Molecular Docking: From Lock and Key to Combination Lock

Blackcurrant press cake by-product: Increased chemical bioaccessibility and reduced antioxidant protection after in vitro simulation of gastrointestinal digestion

This study describes the bioaccessibility in terms of total phenolic content (TPC) and antioxidant capacity before and after in vitro digestion from blackcurrant press cake extracts (BPC) and the bioactivity in cell culture, human erythrocytes as well as the in silico analysis. Chemical analysis of BPC presented an increase in TPC (270%) and anthocyanins (136%) after in vitro digestion, resulting in an improvement of antioxidant activity (DPPH 112%; FRAP: 153%). This behavior may be related to the highest activity of cyanidin-3-rutinoside, as confirmed by in silico analysis. The digested BPC did not exert cytotoxicity in cells and showed less antioxidant activity against the oxidative damage induced in endothelial cells and human erythrocytes compared to the non-digested extract. The results raise a question about the reliability we should place on results obtained only from crude samples, especially those that will be used to produce foods or nutraceuticals.

A flexible data-free framework for structure-based de novo drug design with reinforcement learning

Contemporary structure-based molecular generative methods have demonstrated their potential to model the geometric and energetic complementarity between ligands and receptors, thereby facilitating the design of molecules with favorable binding affinity and target specificity. Despite the introduction of deep generative models for molecular generation, the atom-wise generation paradigm that partially contradicts chemical intuition limits the validity and synthetic accessibility of the generated molecules. Additionally, the dependence of deep learning models on large-scale structural data has hindered their adaptability across different targets. To overcome these challenges, we present a novel search-based framework, 3D-MCTS, for structure-based de novo drug design. Distinct from prevailing atom-centric methods, 3D-MCTS employs a fragment-based molecular editing strategy. The fragments decomposed from small-molecule drugs are recombined under predefined retrosynthetic rules, offering improved drug-likeness and synthesizability, overcoming the inherent limitations of atom-based approaches. Leveraging multi-threaded parallel simulations combined with a real-time energy constraint-based pruning strategy, 3D-MCTS achieves remarkable efficiency. At a fixed computational cost, it outperforms other state-of-the-art (SOTA) methods by producing molecules with enhanced binding affinity. Furthermore, its fragment-based approach ensures the generation of more dependable binding conformations, exhibiting a success rate 43.6% higher than that of other SOTAs. This advantage becomes even more pronounced when handling targets that significantly deviate from the training dataset. 3D-MCTS is capable of achieving thirty times more hits with high binding affinity than traditional virtual screening methods, which demonstrates the superior ability of 3D-MCTS to explore chemical space. Moreover, the flexibility of our framework makes it easy to incorporate domain knowledge during the process, thereby enabling the generation of molecules with desirable pharmacophores and enhanced binding affinity. The adaptability of 3D-MCTS is further showcased in metalloprotein applications, highlighting its potential across various drug design scenarios.

Theoretical study of ArcB and its dimerization, interaction with anaerobic metabolites, and activation of ArcA

The complex metabolism of Escherichia coli has been extensively studied, including its response to oxygen availability. The ArcA/B two-component system (TCS) is the key regulator for the transition between these two environmental conditions and has been thoroughly characterized using genetic and biochemical approaches. Still, to date, limited structural data is available. The breakthrough provided by AlphaFold2 in 2021 has brought a reliable tool to the scientific community for assessing the structural features of complex proteins. In this report, we analyzed the structural aspects of the ArcA/B TCS using AlphaFold2 models. The models are consistent with the experimentally determined structures of ArcB kinase. The predicted structure of the dimeric form of ArcB is consistent with the extensive genetic and biochemical data available regarding mechanistic signal perception and regulation. The predicted interaction of the dimeric form of ArcB with its cognate response regulator (ArcA) is also consistent with both the forward and reverse phosphotransfer mechanisms. The ArcB model was used to detect putative binding cavities to anaerobic metabolites, encouraging testing of these predictions experimentally. Finally, the highly accurate models of other ArcB homologs suggest that different experimental approaches are needed to determine signal perception in kinases lacking the PAS domain. Overall, ArcB is a kinase with features that need further testing, especially in determining its crystal structure under different conditions.

Anti-inflammatory and Antiphytopathogenic Fungal Activity of 2,3-seco-Tirucallane Triterpenoids Meliadubins A and B from Melia dubia Cav. Barks with ChemGPS-NP and In Silico Prediction

Two new rearranged 2,3-seco-tirucallane triterpenoids, meliadubins A (1) and B (2), along with four known compounds, 3-6, were isolated from the barks of Melia dubia Cav. Compound 2 exhibited a significant inflammatory inhibition effect toward superoxide anion generation in human neutrophils (EC50 at 5.54 ± 0.36 μM). It bound to active sites of a human inducible nitric oxide synthase (3E7G) through interactions with the residues of GLU377 and PRO350, which may benefit in reducing the neutrophilic inflammation effect. The ChemGPS-NP interpretation combined with bioactivity assay and in silico prediction results suggested 2 to be an agent for targeting iNOS with different mechanisms as compared to a selected set of current approved drugs. Moreover, compounds 1 and 2 showed remarkable inhibition against the rice pathogenic fungus Magnaporthe oryzae in a dose-dependent manner with IC50 values of 137.20 ± 9.55 and 182.50 ± 18.27 μM, respectively. Both 1 and 2 displayed interactions with the residue of TYR223, a key active site of trihydroxynaphthalene reductase (1YBV). The interpretation of 1 and 2 in the ChemGPS-NP physical-chemical property space indicated that both compounds are quite different compared to all members of a selected set of reference compounds. In light of demonstrated biological activity and in silico prediction experiments, both compounds possibly exhibited activity against phytopathogenic fungi via a novel mode of action.

Fine-tuning non-covalent interactions between hybrid metal-oxo clusters and proteins

Interactions between the protein Hen Egg White Lysozyme (HEWL) and three different hybrid Anderson-Evans polyoxometalate clusters - AE-NH2 (δ-[MnMo6O18{(OCH2)3CNH2}2]3-), AE-CH3 (δ-[MnMo6O18{(OCH2)3CCH3}2]3-) and AE-Biot (δ-[MnMo6O18{(OCH2)3CNHCOC9H15N2OS}2]3-) - were studied via tryptophan fluorescence spectroscopy and single crystal X-ray diffraction. Quenching of tryptophan fluorescence was observed in the presence of all three hybrid polyoxometalate clusters (HPOMs), but the extent of quenching and the binding affinity were greatly dependent on the nature of the organic groups attached to the cluster. Control experiments further revealed the synergistic effect of the anionic polyoxometalate core and organic ligands towards enhanced protein interactions. Furthermore, the protein was co-crystallised with each of the three HPOMs, resulting in four different crystal structures, thus allowing for the binding modes of HPOM-protein interactions to be investigated with near-atomic precision. All crystal structures displayed a unique mode of binding of the HPOMs to the protein, with both functionalisation and the pH of the crystallisation conditions influencing the interactions. From the crystal structures, it was determined that HPOM-protein non-covalent complexes formed through a combination of electrostatic attraction between the polyoxometalate cluster and positively charged surface regions of HEWL, and direct and water-mediated hydrogen bonds with both the metal-oxo inorganic core and the functional groups of the ligand, where possible. Hence, functionalisation of metal-oxo clusters shows great potential in tuning their interactions with proteins, which is of interest for several biomedical applications.

An equivariant generative framework for molecular graph-structure Co-design

Designing molecules with desirable physiochemical properties and functionalities is a long-standing challenge in chemistry, material science, and drug discovery. Recently, machine learning-based generative models have emerged as promising approaches for de novo molecule design. However, further refinement of methodology is highly desired as most existing methods lack unified modeling of 2D topology and 3D geometry information and fail to effectively learn the structure-property relationship for molecule design. Here we present MolCode, a roto-translation equivariant generative framework for molecular graph-structure Co-design. In MolCode, 3D geometric information empowers the molecular 2D graph generation, which in turn helps guide the prediction of molecular 3D structure. Extensive experimental results show that MolCode outperforms previous methods on a series of challenging tasks including de novo molecule design, targeted molecule discovery, and structure-based drug design. Particularly, MolCode not only consistently generates valid (99.95% validity) and diverse (98.75% uniqueness) molecular graphs/structures with desirable properties, but also generates drug-like molecules with high affinity to target proteins (61.8% high affinity ratio), which demonstrates MolCode's potential applications in material design and drug discovery. Our extensive investigation reveals that the 2D topology and 3D geometry contain intrinsically complementary information in molecule design, and provide new insights into machine learning-based molecule representation and generation.

Screening of Potential Inhibitors Targeting the Main Protease Structure of SARS-CoV-2 via Molecular Docking, and Approach with Molecular Dynamics, RMSD, RMSF, H-Bond, SASA and MMGBSA

Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the M^pro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the M^pro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.

Biochar-extracted liquor stimulates nitrogen related gene expression on improving nitrogen utilization in rice seedling

Introduction

Biochar has been shown to be an effective soil amendment for promoting plant growth and improving nitrogen (N) utilization. However, the physiological and molecular mechanisms behind such stimulation remain unclear.

Methods

In this study, we investigated whether biochar-extracted liquor including 21 organic molecules enhance the nitrogen use efficiency (NUE) of rice plants using two N forms (NH4 +-N and NO3 --N). A hydroponic experiment was conducted, and biochar-extracted liquor (between 1 and 3% by weight) was applied to rice seedlings.

Results

The results showed that biochar-extracted liquor significantly improved phenotypic and physiological traits of rice seedlings. Biochar-extracted liquor dramatically upregulated the expression of rice N metabolism-related genes such as OsAMT1.1, OsGS1.1, and OsGS2. Rice seedlings preferentially absorbed NH4 +-N than NO3 --N (p < 0.05), and the uptake of NH4 +-N by rice seedlings was significantly increased by 33.60% under the treatment of biochar-extracted liquor. The results from molecular docking showed that OsAMT1.1protein can theoretically interact with 2-Acetyl-5-methylfuran, trans-2,4-Dimethylthiane, S, S-dioxide, 2,2-Diethylacetamide, and 1,2-Dimethylaziridine in the biochar-extracted liquor. These four organic compounds have similar biological function as the OsAMT1.1 protein ligand in driving NH4 +-N uptakes by rice plants.

Discussion

This study highlights the importance of biochar-extracted liquor in promoting plant growth and NUE. The use of low doses of biochar-extracted liquor could be an important way to reduce N input in order to achieve the purpose of reducing fertilizer use and increasing efficiency in agricultural production.

Structure-Based Design of Novel MAO-B Inhibitors: A Review

With the significant growth of patients suffering from neurodegenerative diseases (NDs), novel classes of compounds targeting monoamine oxidase type B (MAO-B) are promptly emerging as distinguished structures for the treatment of the latter. As a promising function of computer-aided drug design (CADD), structure-based virtual screening (SBVS) is being heavily applied in processes of drug discovery and development. The utilization of molecular docking, as a helping tool for SBVS, is providing essential data about the poses and the occurring interactions between ligands and target molecules. The current work presents a brief discussion of the role of MAOs in the treatment of NDs, insight into the advantages and drawbacks of docking simulations and docking software, and a look into the active sites of MAO-A and MAO-B and their main characteristics. Thereafter, we report new chemical classes of MAO-B inhibitors and the essential fragments required for stable interactions focusing mainly on papers published in the last five years. The reviewed cases are separated into several chemically distinct groups. Moreover, a modest table for rapid revision of the revised works including the structures of the reported inhibitors together with the utilized docking software and the PDB codes of the crystal targets applied in each study is provided. Our work could be beneficial for further investigations in the search for novel, effective, and selective MAO-B inhibitors.

Updates on drug designing approach through computational strategies: a review

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

Structural Complementarity of Bruton’s Tyrosine Kinase and Its Inhibitors for Implication in B-Cell Malignancies and Autoimmune Diseases

Bruton’s tyrosine kinase (BTK) is a critical component in B-cell receptor (BCR) signaling and is also expressed in haematogenic and innate immune cells. Inhibition of BTK hyperactivity is implicated in B-cell malignancies and autoimmune diseases. This review derives the structural complementarity of the BTK-kinase domain and its inhibitors from recent three-dimensional structures of inhibitor-bound BTK in the protein data bank (PDB). Additionally, this review analyzes BTK-mediated effector responses of B-cell development and antibody production. Covalent inhibitors contain an α, β-unsaturated carbonyl moiety that forms a covalent bond with Cys481, stabilizing αC-helix in inactive-out conformation which inhibits Tyr551 autophosphorylation. Asn484, located two carbons far from Cys481, influences the stability of the BTK-transition complex. Non-covalent inhibitors engage the BTK-kinase domain through an induced-fit mechanism independent of Cys481 interaction and bind to Tyr551 in the activation kink resulting in H3 cleft, determining BTK selectivity. Covalent and non-covalent binding to the kinase domain of BTK shall induce conformational changes in other domains; therefore, investigating the whole-length BTK conformation is necessary to comprehend BTK’s autophosphorylation inhibition. Knowledge about the structural complementarity of BTK and its inhibitors supports the optimization of existing drugs and the discovery of drugs for implication in B-cell malignancies and autoimmune diseases.

Chalcone derivatives as xanthine oxidase inhibitors: synthesis, binding mode investigation, biological evaluation, and ADMET prediction

Xanthine oxidase (XO) is a crucial target for the treatment of hyperuricemia and gout. A series of derivatives based on natural 3,4-dihydroxychalcone, obtained from Carthamus tinctorious and Licorice, were designed and synthesized. Nine derivatives (9a-e, 10b,c, and 15a,b) exhibited apparent XO inhibitory activity in vitro (IC₅₀ values varied from 0.121 to 7.086 μM), 15b presented the most potent inhibitory activity (IC₅₀ = 0.121 µM), which was 27.47-fold higher than that of allopurinol (IC₅₀ = 3.324 µM). The SAR analysis indicated that introducing hydroxyl groups at 3'/4'/5'-position on ring A was more beneficial to the inhibition of XO than at 2'/6'-position; the removal of 3‑hydroxyl group on ring B could weaken the inhibitory potency of hydroxychalcones on XO, but it was beneficial to the XO inhibitory potency of methoxychalcones. Molecule modeling studies afforded insights into the binding mode of 15b with XO and supported the findings of SAR analysis. Additionally, kinetics studies demonstrated that 15b presented a reversible and competitive XO inhibitor, which spontaneously combined with XO through hydrophobic force, and finally changed the secondary conformation of XO. Furthermore, the acute hyperuricemia model was employed to investigate the hypouricemic effect of 15b, which could effectively reduce the serum uric acid levels of rats at an oral dose of 10 mg/kg. ADMET prediction suggested that compound 15b possessed good pharmacokinetic properties. Briefly, compound 15b emerges as an interesting XO inhibitor for the treatment of hyperuricemia and gout with beneficial effects on serum uric acid levels regulating. Meanwhile, the XO inhibitors with chalcone skeleton will deserve further attention and discussion.

Synthesis of New Ester Derivatives of Salicylic Acid and Evaluation of Their COX Inhibitory Potential

Salicylic acid is an NSAID with serious side effects on the GIS. The side effects of salicylic acid on the GIS are slightly reduced by acetylating salicylic acid. 12 new ester analogs of salicylic acid were synthesized with high yields in this study. The chemical structures of the synthesized compounds were characterized by ¹ H-NMR, ¹³ C-NMR, and HRMS spectra. The inhibitory potential of the compounds was evaluated on COXs by in vitro and in silico studies. The COX2 inhibitory activity of the most potent inhibitor MEST1 (IC₅₀ : 0.048 μM) was found to be much higher than the COX2 inhibitory activity of aspirin (IC₅₀ : 2.60 μM). In docking studies, the strongest inhibitor among the compounds synthesized was predicted to be MEST1, with the lowest binding energy. Docking studies revealed that MEST1 extends from the hydrophobic channel to the top of the cyclooxygenase active site, forming various interactions with residues in the binding pocket.

Going Retro, Going Viral: Experiences and Lessons in Drug Discovery from COVID-19

The severity of the COVID-19 pandemic and the pace of its global spread have motivated researchers to opt for repurposing existing drugs against SARS-CoV-2 rather than discover or develop novel ones. For reasons of speed, throughput, and cost-effectiveness, virtual screening campaigns, relying heavily on in silico docking, have dominated published reports. A particular focus as a drug target has been the principal active site (i.e., RNA synthesis) of RNA-dependent RNA polymerase (RdRp), despite the existence of a second, and also indispensable, active site in the same enzyme. Here we report the results of our experimental interrogation of several small-molecule inhibitors, including natural products proposed to be effective by in silico studies. Notably, we find that two antibiotics in clinical use, fidaxomicin and rifabutin, inhibit RNA synthesis by SARS-CoV-2 RdRp in vitro and inhibit viral replication in cell culture. However, our mutagenesis studies contradict the binding sites predicted computationally. We discuss the implications of these and other findings for computational studies predicting the binding of ligands to large and flexible protein complexes and therefore for drug discovery or repurposing efforts utilizing such studies. Finally, we suggest several improvements on such efforts ongoing against SARS-CoV-2 and future pathogens as they arise.

Non-invasive photobiomodulation treatment in an Alzheimer Disease-like transgenic rat model

Alzheimer's disease (AD) is the most common form of dementia in the elderly, causing neuronal degeneration and cognitive deficits that significantly impair independence and quality of life for those affected and their families. Though AD is a major neurodegenerative disease with vast avenues of investigation, there is no effective treatment to cure AD or slow disease progression. The present work evaluated the therapeutic effect of long-term photobiomodulation (PBM) treatment with continuous-wave low-level laser on AD and its underlying mechanism. Methods: PBM was implemented for 2 min, 3 times per week for 16 months in 2-month-old transgenic AD rats. A battery of behavioral tests was performed to measure the effect of PBM treatment on cognitive dysfunction in AD rats. The effects of PBM therapy on typical AD pathologies, including amyloid plaques, intracellular neurofibrillary tangles, neuronal loss, neuronal injury, neuronal apoptosis, and neurodegeneration, were then assessed. The underlying mechanisms were measured using immunofluorescence staining, western blotting analysis, mass spectrometry, primary cortical and hippocampal cell cultures, and related assay kits. Results: PBM treatment significantly improved the typical AD pathologies of memory loss, amyloid plaques, tau hyperphosphorylation, neuronal degeneration, spine damage, and synaptic loss. PBM treatment had several mechanistic effects which may explain these beneficial effects, including 1) regulation of glial cell polarization and inhibition of neuroinflammation, 2) preservation of mitochondrial dynamics by regulating fission and fusion proteins, and 3) suppression of oxidative damage to DNA, proteins, and lipids. Furthermore, PBM enhanced recruitment of microglia surrounding amyloid plaques by improving the expression of microglial IL-3Rα and astrocytic IL-3, which implies a potential role of PBM in improving Aβ clearance. Finally, our results implicate neuronal hemoglobin in mediating the neuroprotective effect of PBM, as Hbα knockdown abolished the neuroprotective effect of PBM treatment. Conclusion: Collectively, our data supports the potential use of PBM treatment to prevent or slow the progression of AD and provides new insights into the molecular mechanisms of PBM therapy.

Ultrahigh Throughput Protein-Ligand Docking with Deep Learning

Ultrahigh-throughput virtual screening (uHTVS) is an emerging field linking together classical docking techniques with high-throughput AI methods. We outline mechanistic docking models' goals and successes. We present different AI accelerated workflows for uHTVS, mainly through surrogate docking models. We showcase a novel feature representation technique, molecular depictions (images), as a surrogate model for docking. Along with a discussion on analyzing screens using regression enrichment surfaces at the tens of billion scale, we outline a future for uHTVS screening pipelines with deep learning.

In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II Diabetes

Type-II diabetes mellitus (T2DM) results from a combination of genetic and lifestyle factors, and the prevalence of T2DM is increasing worldwide. Clinically, both α-glucosidase and α-amylase enzymes inhibitors can suppress peaks of postprandial glucose with surplus adverse effects, leading to efforts devoted to urgently seeking new anti-diabetes drugs from natural sources for delayed starch digestion. This review attempts to explore 10 families e.g., Bignoniaceae, Ericaceae, Dryopteridaceae, Campanulaceae, Geraniaceae, Euphorbiaceae, Rubiaceae, Acanthaceae, Rutaceae, and Moraceae as medicinal plants, and folk and herb medicines for lowering blood glucose level, or alternative anti-diabetic natural products. Many natural products have been studied in silico, in vitro, and in vivo assays to restrain hyperglycemia. In addition, natural products, and particularly polyphenols, possess diverse structures for exploring them as inhibitors of α-glucosidase and α-amylase. Interestingly, an in silico discovery approach using natural compounds via virtual screening could directly target α-glucosidase and α-amylase enzymes through Monte Carto molecular modeling. Autodock, MOE-Dock, Biovia Discovery Studio, PyMOL, and Accelrys have been used to discover new candidates as inhibitors or activators. While docking score, binding energy (Kcal/mol), the number of hydrogen bonds, or interactions with critical amino acid residues have been taken into concerning the reliability of software for validation of enzymatic analysis, in vitro cell assay and in vivo animal tests are required to obtain leads, hits, and candidates in drug discovery and development.

Studying the Structures of Relaxed and Fuzzy Interactions: The Diverse World of S100 Complexes

S100 proteins are small, dimeric, Ca²⁺-binding proteins of considerable interest due to their associations with cancer and rheumatic and neurodegenerative diseases. They control the functions of numerous proteins by forming protein–protein complexes with them. Several of these complexes were found to display “fuzzy” properties. Examining these highly flexible interactions, however, is a difficult task, especially from a structural biology point of view. Here, we summarize the available in vitro techniques that can be deployed to obtain structural information about these dynamic complexes. We also review the current state of knowledge about the structures of S100 complexes, focusing on their often-asymmetric nature.

Enzyme Models-From Catalysis to Prodrugs

Enzymes are highly specific biological catalysts that accelerate the rate of chemical reactions within the cell. Our knowledge of how enzymes work remains incomplete. Computational methodologies such as molecular mechanics (MM) and quantum mechanical (QM) methods play an important role in elucidating the detailed mechanisms of enzymatic reactions where experimental research measurements are not possible. Theories invoked by a variety of scientists indicate that enzymes work as structural scaffolds that serve to bring together and orient the reactants so that the reaction can proceed with minimum energy. Enzyme models can be utilized for mimicking enzyme catalysis and the development of novel prodrugs. Prodrugs are used to enhance the pharmacokinetics of drugs; classical prodrug approaches focus on alternating the physicochemical properties, while chemical modern approaches are based on the knowledge gained from the chemistry of enzyme models and correlations between experimental and calculated rate values of intramolecular processes (enzyme models). A large number of prodrugs have been designed and developed to improve the effectiveness and pharmacokinetics of commonly used drugs, such as anti-Parkinson (dopamine), antiviral (acyclovir), antimalarial (atovaquone), anticancer (azanucleosides), antifibrinolytic (tranexamic acid), antihyperlipidemia (statins), vasoconstrictors (phenylephrine), antihypertension (atenolol), antibacterial agents (amoxicillin, cephalexin, and cefuroxime axetil), paracetamol, and guaifenesin. This article describes the works done on enzyme models and the computational methods used to understand enzyme catalysis and to help in the development of efficient prodrugs.

Computer-assisted evaluation of plant-derived β-secretase inhibitors in Alzheimer’s disease

Background

Alzheimer’s disease (AD) is a progressive neurodegenerative age-related dementia that results in memory loss of elderly people. Many hypotheses have been formally articulated till now to decipher the pathogenesis of this disease. According to the compelling amyloidogenic hypothesis, β-secretase is a key regulatory enzyme in AD development and is therefore considered as one of the major targets for the development of drugs to treat AD. In this study, 40 plant-derived phytocompounds, proven to have β-secretase inhibitory activity in different laboratory experiments, were evaluated using computational approaches in order to identify the best possible β-secretase inhibitor(s).

Results

Amentoflavone (IFD score: − 7.842 Kcal/mol), Bilobetin (IFD score: − 7.417 Kcal/mol), and Ellagic acid (IFD score: − 6.923 Kcal/mol) showed highest β-secretase inhibitory activities with high binding affinity among all the selected phytocompounds and interacted with key amino acids, i.e., Asp32, Tyr71, and Asp228 in the catalytic site of β-secretase. Moreover, these three molecules exhibited promising results in different drug potential assessment experiments and displayed signs of correlation with significant pharmacological and biological activities.

Conclusion

Amentoflavone, Biolbetin, and Ellagic acid could be investigated further in developing β-secretase-dependent drug for the effective treatment of AD. However, additional in vivo and in vitro experiments might be required to strengthen the findings of this experiment.

Inhibitory Activity of Quercetin 3-O-Arabinofuranoside and 2-Oxopomolic Acid Derived from Malus domestica on Soluble Epoxide Hydrolase

Flavonoids and triterpenoids were revealed to be the potential inhibitors on soluble epoxide hydrolase (sEH). The aim of this study is to reveal sEH inhibitors from Fuji apples. A flavonoid and three triterpenoids derived from the fruit of Malus domestica were identified as quercetin-3-O-arabinoside (1), ursolic acid (2), corosolic acid (3), and 2-oxopomolic acid (4). They had half-maximal inhibitory concentration of the inhibitors (IC₅₀) values of 39.3 ± 3.4, 84.5 ± 9.5, 51.3 ± 4.9, and 11.4 ± 2.7 μM, respectively, on sEH. The inhibitors bound to allosteric sites of enzymes in mixed (1) and noncompetitive modes (2–4). Molecular simulations were carried out for inhibitors 1 and 4 to calculate the binding force of ligands to receptors. The inhibitors bound to the left (1) and right (4) pockets next to the enzyme’s active site. Based on analyses of their molecular docking and dynamics, it was shown that inhibitors 1 and 4 can stably bind sEH at 1 bar and 300 K. Finally, inhibitors 1 and 4 are promising candidates for further studies using cell-based assays and in vivo cardiovascular tests.

Curcumin analogs as the inhibitors of TLR4 pathway in inflammation and their drug like potentialities: a computer-based study

Toll-like receptor 4 (TLR4) pathway is one of the major pathways that mediate the inflammation in human body. There are different anti-inflammatory drugs available in the market which specifically act on different signaling proteins of TLR4 pathway but they do have few side effects and other limitations for intended use in human body. In this study, Curcumin and its different analogs have been analyzed as the inhibitors of signaling proteins, i.e. Cycloxygenase-2 (COX-2), inhibitor of kappaβ kinase (IKK) and TANK binding kinase-1 (TBK-1) of TLR4 pathway using different computational tools. Initially, three compounds were selected for respective target based on free binding energy among which different compounds were reported to have better binding affinity than commercially available drug (control). Upon continuous computational exploration with induced fit docking (IFD), 6-Gingerol, Yakuchinone A and Yakuchinone B were identified as the best inhibitors of COX-2, IKK, and TBK-1 respectively. Then their drug-like potentialities were analyzed in different experiments where they were also predicted to perform well. Hopefully, this study will uphold the efforts of researchers to identify anti-inflammatory drugs from natural sources.

Inhibitory Activity of Flavonoids, Chrysoeriol and Luteolin-7-O-Glucopyranoside, on Soluble Epoxide Hydrolase from Capsicum chinense

: Three flavonoids derived from the leaves of Capsicum chinense Jacq. were identified as chrysoeriol (1), luteolin-7-O-glucopyranoside (2), and isorhamnetin-7-O-glucopyranoside (3). They had IC50 values of 11.6±2.9, 14.4±1.5, and 42.7±3.5 µg/mL against soluble epoxide hydrolase (sEH), respectively. The three inhibitors (1-3) were found to non-competitively bind into the allosteric site of the enzyme with Ki values of 10.5±3.2, 11.9 ±2.8 and 38.0±4.1 µg/mL, respectively. The potential inhibitors 1 and 2 were located at the left edge ofa U-tube shape that contained the enzyme active site. Additionally, we observed changes in several factors involved in the binding of these complexes under 300 K and 1 bar. Finally, it was confirmed that each inhibitor, 1 and 2, could be complexed with sEH by the "induced fit" and "lock-and-key" models.

Synthesis of Piperidine Conjugated Dihydroquinazolin-4(1H)-ones and their Antiproliferative Activity, Molecular Docking Studies and DFT Calculations

Background:

Xanthatin, fluoropyrimidine and thienopyrimidine, pyrazolopyrimidine, pyrimidine carboxamides, and SKLB1002 are reported as VEGFR2 tyrosine kinase inhibitors. Recently, many studies related to different heterocycles conjugated with dihydroquinazolinones are known to have very good biological activities. In this study, we are intended to explore the cytotoxic studies of piperidine conjugated dihydroquinazolinones against colorectal/colon cancer cell lines and along with molecular docking studies and DFT calculations.

Methods:

The colorectal/colon cell lines HCT116 and A549 cell lines were treated with these compounds and cytotoxic activities were evaluated by MTT dye uptake method. We performed molecular modelling for compound 3d using the Auto Dock software. The binding of compound 3d with target proteins was studied with the collection of experimentally determined PDB database. Optimized geometry by DFT calculations was performed with B3LYP/6-31G (d) basis set.

Results:

Piperidine-conjugated dihydroquinazolinone analogues displayed anticancer activity. Particularly, the compound 3d with electron-withdrawing substituents on a phenyl ring showed significant cytotoxicity against HCT116 and A549 cell lines. Molecular docking studies proved that the compound 3d has good fitting by forming hydrogen bonds with amino acid residues at the active sites of VEGFR2. The HOMO, LUMO, their energies and UV visible spectrum were predicted using DFT calculations.

Conclusion:

Four piperidine-conjugated dihydroquinazolinones were synthesized and evaluated against colorectal and colon cancer cell lines. Compound 3d significantly inhibited the growth of HCT116 and A549. Molecular docking studies displayed good fitting of compound 3d by forming different H-bonds with the amino acid at the active sites of the VEGFR2 target. Using a theoretical approach, we optimized HOMO and LUMO plots for the compound 3d.

In Silico Study Probes Potential Inhibitors of Human Dihydrofolate Reductase for Cancer Therapeutics

Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes thereduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of humanDHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cellproliferation. In the current study, ligand-based pharmacophore modeling identified and evaluatedthe critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generatedfrom known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS)deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features,including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and onehydrophobic (HYP). Hypo1 was validated using Fischer's randomization, test set, and decoy setvalidations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex,National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered byan absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test andLipinski's rule of five, where the drug-like hit compounds were identified. The hit compounds weredocked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67(docking score for the reference compound), clustering analysis, and hydrogen bond interactionswere identified. Furthermore, molecular dynamics (MD) simulation identified three compounds asthe best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogenbond interactions with hDHFR, and low binding free energy (-127 kJ/mol to -178 kJ/mol). Finally,the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFRin human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoidarthritis chemotherapeutics.

Need for comprehensive standardization strategies for marketed Ayurveda formulations

Ayurveda is known for the use of poly-herbal formulations and multi-component therapeutics for the management of health and diseases. Several pharmaceutical companies are manufacturing and marketing different Ayurvedic formulations, prepared as per the classical texts and the regulatory standards. However, on a cursory glance, marked variations are observed amongst the same formulations manufactured by different companies. This raises questions on the quality standards. Drugs or formulations are expected to exert a desired biological activity at particular concentrations of their chemical constituents. The overall aim of drug standardization is to ensure the quality, efficacy and uniformity of the products, in terms of their chemical and biological properties, across the manufactures. In this article, the authors intend to open up a discussion on the need for comprehensive standardization strategies for marketed Ayurveda formulations taking Lodhrasavam (a classical Ayurveda preparation) as an example. Lodhrasavam procured from six reputed Ayurveda drug manufacturers showed significant variations in their sensorial, physico-chemical, chromatographic as well as biological properties. This is a matter of serious concern and need to be addressed effectively to derive better standardization strategies for Ayurvedic formulations.

New Insights Into DNA Helicases as Druggable Targets for Cancer Therapy

Small molecules that deter the functions of DNA damage response machinery are postulated to be useful for enhancing the DNA damaging effects of chemotherapy or ionizing radiation treatments to combat cancer by impairing the proliferative capacity of rapidly dividing cells that accumulate replicative lesions. Chemically induced or genetic synthetic lethality is a promising area in personalized medicine, but it remains to be optimized. A new target in cancer therapy is DNA unwinding enzymes known as helicases. Helicases play critical roles in all aspects of nucleic acid metabolism. We and others have investigated small molecule targeted inhibition of helicase function by compound screens using biochemical and cell-based approaches. Small molecule-induced trapping of DNA helicases may represent a generalized mechanism exemplified by certain topoisomerase and PARP inhibitors that exert poisonous consequences, especially in rapidly dividing cancer cells. Taking the lead from the broader field of DNA repair inhibitors and new information gleaned from structural and biochemical studies of DNA helicases, we predict that an emerging strategy to identify useful helicase-interacting compounds will be structure-based molecular docking interfaced with a computational approach. Potency, specificity, drug resistance, and bioavailability of helicase inhibitor drugs and targeting such compounds to subcellular compartments where the respective helicases operate must be addressed. Beyond cancer therapy, continued and new developments in this area may lead to the discovery of helicase-interacting compounds that chemically rescue clinically relevant helicase missense mutant proteins or activate the catalytic function of wild-type DNA helicases, which may have novel therapeutic application.