Molecular Dynamics Simulation Approach Research Articles

Identification of Potential Inhibitors of Histone Deacetylase 6 Through Virtual Screening and Molecular Dynamics Simulation Approach: Implications in Neurodegenerative Diseases

Background: Histone deacetylase 6 (HDAC6) plays a crucial role in neurological, inflammatory, and other diseases; thus, it has emerged as an important target for therapeutic intervention. To date, there are no FDA-approved HDAC6-targeting drugs, and most pipeline candidates suffer from poor target engagement, inadequate brain penetration, and low tolerability. There are a few HDAC6 clinical candidates for the treatment of mostly non-CNS cancers as their pharmacokinetic liabilities exclude them from targeting HDAC6-implicated neurological diseases, urging development to address these challenges. They also demonstrate off-target toxicity due to limited selectivity, leading to adverse effects in patients. Selective inhibitors have thus been the focus of development over the past decade, though no selective and potent HDAC6 inhibitor has yet been approved. Methods: This study involved an integrated virtual screening against HDAC6 using the DrugBank database to identify repurposed drugs capable of inhibiting HDAC6 activity. The primary assessment involved the determination of the ability of molecules to bind with HDAC6. Subsequently, interaction analyses and 500 ns molecular dynamics (MD) simulations followed by essential dynamics were carried out to study the conformational flexibility and stability of HDAC6 in the presence of the screened molecules, i.e., penfluridol and pimozide. Results: The virtual screening results pinpointed penfluridol and pimozide as potential repurposed drugs against HDAC6 based on their binding efficiency and appropriate drug profiles. The docking results indicate that penfluridol and pimozide share the same binding site as the reference inhibitor with HDAC6. The MD simulation results showed that stable protein–ligand complexes of penfluridol and pimozide with HDAC6 were formed. Additionally, MMPBSA analysis revealed favorable binding free energies for all HDAC6–ligand complexes, confirming the stability of their interactions. Conclusions: The study implies that both penfluridol and pimozide have strong and favorable binding with HDAC6, which supports the idea of repositioning these drugs for the management of neurodegenerative disorders. However, further in-depth studies are needed to explore their efficacy and safety in biological systems.

Exploring phytochemical inhibitors of protein kinase C alpha for therapeutic targeting of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by neurodegeneration linked to amyloid-β (Aβ) plaques and tau protein tangles. Protein kinase C alpha (PKCα) plays a crucial role in modulating amyloid-β protein precursor (AβPP) processing, potentially mitigating AD progression. Consequently, PKCα stands out as a promising target for AD therapy. Despite the identification of numerous inhibitors, the pursuit of more effective and precisely targeted PKCα inhibitors remains crucial. In this study, we employed an integrated virtual screening approach of molecular docking and molecular dynamics (MD) simulations to identify phytochemical inhibitors of PKCα from the IMPPAT database. Molecular docking screening via InstaDock identified compounds with strong binding affinities to PKCα. Subsequent ADMET and PASS analyses filtered out compounds with favorable pharmacokinetic profiles. Interaction analysis using Discovery Studio Visualizer and PyMOL further elucidated binding conformations of selected compounds with PKCα. Top hits underwent 200 ns MD simulations using GROMACS to validate stability of the interactions. Finally, we propose two phytochemicals, Kammogenin and Imperialine, with appreciable drug-likeliness and binding potential with PKCα. Taken together, the findings suggest Kammogenin and Imperialine as potential PKCα inhibitors, highlighting their therapeutic promise for AD after further validation.

Molecular dynamics simulations reveal concentration-dependent blockage of graphene quantum dots to water channel protein openings

Graphene quantum dots (GQDs) have attracted significant attention across various scientific research areas due to their exceptional properties. However, studies on the potential toxicity of GQDs have yielded conflicting results. Therefore, a comprehensive evaluation of the toxicity profile of GQDs is essential for a thorough understanding of their biosafety. In this work, employing a molecular dynamics (MD) simulation approach, we investigate the interactions between GQDs and graphene oxide quantum dots (GOQDs) with the AQP1 water channel protein, aiming to explore the potential biological influence of GQDs/GOQDs. Our MD simulation results reveal that GQDs can adsorb to the loop region around the openings of AQP1 water channels, resulting in the blockage of these channels and potential toxicity. Interestingly, this blockage is concentration-dependent, with higher GQD concentrations leading to a greater likelihood of blockage. Additionally, GOQDs show a lower probability of blocking the openings of AQP1 water channels compared to GQDs, due to the hydrophobicity of the loop regions around the openings, which ultimately leads to lower interaction energy. Therefore, these findings provide new insights into the potential adverse impact of GQDs on AQP1 water channels through the blockage of their openings, offering valuable molecular insights into the toxicity profile of GQD nanomaterials.

Rational design of some 1,3,4 trisubstituted pyrazole-thiazole derivatives to serve as MtInhA inhibitors using QSAR, ADMET, molecular docking, MM-GBSA, and molecular dynamics simulations approach

Using computational approaches, the potential efficacy and specificity of 1,3,4 trisubstituted pyrazole derivatives as MtInhA inhibitors which will aid in rational drug design for tubercular therapy were forecasted. QSARINS software was used to investigate the ability of compound to inhibit MtInhA. Three noteworthy descriptors with significant correlations and impressive statistical values were identified by the produced QSAR model: Correlation of coefficient(R2)= 0.8789, Cross-validation leave one out correlation coefficient (Q2LOO)= 0.8402, Cross-validation leave-many-out correlation coefficient(Q2LMO)=0.7321, Concordance Correlation Coefficient for cross-validation(CCCtr)=0.9355, CCCext =0.888. The descriptor generated by the QSAR model includes Centered Broto-Moreau autocorrelation weighted by Sanderson electronegativities (ATSC1e), Radial distribution functions at 15.0 and 2.0 Å inter-atomic distances weighted by relative van der Waals volumes (RDF150v), Radial distribution function – 145/weighted by relative I-state (RDF145s). Using these, three descriptor model was developed and the designed compounds were evaluated for their MtInhA inhibitory activity. Further, ADMET prediction and Molecular docking studies were carried out using Schrodinger's Software. ADMET prediction were used to evaluate drug likeliness and molecular docking was used to determine the interactions of designed compounds with the target protein. After the docking studies, the compounds were subjected for MM-GBSA calculations and MD simulation. Among the designed compounds, AP2 had the strongest binding affinity towards the MtInhA enzyme. The result of this work helps to understand the key interactions between 1,3,4 trisubstituted pyrazole derivatives and MtInhA protein that may be necessary to develop new lead compounds against tuberculosis.

Probing marine macroalgal phlorotannins as an antibacterial candidate against Salmonella typhi: Molecular docking and dynamics simulation approach

The increasing prevalence of drug-resistant bacterial strains, including multidrug-resistant Salmonella typhi, has raised significant concerns about the effectiveness of traditional antimicrobial treatments. To address this issue, the study employed computational techniques to evaluate the potential of natural phlorotannins derived from marine algae as alternative antibacterial agents against S. typhi. A total of 104 phlorotannins were retrieved from PubChem and subjected to molecular docking with three specific target proteins of S. typhi. Among the compounds tested, Compound-10 a derivative of dieckol exhibited the highest affinity for the Omptin family outer membrane protease [pgtE] protein and for the cell invasion protein sipB protein. The docking results revealed strong interactions between the phlorotannins and the target proteins, indicating their potential as antimicrobial agents. Additionally, pharmacokinetic studies using the QikProp module demonstrated that the top-ranked compounds showed favourable drug-like properties with good druggable efficiency, moderate gut-blood barrier transport, and high human oral absorption. Most compounds passed the rule of three and five drug-likeness criteria, indicating their potential as drug candidates. Furthermore, MM-GBSA analysis provided relative binding affinity estimations, ranking the compounds based on their calculated binding energies. These results align reasonably well with experimental binding affinities, reinforcing the potential of the identified compounds as potent binders to their target proteins. This study highlights the promising antibacterial potential of marine phlorotannins against S. typhi. Further in vitro studies are warranted to validate these compounds' efficacy and anti-microbial activity, ultimately paving the way for developing new therapeutic strategies to combat drug-resistant Salmonella infections.

Cryptochrome magnetoreception: time course of photoactivation from non-equilibrium coarse-grained molecular dynamics

Magnetoreception, the ability to sense magnetic fields, is widespread in animals but remains poorly understood. The leading model links this ability in migratory birds to the photo-activation of the protein cryptochrome. Magnetic information is thought to induce structural changes in cryptochrome via a transient radical pair intermediate. This signal transduction pathway has been the subject of previous all-atom molecular dynamics (MD) simulations, but insights were limited to short timescales and equilibrium structures. To address this, we developed a non-equilibrium coarse-grained MD simulation approach, exploring cryptochrome’s photo-reduction over 20 replicates of 20 µs each. Our results revealed significant structural changes across the protein, with an overall time constant of 3 µs. The C-terminal (CT) region responded on a timescale of 4.7 µs, followed by the EEE-motif, while the phosphate binding loop (PBL) showed slower dynamics (9 µs). Network analysis highlighted direct pathways connecting the tryptophan tetrad to the CT, and distant pathways involving the EEE and PBL regions. The CT-dynamics are significantly impacted by a rearrangement of tryptophan residues in the central electron transfer chain. Our findings underscore the importance of considering longer timescales when studying cryptochrome magnetoreception and highlight the potential of non-equilibrium coarse-grained MD simulations as a powerful tool to unravel protein photoactivation reactions.

Repurposed pharmacotherapy: targeting cathepsin L with repurposed drugs in virtual screening.

Proteolytic enzymes are closely associated with cancer and are important in different phases, including tumor growth, angiogenesis, and metastasis. Despite efforts to target matrix metalloproteases (MMPs), clinical trials have often resulted in various side effects such as musculoskeletal pain, joint stiffness, and tendinitis, making them less optimal for chronic cancer treatment. Thus, there is a need for the identification of other protease targets that would provide different approaches towards the management of cancer. Of these targets, Cathepsin L (CatL) is a lysosomal cysteine protease that has been identified as a therapeutic target that is implicated in cancer development and metastasis. In this study, we performed an integrated approach of virtual screening and molecular dynamics (MD) simulations to identify the potential inhibitors of CatL from a library of drugs that have been used for different treatments. Towards this goal, we performed virtual screening of the DrugBank database and found two repurposed drugs, Irinotecan and Nilotinib, against CatL based on their docking profiles, favorable docking scores, and specific interaction with the CatL binding pocket. MD simulations of the Irinotecan and Nilotinib bound structures with CatL were carried out, and the analysis showed that both these compounds could function as CatL inhibitors as the protein-ligand interactions were stable for 300 ns. This study highlights the robustness of these drugs bound to CatL and indicates that they could be repurposed for the treatment of cancer. These findings endorse the use of computer-based approaches for the identification of new inhibitors, and the present study will be a useful resource for future experimental research towards the targeting of CatL in cancer therapeutics.

Molecular Dynamic Simulations of the Physical Properties of Four Ionic Liquids

In this study, the molecular structure models of four ionic liquids were created, the reverse nonequilibrium molecular dynamics simulation (RNEMD) approach was used to predict their densities and viscosities, and their thermal conductivity was simulated using the non-equilibrium molecular dynamic simulation method (NEMD). The calculated results of ionic liquid densities were compared with the data in the literature; most of the variances are around 2.5%, and the maximum relative deviation was less than 6.27%; viscosity values were compared with the experimental data, with a maximum relative deviation of −8.96% and a minimum relative deviation of −2.72%. The simulated thermal conductivity has a good linear relationship with respect to temperature and pressure, which is in good agreement. This study provides a reference for molecular dynamics simulation to measure the physical properties of ionic liquids, which is important for the development of ionic liquids.

Exploring the therapeutic mechanisms of millet in obesity through molecular docking, pharmacokinetics, and dynamic simulation.

Obesity, a prevalent global health concern, is characterized by excessive fat accumulation, which confers significant nutritional and health risks, including a shortened lifespan and diminished wellbeing. Central to the regulation of energy balance and food intake is the fat mass and obesity-associated (FTO) protein, which modulates the interplay between caloric consumption and energy expenditure. Given its pivotal role in obesity regulation, the identification of effective inhibitors targeting the FTO protein is imperative for developing therapeutic interventions. Currently available anti-obesity drugs are often plagued by undesirable side effects. In contrast, natural plant-derived bioactive compounds are gaining prominence in the pharmaceutical industry due to their efficacy and lower incidence of adverse effects. Little Millet, a traditional cereal known for its rich nutritional profile and high satiety index, was investigated in this study using molecular docking and dynamics simulation approach for its potential as an anti-obesity agent. Our research demonstrates that four bioactive compounds from Little Millet exhibit superior binding energies ranging from 7.22 to 8.83 kcal/mol, compared to the standard anti-obesity drug, orlistat, which has a binding energy of 5.96 kcal/mol. These compounds fulfilled all drug-like criteria, including the Lipinski, Ghose, Veber, Egan, and Muegge rules, and exhibited favorable profiles in terms of distribution, metabolism, and prolonged half-life without toxicity. Conversely, orlistat was associated with hepatotoxicity, a reduced half-life, and multiple violations of drug-likeness parameters, undermining its efficacy. Molecular dynamics simulations and Gibbs free energy assessments revealed that the four identified compounds maintain stable interactions with key residues in the FTO protein's active site. We propose further validation through extensive In vitro, In vivo, and clinical studies to ascertain the therapeutic potential of these compounds in combating obesity.

Thermal Conductivity Enhancement of Doped Magnesium Hydroxide for Medium-Temperature Heat Storage: A Molecular Dynamics Approach and Experimental Validation.

Magnesium hydroxide, Mg(OH)2, is recognized as a promising material for medium-temperature heat storage, but its low thermal conductivity limits its full potential application. In this study, thermal enhancement of a developed magnesium hydroxide-potassium nitrate (Mg(OH)2-KNO3) material was carried out with aluminum oxide (Al2O3) nanomaterials. The theoretical results obtained through a molecular dynamics (MD) simulation approach showed an enhancement of about 12.9% in thermal conductivity with an optimal 15 wt% of Al2O3. There was also close agreement with the experimental results within an error of ≤10%, thus confirming the reliability of the theoretical approach and the potential of the developed Mg(OH)2-KNO3 as a medium heat storage material. Further investigation is, however, encouraged to establish the long-term recyclability of the material towards achieving a more efficient energy storage process.

Engineering affinity of humanized ScFv targeting CD147 antibody: A combined approach of mCSM-AB2 and molecular dynamics simulations

This study aims to assess the effectiveness of mCSM-AB2, a graph-based signature machine learning method, for affinity engineering of the humanized single-chain Fv anti-CD147 (HuScFvM6-1B9). In parallel, molecular dynamics (MD) simulations were used to gain valuable insights into the dynamics and affinity of the HuScFvM6-1B9-CD147 complex. The result analysis involved integrating free energy changes calculated from the mCSM-AB2 with binding free energy predictions from MD simulations. The simulated structures of the modified HuScFvM6-1B9-CD147 domain 1 complex from MD simulations were used to highlight critical residues participating in the binding surface. Interestingly, alterations in the pattern of amino acids of HuScFvM6-1B9 at the complementarity determining regions interacting with the 31EDLGS35 epitope were observed, particularly in mutants that lost binding activity. The predicted mutants of HuScFvM6-1B9 were subsequently engineered and expressed in E. coli for subsequent binding property validation. Compared to WT HuScFvM6-1B9, the mutant HuScFvM6-1B9L1:N32Y exhibited a 1.66-fold increase in binding affinity, with a KD of 1.75 × 10−8 M. While mCSM-AB2 demonstrates insignificant improvement in predicting binding affinity enhancements, it excels at predicting negative effects, aligning well with experimental validation. In addition to binding free energies, total entropy was considered to explain the discrepancy between mCSM-AB2 predictions and experimental results. This study provides guidelines and identifies the limitations of mCSM-AB2 and MD simulations in antibody engineering.

In-depth exploration of the interface mechanism of aqueous ammonium-ion batteries with ionic liquids

Aqueous ammonium-ion batteries have emerged as a research focus in recent years because of their distinctive advantages. Nevertheless, issues such as the side reaction of water, electrode element dissolution and others have an impact on their stability. The experimental findings demonstrate that the system incorporating ionic liquids (ILs) exhibits gratifying electrochemical performance. The Molecular Dynamics (MD) simulation approach was employed to investigate the alterations of NH4Cl aqueous batteries prior to and subsequent to the addition of imidazolium ionic liquids (ILs), with a focus on the impact on the anode's interface. It is found that the addition of ILs can reduce the interfacial water’s content at low charge. Interestingly, in the case of high charge, the water content at the interface didn’t decrease; instead, it increased. This phenomenon is associated with the initial increase followed by a decrease in the number of ionic liquid (IL) cations. Three conformations for IL cations were found near the interface, which are “parallel”, “slant” and “vertical”, and the proportion of the three had a certain influence on the content of interfacial water. The "parallel" configuration is more effective in reducing the interfacial water content, establishing it as the dominant conformation. The findings reported above will offer new theoretical support for the design and modification of aqueous ammonium ion electrolytes.

Identification of Peptidoglycan Glycosyltransferase FtsI as a Potential Drug Target against Salmonella Enteritidis and Salmonella Typhimurium Serovars Through Subtractive Genomics, Molecular Docking and Molecular Dynamics Simulation Approaches.

Salmonella enterica serovar Enteritidis and Salmonella enterica serovar Typhimurium are among the main causative agents of nontyphoidal Salmonella infections, imposing a significant global health burden. The emergence of antibiotic resistance in these pathogens underscores the need for innovative therapeutic strategies. To identify proteins as potential drug targets against Salmonella Enteritidis and Salmonella Typhimurium serovars using In silico approaches. In this study, a subtractive genomics approach was employed to identify potential drug targets. The whole proteome of Salmonella enteritidis PT4 and Salmonella typhimurium (D23580), containing 393 and 478 proteins, respectively, was analyzed through subtractive genomics to identify human homologous proteins of the pathogen and also the proteins linked to shared metabolic pathways of pathogen and its host. Subsequent analysis revealed 19 common essential proteins shared by both strains. To ensure hostspecificity, we identified 10 non-homologous proteins absent in humans. Among these proteins, peptidoglycan glycosyltransferase FtsI was pivotal, participating in pathogen-specific pathways and making it a promising drug target. Molecular docking highlighted two potential compounds, Balsamenonon A and 3,3',4',7-Tetrahydroxyflavylium, with strong binding affinities with FtsI. A 100 ns molecular dynamics simulation having 10,000 frames substantiated the strong binding affinity and demonstrated the enduring stability of the predicted compounds at the docked site. The findings in this study provide the foundation for drug development strategies against Salmonella infections, which can contribute to the prospective development of natural and cost-effective drugs targeting Salmonella Enteritidis and Salmonella Typhimurium.

Searching for potential acetylcholinesterase inhibitors: a combined approach of multi-step similarity search, machine learning and molecular dynamics simulations.

Targeting acetylcholinesterase is one of the most important strategies for developing therapeutics against Alzheimer's disease. In this work, we have employed a new approach that combines machine learning models, a multi-step similarity search of the PubChem library and molecular dynamics simulations to investigate potential inhibitors for acetylcholinesterase. Our search strategy has been shown to significantly enrich the set of compounds with strong predicted binding affinity to acetylcholinesterase. Both machine learning prediction and binding free energy calculation, based on linear interaction energy, suggest that the compound CID54414454 would bind strongly to acetylcholinesterase and hence is a promising inhibitor.

Molecular Docking and Dynamic Simulation Approach to Target Penicillin-Binding Protein 1B (LpoB) of Salmonella typhimurium with Flavonoids

Background and Objective: Lipopolysaccharide (LPS) is an essential constituent of the outer membrane of gram-negative bacteria, such as Salmonella typhimurium, and it plays a crucial role by inducing disease in the host. Penicillin-binding protein 1B (LpoB) is a key enzyme in the production of peptidoglycans, making it a potential target for the development of new antimicrobials. Flavonoids are naturally occurring plant-derived chemicals with a wide range of pharmacological properties, including antibacterial capabilities. The goal of this study was to identify the potential flavonoid that inhibits the protein LpoB using computational approaches and compare it with the standard antibiotic ciprofloxacin. Methods: The study was carried out by selecting fifty flavonoids based on Lipinski’s rule of five. Molecular docking was carried out for selected flavonoids and ciprofloxacin against the LpoB protein using AutoDock 4. A 100 nanosecond molecular dynamic simulation was performed for apoprotein, LopB-fisetin, and LpoB-ciprofloxacin complexes, followed by free energy calculation by Molecular Mechanics Generalized Born Surface Area (MMGBSA) solvation analysis. Results: The docking results revealed that fisetin displayed five hydrogen bonds with a binding affinity of -4.67 kcal/mol, and ciprofloxacin exhibited a binding affinity of -4.36 kcal/mol with two hydrogen bonds. The apoprotein and fisetin complex remained stable throughout the 100 ns molecular dynamic simulation, while the ciprofloxacin complex lost its stability. The MMGBSA analysis with fisetin showed better binding free energy compared to ciprofloxacin. Conclusion: The present study has emphasized the potential of flavonoids as probable candidates that can inhibit the protein LpoB. The integration of molecular docking, dynamic simulations, and MMGBSA analysis has provided significant insight into the thermodynamics and binding interactions of the LpoB- fisetin complex, and it has enabled further experimental validations.

Marine Bioactive Molecules as Inhibitors of the Janus Kinases: A Comparative Molecular Docking and Molecular Dynamics Simulation Approach.

A treasure trove of naturally occurring biomolecules can be obtained from sea living organisms to be used as potential antioxidant and anti-inflammatory agents. These bioactive molecules can target signaling molecules involved in the severity of chronic autoimmune diseases such as rheumatoid arthritis (RA). The intracellular tyrosine kinases family, Janus kinases (JAKs, includes JAK1, JAK2, and JAK3), is implicated in the pathogenesis of RA through regulating several cytokines and inflammatory processes. In the present study, we conducted molecular docking and structural analysis investigations to explore the role of a set of bioactive molecules from marine sources that can be used as JAKs' specific inhibitors. Around 200 antioxidants and anti-inflammatory molecules out of thousands of marine molecules found at the Comprehensive Marine Natural Products Database (CMNPD) website, were used in that analysis. The details of the interacting residues were compared to the recent FDA approved inhibitors tofacitinib and baricitinib for data validation. The shortlisted critical amino acids residues of our pharmacophore-based virtual screening were LYS905, GLU957, LEU959, and ASP1003 at JAK1, GLU930 and LEU932 at JAK2, and GLU905 and CYS909 of JAK3. Interestingly, marine biomolecules such as Sargachromanol G, Isopseudopterosin E, Seco-Pseudopterosin, and CID 10071610 showed specific binding and significantly higher binding energy to JAK1 active/potential sites when being compared with the approved inhibitors. In addition, Zoanthoxanthin and Fuscoside E bind to JAK2's critical residues, GLU930 and LEU932. Moreover, Phorbaketal and Fuscoside E appear to be potential candidates that can inhibit JAK3 activity. These results were validated using molecular dynamics simulation for the docked complexes, JAK1(6sm8)/SG, JAK2 (3jy9)/ZAX, and JAK3 (6pjc)/Fuscoside E, where stable and lower binding energy were found based on analyzing set of parameters, discussed below (videos are attached). A promising role of these marine bioactive molecules can be confirmed in prospective preclinical/clinical investigations using rheumatoid arthritis models.

Elucidating the resistance mechanisms and binding pattern of novel Oxa-48-like carbapenemases covalent inhibitors: A hybrid experimental and in silico approach

Klebsiella pneumoniae is a Gram negative bacteria that can cause harm to the public's health and vulnerability has increased due to the emergence of highly virulent strains resistant to carbapenem antibiotics. The K. pneumoniae resistance mechanism involves extended-spectrum beta-lactamases, which are enzymes that can break down a broad range of antibiotics. The particular concern is Class D β-lactamases like OXA-48, which further complicates treatment options for infections caused by K. pneumoniae. The current study screened 7800 samples from three hospitals in Pakistan and found 353 positive samples of K. pneumoniae. The isolates were resistant to SXT, AMP, FEP CTX, CIP, TET, MEM, and IPM, while effective antibiotics were TGC, FOS, FOX, SCF and TZP. The sequencing and mutational analysis of the OXA-48 gene revealed 45-point mutations, including five novel missense mutations (Thr104:Ala104, Asn110:Asp110, Glu168:Gln168, Ser171:Ala171 and Arg214:Ser214). These mutations can contribute to the antibiotic affinity decrease and cause resistance. Furthermore, the study aimed to develop covalent inhibitors of OXA-48 (wild type and mutant) carbapenemases using a combination of molecular docking and molecular dynamic (MD) simulation approaches from natural products from the ZNINC20 database. 10 compounds (ZINC103533306, ZINC103531564, ZINC3861001, ZINC103533375, ZINC12411532, ZINC103533290, ZINC12376465, ZINC85875819, ZINC59586513 and ZINC13370550) showed best fit and high interactions with the OXA-48 active pocket. The binding free energies calculated from the MD showed that these compounds have high affinity with both the wild type and mutated OXA-48 protein. The selected compounds showed good drug-like properties and can be the leading inhibitors to combat the resistant K. pneumoniae strains.

Potential Advantages of Idarubicin-Loaded Trastuzumab-Coated Liposomes for Combating Head and Neck Squamous Cancer Cells.

Head and neck squamous cell carcinoma (HNSCC) with a high mortality rate is among the most common types of cancer in the world. Human epidermal growth factor receptor 2 (HER2) is expressed higher than normal level in the most HNSCC tumors, making them resistant to chemotherapy and radiotherapy. Therefore, HER2 has been introduced as a suitable target for anticancer drugs. The aim of this study is to examine the efficacy of a treatment protocol involving targeted delivery of idarubicin encapsulated in trastuzumab-decorated liposomes to HNSCC cells. In the current experimental study, efficacies of idarubicin, prepared liposomal idarubicin, and constructed immunoliposomal idarubicin (trastuzumab-decorated) were investigated in killing HN5 cells, a HER2- overexpressing HNSCC-originating cell line. Liposomal content of idarubicin and trastuzumab were qualified by UVVisible spectroscopy and preparations were characterized for shape and size by atomic force microscopy (AFM) and dynamic light scattering (DLS). To clarify role of the missing parts of the available crystal structure (PDB ID: 1n8z) within trastuzumab-HER2 interactions, we used a 40 ns molecular dynamic simulation approach. Based on the obtained results, liposomal idarubicin showed higher toxicity of the encapsulated drug on HN5 cells compared to the traditional free drug formulations. The immunoliposomal form of idarubicin was more effective than the liposomal formulation, in killing of HN5 cells. In addition, simulation of interactions between trastuzumab and HER2 revealed that the missing parts (in the crystal structure) of HER2 have critical interaction with trastuzumab, through salt-bridges and hydrogen bonds. It seems that the prepared immunoliposomes could attach more efficiently to HER2 overexpressing cells, which consequently leads to increasing cellular uptake of idarubicin through a receptor-mediated endocytosis mechanism. Moreover, simulation of the interaction between HER2 and trastuzumab suggested considerable possibilities for increasing trastuzumab affinity to HER2.

Pharmacophore-Based Study: An In Silico Perspective for the Identification of Potential New Delhi Metallo-β-lactamase-1 (NDM-1) Inhibitors.

In the ongoing battle against antibiotic-resistant bacteria, New Delhi metallo-β-lactamase-1 (NDM-1) has emerged as a significant therapeutic challenge due to its ability to confer resistance to a broad range of β-lactam antibiotics. This study presents a pharmacophore-based virtual screening, docking, and molecular dynamics simulation approach for the identification of potential inhibitors targeting NDM-1, a critical enzyme associated with antibiotic resistance. Through the generation of a pharmacophore model and subsequent virtual screening of compound libraries, candidate molecules (ZINC29142850 (Z1), ZINC78607001 (Z2), and ZINC94303138 (Z3)) were prioritized based on their similarity to known NDM-1 binder (hydrolyzed oxacillin (0WO)). Molecular docking studies further elucidated the binding modes and affinities of the selected compounds towards the active site of NDM-1. These compounds demonstrated superior binding affinities to the enzyme compared to a control compound (-7.30 kcal/mol), with binding scores of -7.13, -7.92, and -8.10 kcal/mol, respectively. Binding interactions within NDM-1's active site showed significant interactions with critical residues such as His250, Asn220, and Trp93 for these compounds. Subsequent molecular dynamics simulations were conducted to assess the stability of the ligand-enzyme complexes, showing low root mean square deviation (RMSD) values between 0.5 and 0.7 nm for Z1, Z2, which indicate high stability. Z2's compactness in principal component analysis (PCA) suggests that it can stabilize particular protein conformations more efficiently. Z2 displays a very cohesive landscape with a notable deep basin, suggesting a very persistent conformational state induced by the ligand, indicating robust binding and perhaps efficient inhibition. Z2 demonstrates the highest binding affinity among the examined compounds with a binding free energy of -25.68 kcal/mol, suggesting that it could offer effective inhibition of NDM-1. This study highlights the efficacy of computational tools in identifying novel antimicrobial agents against resistant bacteria, accelerating drug discovery processes.

Molecular docking and molecular dynamics study of 3-hydroxybutyrate with polymers for diabetic ketoacidosis-targeted molecularly imprinted polymers

Context: Molecularly imprinted polymers (MIPs) are promising materials with tailored binding sites that can selectively recognize and bind target molecules. The combined approach of molecular docking and molecular dynamics (MD) simulation provides valuable insights into the interactions between 3-hydroxybutyrate (3HB) and the designed MIPs, shedding light on the intricate details of their binding mechanisms. This information is crucial for designing MIPs with high selectivity and affinity for 3HB, which is a key biomarker of diabetic ketoacidosis (DKA). Aims: To examine the interactions and dynamic behavior of 3HB in a complex with ten polymers by employing molecular docking and MD simulations. Methods: Initially, molecular docking was employed to predict the binding orientations and affinities of the 3HB molecule within the active sites of the polymers. Subsequently, molecular dynamics simulation was utilized to explore the dynamic behavior, stability, and interactions within these complexes for 100 ns. Metabolic and toxicological properties of 3HB using SwissADME were also predicted. Results: N-(hydroxymethyl)acrylamide (NHMAm), hydroxyethyl methacrylate (HEMA), itaconic acid (ITA), and N-[tris(hydroxymethyl)methyl]acrylamide (TrisNHMAm) displayed the strongest interactions with 3HB, with binding affinities of -2.64, 2.523, 2.469, and 2.305 kcal/mol, respectively. Various kinds of molecular interactions influence ligand-polymer binding in a variety of ways, as illustrated by the four polymers with the lowest binding affinities. In molecular dynamics, 4-vinylpyridine (4VP), N,N-dimethylacylamide (DMAm), N-(hydroxyethyl)acrylamide (NHEAm), and hydroxyethyl methacrylate (HEMA) suggest a strong stable complex with 3HB with an overall ΔTOTAL of -0.56, -0.35, -0.32, and -0.27 kcal/mol, respectively. The ADME prediction indicated that 3HB has favorable pharmacokinetic properties. Conclusions: HEMA shows the ability to interact well with 3HB both by molecular docking and molecular dynamics.