Binding Free Energy Research Articles

Discovery of α-amylase and α-glucosidase dual inhibitors from NPASS database for management of Type 2 Diabetes Mellitus: A chemoinformatic approach

Postprandial hyperglycemia, typical manifestation of Type 2 Diabetes Mellitus (T2DM), is associated with notable global morbidity and mortality. Preventing the advancement of this condition by delaying the rate of glucose absorption through inhibition of α-amylase and α-glucosidase enzymatic activities is of utmost importance. Finding a safe antidiabetic drug is essential since those that are currently on the market have drawbacks like unpleasant side effects. The current study utilized computer-aided drug design (CADD), as a quick and affordable method to find a substitute drug template that can be used to control postprandial hyperglycemia by modulating the activity of α-amylase and α-glucosidase enzymes. The Natural Products Activity and Species database (NPASS) (30,926 compounds) was screened in silico, with a focus on evaluating drug-likeness, toxicity profiles and ability to bind on a target protein. Two molecules NPC204580 (Chrotacumine C) and NPC137813 (1-O-(2-Methoxy-4-Acetylphenyl)-6-O-(E-Cinnamoyl)-Beta-D-Glucopyranoside) were identified as potential dual inhibitors for α-amylase and α-glucosidase with free binding energies of -14.46 kcal/mol and -12.58 kcal/mol for α-amylase, and -8.42 kcal/mol and -8.76 kcal/mol for α-glucosidase, respectively. The molecules showed ionic, H-bonding and hydrophobic interactions with critical amino acid residues of both enzymes. Moreover, 100 ns molecular dynamic simulations showed that both molecules are stable on the receptors’ active sites based on root mean square deviation (RMSD), root mean square fluctuation (RMSF), and the Generalized Born surface area (GBSA) energy calculated. The two compounds are thus promising therapeutic agents for T2DM that merit further investigation due to their excellent binding energies, encouraging pharmacokinetics, toxicity profiles, and stability as demonstrated in simulated studies.

Insilico discovery of novel Phosphodiesterase 4 (PDE4) inhibitors for the treatment of psoriasis: Insights from computer aided drug design approaches

Psoriasis is chronic immune-mediated inflammatory disorder characterized by various comorbidities, erythematous plaques with silvery scale which can lead to psoriatic arthritis. The phosphodiesterase 4 (PDE4) protein is a potential drug target to control Psoriasis. In the current study, pharmacophore-based virtual screening of Diversity library of ChemDiv database was first performed, and then the screened hits were docked to the active site of PDE4 to choose the best binding modes. Forty-six hits generated during the virtual screening were prepared and docked to the PDE4 receptor by SP docking module of glide. The binding affinities of the selected hits were calculated by molecular docking and based on the affinities, ten hits were selected for the bioactivity scores prediction and ADMET analysis. Based on the ADMET profiling, four hits D356-2630, C700-2058, G842-0420 and F403-0203 were processed to MD simulations for stability analysis. The outcomes showed that these compounds showed strong binding with proteins with better binding free energies. Based on the results of our study, we proposed that these hits can function as lead in the biological assays and in vitro studies are required to develop the novel drug candidates.

Activating Oxygen via the 3‐Electron Pathway to Hydroxyl Radical by La‐O4 Single‐atom on WO3 for Water Purification

Shifting photocatalytic oxygen activation towards 3‐electron (e‐) pathway to hydroxyl radicals, instead of the normal 1 e‐ to superoxide radicals, becomes increasingly important for pollution degradation since hydroxyl radicals possess a high oxidation potential (2.80 V). Here, we demonstrate a selective oxygen activation to hydroxyl radicals via 3 e‐ pathway using single atomically dispersed La based on WO3 fabricated with oxygen vacancies to weaken La‐O coordination strength (denoted as LaO4‐WOv). Unsaturated‐state La overcomes the rate‐limited step of 2 e‐ oxygen reduction reaction towards to hydrogen peroxide via tuning binding free energy of key reaction intermediate *OOH, stepped by easy generation of hydroxyl radicals via 1 e‐. This strategy alters the activation of oxygen process from 1 e‐ to 3 e‐. Hydrogen peroxide and hydroxyl radicals over LaO4‐WOv produces 3.8 and 3.3 mmol L‐1 h‐1, 35 and 8 times that of detected over WO3, respectively. Rapid and complete removal of tetracycline realizes over LaO4‐WOv with 0.077 min‐1 of rate constant, 38 times that of WO3. Degradation efficiencies keep greater than 98% following five repeats, revealing a practical‐utilization‐level robust stability. This work builds an unsaturated‐state transition metal site for manipulating oxygen activation towards an effective water purification as a representative application.

Activating Oxygen via the 3‐Electron Pathway to Hydroxyl Radical by La‐O4 Single‐atom on WO3 for Water Purification

Shifting photocatalytic oxygen activation towards 3‐electron (e‐) pathway to hydroxyl radicals, instead of the normal 1 e‐ to superoxide radicals, becomes increasingly important for pollution degradation since hydroxyl radicals possess a high oxidation potential (2.80 V). Here, we demonstrate a selective oxygen activation to hydroxyl radicals via 3 e‐ pathway using single atomically dispersed La based on WO3 fabricated with oxygen vacancies to weaken La‐O coordination strength (denoted as LaO4‐WOv). Unsaturated‐state La overcomes the rate‐limited step of 2 e‐ oxygen reduction reaction towards to hydrogen peroxide via tuning binding free energy of key reaction intermediate *OOH, stepped by easy generation of hydroxyl radicals via 1 e‐. This strategy alters the activation of oxygen process from 1 e‐ to 3 e‐. Hydrogen peroxide and hydroxyl radicals over LaO4‐WOv produces 3.8 and 3.3 mmol L‐1 h‐1, 35 and 8 times that of detected over WO3, respectively. Rapid and complete removal of tetracycline realizes over LaO4‐WOv with 0.077 min‐1 of rate constant, 38 times that of WO3. Degradation efficiencies keep greater than 98% following five repeats, revealing a practical‐utilization‐level robust stability. This work builds an unsaturated‐state transition metal site for manipulating oxygen activation towards an effective water purification as a representative application.

Anti-thrombotic Mechanisms of Echinochrome A on Arterial Thrombosis in Rats: In-Silico, In-Vitro and In-Vivo Studies

Background: Arterial thrombosis is one of the most significant healthcare concerns in the world. Echinochrome A (Ech-A) is a natural quinone pigment isolated from sea urchins. It has a variety of medicinal values associated with its antioxidant, anticancer, antiviral, anti-diabetic, and cardio-protective activities. Objective: The current study aims to investigate the effect and mechanism of Ech-A to inhibit thrombus formation induced by ferric chloride in rats. Methods: Twenty-four rats were assigned into four groups (n= 6); sham and thrombotic model groups were orally administered 2% DMSO, while the other groups were treated with two dosages of Ech-A (1 and 10 mg/kg, body weight). After seven days of administration, all groups were exposed to 50% ferric chloride for 10 min, except the sham group exposure to normal saline. Results: The molecular docking showed the free binding energies of Ech-A and vitamin K (Vit. K) with Vit. K epoxide reductase were -8.5 and -9.8 kcal/mol, which confirm the antithrombotic activity of Ech-A. The oral administration of Ech-A caused a significant increase in partial thromboplastin time, prothrombin time, clotting time, platelet count, fibrinogen levels, factor VIII, glutathione reduced, catalase, nitric oxide, and glutathione S-transferase. While white blood cells count, calcium level, and malondialdehyde concentration significantly decreased. The histological examination revealed a definite improvement in the carotid and cardiac tissues in the Ech-A groups. Conclusion: The study results showed that Ech-A prevented thrombosis by several mechanisms, including chelating calcium ions, increasing the NO concentration, suppressing oxidative stress, and antagonizing Vit. K.

A Comprehensive Evaluation of a Coumarin Derivative and Its Corresponding Palladium Complex as Potential Therapeutic Agents in the Treatment of Gynecological Cancers: Synthesis, Characterization, and Cytotoxicity

Background: The aim of this research is the synthesis and characterization of coumarin-palladium complex and the investigation of the cytotoxicity of both the ligand and the complex. Methods: The palladium( II) complex (CC) was obtained in the reaction between (E)-3-(1-((4-hydroxy-3-methoxyphenyl)amino)ethylidene)-2,4-dioxochroman-7-yl-acetate (CL) and potassium-tetrachloropalladate(II) and characterized using IR and NMR spectra, experimentally and theoretically. Cytotoxicity of CL and CC were determined for human cervical carcinoma HeLa, ovarian cancer A2780, hormone dependent breast cancer MCF7, and colorectal cancer HCT116 lines. The interaction of investigated compounds with HSA was followed by spectrofluorimetric method. The binding mechanism in the active pocket was assessed via molecular docking simulations. Results: A low mean absolute error between experimental and theoretical data proved that the optimized structure corresponded to the experimental one. Both compounds showed a satisfactory selectivity index towards neoplastic cells. The binding affinity of tested compounds to the HSA were confirmed. The molecular docking showed a much lower change in the Gibbs free energy of binding for CC compared to CL. Conclusions: The obtained results revealed that CL and CC exhibit significant effects on several cancer cell lines and good binding properties to HSA, while molecular docking discovered that CC has the most pronounced activity against alpha-fetoprotein.

Spectroscopic, quantum computational, molecular dynamic simulations, and molecular docking investigation of the biologically important compound-2,6-diaminopyridine

To establish the role in future drug development, 2,6-diamino pyridine (2,6-DAP) was investigated experimentally using computational tools. NMR (1H,13C), FTIR, and UV–Vis spectra were analyzed for the titled compound. The molecular structure was optimized via DFT with the “B3LYP method with 6-311++G(d,p)” The optimized parameters of the structure were assessed with the observed bond characteristics. The vibrational frequencies were studied, PED was carried out, and the calculated vibrational frequency obtained was compared with the experimentally obtained FTIR. NMR (1H,13C) was calculated and compared with the experimentally obtained spectra. UV–vis spectra are calculated in the gaseous phase and different mediums of solvents (methanol, DMSO) by employing the PCM solvent model and TD-DFT method, and the estimated value was compared with experimentally measured data. NBO analysis was done to study the donor-acceptor interaction. The extent of electron charge transfer inside the molecular structure was examined using HOMO–LUMO energy values. The study of excitation analysis led to the creation of E.D.D and H.D.D maps in methanol and DMSO. The AIM and ELF analysis was employed to compute the iso-surface projections, ellipticity, and binding energies. The MEP and Fukui functions evaluate the molecule’s reactive zones. Hirshfeld research was done to analyze interactions among the molecules in the structure of the crystal, and 3D Hirshfeld tops and 2D fingerprint layouts were developed. The molecular docking procedure was used, followed by a 100 ns MD simulation and computation of binding free energy found to delineate the binding affinity of the molecule toward human carbonic anhydrase II (HCA II). Molecular docking studies with several receptor proteins were also conducted to determine the most effective protein-ligand interactions. Biological assessments like drug-likeness also act upon the compound to verify the molecule’s drug-like nature.

New Indole‐based Phenylthiazolyl‐2,4‐dihydropyrazolones as Tubulin polymerization inhibitors: Multicomponent synthesis, cytotoxicity evaluation, and in silico studies

A facile multicomponent synthesis of new indole‐based phenylthiazolyl‐dihydropyrazolone hybrids, their structural characterization, biological evaluation, and in silico investigations as anticancer agents are reported. Lead molecule 5i of the series showed potent activity against MCF‐7 breast cancer cells with an IC50 of 3.92 ± 0.01 µM while showing minimal toxicity to normal human lung cells (IC50 = 69.85 ± 3.95 µM). Further studies show that the compound exhibits antiproliferative activity by inducing apoptosis in MCF‐7 cancer cells. The wound healing assay indicated impaired cell migration under the concentration‐dependent dosage. The lead molecule 5i also successfully inhibited the tubulin polymerase enzyme with an IC50 of 4.16 ± 0.18 µM. A flow cytometric assay indicated compound 5i induced apoptosis through G0 phase cell cycle arrest. The binding mode and interactions of the compound with the tubulin were predicted by molecular modelling and calculating binding free energies. These findings explain the current series as a new class of microtubule polymerization inhibitors with anticancer activity suitable for developing anticancer agents targeting tubulin.

NOVEL HYBRIDS OF QUINOLINE LINKED PYRIMIDINE DERIVATIVES AS CYCLOOXYGENASE INHIBITORS: MOLECULAR DOCKING, ADMET STUDY, AND MD SIMULATION

Objective: Finding novel anti-inflammatory compounds is a crucial sector of research despite the significant advances this field has made. Inefficiency and unfavorable side effects are indeed potential drawbacks of conventional therapy utilizing steroidal or nonsteroidal drugs. This study aims to screen the designed quinoline-linked pyrimidine derivatives as Cyclooxygenase (COX) inhibitors. Methods: In the present study, we assessed the binding interactions of designed quinoline-linked pyrimidine derivatives with COX enzymes using a molecular docking approach. Using Molecular Dynamics (MD) simulations, the compound’s behavior was further investigated and its stability and conformational dynamics were demonstrated. Schrödinger's QikProp program was utilized to analyze the Absorption, Distribution, Metabolism, and Excretion (ADME) properties and toxicity properties were further investigated using Osiris Property Explorer. Additionally, the protein-ligand complexes' binding free energy has been ascertained using the Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) approach, which offered crucial information regarding the strength of their interactions. Results: The designed quinoline-linked pyrimidine derivatives fulfilled the Lipinski Rule of Five and had physicochemical characteristics within acceptable ranges, better ADME properties, and were non-toxic. Among the designed compounds, QPDU1 and QPDT6 showed correspondingly good docking scores for COX-1 and COX-2. QPDT6 was additionally analyzed by MD simulation studies to thoroughly examine the interaction between protein and ligand and their stability. Conclusion: The proposed compounds exhibit strong binding affinities to COX enzymes, stable interactions in MD simulations, and favorable drug-like features. These results support the need for more research and development of these substances as possible anti-inflammatory drugs.

Discovery of novel fused-heterocycle-bearing diarypyrimidine derivatives as HIV-1 potent NNRTIs targeting tolerant region I for enhanced antiviral activity and resistance profile

As an important part of anti-AIDS therapy, HIV-1 non-nucleoside reverse transcriptase inhibitors are plagued by resistance and toxicity issues. Taking our reported XJ-18b1 as lead compound, we designed a series of novel diarypyrimidine derivatives by employing a scaffold hopping strategy to discover potent NNRTIs with improved anti-resistance properties and drug-like profiles. The most active compound 3k exhibited prominent inhibitory activity against wild-type HIV-1 (EC50 = 0.0019 μM) and common mutant strains including K103 N (EC50 = 0.0019 μM), L100I (EC50 = 0.0087 μM), E138K (EC50 = 0.011 μM), along with low cytotoxicity and high selectivity index (CC50 = 21.95 μM, SI = 11478). Additionally, compound 3k demonstrated antiviral activity against HIV-2 with EC50 value of 6.14 μM. The enzyme-linked immunosorbent assay validated that 3k could significantly inhibit the activity of HIV-1 reverse transcriptase (IC50 = 0.025 μM). Furthermore, molecular dynamics simulation studies were performed to illustrate the potential binding mode and binding free energy of the RT-3k complex, and in silico prediction revealed that 3k possessed favorable drug-like profiles. Collectively, 3k proved to be a promising lead compound for further optimization to obtain anti-HIV drug candidates.

IDENTIFYING POTENTIAL hENR INHIBITORS AGAINST PROSTATE CANCER EMPLOYING IN SILICO DRUG REPURPOSING APPROACH

Objective: This study employed an in silico drug repurposing strategy to identify potential human enoyl acyl carrier protein reductase (hENR) inhibitors. Methods: The co-crystallized ligand triclosan was used as a reference standard. Initially, FDA-approved drugs from the Drug Bank database were docked against the hENR and compounds with appreciable binding affinities with the protein were shortlisted. The binding energy calculations, ADME analysis, and induced-fit docking results of shortlisted compounds led to the identification of two top hits, DB07676 and DB11399, which were further subjected to molecular dynamics simulation. Results: Of 2,509 ligands docked via High Throughput Virtual Screening (HTVS), the top 250 were assessed with Standard Precision (SP) and the top 25 with Extra Precision (XP) mode. Thirteen compounds were selected based on interactions and XP scores, ranging from-15.245 to-10.031. Relative binding free energies of ligands DB07676 and DB11399 were-54.18 and-61.38 kcalmol-1, respectively. ADME analysis confirmed that both ligands followed Lipinski's Rule, though DB11399 had a high log P, which could be addressed by adding polar groups. Induced Fit scores for DB07676 and DB11399 were-10.592 and-11.220, respectively. Molecular Dynamics simulations confirmed superior stability of these complexes with RMSD ranging from 1.2 to 3.5 Å for the protein and 1.7 to 5.2 Å for the ligand with DB07676-protein complex and 1.4 to 3.0 Å for the protein and 1.1 to 5.8 Å for the ligand with DB11399-protein complex. Conclusion: Our final findings suggested that DB07676 and DB11399 could be potential lead compounds as hENR inhibitors.

Molecular docking and molecular dynamics of hypoxia-inducible factor (HIF-1alpha): towards potential inhibitors

HIF-1α is a primary regulator in the adaptation of cancer cells to hypoxia. The aim was to find out new inhibitors of the HIF-1α. A molecular dynamic (MD) simulation performed on HIF-1α showed stable dynamic features. Virtual screening of 217 anticancer drugs was performed along with a positive control (2-Methoxyestradiolm, 2-ME2) on an optimized HIF-1α and dynamically simulated structure. Docking results produced two compounds namely pycnidione and nilotinib of high binding affinity −9.34 kcal/mol and −9.04 kcal/mol respectively, whereas 2-ME2 displayed a relatively lower affinity (-6.68 kcal/mol). For the three complexes, MD of 200 ns simulation was run. Data analysis showed that the three medications behaved similarly in the MD simulation. Nilotinib had a lower RMSD and higher SASA than the other complexes. In addition, the Nilotinib-HIF-1α combination had a lower RMSF value, a flatter Rg, and a number of hydrogen bonds similar to other complexes. MM-GBSA analysis revealed that nilotinib, pycnidione and 2-ME2 compounds had free binding energy of −23.77 ± 5.29, −21.85 ± 4.24 and −7.53 ± 6.62 kcal/mol respectively. Nilotinib and pycnidione bind competitively to HIF-1α, with nilotinib showing consistent molecular-dynamic properties. They relatively pass the blood-brain barrier, non-carcinogenic, and have IV-category acute oral toxicity. They have low CYP inhibitory characteristics. Further investigations are therefore warranted to elucidate their implications in hypoxia pathways, cell proliferation, apoptosis, survival, and metastatic potential.

Improving the Performance of Screening MM/PBSA in Protein-Ligand Interactions via Machine Learning

Abstract Accurately estimating protein-ligand binding free energy is crucial for drug design and biophysics, yet remains a challenging task. In this study, we applied the screening molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) method in combination with various machine learning techniques to compute the binding free energies of protein-ligand interactions. Our results demonstrate that machine learning outperforms direct screening MM/PBSA calculations in predicting protein-ligand binding free energies. Notably, the random forest (RF) method exhibited the best predictive performance, with a Pearson correlation coefficient (r p ) of 0.702 and a mean absolute error (MAE) of 1.379 kcal/mol. Furthermore, we analyzed feature importance rankings in the gradient boosting (GB), adaptive boosting (AdaBoost), and RF methods, and found that feature selection significantly impacted predictive performance. In particular, molecular weight (MW) and van der Waals (VDW) energies played a decisive role in the prediction. Overall, this study highlights the potential of combining machine learning methods with screening MM/PBSA for accurately predicting binding free energies in biosystems.

StreaMD: the toolkit for high-throughput molecular dynamics simulations.

Molecular dynamics simulations serve as a prevalent approach for investigating the dynamic behaviour of proteins and protein-ligand complexes. Due to its versatility and speed, GROMACS stands out as a commonly utilized software platform for executing molecular dynamics simulations. However, its effective utilization requires substantial expertise in configuring, executing, and interpreting molecular dynamics trajectories. Existing automation tools are constrained in their capability to conduct simulations for large sets of compounds with minimal user intervention, or in their ability to distribute simulations across multiple servers. To address these challenges, we developed a Python-based tool that streamlines all phases of molecular dynamics simulations, encompassing preparation, execution, and analysis. This tool minimizes the required knowledge for users engaging in molecular dynamics simulations and can efficiently operate across multiple servers within a network or a cluster. Notably, the tool not only automates trajectory simulation but also facilitates the computation of free binding energies for protein-ligand complexes and generates interaction fingerprints across the trajectory. Our study demonstrated the applicability of this tool on several benchmark datasets. Additionally, we provided recommendations for end-users to effectively utilize the tool.Scientific contributionThe developed tool, StreaMD, is applicable to different systems (proteins, ligands and their complexes including co-factors) and requires a little user knowledge to setup and run molecular dynamics simulations. Other features of StreaMD are seamless integration with calculation of MM-GBSA/PBSA binding free energies and protein-ligand interaction fingerprints, and running of simulations within distributed environments. All these will facilitate routine and massive molecular dynamics simulations.

Exploring the Dynamic Interplay of Deleterious Variants on the RAF1-RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics.

The RAF1-RAP1A interaction activates the MAPK/ERK pathway which is very crucial in the carcinogenesis process. This protein complex influences tumor formation, proliferation, and metastasis. Understanding aberrant interactions driven by clinical mutations is vital for targeted therapies. Hence, the current study focuses on the screening of clinically reported substitutions in the RAF1 and RAP1A genes using predictive algorithms integrated with all-atoms simulation, essential dynamics, and binding free energy methods. Survival analysis results revealed a strong association between RAF1 and RAP1A expression levels and diminished survival rates in cancer patients across different cancer types. Integrated machine learning algorithms showed that among the 134 mutations reported for these 2 proteins, only 13 and 35 were classified as deleterious mutations in RAF1 and RAP1P, respectively. Moreover, one mutation in RAF1 reported elevated levels of binding between RAF1 and RAP1P while in RAP1A, 7 mutations were reported to increase the binding affinity. The high-binding mutations, P34Q and V60F, were subjected to protein-protein coupling which confirmed the increase in the binding affinity. Wild-type and mutant RAF1-RAP1P bound complexes were subjected to molecular simulation investigation, revealing enhanced structural stability, increased compactness, and stabilized residue fluctuations of the mutant systems in contrast to the wild-type. In addition, hydrogen bonding analysis revealed a variation in the binding paradigm which further underscores the impact of these substitutions on the coupling of RAF1 and RAP1A. Principal component analysis (PCA) and free energy landscape (FEL) evaluation further determined dynamical variations in the wild-type and mutant complexes. Finally, the Gibbs free energy for each complex was estimated and found to be -71.94 ± 0.38 kcal/mol for the wild-type, -95.57 ± 0.37 kcal/mol for the V60F, and -85.76 ± 0.72 kcal/mol for P34Q complex. These findings confirm the effect of these variants on increasing the binding affinity of RAF1 to RAP1P. These mutations can therefore be targeted for cancer therapy to modulate the activity of the MAPK/ERK signaling pathway.

Discovery of potential natural therapeutics targeting cell wall biosynthesis in multidrug-resistant Enterococcus faecalis: a computational perspective.

Identifying therapeutic inhibitors of crucial enzymes involved in the peptidoglycan biosynthesis pathway is pivotal for developing new treatments against multidrug-resistant Enterococcus faecalis V583. MurM, an essential enzyme in this pathway, plays a significant role in the bacterium's cell wall synthesis, making it an attractive druggable target for novel antimicrobial strategies. This study explored the potential of natural compounds as inhibitors of MurM, aiming to discover promising drug candidates that could serve as the foundation for future therapeutic development. The three-dimensional structure of MurM was predicted, optimized, and its binding pocket was analyzed by comparing it with related structures. Over 4,70,000 natural compounds from the COCONUT database were subjected to virtual high-throughput screening (vHTS). The top lead candidates were selected based on their Lipinski's profile, ADME profile, toxicity profile, estimated binding free energy (ΔG) and estimated inhibition constant (Ki). Interaction pattern analysis was used to evaluate the non-covalent interactions between the inhibitors and key residues in MurM's binding pocket. Molecular dynamics simulations were performed over 300 ns to assess the structural stability and impact of these inhibitors on MurM's enzyme. Three lead compounds-CNP0056520, CNP0126952, and CNP0248480-were identified and prioritized with estimated ΔG ranging from - 9.35 to -7.9kcal/mol. Molecular dynamics simulations revealed minimal impact on MurM's overall structure and dynamics, with the candidate inhibitors forming stable protein-ligand complexes. These interactions were supported by several non-covalent interactions between the candidate inhibitors and key residues within MurM's binding pocket. These findings suggest that the identified natural product candidates could serve as promising inhibitors of MurM, potentially leading to novel therapeutics targeting cell wall biosynthesis in multidrug-resistant E. faecalis.

In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

Computational Screening of Novel Nitroimidazole Candidates: Targeting Key Enzymes of Oral Anaerobes for Anti-Parasitic Potential.

The study focuses on evaluating the parasitic potential of novel metronidazole analogs using computational methods. Specifically, it aims to target key enzymes of oral anaerobes, including UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA) of Fusobacterium nucleatum and DNA topoisomerase (Topo) of Prevotella intermedia. The objective is to assess the pharmacokinetic and toxicity properties of 368 novel nitroimidazole candidates through virtual screening. Additionally, the study aims to determine the binding affinity of the most promising candidates with the target proteins through molecular docking analyses. A combinatorial library of nitroimidazole candidates was constructed, and virtual screening was performed. Molecular docking analyses were conducted to evaluate the binding affinity of selected compounds with MurA and Topo. Further investigation involved molecular dynamic simulation to assess the stability of the compounds within the active sites of MurA and Topo. All selected compounds exhibited activity against both MurA and Topo. Among them, Mnz11, Mnz12, and Mnz15 demonstrated the lowest binding free energies and IC50 values. Molecular dynamic simulation indicated that these three compounds remained stable within the active sites of MurA and Topo, with RMSD values consistently below 2Å. Additionally, the antibacterial potential of the most potent compound, Mnz15, was evaluated against a series of oral microbes. The study concludes that the newly identified nitroimidazole candidates show promise as anti-parasitic agents, based on their activity against key enzymes of oral anaerobes and their pharmacokinetic properties evaluated through computational methods.

Screening and design of PARP12 inhibitors from traditional Chinese medicine small molecules using computational modeling and simulation

The poly (ADP-ribose) polymerase (PARP) family of enzymes plays a pivotal role in orchestrating a multitude of cellular processes, including DNA repair mechanisms, transcriptional regulation, and modulation of immune responses. Within this family, PARP12 emerges as a noteworthy candidate for targeted cancer therapeutics. Consequently, this investigation endeavors to screen and design potential PARP12 inhibitors derived from traditional Chinese medicinal compounds by employing sophisticated molecular modeling and computational medicinal chemistry approaches. The compound RBN2397 is utilized as a benchmark, and the binding efficacies of the newly identified small molecules are assessed against a spectrum of criteria, encompassing molecular interactions, binding free energy, and extensive post-simulation analyses. The outcomes demonstrated that the identified small molecules, specifically tcm8650 and its derivative XC-1, possess remarkable binding affinities and exhibit reduced binding free energies compared to RBN2397. The molecular docking and interaction profiles of these compounds were also comprehensively scrutinized. Moreover, ADMET profiling meticulously evaluated the pharmacokinetic profiles and physicochemical characteristics of these promising molecules and their projected human physiological impact. These computational studies indicated their potential therapeutic applicability and predicted acceptable safety profile, advocating their further exploration as viable candidates in cancer treatment.

Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer

ABSTRACT Human aldehyde dehydrogenases (ALDHs) are a group of 19 isoforms often overexpressed in cancer stem cells (CSCs). These enzymes play critical roles in CSC protection, maintenance, cancer progression, therapeutic resistance, and poor prognosis. Thus, targeting ALDH isoforms offers potential for innovative cancer treatments. Flavonoids, known for their ability to affect multiple cancer-related pathways, have shown anticancer activity by downregulating specific ALDH isoforms. This study aimed to evaluate 830 flavonoids from the PubChem database against five ALDH isoforms (ALDH1A1, ALDH1A2, ALDH1A3, ALDH2, ALDH3A1) using computational methods to identify potent inhibitors. Extra precision (XP) Glide docking and MM-GBSA free binding energy calculations identified several flavonoids with high binding affinities. MD simulation highlighted flavonoids 1, 2, 18, 27, and 42 as potential specific inhibitors for each isoform, respectively. Flavonoid 10 showed high binding affinities for ALDH1A2, ALDH1A3, and ALDH3A1, emerging as a potential multi-ALDH inhibitor. ADMET property evaluation indicated that the promising hits have acceptable drug-like profiles, but further optimization is needed to enhance their therapeutic efficacy and reduce toxicity, making them more effective ALDH inhibitors for future cancer treatment.