Binding Free Energy Calculations Research Articles

Rational Design of Loop Dynamics for a Barrel-Shaped Enzyme by Introducing Disulfide Bonds.

Loop dynamics redesign is an important strategy to manipulate protein function. Cellobiose 2-epimerase (CE) and other members of its superfamily are widely used for diverse industrial applications. The structural feature of the loops connecting barrel helices contributes greatly to the differences in their functional characteristics. Inspired by the in-silico mutation with molecular dynamics (MD) simulation analysis, we propose a strategy for identifying disulfide bond mutation candidates based on the prediction of protein flexibility and residue-residue interaction. The most beneficial mutant with the newly introduced disulfide bond would simultaneously improve both its thermostability and its reaction propensity to the targeting isomerization product. The ratio of the isomerization/epimerization catalytic rate was improved from 4:103 to 9:22. MD simulation and binding free energy calculations were applied to provide insights into molecular recognition upon mutations. The comparative analysis of enzyme/substrate binding modes indicates that the altered catalytic reaction pathway is due to less efficient binding of the native product. The key residue responsible for the observed phenotype was identified by energy decomposition and was further confirmed by the mutation experiment. The rational design of the key loop region might be a promising strategy to alter the catalytic behavior of all (α/α)6-barrel-like proteins.

In silico design of peptide inhibitors for Dengue virus to treat Dengue virus-associated infections

Dengue virus is a single positive-strand RNA virus that is composed of three structural proteins including capsid, envelope, and precursor membrane while seven non-structural proteins (NS1, NS2A, NS2B, NS3A, NS3B, NS4, and NS5). Dengue is a viral infection caused by the dengue virus (DENV). DENV infections are asymptomatic or produce only mild illness. However, DENV can occasionally cause more severe cases and even death. There is no specific treatment for dengue virus infections. Therapeutic peptides have several important advantages over proteins or antibodies: they are small in size, easy to synthesize, and have the ability to penetrate the cell membranes. They also have high activity, specificity, affinity, and less toxicity. Based on the known peptide inhibitor, the current study designs peptide inhibitors for dengue virus envelope protein using an alanine and residue scanning technique. By replacing I21 with Q21, L14 with H14, and V28 with K28, the binding affinity of the peptide inhibitors was increased. The newly designed peptide inhibitors with single residue mutation improved the binding affinity of the peptide inhibitors. The inhibitory capability of the new promising peptide inhibitors was further confirmed by the utilization of MD simulation and free binding energy calculations. The molecular dynamics simulation demonstrated that the newly engineered peptide inhibitors exhibited greater stability compared to the wild-type peptide inhibitors. According to the binding free energies MM(GB)SA of these developed peptides, the first peptide inhibitor was the most effective against the dengue virus envelope protein. All peptide derivatives had higher binding affinities for the envelope protein and have the potential to treat dengue virus-associated infections. In this study, new peptide inhibitors were developed for the dengue virus envelope protein based on the already reported peptide inhibitor.

SARS-CoV-2: Prediction of critical ionic amino acid mutations

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that caused coronavirus disease 2019 (COVID-19), has been studied thoroughly, and several variants are revealed across the world with their corresponding mutations. Studies and vaccines development focus on the genetic mutations of the S protein due to its vital role in allowing the virus attach and fuse with the membrane of a host cell. In this perspective, we study the effects of all ionic amino acid mutations of the SARS-CoV-2 viral spike protein S1 when bound to Antibody CC12.1 within the SARS-CoV-2:CC12.1 complex model. Binding free energy calculations between SARS-CoV-2 and antibody CC12.1 are based on the Analysis of Electrostatic Similarities of Proteins (AESOP) framework, where the electrostatic potentials are calculated using Adaptive Poisson-Boltzmann Solver (APBS). The atomic radii and charges that feed into the APBS calculations are calculated using the PDB2PQR software. Our results are the first to propose in silico potential life-threatening mutations of SARS-CoV-2 beyond the present mutations found in the five common variants worldwide. We find each of the following mutations: K378A, R408A, K424A, R454A, R457A, K458A, and K462A, to play significant roles in the binding to Antibody CC12.1, since they are turned into strong inhibitors on both chains of the S1 protein, whereas the mutations D405A, D420A, and D427A, show to play important roles in this binding, as they are turned into mild inhibitors on both chains of the S1 protein.

Discovery of highly potent phosphodiesterase-1 inhibitors by a combined-structure free energy perturbation approach

Accurate receptor/ligand binding free energy calculations can greatly accelerate drug discovery by identifying highly potent ligands. By simulating the change from one compound structure to another, the relative binding free energy (RBFE) change can be calculated based on the theoretically rigorous free energy perturbation (FEP) method. However, existing FEP-RBFE approaches may face convergence challenges due to difficulties in simulating non-physical intermediate states, which can lead to increased computational costs to obtain the converged results. To fundamentally overcome these issues and accelerate drug discovery, a new combined-structure RBFE (CS-FEP) calculation strategy was proposed, which solved the existing issues by constructing a new alchemical pathway, smoothed the alchemical transformation, increased the phase-space overlap between adjacent states, and thus significantly increased the convergence and accelerated the relative binding free energy calculations. This method was extensively tested in a practical drug discovery effort by targeting phosphodiesterase-1 (PDE1). Starting from a PDE1 inhibitor (compound 9, IC50 = 16.8 μmol/L), the CS-FEP guided hit-to-lead optimizations resulted in a promising lead (11b and its mesylate salt formulation 11b-Mesylate, IC50 = 7.0 nmol/L), with ∼2400-fold improved inhibitory activity. Further experimental studies revealed that the lead showed reasonable metabolic stability and significant anti-fibrotic effects in vivo.

Machine learning-based QSAR modeling, molecular docking, dynamics simulation studies for cytotoxicity prediction in MDA-MB231 triple-negative breast cancer cell line

Triple-negative breast cancer (TNBC) is the most aggressive cancer type that tests negative for progesterone, estrogen, and HER2 protein receptors. Therefore, TNBC is unlikely to respond either to drugs that target HER2 receptors or to hormonal therapy drugs. In the present study, 2D-QSAR model was developed to predict the inhibitory concentration (IC50) of terpene derivatives against human breast cancer metastatic cell line MDA-MB231, using V-Life MDS v4.5, module. The model was developed using the forward stepwise multiple linear regression method, with a regression coefficient (r2) of 0.86, and a cross-validated r2 (q2) of 0.8448. Molecular descriptors namely electronegativity (Epsilon-3), carbon atoms separated through five bond distances (T_C_C_5), Sum of Electrotopological state indices of –CH2 group (SssCH2count), Dipole moment of coordinate-z (Zcomp Dipole), and Distance between highest positive and negative electrostatic potential on van-der Waals surface area (Most +ve & -ve Potential Distance) were found to be the most potent contributing chemical descriptors for cytotoxicity against TNBC MDA-MB231 cell line. Additionally, binding affinities and interaction patterns revealed that the proposed compounds exhibit good binding affinities and substantial stability with c-Met-and β-tubulin receptors, as assessed by docking studies. Molecular dynamics simulations (100 ns) and binding free energy calculations were also performed using the MMGBSA method. The pharmacokinetic and eADME/T analysis of predicted compounds were assessed through Discovery Studio software. These findings may be of immense importance in the optimization and development of dual inhibitory potent anti-cancer inhibitors against the MDA-MB231 TNBC cell line. Moreover, this novel QSAR based prediction model/method is implemented in R-package and software tool developed for virtual screening purposes and available online for download through the public repository GitHub.

Identification of small molecular inhibitors of SIRT3 by computational and biochemical approaches a potential target of breast cancer

Sirtuin 3 (SIRT3) belongs to the Sirtuin protein family, which consists of NAD+-dependent lysine deacylase, involved in the regulation of various cellular activities. Dysregulation of SIRT3 activity has been linked to several types of cancer, including breast cancer. Because of its ability to stimulate adaptive metabolic pathways, it can aid in the survival and proliferation of breast cancer cells. Finding new chemical compounds targeted towards SIRT3 was the primary goal of the current investigation. Virtual screening of ~ 800 compounds using molecular docking techniques yielded 8 active hits with favorable binding affinities and poses. Docking studies verified that the final eight compounds formed stable contacts with the catalytic domain of SIRT3. Those compounds have good pharmacokinetic/dynamic properties and gastrointestinal absorption. Based on excellent pharmacokinetic and pharmacodynamic properties, two compounds (MI-44 and MI-217) were subjected to MD simulation. Upon drug interaction, molecular dynamics simulations demonstrate mild alterations in the structure of proteins and stability. Binding free energy calculations revealed that compounds MI-44 (− 45.61 ± 0.064 kcal/mol) and MI-217 (− 41.65 ± 0.089 kcal/mol) showed the maximum energy, suggesting an intense preference for the SIRT3 catalytic site for attachment. The in-vitro MTT assay on breast cancer cell line (MDA-MB-231) and an apoptotic assay for these potential compounds (MI-44/MI-217) was also performed, with flow cytometry to determine the compound’s ability to cause apoptosis in breast cancer cells. The percentage of apoptotic cells (including early and late apoptotic cells) increased from 1.94% in control to 79.37% for MI-44 and 85.37% for MI-217 at 15 μM. Apoptotic cell death was effectively induced by these two compounds in a flow cytometry assay indicating them as a good inhibitor of human SIRT3. Based on our findings, MI-44 and MI-217 merit additional investigation as possible breast cancer therapeutics.

Screening approach by a combination of computational and in vitro experiments: identification of fluvastatin sodium as a potential SIRT2 inhibitor.

Sirtuins (SIRTs) are NAD+-dependent deacetylases that play various roles in numerous pathophysiological processes, holding promise as therapeutic targets worthy of further investigation. Among them, the SIRT2 subtype is closely associated with tumorigenesis and malignancies. Dysregulation of SIRT2 activation can regulate the expression levels of related genes in cancer cells, leading to tumor occurrence and metastasis. In this study, we used computer simulations to screen for novel SIRT2 inhibitors from the FDA database, based on which 10 compounds with high docking scores and good interactions were selected for in vitro anti-pancreatic cancer metastasis testing and enzyme binding inhibition experiments. The results showed that fluvastatin sodium may possess inhibitory activity against SIRT2. Subsequently, fluvastatin sodium was subjected to molecular docking experiments with various SIRT isoforms, and the combined results from Western blotting experiments indicated its potential as a SIRT2 inhibitor. Next, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were performed, revealing the binding mode of fluvastatin sodium at the SIRT2 active site, further validating the stability and interaction of the ligand-protein complex under physiological conditions. Overall, this study provides a systematic virtual screening workflow for the discovery of SIRT2 activity inhibitors, identifies the potential inhibitory effect of fluvastatin sodium as a lead compound on SIRT2, and opens up a new direction for developing highly active and selectively targeted SIRT2 inhibitors.

Are Terminal Alkynes Necessary for MAO-A/MAO-B Inhibition? A New Scaffold Is Revealed.

A versatile family of quaternary propargylamines was synthesized employing the KA2 multicomponent reaction, through the single-step coupling of a number of amines, ketones, and terminal alkynes. Sustainable synthetic procedures using transition metal catalysts were employed in all cases. The inhibitory activity of these molecules was evaluated against human monoaminoxidase (hMAO)-A and hMAO-B enzymes and was found to be significant. The IC50 values for hMAO-B range from 152.1 to 164.7 nM while the IC50 values for hMAO-A range from 765.6 to 861.6 nM. Furthermore, these compounds comply with Lipinski's rule of five and exhibit no predicted toxicity. To understand their binding properties with the two target enzymes, key interactions were studied using molecular docking, all-atom molecular dynamics (MD) simulations, and MM/GBSA binding free energy calculations. Overall, herein, the reported family of propargylamines exhibits promise as potential treatments for neurodegenerative disorders, such as Parkinson's disease. Interestingly, this is the first time a propargylamine scaffold bearing an internal alkyne has been reported to show activity against monoaminoxidases.

Molecular Generation, QSAR, and Molecular Dynamic Simulation Studies for Virtual Screening of DNA Polymerase Theta Inhibitors.

The machine learning-based QSAR modeling procedure, molecular generations, and molecular dynamic simulations were applied to virtually screen the DNA polymerase theta inhibitors. The DNA polymerase theta (Polθ or POLQ) is an attractive target for treatments of homologous recombination deficient (such as BRCA deficient) cancers. There are no approved drugs for targeting POLQ, and only one inhibitor is in Phase Ⅱclinical trials; thus, it is necessary to develop novel POLQ inhibitors. To build machine learning models that predict the bioactivities of POLQ inhibitors. To build molecular generation models that generate diverse molecules. To virtually screen the generated molecules by the machine learning models. To analyze the binding modes of the screening results by molecular dynamic simulations. In the present work, 325 inhibitors with POLQ polymerase domain bioactivities were Collected. Two machine learning methods, random forest and deep neural network, were used for building the ligand- and structure-based quantitative structure-activity relationship (QSAR) models. The substructure replacement-based method and transfer learning-based deep recurrent neural network method were used for molecular generations. Molecular docking and consensus QSAR models were carried out for virtual screening. The molecular dynamic simulations and MM/GBSA binding free energy calculation and decomposition were used to further analyze the screening results. The MCC values of the best ligand- and structure-based consensus QSAR models reached 0.651 and 0.361 for the test set, respectively. The machine learning-based docking scores had better-predicted ability to distinguish the highly and weakly active poses than the original docking scores. The 96490 molecules were generated by both molecular generation methods, and 10 molecules were retained by virtual screening. Four favorable interactions were concluded by molecular dynamic simulations. We hope that the screening results and the binding modes are helpful for designing the highly active POLQ polymerase inhibitors and the models of the molecular design workflow can be used as reliable tools for drug design.

Calculating Binding Free Energies in Model Host-Guest Systems with Unrestrained Advanced Sampling.

Host-guest interactions are important to the design of pharmaceuticals and, more broadly, to soft materials as they can enable targeted, strong, and specific interactions between molecules. The binding process between the host and guest may be classified as a "rare event" when viewing the system at atomic scales, such as those explored in molecular dynamics simulations. To obtain equilibrium binding conformations and dissociation constants from these simulations, it is essential to resolve these rare events. Advanced sampling methods such as the adaptive biasing force (ABF) promote the occurrence of less probable configurations in a system, therefore facilitating the sampling of essential collective variables that characterize the host-guest interactions. Here, we present the application of ABF to a rod-cavitand coarse-grained model of host-guest systems to acquire the potential of mean force. We show that the employment of ABF enables the computation of the configurational and thermodynamic properties of bound and unbound states, including the free energy landscape. Moreover, we identify important dynamic bottlenecks that limit sampling and discuss how these may be addressed in more general systems.

In-Silico study of Destabilizing Alzheimer’s Aβ42 Protofibrils with Curcumin.

Aggregation of amyloid beta (Aβ) peptides leads to formation of fibrilar, soluble oligomers, and their deposition is a key event in progression of Alzheimer’s disease (AD). Recent experimental studies of (Curcumin) showed\ significant Aβ aggregation inhibition, but its molecular mechanism is not yet clear. Hence, the present study aims at exploring the underlying mechanism of destabilization and inhibition of aggregation of the Aβ protofibril by Curcumin at the molecular level. Molecular docking analysis shows that Curcumin binds to chain E of the Aβ protofibril through hydrogen bonding interactions. Comparative molecular dynamics simulations depict the binding of Curcumin at the edge of chain E, and its partially inserted conformation at the hydrophobic core destabilizes the Aβ protofibril. Its binding causes loss of hydrophobic contacts, leading to a partial opening of tightly packed β-sheet protofibrils. The hydration effect of salt bridge between the amino group of Lys28 and the oxygen atom of Curcumin contributes in destabilization of Aβ protofibrils. Binding free energy calculations of Curcumin and the Aβ protofibril showed that van der Waals interactions are dominant over the others. Thus, our results revealed that Curcumin interacts mainly with the hydrophobic core along with positively charged residues of the Aβ protofibril for effective destabilization. Thus, this structural information could be useful to design new inhibitors to control the aggregation of Aβ protofibrils in AD patients.

Isolation, Virtual Screening, and Evaluation of Hazelnut-Derived Immunoactive Peptides for the Inhibition of SARS-CoV-2 Main Protease.

The aim of this study is to validate the activity of hazelnut (Corylus avellana L.)-derived immunoactive peptides inhibiting the main protease (Mpro) of SARS-CoV-2 and further unveil their interaction mechanism using in vitro assays, molecular dynamics (MD) simulations, and binding free energy calculations. In general, the enzymatic hydrolysis components, especially molecular weight < 3 kDa, possess good immune activity as measured by the proliferation ability of mouse splenic lymphocytes and phagocytic activity of mouse peritoneal macrophages. Over 866 unique peptide sequences were isolated, purified, and then identified by nanohigh-performance liquid chromatography/tandem mass spectrometry (NANO-HPLC-MS/MS) from hazelnut protein hydrolysates, but Trp-Trp-Asn-Leu-Asn (WWNLN) and Trp-Ala-Val-Leu-Lys (WAVLK) in particular are found to increase the cell viability and phagocytic capacity of RAW264.7 macrophages as well as promote the secretion of the cytokines nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β). Fluorescence resonance energy transfer assay elucidated that WWNLN and WAVLK exhibit excellent inhibitory potency against Mpro, with IC50 values of 6.695 and 16.750 μM, respectively. Classical all-atom MD simulations show that hydrogen bonds play a pivotal role in stabilizing the complex conformation and protein-peptide interaction. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation indicates that WWNLN has a lower binding free energy with Mpro than WAVLK. Furthermore, adsorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions illustrate favorable drug-likeness and pharmacokinetic properties of WWNLN compared to WAVLK. This study provides a new understanding of the immunomodulatory activity of hazelnut hydrolysates and sheds light on peptide inhibitors targeting Mpro.

Impact of protein conformations on binding free energy calculations in the beta-secretase 1 system.

In binding free energy calculations, simulations must sample all relevant conformations of the system in order to obtain unbiased results. For instance, different ligands can bind to different metastable states of a protein, and if these protein conformational changes are not sampled in relative binding free energy calculations, the contribution of these states to binding is not accounted for and thus calculated binding free energies are inaccurate. In this work, we investigate the impact of different beta-sectretase 1 (BACE1) protein conformations obtained from x-ray crystallography on the binding of BACE1 inhibitors. We highlight how these conformational changes are not adequately sampled in typical molecular dynamics simulations. Furthermore, we show that insufficient sampling of relevant conformations induces substantial error in relative binding free energy calculations, as judged by a variation in calculated relative binding free energies up to 2kcal/mol depending on the starting protein conformation. These results emphasize the importance of protein conformational sampling and pose this BACE1 system as a challenge case for further method development in the area of enhanced protein conformational sampling, either in combination with binding calculations or as an endpoint correction.

Experimental and computational study on anti-gastric cancer activity and mechanism of evodiamine derivatives.

Introduction: Human topoisomerase 1 (TOP1) is an important target of various anticancer compounds. The design and discovery of inhibitors targeting TOP1 are of great significance for the development of anticancer drugs. Evodiamine and thieno [2,3-d] pyridine hybrids show potential antitumor activity. Herein, the anti-gastric cancer activities of these hybrids were investigated. Methods: The inhibitory effects of different concentrations of ten evodiamine derivatives on the gastric cancer cell line SGC-7901 were assessed using a methyl thiazolyl tetrazolium assay. Compounds EVO-1 and EVO-6 strongly inhibited gastric cancer cell proliferation, with inhibition rates of 81.17% ± 5.08% and 80.92% ± 2.75%, respectively. To discover the relationship between the structure and activity of these two derivatives, density functional theory was used to investigate their optimized geometries, natural population charges, frontier molecular orbitals, and molecular electrostatic potentials. To clarify their anti-gastric cancer mechanisms, molecular docking, molecular dynamics simulations, and binding free energy calculations were performed against TOP1. Results: The results demonstrated that these compounds could intercalate into the cleaved DNA-binding site to form a TOP1-DNA-ligand ternary complex, and the ligand remained secure at the cleaved DNA-binding site to form a stable ternary complex. As the binding free energy of compound EVO-1 with TOP1 (-38.33kcal·mol-1) was lower than that of compound EVO-6 (-33.25kcal·mol-1), compound EVO-1 could be a more potent anti-gastric cancer agent than compound EVO-6. Discussion: Thus, compound EVO-1 could be a promising anti-gastric cancer drug candidate. This study may facilitate the design and development of novel TOP1 inhibitors.

MOLECULAR DOCKING DYNAMICS OF SELECTED BENZYLIDENE AMINO PHENYL ACETAMIDES AS TMK INHIBITORS USING HIGH THROUGHPUT VIRTUAL SCREENING (HTVS)

Objective: Thymidylate kinase (TMK) plays a crucial role in bacterial DNA synthesis by catalyzing the phosphorylation of deoxythymidine monophosphate (dTMP) to form deoxythymidine diphosphate (dTDP). Consequently, this enzyme emerges as a promising target for developing novel antibacterial drugs. However, no antibiotics were reported for this target, especially active against Staphylococcus aureus thymidylate kinase. Methods: Benzylidene acetamide-based ligands were examined for their potency using the in silico method. These novel ligand structures were built using ChemDraw software. The protein was retrieved from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) website. The molecular docking and binding free energy calculation by prime Molecular Mechanics in Generalized Bond Surface Area (MM-GBSA) was performed for selected ligands. A 100 ns molecular dynamic simulation was also performed to assess the stability of the potential ligand as TMK inhibitors. Results: All ten molecules have shown good glide scores and hydrophobic and hydrogen hydrophobic hydrogen bonding interactions with Arg48, Arg36, and π-π stacking Phe66 in the TMK enzyme (PDB: 4HLC). Among them, N-(2-ethylphenyl)-2-(4-((4-nitrobenzylidene) amino) phenoxy) acetamide molecule had high XP-docking scores of-3.27 kcal/mol based on extra-precision data. Prime Molecular Mechanics in Generalized Bond Surface Area study (MM-GBSA) studies also showed promising binding affinities that are ΔBind (-65.80), ΔLipo (-28.55), and ΔVdW (-55.10). Phe66 amino acid residue maintained continuous connections with the ligand during MD simulation. This ligand showed promising binding affinity with the SaTMK target. Conclusion: The N-(2-ethylphenyl)-2-(4-((4-nitrobenzylidene) amino) phenoxy) acetamide ligand at the position of the benzene ring displayed nitrogen and oxygen group, thus indicating good potential activity as the inhibitor of TMK to treat antibacterial agents.

Evaluation of surfactant-aided polycyclic aromatic hydrocarbon biodegradation by molecular docking and molecular dynamic simulation in the marine environment

Marine oil spills directly cause polycyclic aromatic hydrocarbons (PAHs) pollution and affect marine organisms due to their toxic property. Chemical and bio-based dispersants composed of surfactants and solvents are considered effective oil spill-treating agents. Dispersants enhance oil biodegradation in the marine environment by rapidly increasing their solubility in the water column. However, the effect of dispersants, especially surfactants, on PAHs degradation by enzymes produced by microorganisms has not been studied at the molecular level. The role of the cytochrome P450 (CYP) enzyme in converting contaminants into reactive metabolites during the biodegradation process has been evidenced, but the activity in the presence of surfactants is still ambiguous. Thus, this study focused on the evaluation of the impact of chemical and bio-surfactants (i.e., Tween 80 (TWE) and Surfactin (SUC)) on the biodegradation of naphthalene (NAP), chrysene (CHR), and pyrene (PYR), the representative components of PAHs, with CYP enzyme from microalgae Parachlorella kessleri using molecular docking and molecular dynamics (MD) simulation. The molecular docking analysis revealed that PAHs bound to residues at the CYP active site through hydrophobic interactions for biodegradation. The MD simulation showed that the surfactant addition changed the enzyme conformation in the CYP-PAH complexes to provide more interactions between the enzyme and PAHs. This led to an increase in the enzyme's capability to degrade PAHs. Binding free energy (ΔG‌‌Bind) calculations confirmed that surfactant treatment could enhance PAHs degradation by the enzyme. The SUC gave a better result on NAP and PYR biodegradation based on ΔG‌‌Bind, while TWE facilitated the biodegradation of CHR. The research outputs could greatly facilitate evaluating the behaviors of oil spill-treating agents and oil spill response operations in the marine environment.

Phloretin prolongs lifespan of Caenorhabditis elegans via inhibition of NDUFS1 and NDUFS6 at mitochondrial complex Ⅰ

Phloretin has been widely perceived as an antioxidant. However, the bioavailability of phloretin in vivo is generally far too low to elicit a direct antioxidant effect by scavenging reactive oxygen species (ROS). Here we showed that administration of phloretin of apple polyphenols extended lifespan of Caenorhabditis elegans and promoted fitness. Specially phloretin enhanced the survival rates of nematodes under oxidants in an inverted U-shaped dose-response manner. The lifespan-extending effects of phloretin were mediated by ROS via mitochondrial complex I inhibition. The increase of ROS stimulated p38 MAPK/PMK-1 as well as transcription factors of NRF2/SKN-1 and FOXO/DAF-16. Consistent with the involvement of NRF2/SKN-1 and FOXO/DAF-16 in lifespan-extending effects, activities of superoxide dismutase (SOD) and catalase (CAT) were enhanced by phloretin. The exogenous application of antioxidants butylated hydroxyanisole and N-acetylcysteine abolished the increase of ROS, the enhancement of SOD and CAT activities, and the lifespan extending effects of phloretin. Meanwhile, with the inhibition of mitochondrial complex I, ATP was instantly decreased. Both energy sensors of AMPK/AAK-2 and SIRT1/SIR-2.1 were involved in the lifespan extension by phloretin. Transcriptomic, real-time qPCR and molecular docking analyses demonstrated that the binding of phloretin at complex I located at NDUFS1/NUO-5, NDUFS2/GAS-1, and NDUFS6/NDUF-6. The molecular dynamic simulation and binding free energy calculations showed that phloretin had high binding affinities towards NDUFS1 (−7.21 kcal/mol) and NDUFS6 (−7.02 kcal/mol). Collectively, our findings suggested phloretin had effects of life expectancy enhancement and fitness promotion via redox regulations in vivo. NDUFS1/NUO-5 and NDUFS6/NDUF-6 might be new targets in the lifespan and wellness regulations.

In silico analysis and characterization of potential inhibitors of MmaA3, a methoxy mycolic acid synthase from Mycobacterium tuberculosis

The emergence of the multi-and extensively drug-resistant (MDR and XDR) strains of Mycobacterium tuberculosis (M.tb), necessitates paradigm-shifting therapeutic approaches. The impermeable waxy lipid layer, primarily composed of mycolic acids, is a key factor in conferring resistance to conventional drugs. This study introduces a novel strategy to combat drug resistance by targeting Methoxy mycolic acid synthase 3 (MmaA3), a critical enzyme in the mycolic acid biosynthesis pathway. MmaA3 is responsible for the O-methylation of hydroxymycolate precursors and emerges as a promising therapeutic target. Through homology-based modeling, we generated a three-dimensional structure of MmaA3, providing crucial insights into its structural characteristics. High throughput virtual screening was performed against the MmaA3 model, using diverse sources: knowledge-based, FDA-approved Drugbank, and Asinex-Elite libraries. Through rigorous computational analyses, including binding affinity assessments, molecular interactions analysis, and binding free energy calculations, potential inhibitors of MmaA3 have been identified. Subsequent validation studies evaluated the stability of top protein-ligand complexes, and free energy calculations using molecular dynamics simulations. The stability of complexes within the catalytic site was confirmed through RMSD and RMSF profile analyses. Furthermore, binding free energy calculations using the MM-GBSA approach revealed significant binding affinity of identified ligands for MmaA3 target protein, comparable to its substrate/cofactors. These findings underscore the potential of the proposed molecules as candidates for further experimental exploration, offering promising avenues for the development of effective inhibitors against M.tb. Overall, our research contributes to significantly advancing the formulation of progressive therapeutic strategies in combating drug-resistant tuberculosis. Communicated by Ramaswamy H. Sarma

In silico evaluation of anti-colorectal cancer inhibitors by Resveratrol derivatives targeting Armadillo repeats domain of APC: molecular docking and molecular dynamics simulation.

Colorectal cancer is the second leading cause of cancer-related deaths. In 2018, there were an estimated 1.8 million cases, and this number is expected to increase to 2.2 million by 2030. Despite its prevalence, the current therapeutic option has a lot of side effects and limitations. Therefore, this study was designed to employ a computational approach for the identification of anti-cancer inhibitors against colorectal cancer using Resveratrol derivatives. Initially, the pass prediction spectrum of 50 derivatives was conducted and selected top seven compounds based on the maximum pass prediction score. After that, a comprehensive analysis, including Lipinski Rule, pharmacokinetics, ADMET profile study, molecular orbitals analysis, molecular docking, molecular dynamic simulations, and MM-PBSA binding free energy calculations. The reported binding affinity ranges of Resveratrol derivatives from molecular docking were -6.1 kcal/mol to -7.9 kcal/mol against the targeted receptor of human armadillo repeats domain of adenomatous polyposis coli (APC) (PDB ID: 3NMW). Specifically, our findings reported that two compounds [(03) Resveratrol 3-beta-mono-D-glucoside, and (29) Resveratrol 3-Glucoside] displayed the highest level of effectiveness compared to all other derivatives (-7.7 kcal/mol and -7.9 kcal/mol), and favorable drug-likeness, and exceptional safety profiles. Importantly, almost all the molecules were reported as free from toxic effects. Subsequently, molecular dynamic simulations conducted over 100ns confirmed the stability of the top two ligand-protein complexes. These findings suggest that Resveratrol derivatives may be effective drug candidate to manage the colorectal cancer. However, further experimental research, such as in vitro/in vivo studies, is essential to validate these computational findings and confirm their practical value.

A structure-based pharmacophore modelling approach to identify and design new neprilysin (NEP) inhibitors: An in silico-based investigation

Neutral endopeptidase or neprilysin (NEP) cleaves the natriuretic peptides, bradykinin, endothelin, angiotensin II, amyloid β protein, substance P, etc., thus modulating their effects on heart, kidney, and other organs. NEP has a proven role in hypertension, heart disease, renal disease, Alzheimer's, diabetes, and some cancers. NEP inhibitor development has been in focus since the US FDA approved a combination therapy of angiotensin II type 1 receptor inhibitor (valsartan) and NEP inhibitor (sacubitril) for use in heart failure. Considering the importance of NEP inhibitors the present work focuses on the designing of a potential lead for NEP inhibition. A structure-based pharmacophore modelling approach was employed to identify NEP inhibitors from the pool of 1140 chemical entities obtained from the ZINC database. Based on the docking score and pivotal interactions, ten molecules were selected and subjected to binding free energy calculations and ADMET predictions. The top two compounds were studied further by molecular dynamics simulations to determine the stability of the ligand-receptor complex. ZINC0000004684268, a phenylalanine derivative, showed affinity and complex stability comparable to sacubitril. However, in silico studies indicated that it may have poor pharmacokinetic parameters. Therefore, the molecule was optimized using bioisosteric replacements, keeping the phenylalanine moiety intact, to obtain five potential lead molecules with an acceptable pharmacokinetic profile. The works thus open up the scope to further corroborate the present in silico findings with the biological analysis.