-2 M^pro when different protonation states of the catalytic dyad are considered. The binding of fullerenes to M^pro is due to shape complementarity, i.e., vdW interactions, and is aspecific. As such, it is not sensitive to mutations that can eliminate or invert the charges of the amino acids composing the binding pocket. Fullerenic cages should therefore be more effective against the SARS-CoV-2 virus than the available inhibitors such as masinitib, where the electrostatic term plays a crucial role in the binding. Full article

The HIV-1 Gag polyprotein plays essential roles during the late stage of the HIV-1 replication cycle, and has recently been identified as a promising therapeutic target. The N-terminal portion of the HIV-1 Gag polyprotein encodes the myristoylated matrix (MA) protein, which functions in the trafficking of the structural proteins to the plasma membrane (PM) and facilitation of envelope incorporation into budding virus. Numerous host cell proteins interact with the MA portion of the Gag polyprotein during this process. One such factor is the ubiquitous calcium-binding protein calmodulin (CaM), which interacts preferentially with myristoylated proteins, thereby regulating cell physiology. The exact role of this interaction is poorly understood to date. Atomic resolution structures revealed the nature of the CaM-MA interaction for clade B isolates. In this study, we expanded our knowledge and characterized biophysically and computationally the CaM interaction with MA from other HIV-1 clades and discovered differences in the CaM recognition as compared to the prototypical clade B MA, with significant alterations in the interaction with the MA protein from clade C. Structural investigation and in silico mutational analysis revealed that HIV-1 MA protein from clade C, which is responsible for the majority of global HIV-1 infections, interacts with lower affinity and altered kinetics as compared to the canonical clade B. This finding may have implications for additional altered interaction networks as compared to the well-studied clade B. Our analysis highlights the importance of expanding investigations of virus-host cell factor interaction networks to other HIV-1 clades. Full article

The serine protease, DegP exhibits proteolytic and chaperone activities, essential for cellular protein quality control and normal cell development in eukaryotes. The P. falciparum DegP is essential for the parasite survival and required to combat the oscillating thermal stress conditions during the infection, protein quality checks and protein homeostasis in the extra-cytoplasmic compartments, thereby establishing it as a potential target for drug development against malaria. Previous studies have shown that diisopropyl fluorophosphate (DFP) and the peptide SPMFKGV inhibit E. coli DegP protease activity. To identify novel potential inhibitors specific to PfDegP allosteric and the catalytic binding sites, we performed a high throughput in silico screening using Malaria Box, Pathogen Box, Maybridge library, ChEMBL library and the library of FDA approved compounds. The screening helped identify five best binders that showed high affinity to PfDegP allosteric (T0873, T2823, T2801, RJC02337, CD00811) and the catalytic binding site (T0078L, T1524, T2328, BTB11534 and 552691). Further, molecular dynamics simulation analysis revealed RJC02337, BTB11534 as the best hits forming a stable complex. WaterMap and electrostatic complementarity were used to evaluate the novel bio-isosteric chemotypes of RJC02337, that led to the identification of 231 chemotypes that exhibited better binding affinity. Further analysis of the top 5 chemotypes, based on better binding affinity, revealed that the addition of electron donors like nitrogen and sulphur to the side chains of butanoate group are more favoured than the backbone of butanoate group. In a nutshell, the present study helps identify novel, potent and Plasmodium specific inhibitors, using high throughput in silico screening and bio-isosteric replacement, which may be experimentally validated. Full article