Virtual screening assisted discovery of novel natural products to inhibit the catalytic mechanism of Mycobacterium tuberculosis InhA

Designing novel potent oxindole derivatives as VEGFR2 inhibitors for cancer therapy: Computational insights from molecular docking, drug-likeness, DFT, and structural dynamics studies

Oxindole is a γ-lactam featuring a heterocyclic core, combining pyrrole and benzene rings with a carbonyl group at the second position. This scaffold is present in numerous bioactive compounds, both natural and synthetic, and has emerged as a privileged pharmacophore in medicinal chemistry due to its broad biological activity. Substitution at the 3-position of the 2-oxindole structure has been shown to enhance potency and selectivity, especially in anticancer drug development. Breast cancer, a prevalent and challenging disease affecting millions of women worldwide, underscores an urgent need for more effective treatments. Current therapies often exhibit limited efficacy, significant side effects, and resistance issues, highlighting the demand for novel drugs with improved safety profiles. This study focuses on vascular endothelial growth factor receptor-2 (VEGFR-2), an essential regulator of tumor angiogenesis, as a potential target for breast cancer therapy. Through molecular docking-based virtual screening of 360 designed oxindole derivatives, three compounds (BIATAM, CIHTAM, and IATAM) were identified as potential candidates, each demonstrating high docking scores (>7 kcal/mol) and favorable interactions, including hydrogen bonding, hydrophobic contacts, and stacking. Among these, BIATAM emerged as the lead compound due to its superior docking performance, favorable pharmacokinetic profiles, and compliance with Lipinski's Rule of Five. Density functional theory (DFT) calculations confirmed its chemical stability, while molecular dynamics simulations (MDS) revealed high structural stability. Principal component-based free energy landscape (FEL) analysis highlighted limited conformational flexibility, and MM/PBSA-based binding energy calculations reinforced its strong affinity within the VEGFR-2 binding pocket. These comprehensive computational findings suggest that BIATAM holds promising potential as a novel therapeutic option for treating breast cancer.

Computational design and structural insights into quinazoline-based lead molecules for targeting PARP10 in cancer therapy

Quinazoline scaffolds, a class of nitrogen-containing heterocyclic compounds, are considered a "privileged structure" in drug development due to their broad physiological activities and significant therapeutic potential. Many anti-breast cancer therapies are designed using this pharmacophore. Structural modifications such as halogen substitution and aromatic amino group insertion have been explored to improve the anticancer efficacy of quinazoline derivatives. Breast cancer continues to be the primary cause of cancer-related mortality among women, approximately 670,000 deaths globally in 2022, emphasizing the need for novel therapies. To combat multidrug resistance in breast cancer, new drug candidates targeting the Poly (ADP-ribose) polymerase (PARP) enzyme are being developed to improve chemotherapeutic efficacy and reduce toxicity. In this study, computational screening of 365 quinazoline derivatives was conducted to identify potential PARP inhibitors. Docking based screening identified three quinazoline scaffolds (RFAP77, RISA30, and RISAC) as top hits, demonstrating docking scores ranging from -8.41 to -9.31 kcal/mol and MM-GBSA binding free energy scores between -52.08 and -55.99 kcal/mol, compared to the reference approved inhibitor. ADMET analysis revealed favorable predicted drug-likeness profiles for the identified scaffolds. The structural stability of the docked PARP-ligand complexes was further investigated using molecular dynamics simulations (MDS). The computational simulations revealed significant conformational changes upon ligand binding, as evidenced by RMSD, RMSF, and hydrogen bond analyses. Essential dynamics analysis, including PCA-based FEL mapping, demonstrated energy minima profiles for all top docked PARP complexes. These computational findings highlight the potential of these scaffolds as promising candidates for further development as PARP inhibitors.

Valorization of organic fruit peel wastes for Aedes aegypti control: A green chemistry approach integrating in vitro and in silico studies

Vector-borne diseases affect millions of people worldwide, with a significant impact on children below five years. The infections transmitted by mosquitoes cause an estimate of 219 million cases globally, resulting in more than 400,000 deaths every year. As per WHO protocol, spraying of synthetic larvicides over the stagnant drainages and water systems is being one of the most common and effective techniques in the process of disease control. In parallel, the awareness on organic waste pollution had led to the increased practice of sustainable valorization to tackle daily needs. The present study focuses on mixed fruit peel liquid (MFPL) production through anaerobic fermentation of fruit peel wastes and evaluation of its larvicidal efficacy against Aedes aegypti. The in vitro assay revealed that higher concentrations of MFPL and exposure period increased larval mortality, with LC50 values ranging from 1.4% at 6 h to 0.3% at 24 h. Among the twenty bioactive compounds identified through GC-MS analysis of MFPL, n-hexadecanoic acid,2(1H) - quinolinone hydrazone and benzofuran, had significant glide scores of. -12.3 kcal/mol, -7.1 kcal/mol and -5.7 kcal/mol against the target protein 1PZ4 and -11.1 kcal/mol, -7.2 kcal/mol and -5.2 kcal/mol against 1YIY during molecular docking. The stability and interactions of three bioactive compounds were then assessed using DFT and molecular dynamics simulations, in which n-hexadecanoic acid was significantly stable with optimal hydrogen bond interactions. The novel findings of the study confirm MFPL's potential as an effective larvicide which could substitute commercial larvicides that are harmful to the ecosystem.

Discovery of sugar-based natural framework as phytopathogenic virus capsid protein inhibitors using a state-of-the-art multiple screening strategy

The prompt and efficient identification of targeted inhibitors against unscrupulous pathogenic viruses holds promise for preventing epidemic disease outbreaks. Herein, a comprehensive multichannel screening method (multiple docking cross-validation, molecular dynamics simulation, and density functional theory calculation) integrated with bioactivity identification is rationally established using sugar-based natural ligand libraries to target tobacco mosaic virus (TMV) capsid proteins. Encouragingly, compounds A0 (Kd = 0.14 μM) and A4 (Kd = 1.43 μM) were evaluated to have excellent binding capacities to TMV capsid protein, evidently exceeding that of viricide Ningnanmycin (Kd = 3.47 μM) by 24.8 and 2.4-folds. Moreover, A0 and A4 significantly down-regulated the expression of capsid proteins at the transcriptional level, effectively blocking the biosynthesis and assembly of TMV in tobacco. Additionally, bioactivity evaluation illustrated that the anti-TMV curative effects of A0 (EC50 = 310.9 μg/mL) and A4 (EC50 = 371.2 μg/mL) were comparable to Ningnanmycin (EC50 = 343.8 μg/mL). Considering the availability, cost and synthesis difficulty of precursors, the more affordable A4 is reckoned to be a promising candidate for capsid protein inhibitors and warrants further exploration in follow-up studies. Current findings highlight that this state-of-the-art virtual strategy, integrated with bioactivity validation, facilitates the discovery of targeted candidates to combat pathogenic viruses.

Exploring Marine natural products as potential Quorum sensing inhibitors by targeting the PqsR in Pseudomonas aeruginosa: Virtual screening assisted structural dynamics study

Antibiotic resistance is a critical global health issue, and Pseudomonas aeruginosa is a particularly challenging pathogen. This gram-negative bacterium is notorious for its high virulence and resistance to antimicrobial agents, making it a leading cause of nosocomial infections, significantly impacting public health. The adaptability and multidrug resistance of P. aeruginosa exacerbate treatment difficulties, resulting in increased morbidity and mortality rates worldwide. Consequently, targeting bacterial quorum sensing (QS) systems is a promising strategy for the development of novel antimicrobial compounds against this resilient pathogen. In this study, a structure-based virtual screening (SBVS) approach was employed to identify marine natural products (MNPs) as potential lead molecules targeting the biofilm-forming PqsR protein of P. aeruginosa. A total of ~37,000 MNPs were initially evaluated and ranked based on docking scores using high-throughput virtual screening (HTVS), Standard Precision (SP), and Extra Precision (XP) methods. Ten lead molecules (five from the CMNPD database and five from the MNPD database) were shortlisted based on their docking scores (<-10.0 kcal/mol) and binding free energy values (MM-GBSA ΔG <-40 kcal/mol). Their drug-likeness profiles were assessed using stringent criteria in the QikProp module of Schrödinger, and their chemical reactivity was evaluated through density functional theory (DFT) calculations. The structural and energetic interactions between the identified MNPs and the PqsR-binding pocket were validated through molecular dynamics simulations (MDS) and binding free energy (BFE) calculations. Structural dynamic analyses revealed that the MNP-bound PqsR complexes demonstrated stable interactions within the binding pocket, with hydrophobic residues such as L208, I236, and I263 playing a crucial role in maintaining stability. Among the identified MNPs, CMNPD14329, CMNPD23880, MNPD13399, and MNPD13725 emerged as promising lead molecules for further research. These candidates can serve as foundations for developing structural analogs with enhanced binding affinities for PqsR and other biofilm-forming proteins. Further experimental validation is essential to confirm the therapeutic potential of these identified MNPs.

Molecular dynamics simulations, essential dynamics and MMPBSA to evaluate natural compounds as potential inhibitors for AccD6, a key drug target in the fatty acid biosynthesis pathway in Mycobacterium tuberculosis

Antibiotic resistance in Mycobacterium tuberculosis, the primary causative agent of the tuberculosis disease is an ever growing threat especially in developing and underdeveloped countries. Isoniazid is a commonly used first line anti-tuberculosis drug used during the first phase of tuberculosis treatment. However, due to its improper use, many strains of Mycobacterium tuberculosis have acquired resistance to the drug. Advancements in next generation sequencing technologies, such as transcriptomics have paved way for identifying alternative drug targets based on the differential expression pattern of genes. Therefore, this study makes use of RNA-Seq data of Mycobacterium tuberculosis isolates treated with different concentrations of isoniazid to identify genes that can be proposed as drug targets. From the differential expression analysis, it was observed that four genes were significantly upregulated under all the conditions. Among the four genes, accD6 was selected as the drug target for virtual screening and molecular dynamics studies, because of its role in fatty acid elongation and contribution to the synthesis of mycolic acids. The protein-protein interaction network and gene ontology based functional enrichment studies show an enrichment in fatty acid biosynthesis related pathways. Furthermore, virtual screening studies successfully screened the top three natural inhibitor molecules with satisfactory ADME properties and a better glide score than the reference compound, NCI-172033. The trajectory analysis, essential dynamics studies and MMPBSA analysis, concluded that among the hit molecules, NPC41982, a thiazole derivative showed the most promising results and can be considered as a potential drug candidate.

Computational insights into marine natural products as potential antidiabetic agents targeting the SIK2 protein kinase domain

Diabetes mellitus (DM) affects over 77 million adults in India, with cases expected to reach 134 million by 2045. Current treatments, including sulfonylureas and thiazolidinediones, are inadequate, underscoring the need for novel therapeutic strategies. This study investigates marine natural products (MNPs) as alternative therapeutic agents targeting SIK2, a key enzyme involved in DM. The structural stability of the predicted SIK2 model was validated using computational methods and subsequently employed for structure-based virtual screening (SBVS) of over 38,000 MNPs. This approach identified five promising candidates: CMNPD21753 and CMNPD13370 from the Comprehensive Marine Natural Product Database, MNPD10685 from the Marine Natural Products Database, and SWMDRR053 and SWMDRR052 from the Seaweed Metabolite Database. The identified compounds demonstrated docking scores ranging from -7.64 to -11.95 kcal/mol and MMGBSA binding scores between -33.29 and -68.29 kcal/mol, with favourable predicted pharmacokinetic and toxicity profiles. Molecular dynamics simulations (MDS) revealed stronger predicted binding affinity for these compounds compared to ARN-3236, a known SIK2 inhibitor. Principal component (PC)-based free energy landscape (FEL) analysis further supported the stable binding of these compounds to SIK2. These computational findings highlight the potential of these leads as novel SIK2 inhibitors, warranting future in vitro and in vivo validation.

Unveiling therapeutic biomarkers and druggable targets in ALS: An integrative microarray analysis, molecular docking, and structural dynamic studies

Amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig's disease, is a debilitating neurodegenerative disorder characterized by the progressive degeneration of nerve cells in the brain and spinal cord. Despite extensive research, its precise etiology remains elusive, and early diagnosis is challenging due to the absence of specific tests. This study aimed to identify potential blood-based biomarkers for early ALS detection and monitoring using datasets from whole blood samples (GSE112680) and oligodendrocytes, astrocytes, and fibroblasts (GSE87385) obtained from the NCBI-GEO repository. Through bioinformatics analysis, including protein-protein interactions and molecular pathway analyses, we identified differentially expressed genes (DEGs) associated with ALS. Notably, ALS2, ADH7, ALDH8A1, ALDH3B1, ABHD2, ABHD17B, ABHD12, ABHD13, PGAM2, AURKB, ANAPC11, VAPA, UNC45B, and TNNT2 emerged as top-ranked DEGs, implicated in drug metabolism, protein depalmytilation, and the AKT/mTOR signaling pathways. Among these, AurKB established as a potential therapeutic biomarker with relevance to various neurological conditions. Consequently, AurKB was selected for identifying potential therapeutic molecules and utilized for in silico structural characterization studies. Exploration of the IMPATT database led to the discovery of a lead compound similar to Fostamatinib, currently used for AurKB. Initial molecular docking and MMGBSA-based binding energy analysis were followed by molecular dynamics simulation (MDS) and free energy landscape (FEL) analysis to validate the ligand's binding efficacy and understand dynamic processes within the biological system. The identified potential biomarkers and lead molecule provide novel insights into the correlation between blood cell transcripts and ALS pathology, paving the way for blood-based diagnostic tools for early ALS detection and ongoing disease monitoring.

Transcriptomic, mutational and structural bioinformatics approaches to explore the therapeutic role of FAP in predominant cancer types

Fibroblast activating protein (FAP) is a cell surface marker of cancer-associated fibroblasts with a distinct pro-tumorigenic role. The present study analyzed the pan-cancer expression; and clinical and mutational profiles of the FAP coding gene. Molecular dynamics simulation (MDS) deciphered the backbone dynamics and energetics of FAP. Virtual screening and subsequent pharmacokinetic-profiling (PK) filtered lead molecules, which were subjected to molecular docking. MDS projected a stable trajectory for the protein, as dynamics evidenced by low residue-level fluctuations, stable backbone dynamics, and energetics. Around five stabilization and deleterious mutations in the catalytic domain were identified. The low binding energy (BE) profiles from molecular docking studies screened the top five lead molecules for site-specific intermolecular interaction studies. Lead-16 (ZINC000245289699) exhibited a significant BE and inhibition constant of -6.87 kcal/mol and 12.27 μM, respectively, across FAP and its mutants. Interestingly, the docked complexes of Lead-16 interacted with the catalytic triad residues (S624, D702, and H734). The docked complexes of Lead-16 with FAP showed lower average root-mean-square fluctuations compared to the unbound protein, suggesting a stable ligand-protein complex. The tumor-specific expression and its critical overall survival suggest the inhibitors of FAP for potential cancer therapeutic intervention and hindering tumor microenvironment-driven cancer progression.

Harnessing marine natural products to inhibit PAD4 triple mutant: A structure-based virtual screening approach for rheumatoid arthritis therapy

Peptidylarginine deiminase type4 (PAD4) is a pivotal pro-inflammatory protein within the human immune system, intricately involved in both inflammatory processes and immune responses. Its role extends to the generation of diverse immune cell types, including T cells, B cells, natural killer cells, and dendritic cells. PAD4 has recently garnered attention due to its association with a spectrum of inflammatory and autoimmune disorders, notably rheumatoid arthritis (RA). Mutations in the PAD4 gene, leading to the conversion of arginine to citrulline, have emerged as significant factors in the pathogenesis of RA and related conditions. As a calcium-dependent enzyme, PAD4 is central to the citrullination process, a crucial post-translational modification implicated in disease pathophysiology. Its critical role in autoimmune disorders and inflammation makes PAD4 a prime candidate for therapeutic intervention in RA. Inhibiting PAD4 presents a promising avenue for mitigating inflammatory responses and curtailing joint degradation and impairment. To explore its therapeutic potential, a structure-based virtual screening (SBVS) approach was employed, harnessing an array of marine natural products (MNPs) sourced from databases such as CMNPD, MNPD, and Seaweed. Notably, MNPD10752, CMNPD12680, and CMNPD2751 emerged as potential hit molecules, exhibiting adherence to essential pharmacokinetic properties and favorable toxicity profiles. Quantum mechanics studies using density functional theory (DFT) calculations revealed the inhibitory potential of these identified natural products. Further structural elucidation through molecular dynamics simulations (MDS) and principal component-based free energy landscape (FEL) analysis shed light on the stability of MNP-bound PAD4 complexes. In conclusion, this computational study serves as a stepping stone for further experimental evaluation, aiming to explore the potential of MNPs in addressing PAD4-related human pathologies.

Structure based exploration of potential lead molecules against the extracellular cysteine protease (EcpA) of Staphylococcus epidermidis: a therapeutic halt

Nosocomial infection caused by Staphylococcus epidermidis is one of the most widely spread diseases affecting the world's population. No strategies have been developed to overcome this infection and inhibit its spread in immunocompromised patients or patients with indwelling medical devices. EcpA is an extracellular cysteine protease protein involved in biofilm formation on medical devices. Thus, blocking this mechanism may be viable for developing a drug against S. epidermidis. The current research aimed to find new, potent inhibitors that could stop the S. epidermidis EcpA protein from functioning. This study attempted to identify the most promising drug candidates using structure-based virtual screening (SBVS) from libraries of natural ligands. The top-scored molecules were shortlisted based on their IC50 values and pharmacophore properties and further validated through density functional theory (DFT) studies. We found five inhibitors using virtual screening, and the results indicate that these drugs had the highest energy binding potential towards the EcpA targets when compared to the reference molecule E-64, a known cysteine protease inhibitor. In order to evaluate the binding conformational stability of protein-ligand complexes, molecular dynamics (MD) simulations were performed in triplicate for 100 ns, revealing the significant stability of anticipated molecules at the docked site. Furthermore, principal component analysis and binding free energy calculations were performed to understand the dynamics and stability of the complexes. The current study indicated that these compounds looked to be suitable novel inhibitors of the EcpA protein and pave the path for further discovery of novel inhibitors of EcpA.Communicated by Ramaswamy H. Sarma.

Elucidation of escitalopram oxalate and related antidepressants as putative inhibitors of PTP4A3/PRL-3 protein in hepatocellular carcinoma: A multi-computational investigation

Hepatocellular carcinoma (HCC) persists to be one of the most devastating and deadliest malignancies globally. Recent research into the molecular signaling networks entailed in many malignancies has given some prominent insights that can be leveraged to create molecular therapeutics for combating HCC. Therefore, in the current communication, an in-silico drug repurposing approach has been employed to target the function of PTP4A3/PRL-3 protein in HCC using antidepressants: Fluoxetine hydrochloride, Citalopram, Amitriptyline, Imipramine, and Escitalopram oxalate as the desired ligands. The density function theory (DFT) and chemical absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters for the chosen ligands were evaluated to comprehend the pharmacokinetics, drug-likeness properties, and bioreactivity of the ligands. The precise interaction mechanism was explored using computational methods such as molecular docking and molecular dynamics (MD) simulation studies to assess the inhibitory effect and the stability of the interactions against the protein of interest. Escitalopram oxalate exhibited a comparatively significant docking score (-7.4 kcal/mol) compared to the control JMS-053 (-6.8 kcal/mol) against the PRL-3 protein. The 2D interaction plots exhibited an array of hydrophobic and hydrogen bond interactions. The findings of the ADMET forecast confirmed that it adheres to Lipinski's rule of five with no violations, and DFT analysis revealed a HOMO-LUMO energy gap of -0.26778 ev, demonstrating better reactivity than the control molecule. The docked complexes were subjected to MD studies (100 ns) showing stable interactions. Considering all the findings, it can be concluded that Escitalopram oxalate and related therapeutics can act as potential pharmacological candidates for targeting the activity of PTP4A3/PRL-3 in HCC.

Antiviral Potential of Fucoxanthin, an Edible Carotenoid Purified from Sargassum siliquastrum, against Zika Virus

Considering the lack of antiviral drugs worldwide, we investigated the antiviral potential of fucoxanthin, an edible carotenoid purified from Sargassum siliquastrum, against zika virus (ZIKV) infection. The antiviral activity of fucoxanthin was assessed in ZIKV-infected Vero E6 cells, and the relevant structural characteristics were confirmed using molecular docking and molecular dynamics (MD) simulation. Fucoxanthin decreased the infectious viral particles and nonstructural protein (NS)1 mRNA expression levels at concentrations of 12.5, 25, and 50 µM in ZIKV-infected cells. Fucoxanthin also decreased the increased mRNA levels of interferon-induced proteins with tetratricopeptide repeat 1 and 2 in ZIKV-infected cells. Molecular docking simulations revealed that fucoxanthin binds to three main ZIKV proteins, including the envelope protein, NS3, and RNA-dependent RNA polymerase (RdRp), with binding energies of -151.449, -303.478, and -290.919 kcal/mol, respectively. The complex of fucoxanthin with RdRp was more stable than RdRp protein alone based on MD simulation. Further, fucoxanthin bonded to the three proteins via repeated formation and disappearance of hydrogen bonds. Overall, fucoxanthin exerts antiviral potential against ZIKV by affecting its three main proteins in a concentration-dependent manner. Thus, fucoxanthin isolated from S. siliquastrum is a potential candidate for treating zika virus infections.

Unlocking InhA: Novel approaches to inhibit Mycobacterium tuberculosis

Multidrug-resistant tuberculosis continues to pose a health security risk and remains a public health emergency. Antimicrobial resistance result from treatment regimens that are both insufficient and incomplete leading to the emergence of multidrug-resistant tuberculosis, extensively drug-resistant tuberculosis and totally drug-resistant tuberculosis. The impact of tuberculosis on the people suffering from HIV (Human immunodeficiency virus infection) have resulted in the increased research efforts in designing and discovery of novel antitubercular drugs that may result in decreasing treatment duration, minimising the need for multiple drug intake, minimising cytotoxicity and enhancing the mechanism of action of drug. While many drugs are available to treat tuberculosis, a precise and timely cure is still absent. Consequently, further investigation is needed to identify more recent molecular equivalents that have the potential to swiftly remove this disease. Isoniazid (INH), a treatment for tuberculosis (TB), targets the enzyme InhA (mycobacterium enoyl acyl carrier protein reductase), the Mycobacterium tuberculosis enoyl-acyl carrier protein (ACP) reductase, most common INH resistance is circumvented by InhA inhibitors that do not require KatG (catalase-peroxidase) activation, as a result, researchers are trying to work in the area of development of InhA inhibitors which could help in eradicating the era of tuberculosis from the world.

Computational insights into potential marine natural products as selective inhibitors of Mycobacterium tuberculosis InhA: A structure-based virtual screening study

Several factors are associated with the emergence of drug resistance mechanisms, such as impermeable cell walls, gene mutations, and drug efflux systems. Consequently, bacteria acquire resistance, leading to a decrease in drug efficacy. A new and innovative strategy is required to combat drug resistance in tuberculosis (TB) effectively. Therefore, targeting the mycolic acid biosynthesis pathway, which is involved in synthesising mycolic acids (MAs), essential structural components responsible for mycobacterial pathogenicity, has garnered interest in TB research and the concept of drug resistance. In this context, InhA, which plays a crucial role in the fatty acid synthase-II (FAS-II) system of the MA biosynthetic pathway, was selected as a druggable target for screening investigation. To identify potential lead molecules against InhA, diverse marine natural products (MNPs) were collected from the comprehensive marine natural products database (CMNPD). Virtual screening studies aided in selecting potential lead molecules that best fit within the substrate-binding pocket (SBP) of InhA, forming crucial hydrogen bond interaction with the catalytic residue Tyr158. Three MNPs, CMNPD30814, CMNPD1702, and CMNPD27355, were chosen as prospective alternative molecules due to their favorable pharmacokinetic properties and lack of toxicity according to ProTox-II predictions. Additionally, improved reactivity of the MNPs was observed in the results of density functional theory (DFT) studies. Furthermore, comparative molecular dynamics simulation (MDS), principal component (PC)-based free energy landscape (FEL) analysis, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) were employed to show enhanced structural stability, increased H-bond potential, and high binding affinity toward the target InhA. Moreover, the hot spot residues that contributed to the high binding energy profile and anchored the stability of the complexes were revealed with their individual interaction energy. The computational insights from this study provide potential avenues to combat TB through the multifaceted mode of action of these marine lead molecules, which can be further explored in future experimental investigations.

Impact of PmrB mutations on clinical Klebsiella pneumoniae with variable colistin-susceptibilities: Structural insights and potent therapeutic solutions

Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections continue to impose high morbidity threats to hospitalized patients worldwide, limiting therapeutic options to last-resort antibiotics like colistin. However, the dynamic genomic landscape of colistin-resistant K. pneumoniae (COLR-Kp) invoked ardent exploration of underlying molecular signatures for therapeutic propositions/designs. We unveiled the structural impact of the widespread and emerging PmrB mutations involved in colistin resistance (COLR) in K. pneumoniae. In the present study, clinical isolates of K. pneumoniae expressed variable susceptibilities to colistin (>0.5 μg/mL for resistant and ≤0.25 μg/mL for susceptible) despite mutations such as T157P, G207D and T246A. The protein sequences extracted from in-house sequenced genomes were used to model mutant PmrB proteins and analyze the underlying structural alterations. The mutations were contrasted based on molecular dynamics simulation trajectories, free-energy landscapes and structural flexibility profiles. The altered backbone flexibilities can be an essential factor for mutant selection by COLR K. pneumoniae and can provide clues to deal with emerging mutants. Furthermore, PmrB having high druggability confidence (>0.99), was explored as a potential target for 1396 virtually screened FDA-approved drug candidates. Among the top-10 compounds (scores >70), amphotericin B was found to be potential candidate with high affinity (Binding energy <-8 kcal/mol) and stable interactions (RMSF <0.7 Å) against PmrB druggable pockets, despite the mutations, which encourages future adjunct therapeutic research against COLR-Kp.

Structure-Based In Silico Screening of Marine Phlorotannins for Potential Walrus Calicivirus Inhibitor

A new calicivirus isolated from a walrus was reported in 2004. Since unknown marine mammalian zoonotic viruses could pose great risks to human health, this study aimed to develop therapeutic countermeasures to quell any potential outbreak of a pandemic caused by this virus. We first generated a 3D model of the walrus calicivirus capsid protein and identified compounds from marine natural products, especially phlorotannins, as potential walrus calicivirus inhibitors. A 3D model of the target protein was generated using homology modeling based on two publicly available template sequences. The sequence of the capsid protein exhibited 31.3% identity and 42.7% similarity with the reference templates. The accuracy and reliability of the predicted residues were validated via Ramachandran plotting. Molecular docking simulations were performed between the capsid protein 3D model and 17 phlorotannins. Among them, five phlorotannins demonstrated markedly stable docking profiles; in particular, 2,7-phloroglucinol-6,6-bieckol showed favorable structural integrity and stability during molecular dynamics simulations. The results indicate that the phlorotannins are promising walrus calicivirus inhibitors. Overall, the study findings showcase the rapid turnaround of in silico-based drug discovery approaches, providing useful insights for developing potential therapies against novel pathogenic viruses, especially when the 3D structures of the viruses remain experimentally unknown.

Theoretical investigation on known renin inhibitors and generation of ligand-based pharmacophore models for hypertension treatment

The renin enzyme is considered a promising target for hypertension and renal diseases. Over the last three decades, several experimental and theoretical studies have been engaged in the discovery of potent renin inhibitors. The identified inhibitors that undergo clinical trials are still failing to meet the criteria of potency and safety. To date, there is no specific FDA-approved drug for renin inhibition. Our theoretical opinion describes that the most potent compounds identified in experimental studies but lacking safety and overdose issues could be solved by finding similar molecules that are stable, very active, and have no side effects, which will kick start the drug discovery process. Here, we utilized the most potent direct renin inhibitors reported earlier, followed further by our theoretical study reported in 2019. Ligand-based virtual screening, density functional theory, and dynamic simulation studies were employed to explore the identified compounds and co-crystallized molecule in the protein structure. From the diverse databases, we have identified several identical molecules based on their structural features, such as functional groups like hydrophobic (H), aromatic rings (R), hydrogen bond acceptor (A), and donor (D). The HHHPR five-point pharmacophore feature was identified as a template pharmacophore to search the potential compounds from the Enamine and LifeChemical databases and have a good fitness score with known renin inhibitors. Furthermore, theoretical validation was done through several studies that confirmed the activity of the identified molecules. Overall, we propose that these compounds might break the failure in adverse events and improve the potency of hypertension treatment.Communicated by Ramaswamy H. Sarma.

Unleashing Nature's potential: a computational approach to discovering novel VEGFR-2 inhibitors from African natural compound using virtual screening, ADMET analysis, molecular dynamics, and MMPBSA calculations

One of the characteristic features of cancer is angiogenesis, the process by which new, aberrant blood vessels are formed from pre-existing blood vessels. The process of angiogenesis begins when VEGF binds to its receptor, the VEGF receptor (VEGFR). The formation of new blood vessels provides nutrients that can promote the growth of cancer cells. When it comes to new blood vessel formation, VEGFR2 is a critical player. Therefore, inhibiting VEGFR2 is an effective way to target angiogenesis in cancer treatment. The aim of our research was to find new VEGFR-2 inhibitors by performing a virtual screening of 13313 from African natural compounds using different in silico techniques. Using molecular docking calculations and ADMET properties, we identified four compounds that exhibited a binding affinity ranging from -11.0 kcal/mol to -11.5 Kcal/mol when bound to VEGFR-2. These four compounds were further analyzed with 100 ns simulations to determine their stability and binding energy using the MM-PBSA method. After comparing the compounds with Regorafenib, a drug approved for anti-angiogenesis treatment, it was found that all the candidates (EANPDB 252, NANPDB 4577, and NANPDB 4580), with the exception of EANPDB 76, could target VEGFR-2 similarly effectively to Regorafenib. Therefore, we recommend three of these agents for anti-angiogenesis treatment because they are likely to deactivate VEGFR-2 and thus inhibit angiogenesis. However, it should be noted that the safety and suitability of these agents for clinical use needs further investigation, as the computer-assisted study did not include in vitro or in vivo experiments.

Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB

Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.

Translational protein RpsE as an alternative target for novel nucleoside analogues to treat MDR Enterobacter cloacae ATCC 13047: network analysis and molecular dynamics study

The pathogenic Enterobacter cloacae subsp. cloacae str. ATCC 13047 has contemporarily emerged as a multi-drug resistant strain. To formulate an effective treatment option, alternative therapeutic methods need to be explored. The present study focused on Gene Interaction Network study of 46 antimicrobial resistance genes to reveal the densely interconnecting and functional hub genes in E. cloacae ATCC 13047. The AMR genes were subjected to clustering, topological and functional enrichment analysis, revealing rpsE (RpsE), acrA (AcrA) and arnT (ArnT) as novel therapeutic drug targets for hindering drug resistance in the pathogenic strain. Network topology further indicated translational protein RpsE to be exploited as a promising drug-target candidate for which the structure was predicted, optimized and validated through molecular dynamics simulations (MDS). Absorption, distribution, metabolism and excretion screening recognized ZINC5441082 (N-Isopentyladenosine) (Lead_1) and ZINC1319816 (cyclopentyl-aminopurinyl-hydroxymethyl-oxolanediol) (Lead_2) as orally bioavailable compounds against RpsE. Molecular docking and MDS confirmed the binding efficacy and protein-ligand complex stability. Furthermore, binding free energy (G_bind) calculations, principal component and free energy landscape analyses affirmed the predicted nucleoside analogues against RpsE protein to be comprehensively examined as a potential treatment strategy against E. cloacae ATCC 13047.

Application of Molecular Simulation Methods in Food Science: Status and Prospects

Molecular simulation methods, such as molecular docking, molecular dynamic (MD) simulation, and quantum chemical (QC) calculation, have become popular as characterization and/or virtual screening tools because they can visually display interaction details that in vitro experiments can not capture and quickly screen bioactive compounds from large databases with millions of molecules. Currently, interdisciplinary research has expanded molecular simulation technology from computer aided drug design (CADD) to food science. More food scientists are supporting their hypotheses/results with this technology. To understand better the use of molecular simulation methods, it is necessary to systematically summarize the latest applications and usage trends of molecular simulation methods in the research field of food science. However, this type of review article is rare. To bridge this gap, we have comprehensively summarized the principle, combination usage, and application of molecular simulation methods in food science. We also analyzed the limitations and future trends and offered valuable strategies with the latest technologies to help food scientists use molecular simulation methods.

Identification of Novel Inhibitor of Enoyl-Acyl Carrier Protein Reductase (InhA) Enzyme in Mycobacterium tuberculosis from Plant-Derived Metabolites: An In Silico Study

Mycobacterium tuberculosis (M.tb.) enoyl-acyl carrier protein (ACP) reductase (InhA) is validated as a useful target for tuberculosis therapy and is considered an attractive enzyme to drug discovery. This study aimed to identify the novel inhibitor of the InhA enzyme, a potential target of M.tb. involved in the type II fatty acid biosynthesis pathway that controls mycobacterial cell envelope synthesis. We compiled 80 active compounds from Ruta graveolens and citrus plants belonging to the Rutaceae family for pharmacokinetics and molecular docking analyses. The chemical structures of the 80 phytochemicals and the 3D structure of the target protein were retrieved from the PubChem database and RCSB Protein Data Bank, respectively. The evaluation of druglikeness was performed based on Lipinski’s Rule of Five, while the computed phytochemical properties and molecular descriptors were used to predict the ADMET of the compounds. Amongst these, 11 pharmacokinetically-screened compounds were further examined by performing molecular docking analysis with an InhA target using AutoDock 4.2. The docking results showed that gravacridonediol, a major glycosylated natural alkaloid from Ruta graveolens, might possess a promising inhibitory potential against InhA, with a binding energy (B.E.) of −10.80 kcal/mole and inhibition constant (Ki) of 600.24 nM. These contrast those of the known inhibitor triclosan, which has a B.E. of −6.69 kcal/mole and Ki of 12.43 µM. The binding efficiency of gravacridonediol was higher than that of the well-known inhibitor triclosan against the InhA target. The present study shows that the identified natural compound gravacridonediol possesses drug-like properties and also holds promise in inhibiting InhA, a key target enzyme of M.tb.

Mechanistic insights on nsSNPs on binding site of renin and cytochrome P450 proteins: A computational perceptual study for pharmacogenomics evaluation

Past several decades, therapeutic investigations lead to the discovery of numerous antihypertensive drugs. Although it has been proved for their potency, altered efficacy is common norms in several conditions due to genetic variations. Cytochrome P450 plays a crucial role in drug metabolism and responsible for the pharmacokinetic and pharmacodynamic properties of the drug molecules. Here, we report the deleterious point mutations in the genes associated with the altered response of antihypertensive drug molecules and their metabolizers. Missense variants were filtered as potential nonsynonymous single nucleotide polymorphisms among the available data for the target genes (REN, CYP2D6, CYP3A4). The key objective of the work is to identify the deleterious single nucleotide polymorphisms (SNPs) responsible for the drug response and metabolism for the application of personalized medication. The molecular docking studies revealed that Aliskiren and other clinically approved drug molecules have a high binding affinity with both wild and mutant structures of renin, CYP2D6, and CYP3A4 proteins. The docking (Glide XP) score was observed to have in the range of -8.896 to -11.693 kcal/mol. The molecular dynamics simulation studies were employed to perceive the structural changes and conformational deviation through various analyses. Each studied SNPs was observed to have disparate scoring in the binding affinity to the specific drug molecules. As a prospective plan, we assume this study might be applied to identify the risky SNPs associated with hypertension from the patients to recommend the suitable drug for personalized hypertensive treatment. Further, extensive clinical pharmacogenomics studies are required to support the findings.