Observing Noncovalent Interactions in Experimental Electron Density for Macromolecular Systems: A Novel Perspective for Protein–Ligand Interaction Research

Computer aided design of inhibitor molecules against Vpr protein from different HIV-1 subtypes

HIV-1 is a retrovirus that affects the human immune system and consequently leads to the development of AIDS. The high mutation rate in HIV-1 produces different subtypes which underscores the development of new therapeutics against it. This study aims to develop a novel small molecule that can be used as a potential inhibitor against the Vpr protein of all the subtypes of HIV-1. The druggable pockets of the Vpr protein of each subtype were identified and the conformational stability of these pockets was studied. The structure-based Drug Design method was used to design small molecules against the high-scoring pocket from each subtype individually using AutoGrow4 software. Molecules with strong binding affinity were selected from each subtype individually and binding affinity was checked for all the subtypes. Considering druggability and ADMET properties, we have identified two novel molecules that act as potential Vpr protein inhibitors. Both the molecules were shown to form stable complexes with the Vpr proteins of all the subtypes. The biological activity of both molecules was examined using DFT calculation. This study may provide some insight into developing of new therapies in HIV-1 treatment by interrupting protein-protein interaction.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00318-4.

Batzelladine D, a Marine Natural Product, Reverses the Fluconazole Resistance Phenotype Mediated by Transmembrane Transporters in Candida albicans and Interferes with Its Biofilm: An In Vitro and In Silico Study

Numerous Candida species are responsible for fungal infections; however, Candida albicans stands out among the others. Treatment with fluconazole is often ineffective due to the resistance phenotype mediated by transmembrane transporters and/or biofilm formation, mechanisms of resistance commonly found in C. albicans strains. A previous study by our group demonstrated that batzelladine D can inhibit the Pdr5p transporter in Saccharomyces cerevisiae. In the present study, our aim was to investigate the efficacy of batzelladine D in inhibiting the main efflux pumps of Candida albicans, CaCdr1p and CaCdr2p, as well as to evaluate the effect of the compound on C. albicans biofilm. Assays were conducted using a clinical isolate of Candida albicans expressing both transporters. Additionally, to allow the study of each transporter, S. cerevisiae mutant strains overexpressing CaCdr1p or CaCdr2p were used. Batzelladine D was able to reverse the fluconazole resistance phenotype by acting on both transporters. The compound synergistically improved the effect of fluconazole against the clinical isolate when tested in the Caenorhabditis elegans animal model. Moreover, the compound disrupted the preformed biofilm. Based on the obtained data, the continuation of batzelladine D studies as a potential new antifungal agent and/or chemosensitizer in Candida albicans infections can be suggested.

Red-emitting 4-methyl coumarin fused barbituric acid as an electrochemical sensor for catechol detection and probe for latent fingerprints

Herein, we have reported a red-emitting 4-methyl coumarin fused barbituric acid azo dye (4-MCBA) synthesized by conventional method. Density functional theory (DFT) studies of tautomer compounds were done using (B3LYP) with a basis set of 6-31G(d,p). NLO analysis has shown that tautomer has mean first-order hyperpolarisabilities (β) value of 1.8188 × 10-30 esu and 1.0470 × 10-30 esu for azo and hydrazone forms, respectively, which is approximately nine and five times greater than the magnitude of urea. 4-MCBA exhibited two absorption peaks in the range of 290-317 and 379-394 nm, and emission spectra were observed at 536 nm. CV study demonstrated that the modified 4-MCBA/MGC electrode exhibited excellent electrochemical sensitivity towards the detection of catechol and the detection limit is 9.39 μM under optimum conditions. The 4-MCBA employed as a fluorescent probe for the visualisation of LFPs on various surfaces exhibited Level-I to level-II LFPs, with low background interference.

Transport mechanism of presynaptic high-affinity choline uptake by CHT1

Choline is a vital nutrient and a precursor for the biosynthesis of essential metabolites, including acetylcholine (ACh), that play a central role in fetal development, especially in the brain. In cholinergic neurons, the high-affinity choline transporter (CHT1) provides an extraordinarily efficient reuptake mechanism to reutilize choline derived from intrasynaptical ACh hydrolysis and maintain ACh synthesis in the presynapse. Here, we determined structures of human CHT1 in three discrete states: the outward-facing state bound with the competitive inhibitor hemicholinium-3 (HC-3); the inward-facing occluded state bound with the substrate choline; and the inward-facing apo open state. Our structures and functional characterizations elucidate how the inhibitor and substrate are recognized. Moreover, our findings shed light on conformational changes when transitioning from an outward-facing to an inward-facing state and establish a framework for understanding the transport cycle, which relies on the stabilization of the outward-facing state by a short intracellular helix, IH1.

Analyzing the cation-aromatic interactions in proteins: Cation-aromatic database V2.0

The cation-aromatic database (CAD) is a comprehensive repository of cation-aromatic motifs found in experimentally determined protein structures, first reported in 2007 [Proteins, 2007, 67, 1179]. The present article is an update of CAD that contains information of approximately 27.26 million cation-aromatic motifs. CAD uses three distance parameters (r, d1, and d2) to determine the position of the cation relative to the centroid of the aromatic residue and classifies the motifs as cation-π or cation-σ interactions. As of June 2023, about 193 936 protein structures were retrieved from Protein Data Bank, and this resulted in the identification of an impressive number of 27 255 817 cation-aromatic motifs. Among these motifs, spherical motifs constituted 94.09%, while cylindrical motifs made up the remaining 5.91%. When considering the interaction of metal ions with aromatic residues, 965 564 motifs are identified. Remarkably, 82.08% of these motifs involved the binding of metal ions to the amino acid HIS. Moreover, the analysis of binding preferences between cations and aromatic residues revealed that the HIS-HIS, PHE-ARG, and TRP-ARG pairs exhibited a preferential geometry. The motif pair HIS-HIS was the most prevalent, accounting for 19.87% of the total, closely followed by TYR-LYS at 10.17%. Conversely, the motif pair TRP-HIS had the lowest occurrence, representing only 4.20% of the total. The data generated help in revealing the characteristics and biological functions of cation-aromatic interactions in biological molecules. The updated version of CAD (Cation-Aromatic Database V2.0) can be accessed at https://acds.neist.res.in/cadv2.

Analyzing the aromatic-aromatic interactions in proteins: A2ID 2.0

The Aromatic-Aromatic Interactions Database (A2ID) is a comprehensive repository dedicated to documenting aromatic-aromatic (π-π) networks observed in experimentally determined protein structures. The first version of A2ID was reported in 2011 [Int J Biol Macromol, 2011, 48, 540]. It has undergone a series of significant updates, leading to its current version, which focuses on the identification and analysis of 3,444,619 π-π networks from proteins. The geometrical parameters such as centroid-centroid distances (r) and interplanar angles (ϕ) were used to identify and characterize π-π networks. It was observed that among the 84,500 proteins with at least one aromatic π-π network, about 92.50 % of the instances are found to be either 2π (77.34 %) or 3π (15.23 %) networks. The analysis of interacting amino acid pairs in 2π networks indicated a dominance of PHE residues followed by TYR. The updated version of A2ID incorporates analysis of π-π networks based on SCOP2 and ECOD classifiers, in addition to the existing SCOP, CATH, and EC classifications. This expanded scope allows researchers to explore the characteristics and functional implications of π-π networks in protein structures from multiple perspectives. The current version of A2ID along with its extensive dataset and detailed geometric information is publicly accessible using https://acds.neist.res.in/a2idv2.

1,2,3-Triazoles in Biomolecular Crystallography: A Geometrical Data-Mining Approach

The 1,2,3-triazole scaffold has become very attractive to identify new chemical entities in drug discovery projects. Despite the widespread use of click chemistry to synthesize numerous 123Ts, there are few drugs on the market that incorporate this scaffold as a substructure. To investigate the true potential of 123Ts in protein-ligand interactions, we examined the noncovalent interactions between the 1,2,3-triazole ring and amino acids in protein-ligand cocrystals using a geometrical approach. For this purpose, we constructed a nonredundant database of 220 PDB IDs from available 123T-protein cocrystal structures. Subsequently, using the Protein Ligand Interaction Profiler web platform (PLIP), we determined whether 1,2,3-triazoles primarily act as linkers or if they can be considered interactive scaffolds. We then manually analyzed the geometrical descriptors from 333 interactions between 1,4-disubstituted 123T rings and amino acid residues in proteins. This study demonstrates that 1,2,3-triazoles exhibit diverse preferred interactions with amino acids, which contribute to protein-ligand binding.

Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening

The quest for effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by ED's ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS identified four active inhibitors of 3CLpro, with the most effective showing an IC50 value of 1.9 µM. We also developed an online database containing experimental ED grids for over 17,000 proteins to facilitate the use of ExptGMS for academic users.

The NCIWEB Server: A Novel Implementation of the Noncovalent Interactions Index for Biomolecular Systems

It is well-known that the activity and function of proteins is strictly correlated with their secondary, tertiary, and quaternary structures. Their biological role is regulated by their conformational flexibility and global fold, which, in turn, is largely governed by complex noncovalent interaction networks. Because of the large size of proteins, the analysis of their noncovalent interaction networks is challenging, but can provide insights into the energetics of conformational changes or protein-protein and protein-ligand interactions. The noncovalent interaction (NCI) index, based on the reduced density gradient, is a well-established tool for the detection of weak contacts in biological systems. In this work, we present a web-based application to expand the use of this index to proteins, which only requires a molecular structure as input and provides a mapping of the number, type, and strength of noncovalent interactions. Structure preparation is automated and allows direct importing from the PDB database, making this server (https://nciweb.dsi.upmc.fr) accessible to scientists with limited experience in bioinformatics. A quick overview of this tool and concise instructions are presented, together with an illustrative application.

Structural basis of TRPV3 inhibition by an antagonist

The TRPV3 channel plays vital roles in skin physiology. Dysfunction of TRPV3 causes skin diseases, including Olmsted syndrome. However, the lack of potent and selective inhibitors impedes the validation of TRPV3 as a therapeutic target. In this study, we identified Trpvicin as a potent and subtype-selective inhibitor of TRPV3. Trpvicin exhibits pharmacological potential in the inhibition of itch and hair loss in mouse models. Cryogenic electron microscopy structures of TRPV3 and the pathogenic G573S mutant complexed with Trpvicin reveal detailed ligand-binding sites, suggesting that Trpvicin inhibits the TRPV3 channel by stabilizing it in a closed state. Our G573S mutant structures demonstrate that the mutation causes a dilated pore, generating constitutive opening activity. Trpvicin accesses additional binding sites inside the central cavity of the G573S mutant to remodel the channel symmetry and block the channel. Together, our results provide mechanistic insights into the inhibition of TRPV3 by Trpvicin and support TRPV3-related drug development.

A pocket-based 3D molecule generative model fueled by experimental electron density

We report for the first time the use of experimental electron density (ED) as training data for the generation of drug-like three-dimensional molecules based on the structure of a target protein pocket. Similar to a structural biologist building molecules based on their ED, our model functions with two main components: a generative adversarial network (GAN) to generate the ligand ED in the input pocket and an ED interpretation module for molecule generation. The model was tested on three targets: a kinase (hematopoietic progenitor kinase 1), protease (SARS-CoV-2 main protease), and nuclear receptor (vitamin D receptor), and evaluated with a reference dataset composed of over 8000 compounds that have their activities reported in the literature. The evaluation considered the chemical validity, chemical space distribution-based diversity, and similarity with reference active compounds concerning the molecular structure and pocket-binding mode. Our model can generate molecules with similar structures to classical active compounds and novel compounds sharing similar binding modes with active compounds, making it a promising tool for library generation supporting high-throughput virtual screening. The ligand ED generated can also be used to support fragment-based drug design. Our model is available as an online service to academic users via https://edmg.stonewise.cn/#/create .