Site Of Target Protein Research Articles

Design, synthesis, structural characterization, cytotoxicity and computational studies of Usnic acid derivative as potential anti-breast cancer agent against MCF7 and T47D cell lines

Development of novel inhibitors is necessary to counteract the rising prevalence of breast cancer (BC) in women in recent years, as evidenced by the side-effect profiles of a few clinically approved inhibitors. In this study, the usnic acid derivative (UA1) was synthesized due to the effectiveness of usnic acid (UA) against BC cell line. Furthermore, the structure of synthesized compound was determined using FT-IR, 1H-NMR, 13C-NMR, HSQC, and HMBC spectroscopic techniques. The anticancer potential of UA1 was assessed using the MTT assay on two different cell lines of BC including MCF7 and T47D. To ascertain the binding affinity and stability of the docking complex, further procedures included the in silico molecular docking, molecular dynamic simulation, principal component analysis, and binding free energy experiments. The cytotoxicity results show that the UA1 exhibits strong antitumor activities and comparable effects against BC cell lines with the IC50 values of 9.21µM for MCF7 cell and 14.8µM for T47D cell, respectively, where the positive control cisplatin showed the IC50 values of 8.95µM for MCF7 cell and 10.9µM for T47D cell. Additionally, the molecular docking results of UA1 showed that it interacts strongly into the active site of target protein. Molecular dynamics simulation results also revealed that the docking complex was formed stability with the RMSD and RMSF values of 0.50nm and 0.19nm, respectively. According to the PCA analysis, the target protein displays good conformational space behaviour when bound with UA1. Furthermore, the UA1 showed the free binding energy value of -18.52kcal/mol with the target protein, which indicating that UA1 may prevent BC.

Exploring 5-Nitro-N-phenyl-3-(phenylamino)-1H-indazole-1-carboxamide (5-NPIC) Derivatives as Anticancer Agents: Synthesis, Docking and Molecular Dynamics Insights

The synthesis and characterization of a series of 5-nitro-[Formula: see text]-phenyl-3-(phenylamino)-1[Formula: see text]-indazole-1-carboxamide 5-NPIC derivatives (5a– 5v) have been reported as anticancer agents in this study. These derivatives were synthesized by reacting 3-chloro-5-nitro-[Formula: see text]-phenyl-1[Formula: see text]-indazole-1-carboxamide (4) with a variety of aniline derivatives in isopropanol. FT-IR, 1H-NMR, 13C-NMR and mass spectral methods were employed to confirm the structures of analogues (5a– 5v). The anticancer activity evaluation of compounds 5a– 5v revealed that 3-((3-methoxyphenyl) amino)-5-nitro-[Formula: see text]-phenyl-1[Formula: see text]-indazole-1-carboxamide (5j) exhibited good efficacy. The stability of ligand–protein complexes was systematically evaluated using molecular dynamics simulations (MDS), which demonstrated a consistent and robust binding of the most potent compound within the binding sites of target proteins. The results confirmed the anticancer activity, which was further substantiated by comprehensive molecular docking analyses that revealed complex interactions involving hydrophobic contacts, electrostatic forces and hydrogen bonds. Our results would collectively provide invaluable insights into the intricate molecular structure and dynamics of receptor target sites, thereby establishing a solid foundation for the development of novel and potent anticancer agents with optimistic pharmaceutical implications in near future.

Proanthocyanidin Regulates NETosis and Inhibits the Growth and Proliferation of Liver Cancer Cells - In Vivo, In Vitro and In Silico Investigation.

Liver cancer ranks third in global cancer-related mortality, with about 700,000 deaths recorded yearly, making it one of the most common cancers worldwide. Even though prognoses differ according to the severity of the diseases, many patients now exhibit an increased life cycle since the implementation of chemotherapy. In the current study, we investigated the effect of proanthocyanidin ‒a polyphenol molecule found in many plants‒ on the proliferation and invasion of liver cancer cells. In particular, we determined the effect of proanthocyanidin on the serum levels of four strategic liver cancer target, TNFα, IL-6, cfDNA, and IL-1β. Further molecular insight on the inhibitory mechanism of proanthocyanidin against TNFα, IL-6, and IL-1β was obtained via molecular docking, molecular dynamics simulations and binding free energy calculations. Results showed that proanthocyanidin inhibited the growth of HepG2 and HEP3B cells, and effectively reduced clonogenic survival and invasion potential when compared to control cells. Proanthocyanidin was also found to suppress the expression of Bcl-2 (26 kDa) protein in HepG2 cells, while increasing the expression of Bax (21 kDa). Molecular dynamics (MD) and thermodynamic binding free energy calculations showed that proanthocyanidin maintained stable binding within the active site of target proteins across the entire 100 ns MD simulation period, and its binding affinity outscored respective control molecules.In conclusion, the multifaceted analysis showcased in this study demonstrated promising anti-cancer effect of proanthocyanidin on HepG2 and HEP3B cancer cells, highlighting its potential as a viable liver cancer therapeutic alternative.

Turbocharging protein binding site prediction with geometric attention, inter-resolution transfer learning, and homology-based augmentation

BackgroundLocating small molecule binding sites in target proteins, in the resolution of either pocket or residue, is critical in many drug-discovery scenarios. Since it is not always easy to find such binding sites using conventional methods, different deep learning methods to predict binding sites out of protein structures have been developed in recent years. The existing deep learning based methods have several limitations, including (1) the inefficiency of the CNN-only architecture, (2) loss of information due to excessive post-processing, and (3) the under-utilization of available data sources.MethodsWe present a new model architecture and training method that resolves the aforementioned problems. First, by layering geometric self-attention units on top of residue-level 3D CNN outputs, our model overcomes the problems of CNN-only architectures. Second, by configuring the fundamental units of computation as residues and pockets instead of voxels, our method reduced the information loss from post-processing. Lastly, by employing inter-resolution transfer learning and homology-based augmentation, our method maximizes the utilization of available data sources to a significant extent.ResultsThe proposed method significantly outperformed all state-of-the-art baselines regarding both resolutions—pocket and residue. An ablation study demonstrated the indispensability of our proposed architecture, as well as transfer learning and homology-based augmentation, for achieving optimal performance. We further scrutinized our model’s performance through a case study involving human serum albumin, which demonstrated our model’s superior capability in identifying multiple binding sites of the protein, outperforming the existing methods.ConclusionsWe believe that our contribution to the literature is twofold. Firstly, we introduce a novel computational method for binding site prediction with practical applications, substantiated by its strong performance across diverse benchmarks and case studies. Secondly, the innovative aspects in our method— specifically, the design of the model architecture, inter-resolution transfer learning, and homology-based augmentation—would serve as useful components for future work.

Chemical composition and bio-efficacy of agro-waste plant extracts and their potential as bioinsecticides against Culex pipiens mosquitoes

Mosquitoes are considered one of the most lethal creatures on the planet and are responsible for millions of fatalities annually through the transmission of several diseases to humans. Green trash is commonly employed in agricultural fertilizer manufacturing and microbial bioprocesses for energy production. However, there is limited information available on the conversion of green waste into biocides. This study investigates the viability of utilizing green waste as a new biopesticide against Culex pipiens mosquito larvae. The current study found that plant extracts from Punica granatum (98.4 % mortality), Citrus sinensis (92 % mortality), Brassica oleracea (88 % mortality), Oryza sativa (81.6 % mortality), and Colocasia esculenta (53.6 % mortality) were very good at killing Cx. pipiens larvae 24 h post-treatment. The LC50 values were 314.43, 370.72, 465.59, 666.67, and 1798.03 ppm for P. granatum, C. sinensis, B. oleracea, O. sativa, and C. esculenta, respectively. All plant extracts, particularly P. granatum extract (14.93 and 41.87 U/g), showed a significant reduction in acid and alkaline phosphate activity. Additionally, pomegranate extract showed a significant decrease (90 %) in field larval density, with a stability of up to five days post-treatment. GC–MS results showed more chemical classes, such as terpenes, esters, fatty acids, alkanes, and phenolic compounds. HPLC analysis revealed that the analyzed extracts had a high concentration of phenolic and flavonoid components. Moreover, there are many variations among these plants in the amount of each compound. The docking interaction showed a simulation of the atomic-level interaction between a protein and a small molecule through the binding site of target proteins, explaining the most critical elements influencing the enzyme's activity or inhibitions. The study's findings showed that the various phytochemicals found in agro-waste plants had high larvicidal activity and provide a safe and efficient substitute to conventional pesticides for pest management, as well as a potential future in biotechnology.

Identifying plant-derived antiviral alkaloids as dual inhibitors of SARS-CoV-2 main protease and spike glycoprotein through computational screening.

COVID-19 is currently considered the ninth-deadliest pandemic, spreading through direct or indirect contact with infected individuals. It has imposed a consistent strain on both the financial and healthcare resources of many countries. To address this challenge, there is a pressing need for the development of new potential therapeutic agents for the treatment of this disease. To identify potential antiviral agents as novel dual inhibitors of SARS-CoV-2, we retrieved 404 alkaloids from 12 selected medicinal antiviral plants and virtually screened them against the renowned catalytic sites and favorable interacting residues of two essential proteins of SARS-CoV-2, namely, the main protease and spike glycoprotein. Based on docking scores, 12 metabolites with dual inhibitory potential were subjected to drug-likeness, bioactivity scores, and drug-like ability analyses. These analyses included the ligand-receptor stability and interactions at the potential active sites of target proteins, which were analyzed and confirmed through molecular dynamic simulations of the three lead metabolites. We also conducted a detailed binding free energy analysis of pivotal SARS-CoV-2 protein inhibitors using molecular mechanics techniques to reveal their interaction dynamics and stability. Overall, our results demonstrated that 12 alkaloids, namely, adouetine Y, evodiamide C, ergosine, hayatinine, (+)-homoaromoline, isatithioetherin C, N,alpha-L-rhamnopyranosyl vincosamide, pelosine, reserpine, toddalidimerine, toddayanis, and zanthocadinanine, are shortlisted as metabolites based on their interactions with target proteins. All 12 lead metabolites exhibited a higher unbound fraction and therefore greater distribution compared with the standards. Particularly, adouetine Y demonstrated high docking scores but exhibited a nonspontaneous binding profile. In contrast, ergosine and evodiamide C showed favorable binding interactions and superior stability in molecular dynamics simulations. Ergosine demonstrated exceptional performance in several key pharmaceutical metrics. Pharmacokinetic evaluations revealed that ergosine exhibited pronounced bioactivity, good absorption, and optimal bioavailability. Additionally, it was predicted not to cause skin sensitivity and was found to be non-hepatotoxic. Importantly, ergosine and evodiamide C emerged as superior drug candidates for dual inhibition of SARS-CoV-2 due to their strong binding affinity and drug-like ability, comparable to known inhibitors like N3 and molnupiravir. This study is limited by its in silico nature and demands the need for future in vitro and in vivo studies to confirm these findings.

Studies on N-(6-Indazolyl) benzenesulfonamide Derivatives as Potential Anticancer Agents: Integrating Synthesis, In silico Docking, and Molecular Dynamics Simulations

A new series of benzenesulfonamide derivatives, namely N-(1-(2-chloropyrimidin-4-yl)-1[Formula: see text]-indazol-5-yl) compounds (4a-i) and N-(1-(2-chloropyrimidin-4-yl)-6-ethoxy-1[Formula: see text]-indazol-5-yl) derivatives (5a-i), were synthesized. This was achieved by reducing 1-(2-halopyrimidin-4-yl)-5-nitro-1[Formula: see text]-indazole (3) with SnCl2, followed by reacting with various aryl sulphonyl chlorides in pyridine. Structural confirmation was carried out through IR, 1H-NMR, [Formula: see text]C-NMR and mass spectral methods. Anticancer activity evaluation of compounds 4a-i and 5a-i revealed that N-(1-(2-chloropyrimidin-4-yl)-6-ethoxy-1H-indazol-5-yl)-2-nitrobenzenesulfonamide (5b) displayed exceptional efficacy. Molecular dynamics simulations were employed to rigorously assess the stability of ligand–protein complexes, highlighting a consistent and robust binding of the most potent compound within the binding sites of target proteins. The results unequivocally affirmed the remarkable anticancer activity, supported by comprehensive molecular docking analyses uncovering intricate interactions involving hydrogen bonds, electrostatic forces and hydrophobic contacts. These findings collectively offer invaluable insights into the complex molecular structure and dynamics of receptor target sites, establishing a robust foundation for the development of novel and potent anticancer agents with promising pharmaceutical implications.

Bioactive molecules isolated from Cymbopogon flexuosus and Monarda citriodora essential oils: Chemical profiling, antimycotic potential, and molecular docking studies against green and blue molds of Kinnow

Among the most alarming postharvest fungal pathogens affecting the shelf life of citrus fruits are green (Penicillium digitatum) and blue (Penicillium italicum) molds. This in vitro study was aimed to evaluate the essential oils (EOs) of Cymbopogon flexuosus (CF) and Monarda citriodora (MC) and their principal components against these fungal pathogens. The composition of selected EOs was analyzed using Gas Chromatography- Mass Spectrometry (GC-MS) and Gas Chromatography-Flame Ionization Detector (GC-FID). Citral (83.81%) and thymol (62.51%) were identified as major components and were isolated by column chromatography from CF and MC EO respectively followed by characterization using spectral techniques such as Fourier Transform Infrared Spectroscopy (FTIR), Proton Nuclear Magnetic Resonance Spectroscopy (1H-NMR) and Carbon Nuclear Magnetic Resonance Spectroscopy (13C-NMR). Among EOs and their major components, thymol displayed promising potential against both Penicillium species with MIC values of 50 and 80 mg L-1 respectively. Molecular docking studies also confirmed the stable binding interaction of both components, particularly thymol with the active sites of target proteins i.e. 14-α-demethylase and chitin synthase of P. digitatum and P. italicum with the docking scores of -5.07, -5.41 kcal/mol and -5.78, -5.23 kcal/mol respectively. Optical microscopy studies revealed hyphal thinning and fragmentation at frequent sites with contraction of cytoplasmic content indicating incipient plasmolysis. The tested principal components, citral and thymol were predicted to exhibit similar mechanism of action to that of synthetic recommended molecules as revealed by molecular docking. Therefore, these findings provide empirical support to explore thymol as a promising eco-friendly antifungal agent for postharvest application in Kinnow.

Covalent adduct formation of histone with organophosphorus pesticides in vitro

It is established that organophosphorus pesticide (OPP) toxicity results from modification of amino acids in active sites of target proteins. OPPs can also modify unrelated target proteins such as histones and such covalent histone modifications can alter DNA-binding properties and lead to aberrant gene expression. In the present study, we report on non-enzymatic covalent modifications of calf thymus histones adducted to selected OPPs and organophosphate flame retardants (OPFRs) in vitro using a bottom-up proteomics method approach. Histones were not found to form detectable adducts with the two tested OPFRs but were avidly modified by a few of the seven OPPs that were tested in vitro. Dimethyl phosphate (or diethyl phosphate) adducts were identified on Tyr, Lys and Ser residues. Most of the dialkyl phosphate adducts were identified on Tyr residues. Methyl and ethyl modified histones were also detected. Eleven amino residues in histones showed non-enzymatic covalent methylation by exposure of dichlorvos and malathion. Our bottom-up proteomics approach showing histone-OPP adduct formation warrants future studies on the underlying mechanism of chronic illness from exposure to OPPs.

Investigating the interplay of genetic variations, MCP-1 polymorphism, and docking with phytochemical inhibitors for combatting dengue virus pathogenicity through in silico analysis

Abstract Understanding ten significant of dengue virus a paramount due to its persistent threat across the globe causing numerous epidemic and millions of deaths every year. Despite advancement in healthcare, emerging outbreaks continue to claim millions of lives annually. The virus with its various serotype possesses a significant challenge to public health worldwide, its transmission through the arthropods which feed on the blood of higher animals further exacerbates its impact. This elucidating the mechanism and factor contributing to dengue virus pathogenicity is essential for developing strategies to combat its spreading. A systemic review is done while studying about Dengue virus serotypes to evaluate the relationship of dengue with other viral load and to develop an inhibitor in viral protein by using different bioinformatics tools in silico molecular docking. Phytochemicals were chosen to hit the target site of protein for inhibiting its active site in pathogenesis of Dengue virus. A phylogenetic lineage was observed of virus with other members of its family. Dengue virus has same similarities in some part of genomic structure with other viruses. Data bases were used to trace the genome of the virus. Different components of virus were analyzed and link was developed among those components within virus and other family members. Protein docking was performed by using the bioinformatics software auto docking. A pharmaceutical drug designing was developed to create inhibitor of protein structure in Dengue virus serotype-2. A comprehensive review of the methodology employed in our study including the experimental and computational techniques were utilized. Further we presented the results by analysis of genetic variation MCP-1 polymorphism and docking phytochemical inhibitors.

Computational insight into the spectroscopic and molecular docking analysis of estrogen receptor with ligand 2,3-dimethyl-N[2-(hydroxy)benzylidene] aniline

A comprehensive approach encompassing a blend of spectral techniques and Density Functional Theory (DFT) was employed to elucidate the electronic, vibrational, structural, and nonlinear optical properties of 2,3-dimethyl-N[2-(Hydroxy)benzylidene] aniline (DNHBA). The investigation of this chemical compound involved a meticulous examination using spectroscopic techniques (FTIR, FT-Raman). The DFT calculations utilized the B3LYP method in conjunction with 6-311G (d, p) basis sets. The findings were substantiated by comparing the estimated vibrational frequencies and molecule geometry with experimental data. Using the Time Dependent −Density Functional Theory (TD-DFT) method to calculate the energy band gap of the compound at different solvents. We looked into frontier molecular orbitals (FMO) Molecular electrostatic potential (MEP) and natural bond analysis (NBO) to determine the compound’s kinetic stability and chemical reactivity. Hirshfeld surface (HS) analysis calculated the O–H..O, H-H and intermolecular interaction energy of the compound. The electron density distribution, interactions, and excitation within the title molecule are illustrated by performing topological analyses (RDG, ELF and LOL) using the Multiwfn software. In addition to these assessments, molecular dynamics provides an understanding of the system's dynamic development over a predefined duration during which atoms and molecules are permitted to interact. Utilizing the molecular docking approach allows us to energize the atomic-level interplay between small molecules and proteins within the binding sites of target proteins. This approach enhances our comprehension of vital biochemical processes associated with the behavior of small molecule. The intricacy and hazards associated with drug discovery and development processes have increased dramatically, leading to higher drug research costs.

Deciphering the multi-functional role of Indian propolis for the management of Alzheimer's disease by integrating LC-MS/MS, network pharmacology, molecular docking, and in-vitro studies.

The conventional one-drug-one-disease theory has lost its sheen in multigenic diseases such as Alzheimer's disease (AD). Propolis, a honeybee-derived product has ethnopharmacological evidence of antioxidant, anti-inflammatory, antimicrobial and neuroprotective properties. However, the chemical composition is complex and highly variable geographically. So, to leverage the potential of propolis as an effective treatment modality, it is essential to understand the role of each phytochemical in the AD pathophysiology. Therefore, the present study was aimed at investigating the anti-Alzheimer effect of bioactive in Indian propolis (IP) by combining LC-MS/MS fingerprinting, with network-based analysis and experimental validation. First, phytoconstituents in IP extract were identified using an in-house LC-MS/MS method. The drug likeness and toxicity were assessed, followed by identification of AD targets. The constituent-target-gene network was then constructed along with protein-protein interactions, gene pathway, ontology, and enrichment analysis. LC-MS/MS analysis identified 16 known metabolites with druggable properties except for luteolin-5-methyl ether. The network pharmacology-based analysis revealed that the hit propolis constituents were majorly flavonoids, whereas the main AD-associated targets were MAOB, ESR1, BACE1, AChE, CDK5, GSK3β, and PTGS2. A total of 18 gene pathways were identified to be associated, with the pathways related to AD among the topmost enriched. Molecular docking analysis against top AD targets resulted in suitable binding interactions at the active site of target proteins. Further, the protective role of IP in AD was confirmed with cell-line studies on PC-12, in situ AChE inhibition, and antioxidant assays.

Evaluation of influence ofButea monospermafloral extract on inflammatory biomarkers

AbstractButea monospermais a deciduous tree, widely distributed throughout India, Burma, and Ceylon. The present study was intended to investigate the anti-inflammatory effects ofButea monospermaon the induced inflammatory model by evaluating pro-inflammatory biomarkers and their computational analysis. The anti-inflammatory activity may be attributed to the phyto-constituents for inhibitory effects on the two pro-inflammatory mediators (IL-8 and TNF-α). For this purpose, rats (n= 48) were equally divided in each group, i.e., 8 each in the negative and positive control and 32 in the experimental group with 8 rats for each dose, i.e., 50, 100, 200, and 400 mg/kg. TNF-α and IL-8 were tested by serum enzyme-linked immunosorbent assay (ELISA). The ELISA results showed 400 mg/kg dose as the potent anti-inflammatory. The binding sites of target proteins (TNF-α and IL-8) were docked with the active compounds (butrin and butein) ofButea monosperma. The butrin (target: TNF-α) and butein (target: IL-8) showed −8.4 and −6.0 kcal/mol binding energies, respectively, compared to the (diclofenac) standard drug with −6.8 kcal/mol binding energy. Hence, we concluded thatButea monospermacan be subjected to as a useful anti-inflammatory drug.

The Rise of Boron-Containing Compounds: Advancements in Synthesis, Medicinal Chemistry, and Emerging Pharmacology.

Boron-containing compounds (BCC) have emerged as important pharmacophores. To date, five BCC drugs (including boronic acids and boroles) have been approved by the FDA for the treatment of cancer, infections, and atopic dermatitis, while some natural BCC are included in dietary supplements. Boron's Lewis acidity facilitates a mechanism of action via formation of reversible covalent bonds within the active site of target proteins. Boron has also been employed in the development of fluorophores, such as BODIPY for imaging, and in carboranes that are potential neutron capture therapy agents as well as novel agents in diagnostics and therapy. The utility of natural and synthetic BCC has become multifaceted, and the breadth of their applications continues to expand. This review covers the many uses and targets of boron in medicinal chemistry.

Mechanistic insight into the membrane disrupting properties of thymol in Candida species

Candida infection is a major problem in immunocompromised patients and has become a significant public health concern in recent years due to high toxicity, multidrug resistance and unfavourable side effects of conventional antifungal drugs. This study aims to investigate the antifungal efficacy of thymol, a natural monoterpenoid, on the membrane integrity of Candida albicans, Candida glabrata and Candida tropicalis. Minimum inhibitory concentrations (MICs) of thymol were 32 µg/ml, 63 µg/ml, and 125 µg/ml for C. albicans, C. tropicalis and C. glabrata, respectively. The minimum fungicidal concentrations (MFC) were 64 µg/ml, 110 µg/ml and 240 µg/ml, respectively. At MIC, thymol treated cells showed complete suppression of cell growth (growth kinetics, disc diffusion), altered morphology (scanning electron microscopy), leakage of intracellular macromolecules (absorption at 260 nm), significant reduction in ergosterol levels and inhibition of plasma membrane H+-ATPase (Pma1) activity. The disruption of the fungal membranes by thymol was further confirmed by propidium iodide uptake using flow cytometry and confocal microscopy. In silico studies with membrane-bound proteins (lanosterol 14-α demethylase (LDM) and Pma1), showed good binding affinity of −6.3 kcal/mol and −6.7 kcal/mol, respectively, and formed hydrogen bonds with crucial amino acid residues at the active site of target proteins. With low MIC values, negligible host toxicity, desirable ADME properties, thymol has immense potential as a potent antifungal drug that can be used for developing mechanism-based drugs as it has specific binding affinity for specific target proteins. Studies using animal models are required for further validation.

ARTR-seq for determining RNA-binding protein target sites through in situ reverse transcription.

ARTR-seq for determining RNA-binding protein target sites through in situ reverse transcription.

C7‐Halomethylene/methyl‐C3‐thiophenyl‐spirocyclic‐β‐lactams: Synthesis, X‐ray Analysis, Antimicrobial Evaluation, Cytotoxicity Profile and Molecular Docking Interactions

AbstractIn the realm of healthcare, the continuous evolution of new alternative antimicrobial agents provides hope in addressing the progressively daunting issue of severe multidrug resistance. In our quest to confront drug resistance, we explored the conjugation of thiophene motif with β‐lactams into single matrix to develop a series of spirocyclic‐β‐lactams. For this, stereoselective synthesis of cis‐C3‐alkyloxy‐C4‐thiophenyl substituted monocyclic β‐lactams was achieved which were further subjected to intramolecular sulfenyl‐cyclization to furnish C7‐halomethylene/methyl‐C3‐thiophenyl substituted spirocyclic‐β‐lactams. The synthesized compounds were investigated in vitro for their potential activity against six multidrug‐resistant bacterial strains. The most promising C7‐iodomethylene‐C3‐thiophenyl‐spirocyclic‐β‐lactam 7 a appended with 4′‐methoxyphenyl moiety, exhibited acceptable activity against B. cereus and P. aeruginosa with MIC values of 0.75 and 6.25 μg/mL respectively, surpassing ampicillin and vancomycin. Furthermore, this compound demonstrated antifungal effectiveness against C. tropicalis (1.5 μg/mL). On the basis of substituent type and their respective positions, compounds possessing −OCH3 and −C=CHX (halomethylene) groups exhibited more inhibitory potential than others. Active derivatives tested for their cytotoxicity on normal human hepatic (THLE‐2) cell lines confirmed their non‐toxic nature. Further, molecular docking studies predicted the favourable binding interactions of spirocycles within active sites of target proteins. Moreover, several compounds illustrate satisfactory in silico ADME profile. These outcomes provided bright prospect for development of spirocyclic‐β‐lactams as potential solution to combat evolving multidrug resistance.

AutoDock Koto: A Gradient Boosting Differential Evolution for Molecular Docking

Molecular docking plays a vital role in modern drug discovery, by supporting predictions of the binding modes and affinities of ligands at the binding site of target proteins. Several docking programs have been developed for both commercial and academic applications. Typically, a docking program’s performance depends on the sampling algorithm used to generate the ligand’s potential conformations and the scoring function applied to evaluate and rank these conformations. Evolutionary algorithms are widely used as sampling algorithms in docking programs. However, both the linkage problem and the dimensionality degenerate the search ability of evolutionary algorithms in the docking process. Therefore, a newly designed docking program named AutoDock Koto was developed in this study, which adopts a novel gradient boosting differential evolution algorithm to effectively address these issues. Experimental results show that compared with commonly used docking programs, AutoDock Koto yields dramatic improvements in docking performance based on an extensive dataset of 285 protein-ligand complexes. In addition, due to its strong docking ability, AutoDock Koto was used to identify potential drugs for COVID-19 based on a virtual screening of all approved drugs in our experiments. Sixteen drugs are found to possess low binding energy to the main target protease of SARS-CoV-2, and thus have the potential to treat COVID-19 as antiviral drugs. The source code of AutoDock Koto can be downloaded for free from. https://github.com/codezhouj/Molecular_Docking.

A repository of COVID-19 related molecular dynamics simulations and utilisation in the context of nsp10-nsp16 antivirals

The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of establishing systems and infrastructure to develop vaccines, antiviral drugs, and therapeutic antibodies against emerging pathogens. Typical drug discovery processes involve targeting suitable proteins to effect pathogen replication or to attenuate host responses, by examining either large chemical databases or protein-protein interactions. Following initial screens, molecular dynamics (MD) simulations are critical for gaining further insight into molecular interactions. During the COVID-19 pandemic, many research groups made their simulations widely available, as highlighted by the comprehensive D.E. Shaw Research trajectory database. To investigate protein target sites and evaluate potential lead compounds, we performed over 300 MD simulations relating to COVID-19. We organised our simulations into a repository, which is publicly available at https://epimedlab.org/trajectories/. The trajectories cover a large part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome, and the majority of our MD simulations focused on the identification of potential antivirals. For example, we focused on the S-adenosyl-l-methionine binding site of the nsp10-nsp16 complex, a critical component of viral replication, revealing verbascoside as a potential lead. Moreover, we utilised MD trajectories to explore the interface between the spike protein receptor binding domain and human angiotensin-converting enzyme 2 receptor, with the ultimate aim being investigation of new variants in real-time. Overall, MD simulations are a critical component of the in silico drug discovery process and as highlighted throughout the pandemic, data sharing enables accelerated progress. We have organised our extensive collection of COVID-19 related MD trajectories into an easily accessible repository.

Diabetic wound healing of aloe vera major phytoconstituents through TGF-β1 suppression via in-silico docking, molecular dynamic simulation and pharmacokinetic studies

To restore the integrity of the skin and subcutaneous tissue, the wound healing process involves a complex series of well-orchestrated biochemical and cellular events. Due to the existence of various active components, accessibility and few side effects, some plant extracts and their phytoconstituents are recognised as viable options for wound healing agents. To find possible inhibitors of diabetic wound healing, four main constituents of aloe vera were identified from the literature. TGF-β1 and the compounds were studied using molecular docking to see how they interacted with the active site of target protein (PDB ID: 6B8Y). The pharmacokinetics investigation of the aloe emodin with the highest dock score complied with all the Lipinski’s rule of five and pharmacokinetics criteria. Conformational change in the docked complex of Aloe emodin was investigated with the Amber simulation software, via a molecular dynamic (MD) simulation. The MD simulations of aloe emodin bound to TGF-β1 showed the significant structural rotations and twists occurring from 0 to 200 ns. The estimate of the aloe emodin-TGF-β1 complex’s binding free energy has also been done using MM-PBSA/GBSA techniques. Additionally, aloe emodin has a wide range of enzymatic activities since their probability active (Pa) values is >0.700. ‘Aloe emodin’, an active extract of aloe vera, has been identified as the key chemical in the current investigation that can inhibit diabetic wound healing. Both in-vitro and in-vivo experiments will be used in a wet lab to confirm the current computational findings. Communicated by Ramaswamy H. Sarma