Molecular Mechanics Poisson-Boltzmann Surface Area Research Articles

Molecular Mechanism for Regioselectivity of P450-BM3 Monooxygenase Towards Stearic Acid Hydroxylation

Hydroxy stearic acid is an important raw material for the synthesis of biobased materials, and the hydroxylation at different positions showed different properties. With the catalysis of P450-BM3 monooxygenase, (ω - 1)-Hydroxy stearic acid was generated, which is a precursor of macrocyclic musk. Experimental results have shown that the L188Q mutant can increase the yield of (ω - 1)-Hydroxy stearic acid by more than three times, but the reason and underlying molecular mechanism are still unclear. In this study, molecular dynamics (MD) simulations were conducted to study the structural characteristics of the P450-BM3 wild type and its three mutants (F87V, L188Q, and F87V-L188Q) in combination with stearic acid. The MD simulation results showed significant changes in the interactions between the three mutants and the carboxyl- and terminal-end of stearic acid. The results of the Molecular mechanics-Poisson-Boltzmann surface area (MMPBSA) binding free energies indicated that the L188Q mutant showed the most stable binding with the stearic acid. Finally, the H-abstraction free energy barriers of L188Q and wild type systems were calculated to study the regioselectivity, and the results indicated that the L188Q mutant shown a significant advantage in the hydroxylation of stearic acid at the ω - 1 position. Our research results not only explain molecular mechanism for regioselectivity of P450-BM3 towards stearic acid hydroxylation, but also provide some useful ideas for the synthesis of biobased materials from hydroxy fatty acids.

Decoding dynamic interactions between EGFR-TKD and DAC through computational and experimental approaches: A novel breakthrough in lung melanoma treatment.

In the quest for effective lung cancer treatments, the potential of 3,6-diaminoacridine-9-carbonitrile (DAC) has emerged as a game changer. While DAC's efficacy against glioblastoma is well documented, its role in combating lung cancer has remained largely untapped. This study focuses on CTX-1, exploring its interaction with the pivotal EGFR-TKD protein, a crucial target in lung cancer therapeutics. A meticulous molecular docking analysis revealed that CTX-1 exhibits a noteworthy binding affinity of -7.9 kcal/mol, challenging Erlotinib, a conventional lung cancer medication, which displayed a binding affinity of -7.3 kcal/mol. For a deeper understanding of CTX-1's molecular mechanics, this study employed rigorous 100-ns molecular dynamics simulations, demonstrating CTX-1's remarkable stability in comparison with erlotinib. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method further corroborated these results, with CTX-1 showing a free binding energy of -105.976 ± 1.916 kJ/mol. The true prowess of CTX-1 was tested against diverse lung cancer cell lines, including A549, Hop-62 and H-1299. CTX-1 not only significantly outperformed erlotinib in anticancer activity but also exhibited a spectrum of therapeutic effects. It effectively diminished cancer cell viability, induced DNA damage, halted cell cycle progression, generated reactive oxygen species (ROS), impaired mitochondrial transmembrane potential, instigated apoptosis and successfully inhibited EGFR-TKD. This study not only underscores the potential of CTX-1 a formidable contender in lung cancer treatment but also marks a paradigm shift in oncological therapeutics, offering new horizons in the fight against this formidable disease.

Isatin based 1,2,3-triazole derivatives as antimicrobial agents: Synthesis, in silico docking and molecular dynamics simulations

With the aim to identify new antimicrobials, in the present study a new series of isatin based 1,2,3-triazoles (5a-5f & 6a-6f) has been synthesized through CuAAC click reaction and characterized by FTIR, NMR and MS spectral methods. In vitro antimicrobial assay suggested that synthesized derivatives exhibited good to high efficacy against tested microorganisms. Compounds 5c, 5d, 5f exhibited promising potency towards E. coli, similarly, 5b, 5d, 5e and 6d displayed good antifungal efficacy against C. albicans. These compounds also exhibited better potency against both the fungal strains as compared to the standard drug. Molecular docking studies of these derivatives performed against antibacterial and antifungal targets 1KZN (E. coli) and 5TZ1(C. albicans) revealed that hybrid 5b possessed lowest binding energy i.e. -9.1 kcal/mol and -11.0 kcal/mol, respectively. Moreover, Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) analysis was used to compute the various components contributing to binding free energy of 5b with these biological targets.

Computational exploration of novel antimicrobial modalities targeting fucose-binding lectins and ribosomes in Mycobacterium smegmatis using tRNA-encoded peptides

tRNA-Encoded Peptides (tREPs), encoded by small open reading frames (smORFs) within tRNA genes, have recently emerged as a new class of functional peptides exhibiting antiparasitic activity. The discovery of tREPs has led to a re-evaluation of the role of tRNAs in biology and has expanded our understanding of the genetic code. This presents an immense, unexplored potential in the realm of tRNA-peptide interactions, paving the way for groundbreaking discoveries and innovative applications in various biological functions. This study explores the antimicrobial potential of tREPs against protein targets by employing a computational method that uses verified data sources and highly recognized predictive algorithms to provide a sorted list of likely antimicrobial peptides, which were then filtered for toxicity, cell permeability, allergenicity and half-life. These peptides were then docked with screened protein targets and computationally validated using molecular dynamics (MD) simulations for 150 ns and the binding free energy was estimated. The peptides Pep2 (VVLWRKPRVRKTG) and Pep6 (HRLRLRRRKPWW) exhibited good binding affinities of −110.5 +/− 2.5 and −129.0 +/− 3.9, respectively, with RMSD values of 0.4 and 0.25 nm against the fucose-binding lectin (7NEF) and the 30S ribosome of Mycobacterium smegmatis (5O5J) protein targets. The 7NEF-Pep2 and 5O5J-Pep6 complexes indicated higher negative binding free energies of −52.55 kcal/mol and −55.52 kcal/mol respectively, as calculated by Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA). Thus, the tREPs derived peptides designed as a part of this study, provide novel approaches for potential anti-bacterial therapeutic modalities. Communicated by Ramaswamy H. Sarma

Bioinformatics-driven discovery of novel EGFR kinase inhibitors as anti-cancer therapeutics: In silico screening and in vitro evaluation.

Epidermal growth factor receptor EGFR inhibitors are widely used as first line therapy for the treatment of non-small-cell lung cancer (NSCLC) in patients harboring EGFR mutation. However, the acquisition of a second-site mutation (T790 M) limited the efficacy and developed resistance. Therefore, discovery and development of specific drug target for this mutation is of urgent needs. In our study we used the ChemDiv diversity database for receptor-based virtual screening to secure EGFR-TK inhibitors chemotherapeutics. We identified four compounds that bind to the ATP-binding region of the EGFR-TK using AutoDock 4.0 and AutoDock Vina1.1.2 and post-docking investigations. The ligand showed hydrophobic interactions to the hydrophobic region of the binding site and engaged in hydrogen bonding with Met793. The ligands also explored π-cation interactions between the π-system of the ligand-phenyl ring and the positive amino group of Lys745. Molecular mechanics Poisson-Boltzmann surface area MM/PBSA per-residue energy decomposition analyses revealed that Val726, Leu792, Met793, Gly796, Cys797, Leu798, and Thr844 contributed the most to the binding energy. Biological evaluation of the retrieved hit compounds showed suppressing activity against EGFR auto phosphorylation and selective apoptosis-induced effects toward lung cancer cells harboring the EGFR L858R/T790M double mutation. Our work anticipated into novel and specific EGFR-TKIs and identified new compounds with therapeutic potential against lung cancer.

Molecular docking and molecular dynamics simulation decoding molecular mechanism of EDCs binding to hERRγ.

Human estrogen-related receptor γ (hERRγ) is a key protein involved in various endocrines and metabolic signaling. Numerous environmental endocrine-disrupting chemicals (EDCs) can impact related physiological activities through receptor signaling pathways. Focused on hERRγ with 4-isopropylphenol, bisphenol-F (BPF), and BP(2,2)(Un) complexes, we executed molecular docking and multiple molecular dynamics (MD) simulations along with molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) and solvation interaction energy (SIE) calculation to study the detailed dynamical structural characteristics and interactions between them. Molecular docking showed that hydrogen bonds and hydrophobic interactions were the prime interactions to keep the stability of BPF-hERRγ and hERRγ-BP(2,2)(Un) complexes. Through MD simulations, we observed that all complexes reach equilibrium during the initial 50ns of simulation, but these three EDCs lead to local structure changes in hERRγ. Energy results further identified key residues L268, V313, L345, and F435 around the binding pockets through CH-π, π-π, and hydrogen bonds interactions play an important stabilizing role in the recognition with EDCs. And most noticeable of all, hydrophobic methoxide groups in BP(2,2)(Un) is useful for decreasing the binding ability between EDCs and hERRγ. These results may contribute to evaluate latent diseases associated with EDCs exposure at the micro level and find potential substitutes. Autodock4.2 was used to conduct the molecular docking, sietraj program was performed to calculate the energy, and VMD software was used to visualize the structure. Amber18 was conducted to perform the MD simulation and other analyses.

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study.

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Network Pharmacology Approach to Identify the Calotropis Phytoconstituents' Potential Epileptic Targets and Evaluation of Molecular Docking, MD Simulation, and MM-PBSA Performance.

Epilepsy originates from unusual electrical rhythm within brain cells, causes seizures. Calotropis species have been utilized to treat a wide spectrum of ailments since antiquity. Despite chemical and biological investigations, there have been minimal studies on their anticonvulsant activity, and the molecular targets of this plant constituents are unexplored. This study was aimed at investigating the plausible epileptic targets of Calotropis phytoconstituents through network pharmacology, and to evaluate their binding strength and stability with the identified targets. In detail, 125 phytoconstituents of Calotropis plant (C. procera and C. gigantea) were assessed for their drug likeness (DL), blood-brain-barrier (BBB) permeability and oral bioavailability (OB). Network analysis revealed that targets PTGS2 and PPAR-γ were ranked first and fourth, respectively, among the top ten hub genes significantly linked with antiepileptic drug targets. Additionally, docking, molecular dynamic (MD) simulation and Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) were employed to validate the compound-gene interactions. Docking studies suggested ergost-5-en-3-ol, stigmasterol and β-sitosterol exhibit strong binding affinity and favorable interactions than co-crystallized ligands with both the targets. Furthermore, both MD simulations and MM-PBSA calculations substantiated the docking results. Combined data revealed Calotropis phytoconstituents ergost-5-en-3-ol, stigmasterol and β-sitosterol might be the best inhibitors of both PTGS2 and PPAR-γ.

A computational approach to design a multiepitope vaccine against H5N1 virus

Since 1997, highly pathogenic avian influenza viruses, such as H5N1, have been recognized as a possible pandemic hazard to men and the poultry business. The rapid rate of mutation of H5N1 viruses makes the whole process of designing vaccines extremely challenging. Here, we used an in silico approach to design a multi-epitope vaccine against H5N1 influenza A virus using hemagglutinin (HA) and neuraminidase (NA) antigens. B-cell epitopes, Cytotoxic T lymphocyte (CTL) and Helper T lymphocyte (HTL) were predicted via IEDB, NetMHC-4 and NetMHCII-2.3 respectively. Two adjuvants consisting of Human β-defensin-3 (HβD-3) along with pan HLA DR-binding epitope (PADRE) have been chosen to induce more immune response. Linkers including KK, AAY, HEYGAEALERAG, GPGPGPG and double EAAAK were utilized to link epitopes and adjuvants. This construct encodes a protein having 350 amino acids and 38.46 kDa molecular weight. Antigenicity of ~ 1, the allergenicity of non-allergen, toxicity of negative and solubility of appropriate were confirmed through Vaxigen, AllerTOP, ToxDL and DeepSoluE, respectively. The 3D structure of H5N1 was refined and validated with a Z-Score of − 0.87 and an overall Ramachandran of 99.7%. Docking analysis showed H5N1 could interact with TLR7 (docking score of − 374.08 and by 4 hydrogen bonds) and TLR8 (docking score of − 414.39 and by 3 hydrogen bonds). Molecular dynamics simulations results showed RMSD and RMSF of 0.25 nm and 0.2 for H5N1-TLR7 as well as RMSD and RMSF of 0.45 nm and 0.4 for H5N1-TLR8 complexes, respectively. Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) confirmed stability and continuity of interaction between H5N1-TLR7 with the total binding energy of − 29.97 kJ/mol and H5N1-TLR8 with the total binding energy of − 23.9 kJ/mol. Investigating immune response simulation predicted evidence of the ability to stimulate T and B cells of the immunity system that shows the merits of this H5N1 vaccine proposed candidate for clinical trials.

A novel immunoinformatics approach for developing a poly-epitope vaccine targeting foot and mouth disease virus, exploiting structural VP proteins

Foot and mouth Disease virus (FMDV) belongs to Picornaviridae family and Aphthovirus genus causing Foot and mouth disease (FMD) in cloven-hoofed animals. FMDV, a prevalent virus induces both acute and chronic infections with high mutation rates resulting in seven primary serotypes, making vaccine development indispensable. Due to time and cost effectiveness of the immunoinformatic approach, we designed in-silico polyepitope vaccine (PEV) for the curtailment of FMDV. Structural and immunogenic parts of FMDV (Viral Protein 1 (VP1), Viral Protein 2 (VP2), Viral Protein 3 (VP3), and Viral Protein 4 (VP4)) were used to design the cytotoxic T Lymphocyte (CTL), Helper T Lymphocyte (HTL), and B-cell epitopes, followed by screening for antigenic, non-allergenic, Interferon (IFN) simulator, and non-toxicity, which narrowed down to 7 CTL, 3 HTL, and 12 B-cell epitopes. These selected epitopes were linked using appropriate linkers and Cholera Toxin B (CTB) adjuvant for immunological modulation. The physiochemical analyses followed by the structure prediction demonstrated the stability, hydrophilicity and solubility of the PEV. The interactions and stability between the vaccine, Toll like Receptor 3 (TLR3) and Toll like receptor 7 (TLR7) were revealed by molecular docking and Molecular Mechanics/Poisson Boltzmann Surface Area (MMPBSA) with high stability and compactness verified by MD simulation. In-silico immune simulation demonstrated a strong immunological response. FMDV-PEV (Poly epitope vaccine) will be effectively produced in an E. coli system, as codon optimization and cloning in an expression vector was performed. The effectiveness, safety, and immunogenicity profile of FMDV-PEV may be confirmed by further experimental validations. Communicated by Ramaswamy H. Sarma

The Virtual Screening of Compounds from the ZINC Database against PARP‐1 in Triple‐Negative Breast Cancer

AbstractTriple‐negative breast cancer (TNBC) is the most aggressive kind of breast cancer that has disseminated worldwide, decimating millions of people. Especially, since it is capable of forming complex mutations, the design and development of effective drugs are much needed. Clinically, though talazoparib is an FDA‐approved drug for PARP against advanced breast cancer, it has several adverse side effects such as anaemia, alopecia, neutropenia and thrombocytopenia. Herein, to understand the molecular interactions and mode of binding, 4.59 million lead‐like compounds from the ZINC database were virtually screened against poly(ADP‐ribose) polymerase‐1 (PARP‐1) protein using molecular docking. ADMET analysis were also performed for these compounds. Molecular dynamics (MD) simulations were conducted for a period of 100 ns for the best five compounds to validate the stability of the complexes. Root‐mean‐square deviation (RMSD), root‐mean‐square fluctuation (RMSF), and the radius of gyration (Rg) were analyzed and the number of hydrogen bonding interactions was identified to determine the structure and stability of these protein‐ligand complexes. Further, binding free energy calculations were performed using the molecular mechanics‐Poisson‐Boltzmann surface area (MM/PBSA) approach to identify the effective anticancer agents. Z02, Z03, and Z04 have the highest binding affinity of −19.6, −18.1, and −18.1 kcal/mol, respectively, with PARP‐1. They also have been found to strongly enhance the stability of the target. All things considered; we determine that compound Z04 is the most promising hit for TNBC.

Decoding Molecular Mechanism Underlying Human Olfactory Receptor OR8D1 Activation by Sotolone Enantiomers.

Sotolone, a chiral compound, plays an important role in the food industry. Herein, (R)-/(S)-sotolone were separated to determine their odor characteristics and thresholds in air (R-form: smoky, burned, herb, and green aroma, 0.0514 μg/m3; S-form: sweet, milk, acid, and nutty aroma, 0.0048 μg/m3). OR8D1 responses to (R)-/(S)-sotolone were detected in a HEK293 cell-based luminescence assay. (S)-Sotolone was a more potent agonist than (R)-sotolone (EC50 values of 84.98 ± 1.05 and 167.20 ± 0.25 μmol/L, respectively). Molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area analyses confirmed that the combination of (S)-sotolone and OR8D1 was more stable than that of (R)-sotolone. Odorant docking, multiple sequence alignments, site-directed mutagenesis, and functional studies with recombinant odorant receptors (ORs) in a cell-based luminescence assay identified 11 amino-acid residues that influence the enantioselectivity of OR8D1 toward sotolone significantly and that N2065.46 was indispensable to the activation of OR8D1 by (S)-sotolone.

Harnessing Brazilian biodiversity database: identification of flavonoids as potential inhibitors of SARS-CoV-2 main protease using computational approaches and all-atom molecular dynamics simulation.

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is the etiological agent responsible for the global outbreak of COVID-19 (Coronavirus Disease 2019). The main protease of SARS-CoV-2, Mpro, is a key enzyme that plays a vital role in mediating viral replication and transcription. In this study, a comprehensive computational approach was employed to investigate the binding affinity, selectivity, and stability of natural product candidates as potential new antivirals acting on the viral polyprotein processing mediated by SARS-CoV-2 Mpro. A library of 288 flavonoids extracted from Brazilian biodiversity was screened to select potential Mpro inhibitors. An initial filter based on Lipinski's rule of five was applied, and 204 compounds that did not violate any of the Lipinski rules were selected. The compounds were then docked into the active site of Mpro using the GOLD program, and the poses were subsequently re-scored using MM-GBSA (Molecular Mechanics Generalized Born Surface Area) binding free energy calculations performed by AmberTools23. The top five flavonoids with the best MM-GBSA binding free energy values were selected for analysis of their interactions with the active site residues of the protein. Next, we conducted a toxicity and drug-likeness analysis, and non-toxic compounds were subjected to molecular dynamics simulation and free energy calculation using the MM-PBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) method. It was observed that the five selected flavonoids had lower MM-GBSA binding free energy with Mpro than the co-crystal ligand. Furthermore, these compounds also formed hydrogen bonds with two important residues, Cys145 and Glu166, in the active site of Mpro. Two compounds that passed the drug-likeness filter showed stable conformations during the molecular dynamics simulations. Among these, NuBBE_867 exhibited the best MM-PBSA binding free energy value compared to the crystallographic inhibitor. Therefore, this study suggests that NuBBE_867 could be a potential inhibitor against the main protease of SARS-CoV-2 and may be further examined to confirm our results.

Unraveling Bacterial Single-Stranded Sequence Specificities: Insights from Molecular Dynamics and MMPBSA Analysis of Oligonucleotide Probes.

We utilized molecular dynamics (MD) simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) free energy calculations to investigate the specificity of two oligonucleotide probes, namely probe B and probe D, in detecting single-stranded DNA (ssDNA) within three bacteria families: Enterobacteriaceae, Pasteurellaceae, and Vibrionaceae. Due to the limited understanding of molecular mechanisms in the previous research, we have extended the discussion to focus specifically on investigating the binding process of bacteria-probe DNA duplexes, with an emphasis on analyzing the binding free energy. The role of electrostatic contributions in the specificity between the oligonucleotide probes and the bacterial ssDNAs was investigated and found to be crucial. Our calculations yielded results that were highly consistent with the experimental data. Through our study, we have successfully exhibited the benefits of utilizing in-silico approaches as a powerful virtual-screening tool, particularly in research areas that demand a thorough comprehension of molecular interactions.

Discovery of small molecules from natural compound databases as potent retinoid X alpha receptor agonists to treat Alzheimer's disease.

Alzheimer's is characterized as a progressive neurodegenerative disease due to beta-amyloid accumulation in the brain. Some previous studies reported that RXR agonists could be effective in the treatment of Alzheimer's disease. There are currently numerous attempts being made to discover a natural RXR agonist that is more potent than 9-cis-retinoic acid (9CR). One of the most efficient resources for finding high-potential compounds is natural databases. In this study, 81215 compounds from the IB screen library as natural databases were docked against the RXR-alpha binding site. The best compounds discovered interact with the RXR-alpha binding site with a lower binding energy (-11 to -13 kcal/mol) than the binding energy of -10.94 kcal/mol for 9-cis, which means that these compounds could interact stronger with RXR-alpha than 9CR. All selected compounds could pass the blood-brain barrier. Physiochemical properties assessment indicated that all compounds passed Lipinski's rule and had the potential to be oral drug candidates. The stability of protein-ligand complexes during a timescale of 100 ns by Molecular Dynamics simulation demonstrated that all compounds could effectively interact with the RXR binding site. The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) represented that all selected hit compounds had a better binding affinity to the alpha RXR binding site compared to 9CR, which means these hit compounds had potential drug candidates for the treatment of Alzheimer's disease. However, experimental assessment is needed to validate this result.Communicated by Ramaswamy H. Sarma.

Bioinformatics analysis and molecular dynamics simulations of azoreductases (AzrBmH2) from Bacillus megaterium H2 for the decolorization of commercial dyes

The present study aimed to investigate the decolorization of various commercial dyes by azoreductases (AzrBmH21, AzrBmH22/3, and AzrBmH24/5) through bioinformatics means, comprising molecular docking, molecular dynamics simulation, and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA). Therefore, four commercial dyes, namely acid orange 7, cresol red, methylene blue, and malachite green, were selected as potential targets for degradation by the above said azoreductases derived from Bacillus megaterium H2. The prediction of ligand binding or catalytic sites for AzrBmH21, AzrBmH22/3, and AzrBmH24/5 were performed using a machine learning algorithm based on the Prank Web and DeepSite chemoinformatic tool. This analysis revealed that several amino acids of AzrBmH2 interacted with the tested dyes, indicating the presence of distinct ligand-binding sites for AzrBmH2-dye complexes. Likewise, the binding affinity for AzrBmH21, AzrBmH22/3, and AzrBmH24/5 ranged from − 9.4 to − 5.5 kcal/mol, − 9.2 to − 5.4 kcal/mol, and − 9.0 to − 5.4 kcal/mol, respectively, with each complex stabilized at a minimum of 0–5 hydrogen bonds. MD simulations revealed stable AzrBmH2-dye complexes with RMSD and RMSF values ranging from 0.15 to 0.42 nm and 0.05 to 0.48 nm, respectively, with Rg values between 1.75 and 1.88 nm. MM-PBSA calculations indicated that the AzrBmH2–dye complexes, except for AzrBmH2–malachite green, exhibited the lowest binding energy (− 191.05 ± 7.08 to 314.19 ± 6.88 kcal/mol), with prevalent hydrophobic interactions (− 268.25 ± 12.25 to − 418.92 ± 29.45 kcal/mol) through van der Waals forces. Therefore, this study was able to highlight the potential role of enzymes, specifically azoreductases from Bacillus megaterium H2, in predicting the decolorization of commercial dyes. These findings could contribute to our understanding of the azoreductases’ mechanisms in bioremediation and for biotechnological applications.

Biophysical and structural characterization of tetramethrin serum protein complex and its toxicological implications.

Tetramethrin (TMT) is a commonly used insecticide and has a carcinogenic and neurodegenerative effect on humans. The binding mechanism and toxicological implications of TMT to human serum albumin (HSA) were examined in this study employing a combination of biophysical and computational methods indicating moderate binding affinity and potential hepato and renal toxicity. Fluorescence quenching experiments showed that TMT binds to HSA with a moderate affinity, and the binding process was spontaneous and predominantly enthalpy-driven. Circular dichroism spectroscopy revealed that TMT binding did not induce any significant conformational changes in HSA, resulting in no changes in its alpha-helix content. The binding site and modalities of TMT interactions with HSA as computed by molecular docking and molecular dynamics simulations revealed that it binds to Sudlow site II of HSA via hydrophobic interactions through its dimethylcyclopropane carboxylate methyl propanyl group. The structural dynamics of TMT induce proper fit into the binding site creating increased and stabilizing interactions. Additionally, molecular mechanics-Poisson Boltzmann surface area calculations also indicated that non-polar and van der Waals were found to be the major contributors to the high binding free energy of the complex. Quantum mechanics (QM) revealed the conformational energies of the binding confirmation and the degree of deviation from the global minimum energy conformation of TMT. The results of this study provide a comprehensive understanding of the binding mechanism of TMT with HSA, which is important for evaluating the toxicity of this insecticide in humans.

Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer.

In the current study, Neosetophomone B (NSP-B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues' flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of -36.85kcal/mol for the FGF6-NSP-B complex, -43.87kcal/mol for the FGF20-NSP-B complex, and -37.42kcal/mol for the FGF22-NSP-B complex, and -41.91kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of -30.05kcal/mol for the FGF6-NSP-B complex, -39.62kcal/mol for the FGF20-NSP-B complex, -34.89kcal/mol for the FGF22-NSP-B complex, and -37.18kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.

Biochemical and in silico analysis of the binding mode of erastin with tubulin

Erastin (ERN) is a small molecule that induces different forms of cell death. For example, it has been reported to induce ferroptosis by disrupting tubulin subunits that maintain the voltage-dependent anion channels (VDACs) of mitochondria. Although its possible binding to tubulin has been suggested, the fine details of the interaction between ERN and tubulin are poorly understood. Using a combination of biochemical, cell-model and in silico approaches, we elucidate the interactions of ERN with tubulin and their biological manifestations. After confirming ERN's antiproliferative efficacy (IC50, 20 ± 3.2 M) and induction of cell death in the breast cancer cell line MDA-MB-231, the binding interactions of ERN with tubulin were examined. ERN bound to tubulin in a concentration-dependent manner, disorganizing the structural integrity of the protein, as substantiated via the tryptophan-quenching assay and the aniline-naphthalene sulfonate binding assay, respectively. In silico studies based on molecular docking revealed a docking score of −5.863 kcal/mol, suggesting strong binding interactions of ERN with tubulin. Additionally, molecular dynamics simulation and Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) analyses evinced the binding free energy (ΔGbinding) of −31.235 kcal/mol, substantiating strong binding affinity of ERN with tubulin. Ligplot analysis showed hydrogen bonding with specific amino acids (Asn A226, Thr A223, Gln B247 and Val B355). QikProp-based ADME (absorption, distribution, metabolism and excretion) assessment showed considerable therapeutic potential for ERN. Communicated by Ramaswamy H. Sarma

Use of hybrid molecular simulation techniques for systematic analysis of polyphenols as promising therapeutic agent against SARS-CoV-2

In our current study, we systematically report the four phenol classes via three-layer in silico screening approaches consisting of quantum chemical methods, molecular docking and molecular dynamics simulations. We studied the interactions of main protease (Mpro) and Nsp9 proteins of SARS-CoV-2 with four classes of polyphenolic compounds, where both proteins are crucial for virus replication. The phenols are extensively reported for medicinal applications, as these are antioxidants, anti-parasitic, anti-viral, anti-diabetic and anti-inflammatory compounds. Initial molecular docking study shows that among forty phenolic compounds the L9, L17, L26 and, L32 reveal the best binding energies with Mpro protein. Their values of docking score in terms of binding energy with Mpro protein is ranging from -5.7 to -6.8 kcal.mol−1. While on the other hands, L8, L11, L22 and, L34 exhibit the best docking scores with Nsp9 protein, which are ranging from -5.8 to -6.8 kcal.mol−1. Additionally, the lead compounds (ligands) were studied by quantum chemical methods for their optimized or the lowest energy structures, electronic properties, frontier molecular orbitals (FMOs) as well as molecular electrostatic potentials (MEPs). The global chemical descriptors are also calculated to explain the global reactivity trend for the lead compounds. To mimic the aqueous like environment, we added ions according to the electrostatic potential of the macromolecule, water molecules are being added to create physiologically relevant environment for studying biological molecules. Proteins, nucleic acids, and other biomolecules are typically surrounded by water molecules in biological systems. The addition of water molecules in MD simulations may provide a more accurate representation of their natural environment. The molecular dynamics simulations are performed for the complexes of best-docked lead compounds and for both proteins (Mpro and, Nsp9) over multiple replicate trajectories of 320 ns. The flexibility and stability behavior of the lead compounds in terms of RMSD and RMSF plots are analyzed through MD simulations results. The binding free energy of the best-docked lead compounds with both proteins in terms of Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis are calculated, which are found as -8.79 and -3.97 kcal.mol−1 for Mpro-L32 and Nsp9-L8 complexes, respectively. The pharmacokinetic analysis of the lead compounds are also performed to disclose their ADME (absorption, distribution, metabolism, and excretion) and toxic character using online server pkCSM. This allowed for a comprehensive understanding of how these compounds would behave in the organism, specifically focusing on their ADME properties. We believe that the current study can evoke the interest of scientific community by providing fundamental insights, which will ultimately lead in-vivo and in-vitro analysis to assess the studied phenolic therapeutic inhibitors against the SARS-CoV-2.