Molecular simulation of N-acetylneuraminic acid analogs and molecular dynamics studies of cholera toxin-Neu5Gc complex

Advancements in nanobody generation: Integrating conventional, in silico, and machine learning approaches

Nanobodies, derived from camelids and sharks, offer compact, single-variable heavy-chain antibodies with diverse biomedical potential. This review explores their generation methods, including display techniques on phages, yeast, or bacteria, and computational methodologies. Integrating experimental and computational approaches enhances understanding of nanobody structure and function. Future trends involve leveraging next-generation sequencing, machine learning, and artificial intelligence for efficient candidate selection and predictive modeling. The convergence of traditional and computational methods promises revolutionary advancements in precision biomedical applications such as targeted drug delivery and diagnostics. Embracing these technologies accelerates nanobody development, driving transformative breakthroughs in biomedicine and paving the way for precision medicine and biomedical innovation.

Decrypting the multi-genome data for chimeric vaccine designing against the antibiotic resistant Yersinia pestis

Yersinia pestis, the causative agent of plague, is a gram-negative bacterium that can be fatal if not treated properly. Three types of plague are currently known: bubonic, septicemic, and pneumonic plague, among which the fatality rate of septicemic and pneumonic plague is very high. Bubonic plague can be treated, but only if antibiotics are used at the initial stage of the infection. But unfortunately, Y. pestis has also shown resistance to certain antibiotics such as kanamycin, minocycline, tetracycline, streptomycin, sulfonamides, spectinomycin, and chloramphenicol. Despite tremendous progress in vaccine development against Y. pestis, there is no proper FDA-approved vaccine available to protect people from its infections. Therefore, effective broad-spectrum vaccine development against Y. pestis is indispensable. In this study, vaccinomics-assisted immunoinformatics techniques were used to find possible vaccine candidates by utilizing the core proteome prepared from 58 complete genomes of Y. pestis. Human non-homologous, pathogen-essential, virulent, and extracellular and membrane proteins are potential vaccine targets. Two antigenic proteins were prioritized for the prediction of lead epitopes by utilizing reverse vaccinology approaches. Four vaccine designs were formulated using the selected B- and T-cell epitopes coupled with appropriate linkers and adjuvant sequences capable of inducing potent immune responses. The HLA allele population coverage of the T-cell epitopes selected for vaccine construction was also analyzed. The V2 constructs were top-ranked and selected for further analysis on the basis of immunological, physicochemical, and immune-receptor docking interactions and scores. Docking and molecular dynamic simulations confirmed the stability of construct V2 interactions with the host immune receptors. Immune simulation analysis anticipated the strong immune profile of the prioritized construct. In silico restriction cloning ensured the feasible cloning ability of the V2 construct in the expression system of E. coli strain K12. It is anticipated that the designed vaccine construct may be safe, effective, and able to elicit strong immune responses against Y. pestis infections and may, therefore, merit investigation using in vitro and in vivo assays.

Identification of potential focal adhesion kinase (FAK) inhibitors: a molecular modeling approach

Focal adhesion kinase (FAK) is an enzyme of paramount importance as it is involved in several critical roles, which are linked to proliferation of cancer cells. FAK is quintessential for cancer cell mitigation, adhesion and survival, downregulation of which interferes with the growth of cancer cells. The expression of FAK is elevated in breast cancer, hepatocellular carcinomas, neuroblastoma cells, demonstrating the need for FAK inhibitors as a potential treatment. Based on an in silico drug screen, the study aimed to identify potential FAK inhibitors. 3180 molecules retrieved from the Zinc database comprising biogenic molecules, FDA-approved drugs and compounds in clinical trials were screened against the FAK enzyme (PDB:2ETM). The XP docking study of the best 51 ligands revealed that ZINC02033589 (Silymarin) showed good binding to FAK with -10.97 kcal/mol dock score followed by ZINC00518397 with -8.23 kcal/mol and ZINC03831112 - 8.07 kcal/mol. The interactions of the top three ligands with FAK were further validated by molecular dynamic simulation study of 100 ns and MM-GBSA calculations. The ΔG of binding of ZINC02033589, ZINC00518397 and ZINC03831112 was found to be -59.09, -45.08 and -48.53 kcal/mol respectively. The study established the fact that among the three molecules, ZINC02033589 showed good stability and binding towards FAK. These results could usher in the development of potential FAK inhibitor entities, that could be persuaded and substantiated by the molecules identified in this study for subsequent synthetic and bioactivity research studies.Communicated by Ramaswamy H. Sarma.

Immunoinformatics study to explore dengue (DENV-1) proteome to design multi-epitope vaccine construct by using CD4+ epitopes

BACKGROUND

Immunoinformatics is an emerging interdisciplinary field which integrates immunology, bioinformatics, and computational biology to study the immune system. In this study, we apply immunoinformatics approaches to explore the dengue proteome in order to design a multi-epitope vaccine construct.

METHODS

We used existing databases and algorithms to predict potential epitopes on dengue proteins and used a bioinformatics approach to identify the most promising epitopes. We then used molecular modelling to develop a multi-epitope construct which could be used as a potential vaccine. The results of this study demonstrate that immunoinformatics is a powerful tool for exploring and designing potential vaccines for infectious diseases like dengue.

RESULTS

Here, we found four CD4+ epitopes NLKYSVIVTVHTGDQ, ANPIVTDKEKPVNIE, LDPVVYDAKFEKQL, and VGAIALDFKPGTSGS that were used to design vaccine construct. The vaccine construct docked with TLR5. RMSD values suggest that docked complex of TLR5 and vaccine construct have putative stable interaction to induce immunogenic effects on host.

CONCLUSIONS

Furthermore, our study provides a proof of concept for the use of immunoinformatics approaches in DENV vaccine design. This vaccine can be effective in treating patients infected with DENV virus.

Computational Study of Bis-(1-(Benzoyl)-3-Methyl Thiourea) Platinum (II) Complex Derivatives as Anticancer Candidates

Background

The increasing incidence of cancer every year has resulted in cancer becoming one of the most common causes of death in the world. The most common types of cancer are breast cancer, lung cancer and prostate cancer. Thiourea is one of the compounds that have anticancer effects, and its activity can be increased by structural modifications, one of which involves making a Bis-(1-(benzoyl)-3-methyl thiourea) platinum (II) metal complex.

Purpose

This study aims to obtain platinum (II)-thiourea complex compounds that have a more stable interaction as an anticancer agent compared to cisplatin.

Methods

The methods used are computational studies with molecular docking, simulation of molecular dynamics, and prediction of pharmacokinetics and toxicity.

Results

Based on the molecular docking of the platinum (II)-thiourea complex which has the most stable interaction with lower binding energy than the native ligand and the cisplatin, namely Bis-(3-methyl-1-(naphthalene-2-carbonyl)thiourea)) Platinum (II) against breast cancer receptors (3ERT) and lung cancer (2ITO) and compounds Bis-(1-(3-chlorobenzoyl)-3-methylthiourea) Platinum (II) against prostate cancer receptors (1Z95). The evaluation results of the stability of the interaction using a 50 ns molecular dynamic simulation showed that the Bis-(1-benzoyl-3-methylthiourea) Platinum (II) which binds to the prostate cancer receptor (1Z95) has the most stable interaction. Pharmacokinetic prediction results show that the platinum (II)-thiourea complex has a good pharmacokinetic profile, but there are several compounds that are mutagenic and hepatotoxic.

Conclusion

The Bis-(1-(3,4-dichlorobenzoyl)-3-methyl thiourea) platinum (II) compounds could be a suitable anticancer agent for the lungs.

Significance of D- tryptophan in Contryphan-Ar1131 Conus peptide: Oxidative folding, trypsin binding, and photostabilization activity

Distinct differences have been observed between L-tryptophan and D-tryptophan containing contryphan-Ar1131 in oxidative folding, trypsin binding, and photostabilization activity on avobenzone. [W⁵] contryphan-Ar1131 and [w⁵] contryphan-Ar1131 were chemically synthesized and characterized using RP-HPLC and mass spectrometry. Structural differences due to the change of configuration of tryptophan were evident from the optimized structures of contryphan-Ar1131 using density functional theory (DFT). The comparison of early events of oxidative folding has revealed the role of D-tryptophan in accelerating the formation of a disulfide bond. The optimized structures of the reduced form of peptides revealed the occurrence of aromatic-aromatic and aromatic-proline interactions in [w⁵] contryphan-Ar1131 which may be critical in aiding the oxidative folding reaction. The presence of the Lys6-Pro7 peptide bond indicates that contryphan-Ar1131 is resistant but may bind to trypsin allowing to assign the binding affinity of peptides to the protein surface. Competitive binding studies and molecular docking along with molecular dynamic (MD) simulations have revealed that [w⁵] contryphan-Ar1131 has more affinity for the active site of trypsin. Given tryptophan is a photostabilizer of FDA-approved chemical UV-A filter avobenzone, the report has compared the photostabilization activity of [W⁵]/ [w⁵] contryphan-Ar1131 on avobenzone under natural sunlight. [w⁵] contryphan-Ar1131 has better photostabilization activity than that of [W⁵] contryphan-Ar1131 and also individual D-tryptophan and L-tryptophan amino acids. These biochemical studies have highlighted the significance of D-tryptophan in contryphan-Ar1131 and its photostabilization activity on avobenzone may find applications in cosmetics.

Potential Therapeutic Candidates against Chlamydia pneumonia Discovered and Developed In Silico Using Core Proteomics and Molecular Docking and Simulation-Based Approaches

Chlamydia pneumonia, a species of the family Chlamydiacea, is a leading cause of pneumonia. Failure to eradicate C. pneumoniae can lead to chronic infection, which is why it is also considered responsible for chronic inflammatory disorders such as asthma, arthritis, etc. There is an urgent need to tackle the major concerns arising due to persistent infections caused by C. pneumoniae as no FDA-approved drug is available against this chronic infection. In the present study, an approach named subtractive proteomics was employed to the core proteomes of five strains of C. pneumonia using various bioinformatic tools, servers, and software. However, 958 non-redundant proteins were predicted from the 4754 core proteins of the core proteome. BLASTp was used to analyze the non-redundant genes against the proteome of humans, and the number of potential genes was reduced to 681. Furthermore, based on subcellular localization prediction, 313 proteins with cytoplasmic localization were selected for metabolic pathway analysis. Upon subsequent analysis, only three cytoplasmic proteins, namely 30S ribosomal protein S4, 4-hydroxybenzoate decarboxylase subunit C, and oligopeptide binding protein, were identified, which have the potential to be novel drug target candidates. The Swiss Model server was used to predict the target proteins’ three-dimensional (3D) structure. The molecular docking technique was employed using MOE software for the virtual screening of a library of 15,000 phytochemicals against the interacting residues of the target proteins. Molecular docking experiments were also evaluated using molecular dynamics simulations and the widely used MM-GBSA and MM-PBSA binding free energy techniques. The findings revealed a promising candidate as a novel target against C. pneumonia infections.

Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer

Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.

Computational insight of dexamethasone against potential targets of SARS-CoV-2

The health sector has been on the race to find a potent therapy for coronavirus disease (COVID)-19, a diseases caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Repurposed anti-viral drugs have played a huge role in combating the virus, and most recently, dexamethasone (Dex) have shown its therapeutic activity in severe cases of COVID-19 patients. The study sought to provide insights on the anti-COVID-19 mechanism of Dex at both atomic and molecular level against SARS-CoV-2 targets. Computational methods were employed to predict the binding affinity of Dex to SARS-CoV-2 using the Schrodinger suite (v2020-2). The target molecules and ligand (Dex) were retrieved from PDB and PubChem, respectively. The selected targets were SARS-CoV-2 main protease (Mpro), and host secreted molecules glucocorticoid receptor, and Interleukin-6 (IL-6). Critical analyses such as Protein and ligand preparation, molecular docking, molecular dynamic (MD) simulations, and absorption, distribution, metabolism, excretion (ADME), and toxicity analyses were performed using the targets and the ligand as inputs. Dex showed stronger affinity to its theoretical (glucocorticoid) receptor with a superior docking score of -14.7 and a good binding energy value of -147.48 kcal/mol; while short hydrogen bond distances were observed in both Mpro and IL-6 when compared to glucocorticoid receptor. Based on these findings, Dex-target complexes were used to perform MD simulations to analyze Dex stability at 50 ns. This study demonstrates that Dex could bind to both the viral and host receptors as a potential drug candidate for COVID-19. To ascertain the biological fitness of this study, other SARS-CoV-2 targets should be explored. Also, the in vitro studies of dexamethasone against several SARS-CoV-2 targets warrant further investigation.Communicated by Ramaswamy H. Sarma.

Screening of phytoconstituents of Andrographis paniculata against various targets of Japanese encephalitis virus: An in-silico and in-vitro target-based approach

Japanese encephalitis (JE) is one of the viral diseases affecting millions of peoples across the globe specifically developing countries. There is no specific treatment available, however, vaccines are available for its prevention. Unfortunately, available vaccines are not effective against all clinical isolates and are also associated with neurological complications in some individuals. We have screened the selected phytoconstituents of Andrographis paniculata against various targets of Japanese encephalitis virus (JEV) using Schrodinger suite 2019-3. Among all selected phytoconstituents, andrographolide has shown a good binding affinity towards NS3 protease as compared to NS3 helicase and NS5 Rdrp (RNA dependent RNA polymerase) of JEV. The molecular dynamics (MD) results have also shown good stability of andrographolide in the active site of NS3 protease. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis has also indicated a good pharmacokinetic and safety profile of andrographolide. Finally, the in-vitro target-based assay have confirmed the inhibitory potential of andrographolide against the NS3 protease of JEV. In conclusion, andrographolide could have the potential to develop as an antiviral agent against JEV through inhibition of protease, however, further investigations are required.

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Andrographolide has shown stable binding conformation in the active site of protease of JEV.

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The protease of JEV was inhibited in a concentration dependent manner.

Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host-pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1-4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2 show that these candidate vaccines perfectly fit into the binding domains of the receptors. In addition, DV-1 has a better binding energies of - 60.07, - 63.40, - 69.89 kcal/mol against MHC-1, TLR-2, and TLR-4, with respect to the other vaccines. All the designed vaccines were highly antigenic, soluble, non-allergenic, non-toxic, flexible, and topologically assessable. The immune simulation analysis showed that DV-1 may elicit specific immune response against dengue virus. Moreover, codon optimization and in silico cloning validated the expressions of all the designed vaccines in E. coli. Finally, the molecular dynamic study shows that DV-1 is stable with minimum RMSF against TLR4. Immunoinformatics tools are now applied to screen genomes of interest for possible vaccine target. The designed vaccine candidates may be further experimentally investigated as potential vaccines capable of providing definitive preventive measure against dengue virus infection.

Screening Balanites aegyptiaca for inhibitors against putative drug targets in Microsporum gypseum - Subtractive proteome, docking and simulation approach

Microsporum gypseum is a keratinophilic fungi grouped under dermatophytes infecting skin, hair and nail portions in human and animals causing tinea corporis, tinea facei and tinea capitis. As both human and fungi are eukaryotes, the available drugs for treating dermatophytes produce some side effects due to drug interaction with human also. Apart from this, the gut microbiota has a very big role in the health of human which should not be affected by the drugs. Hence this study focused on finding a target which is unique and essential to M. gypseum and non-homologous to human and gut microbiota, non-homologous to human domain architecture, highly interacting with other proteins, sub-cellular localization of proteins and non-druggability analysis of the targets using subtractive proteomics approach which resulted with 3 novel drug targets from M. gypseum which were modeled using I-TASSER, refined by ModRefiner and validated by PROCHECK. Further these targets were docked with compounds identified through LC-MS of fractioned methanol extract of B. aegyptiaca fruit pulp using Glide module and the stability of the docked complex was analyzed by molecular dynamics simulation using Desmond module of Schrodinger. Cyanidin-3-O-rhamnoside had better interaction with all the targets and Taurocholic acid had better result with ECCP which suggests the multi-targeting potency of these two compounds against M. gypseum which has to be confirmed by in vitro and in vivo studies.

A computational prospective on isoform-selective CB2 inhibitors

The strategy of enlarging the molecular size, increasing hydrogen bond interactions with the key residues of CB2, and furthering geometric distribution of hydrophobic groups would improve the selectivity towards CB2 receptor.

Investigating Conformational Dynamics of Lewis Y Oligosaccharides and Elucidating Blood Group Dependency of Cholera Using Molecular Dynamics

Cholera is caused by Vibrio cholerae and is an example of a blood-group-dependent disease. Recent studies suggest that the receptor-binding B subunit of the cholera toxin (CT) binds histo-blood group antigens at a secondary binding site. Herein, we studied the conformational dynamics of Lewis Y (Le^Y) oligosaccharides, H-tetrasaccharides and A-pentasaccharides, in aqueous solution by conducting accelerated molecular dynamics (aMD) simulations. The flexible nature of both oligosaccharides was displayed in aMD simulations. Furthermore, aMD simulations revealed that for both oligosaccharides in the free form, ⁴C₁ and ¹C₄ puckers were sampled for all but GalNAc monosaccharides, while either the ⁴C₁ (GlcNAc, Gal, GalNAc) or ¹C₄ (Fuc2, Fuc3) pucker was sampled in the CT-bound forms. In aMD, the complete transition from the ⁴C₁ to ¹C₄ pucker was sampled for GlcNAc and Gal in both oligosaccharides. Further, we have observed a transition from the open to closed conformer in the case of A-pentasaccharide, while H-tetrasaccharide remains in the open conformation throughout the simulation. Both oligosaccharides adopted an open conformation in the CT binding site. Moreover, we have investigated the molecular basis of recognition of Le^Y oligosaccharides by the B subunit of the cholera toxin of classical and El Tor biotypes using the molecular mechanics generalized Born surface area (MM/GBSA) scheme. The O blood group determinant, H-tetrasaccharide, exhibits a stronger affinity to both biotypes compared to the A blood group determinant, A-pentasaccharide, which agrees with the experimental data. The difference in binding free energy between O and A blood group determinants mainly arises due to the increased entropic cost and desolvation energy in the case of A-pentasaccharide compared to that of H-tetrasaccharide. Our study also reveals that the terminal Fuc3 contributes most to the binding free energy compared to other carbohydrate residues as it forms multiple hydrogen bonds with CT. Overall, our study might help in designing glycomimetic drugs targeting the cholera toxin.

Theoretical Studies on the Electronic Structure Parameters and Reactive Activity of Neu5Gc and Neu5Ac under Food Processing Solvent Environment

The animal product hazard factor N-glycolylneuraminic (Neu5Gc) and brain nutrient substance N-acetylneuraminic acid (Neu5Ac) were studied at the M062X/6-311 + G(d,p) geometry optimization level. We considered the electronic structure parameters with different solvents: (benzene ε = 2.27, acetic acid ε = 6.25, ethanol ε = 24.85, lactic acid ε = 22.00, formic acid ε = 51.1, water ε = 78.35). The maximum molecular surface electrostatic potentials, which were 62.77 for Neu5Gc and 60.90 kcal/mol for Neu5Ac, are both located on the carboxyl group hydrogen. The orbital analysis showed that the amide group and carboxyl group confer the sites with susceptibility to nucleophilic and electrophilic attack, respectively. The solvent effect showed that polar solvents, such as formic acid and water, can enhance the two molecules’ nucleophilic activity. To better understand the roles of the hydroxyl group in the two molecules, the independent gradient model theory confirmed the four intramolecular hydrogen bonds of Neu5Gc at gas phase, whereas Neu5Ac only has two. The lowest bond dissociation energy in solvent occurs at O7-H, which is 104.03 kcal/mol in water for Neu5Gc and 104.57 kcal/mol in lactic acid for Neu5Ac. The lowest proton affinity value for Neu5Gc (20.34 kcal/mol) and Neu5Ac (20.76 kcal/mol) was both occur at the carboxyl group O6-H under ethanol. The antioxidant mechanisms of the two sialic acid are prone to sequential proton-loss electron transfer under polar or non-polar solvents.

Design, sythesis and evaluation of a series of 3- or 4-alkoxy substituted phenoxy derivatives as PPARs agonists

Peroxisome proliferators-activated receptors (PPARα, γ and δ) are potentially effective targets for Type 2 diabetes mellitus therapy. The severe effects of known glitazones and the successfully approved agents (saroglitazar and lobeglitazone) motivated us to study novelly potent PPARs drugs with improved safety profile. In this work, we received 15 carboxylic acids based on the combination principle to integrate the polar head of bezafibrate with the hydrophobic tail of pioglitazone. Another 12 tetrazoles based on the bioisosterism principle were obtained accordingly. Furthermore, in vitro PPARs transactivation assays on these 3- or 4-alkoxy substituted phenoxy derivatives afforded six compounds. Interactions and binding stability from the docking analysis and 20 ns molecular dynamic simulations confirmed the representative compounds to be suitable and plausible for PPARs pockets. The above-mentioned results demonstrated that the compounds may be used as reference for further optimization for enhanced PPARs activities and wide safety range.

Novel ligand-based docking; molecular dynamic simulations; and absorption, distribution, metabolism, and excretion approach to analyzing potential acetylcholinesterase inhibitors for Alzheimer's disease

Acetylcholinesterase (AChE) plays an important role in Alzheimer's disease (AD). The excessive activity of AChE causes various neuronal problems, particularly dementia and neuronal cell deaths. Generally, anti-AChE drugs induce some serious neuronal side effects in humans. Therefore, this study sought to identify alternative drug molecules from natural products with fewer side effects than those of conventional drugs for treating AD. To achieve this, we developed computational methods for predicting drug and target binding affinities using the Schrodinger suite. The target and ligand molecules were retrieved from established databases. The target enzyme has 539 amino acid residues in its sequence alignment. Ligand molecules of 20 bioactive molecules were obtained from different kinds of plants, after which we performed critical analyses such as molecular docking; molecular dynamic (MD) simulations; and absorption, distribution, metabolism, and excretion (ADME) analysis. In the docking studies, the natural compound rutin showed a superior docking score of −12.335 with a good binding energy value of −73.313 kcal/mol. Based on these findings, rutin and the target complex was used to perform MD simulations to analyze rutin stability at 30 ns. In conclusion, our study demonstrates that rutin is a superior drug candidate for AD. Therefore, we propose that this molecule is worth further investigation using in vitro studies.

Identification of dual ligands targeting angiotensin II type 1 receptor and peroxisome proliferator-activated receptor-γ by core hopping of telmisartan

It has been reported previously that some angiotensin II receptor blockers not only antagonize angiotensin II type 1 receptor (AT₁R), but also exert stimulation in peroxisome proliferator-activated receptor γ (PPARγ) partial activation, among which telmisartan displays the best. Telmisartan has been tested as a bifunctional ligand with antihypertensive and hypoglycemic activity. Aiming at more potent leads with selective AT₁R antagonism and PPARγ partial agonism, the three parts of telmisartan including the distal benzimidazole ring, the biphenyl moiety, and the carboxylic acid group experienced modification by core hopping method in our study. The central benzimidazole ring, however, remained intact considering its great affinity toward AT₁R and PPARγ. We utilized computational techniques for the sake of details on the binding interactions and conformational stability. Standard precision docking analysis and absorption, distribution, metabolism, excretion, and toxicity prediction received 10 molecules with higher Glide scores, similar interactions, and improved pharmacokinetic profiles compared to telmisartan. Comp#91 with highest scores for AT₁R (-11.92 kcal/mol) and PPARγ (-13.88 kcal/mol) exhibited excellent binding modes and pharmacokinetic parameters. Molecular dynamics trajectories on best docking pose of comp#91 confirmed the docking results and verified the conformational stability with both receptors throughout the course of 20-ns simulations. Thus, comp#91 could be identified as a promising lead in the development of dual AT₁R antagonist and PPARγ partial agonist against hypertension and type 2 diabetes.

Molecular dynamics of sialic acid analogues complex with cholera toxin and DFT optimization of ethylene glycol-mediated zinc nanocluster conjugation

Cholera is an infectious disease caused by cholera toxin (CT) protein of bacterium Vibrio cholerae. A sequence of sialic acid (N-acetylneuraminic acid, NeuNAc or Neu5Ac) analogues modified in its C-5 position is modelled using molecular modelling techniques and docked against the CT followed by molecular dynamics simulations. Docking results suggest better binding affinity of NeuNAc analogue towards the binding site of CT. The NeuNAc analogues interact with the active site residues GLU:11, TYR:12, HIS:13, GLY:33, LYS:34, GLU:51, GLN:56, HIE:57, ILE:58, GLN:61, TRP:88, ASN:90 and LYS:91 through intermolecular hydrogen bonding. Analogues N-glycolyl-NeuNAc, N-Pentanoyl-NeuNAc and N-Propanoyl-NeuNAc show the least XPGscore (docking score) of -9.90, -9.16, and -8.91, respectively, and glide energy of -45.99, -42.14 and -41.66 kcal/mol, respectively. Stable nature of CT-N-glycolyl-NeuNAc, CT-N-Pentanoyl-NeuNAc and CT-N-Propanoyl-NeuNAc complexes was verified through molecular dynamics simulations, each for 40 ns using the software Desmond. All the nine NeuNAc analogues show better score for drug-like properties, so could be considered as suitable candidates for drug development for cholera infection. To improve the enhanced binding mode of NeuNAc analogues towards CT, the nine NeuNAc analogues are conjugated with Zn nanoclusters through ethylene glycol (EG) as carriers. The NeuNAc analogues conjugated with EG-Zn nanoclusters show better binding energy towards CT than the unconjugated nine NeuNAc analogues. The electronic structural optimization of EG-Zn nanoclusters was carried out for optimizing their performance as better delivery vehicles for NeuNAc analogues through density functional theory calculations. These sialic acid analogues may be considered as novel leads for the design of drug against cholera and the EG-Zn nanocluster may be a suitable carrier for sialic acid analogues.