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Adopting computational tools for analyzing extensive biological datasets has profoundly transformed our understanding and interpretation of biological phenomena. Innovative platforms have emerged, providing automated analysis to unravel essential insights about proteins and the complexities of their interactions. These computational advancements align with traditional studies, which employ experimental techniques to discern and quantify physical and functional protein-protein interactions (PPIs). Among these techniques, tandem mass spectrometry is notably recognized for its precision and sensitivity in identifying PPIs. These approaches might serve as important information enabling the identification of PPIs with potential pharmacological significance. This review aims to convey our experience using computational tools for detecting PPI networks and offer an analysis of platforms that facilitate predictions derived from experimental data.
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INTRODUCTION: The use of triphenylphosphonium cation (TPP+) linked to phenolic compounds by alkyl chains has a significant relevance as a mitochondrial delivery strategy in biomedicine because it affects mitochondrial bioenergetics in models of noncommunicable diseases such as cancer and cardiovascular-related conditions. Studies indicate that a long alkyl chain (10-12 carbon) increases the mitochondrial accumulation of TPP+-linked drugs. In contrast, other studies show that these compounds are consistently toxic to micromolar concentrations (as observed in platelets). In the present study, we evaluated the in vitro effect of three series of triphenylphosphonium-linked acyl hydroquinones derivates on the metabolism and function of human platelets using 3-9 carbons for the alkyl linker. Those were assessed to determine the role of the length of the alkyl chain linker on platelet toxicity. METHODS: Human platelets were exposed in vitro to different concentrations (2-40 µM) of every compound; cellular viability, phosphatidylserine exposition, mitochondrial membrane potential (ΔΨm), intracellular calcium release, and intracellular ROS generation were assessed by flow cytometry. An in silico energetic profile was generated with Umbrella sampling molecular dynamics (MD). RESULTS AND CONCLUSIONS: There was an increase in cytotoxic activity directly related to the length of the acyl chain and lipophilicity, as seen by three techniques, and this was consistent with a decrease in ΔΨm. The in silico energetic profiles point out that the permeability of the mitochondrial membrane may be involved in the cytotoxicity of phosphonium salts. This information may be relevant for the design of new TPP+ -based drugs with a safe cardiovascular profile.
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Antineoplásicos , Hidroquinonas , Humanos , Hidroquinonas/farmacología , Mitocondrias/metabolismo , Membranas Mitocondriales/metabolismo , Antineoplásicos/farmacología , Metabolismo Energético , Compuestos Organofosforados/farmacología , Compuestos Organofosforados/metabolismo , Potencial de la Membrana MitocondrialRESUMEN
Glucosinolate transporters (GTRs) are part of the nitrate/peptide transporter (NPF) family, members of which also transport specialized secondary metabolites as substrates. Glucosinolates are defense compounds derived from amino acids. We selected 4-methylthiobutyl (4MTB) and indol-3-ylmethyl (I3M) glucosinolates to study how GTR1 from Arabidopsis thaliana transports these substrates in computational simulation approaches. The designed pipeline reported here includes massive docking of 4MTB and I3M in an ensemble of GTR1 conformations (in both inward and outward conformations) extracted from molecular dynamics simulations, followed by clustered and substrate-protein interactions profiling. The identified key residues were mutated, and their role in substrate transport was tested. We were able to identify key residues that integrate a major binding site of these substrates, which is critical for transport activity. In silico approaches employed here represent a breakthrough in the plant transportomics field, as the identification of key residues usually takes a long time if performed from a purely wet-lab experimental perspective. The inclusion of structural bioinformatics in the analyses of plant transporters significantly speeds up the knowledge-gaining process and optimizes valuable time and resources.
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Arabidopsis/metabolismo , Glucosinolatos/metabolismo , Proteínas de Transporte de Monosacáridos/química , Proteínas de Transporte de Monosacáridos/metabolismo , Proteínas de Arabidopsis/química , Proteínas de Arabidopsis/metabolismo , Transporte Biológico , Butiratos/metabolismo , Indoles/metabolismo , Modelos Moleculares , Simulación del Acoplamiento Molecular , Unión Proteica , Conformación Proteica , Tioglucósidos/metabolismoRESUMEN
The sigma 1 receptor (S1R) is an enigmatic ligand-operated chaperone involved in many important biological processes, and its functions are not fully understood yet. Herein, we developed a novel series of bitopic S1R ligands as versatile tools to investigate binding processes, allosteric modulation, and the oligomerization mechanism. These molecules have been prepared in the enantiopure form and subjected to a preliminary biological evaluation, while in silico investigations helped to rationalize the results. Compound 7 emerged as the first bitopic S1R ligand endowed with low nanomolar affinity (Ki = 2.6 nM) reported thus far. Computational analyses suggested that 7 may stabilize the open conformation of the S1R by simultaneously binding the occluded primary binding site and a peripheral site on the cytosol-exposed surface. These findings pave the way to new S1R ligands with enhanced activity and/or selectivity, which could also be used as probes for the identification of a potential allosteric site.
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Encéfalo/metabolismo , Receptores sigma/metabolismo , Animales , Sitios de Unión , Relación Dosis-Respuesta a Droga , Cobayas , Ligandos , Estructura Molecular , Neuritas/metabolismo , Células PC12 , Ratas , Receptores sigma/química , Relación Estructura-Actividad , Receptor Sigma-1RESUMEN
Mass spectrometry-based proteomics methods are widely used to identify and quantify protein complexes involved in diverse biological processes. Specifically, tandem mass spectrometry methods represent an accurate and sensitive strategy for identifying protein-protein interactions. However, most of these approaches provide only lists of peptide fragments associated with a target protein, without performing further analyses to discriminate physical or functional protein-protein interactions. Here, we present the PPI-MASS web server, which provides an interactive analytics platform to identify protein-protein interactions with pharmacological potential by filtering a large protein set according to different biological features. Starting from a list of proteins detected by MS-based methods, PPI-MASS integrates an automatized pipeline to obtain information of each protein from freely accessible databases. The collected data include protein sequence, functional and structural properties, associated pathologies and drugs, as well as location and expression in human tissues. Based on this information, users can manipulate different filters in the web platform to identify candidate proteins to establish physical contacts with a target protein. Thus, our server offers a simple but powerful tool to detect novel protein-protein interactions, avoiding tedious and time-consuming data postprocessing. To test the web server, we employed the interactome of the TRPM4 and TMPRSS11a proteins as a use case. From these data, protein-protein interactions were identified, which have been validated through biochemical and bioinformatic studies. Accordingly, our web platform provides a comprehensive and complementary tool for identifying protein-protein complexes assisting the future design of associated therapies.
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Significant progresses have been made to understand the molecular basis of the Sigma1 receptor (S1R) operating in normal and pathological conditions. S1R is a transmembrane protein that participates in a wide variety of processes at the central nervous system; hence, its function has been associated with mental and neurological disorders. Several ligands have been proposed to regulate the function of S1R revealing a high plasticity of the ligand-binding pocket. Previous drug-design studies have been mainly based on pharmacophore models; however, the recently revealed crystal structure of S1R provides an excellent opportunity for verifying previous predictions and for evaluating the binding of novel compounds. Interestingly, the crystal structure shows that the binding pocket of S1R is highly occluded from solvent; therefore, it is not clear how ligands access this site. In the present work, we applied steered molecular dynamics (SMD) simulations to open the occluded ligand-binding pocket in the S1R crystal structure and to determine the preferred ligand pathway to enter and exit the binding site. The intracellular surface of the ß-barrel ligand-binding region was found the most favorable route to accommodate ligands. This route supports the binding of RC-33 (our in-house-developed S1R modulator) and a new bivalent derivative that constitutes the first divalent structure shown to interact with S1R. Free energy calculations of these compounds associated with S1R agree with experimental Ki values and provide molecular insights of the binding mode of modulators that could access the S1R ligand-binding pocket through the cytoplasmic region.