Molecular Mechanics Generalized Born Surface Area Research Articles

NOVEL HYBRIDS OF QUINOLINE LINKED PYRIMIDINE DERIVATIVES AS CYCLOOXYGENASE INHIBITORS: MOLECULAR DOCKING, ADMET STUDY, AND MD SIMULATION

Objective: Finding novel anti-inflammatory compounds is a crucial sector of research despite the significant advances this field has made. Inefficiency and unfavorable side effects are indeed potential drawbacks of conventional therapy utilizing steroidal or nonsteroidal drugs. This study aims to screen the designed quinoline-linked pyrimidine derivatives as Cyclooxygenase (COX) inhibitors. Methods: In the present study, we assessed the binding interactions of designed quinoline-linked pyrimidine derivatives with COX enzymes using a molecular docking approach. Using Molecular Dynamics (MD) simulations, the compound’s behavior was further investigated and its stability and conformational dynamics were demonstrated. Schrödinger's QikProp program was utilized to analyze the Absorption, Distribution, Metabolism, and Excretion (ADME) properties and toxicity properties were further investigated using Osiris Property Explorer. Additionally, the protein-ligand complexes' binding free energy has been ascertained using the Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) approach, which offered crucial information regarding the strength of their interactions. Results: The designed quinoline-linked pyrimidine derivatives fulfilled the Lipinski Rule of Five and had physicochemical characteristics within acceptable ranges, better ADME properties, and were non-toxic. Among the designed compounds, QPDU1 and QPDT6 showed correspondingly good docking scores for COX-1 and COX-2. QPDT6 was additionally analyzed by MD simulation studies to thoroughly examine the interaction between protein and ligand and their stability. Conclusion: The proposed compounds exhibit strong binding affinities to COX enzymes, stable interactions in MD simulations, and favorable drug-like features. These results support the need for more research and development of these substances as possible anti-inflammatory drugs.

A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands.

The substantial increase in the number of active and inactive-state CB1 receptor experimental structures has provided opportunities for CB1 drug discovery using various structure-based drug design methods, including the popular end-point methods for predicting binding free energies-Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA). In this study, we have therefore evaluated the performance of MM/PBSA and MM/GBSA in calculating binding free energies for CB1 receptor. Additionally, with both MM/PBSA and MM/GBSA being known for their highly individualized performance, we have evaluated the effects of various simulation parameters including the use of energy minimized structures, choice of solute dielectric constant, inclusion of entropy, and the effects of the five GB models. Generally, MM/GBSA provided higher correlations than MM/PBSA (rMM/GBSA = 0.433 - 0.652 vs. rMM/PBSA = 0.100 - 0.486) regardless of the simulation parameters, while also offering faster calculations. Improved correlations were observed with the use of molecular dynamics ensembles compared with energyminimized structures and larger solute dielectric constants. Incorporation of entropic terms led to unfavorable results for both MM/PBSA and MM/GBSA for a majority of the dataset, while the evaluation of the various GB models exerted a varying effect on both the datasets. The findings obtained in this study demonstrate the utility of MM/PBSA and MM/GBSA in predicting binding free energies for the CB1 receptor, hence providing a useful benchmark for their applicability in the endocannabinoid system as well as other G protein-coupled receptors. The study utilized the docked dataset (Induced Fit Docking with Glide XP scoring function) from Loo et al., consisting of 46 ligands-23 agonists and 23 antagonists. The equilibrated structures from Loo et al. were subjected to 30ns production simulations using GROMACS 2018 at 300K and 1atm with the velocity rescaling thermostat and the Parinello-Rahman barostat. AMBER ff99SB*-ILDN was used for the proteins, General Amber Force Field (GAFF) was used for the ligands, and Slipids parameters were used for lipids. MM/PBSA and MM/GBSA binding free energies were then calculated using gmx_MMPBSA. The solute dielectric constant was varied between 1, 2, and 4 to study the effect of different solute dielectric constants on the performance of MM/PB(GB)SA. The effect of entropy on MM/PB(GB)SA binding free energies was evaluated using the interaction entropy module implemented in gmx_MMPBSA. Five GB models, GBHCT, GBOBC1, GBOBC2, GBNeck, and GBNeck2, were evaluated to study the effect of the choice of GB models in the performance of MM/GBSA. Pearson correlation coefficients were used to measure the correlation between experimental and predicted binding free energies.

In silico analysis of the melamine structural analogues interaction with calcium-sensing receptor: A potential for nephrotoxicity

In recent years, melamine, and its structural analogues, as adulterants in various food products including protein supplements,have been widely studied for their nephrotoxic effects. Previous research has presented evidence that certain small molecules can alter the calcium-sensing receptor (CaSR) function, contributing to nephrotoxicity. Melamine, for example, has been observed in in vitro settings to interact with the allosteric binding site of CaSR, resulting in uncontrolled CaSR activation. This activation results in the production of reactive oxygen species, which eventually causes kidney cell apoptosis and/or necrosis. The present research used the in silico molecular modelling to evaluate the CaSR binding profilesof four common adulterants in protein supplements: melamine, cyanuric acid, uric acid, and melamine cyanurate. Using Schrödinger’s Maestro docking software (version 13.2.128), the docking studies coupled a noncovalent extra precision mode with the molecular mechanics-generalized born surface area (MM-GBSA) simulation for enhanced binding affinity prediction accuracy. This study identified that cyanuric acid, uric acid, and melamine cyanurate have greater CaSR binding affinities than melamine. Interestingly, melamine cyanurate had the highest binding potential to CaSR. Previous animal studies have reported high concentrations of melamine cyanurate complex in rat kidneys following melamine administration. These findings demonstrate a molecular explanation melamine cyanurate complex-induced nephrotoxicity. This research offers new insight regarding the probable mechanism through which melamine, its analogues, and complexes may cause nephrotoxicity.

Cheminformatics-driven prediction of BACE-1 inhibitors: Affinity and molecular mechanism exploration

The β-secretase, sometimes referred to as BACE1 or Asp2, is the enzyme responsible for initiating the production of Aβ by breaking down the amyloid precursor protein. Hence, BACE is a pivotal target for pharmacological intervention aimed at diminishing the production of Aβ in Alzheimer's disease (AD). We did a quantitative structure-activity relationship (QSAR) study on 1235 compounds that had been experimentally reported as BACE-1 inhibitors (Ki) to find the target molecule and structural patterns linked to blocking the BACE-1 receptor. The OECD-recommended genetic algorithm-multiple linear regression (GA-MLR) QSAR model strikes a good balance between being able to make accurate predictions and understanding how things work. It achieves high values for many evaluation metrics, including R2tr = 0.8047, Q2LMO = 0.802, R2ex = 0.805, CCCex = 0.891, Q2-F1=0.801, Q2-F2=0.799, and Q2-F3=0.815. The mechanistic interpretation of QSAR has identified some nitrogen atoms that are required to block beta-secretase and make it less effective at doing its job. A positively charged aromatic carbon atom has a more significant impact on beta-secretase-1 inhibition. The docking study showed that the catalytic dye residues Asp32 and Asp228 become protonated when compound 27 is present, but they stay unprotonated when compound 27 is not present. These rings of pyrazine and pyridine interact hydrophobically with Tyr71 and Ile118 residues, confirming the pharmacophoric features seen in the QSAR data. We examined the stability of both the protein-ligand complex and the apo-protein. The apoprotein had an average gyration radius of 22.13, whereas the protein-ligand complex had an average gyration radius of 22.91. No changes were made to the results from the molecular docking, molecular dynamics (MD) simulation, MMGBSA (Molecular Mechanics Generalized Born Surface Area), or DFT analyses. Therefore, the current work could effectively contribute to the future development of BACE inhibitors in medication design.

Exploring novel natural compound-based therapies for Duchenne muscular dystrophy management: insights from network pharmacology, QSAR modeling, molecular dynamics, and free energy calculations.

Muscular dystrophies encompass a heterogeneous group of rare neuromuscular diseases characterized by progressive muscle degeneration and weakness. Among these, Duchenne muscular dystrophy (DMD) stands out as one of the most severe forms. The present study employs an integrative approach combining network pharmacology, quantitative structure-activity relationship (QSAR) modeling, molecular dynamics (MD) simulations, and free energy calculations to identify potential therapeutic targets and natural compounds for DMD. Upon analyzing the GSE38417 dataset, it was found that individuals with DMD exhibited 290 upregulated differentially expressed genes (DEGs) compared to healthy controls. By utilizing gene ontology (GO) and protein-protein interaction (PPI) network analysis, this study provides insights into the functional roles of the identified DEGs, identifying ten hub genes that play a critical role in the pathology of DMD. These key genes include DMD, TTN, PLEC, DTNA, PKP2, SLC24A, FBXO32, SNTA1, SMAD3, and NOS1. Furthermore, through the use of ligand-based pharmacophore modeling and virtual screening, three natural compounds were identified as potential inhibitors. Among these, compounds 3874518 and 12314417 have demonstrated significant promise as an inhibitor of the SMAD3 protein, a crucial factor in the fibrotic and inflammatory mechanisms associated with DMD. The therapeutic potential of the compounds was further supported by molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis. These findings suggest that the compounds are viable candidates for experimental validation against DMD.

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.

Adenosyl derivatives as a potential inhibitors of NS3 protease of Japanese encephalitis virus (JEV): In silico molecular insight into therapeutic discovery

The genus Flavivirus NS3 a non-structural protein of Japanes Encephalitis Virus (JEV), a serious deadly human pathogen responsible for several deaths in South East Asia, consists of helicase/NTPase domain forming a cleft known for their role in the enzymatic activity and viral replication represented biological relevance. S-Adenosyl derivatives act as powerful inhibitors in viral replication in NS5 of the same genus as of NS3, provide a powerful base to test its effectiveness in NS3 protein due to the compatibility of both proteins. The MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) simulation were performed to evaluate the binding free energy, following the 100 (ns) production MD simulation in the periodic boundary condition (PBC) for the selected docked inhibitors with NS3. The residue-wise decomposition energy determined in our study revealed the active site region made the high stability with the potential inhibitors.

Integrative residue-intuitive machine learning and MD Approach to Unveil Allosteric Site and Mechanism for β2AR

Allosteric drugs offer a new avenue for modern drug design. However, the identification of cryptic allosteric sites presents a formidable challenge. Following the allostery nature of residue-driven conformation transition, we propose a state-of-the-art computational pipeline by developing a residue-intuitive hybrid machine learning (RHML) model coupled with molecular dynamics (MD) simulation, through which we can efficiently identify the allosteric site and allosteric modulator as well as reveal their regulation mechanism. For the clinical target β2-adrenoceptor (β2AR), we discover an additional allosteric site located around residues D792.50, F2826.44, N3187.45 and S3197.46 and one putative allosteric modulator ZINC5042. Using Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and protein structure network (PSN), the allosteric potency and regulation mechanism are probed to further improve identification accuracy. Benefiting from sufficient computational evidence, the experimental assays then validate our predicted allosteric site, negative allosteric potency and regulation pathway, showcasing the effectiveness of the identification pipeline in practice. We expect that it will be applicable to other target proteins.

Repurposing FDA-Approved Drugs as Potential Inhibitors of SARS-CoV-2 PLpro: A Comprehensive Computational Study

This study explores the repurposing of Food and Drug Administration (FDA)-approved drugs as potential inhibitors of SARS-CoV-2 papain-like protease (PLpro), a critical enzyme for viral replication. Initially, 3009 FDA approved drugs were screened to identify candidates structurally similar to the co-crystallized ligand XT7 in the SARS-CoV-2 PLpro complex (PDB ID: 7LBR). A fingerprint analysis narrowed the selection to the top 5% )150 drugs) most structurally akin to XT7, followed by a more refined structural similarity test that identified the top 1% (30 drugs). Molecular docking studies highlighted several compounds with strong binding affinities to the SARS-CoV-2 PLpro. Notably, Fedratinib exhibited a particularly robust binding energy of [Formula: see text]kcal/mol and was chosen for further investigation. Subsequent molecular dynamics (MD) simulations over 100 ns confirmed the stability and efficacy of Fedratinib’s binding, as evidenced by favorable energetic and dynamic profiles. The molecular mechanics-generalized born surface area (MM-GBSA) calculations corroborated these findings, revealing a binding energy of [Formula: see text]kcal/mol. Additionally, PLIP, ProLIF, and PCAT analyses further validated the stability and interactions of the PLpro-Fedratinib complex observed during the MD simulations. Overall, our results indicate that Fedratinib, an FDA-approved drug, demonstrates promising potential as an inhibitor of SARS-CoV-2 PLpro, warranting further in vitro and in vivo experimental validation as well as potential clinical evaluation.

Insight of the molecular mechanism of inhibitors located at different allosteric sites regulating the activity of wild type and mutant KRAS (G12)

As the important hub of many cellular signaling networks, KRAS (Kirsten rat sarcoma viral oncogene homologue) has been identified as a tumor biomarker. It is the frequently mutated oncogene in human cancers, and KRAS protein activation caused by mutations, such as G12D, has been found in many human tumors tissues. Although, there are two specific allosteric sites (AS1 and AS2) on the KRAS protein that can be used as the targets for inhibitor development, the difference of regulatory mechanisms between two individual allosteric sites still not be reported. Here, using molecular dynamics simulations combined with molecular mechanics generalized born surface area (MM/GBSA) analysis, we found that both of the inhibitors, located at AS1 and AS2, were able to reduce the binding free energy between wild type, mutant KRAS (G12/D/V/S/C) and GTP remarkably, however the effect of inhibitors on the binding free energy between wild type, mutant KRAS and GDP was limited. In addition, the degree of decrease of binding free energy between KRAS and GTP caused by inhibitors at AS2 was significantly greater than that caused by inhibitors at AS1. Further analysis revealed that both inhibitors at AS1 and AS2 were able to regulate the fluctuation of Switch Ⅰ and Switch Ⅱ to expand the pocket of the orthosteric site (GTP binding site), thereby reducing the binding of KRAS to GTP. Noteworthy there was significant differences in the regulatory preferences on Switch Ⅰ and Switch Ⅱ between two type inhibitor. The inhibitor at AS2 mainly regulated Switch Ⅱ to affect the pocket of the orthosteric site, while the inhibitor at AS1 mainly expand the pocket of the orthosteric site by regulating the fluctuation of Switch Ⅰ. Our study compared the differences between two type inhibitors in regulating the KRAS protein activity and revealed the advantages of the AS2 as the small molecule drug target, aiming to provide theoretical guidance for the research of novel KRAS protein inhibitors.

Computational insights into rational design and virtual screening of pyrazolopyrimidine derivatives targeting Janus kinase 3 (JAK3).

The Janus kinase 3 (JAK3) family, particularly JAK3, is pivotal in initiating autoimmune diseases such as rheumatoid arthritis. Recent advancements have focused on developing antirheumatic drugs targeting JAK3, leading to the discovery of novel pyrazolopyrimidine-based compounds as potential inhibitors. This research employed covalent docking, ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) analysis, molecular dynamics modeling, and MM/GBSA (Molecular Mechanics Generalized Born Surface Area) binding free energy techniques to screen 41 in silico-designed pyrazolopyrimidine derivatives. Initially, 3D structures of the JAK3 enzyme were generated using SWISS-MODEL, followed by virtual screening and covalent docking via AutoDock4 (AD4). The selection process involved the AMES test, binding affinity assessment, and ADMET analysis, narrowing down the candidates to 27 compounds that passed the toxicity test. Further covalent docking identified compounds 21 and 41 as the most promising due to their high affinity and favourable ADMET profiles. Subsequent development led to the creation of nine potent molecules, with derivatives 43 and 46 showing exceptional affinity upon evaluation through molecular dynamics simulation and MM/GBSA calculations over 300 nanoseconds, comparable to tofacitinib, an approved RA drug. However, compounds L21 and L46 demonstrated stable performance, suggesting their effectiveness in treating rheumatoid arthritis and other autoimmune conditions associated with JAK3 inhibition.

In silico Identification of Novel SphK1 Inhibitors

Aims: In silico Identification of Novel SphK1 Inhibitors. Background: A tumor is one of the major causes of death worldwide; the emergence of new targeted drugs has changed the mode of tumor treatment and opened up the era of targeted therapy. Sphingosine kinase 1 (SphK1) is a strictly conserved lipid checkpoint kinase, mainly located in the cytosol, and is overexpressed and enhances the development and progression of various type of tumors, such as melanoma, esophageal, gastric, and colon cancers. SphK1, consisting of 384 amino acid residues, has two domains: C-terminal (CTD) and N-terminal (NTD). SphK1 phosphorylates sphingosine to generate sphingosine-1-phosphate (S1P), which exists in high concentration in both the plasma and the lymph of cancer patients. S1P has 5 receptors (S1PRs) and controls 5 signal pathways, Ras/Raf/MEK1/2, PI3K/Akt, G-protein/PLC/PKC, Rho/Rock/NF-ĸB and PTEN; they are all related to cell growth, proliferation, differentiation, apoptosis, migration, and stress fiber formation. The sphK1/S1P signal pathway influences tumor cells' growth, proliferation, survival and angiogenesis, and SphK1 inhibitors can decrease Treg cell recruitment at tumor location. In T cells, SphK1/S1P signal way activates NF-ĸB and induces proliferator-activated receptor γ (PPARγ) transcription, which in turn regulates lipolysis in T cells. SphK1 can induce T cell failure through excessive S1P in extracellular vesicles of the tumor microenvironment. SphK1 inhibitors block S1P generation and inhibit cell growth, proliferation, differentiation, apoptosis, migration, and stress fiber formation, leading to increased CD8+T cells and decreased Treg cells in the tumor microenvironment. S1P also upregulates the expression of programmed cell death 1 ligand 1(PD-L1) through Early 2-factor transcription factor 1 (E2F1). Objective: The discovery of better Sphk1 inhibitors by pharmacophore model, ADMET, molecular docking, MM/GBSA, and MD simulation. Methods: Here, SphK1 pharmacophore was created; first, it was used for virtual screening, ADMET properties of screened-out molecules were predicted, and the obtained molecules were performed molecular docking and Molecular Mechanics Generalized Born Surface Area (MM/GBSA) calculation, then molecular dynamics (MD) simulation was performed, and Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) were calculated. Results: Compounds 1, 2, and 3 were obtained through screening, and the binding energy of 1, 2, and 3 were better than that of the existing corresponding target inhibitors. Conclusion: The overexpression of Sphk1 is closely related to the occurrence, development, migration and drug resistance of tumors and has a good prospect of drug development. Given the important role of SphK1 inhibitors in treating tumors and the shortcomings of clinical application of SphK1 inhibitors, small molecule targeting inhibition SphK1 was screened to overcome the low efficiency. Firstly, establishing a pharmacophore model for virtual screening, and then ADMET prediction, sixty-seven molecules were selected. And then, molecular docking and MM/GBSA calculation obtain three compounds with lower Glide Score. In addition, they both have lower binding energy than PF-543. The docking result shows that Asp167, Asp264, and Thr282 of SphK1 with ligand more easily form H-bonds interaction. Next, in molecular dynamics simulation, compounds 1, 2, and 3 can stably bind with SphK1 and have a high activity of inhibiting SphK1, with more research potential. In conclusion, compounds 1, 2, and 3 inhibit SphK1 laying a foundation for further compound synthesis and activity evaluation. Compounds 1, 2 and 3 can stably bind to the receptor protein, which is valuable for further experimental research.

The potential of Chlorella spp. as antiviral source against African swine fever virus through a virtual screening pipeline

African swine fever (ASF) causes high mortality in pigs and threatens global swine production. There is still a lack of therapeutics available, with two vaccines under scrutiny and no approved small-molecule drugs. Eleven (11) viral proteins were used to identify potential antivirals in in silico screening of secondary metabolites (127) from Chlorella spp. The metabolites were screened for affinity and binding selectivity. High-scoring compounds were assessed through in silico ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) predictions, compared to structurally similar drugs, and checked for off-target docking with prepared swine receptors. Molecular dynamics (MD) simulations determined binding stability while binding energy was measured in Molecular Mechanics - Generalized Born Surface Area (MMGBSA) or Poisson-Boltzmann Surface Area (MMPBSA). Only six (6) compounds passed until MD analyses, of which five (5) were stable after 100 ns of MD runs. Of these five compounds, only three had binding affinities that were comparable to or stronger than controls. Specifically, phytosterols 24,25-dihydrolanosterol and CID 4206521 that interact with the RNA capping enzyme (pNP868R), and ergosterol which bound to the Erv-like thioreductase (pB119L). The compounds identified in this study can be used as a theoretical basis for in vitro screening to develop potent antiviral drugs against ASFV.

Virtual screening and molecular dynamics simulation of natural compounds as potential inhibitors of serine/threonine kinase 16 for anticancer drug discovery.

Serine/threonine kinase 16 (STK 16) is involved in many facets of cellular regulation; activation of STK 16 plays a crucial role in the migration of cancer cells. Therefore, it is a novel target for the discovery of anticancer agents. Herein, virtual screening and dynamics simulation were used to screen a large library of natural compounds against STK 16 using Schrodinger suit 2021-2 and GROMACS 2021.6. The results predicted five molecules with high binding affinity against the target, with NPC132329 (Arcyriaflavin C) and NPC160898 having higher binding affinity and molecular mechanics generalized born surface area (MM/GBSA), suggesting that it is better than the standard inhibitor. The molecular dymanics (MD) simulation studies showed that the STK 16-NPC132329 complex has the lowest root mean square deviation, and STK 16-NPC160898 was the most stable compared with the standard drug and selective STK 16 inhibitor. The minimal fluctuation was observed in the STK 16-NPC132329 and STK 16-NPC160898 complexes based on the root mean square fluctuation trajectory with NPC132329 and NPC160898 forming 2 and 3 hydrogen bonds respectively with the amino acid residue of the target's binding site. Overall, NPC132329 and NPC160898 are better STK 16 inhibitors than the standard drug and selective inhibitor, which can be further studied to discover novel anticancer drugs.

Crucial Structural Understanding for Selective HDAC8 Inhibition: Common Pharmacophores, Molecular Docking, Molecular Dynamics, and Zinc Binder Analysis of selective HDAC8 inhibitors.

Overexpression of HDAC8 was observed in various cancers and inhibition of HDAC8 has emerged as a promising therapeutic approach in recent decades. This review aims to facilitate the discovery of novel selective HDAC8 inhibitors by analyzing the structural scaffolds of 66 known selective HDAC8 inhibitors, along with their IC50 values against HDAC8 and other HDACs. The inhibitors were clustered based on structural symmetry, and common pharmacophores for each cluster were identified using Phase. Molecular docking with all HDACs was performed to determine binding affinity and crucial interacting residues for HDAC8 inhibition. Representative inhibitors from each cluster were subjected to molecular dynamics simulation to analyze RMSD, RMSF, active site amino acid residues, and crucial interacting residues responsible for HDAC8 inhibition. The study reviewed the active site amino acid information, active site cavities of all HDACs, and the basic structure of Zn2+ binding groups. Common pharmacophores identified included AADHR_1, AADDR_1, ADDR_1, ADHHR_1, and AADRR_1. Molecular docking analysis revealed crucial interacting residues: HIS- 142, GLY-151, HIS-143, PHE-152, PHE-20 in the main pocket, and ARG-37, TYR-100, TYR-111, TYR-306 in the secondary pocket. The RMSD of protein and RMSF of active site amino acid residues for stable protein-ligand complexes were less than 2.4 Å and 1.0 Å, respectively, as identified from MD trajectories. The range of Molecular Mechanics Generalized Born Surface Area (MMGBSA) ΔG predicted from MD trajectories was between -15.8379 Å and -61.5017 Å kcal/mol. These findings may expedite the rapid discovery of selective HDAC8 inhibitors subject to experimental evaluation.

Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor-MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.

Computational Design of Novel Tau-Tubulin Kinase 1 Inhibitors for Neurodegenerative Diseases.

The tau-tubulin kinase 1 (TTBK1) protein is a casein kinase 1 superfamily member located at chromosome 6p21.1. It is expressed explicitly in the brain, particularly in the cytoplasm of cortical and hippocampal neurons. TTBK1 has been implicated in the phosphorylation and aggregation of tau in Alzheimer's disease (AD). Considering its significance in AD, TTBK1 has emerged as a promising target for AD treatment. In the present study, we identified novel TTBK1 inhibitors using various computational techniques. We performed a virtual screening-based docking study followed by E-pharmacophore modeling, cavity-based pharmacophore, and ligand design techniques and found ZINC000095101333, LD7, LD55, and LD75 to be potential novel TTBK1 lead inhibitors. The docking results were complemented by Molecular Mechanics/Generalized Born Surface Area (MMGBSA) calculations. The molecular dynamics (MD) simulation studies at a 500 ns scale were carried out to monitor the behavior of the protein toward the identified ligands. Pharmacological and ADME/T studies were carried out to check the drug-likeness of the compounds. In summary, we identified a new series of compounds that could effectively bind the TTBK1 receptor. The newly designed compounds are promising candidates for developing therapeutics targeting TTBK1 for AD.

Epigallocatechin gallate and curcumin inhibit Bcl-2: a pharmacophore and docking based approach against cancer

The protein Bcl-2, well-known for its anti-apoptotic properties, has been implicated in cancer pathogenesis. Identifying the primary gene responsible for promoting improved cell survival and development has provided compelling evidence for preventing cellular death in the progression of malignancies. Numerous research studies have provided evidence that the abundance of Bcl-2 is higher in malignant cells, suggesting that suppressing Bcl-2 expression could be a viable therapeutic approach for cancer treatment. In this study, we acquired a compound collection using a database that includes constituents from Traditional Chinese Medicine (TCM). Initially, we established a pharmacophore model and utilized it to search the TCM database for potential compounds. Compounds with a fitness score exceeding 0.75 were selected for further analysis. The Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis identified six compounds with favorable therapeutic characteristics. The compounds that successfully passed the initial screening process based on the pharmacodynamic model were subjected to further evaluation. Extra-precision (XP) docking was employed to identify the compounds with the most favorable XP docking scores. Further analysis using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method to calculate the overall free binding energy. The binding energy between the prospective ligand molecule and the target protein Bcl-2 was assessed by a 100 ns molecular dynamics simulation for curcumin and Epigallocatechin gallate (EGCG). The findings of this investigation demonstrate the identification of a molecular structure that effectively inhibits the functionality of the Bcl-2 when bound to the ligand EGCG. Consequently, this finding presents a novel avenue for the development of pharmaceuticals capable of effectively addressing both inflammatory and tumorous conditions.

Molecular docking and molecular dynamics studies of Glu‐Glu‐Arg, Glu‐Pro‐Arg, and Pro‐Arg‐Pro tripeptides to reveal their anticancer and antiviral potentials

AbstractBioactive peptides have been emerging as drug candidates with increasing importance in the last few decades. In this study, to evaluate the anticancer and antiviral properties of EER (Glu‐Glu‐Arg), EPR (Glu‐Pro‐Arg), and PRP (Pro‐Arg‐Pro) tripeptides, firstly their conformation preferences were searched, and the most stable optimized structure of each tripeptide was determined, using the molecular mechanics force field (MMFF) method and the Spartan06 program. Afterwards, each tripeptide was docked to SARS‐CoV‐2 spike protein receptor‐binding domain (6M0J), SARS‐CoV‐2 main protease (6M03, 6LU7), spike glycoprotein (6VXX), DNA (1BNA), integrins (4WK0, 3ZDX, 1JV2) and epidermal growth factor receptor tyrosine kinase (4HJO). Moreover, molecular dynamics (MD) simulations were performed to validate the stability of the EER, EPR and PRP tripeptides docked to SARS‐CoV‐2 main protease, MPro (6M03) and epidermal growth factor receptor tyrosine kinase (4HJO) within 100 ns time scale and ligand‐receptor interactions were evaluated. The metrics root‐mean‐square deviation, root‐mean‐square fluctuation, intermolecular hydrogen bonding, and radius of gyration revealed that the EER, EPR, and PRP tripeptides form energetically stable complexes with the target proteins. The binding free energies were calculated by the combination of Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Molecular Mechanics/Poisson‐Boltzmann Surface Area (MM‐PBSA) methods (MM/PB(GB)SA). Principal Component Analysis on MD data was performed to evaluate the energy and structural information of the tripeptide‐protein complexes. Additionally, in‐silico structure‐based pharmacological predictions were made and the anticancer and antibacterial activities of the tripeptides were predicted.

Spondias mombin flavonoids showed super-binder ability with downstream molecular targets of Parkinson's disease: A structural study

Spondias mombin is a prominent botanical resource and has garnered recognition within folkloric therapy. Parkinson's disease (PD), characterized by dopaminergic neuron attrition in the substantia nigra, manifests as motor anomalies like tremors, rigidity, and bradykinesia. This study capitalizes on S. mombin's reservoir of 100 characterized phytocompounds and employs computational methodologies to interrogate their potential with 35 PD-associated target proteins. Employing a multifaceted approach, we engaged in molecular docking, ADMET predictions, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) evaluations, Density Functional Theory (DFT), and Molecular Dynamic Simulations (MDS). This comprehensive framework facilitated insightful structural assessments and predictive analyses. Impressively, flavonoids hailing from S. mombin, including quercetin, catechin, ellagic acid, and epicatechin, showed optimal binding affinities for PD-related target proteins. Moreover, these identified ligands exhibited minimal signs of mutagenicity, tumorigenicity, or irritancy, except for quercetin, which displayed elevated tumorigenic potential. Notably, quercetin and dopamine exhibited varying band gap energies, with quercetin the lowest (3.63 eV) and dopamine the highest (5.76 eV) values. MDS result suggests a synergistic outcome based on the RMSD and RMSF graphs for quercetin highlighting it as the best of all including the co-ligand. In a collective sense, our findings present S. mombin as a promising reservoir of active pharmaceutical ingredients, warranting further exploration for novel PD therapeutic avenues. Consequently, this study underscores the enhanced efficacy of phyto-ligands sourced from S. mombin, advocating their optimization as potential drug candidates.