Quantitative structure-activity relationship and ADME prediction studies on series of spirooxindoles derivatives for anti-cancer activity against colon cancer cell line HCT-116.

Forty-one derivatives of spirooxindoles, active against HCT-116 colon cancer cells, underwent pharmacophore-based 3D-QSAR analysis to understand their correlation with anti-cancer activity. The study identified a seven-point pharmacophore model (ADHHRRR1) and QSAR models, offering insights for lead optimization and novel analogue design, thus advancing anti-cancer drug discovery. This research underscores the value of molecular modeling in elucidating structure-activity relationships and enhancing drug development efforts.

Experimental and computational evaluation of anti-malarial and antioxidant potential of transition metal (II) complexes with tridentate schiff base derived from pyrrolopyrimidine.

In the twenty-first century, we are experiencing persistent waves of diverse pathogen variations, contributing significantly to global illness and death rates. Within this varied spectrum of illnesses, malaria and oxidative damage emerge as prominent obstacles that have persistently affected human health. The motivation for exploring the antioxidant potential of transition metal (II) complexes with tridentate Schiff base ligands is driven by the need for effective treatments against malaria and oxidative stress-related conditions. Both malaria and oxidative damage are significant global health concerns. Transition metal complexes can potentially offer enhanced anti-malarial and antioxidant activities, providing a dual benefit. To explore the aforementioned facts and examine the therapeutic potential, the previously synthesized pyrrolopyrimidinehydrazide-3-chlorobenzaldehyde, such as HPPHmCB ligand(1)andtheirMn(II),Fe(II),Co(II),Ni(II), Pd(II),Cu(II),Zn(II),Cd(II),Hg(II)complexes(2-10) of benzaldehydes and pyrrolopyrimidinehydrazide were proposed for in vitro anti-malarial and antioxidant investigation. These compounds were assessed for their anti-malarial efficacy against Plasmodium falciparum using a micro assay protocol, with IC50 values indicating the concentration required to inhibit parasite maturation by 50%. The Hg(II) complex displays pronounced antimalarial activity with an IC50 value of 1.98 ± 0.08 µM, closely aligning with the efficacy of quinine, whereas Zn(II), Cu(II), Pd(II) complexes demonstrates most significant anti-malarial activity, with IC50 values close to the reference compound quinine. The antioxidant activity of the compounds was evaluated using the DPPH assay, with several metal complexes such as Cu(II)and Zn(II) showing strong potential in neutralizing oxidative stress. Furthermore, molecular docking simulations were conducted to explore the binding interactions of the compounds with PfNDH2, providing insights into their pharmacological potential. The study also examined the electronic properties, solubility, and potential hepatotoxicity of the compounds. The findings suggest that the metal complexes could be promising candidates for further development as anti-malarial agents, offering enhanced potency compared to the base compound.

Identification of novel PHGDH inhibitors based on computational investigation: an all-in-one combination strategy to develop potential anti-cancer candidates.

Objective: Biological studies have elucidated that phosphoglycerate dehydrogenase (PHGDH) is the rate-limiting enzyme in the serine synthesis pathway in humans that is abnormally expressed in numerous cancers. Inhibition of the PHGDH activity is thought to be an attractive approach for novel anti-cancer therapy. The development of structurally diverse novel PHGDH inhibitors with high efficiency and low toxicity is a promising drug discovery strategy. Methods: A ligand-based 3D-QSAR pharmacophore model was developed using the HypoGen algorithm methodology of Discovery Studio. The selected pharmacophore model was further validated by test set validation, cost analysis, and Fischer randomization validation and was then used as a 3D query to screen compound libraries with various chemical scaffolds. The estimated activity, drug-likeness, molecular docking, growing scaffold, and molecular dynamics simulation processes were applied in combination to reduce the number of virtual hits. Results: The potential candidates against PHGDH were screened based on estimated activity, docking scores, predictive absorption, distribution, metabolism, excretion, and toxicity (ADME/T) properties, and molecular dynamics simulation. Conclusion: Finally, an all-in-one combination was employed successfully to design and develop three potential anti-cancer candidates.

Syk protein inhibitors treatment for the allergic symptoms associated with hyper immunoglobulin E syndromes: A focused on a computational approach.

Background: Mutations in the Spleen tyrosine kinase (Syk) protein have significant implications for its function and response to treatments. Understanding these mutations and identifying new inhibitors can lead to more effective therapies for conditions like autosomal dominant hyper-IgE syndrome (AD-HIES) and related immunological disorders. Objective: To investigate the impact of mutations in the Syk protein on its function and response to reference treatments, and to explore new inhibitors tailored to the mutational profile of Syk. Methods: We collected and analyzed mutations affecting the Syk protein to assess their functional impact. We screened 94 deleterious mutations in the kinase domain using molecular docking techniques. A library of 997 compounds with potential inhibitory activity against Syk was filtered based on Lipinski and Veber rules and toxicity assessments. We evaluated the binding affinity of reference inhibitors and 14 eligible compounds against wild-type and mutant Syk proteins. Molecular dynamics simulations were conducted to evaluate the interaction of Syk protein complexes with the reference inhibitor and potential candidate inhibitors. Results: Among the analyzed mutations, 60.5% were identified as deleterious, underscoring their potential impact on cellular processes. Virtual screening identified three potential inhibitors (IDs: 118558008, 118558000, and 118558092) with greater therapeutic potential than reference treatments, meeting all criteria and exhibiting lower IC50 values. Ligand 1 (ID: 118558000) demonstrated the most stable binding, favorable compactness, and extensive interaction with solvents. A 3D pharmacophore model was constructed, identifying structural features common to these inhibitors. Conclusion: This study found that 60.5% of reported mutations affecting the Syk protein are deleterious. Virtual screening revealed three top potential inhibitors, with ligand 1 (ID: 118558000) showing the most stable binding and favorable interactions. These inhibitors hold promise for more effective therapies targeting Syk-mediated signaling pathways. The pharmacophore model provides valuable insights for developing targeted therapies for AD-HIES and related disorders, offering hope for patients suffering from Hyper IgE syndrome with allergic symptoms.

In silico fragment-based design and pharmacophore modelling of therapeutics against dengue virus envelope protein.

Dengue virus, an arbovirus of genus Flavivirus, is an infectious disease causing organisms in the tropical environment leading to numerous deaths every year. No therapeutic is available against the virus till date with only symptomatic relief available. Here, we have tried to design therapeutic compounds from scratch by fragment based method followed by pharmacophore based modelling to find suitable similar structure molecules and validated the same by MD simulation, followed by binding energy calculations and ADMET analysis. The receptor binding region of the dengue envelope protein was considered as the target for prevention of viral host cell entry and thus infection. This resulted in the final selection of kanamycin as a stable binding molecule against the Dengue virus envelope protein receptor binding domain. This study results in selection of a single molecule having high binding energy and prominent stable interactions as determined by post simulation analyses. This study aims to provide a direction for development of small molecule therapeutics against the dengue virus in order to control infection. This study may open a new avenue in the arena of structure based and fragment based therapeutic design to obtain novel molecules with therapeutic potential. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00262-9.

Crotalaria quinquefolia L. Revealed as a Potential Source of Neuropharmacophore in Both Experimental and Computational Studies.

Herbal remedies have shown great promise for improving human health. The plant Crotalaria quinquefolia is used in folk medicine to cure different diseases, including scabies, fever, discomfort, and lung infections. The present research was designed to explore bioactive compounds and evaluate the neuropharmacological effects of C. quinquefolia through in vivo and in silico approaches. Different secondary metabolites as well as the antioxidant activity were measured. Furthermore, chemical compounds were identified by HPLC and GCMS analysis. The neuropharmacological activity was examined by hole cross, hole board, open field, Y-maze, elevated plus maze, and thiopental sodium induced sleeping time tests in mice at doses of 100 mg/kg and 200 mg/kg body weight. Besides, an in-silico study was performed on proteins related to Alzheimer disease. The extract showed a significant content of secondary metabolites and antioxidant potential. The in-silico analysis showed that myricetin, quercetin, rutin, and kaempferol have good binding affinity with studied proteins, and QSAR studies revealed potential benefits for treating dementia, age-related macular degeneration, and more. The findings of the present neurological activity collectively imply that the extract has strong CNS depressant and anxiolytic activity. Therefore, C. quinquefolia can be a potential source of secondary metabolites to treat Alzheimer disease.

Design, synthesis, evaluation, pharmacophore modeling, and 3D-QSAR of lappaconitine analogs as potential analgesic agents.

Alleviating pain is crucial for patients with various diseases. This study aimed to enhance the analgesic properties of lappaconitine, a natural drug, through structural modifications. Specifically, carbamate analgesic active fragments were innovatively introduced at multiple sites on the benzene ring of lappaconitine. A total of 53 lappaconitine analogs were synthesized and evaluated. Compounds 5a, 5c, 5e, 6, and 15j addressed the narrow therapeutic window of lappaconitine, enhancing drug safety. Notably, carbamate analogs exhibited significantly enhanced analgesic activity, with compounds 5a and 5c having ED50 values of 1.2 and 1.6 mg/kg, respectively, indicating higher potency than lappaconitine (3.5 mg/kg). A metabolic analysis of compound 5e was conducted in mice, revealing its primary metabolic processes and metabolites, and providing preliminary exploration for the druggability. Given the multiple analgesic targets of lappaconitine, its analgesic mechanism remains inconclusive. This study, for the first time, analyzed the pharmacological activity characteristics of the lappaconitine analogs using a pharmacophore model and established a three-dimensional quantitative structure-activity relationship (3D-QSAR) to elucidate the quantitative relationship between the structures of the synthesized compounds and their analgesic activities. These findings provide valuable guidance for future structural modification and optimization of analgesic drugs.

Exploration of newly synthesized transition metal(II) complexes for infectious diseases.

Aim: In the annals of human history, infectious diseases significantly influencing the collective well-being of people worldwide. Consequently, to identify effective agents for infectious ailments, the octahedral Co(II), Ni(II), Cu(II), Zn(II) complexes of 4-(3-methoxyphenyl)pyrimidin-2-amine and 2-methoxy-1-napthaldehyde based ligand were synthesized and well characterized in the current investigation.Results & methodology: The synthesized compounds were evaluated for anti-TB, anti-inflammatory, antibacterial, antifungal activities by microplate Alamar blue, bovine serum albumin, serial dilution assays. The [Zn(L1)2(H2O)2] complex (5) demonstrates robust potency with 0.0040 ± 0.0007 and 0.0038 µmol/ml MIC value in anti-tuberculosis and antimicrobial activities, correspondingly while 06.57 ± 0.03 µM IC50 value in anti-inflammatory investigation.Conclusion: Complex (5) show promising potential as targets for pathogen deformities, supported by rigorous biological and computational investigations including pharmacophore modelling, molecular docking (binding score -121.018 and -59.8662 kcal/mol for 6H53 and 1CX2 proteins, respectively), DFT (Density functional theory), MESP (Molecular Electrostatic Potential) and ADMET (absorption, distribution, metabolism, excretion and toxicity).

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Discovery of selective ACAT2 antagonist via a combination strategy based on deep docking, pharmacophore modelling, and molecular dynamics simulation.

Acyl-CoA: cholesterol acyltransferase (ACAT), a pivotal enzyme in the absorption and metabolism of cholesterol, is primarily responsible for intracellular esterification. ACAT inhibition is expected to diminish plasma lipid levels by impeding intestinal cholesterol absorption, thereby preventing the progression of atherosclerotic lesions. A previous study shows that selective inhibition of ACAT2 significantly mitigated hypercholesterolaemia and atherosclerosis in mouse models. Therefore, the need for ACAT2 selective inhibitors becomes particularly urgent. In this study, we established a multilayer virtual screening workflow and subjected biologically evaluated representative compounds to enzyme inhibitory assays. The experimental results indicated that the two compounds, STL565001 (inhibition rate at 25 µM: 75.7 ± 27.8%, selectivity = 6) and STL528213 (inhibition rate at 25 µM: 87.8 ± 12.4%, selectivity = 13), demonstrated robust activity against ACAT2, displaying greater selectivity for ACAT2 than for ACAT1. The molecular mechanisms governing the inhibitory activities of the selected compounds were systematically elucidated using computational approaches. In addition, hotspot residues in ACAT2 that are crucial for ligand binding were successfully identified. In summary, we devised a multilayer screening scheme to expeditiously and efficiently identify compounds with enzyme inhibitory activity, offering novel scaffolds for subsequent drug design centred on ACAT2 targets.

In Silico Exploration of Novel EGFR Kinase Mutant-Selective Inhibitors Using a Hybrid Computational Approach.

Targeting epidermal growth factor receptor (EGFR) mutants is a promising strategy for treating non-small cell lung cancer (NSCLC). This study focused on the computational identification and characterization of potential EGFR mutant-selective inhibitors using pharmacophore design and validation by deep learning, virtual screening, ADMET (Absorption, distribution, metabolism, excretion and toxicity), and molecular docking-dynamics simulations. A pharmacophore model was generated using Pharmit based on the potent inhibitor JBJ-125, which targets the mutant EGFR (PDB 5D41) and is used for the virtual screening of the Zinc database. In total, 16 hits were retrieved from 13,127,550 molecules and 122,276,899 conformers. The pharmacophore model was validated via DeepCoy, generating 100 inactive decoy structures for each active molecule and ADMET tests were conducted using SWISS ADME and PROTOX 3.0. Filtered compounds underwent molecular docking studies using Glide, revealing promising interactions with the EGFR allosteric site along with better docking scores. Molecular dynamics (MD) simulations confirmed the stability of the docked conformations. These results bring out five novel compounds that can be evaluated as single agents or in combination with existing therapies, holding promise for treating the EGFR-mutant NSCLC.

Tanomastat exerts multi-targeted inhibitory effects on viral capsid dissociation and RNA replication in human enteroviruses.

BACKGROUND: Global cyclical outbreaks of human enterovirus infections has positioned human enterovirus A71 (EV-A71) as a neurotropic virus of clinical importance. However, there remains a scarcity of internationally approved antivirals and vaccines. METHODS: In pursuit of repurposing drugs for combating human enteroviruses, we employed a comprehensive pharmacophore- and molecular docking-based virtual screen targeting EV-A71 capsid protein VP1-4, 3C protease, and 3D polymerase proteins. Among 15 shortlisted ligand candidates, we dissected the inhibitory mechanism of Tanomastat in cell-based studies and evaluated its in vivo efficacy in an EV-A71-infected murine model. FINDINGS: We demonstrated that Tanomastat exerts dose-dependent inhibition on EV-A71 replication, with comparable efficacy profiles in enterovirus species A, B, C, and D in vitro. Time-course studies suggested that Tanomastat predominantly disrupts early process(es) of the EV-A71 replication cycle. Mechanistically, live virus particle tracking and docking predictions revealed that Tanomastat specifically impedes viral capsid dissociation, potentially via VP1 hydrophobic pocket binding. Bypassing its inhibition on entry stages, we utilized EV-A71 replication-competent, 3Dpol replication-defective, and bicistronic IRES reporter replicons to show that Tanomastat also inhibits viral RNA replication, but not viral IRES translation. We further showed that orally administered Tanomastat achieved 85% protective therapeutic effect and alleviated clinical symptoms in EV-A71-infected neonatal mice. INTERPRETATION: Our study establishes Tanomastat as a broad-spectrum anti-enterovirus candidate with promising pre-clinical efficacy, warranting further testing for potential therapeutic application. FUNDING: MOE Tier 2 grants (MOE-T2EP30221-0005, R571-000-068-592, R571-000-076-515, R571-000-074-733) and A∗STARBiomedical Research Council (BMRC).

Discovery of novel dihydro-pyrimidine hybrids: insight into the design, synthesis, biological evaluation and absorption, distribution, metabolism and excretion studies.

Aim: By keeping in aspects, the pharmacological potential of heterocyclic compounds, pyrimidine-based compounds were designed, synthesized and evaluated for α-amylase inhibitory potential.Materials & methods: Five new series 1a-l, 2a-d, 3a-d, 4a-d and 5a-d of 1,2,3,4-tetrahydroprimidine-5-carboxylate derivatives were designed by de novo method by taking Alogliptin as reference compound. Here in we describe synthesis and characterization of compounds as potential α-amylase inhibitor.Results: Structure activity relationship (SAR), in vitro analysis and molecular modelling approaches generate compounds 1 h, 1i, 1k and 4c as potential lead with good α-amylase inhibitory selection. However, compound 1k failed the criteria of optimization as drug lead by ADME studies while all other compounds showed optimum range for all in silico ADME parameters.Conclusion: Therefore, these compounds can serve as potential lead candidate in developing anti-diabetic therapy.

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Identification of novel RANKL inhibitors through in silico analysis.

Receptor activator of nuclear factor-κB ligand (RANKL) is considered the principal regulator of osteoclast differentiation. Therefore, strategies interfering with the RANKL-RANK signaling pathway may effectively inhibit osteoclast differentiation and mitigate bone resorption. Consequently, RANKL has become a promising target for new drug design strategies. Despite extensive research on specific drugs and antibodies, only a few have shown efficacy in treating osteoporosis. To address this challenge, we aimed to explore new approaches for designing drugs for osteoporosis. In this study, a 3D quantitative structure-activity relationship (QSAR) pharmacophore model was built for RANKL with reference to known inhibitor IC50 values. The optimal pharmacophore model was then employed as a 3D query to screen databases for novel lead compounds. The obtained compounds were subjected to ADMET and TOPKAT analyses to predict drug pharmacokinetics and toxicity. Molecular docking and de novo evolution approaches were applied to verify the docking binding affinities of the compounds. Five candidate compounds were subjected to further in vitro analyses to assess their anti-osteoporotic effects, among which compound 4 demonstrated significant inhibitory activity, achieving an inhibitory rate of 92.6 % on osteoclastogenesis at a concentration of 10 µM. Subsequent molecular dynamics (MD) simulations to assess the stability and behavior of compound 4 and its evolved variant, ZINC00059014397_Evo, within the RANKL binding site revealed that the variant is a potential therapeutic agent for targeting osteoclasts. This study offers valuable insights for developing next generation RANKL inhibitors for osteoporosis treatments.

Pharmacophore mapping, 3D QSAR, molecular docking, and ADME prediction studies of novel Benzothiazinone derivatives.

In the quest to combat tuberculosis, DprE1, a challenging target for novel anti-tubercular agents due to its small size and membrane location, has been a focus of research. DprE1 catalyzes the transformation of DPR into Ketoribose DPX, with Benzothiazinone emerging as a potent pharmacophore for inhibiting DprE1. Clinical trial drugs such as BTZ043, BTZ038, PBTZ169, and TMC-207 have shown promising results as DprE1 inhibitors. This study employed pharmacophore mapping of Pyrazolopyridine, Dinitrobenzamide, and Benzothiazinone derivatives to identify crucial features for eliciting a biological response. Benzothiazinone (Ligand code: 73) emerged as a reference ligand with a fitness score of 3.000. ROC analysis validated the pharmacophore with an excellent score of 0.71. To build a 3D QSAR model, a series of Benzothiazinone congeneric derivatives were explored. The model exhibited strong performance, with a standard deviation of 0.1531, a correlation coefficient for the training set (R2) value of 0.9754, and a correlation coefficient for test set Q2 value of 0.7632, indicating robust predictive capabilities. Contour maps guided the design of novel benzothiazinone derivatives, emphasizing steric, electrostatic, hydrophobic, H-bond acceptor, and H-bond donor groups for structure-activity relationships. Docking studies against PDB ID: 4NCR demonstrated favorable scores, with interactions aligning well with the in-built ligand 26 J. Docking validation via RMSD values supported the reliability of the docking results. This comprehensive approach aids in the design of novel benzothiazinone derivatives with potential anti-tubercular properties, contributing to the development of novel anti-tubercular agents which can be pivotal in the eradication of tuberculosis.

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

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

Development of a high throughput cytochrome P450-ligand binding assay.

Human cytochrome P450 enzymes are membrane-embedded monooxygenases responsible for xenobiotic metabolism, steroidogenesis, fatty acid metabolism, and vitamin metabolism. Their active sites can accommodate diverse small molecules and understanding these interactions is key to decoding enzymatic functionality and designing drugs. The most common method for characterizing small molecule binding is quantifying absorbance changes that typically occur when substrates enter the active site near the heme iron. Traditionally such titrations are monitored by a spectrophotometer, requiring significant manual time, protein, and increasing solvents. This assay was adapted for semi-automated high throughput screening, increasing throughput 50-fold while requiring less protein and keeping solvent concentrations constant. This 384-well assay was validated for both type I and II shifts typically observed for substrates and heme-coordinating inhibitors, respectively. This assay was used to screen a library of ∼100 diverse imidazole-containing compounds which can coordinate with the heme iron if compatible with the overall active site. Three human cytochrome P450 enzymes were screened: drug-metabolizing CYP2A6 and CYP2D6 and sterol-metabolizing CYP8B1. Each bound different sets of imidazole compounds with varying Kd values, providing a unique binding fingerprint. As a final validation, the Kd values were used to generate pharmacophores to compare to experimental structures. Applications for the high-throughput assay include 1) facilitating generation of pharmacophores for enzymes where structures are not available, 2) screening to identify ligands for P450 orphans, 3) screening for inhibitors of P450s drug targets, 4) screening potential new drugs to avoid and/or control P450 metabolism, and 5) efficient validation of computational predictions.

Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

Thymidylate kinase (TMK) is a pivotal enzyme in Mycobacterium tuberculosis (Mtb), crucial for phosphorylating thymidine monophosphate (dTMP) to thymidine diphosphate (dTDP), thereby playing a critical role in DNA biosynthesis. Dysregulation or inhibition of TMK activity disrupts DNA replication and cell division, making it an attractive target for anti-tuberculosis drug development. In this study, the statistically validated pharmacophore mode was developed from a set of known TMK inhibitors. Further, the robust pharmacophore was considered for screening the Enamine database. The chemical space was reduced through multiple molecular docking approaches, pharmacokinetics, and absolute binding energy estimation. Two different molecular docking algorithms favor the strong binding affinity of the proposed molecules towards TMK. Machine learning-based absolute binding energy also showed the potentiality of the proposed molecules. The binding interactions analysis exposed the strong binding affinity between the proposed molecules and active site amino residues of TMK. Several statistical parameters from all atoms MD simulation explained the stability between proposed molecules and TMK in the dynamic states. The MM-GBSA approach also found a strong binding affinity for each proposed molecule. Therefore, the proposed molecules might be crucial TMK inhibitors for managing Mtb inhibition subjected to in vitro/in vivo validations.

Unveiling structural determinants for FXR antagonism in 1,3,4-trisubstituted-Pyrazol amide derivatives: A multi-scale in silico modelling approach.

Non-alcoholic fatty liver disease (NAFLD) is a growing global health concern due to its potential to progress into severe liver diseases. Targeting the bile acid receptor FXR has emerged as a promising strategy for managing NAFLD. Building upon our previous research on FXR partial agonism, the present study investigates a series of 1,3,4-trisubstituted-pyrazol amide derivatives as FXR antagonists, aiming to delineate the structural features for antagonism. By means of 2D-QSAR (quantitative structure-activity relationships) modelling techniques, we elucidated the key structural elements responsible for the antagonistic properties of these derivatives. We then employed QPhAR, an open-access software, to identify key molecular features within the compounds that enhance their antagonistic activity. Additionally, 3D-QSAR modelling allowed us to analyse the steric and electrostatic fields of aligned 3D structures, further refining our understanding of structure-activity relationships. Subsequent molecular dynamics simulations provided insights into the binding mode interactions between the compounds and FXR, with varying potencies, confirming and complementing the findings from 2D-QSAR, pharmacophore, and 3D-QSAR modelling. Particularly, our study highlighted the significance of hydrophobic interactions in conferring potent antagonism by the 1,3,4-trisubstituted-pyrazol amide derivatives against FXR. Overall, this work underscores the potential of 1,3,4-trisubstituted-pyrazol amides as FXR antagonists for NAFLD treatment. Notably, our reliance on open-access software fosters reproducibility and broadens the accessibility of our findings.

E-pharmacophore and deep learning based high throughput virtual screening for identification of CDPK1 inhibitors of Cryptosporidium parvum.

Cryptosporidiosis, a prevalent gastrointestinal illness worldwide, is caused by the protozoan parasite Cryptosporidium parvum. Calcium-dependent protein kinase 1 (CpCDPK1), crucial for the parasite's life cycle, serves as a promising drug target due to its role in regulating invasion and egress from host cells. While potent Pyrazolopyrimidine analogs have been identified as candidate hit molecules, they exhibit limitations in inhibiting Cryptosporidium growth in cell culture, prompting exploration of alternative scaffolds. Leveraging the most potent compound, RM-1-95, co-crystallized with CpCDPK1, an E-pharmacophore model was generated and validated alongside a deep learning model trained on known CpCDPK1 compounds. These models facilitated screening Enamine's 2 million HTS compound library for novel CpCDPK1 inhibitors. Subsequent hierarchical docking prioritized hits, with final selections subjected to Quantum polarized docking for accurate ranking. Results from docking studies and MD simulations highlighted similarities in interactions between the cocrystallized ligand RM-1-95 and identified hit molecules, indicating comparable inhibitory potential against CpCDPK1. Furthermore, assessing metabolic stability through Cytochrome 450 site of metabolism prediction offered crucial insights for drug design, optimization, and regulatory approval processes.

Computational exploration and molecular dynamic simulation for the discovery of antiviral agents targeting Newcastle disease virus.

Newcastle disease virus (NDV) is a highly infectious viral disease that impacts birds globally, especially domestic poultry. NDV is a type of avian paramyxovirus which poses a major threat to the poultry industry due to its ability to inflict significant economic damage. The membrane protein, Hemagglutinin-Neuraminidase (HN) of NDV is an attractive therapeutic candidate. It contributes to pathogenicity through various functions, such as promoting fusion and preventing viral self-agglutination, which allows for viral spread. In this study, we used pharmacophore modeling to identify natural molecules that can inhibit the HN protein of NDV. Physicochemical characteristics and phylogenetic analysis were determined to elucidate structural information and phylogeny of target protein across different species as well as members of the virus family. For structural analysis, the missing residues of HN target protein were filled and the structure was evaluated by PROCHECK and VERIFY 3D. Moreover, shape and feature-based pharmacophore model was employed to screen natural compounds' library through numerous scoring schemes. Top 48 hits with 0.8860 pharmacophore fit score were subjected towards structure-based molecular docking. Top 9 compounds were observed witihin the range of -8.9 to -7.5 kcal/mol binding score. Five best-fitting compounds in complex with HN receptor were subjected to predict biological activity and further analysis. Top two hits were selected for MD simulations to validate binding modes and structural stability. Finally, upon scrutinization, A1 (ZINC05223166) emerges as potential HN inhibitor to treat NDV, necessitating further validation via clinical trials.