Analysis Of Protein-ligand Interactions Research Articles

Exploration of phytoconstituents of Medhya Rasayana herbs to identify potential inhibitors for cerebroside sulfotransferase through high-throughput screening.

Cerebroside sulfotransferase (CST) is a key enzyme in sulfatide biosynthesis and regulation of the myelin sheath in the nervous system. To counter sulfatide accumulation with the deficiency of aryl sulfatase A, CST is considered a target protein in substrate reduction therapy in metachromatic leukodystrophy. In this study, 461 phytoconstituents from four herbs of Medhya Rasayana were screened using multi-pronged virtual screening methods including molecular docking, molecular dynamics (MD) simulation, and reverse pharmacophore analysis. The initial screening of the top 15 hits was based on the binding affinity of the compounds toward the CST substrate-binding site using the lowest free energy of a binding score cutoff of ≤ -7.5 kcal/mol, with the number of conformations in the largest cluster more than 75. The absorption, distribution, metabolism, and excretion (ADME) and toxicity-based pharmacokinetic analysis delivered the top four hits: 18alpha-glycyrrhetinic acid, lupeol, alpha carotene, and beta-carotene, with high blood-brain barrier permeability and negligible toxicity. Furthermore, a 100-ns simulation of protein-ligand complexes with a trajectory analysis of structural deviation, compactness, intramolecular interactions, principal component analysis, free energy landscape, and dynamic cross-correlation analysis showed the binding potential and positioning of the four hits in the binding pocket. Thus, an in-depth analysis of protein-ligand interactions from pre- and post-molecular dynamics simulation, along with reverse pharmacophore mapping, suggests that 18alpha-glycyrrhetinic acid is the most potent and specific CST inhibitor, while beta-carotene could be considered the second most potent compound for CST inhibition as it also exhibited overall stability throughout the simulation. Therefore, the computational drug screening approach applied in this study may contribute to the development of oral drugs as a therapeutic option for metachromatic leukodystrophy.

Machine Learning Meets Physics-based Modeling: A Mass-spring System to Predict Protein-ligand Binding Affinity.

Computational assessment of the energetics of protein-ligand complexes is a challenge in the early stages of drug discovery. Previous comparative studies on computational methods to calculate the binding affinity showed that targeted scoring functions outperform universal models. The goal here is to review the application of a simple physics-based model to estimate the binding. The focus is on a mass-spring system developed to predict binding affinity against cyclin-dependent kinase. Publications in PubMed were searched to find mass-spring models to predict binding affinity. Crystal structures of cyclin-dependent kinases found in the protein data bank and two web servers to calculate affinity based on the atomic coordinates were employed. One recent study showed how a simple physics-based scoring function (named Taba) could contribute to the analysis of protein-ligand interactions. Taba methodology outperforms robust physics-based models implemented in docking programs such as AutoDock4 and Molegro Virtual Docker. Predictive metrics of 27 scoring functions and energy terms highlight the superior performance of the Taba scoring function for cyclin- dependent kinase. The recent progress of machine learning methods and the availability of these techniques through free libraries boosted the development of more accurate models to address protein-ligand interactions. Combining a naïve mass-spring system with machine-learning techniques generated a targeted scoring function with superior predictive performance to estimate pKi.

Design, Synthesis, and Antifungal Activities of Novel Potent Fluoroalkenyl Succinate Dehydrogenase Inhibitors.

The development of new fungicide molecules is a crucial task for agricultural chemists to enhance the effectiveness of fungicides in agricultural production. In this study, a series of novel fluoroalkenyl modified succinate dehydrogenase inhibitors were synthesized and evaluated for their antifungal activities against eight fungi. The results from the in vitro antifungal assay demonstrated that compound 34 exhibited superior activity against Rhizoctonia solani with an EC50 value of 0.04 μM, outperforming commercial fluxapyroxad (EC50 = 0.18 μM) and boscalid (EC50 = 3.07 μM). Furthermore, compound 34 showed similar effects to fluxapyroxad on other pathogenic fungi such as Sclerotinia sclerotiorum (EC50 = 1.13 μM), Monilinia fructicola (EC50 = 1.61 μM), Botrytis cinerea (EC50 = 1.21 μM), and also demonstrated protective and curative efficacies in vivo on rapeseed leaves and tomato fruits. Enzyme activity experiments and protein-ligand interaction analysis by surface plasmon resonance revealed that compound 34 had a stronger inhibitory effect on succinate dehydrogenase compared to fluxapyroxad. Additionally, molecular docking and DFT calculation confirmed that the fluoroalkenyl unit in compound 34 could enhance its binding capacity with the target protein through p-π conjugation and hydrogen bond interactions.

Applications of Surface Plasmon Resonance (SPR) to the Study of Diverse Protein-Ligand Interactions.

Functional characterization of enzymes/proteins requires determination of the binding affinity of small molecules or other biomolecules with the target proteins. Several available techniques, such as proteomics and drug discovery strategies, require a precise and high-throughput assay for rapid and reliable screening of potential candidates for further testing. Surface plasmon resonance (SPR), a well-established label-free technique, directly measures biomolecular affinities. SPR assays require immobilization of one interacting component (ligand) on a conductive metal (mostly gold or silver) and a continuous flow of solution containing potential binding partner (analyte) across the surface. The SPR phenomenon occurs when polarized light excites the electrons at the interface of the metal and the dielectric medium to generate electromagnetic waves that propagate parallel to the surface. Changes in the refractive index due to interaction between the ligand and analyte are measured by detecting the reflected light, providing real-time data on kinetics and specificity. A prominent use of SPR is identifying compounds in crude plant extracts that bind to specific molecules. Procedures that utilize SPR are becoming increasingly applicable outside the laboratory setting, and SPR imaging and localized SPR (LSPR) are cheaper and more portable alternative for in situ detection of plant or mammalian pathogens and drug discovery studies. LSPR, in particular, has the advantage of direct attachment to test tissues in live-plant studies. Here, we describe three protocols utilizing SPR-based assays for precise analysis of protein-ligand interactions. © 2024 Wiley Periodicals LLC. Basic Protocol 1: SPR comparison of binding affinities of viral reverse transcriptase polymorphisms Basic Protocol 2: SPR screening of crude plant extract for protein-binding agents Basic Protocol 3: Localized SPR-based antigen detection using antibody-conjugated gold nanoparticles.

Elucidating the structural basis of vitamin B12 derivatives as novel potent inhibitors of PTP1B: Insights from inhibitory mechanisms using Gaussian accelerated molecular dynamics (GaMD) and in vitro study

Vitamin B12 is a group of biologically active cobalamin compounds. In this study, we investigated the inhibitory effects of methylcobalamin (MeCbl) and hydroxocobalamin acetate (OHCbl Acetate) on protein tyrosine phosphatase 1B (PTP1B). MeCbl and OHCbl Acetate exhibited an IC50 of approximately 58.390 ± 2.811 μM and 8.998 ± 0.587 μM, respectively. The Ki values of MeCbl and OHCbl Acetate were 25.01 μM and 4.04 μM respectively. To elucidate the inhibition mechanism, we conducted a 500 ns Gaussian accelerated molecular dynamics (GaMD) simulation. Utilizing PCA and tICA, we constructed Markov state models (MSM) to examine secondary structure changes during motion. Our findings revealed that the α-helix at residues 37–42 remained the most stable in the PTP1B-OHCbl Acetate system. Furthermore, upon binding of OHCbl Acetate or MeCbl, the WPD loop of PTP1B moved inward to the active pocket, forming a closed conformation and potentially obstructs substrate entry. Protein-ligand interaction analysis and MM-PBSA showed that OHCbl Acetate exhibited lower binding free energy and engaged in more residue interactions with PTP1B. In summary, our study confirmed the substantial inhibitory activity of OHCbl Acetate against PTP1B, with its inhibitory potency notably surpassing that of MeCbl. We demonstrated potential molecular mechanisms of OHCbl Acetate inhibiting PTP1B.

Novel thiazolidin-4-one benzenesulfonamide hybrids as PPARγ agonists: Design, synthesis and in vivo anti-diabetic evaluation

In the current study, two series of novel thiazolidin-4-one benzenesulfonamide arylidene hybrids 9a-l and 10a-f were designed, synthesized and tested in vitro for their PPARɣ agonistic activity. The phenethyl thiazolidin-4-one sulphonamide 9l showed the highest PPARɣ activation % by 41.7%. Whereas, the 3-methoxy- and 4-methyl-4-benzyloxy thiazolidin-4-one sulphonamides 9i, and 9k revealed moderate PPARɣ activation % of 31.7, and 32.8%, respectively, in addition, the 3-methoxy-3-benzyloxy thiazolidin-4-one sulphonamide 10d showed PPARɣ activation % of 33.7% compared to pioglitazone. Compounds 9b, 9i, 9k, 9l, and 10d revealed higher selectivity to PPARɣ over the PPARδ, and PPARα isoforms. An immunohistochemical study was performed in HepG-2 cells to confirm the PPARɣ protein expression for the most active compounds. Compounds 9i, 9k, and 10d showed higher PPARɣ expression than that of pioglitazone. Pharmacological studies were also performed to determine the anti-diabetic activity in rats at a dose of 36 mg/kg, and it was revealed that compounds 9i and 10d improved insulin secretion as well as anti-diabetic effects. The 3-methoxy-4-benzyloxy thiazolidin-4-one sulphonamide 9i showed a better anti-diabetic activity than pioglitazone. Moreover, it showed a rise in blood insulin by 4-folds and C-peptide levels by 48.8%, as well as improved insulin sensitivity. Moreover, compound 9i improved diabetic complications as evidenced by decreasing liver serum enzymes, restoration of total protein and kidney functions. Besides, it combated oxidative stress status and exerted anti-hyperlipidemic effect. Compound 9i showed a superior activity by normalizing some parameters and amelioration of pancreatic, hepatic, and renal histopathological alterations caused by STZ-induction of diabetes. Molecular docking studies, molecular dynamic simulations, and protein ligand interaction analysis were also performed for the newly synthesized compounds to investigate their predicted binding pattern and energies in PPARɣ binding site.

Designing, DFT, biological, & molecular docking analysis of new Iron(III) & copper(II) complexes incorporating 1-{[-(2-Hydroxyphenyl)methylene]amino}−5,5-diphenylimidazolidine-2,4-dione (PHNS)

The exploration encompassed the synthesis and characterization of two innovative complexes, namely FePHNS and CuPHNS, employing a diverse array of analytical techniques such as elemental analysis, infrared and ultraviolet-visible spectroscopy, mass spectrometry, molar conductivity measurements, magnetic susceptibility assessments, and thermal analysis (TGA). In the spectral domain, infrared spectroscopy substantiated the tridentate ONS coordination of the PHNS ligand to the central metal atom. Thermal analysis offered valuable insights into the distribution and content of water molecules within the complexes. Density functional theory (DFT) calculations were harnessed to validate the molecular structures of both the PHNS ligand and its complex entities, providing an intricate comprehension of their quantum chemical parameters. The investigation extended to an evaluation of the in vitro antibacterial, antifungal, and antioxidant efficacy of the PHNS ligand and its complexes, revealing heightened biological activities for the complexes in comparison to the free PHNS ligand, notably with the CuPHNS complex demonstrating the highest activity, while the PHNS ligand exhibited the lowest. To delve into potential physiological activities, molecular docking studies were conducted, predicting the binding affinity of the compounds to proteins 2vf5 (Glucosamine-6-phosphate synthase in complex with glucosamine-6-phosphate) from Escherichia coli, 3cku (rate oxidase from Aspergillus flavus complexed with its inhibitor 8-azaxanthin and chloride) from Aspergillus flavus, and 5IJT (Crystal structure of Human Peroxiredoxin 2 Oxidized). The ensuing analysis of protein-ligand interactions and binding energies underscored the promising physiological activities of the investigated compounds, warranting further exploration for their potential in novel drug development.

BioProtIS: Streamlining protein-ligand interaction pipeline for analysis in genomic and transcriptomic exploration

The identification of protein-ligand interactions plays a pivotal role in elucidating biological processes and discovering potential bioproducts. Harnessing the capabilities of computational methods in drug discovery, we introduce an innovative Inverted Virtual Screening (IVS) pipeline. This pipeline Integrated molecular dynamics and docking analyses to ensure that protein structures are not only energetically favorable but also representative of stable conformations. The primary objective of this pipeline is to automate and streamline the analysis of protein-ligand interactions at both genomic and transcriptomic scales. In the contemporary post-genomic era, high-throughput computational screening for bioproducts, biological systems, and therapeutic drugs has become a cornerstone practice. This approach offers the promise of cost-effectiveness, time efficiency, and optimization of laboratory work. Nevertheless, a notable deficiency persists in the availability of efficient pipelines capable of automating the virtual screening process, seamlessly integrating input and output, and leveraging the full potential of open-source tools. To bridge this critical gap, we have developed a versatile pipeline known as BioProtIS. This tool seamlessly integrates a suite of state-of-the-art tools, including Modeller, AlphaFold, Gromacs, FPOCKET, and AutoDock Vina, thus facilitating the streamlined docking of ligands with an expansive repertoire of proteins sourced from genomes and transcriptomes, and substrates. To assess the pipeline's performance, we employed the transcriptomes of Cereus jamacaru (a cactus species) and Aspisoma lineatum (firefly), along with the genome of Homo sapiens. This integration not only improves the accuracy of ligand-protein interactions by minimizing replicability deviations but also optimizes the discovery process by enabling the simultaneous evaluation of multiple substrates. Furthermore, our pipeline accommodates distinct testing scenarios, such as blind docking or site-specific targeting, which are invaluable in applications ranging from drug repositioning to the exploration of new allosteric binding sites and toxicity assessments. BioProtIS has been designed with modularity at its core. This inherent flexibility empowers users to make custom modifications directly within the source code, tailoring the pipeline to their specific research needs. Moreover, it lays the foundation for seamless integration of diverse docking algorithms in future iterations, promising ongoing advancements in the field of computational biology. This pipeline is available for free distribution and can be download at: https://github.com/BBMDO/BioProtIS.

Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy.

Global prevalence of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from -11.7 to -10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

In-silico Investigations for the Identification of Novel Inhibitors Targeting Hepatitis C Virus RNA-dependent RNA Polymerase.

Hepatitis C is an inflammatory condition of the liver caused by the hepatitis C virus, exhibiting acute and chronic manifestations with severity ranging from mild to severe and lifelong illnesses leading to liver cirrhosis and cancer. According to the World Health Organization's global estimates, a population of about 58 million have chronic hepatitis C virus infection, with around 1.5 million new infections occurring every year. The present study aimed to identify novel molecules targeting the Hepatitis C viral RNA Dependent RNA polymerases, which play a crucial role in genome replication, mRNA synthesis, etc. Methods: Structure-based virtual screening of chemical libraries of small molecules was done using AutoDock/Vina. The top-ranking pose for every ligand was complexed with the protein and used for further protein-ligand interaction analysis using the Protein-ligand interaction Profiler. Molecules from virtual screening were further assessed using the pkCSM web server. The proteinligand interactions were further subjected to molecular dynamics simulation studies to establish dynamic stability. Molecular docking-based virtual screening of the database of small molecules, followed by screening based on pharmacokinetic and toxicity parameters, yielded eight probable RNA Dependent RNA polymerase inhibitors. The docking scores for the proposed candidates ranged from - 8.04 to -9.10 kcal/mol. The potential stability of the ligands bound to the target protein was demonstrated by molecular dynamics simulation studies. Data from exhaustive computational studies proposed eight molecules as potential anti-viral candidates, targeting Hepatitis C viral RNA Dependent RNA polymerases, which can be further evaluated for their biological potential.

In Situ Monitoring of Membrane Protein Electron Transfer via Surface-Enhanced Resonance Raman Spectroscopy.

In situ analysis of membrane protein-ligand interactions under physiological conditions is of significance for both fundamental and applied science, but it is still a big challenge due to the limits in sensitivity and selectivity. Here, we demonstrate the potential of surface-enhanced resonance Raman spectroscopy (SERRS) for the investigation of membrane protein-protein interactions. Lipid biolayers are successfully coated on silver nanoparticles through electrostatic interactions, and a highly sensitive and biomimetic membrane platform is obtained in vitro. Self-assembly and immobilization of the reduced cytochrome b5 on the coated membrane are achieved and protein native biological functions are preserved. Owing to resonance effect, the Raman fingerprint of the immobilized cytochrome b5 redox center is selectively enhanced, allowing for in situ and real-time monitoring of the electron transfer process between cytochrome b5 and their partners, cytochrome c and myoglobin. This study provides a sensitive analytical approach for membrane proteins and paves the way for in situ exploration of their structural basis and functions.

Probing the mechanisms of hydrazide-based HDAC inhibitors binding to HDAC3 using Gaussian accelerated molecular dynamics (GaMD) simulations

Histone deacetylases (HDACs) have emerged as promising targets for anticancer drug development. They regulate gene expression by removing acetyl groups from lysine residues on histone tails, leading to chromatin condensation. A hydrazide-based HDAC inhibitor, N-(4-(2-Propylhydrazine-1-carbonyl)benzyl)-1H-indole-2-carboxamide (11h), has been reported to exhibit significant in vivo antitumor activity. In comparison to the lead compound N-(4-(2-Propylhydrazine-1-carbonyl)benzyl)cinnamamide (17), compound 11h demonstrates 2- to 5-fold higher HDAC inhibition and cell-based antitumor activity. However, the inhibitory mechanism of 11h remains insufficiently explored. In this study, we conducted 500 ns Gaussian Accelerated Molecular Dynamics (GaMD) simulations on Histone deacetylase 3 (HDAC3) and two complex systems (HDAC3-17 and HDAC3-11h). Our findings revealed that upon inhibitor binding, the active pocket volume of HDAC3 undergone alterations, and the movement of the L6-loop toward the active site impeded substrate entry. Moreover, we observed a destabilization of the α-helix in the aa75-89 region of HDAC3 compared to the two complex systems, indicating partial unwinding. Notably, 11h exhibited a closer proximity of its carbonyl oxygen to the active pocket’s Zn2+ metal compared to 17, increasing the likelihood of coordination with the Zn2+ metal. The analysis of protein-ligand interactions highlighted a greater number of hydrogen bonds and other interactions between 11h and the receptor protein when compared to 17, underscoring the stronger binding of 11h to HDAC3. In conclusion, our study provided theoretical insights into the inhibitory mechanism of hydrazide-based HDAC inhibitors on HDAC3, thereby contributing to the development of improved drug targets for cancer therapy. Communicated by Ramaswamy H. Sarma

Researching of resistance to etravirine in some HIV-1 low-level viremia strains by in-silico methods

Abstract Objectives Human immunodeficiency virus (HIV) is a significant infection that attacks immune system cells and integrates its genetic material into host cells. Left untreated, it leads to acquired immunodeficiency syndrome (AIDS). Antiretroviral therapy (ART) is used to control HIV infection. Etravirine (ETR) is an important non-nucleoside reverse transcriptase inhibitor (NNRTI) utilized in the treatment of HIV. Low-level viremia (LLW) is a serious clinical condition, and the underlying mechanisms remain incompletely understood. The aim of our study is to analyze and elucidate the resistance status of Lys104Gln, Lys102Gln, Lys101Arg-Lys104Arg, Ser191Phe, Ile94Leu-Lys104Arg, Lys104Glu-His235Leu, Ala98Ser and Val179Ile mutations using in-silico methods, which are identified as low-level viremic strains, because their resistance status to ETR is unknown. Methods Homology modeling was performed using the Swiss Model program. Molecular docking of ETR with the reverse transcriptase (RT) enzyme was conducted using the CB-Dock program developed by AutoDock Vina. Protein-ligand interaction analysis was carried out using the protein-ligand interaction profiler (PLIP). Results A98S and V179I mutations altered the physicochemical properties of the region, resulting in changes to the conformational structure of the NNRTI hydrophobic pocket compared to the wild-type and consequently decreased docking scores. Conclusions Based on the evaluation of literature data and in-silico analyses, it is believed that A98S and V179I mutations may alter the conformational structure of the hydrophobic pocket where ETR binds, potentially resulting in low-level resistance against ETR.

Bioinformatics analysis of wild-type ParC and S79F, S79Y mutations in Streptococcus pneumoniae.

S79Y and S79F mutations in ParC at the fluoroquinolone binding site confer resistance to quinolones in Streptococcus pneumoniae. The aim of this study was to perform bioinformatics analysis of wild-type and mutant ParC identified in S. pneumoniae strains. Homology models were created with Swiss Model, and the UCSF Chimera was used for the analysis and evaluation of the models. Molecular docking studies and protein-ligand interaction analysis were performed using CB-Dock developed by AutoDock Vina and Protein Ligand Interaction Profiler (PLIP), respectively. According to the homology modeling results, changes were observed in the physicochemical properties. Both mutant types showed a decrease in hydrophobicity (S79F: 2.0, S79Y: 0.5 - Kyte-Doolittle) and an increase in regional volume (S79F: 95 Å3, S79Y: 100 Å3). The docking scores for the wild-type, S79F, and S79Y types were 6.3, 4.9, and 5.0, respectively. The decrease in docking scores indicates weaker binding in the mutant types. The results of the PLIP analysis indicate that new bonds were formed, and the bond types changed in both mutant types, while some bonds disappeared. It is believed that the change in physicochemical properties caused by the mutation altered the conformation of the quinolone binding region and the bond types, numbers, and proximities of the amino acids involved in the interaction with the active substance. The results obtained from the modeling performed in this study with visualization and analysis of possible conformational, hydrophobic, and volumetric changes of only ParC mutations provided data and literature support to elucidate the mechanism. The molecular docking and PLIP results obtained in this study support both the homology modeling results and the fact that S79F and S79Y have been shown to be resistant in the literature.

Exploration of human pancreatic alpha-amylase inhibitors from Physalis peruviana for the treatment of type 2 diabetes

Type 2 Diabetes (T2D), a chronic metabolic disorder characterized by persistent hyperglycemia, accounts for ∼90% of all types of diabetes. Pancreatic α-amylase is a potential drug target for preventing postprandial hyperglycemia and inhibiting T2D in humans. Although many synthetic drugs have been identified against pancreatic α-amylase, however, reported several side effects, and plant-derived natural products are less explored against T2D. This study tested 34 flavonoids derived from the plant Physalis peruviana against the human pancreatic α-amylase (HPA) using in silico computational approaches such as molecular docking and molecular dynamics simulation approaches. Schrödinger, a drug discovery package with modules applicable for molecular docking, protein-ligand interaction analysis, molecular dynamics, post-dynamics simulation, and binding free energy calculation, was employed for all computational studies. Four flavonoids, namely, Chlorogenic acid, Withaperuvin F, Withaperuvin H, and Rutin, were picked based on their docking score ranging between −7.03 kcal/mol and −11.35 kcal/mol compared to the docking score −7.3 kcal/mol of reference ligand, i.e. Myricetin. The molecular dynamics analysis suggested that all flavonoids showed considerable stability within the protein’s catalytic pocket, except chlorogenic acid, which showed high deviation during the last 15 ns. However, the interactions observed in initial docking and extracted from the simulation trajectory involved > 90% identical residues, indicating the affinity and stability of the docked flavonoids with the protein. Therefore, all four compounds identified in this study are proposed as promising antidiabetic candidates and should be further considered for their in vitro and in vivo validation. Communicated by Ramaswamy H. Sarma

Molecular determinants of avoidance and inhibition of Pseudomonas aeruginosa MexB efflux pump.

Transporters of the resistance-nodulation-cell division (RND) superfamily of proteins are the dominant multidrug efflux power of Gram-negative bacteria. The major RND efflux pump of Pseudomonas aeruginosa is MexAB-OprM, in which the inner membrane transporter MexB is responsible for the recognition and binding of compounds. The high importance of this pump in clinical antibiotic resistance made it a subject of intense investigations and a promising target for the discovery of efflux pump inhibitors. This study is focused on a series of peptidomimetic compounds developed as effective inhibitors of MexAB-OprM. We performed multi-copy molecular dynamics simulations, machine-learning (ML) analyses, and site-directed mutagenesis of MexB to investigate interactions of MexB with representatives of efflux avoiders, substrates, and inhibitors. The analysis of both direct and water-mediated protein-ligand interactions revealed characteristic patterns for each class, highlighting significant differences between them. We found that efflux avoiders poorly interact with the access binding site of MexB, and inhibition engages amino acid residues that are not directly involved in binding and transport of substrates. In agreement, machine-learning models selected different residues predictive of MexB substrates and inhibitors. The differences in interactions were further validated by site-directed mutagenesis. We conclude that the substrate translocation and inhibition pathways of MexB split at the interface (between the main putative binding sites) and at the deep binding pocket and that interactions outside of the hydrophobic patch contribute to the inhibition of MexB. This molecular-level information could help in the rational design of new inhibitors and antibiotics less susceptible to the efflux mechanism. IMPORTANCE Multidrug transporters recognize and expel from cells a broad range of ligands including their own inhibitors. The difference between the substrate translocation and inhibition routes remains unclear. In this study, machine learning and computational and experimental approaches were used to understand dynamics of MexB interactions with its ligands. Our results show that some ligands engage a certain combination of polar and charged residues in MexB binding sites to be effectively expelled into the exit funnel, whereas others engage aromatic and hydrophobic residues that slow down or hinder the next step in the transporter cycle. These findings suggest that all MexB ligands fit into this substrate-inhibitor spectrum depending on their physico-chemical structures and properties.

Brute Force Virtual Drug Screening with Molecular Dynamics Simulation and MM/PBSA to Find Potent Inhibitors of METTL16.

Epitranscriptomic modification is a dynamic modification of RNAs. Epitranscriptomic writer proteins are methyltransferases, such as METTL3 and METTL16. The up regulation of METTL3 have been found to be linked to different cancers and targeting METTL3 is an effective way to reduce tumour progression. Drug development against METTL3 is an active field of research. METTL16, SAM dependent methyltransferase, is another writer protein, that has been found to be upregulated in hepatocellular carcinoma and gastric cancer. In this pioneering study METTL16 has been targeted for virtual drug screening for the very first time using brute force strategy to identify a drug molecule that could be repurposed for the treatment of the disease caused. An unbiased library of the commercially available drug molecules has been used for screening using a multipoint validation process developed for this work, which includes molecular docking, ADMET analysis, protein-ligand interaction analysis, Molecular Dynamics Simulation, binding energy calculation via Molecular Mechanics Poisson-Boltzmann Surface Area method. Upon the in-silico screening of over 650 drugs the authors have found NIL and VXL passed the validation process. The data strongly indicates the potency of these two drugs in the treatment of disease where METTL16 needs to be inhibited.

In silico examination of peptides containing selenium and ebselen Backbone To Assess Their Tumoricidal Potential

Introduction: Cancer has been one of the highest causes of morbidity and mortality in the world for decades. Owing to improved therapeutics along with detection, breast cancer mortality has been slowly reducing. The incidence of breast cancer, on the other hand, has increased gradually. More than 100 types of cancer have been identified with a wide range of treatment protocols comprising of chemotherapy, radiation therapy, hormone therapy, etc. In an attempt to curb the serious deleterious effects caused by the chemotherapeutic drugs, numerous peptide molecules are currently popular as alternatives to the standard chemotherapeutic drugs. Methods: In this study, we have carried out in silico investigations to ascertain the anti-proliferative potential of novel peptides based on selenium and ebselen, i.e. Eb-Trp-Asp, 13, Eb-Trp-Glu, 14, and Eb-Trp-Lys, 15. Analysis of protein-ligand interactions, resulting in protein-ligand complex formation, has been carried out using the AutoDockVina in PyRx aided molecular docking technique, which may be an essential indication of druggability of the test peptides. Results: The molecular docking results revealed that the screened ligands had extraordinarily strong binding interactions and affinity for the target. Conclusion: Findings suggested that novel peptide molecule Eb-Trp-Glu, 14 may be a potent anticancer agent.

Activity‐Based Protein Profiling – Celebrating the Groundbreaking Contributions of Benjamin Cravatt

Activity‐Based Protein Profiling – Celebrating the Groundbreaking Contributions of Benjamin Cravatt

Elucidating Protein-Ligand Interactions in Cell Lysates Using High-Throughput Hydrogen-Deuterium Exchange Mass Spectrometry with Integrated Protein Thermal Depletion.

Hydrogen-deuterium exchange coupled with mass spectrometry (HDX-MS) is a powerful technique for the characterization of protein-ligand interactions. Currently, there is a growing need for breakthroughs in the application of HDX-MS analysis to protein-ligand interactions in highly complex biological samples such as cell lysates. However, HDX-MS analysis in such systems suffers from extreme spectral complexity as a result of high sample complexity and limited LC separation power due to the traditional use of short LC gradients. Here, we introduced protein thermal depletion (PTD) to reduce protein complexity in E. coli cell lysate for our subzero-temperature long gradient UPLC-HDX-MS platform (PTD-HDX-MS) to facilitate high-throughput analysis of protein-ligand interactions in cell lysates. We spiked bovine carbonic anhydrase II (CaII) and its inhibitor acetazolamide (AZM) into E. coli cell lysate as a model system in our study. We demonstrated that PTD at 60 °C greatly reduces protein complexity in cell lysates, while the AZM-targeted CaII complex remains in solution due to improved thermal stability upon binding. Using both PTD to reduce sample complexity and subzero-temperature long gradient UPLC to boost LC separation power, we successfully elucidated the interaction sites between AZM and CaII in E. coli cell lysate from the high-throughput HDX-MS analysis of thousands of deuterated peptides from hundreds of proteins. Our results highlight the great promise of the PTD-HDX-MS platform for the identification of ligand targets and characterization of protein-ligand interactions in highly complex biological samples such as cell lysates.