Molecular Mechanics Generalized Born Surface Area Research Articles

Exploration of Secondary Metabolites in Flower-Petal Annona muricata as Agonists for Peroxisome Proliferator-Activated Receptor-Alpha (PPARα) for Liver Function

The expression of PPARα in the liver is significantly increased in both non-alcoholic fatty liver disease (NAFLD) patients and experimental models. Animal studies have shown promising outcomes in improving histological conditions, such as fibrosis, through the use of PPARα agonists. This particular petal to act as agonists for PPARα. Molecular docking and Prime MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) were employed to analyze the ligand binding affinity, atomistic interactions, and protein stability. Additionally, we conducted evaluations of the identified PPARα agonist candidates to assess their toxicity and pharmacological profiles were conducted. The hit compounds exhibit favourable binding affinity and thermodynamics stability, and interact effectively with key residues in the binding site. Furthermore, the safety assessment indicates minimal to non-acute toxicity and favourable drug-like properties for these compounds. Secondary metabolites in the extract are potential drug candidate. They demonstrate drug-like properties as they adhere to the Lipinski rule.

Investigation of the Binding Interaction of Mfsd2a with NEDD4-2 via Molecular Dynamics Simulations.

Major facilitator superfamily domain-containing 2a (Mfsd2a) is a sodium-dependent lysophosphatidylcholine cotransporter that plays an important role in maintaining the integrity of the blood-brain barrier and neurological function. Abnormal degradation of Mfsd2a often leads to dysfunction of the blood-brain barrier, while upregulation of Mfsd2a can retrieve neurological damage. It has been reported that Mfsd2a can be specifically recognized and ubiquitinated by neural precursor cell-expressed developmentally downregulated gene 4 type 2 (NEDD4-2) ubiquitin ligase and finally degraded through the proteasome pathway. However, the structural basis for the specific binding of Mfsd2a to NEDD4-2 is unclear. In this work, we combined deep learning and molecular dynamics simulations to obtain a Mfsd2a structure with high quality and a stable Mfsd2a/NEDD4-2-WW3 interaction model. Moreover, molecular mechanics generalized Born surface area (MM-GBSA) methods coupled with per-residue energy decomposition studies were carried out to analyze the key residues that dominate the binding interaction. Based on these results, we designed three peptides containing the key residues by truncating the Mfsd2a sequences. One of them was found to significantly inhibit Mfsd2a ubiquitination, which was further validated in an oxygen-glucose deprivation (OGD) model in a human microvascular endothelial cell line. This work provides some new insights into the understanding of Mfsd2a and NEDD4-2 interaction and might promote further development of drugs targeting Mfsd2a ubiquitination.

Inhibition of respiratory syncytial virus by Daclatasvir and its derivatives: synthesis of computational derivatives as a new drug development

The most common cause of respiratory tract illness in newborns and young children is the respiratory syncytial virus (RSV). There is no approved vaccination or specific antiviral medication for RSV infections. Here, an attempt has been made to explore the potential of currently marketed drugs as well as their probable derivatives to improve the possibility of developing stronger medications against RSV. From the 100 synthetic drug compounds library, the best drug molecule was identified through drug-likeness properties, toxicity, molecular docking and molecular dynamics simulations. Molecular Mechanics Generalized Born Surface Area (MM-GBSA) was also a method that was applied in this study. Daclatasvir showed the highest binding energy and appeared as the best drug to inhibit matrix protein and a fusion protein of RSV. Based on Daclatasvir, 40 computational derivatives were made. D28, D34 and D40 showed far better results than the actual drug. Changes in lipophilicity character increase the binding energy of derivatives. Molecular dynamic simulations showed their non-deviated, non-fluctuated and stable complex formation with target proteins. The high number of amino acid contacts throughout the trajectory increases the stability and effectiveness of derivatives. The key to producing a novel medicine to eradicate RSV is provided by derivatives. Daclatasvir will be employed as a potential RSV inhibitor up until that point. Communicated by Ramaswamy H. Sarma

Novel sofosbuvir derivatives against SARS-CoV-2 RNA-dependent RNA polymerase: an in silico perspective

The human coronavirus, SARS-CoV-2, had a negative impact on both the economy and human health, and the emerging resistant variants are an ongoing threat. One essential protein to target to prevent virus replication is the viral RNA-dependent RNA polymerase (RdRp). Sofosbuvir, a uridine nucleotide analog that potently inhibits viral polymerase, has been found to help treat SARS-CoV-2 patients. This work combines molecular docking and dynamics simulation (MDS) to test 14 sofosbuvir-based modifications against SARS-CoV-2 RdRp. The results reveal comparable (slightly better) average binding affinity of five modifications (compounds 3, 4, 11, 12, and 14) to the parent molecule, sofosbuvir. Compounds 3 and 4 show the best average binding affinities against SARS-CoV-2 RdRp (− 16.28 ± 5.69 and − 16.25 ± 5.78 kcal/mol average binding energy compared to − 16.20 ± 6.35 kcal/mol for sofosbuvir) calculated by Molecular Mechanics Generalized Born Surface Area (MM-GBSA) after MDS. The present study proposes compounds 3 and 4 as potential SARS-CoV-2 RdRp blockers, although this has yet to be proven experimentally.

Ruxolitinib'in COVID-19 majör proteaz enzimine ve SARS CoV-2 spike glikoproteinine karşı inhibitör aktivitesi: Bir moleküler kenetlenme çalışması.

Ruxolitinib (C17H18N6) is a Janus kinase (JAK) inhibitor that inhibits JAK1, JAK2, and JAK3 and with its tyrosine kinase inhibitor function It is the first drug approved for use in the treatment of myelofibrosis. The possible conformations of the ruxolitinib molecule were searched using PM3 technique and the Spartan06 software. The estimated molecular energies of the Ruxolitinib conformers, obtained by the variations in dihedral angles, were compared, and the most stable conformer was determined. To enlighten the inhibitory activity of Ruxolitinib agaist the apo (PDB ID: 6M03) and holo (PDB ID: 6LU7) forms of the main protease enzyme (Mpro) of COVID-19 and the SARSCoV-2 spike glycoprotein (PDB ID: 6VXX), molecular docking simulations were performed. The binding affinities and binding modes were determined. The binding free energies of ruxolitinib and 6M03, 6LU7, 6VXX targets calculated by the combination of Molecular Mechanics/Generalized Born Surface Area (MMGBSA) and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) methods {MM/PB(GB)SA approach}, were found to be -22.24, -19.96 and -22.44 kcal/mol, respectively.

In silico screening of natural products as uPAR inhibitors via multiple structure-based docking and molecular dynamics simulations

Cancer remains one of the most pressing challenges to global healthcare, exerting a significant impact on patient life expectancy. Cancer metastasis is a critical determinant of the lethality and treatment resistance of cancer. The urokinase-type plasminogen activator receptor (uPAR) shows great potential as a target for anticancer and antimetastatic therapies. In this work, we aimed to identify potential uPAR inhibitors by structural dynamics-based virtual screenings against a natural product library on four representative apo-uPAR structural models recently derived from long-timescale molecular dynamics (MD) simulations. Fifteen potential inhibitors (NP1-NP15) were initially identified through molecular docking, consensus scoring, and visual inspection. Subsequently, we employed MD-based molecular mechanics-generalized Born surface area (MM-GBSA) calculations to evaluate their binding affinities to uPAR. Structural dynamics analyses further indicated that all of the top 6 compounds exhibited stable binding to uPAR and interacted with the critical residues in the binding interface between uPAR and its endogenous ligand uPA, suggesting their potential as uPAR inhibitors by interrupting the uPAR-uPA interaction. We finally predicted the ADMET properties of these compounds. The natural products NP5, NP12, and NP14 with better binding affinities to uPAR than the uPAR inhibitors previously discovered by us were proven to be potentially orally active in humans. This work offers potential uPAR inhibitors that may contribute to the development of novel effective anticancer and antimetastatic therapeutics. Communicated by Ramaswamy H. Sarma

In silico approach reveals N-(5-phenoxythiophen-2-yl)-2-(arylthio)acetamides as promising selective SIRT2 inhibitors: the case of structural optimization of virtual screening-derived hits

Epigenetic modifications play an essential role in tumor suppression and promotion. Among the diverse range of epigenetic regulators, SIRT2, a member of NAD+-dependent protein deacetylates, has emerged as a crucial regulator of cellular processes, including cell cycle progression, DNA repair, and metabolism, impacting tumor growth and survival. In the present work, a series of N-(5-phenoxythiophen-2-yl)-2-(arylthio)acetamide derivatives were identified following a structural optimization of previously reported virtual screening hits, accompanied by enhanced SIRT2 inhibitory potency. Among the compounds, ST44 and ST45 selectively inhibited SIRT2 with IC50 values of 6.50 and 7.24 μM, respectively. The predicted binding modes of the two compounds revealed the success of the optimization run. Moreover, ST44 displayed antiproliferative effects on the MCF-7 human breast cancer cell line. Further, the contribution of SIRT2 inhibition in this effect of ST44 was supported by western blotting, affording an increased α-tubulin acetylation. Furthermore, molecular dynamics (MD) simulations and binding free energy calculations using molecular mechanics/generalized born surface area (MM-GBSA) method evaluated the accuracy of predicted binding poses and ligand affinities. The results revealed that ST44 exhibited a remarkable level of stability, with minimal deviations from its initial docking conformation. These findings represented a significant improvement over the virtual screening hits and may contribute substantially to our knowledge for further selective SIRT2 drug discovery. Communicated by Ramaswamy H. Sarma

Salazinic Acid and Norlobaridone from the Lichen Hypotrachyna cirrhata: Antioxidant Activity, α-Glucosidase Inhibitory and Molecular Docking Studies

The present study was intended for the identification of secondary metabolites in acetone extract of the lichen Hypotrachyna cirrhata using UPLC-ESI-QToF-MS/MS and the detection of bioactive compounds. This study led to the identification of 22 metabolites based on their MS/MS spectra, accurate molecular masses, molecular formula from a comparison of the literature database (DNP), and fragmentation patterns. In addition, potent antioxidant and α-glucosidase inhibitory potentials of acetone extract of H. cirrhata motivated us to isolate 10 metabolites, which were characterized as salazinic acid (11), norlobaridone (12), atranorin (13), lecanoric acid (14), lichesterinic acid (15), protolichesterinic acid (16), methyl hematommate (17), iso-rhizonic acid (18), atranol (19), and methylatratate (20) based on their spectral data. All these isolates were assessed for their free radicals scavenging, radical-induced DNA damage, and intestinal α-glucosidase inhibitory activities. The results indicated that norlobaridone (12), lecanoric acid (14), methyl hematommate (17), and atranol (19) showed potent antioxidant activity, while depsidones (salazinic acid (11), norlobaridone (12)) and a monophenolic compound (iso-rhizonic acid, (18)) displayed significant intestinal α-glucosidase inhibitory activities (p < 0.001), which is comparable to standard acarbose. These results were further correlated with molecular docking studies, which indicated that the alkyl chain of norlobaridione (12) is hooked into the finger-like cavity of the allosteric pocket; moreover, it also established Van der Waals interactions with hydrophobic residues of the allosteric pocket. Thus, the potency of norlobaridone to inhibit α-glucosidase enzyme might be associated with its allosteric binding. Also, MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) binding free energies of salazinic acid (11) and norlobaridone (12) were superior to acarbose and may have contributed to their high activity compared to acarbose.

Discovery of small molecule c-Maf inhibitors using molecular docking-based virtual screening, molecular dynamics simulation, and biological evaluation.

Multiple myeloma (MM) is a prevalent plasma cell malignancy in the blood system that remains incurable. Given the abnormally high expression of c-Maf in most MM patients, targeting c-Maf presents an attractive therapeutic approach for treating MM malignancies. In this study, we employed a combined strategy involving molecular docking-based virtual screening, molecular dynamics (MD) simulation, and molecular mechanics/generalized Born surface area (MM/GBSA) free energy calculation on existing FDA-approved drugs. Six compounds were selected for further experimental assay: vemurafenib, sorafenib, sildenafil, fluvastatin, erlotinib, and glimepiride. Among these compounds, sorafenib and glimepiride exhibited significant inhibition of myeloma cell proliferation in the RPMI-8226 cell line. Moreover, both compounds simultaneously downregulated c-Maf protein expression to induce G1 phase arrest and apoptosis in myeloma cells. Collectively, sorafenib and glimepiride may be considered promising candidates for developing more potent c-Maf inhibitors in the future.

An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches

Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of −6.31 kcal/mol. Further, molecular mechanics–generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics–Poisson–Boltzmann surface area (MM-PBSA) were carried out to validate the findings. Communicated by Ramaswamy H. Sarma

Evaluation of structural and thermodynamic insight of ERβ with DPN and derivatives through MMGBSA/MMPBSA methods

Estrogen receptors (ERs) are nuclear factors that exist as two subtypes: ERα and ERβ. Among the different selective ERβ agonist ligands, the widely used ERβ-selective agonist DPN (diarylpropionitrile) is highlighted. Recent experimental and thermodynamic information between R-DPN and S-DPN enantiomers with ERβ is important for evaluating further the ability of MD simulations combined with end-point methods to reproduce experimental binding affinity and generate structural insight not provided through crystallographic data. In this research, starting from crystallographic data and experimental binding affinities, we explored the structural and thermodynamic basis of the molecular recognition of ERβ with DPN and derivatives through triplicate MD simulations combined with end-point methods. Conformational analysis showed some regions with the highest mobility linked to ligand association that, at the time, impacted the total protein fluctuation. Binding free energy (ΔG) analysis revealed that the Molecular Mechanics Generalized-Born Surface Area (MMGBSA) approach was able to reproduce the experimental tendency with a strong correlation (R = 0.778), whereas per-residue decomposition analysis revealed that all the systems interacted strongly with eight residues (L298, E305, L339, M340, L343, F356, H475, and L476). The comparison between theoretical studies using the MMGBSA approach with experimental results provides new insights for drug designing of new DPN derivatives.

2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies.

The aurora kinase is a key enzyme that is implicated in tumor growth. Research revealed that small molecules that target aurora kinase have beneficial effects as anticancer agents. In the present study, in order to identify potential antibreast cancer agents with aurora kinase inhibitory activity, we employed QSARINS software to perform the quantitative structure-activity relationship (QSAR). The statistical values resulted from the study include R2 = 0.8902, CCCtr = 0.7580, Q2 LOO = 0.7875, Q2LMO = 0.7624, CCCcv = 0.7535, R2ext = 0.8735, and CCCext = 0.8783. Among the four generated models, the two best models encompass five important variables, including PSA, EstateVSA5, MoRSEP3, MATSp5, and RDFC24. The parameters including the atomic volume, atomic charges, and Sanderson's electronegativity played an important role in designing newer lead compounds. Based on the above data, we have designed six series of compounds including 1a-e, 2a-e, 3a-e, 4a-e, 5a-e, and 6a-e. All these compounds were subjected to molecular docking studies by using AutoDock v4.2.6 against the aurora kinase protein (1MQ4). Among the above 30 compounds, the 2-amino thiazole derivatives 1a, 2a, 3e, 4d, 5d, and 6d have excellent binding interactions with the active site of 1MQ4. Compound 1a had the highest docking score (-9.67) and hence was additionally subjected to molecular dynamic simulation investigations for 100 ns. The stable binding of compound 1a with 1MQ4 was verified by RMSD, RMSF, RoG, H-bond, molecular mechanics-generalized Born surface area (MM-GBSA), free binding energy calculations, and solvent-accessible surface area (SASA) analyses. Furthermore, newly designed compound 1a exhibited excellent ADMET properties. Based on the above findings, we propose that the designed compound 1a may be utilized as the best theoretical lead for future experimental research of selective inhibition of aurora kinase, therefore assisting in the creation of new antibreast cancer drugs.

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2 train = 0.8646, R2 test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules. Communicated by Ramaswamy H. Sarma

Exploring the Binding Effects of Natural Products and Antihypertensive Drugs on SARS-CoV-2: An In Silico Investigation of Main Protease and Spike Protein.

In this in silico study, we conducted an in-depth exploration of the potential of natural products and antihypertensive molecules that could serve as inhibitors targeting the key proteins of the SARS-CoV-2 virus: the main protease (Mpro) and the spike (S) protein. By utilizing Induced Fit Docking (IFD), we assessed the binding affinities of the molecules under study to these crucial viral components. To further comprehend the stability and molecular interactions of the "protein-ligand" complexes that derived from docking studies, we performed molecular dynamics (MD) simulations, shedding light on the molecular basis of potential drug candidates for COVID-19 treatment. Moreover, we employed Molecular Mechanics Generalized Born Surface Area (MM-GBSA) calculations on all "protein-ligand" complexes, underscoring the robust binding capabilities of rosmarinic acid, curcumin, and quercetin against Mpro, and salvianolic acid b, rosmarinic acid, and quercetin toward the S protein. Furthermore, in order to expand our search for potent inhibitors, we conducted a structure similarity analysis, using the Enalos Suite, based on the molecules that indicated the most favored results in the in silico studies. The Enalos Suite generated 115 structurally similar compounds to salvianolic acid, rosmarinic acid, and quercetin. These compounds underwent IFD calculations, leading to the identification of two salvianolic acid analogues that exhibited strong binding to all the examined binding sites in both proteins, showcasing their potential as multi-target inhibitors. These findings introduce exciting possibilities for the development of novel therapeutic agents aiming to effectively disrupt the SARS-CoV-2 virus lifecycle.

In silico approaches for the identification of novel ULK1 inhibitors: pharmacophore model, molecular docking and molecular dynamics simulations

The serine/threonine kinase unc-51-like autophagy activating kinase 1 (ULK1) has been regarded as an attractive target for tumor therapy. In this study, in silico approaches, such as the pharmacophore-based virtual screening strategy, molecular docking and molecular dynamics (MD) simulations, were applied to develop novel potential ULK1 inhibitors. The pharmacophore models based on known aminopyrimidine ULK1 inhibitors were constructed to screen the dataset of 1.68 million compounds, which were obtained via screening the 2.30 million compounds in ChEMBL database by Lipinski’s rule of five. Seven novel compounds and 1 known ULK1 inhibitor stand out for the strong virtual biological activity by molecular docking, cluster analysis, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation and Absorption Distribution Metabolism Excretion Toxicity (ADMET) prediction. Their results of MD included principal component analysis (PCA) and Free Energy Landscapes surface (FELs) indicated that the protein–ligand complex was stable in simulated trajectories of 100 ns. The binding free energy (BFE) calculations showed that a total of 6 novel compounds (CL130, CL834, CL961, CL966, CL163 and CL329) with the stable binding state and stronger BFE (−61.17 to −37.01 kcal/mol) than that of original ligand 3RF (−36.66 kcal/mol). With reference to the ULK1 inhibition of 3RF (IC50 = 160 nM), it can be inferred that these compounds could be used as a new type of potential ULK1 inhibitors and be worthy of further investigation for tumor treatments. Communicated by Ramaswamy H. Sarma

Elucidating the conformational dynamics of histo-blood group antigens and their interactions with the rotavirus spike protein through computational lens

In the present study, we investigated the conformational dynamics of histo-blood group antigens (HBGAs) and their interactions with the VP8* domain of four rotavirus genotypes (P[4], P[6], P[19], and P[11]) utilizing all-atom molecular dynamics simulations in explicit water. Our study revealed distinct changes in the dynamic behavior of the same glycan due to linkage variations. We observed that LNFPI HBGA having a terminal β linkage shows two dominant conformations after complexation, whereas only one was obtained for LNFPI with a terminal α linkage. Interestingly, both variants displayed a single dominant structure in the free state. Similarly, LNT and LNnT show a shift in their dihedral linkage profile between their two terminal monosaccharides because of a change in the linkage from β(1–3) to β(1–4). The molecular mechanics generalized Born surface area (MM/GBSA) calculations yielded the highest binding affinity for LNFPI(β)/P[6] (−13.93 kcal/mol) due to the formation of numerous hydrogen bonds between VP8* and HBGAs. LNnT binds more strongly to P[11] (−12.88 kcal/mol) than LNT (−4.41 kcal/mol), suggesting a single change in the glycan linkage might impact its binding profile significantly. We have also identified critical amino acids and monosaccharides (Gal and GlcNAc) that contributed significantly to the protein-ligand binding through the per-residue decomposition of binding free energy. Moreover, we found that the interaction between the same glycan and different protein receptors within the same rotavirus genogroup influenced the micro-level dynamics of the glycan. Overall, our study helps a deeper understanding of the H-type HBGA and rotavirus spike protein interaction. Communicated by Ramaswamy H. Sarma

Marine-Derived Compounds for CDK5 Inhibition in Cancer: Integrating Multi-Stage Virtual Screening, MM/GBSA Analysis and Molecular Dynamics Investigations.

Cyclin-dependent kinase 5 (CDK5) plays a crucial role in various biological processes, including immune response, insulin secretion regulation, apoptosis, DNA (deoxyribonucleic acid) damage response, epithelial-mesenchymal transition (EMT), cell migration and invasion, angiogenesis, and myogenesis. Overactivation of CDK5 is associated with the initiation and progression of cancer. Inhibiting CDK5 has shown potential in suppressing cancer development. Despite advancements in CDK5-targeted inhibitor research, the range of compounds available for clinical and preclinical trials remains limited. The marine environment has emerged as a prolific source of diverse natural products with noteworthy biological activities, including anti-cancer properties. In this study, we screened a library of 47,450 marine natural compounds from the comprehensive marine natural product database (CMNPD) to assess their binding affinity with CDK5. Marine compounds demonstrating superior binding affinity compared to a reference compound were identified through high-throughput virtual screening, standard precision and extra-precision Glide docking modes. Refinement of the selected molecules involved evaluating molecular mechanics-generalized born surface area (MM/GBSA) free binding energy. The three most promising compounds, (excoecariphenol B, excoecariphenol A, and zyzzyanone B), along with the reference, exhibiting favorable binding characteristics were chosen for molecular dynamics (MD) simulations for 200 nanoseconds. These compounds demonstrated interaction stability with the target during MD simulations. The marine compounds identified in this study hold potential as effective CDK5 inhibitors and warrant subsequent experimental validation.

Exploring bixin from Bixa orellana L. seeds: quantification and in silico insights into its anti-cancer potential

Bixin, the key pigment of Bixa orellana L., is an apo-carotenoid found in the seed arils. The present study aimed to quantitatively determine the bixin content of seeds and explore its anti-cancer activity through in silico studies. The bixin content from the seeds of the local genotype, TNMTP8, quantified by RP-HPLC was 4.58 mg per gram. The prediction of pharmacological activity suggested that bixin may serve as a BRAF, MMP9, TNF expression inhibitors, and TP53 expression enhancer. According to molecular docking analysis, bixin interacted with eight different skin cancer targets and had the lowest binding energy compared to the standard drug, 5-fluorouracil. The binding score between bixin and the targets ranged from −4.7 to −8.7 kcal/mol. The targets BRAF and SIRT3 interacted well with bixin, with binding energies as low as −8.3 and −8.7 kcal/mol, respectively. Hence, the dynamic behavior of these two docked complexes throughout a 500 ns trajectory run was investigated further. The Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) values, and total contacts as a function of time recorded during scrutiny suggest that both complexes were stable. This was validated by post-molecular dynamics analysis using Molecular Mechanics Generalized Born Surface Area (MM-GBSA). Principal component analysis (PCA) was used to analyze the significant differences in motion exhibited by BRAF-Bixin and SIRT3-Bixin. The results showed that bixin is a promising source for potential treatment interventions in skin cancer therapies. Communicated by Ramaswamy H. Sarma

Multi-Target Effect of Aloeresin-A against Bacterial and Host Inflammatory Targets Benefits Contact Lens-Related Keratitis: A Multi-Omics and Quantum Chemical Investigation.

Contact lens-mediated microbial keratitis caused by Pseudomonas aeruginosa and Streptococcus pneumoniae provokes corneal damage and vision loss. Recently, natural phytochemicals have become complementary medicines for corneal destruction. Herein, we aimed to identify multi-targeting Aloe vera-derived phytochemicals capable of inhibiting bacterial and host targets of keratitis through ADME (absorption, distribution, metabolism, and excretion), docking, molecular dynamics (MD) simulation, MMGBSA (molecular mechanics generalized Born surface area) and density functional theory (DFT) investigations. An extensive literature search revealed ExoU, ExoS, ExoT, ExoY, and PLY as virulent bacterial targets. Simultaneously, differential gene expression (DGE) and pathway enrichment analysis-specified host transcription factor (SPI1) influences keratitis pathogenesis. Molecular docking analysis uncovered aloeresin-A as a promising inhibitor against bacterial and host targets, demonstrating strong binding energies ranging from -7.59 to -6.20 kcal/mol. Further, MMGBSA and MD simulation analysis reflect higher binding free energies and stable interactions of aloeresin-A with the targets. In addition, DFT studies reveal the chemical reactiveness of aloeresin-A through quantum chemical calculations. Hence, our findings show aloeresin-A to be a promising candidate for effectively inhibiting keratitis. However, additional research is imperative for potential integration into lens care solutions.

Screening of Phytocompounds for Identification of Prospective Histone Deacetylase 1 (HDAC1) Inhibitor: An In Silico Molecular Docking, Molecular Dynamics Simulation, and MM-GBSA Approach.

The upregulation of HDAC1 facilitate the induction of epigenetic repression of genes responsible for suppressingtumourigenesis, thereby triggering the development of cancer. HDAC1 inhibitors have thus emerged as possible therapeutic approaches against a variety of human malignancies, as they can inhibit the activity of certain HDACs, repair the overexpression of tumour suppressor genes, and induce cell differentiation, cell cycle arrest, and apoptosis. In this study, among 810 virtually screened compounds, Pinocembrin (PHUB000396) had a significant binding affinity (-7.99kcal/mol). In molecular dynamics simulation (MD) studies for 200ns time scale, the compound Pinocembrin effectively undergoes conformationaloptimization, thereby enabling its accommodation within the active site of the receptor. This outcome serves as a rational for the observed binding affinity. The optimal binding free energy calculations using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) (-35.86 ± 7.52kcal/mol) showed the significant role of van der Waals forces and Coulomb interactions in the stability of the respective complex. The pharmacokinetic study showed its potential as a lead compound. The in-silico cytotoxicity prediction also confirmed its potential as an active anticancer phytocompound in lung and brain cancer. Therefore, it can be predicted that Pinocembrin could be a useful bioactive compound as an HDAC1 inhibitor and could be used in developing epigenetic therapy in cancer such as brain cancer and lung cancer to regulate gene expression.