Poisson-Boltzmann Surface Area Research Articles

Expression Pattern and Ligand Binding Characteristics Analysis of Chemosensory Protein SnitCSP2 from Sirex nitobei.

Sirex nitobei is an important wood-boring wasp to conifers native to Asia, causing considerable economic and ecological damage. However, the current control means cannot achieve better efficiency, and it is expected to clarify the molecular mechanism of protein-ligand binding for effective pest control. This study analyzed the expression pattern of CSP2 in S. nitobei (SnitCSP2) and its features of binding to the screened ligands using molecular docking and dynamic simulations. The results showed that SnitCSP2 was significantly expressed in female antennae. Molecular docking and dynamic simulations revealed that SnitCSP2 bound better to the host plant volatile (+)-α-pinene and symbiotic fungal volatiles terpene and (-)-globulol than other target ligands. By the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method, the free binding energies of the three complexes were calculated as -44.813 ± 0.189 kJ/mol, -50.446 ± 0.396 kJ/mol, and -56.418 ± 0.368 kJ/mol, and the van der Waals energy was found to contribute significantly to the stability of the complexes. Some key amino acid residues were also identified: VAL13, GLY14, LYS61, MET65, and LYS68 were important for the stable binding of (+)-α-pinene by SnitCSP2, while for terpenes, ILE16, ALA25, TYR26, CYS29, GLU39, THR37, and GLY40 were vital for a stable binding system. We identified three potential ligands and analyzed the interaction patterns of the proteins with them to provide a favorable molecular basis for regulating insect behavioral interactions and developing new pest control strategies.

Identification of new pentapeptides as potential inhibitors of amyloid–β42 aggregation using virtual screening and molecular dynamics simulations

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease mainly characterized by extracellular accumulation of amyloid-β (Aβ) peptide. Previous studies reported pentapeptide RIIGL as an effective inhibitor of Aβ aggregation and neurotoxicity induced by Aβ aggregates. In this work, a library of 912 pentapeptides based on RIIGL has been designed and assessed for their efficacy to inhibit Aβ42 aggregation using computational techniques. The top hit pentapeptides revealed by molecular docking were further assessed for their binding affinity with Aβ42 monomer using MM-PBSA (molecular mechanics Poisson-Boltzmann surface area) method. The MM-PBSA analysis identified RLAPV, RVVPI, and RIAPA, which bind to Aβ42 monomer with a higher binding affinity −55.80, −46.32, and −44.26 kcal/mol, respectively, as compared to RIIGL (ΔGbinding = −41.29 kcal/mol). The residue-wise binding free energy predicted hydrophobic contacts between Aβ42 monomer and pentapeptides. The secondary structure analysis of the conformational ensembles generated by molecular dynamics (MD) depicted remarkably enhanced sampling of helical and no β–sheet conformations in Aβ42 monomer on the incorporation of RVVPI and RIAPA. Notably, RVVPI and RIAPA destabilized the D23–K28 salt bridge in Aβ42 monomer, which plays a crucial role in Aβ42 oligomer stability and fibril formation. The MD simulations highlighted that the incorporation of proline and arginine in pentapeptides contributed to their strong binding with Aβ42 monomer. Furthermore, RVVPI and RIAPA prevented conformational conversion of Aβ42 monomer to aggregation-prone structures, which, in turn, resulted in a lower aggregation tendency of Aβ42 monomer.

Identification of phytochemical inhibitors targeting phosphate acetyltransferase of Mycoplasma genitalium: insights from virtual screening and molecular dynamics studies.

Mycoplasma genitalium (M. genitalium) has evolved as a superbug, and the developing antimicrobial resistancewith just a few treatment options available is an imminentconcern. Due to the emergence of antibiotic resistance, a new antibiotic class or medications are requiredto combat this pathogen. The phosphate acetyltransferase (PTA) enzyme can be a suitable drug target which is essential for M. genitalium survival and involves in acetate metabolism. To efficiently find potent inhibitors, structure-based drug design approaches targeting the PTA of M. genitalium have been established. In this study, the three most potent phytochemical inhibitors were predicted from virtual screening and these are sitostanyl ferulate, beta-sitosterol-beta-D-glucoside, and brassinolide, with binding energies of - 9.66, - 9.60, and - 9.48kcal/mol, respectively. The active site residues Thr-125, Arg-300, Ser-299, Tyr-272, and Lys-273 appear to be critical in binding the three predicted potentinhibitors. The results of the molecular dynamics study indicate that the three predicted phytochemical inhibitors have formed stable bonds with PTA. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) was utilized for the estimation of binding free energy of PTA-phytochemical complexes. Taken together, the findings of our computational work might aid in the development of possible potential drugsto treat and ameliorate the severity of M. genitalium infection.

Uni-GBSA: an open-source and web-based automatic workflow to perform MM/GB(PB)SA calculations for virtual screening.

Binding free energy calculation of a ligand to a protein receptor is a fundamental objective in drug discovery. Molecular mechanics/Generalized-Born (Poisson-Boltzmann) surface area (MM/GB(PB)SA) is one of the most popular methods for binding free energy calculations. It is more accurate than most scoring functions and more computationally efficient than alchemical free energy methods. Several open-source tools for performing MM/GB(PB)SA calculations have been developed, but they have limitations and high entry barriers to users. Here, we introduce Uni-GBSA, a user-friendly automatic workflow to perform MM/GB(PB)SA calculations, which can perform topology preparation, structure optimization, binding free energy calculation and parameter scanning for MM/GB(PB)SA calculations. It also offers a batch mode that evaluates thousands of molecules against one protein target in parallel for efficient application in virtual screening. The default parameters are selected after systematic testing on the PDBBind-2011 refined dataset. In our case studies, Uni-GBSA produced a satisfactory correlation with the experimental binding affinities and outperformed AutoDock Vina in molecular enrichment. Uni-GBSA is available as an open-source package at https://github.com/dptech-corp/Uni-GBSA. It can also be accessed for virtual screening from the Hermite web platform at https://hermite.dp.tech. A free Uni-GBSA web server of a lab version is available at https://labs.dp.tech/projects/uni-gbsa/. This increases user-friendliness because the web server frees users from package installations and provides users with validated workflows for input data and parameter settings, cloud computing resources for efficient job completions, a user-friendly interface and professional support and maintenance.

Probing some recent natural compounds from Phellinus baumii, Colletotrichum sp. and Ligustrum lucidum as heat shock protein 90 inhibitors

Heat shock protein 90 (HSP90) is one of the most attractive targets for research on cancer treatment, and nowadays, many studies carried out for the development of effective HSP90 inhibitors. In the current study, recently published ten natural compounds have been investigated using computer aided drug design (CADD) approach. The study consists of three parts; (1) density functional theory (DFT) calculations including geometry optimizations, vibrational analyses, and molecular electrostatic potential (MEP) map calculations, (2) molecular docking and molecular dynamics (MD) simulations, and (3) binding energy calculations. In DFT calculations, Becke three-parameter hybrid functional with Lee-Yang-Parr correlation functional (B3LYP) and 6-31 + G(d,p) basis set were used. After performing molecular docking calculations, top-scoring ligand-receptor complexes were subjected to MD simulations for 100 ns to investigate the stability of the ligand-receptor complexes and the interactions in more detail. Finally, in binding energy calculations molecular mechanics with Poisson-Boltzmann surface area (MM-PBSA) method was used. The results showed that five of the investigated ten natural compounds have higher binding affinity to HSP90α than that of reference drug Geldanamycin, and could be promising compounds for future studies. Communicated by Ramaswamy H. Sarma

In silico identification of natural compounds against SARS-CoV-2 main protease from Chinese herbal medicines.

To determine natural compounds with inhibitory effects toward SARS-CoV-2 Mpro from Chinese herbal medicines. ∼1200 natural compounds from 19 Chinese herbal medicines were collected. Computational methods including molecular docking, drug-likeness assessment, molecular dynamics simulation and molecular mechanics Poisson-Boltzmann surface area analysis were combined to obtain potent inhibitors against SARS-CoV-2 Mpro. Top 20 compounds mainly originated from Ranunculus ternatus and Picrasma quassioides exhibited low binding free energies which below -9.0 kcal/mol. Compounds Japonicone G and Picrasidine T were obtained with favorable drug-likeness. Moreover, the complex of Japonicone G and Mpro had prominent stability. Natural compound Japonicone G is highly promising as a potent inhibitor against SARS-CoV-2 for further study.

Investigating the novel-binding site of RPA2 on Menin and predicting the effect of point mutation of Menin through protein–protein interactions

Protein–protein interactions (PPIs) play a critical role in all biological processes. Menin is tumor suppressor protein, mutated in multiple endocrine neoplasia type 1 syndrome and has been shown to interact with multiple transcription factors including (RPA2) subunit of replication protein A (RPA). RPA2, heterotrimeric protein required for DNA repair, recombination and replication. However, it’s still remains unclear the specific amino acid residues that have been involved in Menin-RPA2 interaction. Thus, accurately predicting the specific amino acid involved in interaction and effects of MEN1 mutations on biological systems is of great interests. The experimental approaches for identifying amino acids in menin-RPA2 interactions are expensive, time-consuming, and challenging. This study leverages computational tools, free energy decomposition and configurational entropy scheme to annotate the menin-RPA2 interaction and effect on menin point mutation, thereby proposing a viable model of menin-RPA2 interaction. The menin–RPA2 interaction pattern was calculated on the basis of different 3D structures of menin and RPA2 complexes, constructed using homology modeling and docking strategy, generating three best-fit models: Model 8 (− 74.89 kJ/mol), Model 28 (− 92.04 kJ/mol) and Model 9 (− 100.4 kJ/mol). The molecular dynamic (MD) was performed for 200 ns and binding free energies and energy decomposition analysis were calculated using Molecular Mechanics Poisson–Boltzmann Surface Area (MM/PBSA) in GROMACS. From binding free energy change, model 8 of Menin-RPA2 exhibited most negative binding energy of − 205.624 kJ/mol, followed by model 28 of Menin-RPA2 with − 177.382 kJ/mol. After S606F point mutation in Menin, increase of BFE (ΔGbind) by − 34.09 kJ/mol in Model 8 of mutant Menin-RPA2 occurs. Interestingly, we found a significant reduction of BFE (ΔGbind) and configurational entropy by − 97.54 kJ/mol and − 2618 kJ/mol in mutant model 28 as compared the o wild type. Collectively, this is the first study to highlight the configurational entropy of protein–protein interactions thereby strengthening the prediction of two significant important interaction sites in menin for the binding of RPA2. These predicted sites could be vulnerable for structural alternation in terms of binding free energy and configurational entropy after missense mutation in menin.

Determination of potential combination of non-β-lactam, β-lactam, and β-lactamase inhibitors/β-lactam enhancer against class D oxacillinases producing Acinetobacter baumannii: Evidence from in-vitro, molecular docking and dynamics simulation.

Carbapenem-resistant Acinetobacter baumannii, a predominant nosocomial pathogen in hospitals of intensive care units, is associated with bacteremia and ventilator-associated pneumonia with a high-risk mortality rate. To increase the effectiveness of the β-lactam (BL) antibiotics, the use of β-lactamase inhibitors (BLI) acts as a booster when given in combination with BL antibiotics. To this aspect, we selected BL antibiotics of cefiderocol, cefepime, non-BL antibiotic eravacycline, BLI of durlobactam, avibactam, and a β-lactam enhancer (BLE) of zidebactam. To prove our hypothesis, we determined the minimum inhibitory concentration (MIC) of various BL or non-BL/BLI or BLE combinations using broth microdilution method followed by in silico analysis of molecular docking, molecular dynamics (MD) simulation, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) identifies the potential combination. In MIC testing, eravacycline, cefepime/zidebactam, cefiderocol/zidebactam, and eravacycline in combination with zidebactam or durlobactam were found to be effective against oxacillinases (OXAs) (OXA-23/24/58 like) expressing A. baumannii isolates. The docking results of the selected ligands toward OXA-23, OXA-24, and OXA-58 had an excellent binding score ranging from -5.8 to -9.3 kcal/mol. Further, the docked complexes were subjected and evaluated using gromacs for molecular dynamics simulation of 50 ns toward selected class D OXAs. The binding energies obtained from MM-PBSA shed light on the binding efficiencies of each non-BL, BL, and BLI/BLE, thereby helping us to propose the drug combinations. Based on the MD trajectories scoring acquired, we propose using eravacycline, cefepime/zidebactam, cefiderocol/zidebactam, and eravacycline in combination with durlobactam or zidebactam would be promising for treating OXA-23, OXA-24, and OXA-58 like expressing A. baumannii infections.

In silico analysis of the different variable domain oriented single-chain variable fragment antibody-antigen complexes

Single-chain variable fragment (scFv) antibodies hold great potential as diagnostic tools and therapeutic agents, especially for tumor cells. Since these applications require their production with improved properties, the design strategy of scFvs is crucial for their active, soluble, and high yield expression with high affinity towards their antigens. The order of VL and VH domains is one of the important parameters that affect the expression and binding affinity properties of scFvs. In addition, the optimum order of VL and VH domains could change for each scFv. In the present study, we used computer simulation tools to evaluate the effect of variable domain orientation on structure, stability, interacting residues of scFvs, and binding free energies of scFv-antigen complexes. We selected anti-HER2 scFv, which is specific for human epidermal growth receptor 2 (HER2) overexpressed in breast cancer, and anti-IL-1β scFv against IL-1β which is an important inflammatory biomarker, as model scFvs. Molecular dynamics simulations of the scFv-antigen complexes for 100 ns resulted in stability and compactness for both scFv constructs. Interaction and binding free energies calculated by the Molecular Mechanics–Poisson–Boltzmann Surface Area (MM-PBSA) approach suggested that the relative binding energies of anti-HER2 scFv-VLVH and anti-HER2 scFv-VHVL constructs had similar binding affinity towards HER2, while a relatively more negative binding free energy obtained between anti-IL-1β scFv-VHVL and IL-1β pointed to a higher binding affinity. The in silico approach and the results obtained here could be applied as a guide for future experimental interaction studies for highly specific scFvs used as biotechnological tools. Communicated by Ramaswamy H. Sarma

Design of a novel multi-epitope vaccine candidate against Chlamydia trachomatis using structural and nonstructural proteins: an immunoinformatics study

Chlamydia trachomatis (C. trachomatis) is an obligate intracellular bacterium which causes eye and sexually transmitted infections. During pregnancy, the bacterium is associated with preterm complications, low weight of neonates, fetal demise and endometritis leading to infertility. The aim of our study was design of a multi-epitope vaccine (MEV) candidate against C. trachomatis. After protein sequence adoption from the NCBI, potential epitopes toxicity, antigenicity, allergenicity, MHC-I and MHC-II binding, cytotoxic T lymphocytes (CTLs), Helper T lymphocytes (HTLs) and interferon-γ (IFN-γ)- induction were predicted. The adopted epitopes were fused together using appropriate linkers. In the next step, the MEV structural mapping and characterization, three-dimensional (3D) structure homology modeling and refinement were also performed. The MEV candidate interaction with the toll-like receptor 4 (TLR4) was also docked. The immune responses simulation was assessed using the C-IMMSIM server. Molecular dynamic (MD) simulation verified the structural stability of the TLR4-MEV complex. The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach demonstrated the MEV high affinity of binding to the TLR4, MHC-I and MHC-II. The MEV construct was also stable and water soluble and had enough antigenicity and lacked allergenicity with stimulation of T cells and B cells and INF-γ release. The immune simulation confirmed acceptable responses of both the humoral and cellular arms. It is proposed that in vitro and in vivo studies are needed to evaluate the findings of this study. Communicated by Ramaswamy H. Sarma

In silico and in vitro investigation of dual targeting Prima-1MET as precision therapeutic against lungs cancer

This study emphasizes the explorations of binding of Prima-1MET with two targets, p53 a tumor suppressor protein, and tyrosine kinase of epidermal growth factor receptor. In silico investigations reveal that Prima-1MET showed robust binding with both targets. Molecular docking simulations demonstrated the binding affinity of Prima-1MET with p53 and tyrosine kinase was found to be −38.601 kJ/mol and −38.976 kJ/mol. In addition, the stability of Prima-1MET was explored by molecular dynamics simulation. Prima-1MET attains stability in the binding site of the respective protein till the simulation period is over. Moreover, the free binding energy ΔG bind was calculated by the molecular mechanics Poisson Boltzmann surface area method. The ΔG bind of Prima-1MET with tyrosine kinase was found to be −58.585 ± 0.327 kJ/mol and with p53 it was −35.910 ± 0.335 kJ/mol. Next, cytotoxicity of the Prima-1MET was evaluated using multiple cancer cell lines and the IC50 value were ranging between 4.5 and 30 μM. The cell death was identified by apoptosis assay. Further, the p53 and tyrosine kinase expression was monitored using immunofluorescence techniques, it was found Prima-1MET induces the expression of p53 protein and mimics the level of tyrosine kinase oncogenic target. Also, reactive oxygen species (ROS) and membrane potential activity of Prima-1MET was evaluated by using a lung cancer cell line. A significant decrease in intracellular ROS was observed and resulted in disruption of mitochondrial transmembrane potential. This study uncovers the underlying mechanism of Prima-1MET and could be helpful to design further leads against lung cancers. Communicated by Ramaswamy H. Sarma

At the origin of the selectivity of the chlorophyll-binding sites in Light Harvesting Complex II (LHCII)

The photosynthetic light-harvesting complexes (LHCs) are responsible for light absorption due to their pigment-binding properties. These pigments are primarily Chlorophyll (Chl) molecules of type a and b, which ensure an excellent coverage of the visible light spectrum. To date, it is unclear which factors drive the selective binding of different Chl types in the LHC binding pockets. To gain insights into this, we employed molecular dynamics simulations on LHCII binding different Chl types. From the resulting trajectories, we have calculated the binding affinities per each Chl-binding pocket using the Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) model. To further examine the importance of the nature of the axial ligand in tuning the Chl selectivity of the binding sites, we used Density Functional Theory (DFT) calculations. The results indicate that some binding pockets have a clear Chl selectivity, and the factors governing these selectivities are identified. Other binding pockets are promiscuous, which is consistent with previous in vitro reconstitution studies. DFT calculations show that the nature of the axial ligand is not a major factor in determining the Chl binding pocket selectivity, which is instead probably controlled by the folding process.

Resistance to Resveratrol Treatment in Experimental PTSD Is Associated with Abnormalities in Hepatic Metabolism of Glucocorticoids.

Glucocorticoids are metabolized by the CYP3A isoform of cytochrome P450 and by 11-β-hydroxysteroid dehydrogenase type 1 (11β-HSD-1). Experimental data suggest that post-traumatic stress disorder (PTSD) is associated with an increase in hepatic 11β-HSD-1 activity and a concomitant decrease in hepatic CYP3A activity. Trans-resveratrol, a natural polyphenol, has been extensively studied for its antipsychiatric properties. Recently, protective effects of trans-resveratrol were found in relation to PTSD. Treatment of PTSD rats with trans-resveratrol allowed the rats to be divided into two phenotypes. The first phenotype is treatment-sensitive rats (TSR), and the second phenotype is treatment-resistant rats (TRRs). In TSR rats, trans-resveratrol ameliorated anxiety-like behavior and reversed plasma corticosterone concentration abnormalities. In contrast, in TRR rats, trans-resveratrol aggravated anxiety-like behavior and decreased plasma corticosterone concentration. In TSR rats, hepatic 11β-HSD-1 activity was suppressed, with a concomitant increase in CYP3A activity. In TRR rats, the activities of both enzymes were suppressed. Thus, the resistance of PTSD rats to trans-resveratrol treatment is associated with abnormalities in hepatic metabolism of glucocorticoids. The free energy of binding of resveratrol, cortisol, and corticosterone to the human CYP3A protein was determined using the molecular mechanics Poisson-Boltzmann surface area approach, indicating that resveratrol could affect CYP3A activity.

Molecular modeling study of natural products as potential bioactive compounds against SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the COVID-19 infection and responsible for millions of victims worldwide, remains a significant threat to public health. Even after the development of vaccines, research interest in the emergence of new variants is still prominent. Currently, the focus is on the search for effective and safe drugs, given the limitations and side effects observed for the synthetic drugs administered so far. In this sense, bioactive natural products that are widely used in the pharmaceutical industry due to their effectiveness and low toxicity have emerged as potential options in the search for safe drugs against COVID-19. Following this line, we screened 10 bioactive compounds derived from cholesterol for molecules capable of interacting with the receptor-binding domain (RBD) of the spike protein from SARS-CoV-2 (SC2Spike), responsible for the virus's invasion of human cells. Rounds of docking followed by molecular dynamics simulations and binding energy calculations enabled the selection of three compounds worth being experimentally evaluated against SARS-CoV-2. The 3D structures of the cholesterol derivatives were prepared and optimized using the Spartan 08 software with the semi-empirical method PM3. They were then exported to the Molegro Virtual Docking (MVD®) software, where they were docked onto the RBD of a 3D structure of the SC2Spike protein that was imported from the Protein Data Bank (PDB). The best poses obtained from MVD® were subjected to rounds of molecular dynamics simulations using the GROMACS software, with the OPLS/AA force field. Frames from the MD simulation trajectories were used to calculate the ligand's free binding energies using the molecular mechanics - Poisson-Boltzmann surface area (MM-PBSA) method. All results were analyzed using the xmgrace and Visual Molecular Dynamics (VMD)software.

Identification of potent anti-fibrinolytic compounds against plasminogen and tissue-type plasminogen activator employing in silico approaches

The zymogen protease Plasminogen (Plg) and its active form plasmin (Plm) carry out important functions in the blood clot disintegration (breakdown of fibrin fibers) process. Inhibition of plasmin effectively reduces fibrinolysis to circumvent heavy bleeding. Currently, available Plm inhibitor tranexamic acid (TXA) used for treating severe hemorrhages is associated with an increased incidence of seizures which in turn were traced to gamma-aminobutyric acid antagonistic activity (GABAa) in addition to having multiple side effects. Fibrinolysis can be suppressed by targeting the three important protein domains: the kringle-2 domain of tissue plasminogen activator, the kringle-1 domain of plasminogen, and the serine protease domain of plasminogen. In the present study, one million molecules were screened from the ZINC database. These ligands were docked to their respective protein targets using Autodock Vina, Schrödinger Glide, and ParDOCK/BAPPL+. Thereafter, the drug-likeness properties of the ligands were evaluated using Discovery Studio 3.5. Subsequently, we subjected the protein-ligand complexes to molecular dynamics simulation of 200 ns in GROMACS. The identified ligands P76(ZINC09970930), C97(ZINC14888376), and U97(ZINC11839443) for each protein target are found to impart higher stability and greater compactness to the protein-ligand complexes. Principal component analysis (PCA) implicates, that the identified ligands occupy smaller phase space, form stable clusters, and provide greater rigidity to the protein-ligand complexes. Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis reveals that P76, C97, and U97 exhibit better binding free energy (ΔG) when compared to that of the standard ligands. Thus, our findings can be useful for the development of promising anti-fibrinolytic agents. Communicated by Ramaswamy H. Sarma

Revisiting MMPBSA by Adoption of MC-Based Surface Area/Volume, ANI-ML Potentials, and Two-Valued Interior Dielectric Constant.

Here, we report the accuracy improvements of molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations by adoption of ANI-ML potentials in replacement of MM terms, the use of solvent-accessible surface area (SASA) and volume (SAV) values from the Monte Carlo sampling of the probe, and introducing two different interior dielectric constants for electrostatic interactions of protein-ligand (P-L) and polar solvation term in the MMPBSA calculations. Our results show that the Pearson correlation coefficients of MMPBSA-calculated values with respect to experimental binding free energies can be drastically improved from 0.48 to 0.90 by adoption of ANI-ML potentials in replacement of MM energy terms in the equation, referred to as ANI-PBSA. Moreover, we show that the SASA/SAV-combined equation in the scaled particle theory (SPT) can be a better choice to model nonpolar solvation term, reaching nearly the same accuracy by ANI-PBSA calculations. Finally, we introduce two different values of interior dielectric constants, which could be an alternative strategy between the single and variable constant definitions.

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.

DFT, molecular docking and molecular dynamics simulation studies on some recent natural products revealing their EGFR tyrosine kinase inhibition potential

Phytochemicals are important chemical compounds in pharmaceutical chemistry. These natural compounds have interesting biological activities, including anticancer, as well as many other functions. EGFR (epidermal growth factor receptor) tyrosine kinase inhibition is emerging as one of the accepted methods in the treatment of cancer. On the other hand, computer-aided drug design has become an increasingly important field of study due to its many important advantages such as efficient use of time and other resources. In this study, fourteen phytochemicals which have triterpenoid structure and have recently entered the literature were investigated computationally for their potential as EGFR tyrosine kinase inhibitors. In the study, DFT (density functional theory) calculations, molecular docking, molecular dynamics simulations, binding free energy calculations with the use of MM-PBSA (molecular mechanics Poisson-Boltzmann Surface Area) method, and ADMET predictions were performed. The obtained results were compared to the results obtained for reference drug Gefitinib. Results showed that the investigated natural compounds are promising structures for EGFR tyrosine kinase inhibition. Communicated by Ramaswamy H. Sarma

Evaluation of in vitro effect, molecular docking, and molecular dynamics simulations of some dihydropyridine-class calcium channel blockers on human serum paraoxonase 1 (hPON1) enzyme activity.

Paraoxonase 1 (PON1) was purified 148.80-fold in 37.92% yield by hydrophobic interaction chromatography technique. The purity of PON1 was checked by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) with a single band of 43kDa. The in vitro effects of nine different calcium channel blockers on PON1 activity were evaluated. All drugs strongly decreased PON1 activity, and IC50 levels were between 13.987 ± 0.59 and 238.104 ± 2.14μM, Ki values between 8.58±0.36 and 111±1.27μM. The drugs with the strongest inhibitory effect were nisoldipine with 13.987 ± 0.59μM and nicardipine with 20.158 ± 0.43μM. The mechanism of action for the inhibition of the enzyme by nisoldipine and nicardipine was investigated through molecular docking. The stability of enzyme-ligand complexes obtained from the docking was explored through molecular dynamics simulation. The binding affinity of the ligands toward the enzyme was also investigated through MMPBSA (molecular mechanics Poisson-Boltzmann surface area method). The computational analysis demonstrated these compounds could inhibit the enzyme. Nisoldipine had the strongest binding, and its complex was the most stable one. Furthermore, nicardipine was found to have the highest affinity toward the enzyme.

Discovering potential inhibitors of Raf proto-oncogene serine/threonine kinase 1: a virtual screening approach towards anticancer drug development

Raf proto-oncogene serine/threonine kinase 1 (RAF1 or c-Raf) is a serine/threonine protein kinase crucial in regulating cell growth, differentiation, and survival. Any disruption or overexpression of RAF1 can result in neoplastic transformation and other disorders such as cardiomyopathy, Noonan syndrome, leopard syndrome, etc. RAF1 has been identified as a potential therapeutic target in drug development against various complex diseases, including cancer, due to its remarkable role in disease progression. Here, we carried out a multitier virtual screening study involving different in-silico approaches to discover potential inhibitors of RAF1. After applying the Lipinski rule of five, we retrieved all phytocompounds from the IMPPAT database based on their physicochemical properties. We performed a molecular docking-based virtual screening and got top hits with the best binding affinity and ligand efficiency. Then we screened out the selected hits using the PAINS filter, ADMET properties, and other druglike features. Eventually, PASS evaluation identifies two phytocompounds, Moracin C and Tectochrysin, with appreciable anti-cancerous properties. Finally, all-atom molecular dynamics simulation (MDS) followed by interaction analysis was performed on the elucidated compounds in complex with RAF1 for 200 ns to investigate their time-evolution dynamics and interaction mechanism. Molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) and Dynamical Cross-Correlation Matrix (DCCM) analyses then followed these results from the simulated trajectories. According to the results, the elucidated compounds stabilize the RAF1 structure and lead to fewer conformational alterations. The results of the current study indicated that Moracin C and Tectochrysin could serve as potential inhibitors of RAF1 after required validation. Communicated by Ramaswamy H. Sarma