End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design

Insight into the interaction of serum albumin with antihypertensive peptide Val-Ala-Pro from bovine casein hydrolysate based on the biolayer interferometry, multi-spectroscopic analysis and computational evaluation

Food-derived angiotensin-converting enzyme inhibitory peptide (ACEIP) has an effect in supportive therapeutic on hypertension. Bovine serum albumin (BSA) as a model transporter protein to explore the interaction mechanisms with casein-hydrolyzed ACEIP Val-Ala-Pro (VAP) by multi-spectroscopic, biolayer interferometry (BLI), isothermal titration calorimetry (ITC), molecular docking, and molecular dynamics simulations. Multi-spectroscopic analysis showed that the non-covalent complexes formed by VAP and BSA resulted in decreased hydrophobicity and α-helix contents on BSA, revealing the unfolding of the BSA structure. BLI revealed the reversible binding process of BSA to VAP. ITC confirmed that the combination of VAP to BSA was a spontaneous process mainly driven by entropy. Molecular docking and molecular dynamic simulations showed that VAP was primarily bound in site II of BSA by hydrogen bonding, hydrophobic interactions, van der Waals force, and electrostatic force. This study provides a systematic method to reveal the structure-activity relationship of ACEIPs.

Insight into the enhancement and mechanism of saltiness perception by salty peptides from bovine bone

Food-derived salty peptides have been considered promising substitutes for sodium salt. In this work, three novel salty dipeptides Asp-Pro (DP), Asp-Arg (DR), and Arg-Glu (RE) were identified from bovine bone hydrolysates. The salt reduction rates were 76.85 %, 77.28 %, and 73.72 % by the three peptides (2 mg/mL) in a NaCl concentration of 0.203 g/100 mL, respectively. According to Stevens' law, a non-linear relationship between saltiness intensity and concentration was quantified, showing a slower increase in the sensory intensity perception compared with the changes in physical concentration (β < 1). In molecular detail, electrostatic energy and van der Waals energy were the main energetic contributions to forming stable complexes. The binding of salty peptides to TMC4 was driven by hydrogen bonding and salt bridge, and the main binding sites were Glu319, Ala579, and Thr581. These results could provide new insight into the salt-enhancing property and interaction mechanism of salty peptides as novel sodium substitutes.

Discovery of novel fused-heterocycle-bearing diarypyrimidine derivatives as HIV-1 potent NNRTIs targeting tolerant region I for enhanced antiviral activity and resistance profile

As an important part of anti-AIDS therapy, HIV-1 non-nucleoside reverse transcriptase inhibitors are plagued by resistance and toxicity issues. Taking our reported XJ-18b1 as lead compound, we designed a series of novel diarypyrimidine derivatives by employing a scaffold hopping strategy to discover potent NNRTIs with improved anti-resistance properties and drug-like profiles. The most active compound 3k exhibited prominent inhibitory activity against wild-type HIV-1 (EC50 = 0.0019 μM) and common mutant strains including K103 N (EC50 = 0.0019 μM), L100I (EC50 = 0.0087 μM), E138K (EC50 = 0.011 μM), along with low cytotoxicity and high selectivity index (CC50 = 21.95 μM, SI = 11478). Additionally, compound 3k demonstrated antiviral activity against HIV-2 with EC50 value of 6.14 μM. The enzyme-linked immunosorbent assay validated that 3k could significantly inhibit the activity of HIV-1 reverse transcriptase (IC50 = 0.025 μM). Furthermore, molecular dynamics simulation studies were performed to illustrate the potential binding mode and binding free energy of the RT-3k complex, and in silico prediction revealed that 3k possessed favorable drug-like profiles. Collectively, 3k proved to be a promising lead compound for further optimization to obtain anti-HIV drug candidates.

Molecular basis of the CYFIP2 and NCKAP1 autism-linked variants in the WAVE regulatory complex

The WAVE regulatory pentameric complex regulates actin remodeling. Two components of it (CYFIP2 and NCKAP1) are encoded by genes whose genetic mutations increase the risk for autism spectrum disorder (ASD) and related neurodevelopmental disorders. Here, we use a newly developed computational protocol and hotspot analysis to uncover the functional impact of these mutations at the interface of the correct isoforms of the two proteins into the complex. The mutations turn out to be located on the surfaces involving the largest number of hotspots of the complex. Most of them decrease the affinity of the proteins for the rest of the complex, but some have the opposite effect. The results are fully consistent with the available experimental data. The observed changes in the WAVE regulatory complex stability might impact on complex activation and ultimately play a role in the aberrant pathway of the complex, leading to the cell derangement associated with the disease.

Probing the interaction mechanisms between three β-lactam antibiotics and penicillin-binding proteins of Escherichia coli by molecular dynamics simulations

The presence of antibiotic residues in the aquatic environments poses great potential risks to the aquatic organisms, and even human health. Elucidating the interaction mechanisms between antibiotics and biomacromolecules is crucial for accurately assessing and preventing their potential risks. Therefore, the toxicity of three beta-lactam antibiotics on Escherichia coli (E. coli) was investigated by using the time-dependent toxicity microplate analysis method in this study. Then, molecular docking and molecular dynamics simulation technologies were used to elucidate the potential molecular interactions between β-lactam antibiotics and penicillin-binding proteins of E. coli, and their correlation with the physical and chemical behaviors observed in the physiological and biochemical experiments. The results show that three antibiotics exert inhibitory effects on E. coli cells by modifying their membrane permeability, and even more severe cell damage including rupture, wrinkling, adhesion, indentation, elongation and size alterations. But, toxic effect of the three antibiotics on E. coli varies, and toxicity order is followed by meropenem > cefoperazone > amoxicillin. Van der Waals forces play a vital role in the molecular interactions between the three antibiotics penicillin binding protein of E. coli and the sequence of binding free energy is consistent with the observed toxicity order. Shape compensation is the principal determinant for the binding of antibiotics to penicillin binding proteins, which pertains to the drug-induced alteration in the three-dimensional conformation of penicillin binding proteins.

Mechanisms for translating chiral enantiomers separation research into macroscopic visualization

Chirality is a common phenomenon in nature, including the dominance preference of small biomolecules, the special spatial conformation of biomolecules, and the biological and physiological processes triggered by chirality. The selective chiral recognition of molecules in nature from up-bottom or bottom-up is of great significance for living organisms. Such as the transcription of DNA, the recognition of membrane proteins, and the catalysis of enzymes all involve chiral recognition processes. The selective recognition between these macromolecules is mainly achieved through non covalent interactions such as hydrophobic interactions, ammonia bonding, electrostatic interactions, metal coordination, van der Waals forces, and π-π stacking. Researchers have been committed to studying how to convert this weak non covalent interaction into macroscopic visualization, which has further understood of the interactions between chiral molecules and is of great significance for simulating the interactions between molecules in living organisms. This article reviews several models of chiral recognition mechanisms, the interaction forces involved in the chiral recognition process, and the research progress of chiral recognition mechanisms. The outlook in this review points out that studying chiral recognition interactions provides an important bridge between chiral materials and the life sciences, providing an ideal platform for studying chiral phenomena in biological systems.

Reshaping the substrate-binding pocket of acyl-ACP reductase to enhance the production of sustainable aviation fuel in Escherichia coli

To reduce carbon emissions and address environmental concerns, the aviation industry is exploring the use of sustainable aviation fuel (SAF) as an alternative to traditional fossil fuels. In this context, bio-alkane is considered a potentially high-value solution. The present study focuses on the enzymes acyl-acyl carrier protein [ACP] reductase (AAR) and aldehyde-deformylating oxygenase (ADO), which are crucial enzymes for alka(e)ne biosynthesis. By using protein engineering techniques, including semi-rational design and site-directed mutagenesis, we aimed to enhance the substrate specificity of AAR and improve alkane production efficiency. The co-expression of a modified AAR (Y26G/Q40M mutant) with wild-type ADO in Escherichia coli significantly increased alka(e)ne production from 28.92 mg/L to 167.30 mg/L, thus notably demonstrating a 36-fold increase in alkane yield. This research highlights the potential of protein engineering in optimizing SAF production, thereby contributing to the development of more sustainable and efficient SAF production methods and promoting greener air travel.

Dissecting the geometric and hydrophobic constraints of stapled peptides

Stapled peptides are a promising class of molecules with potential as highly specific probes of protein-protein interactions and as therapeutics. Hydrocarbon stapling affects the peptide properties through the interplay of two factors: enhancing the overall hydrophobicity and constraining the conformational flexibility. By constructing a series of virtual peptides, we study the role of each factor in modulating the structural properties of a hydrocarbon-stapled peptide PM2, which has been shown to enter cells, engage its target Mouse Double Minute 2 (MDM2), and activate p53. Hamiltonian replica exchange molecular dynamics (HREMD) simulations suggest that hydrocarbon stapling favors helical populations of PM2 through a combination of the geometric constraints and the enhanced hydrophobicity of the peptide. To further understand the conformational landscape of the stapled peptides along the binding pathway, we performed HREMD simulations by restraining the peptide at different distances from MDM2. When the peptide approaches MDM2, the binding pocket undergoes dehydration which appears to be greater in the presence of the stapled peptide compared with the linear peptide. In the binding pocket, the helicity of the stapled peptide is increased due to the favorable interactions between the peptide residues as well as the staple and the microenvironment of the binding pocket, contributing to enhanced affinity. The dissection of the multifaceted mechanism of hydrocarbon stapling into individual factors not only deepens fundamental understanding of peptide stapling, but also provides guidelines for the design of new stapled peptides.

Identification of novel inhibitors of cancer target telomerase using a dual structure-based pharmacophore approach to virtually screen libraries, molecular docking and validation by molecular dynamics simulations

In about 85% of cancer malignancies, replicative immortality caused by increased telomerase activity makes it an attractive target for developing anticancer therapeutics. However, the lack of approved small-molecule inhibitors rooted in the structural ambiguity of telomerase has impeded drug development for decades. In this study, we have exploited the FVYL pocket in the thumb domain, which plays a key role in the enzyme's processivity. Due to the unavailability of a co-crystalized structure of BIBR1532 with the catalytic hTERT thumb domain, we utilized the molecular dynamics method to identify the precise binding site of the inhibitor. Two pharmacophore models were generated and validated for the putative (Site-I) and newly identified (Site-II) binding pockets which were screened virtually through the ChemDiv anticancer library, Otava drug-like green collection to identify novel lead compounds, and Binding database to screen out thumb domain-specific telomerase inhibitors. The top hits obtained were filtered using drug-likeliness parameters followed by redocking using a three-level screening strategy into their binding site. The structural investigation, molecular docking studies, and confirmatory molecular dynamics revealed that the exact binding site of BIBR1532 is away from the reported FVYL pocket with characteristic interactions conserved. Subsequently, the lead compounds with the highest docking scores and significant interactions in the newly discovered extended FVYL pocket were validated using 100 ns MD simulations. Additionally, cross-validated binding free energy calculations were performed using MM-PB(GB)SA methods followed by PCA and FEL characterization. The identified top lead compounds can be validated in vitro and taken forward for anticancer drug development.

Advanced Mass-Spectra-Based Machine Learning for Predicting the Toxicity of Traditional Chinese Medicines

Traditional Chinese medicine (TCM) has been a cornerstone of health care for centuries, valued for its preventive and therapeutic properties. However, recent decades have revealed significant toxicological concerns associated with TCMs due to their complex chemical compositions. Traditional QSAR (quantitative structure-activity relationships) models, which predict toxicity based on chemical structures, face challenges with the intricate nature of TCM compounds. In this study, we effectively resolved this issue by correlating the toxicity of TCMs with advanced analytical descriptors from electron ionization mass spectra (EI-MS) data. The optimal classification model achieved a balanced accuracy of over 0.74. Through interpretable machine learning models, we identified specific toxic components, such as 13-hexyloxacyclotridec-10-en-2-one and loliolide. We applied molecular dynamics (MD) simulations to explore the interactions of identified toxic components with crucial protein targets, using hepatic cytochrome P450 3A4 as an example. This novel approach not only enhances our understanding of the toxicological profiles of TCMs but also maximizes their therapeutic benefits while minimizing adverse effects. More importantly, our findings support the application of analytical descriptor-based machine learning in predicting the toxicity of unknown mixtures in the real environment.

Designing microplastic-binding peptides with a variational quantum circuit-based hybrid quantum-classical approach

De novo peptide design exhibits great potential in materials engineering, particularly for the use of plastic-binding peptides to help remediate microplastic pollution. There are no known peptide binders for many plastics-a gap that can be filled with de novo design. Current computational methods for peptide design exhibit limitations in sampling and scaling that could be addressed with quantum computing. Hybrid quantum-classical methods can leverage complementary strengths of near-term quantum algorithms and classical techniques for complex tasks like peptide design. This work introduces a hybrid quantum-classical generative framework for designing plastic-binding peptides combining variational quantum circuits with a variational autoencoder network. We demonstrate the framework's effectiveness in generating peptide candidates, evaluate its efficiency for property-oriented design, and validate the candidates with molecular dynamics simulations. This quantum computing-based approach could accelerate the development of biomolecular tools for environmental and biomedical applications while advancing the study of biomolecular systems through quantum technologies.

Essential Considerations for Free Energy Calculations of RNA-Small Molecule Complexes: Lessons from the Theophylline-Binding RNA Aptamer

Alchemical free energy calculations are widely used to predict the binding affinity of small molecule ligands to protein targets; however, the application of these methods to RNA targets has not been deeply explored. We systematically investigated how modeling decisions affect the performance of absolute binding free energy calculations for a relatively simple RNA model system: theophylline-binding RNA aptamer with theophylline and five analogs. The goal of this investigation was 2-fold: (1) understanding the performance levels we can expect from absolute free energy calculations for a simple RNA complex and (2) learning about practical modeling considerations that impact the success of RNA-binding predictions, which may be different from the best practices established for protein targets. We learned that magnesium ion (Mg2+) placement is a critical decision that impacts affinity predictions. When information regarding Mg2+ positions is lacking, implementing RNA backbone restraints is an alternative way of stabilizing the RNA structure that recapitulates prediction accuracy. Since mistakes in Mg2+ placement can be detrimental, omitting magnesium ions entirely and using RNA backbone restraints are attractive as a risk-mitigating approach. We found that predictions are sensitive to modeling experimental buffer conditions correctly, including salt type and ionic strength. We explored the effects of sampling in the alchemical protocol, choice of the ligand force field (GAFF2/OpenFF Sage), and water model (TIP3P/OPC) on predictions, which allowed us to give practical advice for the application of free energy methods to RNA targets. By capturing experimental buffer conditions and implementing RNA backbone restraints, we were able to compute binding affinities accurately (mean absolute error (MAE) = 2.2 kcal/mol, Pearson's correlation coefficient = 0.9, Kendall's τ = 0.7). We believe there is much to learn about how to apply free energy calculations for RNA targets and how to enhance their performance in prospective predictions. This study is an important first step for learning best practices and special considerations for RNA-ligand free energy calculations. Future studies will consider increasingly complicated ligands and diverse RNA systems and help the development of general protocols for therapeutically relevant RNA targets.

Immunoinformatic based designing of highly immunogenic multi-epitope subunit vaccines to stimulate an adaptive immune response against Junin virus

The Junin virus causes Argentine hemorrhagic fever, leading to severe complications such as high fever, malaise, muscle pain, and bleeding disorders, including hemorrhages in the skin and mucous membranes. Neurological issues like confusion, seizures, and coma can also occur. Without prompt and effective treatment, the disease can be fatal, with mortality rates reaching up to 30%. Taking serious measures is essential to mitigate the spread of the disease. Vaccination is the most effective choice to neutralize the Junin virus in the current situation. Consequently, to design the highly immunogenic and non-allergenic multi-epitope subunit vaccine against the Junin virus, we employed the immunoinformatic approach to screen the glycoprotein, nucleoprotein, and RDRP protein for potential immunogenic CTL (Cytotoxic T Lymphocyte), HTL (Helper T Lymphocyte) and B (B Lymphocyte) cell epitopes. Afterward, the predicted epitopes were subjected to 3D modeling and validation. The strong binding affinity of the constructed vaccines with the human TLR3 was confirmed through molecular docking, with scores of - 333 kcal/mol for glycoprotein, - 297 kcal/mol for nucleoprotein, - 308 kcal/mol for RDRP, and - 305 kcal/mol for combined vaccines. Additionally, the binding free energies recorded were - 63.54 kcal/mol, - 64.16 kcal/mol, - 56.81 kcal/mol, and - 51.52 kcal/mol, respectively. Furthermore, the dynamic stability, residual fluctuation, and compactness of vaccine-TLR-3 complexes were confirmed by the molecular dynamic simulation. The codon adaptation index (CAI) values and high GC content confirmed the stable expression of constructed vaccines in the pET-28a ( +) expression vector. The immune simulation analysis demonstrated that administering booster doses of the developed vaccines resulted in a notable increase in IgG, IgM, interleukins, and cytokines levels, indicating effective antigen clearance over time. In conclusion, our study provides preclinical evidence for designing a highly effective Junin virus vaccine, necessitating further in-vitro and in-vivo experiments.

Flavin-Mediated Reductive Deiodination: Conformational Events and Reactivity Pattern in the Active Site of Human Iodotyrosine Deiodinase

Human iodotyrosine deiodinase (hIYD) catalyzes the reductive deiodination of iodotyrosine using a flavin mononucleotide cofactor to maintain the iodine concentration in the body. Mutations in the hIYD gene are linked to human hypothyroidism, emphasizing its role in thyroid function regulation. The present work employs microsecond-scale molecular dynamics simulations and quantum chemical calculations to elucidate the conformational dynamics and reactivity in the active site at various stages of hIYD enzymatic cycle. The flavin is found to employ a unique butterfly motion of its isoalloxazine ring accompanied by a novel active-and-resting state of its ribose 2'-OH group at different stages of the enzymatic cycle. The flavin dynamics are found to control substrate binding affinity, the active site lid closure, and NADPH recognition. The predicted hIYD model shows enhanced stabilization of NADPH due to additional interactions with the N-terminal and intermediate domains. The enzyme uses a group of basic residues (R100, R101, R104, K182, and R279) to stabilize flavin in different stages of catalysis, suggesting potential mutations to control enzyme activity. The reactivity descriptors and stereoelectronic analysis predict the N5 nitrogen of flavin as a proton source during the reductive deiodination, while the anisotropic charge distribution on the halogen atom has negligible structural and electronic effects. The present findings provide key insights into the molecular basis of hIYD activity and lay the groundwork for future research aimed at therapeutic interventions and industrial applications.

Structure-based virtual screening of Trachyspermum ammi metabolites targeting acetylcholinesterase for Alzheimer's disease treatment

In recent decades, Alzheimer's disease (AD) has garnered significant attention due to its rapid global prevalence. The cholinergic hypothesis posits that the degradation of acetylcholine by acetylcholinesterase (AChE) contributes to AD development. Despite existing anti-AChE drugs, their adverse side effects necessitate new agents. This study analyzed 150 bioactive phytochemicals from Trachyspermum ammi using structure-based drug design and various in-silico tools to identify potent anti-AChE compounds. Compounds were screened for drug-likeness (QEDw ≥50%) and bioavailability (≥55%) and underwent toxicity profiling via the ProTox-II server. Selected compounds were prepared for molecular docking with the human AChE protein as the receptor. Viridifloral, 2-Methyl-3-glucosyloxy-5-isopropyl phenol, Alpha-Curcumene, and Sterol emerged as top candidates with high AChE affinity. These results were validated by molecular dynamics simulations, confirming stable interactions. The hit compounds were further evaluated for drug-likeness using Lipinski's rule and ADMET properties, confirming favorable pharmacokinetic profiles. DFT optimization analyzed frontier molecular orbitals and electrostatic potential, demonstrating favorable chemical reactivity and stability. This study suggests that these identified compounds could be novel nature-derived AChE inhibitors, potentially contributing to AD treatment. However, further in-vitro and in-vivo studies are necessary to confirm their efficacy in biological systems. Future research will focus on developing these compounds into safe and effective drugs to combat Alzheimer's disease.

From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy

Accurate calculation of solvation energies has long fascinated researchers, but complex interactions within bulk water molecules pose significant challenges. Currently, molecular solvation energy calculations are mostly based on implicit solvent approximations in which the solvent molecules are treated as continuum dielectric media. However, the implicit solvent approach is not ideal because it lacks certain real solvation effects, such as that of the first solvation shell, etc. Here, we propose an explicit solvent approach, interaction-reorganization solvation (IRS) method, for molecular solvation energy calculations. The IRS approach achieves predictive accuracy comparable to that of the widely recognized solvation model based on the density (SMD) method and is significantly more accurate than that of the Poisson-Boltzmann/generalized Born surface area (PB/GBSA) methods. This is demonstrated in both the correlation coefficient and the mean absolute error (MAE) with respect to the experimental data. The IRS method is based on molecular dynamics simulation in explicit solvent and does not need to solve Poisson-Boltzmann or Schrödinger equations. On the other hand, the accuracy of the IRS method does depend on the accuracy of the molecular force field used in MD simulations. We expect that the IRS method will be very useful for the solvation energy calculations of molecules.

Exploring the impact of variations in the mucolipin1 protein that result in mucolipidosis type 4 using the technique of molecular docking and dynamics simulation

Mucolipidosis type IV (MLIV) is classified as an exceptionally autosomal recessive condition due to a change in MCOLN1 that encodes the mucolipin-1 protein. ML-1 is a membrane protein comprising 6 Trans regions, which are situated at the LELs, a serine lipase area, and a nuclear localization sign. The characteristic features of the ML4 patients are mental retardation and skeletal deformities due to an increase in lipid molecules in the brain, other tissues, and organs. The fundamental goal of the work is to identify the most significant amino acid variants via a computational pipeline. The twenty-three amino acid variants that are responsible for the condition were retrieved from the public domain: L106P and L447P amino acid variants, with the following categories: extremely conserved, highly pathogenic, most interfering with protein function, more structurally unstable, and having promising Phenotyping characteristics was scrutinized from the series of bioinformatics tools that denote its significant nature. A docking and dynamics study was initiated to identify the interaction profiling and interatomic simulation between the Native, L106P, and L447P and the ligand ML-SA1 (it was known to ease the fatty acid buildup in lysosomes of cellular models of Mucolipidosis type IV) and had a score of -6.19, -5.12, and -5.21 kcal/mol, followed by a duplicate 100-ns run trajectory results, which assisted in detecting the stable nature of all the complex structures. Hence, this work helps to recognize the significant role of the scrutinized amino acid variants and, on the other hand, the stable nature of the ligand using standard computational tools.

Elucidating the mechanisms of a herbal compound fumarine and its modulation on the estrogen receptor 1

Stroke-related numbness and weakness (SRNW) are resultant disabilities following a stroke episode and may present with muscle weakness, numbness, tightness, spasticity, and pain in up to 85% of patients. Huangqi Guizhi Wuwu Decoction (HGWD) has been widely investigated to manage the sensorimotor deficiencies at the herb and formula level. However, detailed molecular mechanisms of its constituents are presently lacking. This project employed computational molecular modelling and docking methods to identify candidate compounds of HGWD which may serve as effective modulators of target proteins involved in SRNW. Estrogen Receptor 1 was identified as a promising target for HGWD compounds, while the herbal compound fumarine, a constituent of Jujubae Fructus, was predicted to exhibit high binding affinity and favourable ligand-receptor interactions with ESR1. There is currently a lack of scientific evidence for specific atomic-level interactions between ESR1 and this compound. Therefore, molecular docking and molecular dynamics simulations were used to elucidate the interaction mechanisms of fumarine with ESR1; and the molecular-level structural and functional consequences of ligand binding. Ligand-receptor contact analysis and free energy decomposition calculations identified Glu419 and Leu38 as stable hydrogen bond partners, while favourable contributions to the binding free energy include in Met421 (-10.74 kJ/mol) and Leu525 (-10.02 kJ/mol). This work provides the basis for further studies on discovering lead compounds which modulate the activity of ESR1.

Insights into in vitro and in silico studies of α-glucosidase inhibitors isolated from the leaves of Grewia optiva (Malvaceae)

α-Glucosidase plays a critical role in glucose metabolism by breaking down complex carbohydrates into simpler sugars for intestinal absorption. Due to the side effects of current α-glucosidase inhibitors, there is increasing interest in exploring alternative therapeutic options. Inspired by the traditional uses of Grewia optiva J.R.Drumm. ex Burret (Malvaceae family) as an anti-diabetic herb, we isolated gnaphaffine A (1), a cyclic glycosylated homolignan, together with kaempferol derivatives (trans-tiliroside 2, cis-tiliroside 3, and astragalin 4) from the ethyl acetate fraction. In vitro antioxidant assays revealed that 1 exhibited anti-DPPH• and anti-ABTS+• activity (IC50 of 39.42 and 52.84 μg/mL, respectively), comparable to ascorbic acid (IC50 of 43.34 and 47.56 μg/mL, respectively). Moreover, 1 demonstrated a seven-fold stronger inhibition of α-glucosidase activity than acarbose (IC50 of 8.2 and 57.8 μg/mL, respectively). Importantly, 1 was non-toxic to AC16 normal cardiomyocyte cell lines. Computational analyses identified two key factors contributing to the α-glucosidase inhibitory activity of 1: (a) hydrogen bonding interactions with catalytic residues (E277 and D352) and (b) a calculated ∆Gbind of -51.20 kcal/mol. Furthermore, 3 showed the most favorable in silico binding profile, with the highest ∆Gbind (-55.89 kcal/mol) and higher hydrogen bond occupancy compared to 1 and 2. These findings suggest that 1 and 3 may serve as promising lead compounds for the development of new α-glucosidase drugs.

Mapping the Binding Hotspots and Transient Binding Pockets on V-Domain Immunoglobulin Suppressor of T Cell Activation Protein Surface

V-domain immunoglobulin suppressor of T cell activation (VISTA), an inhibitory immune checkpoint present on both immune and tumor cells, has emerged as a highly promising target for cancer therapy due to its potential to overcome resistance encountered with existing immune checkpoint treatments. VSIG-3 is determined as an inhibitory ligand for VISTA, leading to the suppression of T cell proliferation. However, hotspots between VISTA/VSIG-3 protein-protein interaction remain ambiguous, mainly attributed to the lack of the structure of the VISTA/VSIG-3 complex. Therefore, in this study, in order to determine the energetic contributions of the interfacial residues on VISTA, we first constructed VISTA/VSIG-3 complex models by the protein docking method, followed by molecular dynamics simulations, binding free-energy decomposition, and alanine scanning. Results suggested that the putative hotspots in VISTA comprise residues His32, Tyr37, Thr35, Glu47, Val48, Gln49, Glu53, Arg54, Gln73, His122, and His126. Moreover, the distribution of the hotspots was clustered into two regions (hot regions I and II), and by using the TRAPP tool, transient subpockets within the hot regions were identified. Furthermore, conformational states of the binding pockets exhibiting druggability scores higher than those observed in the crystal structure were found. Overall, we hope that the findings outlined in this study can be used to facilitate the development of inhibitors targeting the VISTA/VSIG-3 immune checkpoint pathway in the future.

Antioxidant effect, DNA-binding, and transport of the flavonoid acacetin influenced by the presence of redox-active Cu(II) ion: Spectroscopic and in silico study

Acacetin (AC) is a natural polyphenol from the group of flavonoids. It is well established that the behavior of flavonoids depends on the presence of redox-active substances; therefore, we aim to investigate their biological activity following the interaction with Cu(II) ion. Our study demonstrates that AC can effectively bind Cu(II) ions, as confirmed by UV-Vis and EPR spectroscopy as well as DFT calculations. AC appears as a potent scavenger against the model ABTS radical cation by itself, but this ability is significantly limited upon Cu(II) coordination. The possible mild synergistic effect of AC in the presence of vitamin C and glutathione was also shown by the ABTS•+ test. In contrast, an inhibitory effect was observed in the presence of Cu(II) ions. The equimolar addition of AC to the model Fenton-like system containing Cu(II) did not have a noticeable effect on the concentration of hydroxyl radicals produced, but in its excess the formation of •OH decreased, as proved by EPR spin trapping. Absorption titrations and gel electrophoresis revealed effective binding to calf thymus (CT)-DNA with a stronger interaction for the Cu(II)-AC complex. The detailed mode of binding to biomolecules was described using molecular docking and molecular dynamics. Obtained results indicate that the double helix of DNA unwinds after interaction with the Cu(II)-AC complex. Fluorescence spectroscopy, employing human serum albumin (HSA), suggested a potential transport capacity for both AC and its Cu(II) complex.

Identification of Novel Drug Molecules Against NS3-Like Helicase Enzyme of Alongshan Virus

Alongshan virus (ALSV) is a novel tick-borne virus associated with human diseases. The ALSV is a segmented flavivirus from the family Flaviviridae. It is currently considered as tick-borne arbovirus. There is a high incidence of fever and headache among patients with ALSV infection, and some patients also present with fatigue, coma, depression, nausea, myalgia/arthralgia, and skin rashes. Neither a licensed vaccine nor a drug is currently available to treat ALSV. The development of new, practical, and innovative therapeutic approaches is needed to overcome the emergence of the pathogen. Research on drugs remains a complex, time-consuming, and expensive. The field of drug development has undergone a revolution due to the use of computational approaches, which provide several benefits that speed up and improve the process of developing novel drugs. The goal of this study is to identify novel drug-like molecules against NS3-like helicase enzyme of Alongshan virus. Using molecular docking, the binding potential of the top three ligands to the specified target was determined. Molecular dynamic simulations were used to identify the stabilities of the best-docked conformations followed by energy calculations and ADMET analysis. Three potential and promising compounds were identified by performing structure-based virtual screening of non-structural protein 3 (NS3) like helicase of Alongshan virus. The best-docked complexes identified through virtual screening were BDC-23169381, BDB-26412846, BDB-2641954. All these compounds had good pharmacokinetics characteristics and were identified as drug like.

Discovery of potent LRRK2 inhibitors by ensemble virtual screening strategy and bioactivity evaluation

Leucine-rich repeat kinase 2 (LRRK2) has been reported to be associated with familial and idiopathic Parkinson's disease (PD) risk and is a promising target for drug discovery against PD. To identify novel and effective LRRK2 inhibitors, an ensemble virtual screening strategy by combining fingerprint similarity, complex-based pharmacophore and structure-based molecular docking was proposed and applied. Using this strategy, we finally selected 25 compounds from ∼1.7 million compounds for in vitro and in vivo tests. Firstly, the kinase inhibitory activity tests of compounds based on ADP-Glo assay identified three most potent compounds LY2023-19, LY2023-24 and LY2023-25 with IC50 of 556.4 nM, 218.1 nM and 22.4 nM for LRRK2 G2019S mutant, respectively. The further cellular experiments also indicated that three hit compounds significantly inhibited Ser935 phosphorylation of both wide-type and G2019S LRRK2 with IC50 ranging from 27 nM to 1674 nM in HEK293T cells. The MD simulations of three compounds and G2019S LRRK2 showed the hydrogen bond formed by Glu1948 and Ala1950 is crucial for the binding of LRRK2. Afterwards, 6-OHDA-induced PD zebrafish model was constructed to evaluate the neuroprotective effects of hit compounds. The locomotion of the 6-OHDA treated zebrafish larvae was improved after treatment with LY2023-24. The obtained results can provide valuable guidance for the development of PD drugs by targeting LRRK2.

Multi-method computational evaluation of the inhibitors against leucine-rich repeat kinase 2 G2019S mutant for Parkinson's disease

Leucine-rich repeat kinase 2 G2019S mutant (LRRK2 G2019S) is a potential target for Parkinson's disease therapy. In this work, the computational evaluation of the LRRK2 G2019S inhibitors was conducted via a combined approach which contains a preliminary screening of a large database of compounds via similarity and pharmacophore, a secondary selection via structure-based affinity prediction and molecular docking, and a rescoring treatment for the final selection. MD simulations and MM/GBSA calculations were performed to check the agreement between different prediction methods for these inhibitors. 331 experimental ligands were collected, and 170 were used to build the structure-activity relationship. Eight representative ligand structural models were employed in similarity searching and pharmacophore screening over 14 million compounds. The process for selecting proper molecular descriptors provides a successful sample which can be used as a general strategy in QSAR modelling. The rescoring used in this work presents an alternative useful treatment for ranking and selection.

AI screening and molecular dynamic simulation-driven identification of novel inhibitors of TGFßR1 for pancreatic cancer therapy

Pancreatic cancer, with a 5-year survival rate below 10 %, is one of the deadliest malignancies. The TGF-ß pathway plays a crucial role in this disease, making it a key target for therapeutic intervention. Clinical trials targeting TGF-β have faced challenges of toxicity and limited efficacy, highlighting the need for more potent small molecule inhibitors. We selected TGFßR1 as the drug target to inhibit TGF-ß signaling in pancreatic cancer. A multi-faceted approach was employed, commencing with AI-driven screening techniques to rapidly identify potential TGFßR1 inhibitors from vast compound libraries, including the ZINC and ChEMBL databases. AI-screened compounds were further validated through structure-based high-throughput virtual screening (HTVS) to evaluate their binding affinity to TGFßR1. In addition to this, a dedicated library of anticancer compounds (65,000 compounds) and protein kinase inhibitors (36,324 compounds) were also used for HTVS. Subsequently, pharmacokinetic profiling narrowed the selection to 40 hit compounds. Five hit compounds were chosen based on binding affinity, non-bonded interactions, stereochemistry, and pharmacokinetic profiles for molecular dynamics (MD) simulations. Trajectory analysis showed that residues HIS283, ASP351, LYS232, SER280, ILE211, and LYS213 within TGFßR1's active site are crucial for ligand binding through hydrogen bonds and hydrophobic interactions. Principal component analysis (PCA) and Dynamic cross-correlation matrix (DCCM) analysis were used to evaluate the receptor's dynamic response to the hit compounds. The simulation data revealed that compounds 1, 2, 3, 4, and 5 formed stable complexes with TGFßR1. Notably, post-MDS MM-GBSA analysis showed that compounds 4 and 5 exhibited exceptionally strong binding energies of -81.0 kcal/mol and -85.5 kcal/mol, respectively. The comprehensive computational analysis confirms compounds 4 and 5 as promising TGFßR1 hits with potential therapeutic applications in development of new treatments for pancreatic cancer.

Identification and anticoagulant mechanisms of novel factor XIa inhibitory peptides by virtual screening of a in silico generated deep-sea peptide database

The objective of this study was to identify novel anticoagulant peptides from the deep-sea using multiple in silico methods, and to investigate their inhibitory activity and molecular mechanisms. A deep-sea peptide database was firstly constructed by performing virtual proteolysis on protein sequences from animals inhabiting deep-sea hydrothermal vents and cold seeps. Candidate anticoagulant peptides were identified through molecular docking and binding free energy screening against FXIa as the target. Two novel anticoagulant peptides, PRNIF (IC50 = 0.67 mM) and GNDRCL (IC50 = 1.52 mM), were identified, and their anticoagulant activities were verified in vitro. PRNIF was demonstrated to be a noncompetitive inhibitor of FXIa, and caused significant prolongation of thrombin time (TT) and activated partial thromboplastin time (APTT), whereas GNDRCL markedly prolonged the APTT only. Molecular dynamics simulations demonstrated considerable conformational shifts of both anticoagulant peptides when bound to the active sites of FXIa. The lowest energy binding poses of the FXIa-peptide complexes for PRNIF and GNDRCL exhibited comparable numbers of hydrogen bonds and binding free energies. However, occupancy analysis revealed completely distinct stability characteristics of the hydrogen bond interactions. The conserved residue Asp569 in the S1 pocket of FXIa formed strong and stable hydrogen bonds as well as a salt bridge with the arginine residues of PRNIF, which were not observed in the FXIa-GNDRCL complex. To our knowledge, PRNIF represented the first FXIa inhibitory peptide derived from the deep-sea, which may contribute to the development and utilization of deep-sea peptides resources. Two deep-sea peptides may potentially serve as an alternative food-derived ingredient that could be utilized for thrombosis prevention.

Discovery of novel BfmR inhibitors restoring carbapenem susceptibility against carbapenem-resistant Acinetobacter baumannii by structure-based virtual screening and biological evaluation

The emergence and spread of Acinetobacter baumannii pose a severe threat to public health, highlighting the urgent need for the next generation of therapeutics due to its increasing resistance to existing antibiotics. BfmR, a response regulator modulating virulence and antimicrobial resistance, shows a promising potential as a novel antimicrobial target. Developing BfmR inhibitors may propel a new therapeutic direction for intractable infection of resistant strains. In this study, we conducted a structure-based hierarchical virtual screening pipeline combining molecular docking, molecular dynamic simulation, and MM/GBSA calculation to sift the Specs chemical library and finally discover three novel potential BfmR inhibitors. The three hits can reduce the MIC of meropenem for the carbapenem-resistant Acinetobacter baumannii (CRAB) strain ZJ06. Similar to the BfmR knockout strain, Cmp-98 was demonstrated to downregulate the expression of K locus genes, indicating it as a BfmR inhibitor. Bacteria underwent harmful morphological changes after treatment with these inhibitors. Molecular dynamic simulations found that all the hits tend to dynamically bind to different positions of the phosphorylation site of BfmR. Wherein we identified a potential inhibitory-binding cleft, beside a possible activated binding cleft at the edge of the phosphorylation site. Restraining the ligand binding poses may help exert inhibitory effects. This study reports a group of new scaffold BfmR inhibitors, offering new insights for novel antibiotic therapeutics against CRAB.

Natural α-Methylene-γ-Butyrolactone Analogues: Synthesis and Evaluation of Isoaurone Derivatives as Antifungal Agents

In order to develop novel, efficient and green fungicides, a series of novel isoaurone derivatives were designed and synthesized, which were characterized by 1H and 13C NMR, high-resolution mass spectra and melting points. The target compounds showed different inhibitory activities against seven plant pathogenic fungi. Compounds 1, 12, 17, 20, 22, 24 and intermediate A showed more than 90 % inhibition rates against S. s at 50 mg/L. Interestingly, compound 22 and intermediate A showed the great inhibitory effect against S. s with EC50 values of 4.65 and 4.24 mg/L, which were better than the lead compound isoaurone (EC50=15.62 mg/L). The EC50 values of compounds 17 and 24 against B. c were 13.94 and 22.13 mg/L. Moreover, compound 19 displayed significant antifungal activity against G. g with the EC50 value of 11.88 mg/L. Theoretical calculations by DFT revealed that the α, β-unsaturated carbonyl bond and the benzyl ring are very importantly linked to the strength of the fungicidal activity. Therefore, this study identified a valuable antifungal lead compound for further development of green fungicides.

Computational insights into human UCP1 activators through molecular docking, MM-GBSA, and molecular dynamics simulation studies

The prevalence of obesity is rapidly increasing worldwide. Brown adipose tissue activates uncoupling protein 1 (UCP1) to generate heat through bypassing ATP synthesis, offering a potential target for obesity treatment. Targeting UCP1 activation to induce thermogenesis through small molecules presents a promising approach for obesity management. In this study, molecular docking of UCP1 activators, using 2,4-dinitrophenol (DNP) as a reference ligand (PDB ID: 8J1N, docking score: -5.343 kcal/mol), identified seven top-scoring compounds: naringin (-7.284 kcal/mol), quercetin (-6.661 kcal/mol), salsalate (-6.017 kcal/mol), rhein (-5.798 kcal/mol), mirabegron (-5.535 kcal/mol), curcumin (-5.479 kcal/mol), and formoterol (-5.451 kcal/mol). Prime MM-GBSA calculation of the top-scored molecule (i.e., naringin) in the docking study showed ΔGBind of -70.48 kcal/mol. Key interactions of these top 7 activators with UCP1 binding pocket residues Trp280, Arg276, Glu190, Arg83, and Arg91 were observed. Molecular dynamics simulations performed for 100 ns confirmed complex stability, with RMSD values below 6 Å. Additionally, most activators showed favorable intestinal absorption (>90 %) and lipophilicity (LogP 2-4), with pKa values supporting their pharmacological potential as UCP1-targeting therapeutics for obesity. These findings provide a foundation for designing potent UCP1 activators by integrating docking scores, interaction profiles, statistical profiles from MD simulations, and physicochemical assessments to develop effective anti-obesity therapies.

Leukotriene B4 receptor 1 (BLT1) activation by leukotriene B4 (LTB4) and E resolvins (RvE1 and RvE2)

Leukotriene B4 (LTB4) is a lipid inflammatory mediator derived from arachidonic acid (AA). Leukotriene B4 receptor 1 (BLT1), a G protein-coupled receptor (GPCR), is a receptor of LTB4. Nonetheless, the resolution of inflammation is driven by specialized pro-resolving lipid mediators (SPMs) such as resolvins E1 (RvE1) and E2 (RvE2). Both resolvins are derived from omega-3 fatty acid eicosapentaenoic acid (EPA). Here, long-term molecular dynamics simulations (MD) were performed to investigate the activation of the BLT1 receptor using two pro-resolution agonists (RvE1 and RvE2) and an inflammatory agonist (LTB4). We have analyzed the receptor's activation state, electrostatic interactions, and the binding affinity the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach. The results showed that LTB4 and RvE1 have kept the receptor in an active state by higher simulation time. MD showed that the ligand-receptor interactions occurred mainly through residues H94, R156, and R267. The MMPBSA calculations showed residues R156 and R267 were the two mainly hotspots. Our MMPBSA results were compatible with experimental results from other studies. Overall, the results from this study provide new insights into the activation mechanisms of the BLT1 receptor, reinforcing the role of critical residues and interactions in the binding of pro-resolution and pro-inflammatory agonists.

In-depth theoretical modeling to explore the mechanism of TPX-0131 overcoming lorlatinib resistance to ALKL1196M/G1202R mutation

A number of anaplastic lymphoma kinase (ALK) inhibitors have been clinically approved, with lorlatinib, particularly as a third-generation drug, demonstrating efficacy against various drug-resistant ALK single mutations. However, continued clinical use of lorlatinib has led to the emergence of ALK double mutations conferring resistance to lorlatinib, notably ALKL1196M/G1202R. TPX-0131 is a potential fourth-generation ALK inhibitor currently under development. TPX-0131 demonstrates a broader spectrum of activity against ALK-resistant mutations, efficiently inhibiting 26 single-point mutations and various double/triple mutations, including solvent front mutations and gatekeeper mutations. In this study, for the first time, a comprehensive elucidation of the molecular mechanisms by which TPX-0131 overcomes lorlatinib resistance to ALKL1196M/G1202R through modeling, MD simulations, free energy calculations, and US simulations. The results indicate that the interactions between lorlatinib and key residues at the hinge region are disturbed by L1196M/G1202R double mutation, leading to the disruption of important hydrogen bonding between Glu1197 and lorlatinib. For TPX-0131, the L1196M/G1202R mutation enhances electrostatic and van der Waals interactions, causing significant conformational changes primarily in the hinge region, G-loop, and β-strands. The tight binding of TPX-0131 to residues Arg1202, Met1199 and Arg1120 contribute significantly to overcoming lorlatinib resistance in ALKL1196M/G1202R mutant. These research results are expected to offer insights into the mechanism of TPX-0131 in treating ALKG1202R/L1196M-induced NSCLC resistance and optimizing of ALK inhibitors.

Molecular modelling and experimental validation identified a new therapeutic inhibitor of toxoplasmosis

Toxoplasmosis is a widespread parasitic disease, caused by Toxoplasma gondii, that affects nearly one-third of the human population. The lack of effective treatments drives the demand for novel anti-toxoplasmosis therapeutic options. In the present study, we used computational approaches and experimental validation to identify therapeutic inhibitors of toxoplasmosis. Initially, using the structure of the co-crystallized ligand of T. gondii calcium-dependent protein kinase 1 (TgCDPK1), we retrieved 3000 compounds from the database of COCONUT (COlleCtion of Open Natural ProdUcTs). These compounds were docked against the crystal structure of TgCDPK1 on the Glide Ligand Docking panel of Maestro 12.5 (Schrödinger Suite 2020-3). Based on the docking scores, we assessed promising molecules for toxicity potential on the ProTox-II online server, while the ADME profiling was done on the SwissADME server. Following the computational studies, we selected nine promising compounds for experimental validation against T. gondii in vitro. Of the compounds, C4, C5, C6, and C8 exhibited dose-dependent anti-T. gondii action with EC50 values ranging from 3.3 to 120.2 μg/mL. Host toxicity profiling revealed differential cytotoxic action with a selectivity index (SI) of <1 for the compounds except C5, which had an SI of 1.8. To validate our screening assay, we used sulfadiazine, a standard drug for toxoplasmosis and showed that it inhibited parasite growth. Further experiments showed that C5, an imidazole-based natural compound, has strong but reversible anti-parasitic action that peaks within the first 8 h. In addition, C5 exhibited similar toxic tendencies towards T. gondii within (intracellular) and outside (extracellular) the host, suggesting it likely has a parasite target(s). C5 showed no effect on host invasion but strongly impeded parasite replication and growth, thereby affecting the T. gondii lytic cycle. Furthermore, C5 treatment raised the reactive oxygen species level, but this may be a secondary effect because augmentation with Trolox antioxidant failed to block C5 anti-T. gondii action. In addition, molecular dynamics simulations of C5 and TgCDPK1 complex revealed relative stability within 100 ns run time. Collectively, our findings support the potential of imidazole-based compounds as novel, alternative anti-parasitic agents.

Structure-guided discovery of novel dUTPase inhibitors with anti-Nocardia activity by computational design

The zoonosis caused by Nocardia is increasing seriously. But commonly used antibiotic drugs often lead to resistance. N. seriolae dUTPase (NsdUTPase) plays a key role in the proliferation of Nocardia, and was regarded as a potent drug target. However, there was little report about the NsdUTPase inhibitors. In this study, we discovered a series of novel NsdUTPase inhibitors to fight against Nocardia. The first crystal structure of NsdUTPase was released, and a structure-based computational design was performed. Compounds 4b and 12b exhibited promising activities towards NsdUTPase (IC50 = 0.99 μM and 0.7 μM). In addition, they showed satisfied anti-Nocardia activity (MIC value ranges from 0.5 to 2 mg/L) and low cytotoxicity, which were better than approved drugs oxytetracycline and florfenicol. Molecular modelling study indicated that hydrophobic interaction might be the main contribution for ligand binding. Our results suggested that NsdUTPase inhibitors might be a useful way to repress Nocardia.

Searching for novel MDM2/MDMX dual inhibitors through a drug repurposing approach

Disruption of p53-MDM2/MDMX interaction by smaller inhibitors is a promising therapeutic intervention gaining tremendous interest. However, no MDM2/MDMX inhibitors have been marketed so far. Drug repurposing is a validated, practical approach to drug discovery. In this regard, we employed structure-based virtual screening in a reservoir of marketed drugs and identified nintedanib as a new MDM2/MDMX dual inhibitor. The computational structure analysis and biochemical experiments uncover that nintedanib binds MDM2/MDMX similarly to RO2443, a dual MDM2/MDMX inhibitor. Furthermore, the mechanistic study reveals that nintedanib disrupts the physical interaction of p53-MDM2/MDMX, enabling the transcriptional activation of p53 and the subsequent cell cycle arrest and growth inhibition in p53+/+ cancer cells. Lastly, structural minimisation of nintedanib yields H3 with the equivalent potency. In summary, this work provides a solid foundation for reshaping nintedanib as a valuable lead compound for the further design of MDM2/MDMX dual inhibitors.

Identification of novel PD-1/PD-L1 small molecule inhibitors: virtual screening, synthesis and in vitro characterisation

The PD-1/PD-L1 pathway is considered as one of the most promising immune checkpoints in tumour immunotherapy. However, researchers are faced with the inherent limitations of antibodies, driving them to pursue PD-L1 small molecule inhibitors. Virtual screening followed by experimental validation is a proven approach to discover active compounds. In this study, we employed multistage virtual screening methods to screen multiple compound databases to predict new PD-1/PD-L1 ligands. 35 compounds were proposed by combined analysis of fitness scores, interaction pattern and MM-GBSA binding affinities. Enzymatic assay confirmed that 10 out of 35 ligands were potential PD-L1 inhibitors, with inhibitory rate higher than 50% at the concentration of 30 µM. Among them, ZDS20 was identified as the most effective inhibitor with low micromolar activity (IC50 = 3.27 μM). Altogether, ZDS20 carrying novel scaffold was identified and could serve as a lead for the development of new classes of PD-L1 inhibitors.

Hormone response elements for the thyroid receptor-α include specific distal 5'-flanking DNA

Optimal gene transcription is achieved through precise interactions between transcription factors and their DNA binding sites. We provide evidence that conserved distally located 5'-flanking sequences interact directly with the intrinsically disordered amino-terminal region of the thyroid receptor-α (TRα) to control transcriptional activity. Simulated modeling and dynamics with multiple ChIP-seq-derived sequences consistently reveal specific lysine/arginine-DNA minor groove interactions. The impact of these interactions is to distort DNA structural conformations, and these are also revealed with atomic force microscopy. The importance of the 5'-flanking DNA is further emphasized with reporter gene assays and comparisons with canonical response elements. Overall, the study reveals the inadequacy of current definitions of the DNA hormone response element (HRE) and suggests that future descriptions of the HRE include the conserved distal DNA sequences. The broad impact of this study is further underscored by the common occurrence of Lys/Arg-rich motifs within the intrinsically disordered regions of nuclear receptors.

Protein-Ligand Interaction Energies from Quantum-Chemical Fragmentation Methods: Upgrading the MFCC-Scheme with Many-Body Contributions

Quantum-chemical fragmentation methods offer an attractive approach for the accurate calculation of protein-ligand interaction energies. While the molecular fractionation with conjugate caps (MFCC) scheme offers a rather straightforward approach for this purpose, its accuracy is often not sufficient. Here, we upgrade the MFCC scheme for the calculation of protein-ligand interactions by including many-body contributions. The resulting fragmentation scheme is an extension of our previously developed MFCC-MBE(2) scheme [J. Comput. Chem. 2023, 44, 1634-1644]. For a diverse test set of protein-ligand complexes, we demonstrate that by upgrading the MFCC scheme with many-body contributions, the error in protein-ligand interaction energies can be reduced significantly, and one generally achieves errors below 20 kJ/mol. Our scheme allows for systematically reducing these errors by including higher-order many-body contributions. As it combines the use of single amino acid fragments with high accuracy, our scheme provides an ideal starting point for the parametrization of accurate machine learning potentials for proteins and protein-ligand interactions.

Explicit water-ligand docking, drug-likeness and molecular dynamics simulation analysis to predict the potency of Boerhavia diffusa plant extract against mutant wilms tumor-1 protein responsible for type 4 nephrotic syndrome

Thestructure and function of a protein are closely connected. Changes in a protein structure can impact on its function. Nephrotic syndrome type 4 (NPHS4) is an uncommon genetic condition caused by mutations in the WT1 gene, which codes for the wilms tumor-1 protein. Several studies have discovered that patients with nephrotic syndromes are resistant to steroid therapy and are likely to develop end-stage renal failure. The use of phytochemicals-based therapeutics is in demand due to their high potential and low toxicity. Based on this context, we employed the Autodock raccoon to screen 67 distinct potent phytochemicals from the Boerhavia diffusa (B.diffusa) plant against the wild type and mutant model at position C388R (cysteine is replaced with arginine at position 388) of the C-terminal DNA binding domain of the wilms tumor-1 protein. Out of 67 active compounds, only 10 compounds (lunamarine, kaempferol, boeravinone B, boeravinone E, boeravinone A, boeravinone F, boeravinone J, boeravinone P, boerhaavic acid and 4',7-dihydroxy-3'-methylflavone) were screened based on drug-likeness properties and binding energy for explicit water ligand docking against wild and mutant model of C-terminal DNA binding domain of wilms tumor-1 protein. Consequently, the hydrated form of boeravinone F and boeravinone A demonstrated the highest binding energy against the protein mutant model described above, the binding energies were -9.56 and -8.96 Kcal/mol, respectively. Followed by explicit water ligand docking the microscopic properties of wild type, mutant, mutant-boeravinone F complex, and mutant-boeravinone A complex systems were evaluated using molecular dynamics simulation steps with 100 ns of trajectory. The findings indicate that, due to mutation the mutant model system had decreasing stability and decreasing compactness nature. However, boeravinone A effectively monitored the mutant system's stability and improved compactness nature after binding with the mutant model. Boeravinone A with the mutant model complex system was determined to have the lowest energy point as compared to other studied systems. The study revealed minimal structural alterations and reduced conformational mobility.

Benzothiazinone analogs as Anti-Mycobacterium tuberculosis DprE1 irreversible inhibitors: Covalent docking, validation, and molecular dynamics simulations

Mycobacterium tuberculosis is a lethal human pathogen, with the key flavoenzyme for catalyzing bacterial cell-wall biosynthesis, decaprenylphosphoryl-D-ribose oxidase (DprE1), considered an Achilles heal for tuberculosis (TB) progression. Inhibition of DprE1 blocks cell wall biosynthesis and is a highly promising antitubercular target. Macozinone (PBTZ169, a benzothiazinone (BTZ) derivative) is an irreversible DprE1 inhibitor that has attracted considerable attention because it exhibits an additive activity when combined with other anti-TB drugs. Herein, 754 BTZ analogs were assembled in a virtual library and evaluated against the DprE1 target using a covalent docking approach. After validation of the employed covalent docking approach, BTZ analogs were screened. Analogs with a docking score less than -9.0 kcal/mol were advanced for molecular dynamics (MD) simulations, followed by binding energy evaluations utilizing the MM-GBSA approach. Three BTZ analogs-namely, PubChem-155-924-621, PubChem-127-032-794, and PubChem-155-923-972- exhibited higher binding affinities against DprE1 compared to PBTZ169 with ΔGbinding values of -77.2, -74.3, and -65.4 kcal/mol, versus -49.8 kcal/mol, respectively. Structural and energetical analyses were performed for the identified analogs against DprE1 throughout the 100 ns MD simulations, and the results demonstrated the great stability of the identified BTZ analogs. Physicochemical and ADMET characteristics indicated the oral bioavailability of the identified BTZ analogs. The obtained in-silico results provide promising anti-TB inhibitors that are worth being subjected to in-vitro and in-vivo investigations.

Identification and interaction mechanism of novel small molecule antagonists targeting CC chemokine receptor 1/3/5 for treatment of non-small cell lung cancer

Non-Small Cell Lung Cancer (NSCLC) was one of the most prevalent forms of lung cancer. Due to its ease of invasion and migration, the five-year survival rate was relatively low. Therefore, new strategies for NSCLC treatment were needed. CC chemokine receptor 1/3/5 (CCR1/CCR3/CCR5), a member of the G-protein coupled receptor family, could promote the migration and invasion of NSCLC cells by binding to related chemokines. Consequently, targeting CCR1, CCR3 and CCR5 might prevent the progression of the disease. So far, no compound had been reported as a common antagonist for CCR1, CCR3, and CCR5. In this research, we utilized virtual screening and structural optimization to obtain compound 5, which effectively inhibited the migration and invasion of NSCLC cells. Meanwhile, Western Blot and Enzyme linked immunosorbent assay (ELISA) manifested that compound 5 suppressed migration and invasion of NSCLC cells by suppressing the nuclear factor κB (NF-κB) and the consequently decreased Matrix Metalloproteinase-9(MMP-9) secretion. Moreover, drug affinity responsive target stability (DARTS) experiment and molecular simulations confirmed that compound 5 was capable of binding with CCR1/CCR3/CCR5, and Van der Waals forces were instrumental in the binding process. Ile91, Tyr113, Gln284, and Ser184(CCR1-ligand5), Ile189, Met213, and Leu209(CCR3-ligand5), Phe109, Gln194, and Thr195(CCR5-ligand5) had Van der Waals interactions with ligand 5. Dynamic cross-correlation matrix (DCCM) and free energy landscape (FEL) showed that compound 5 could stably bind to CCR1/CCR3/CCR5 to change conformation of the protein and the tendency of residue movements, leading to a persistent inhibitory effect. This study aimed to provide assistance in the rational design of common antagonists for CCR1, CCR3, and CCR5.

Unraveling the Molecular Determinants of Catalytic Efficiency and Substrate Specificity in l-Amino Acid Decarboxylases

l-Tryptophan decarboxylase (TDC) and l-3,4-dihydroxyphenylalanine decarboxylase (DDC) catalyze the decarboxylation of l-tryptophan, 5-hydroxytryptophan, and l-3,4-dihydroxyphenylalanine. In this study, we analyzed the amino acid compositions of the substrate-binding pockets of TDC from Catharanthus roseus (CrTDC) and DDC from Sus scrofa (SsDDC), explored the specificity of key amino acids within these pockets, and elucidated mechanisms influencing substrate selectivity and catalytic activity in both enzymes, using whole-cell catalysis to screen mutants and determine enzymatic kinetic parameters. The results demonstrated that residues Ala-103 and Val-122 in CrTDC, along with their corresponding sites Thr-82 and Ile-101 in SsDDC, significantly influence substrate selectivity and catalytic efficiency. Molecular dynamics simulations revealed that substrate selectivity and catalytic efficiency depends on the nucleophilic attack distance between the substrate's amino group and the C4' of pyridoxal 5'-phosphate. This study elucidates the catalytic mechanisms and structural bases of TDC and DDC, guiding enhancements in the related aromatic monoamine biosynthesis.

Natural AI-based drug designing by modification of ascorbic acid and curcumin to combat buprofezin toxicity by using molecular dynamics study

Buprofezin, a widely employed insecticide in agricultural practices, has elicited significant apprehension due to its prospective deleterious effects on non-target organisms and ecological systems. Its enduring presence in terrestrial and aquatic environments presents potential hazards to human health and biodiversity, thereby necessitating the investigation of safer alternatives or strategies for mitigation. The research focuses on five principal receptors: CAT (Catalase), IL-1B (Interleukin-1 Beta), IL-6 (Interleukin-6), TNF-alpha (Tumor Necrosis Factor-alpha), and SOD (Superoxide Dismutase). These receptors are integral to the processes of inflammation, oxidative stress, and immune responses, rendering them critical for comprehending the biochemical pathways affected by toxic substances and the potential for protective interventions. The investigation employed WADDAICA (Webserver-Aided Drug Design by Artificial Intelligence) to formulate AI-driven pharmaceuticals, complemented by ADME (Absorption, Distribution, Metabolism, Excretion) evaluations, Molecular Dynamics (MD) simulations, as well as MMGBSA and MMPBSA methodologies to examine the stability and interactions of the compounds with the designated receptors. Docking experiments disclosed that the interaction of CAT with the ascorbic acid AI-derived drug demonstrated a binding energy of -7.1 kcal/mol, signifying a robust interaction, while the complex of IL-1B with the curcumin AI-derived drug exhibited a binding energy of -7.3 kcal/mol. The ADME analysis revealed favorable gastrointestinal absorption and aqueous solubility for both compounds. Furthermore, the drug-likeness metrics were deemed satisfactory, with no breaches of Lipinski's rule of five, suggesting promising potential for subsequent advancement as therapeutic agents.

In silico studies for improving target selectivity of anti-malarial dual falcipain inhibitors vis-à-vis human cathepsins

Dual falcipain-2 (FP-2) and falcipain-3 (FP-3) inhibitors, NM12 and NM15, displayed micromolar inhibitions but they exhibit similar binding affinities for the human cathepsins, thus indicating potential toxicity. The current study aims to develop a model to enhance the selectivity of the falcipain inhibitors vis-à-vis human cathepsins using previously identified dual falcipain 2 and 3 inhibitors, NM12 and NM15. To improve the selectivity of NM12 and NM15, analogs with weaker interactions with the conserved residues in the FPs and hCatK were designed while enhancing the unique interactions for the FPs. In silico analysis was carried out in the S2 subsite of both plasmodium and human proteases which is considered the preferred selective site due to the presence of less conserved residues. The Fasta sequence alignment and active/conserved binding site superimposition show that FPs contain acidic polar residues (Asp234 for FP2 and Glu243 for FP3) while hCatK has a neutral hydrophobic residue (Leu209) at the S2 subsite. Therefore, analogs of NM12 and NM15 were designed to enhance affinity and selectivity by improving interactions with these acidic residues while avoiding interactions with hydrophobic residues in hCatK. Newly designed analogs (NM12H and NM15G) show better selectivity as well as binding affinity towards FPs (ΔG of NM12H: -74.49 kcal/mol for FP2, -70.97 kcal/mol for FP3; ΔG of NM15G: -70.09 kcal/mol for FP2, -74.52 kcal/mol for FP3) as compared to NM12 and NM15. Thus, the selectivity and binding affinity against dual falcipains vis-à-vis human cathepsin were improved using molecular dynamic simulations.

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

BACKGROUND

Histone deacetylase 6 (HDAC6) plays a crucial role in neurological, inflammatory, and other diseases; thus, it has emerged as an important target for therapeutic intervention. To date, there are no FDA-approved HDAC6-targeting drugs, and most pipeline candidates suffer from poor target engagement, inadequate brain penetration, and low tolerability. There are a few HDAC6 clinical candidates for the treatment of mostly non-CNS cancers as their pharmacokinetic liabilities exclude them from targeting HDAC6-implicated neurological diseases, urging development to address these challenges. They also demonstrate off-target toxicity due to limited selectivity, leading to adverse effects in patients. Selective inhibitors have thus been the focus of development over the past decade, though no selective and potent HDAC6 inhibitor has yet been approved.

METHODS

This study involved an integrated virtual screening against HDAC6 using the DrugBank database to identify repurposed drugs capable of inhibiting HDAC6 activity. The primary assessment involved the determination of the ability of molecules to bind with HDAC6. Subsequently, interaction analyses and 500 ns molecular dynamics (MD) simulations followed by essential dynamics were carried out to study the conformational flexibility and stability of HDAC6 in the presence of the screened molecules, i.e., penfluridol and pimozide.

RESULTS

The virtual screening results pinpointed penfluridol and pimozide as potential repurposed drugs against HDAC6 based on their binding efficiency and appropriate drug profiles. The docking results indicate that penfluridol and pimozide share the same binding site as the reference inhibitor with HDAC6. The MD simulation results showed that stable protein-ligand complexes of penfluridol and pimozide with HDAC6 were formed. Additionally, MMPBSA analysis revealed favorable binding free energies for all HDAC6-ligand complexes, confirming the stability of their interactions.

CONCLUSIONS

The study implies that both penfluridol and pimozide have strong and favorable binding with HDAC6, which supports the idea of repositioning these drugs for the management of neurodegenerative disorders. However, further in-depth studies are needed to explore their efficacy and safety in biological systems.

Repurposing of drug candidates against Epstein-Barr virus: Virtual screening, docking computations, molecular dynamics, and quantum mechanical study

Epstein-Barr virus (EBV) was the first tumor virus identified in humans, and it is mostly linked to lymphomas and cancers of epithelial cells. Nevertheless, there is no FDA-licensed drug feasible for this ubiquitous EBV viral contagion. EBNA1 (Epstein-Barr nuclear antigen 1) plays several roles in the replication and transcriptional of latent gene expression of the EBV, making it an attractive druggable target for the treatment of EBV-related malignancies. The present study targets EBV viral reactivation and upkeep by inhibiting EBNA1 utilizing a drug-repurposing strategy. To hunt novel EBNA1 inhibitors, a SuperDRUG2 database (> 4,600 pharmaceutical ingredients) was virtually screened utilizing docking computations. In accordance with the estimated docking scores, the most promising drug candidates then underwent MDS (molecular dynamics simulations). Besides, the MM-GBSA approach was applied to estimate the binding affinities between the identified drug candidates and EBNA1. On the basis of MM-GBSA//200 ns MDS, bezitramide (SD000308), glyburide (SD001170), glisentide (SD001159), and glimepiride (SD001156) unveiled greater binding affinities towards EBNA1 compared to KWG, a reference inhibitor, with ΔGbinding values of -44.3, -44.0, -41.7, -40.2, and -32.4 kcal/mol, respectively. Per-residue decomposition analysis demonstrated that LYS477, ASN519, and LYS586 significantly interacted with the identified drug candidates within the EBNA1 binding pocket. Post-dynamic analyses also demonstrated high constancy of the identified drug candidates in complex with EBNA1 throughout 200 ns MDS. Ultimately, electrostatic potential and frontier molecular orbitals analyses were performed to estimate the chemical reactivity of the identified EBNA1 inhibitors. Considering the current outcomes, this study would be an adequate linchpin for forthcoming research associated with the inhibition of EBNA1; however, experimental assays are required to inspect the efficiency of these candidates.

Riddelline from Tamarix articulate as a potential anti-bacterial lead compound for novel antibiotics discovery: A comprehensive computational and toxicological studies

Tamarix articulate from the Tamaricaece family is a halophytic plant. This plant is commonly called Athal or Tamarix in different Arabic and Asian countries. Due to the high load of polyphenolic phytochemicals, the plant has been used as a therapeutic option against several diseases for decades. The plant is an anti-inflammatory, anti-bacterial, anti-viral, anti-cancer, anti-oxidant, and anti-inflammatory. In this work, the 222 phytochemical compounds of T. articulate from our previous study are used in different bioinformatic and biophysics techniques to explore their biological potency against different anti-bacterial, anti-cancer and anti-viral targets. By doing so, it was found that Riddelline ranked as the best binding molecule of biological macromolecules selected herein in particular the bacterial targets. The binding energy value of the compound for the KdsA enzyme was -14.64 kcal/mol, KdsB (-13.09 kcal/mol), MurC (-13.67 kcal/mol), MurD (-13.54 kcal/mol), MurF (-14.20 kcal/mol), Polo-like kinase 1 (Plk1) (-12.34 kcal/mol), Bcl-2 protein (-13.39 kcal/mol), SARS-CoV-2 main protease enzyme (-12.67 kcal/mol), and Human T cell leukemia virus protease (-13.67 kcal/mol). The mean Rg value of KdsA-Riddelline complex and KdsA-FPE complex is 32.67 Å, and average RMSD of KdsA-Riddelline complex and KdsA-FPE complex is 2.31 Å, respectively. The binding energy complexes was found to be dominated by van der Waals (-71.98 kcal/mol for KdsA-Riddelline complex and -65.09 kcal/mol for KdsA-FPE complex). The lead compound was also unveiled to show favorable druglike properties and pharmacokinetics. Together, the data suggest the good anti-bacterial activities of the T. articulate phytochemicals and thus can be subjected to experimental in vitro and in vivo investigations.

Insights into the chirality-dependent recognition of Danshensu Bingpian Zhi stereoisomers with PPARγ

Peroxisome proliferator-activated receptor γ (PPARγ), a nuclear receptor involved in metabolic processes, inflammation, and energy balance, represents a promising therapeutic target for cardiovascular diseases. Danshensu Bingpian Zhi (DBZ), a chiral compound derived from traditional Chinese medicine, exhibits potential as a PPARγ agonist. Using an ensemble-based docking approach, molecular dynamics (MD) simulations, and the molecular mechanics generalized born surface area (MM/GBSA) methods, we explored the binding modes and energetics of DBZ stereoisomers with the PPARγ ligand-binding domain (LBD). The results indicated that the right-handed stereoisomer (DBZR) binds like a full agonist, while the left-handed stereoisomer (DBZS) binds as a partial agonist with stronger binding energies (ΔGbind), indicating a robust interaction with PPARγ. Both the stereoisomers stabilize the β-sheet region of PPARγ-LBD, potentially protecting Ser245 from phosphorylation by Cdk5, a process implicated in atherosclerosis. Principal component analysis (PCA) and dynamic cross-correlation matrices (DCCM) revealed the complex structural dynamics within the Ω loop, β-sheet, and AF-2 region of PPARγ-LBD upon ligand binding, which may contribute to the unique binding mode and efficacy of DBZS. These findings provide insights into the molecular recognition of PPARγ-LBD by DBZ stereoisomers and their impact on the conformational dynamics of PPARγ, highlighting the therapeutic potential of DBZ and the significance of chirality in drug design.

Investigating the effect of 1,2-Dibenzoylhydrazine on Staphylococcus aureus using integrated computational approaches

Staphylococcus aureus, a notorious member of the ESKAPE pathogens, poses significant public health challenges due to its virulence and multidrug-resistant nature, particularly in methicillin-resistant S. aureus (MRSA) strains. With the increasing threat of antibiotic resistance, there is an urgent need to develop novel antibiotic agents. This study therefore aims to explore the antibacterial potential of 1,2-dibenzoylhydrazine (DBH) as a scaffold against S. aureus drug target enzymes, using integrated computational approaches. The study utilized molecular docking, lead optimization, and structure-based virtual screening techniques to evaluate the binding affinities of DBH and its derivatives against various S. aureus enzymes. Prime/MM-GBSA calculations were performed to validate the binding affinities obtained, and molecular dynamics (MD) simulations were conducted to assess the stability of the DBHs-enzyme complexes. Results indicated that, out of twenty enzymes from S. aureus examined against DBH, carotenoid dehydrosqualene synthase was predicted as a suitable target enzyme for DBH, showing a binding affinity of -8.027 kcal/mol. A lead optimization operation of the compound generated 27 DBH derivatives out of which four exhibited enhanced binding affinities compared to both DBH and a standard antibiotic, ofloxacin. The QSAR model predicted that, DBH and molecule_D_1 have higher PIC50 of 4.779 µM compared with the standard drug (ofloxacin = 4.678 µM). MD simulations confirmed the stability of the top-scoring derivatives within the enzyme's binding pocket, with RMSD and RMSF analyses supporting their potential as inhibitors of the enzyme. In conclusion, this study has predicted the effect of DBH derivatives on S. aureus based on their in silico inhibitory capacity against the carotenoid dehydrosqualene synthase from the organism. Future work will seek to experimentally validate these findings against the suggested enzyme.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00278-1.

StreaMD: the toolkit for high-throughput molecular dynamics simulations

Molecular dynamics simulations serve as a prevalent approach for investigating the dynamic behaviour of proteins and protein-ligand complexes. Due to its versatility and speed, GROMACS stands out as a commonly utilized software platform for executing molecular dynamics simulations. However, its effective utilization requires substantial expertise in configuring, executing, and interpreting molecular dynamics trajectories. Existing automation tools are constrained in their capability to conduct simulations for large sets of compounds with minimal user intervention, or in their ability to distribute simulations across multiple servers. To address these challenges, we developed a Python-based tool that streamlines all phases of molecular dynamics simulations, encompassing preparation, execution, and analysis. This tool minimizes the required knowledge for users engaging in molecular dynamics simulations and can efficiently operate across multiple servers within a network or a cluster. Notably, the tool not only automates trajectory simulation but also facilitates the computation of free binding energies for protein-ligand complexes and generates interaction fingerprints across the trajectory. Our study demonstrated the applicability of this tool on several benchmark datasets. Additionally, we provided recommendations for end-users to effectively utilize the tool.Scientific contributionThe developed tool, StreaMD, is applicable to different systems (proteins, ligands and their complexes including co-factors) and requires a little user knowledge to setup and run molecular dynamics simulations. Other features of StreaMD are seamless integration with calculation of MM-GBSA/PBSA binding free energies and protein-ligand interaction fingerprints, and running of simulations within distributed environments. All these will facilitate routine and massive molecular dynamics simulations.