Search

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs. [ABSTRACT FROM AUTHOR]

The SARS‐CoV‐2 3C‐like protease (3CLpro) has emerged as a key target for drug development owing to its crucial role in viral replication of SARS‐CoV‐2 virus. In this study, we employed a ligand‐based virtual screening strategy to identify potential small molecules capable of binding to SARS‐CoV‐2 3CLpro. Using GC376 as a reference compound, we conducted a comprehensive search in a chemical database and identified 178 candidate molecules (CPLs) with structural similarity to GC376. Molecular docking analyses revealed that several CPLs exhibited superior binding affinities to SARS‐CoV‐2 3CLpro compared to GC376. Notably, CPL‐390, CPL‐374, and CPL‐306 displayed the highest binding energies, indicating their potential as inhibitors of SARS‐CoV‐2 3CLpro. Detailed analysis of noncovalent interactions and molecular mechanics generalized Born surface area (MMGBSA) calculations further supported the binding affinity of CPLs to SARS‐CoV‐2 3CLpro. Key interactions with catalytic residues and steric hindrance within the binding pocket highlighted potential inhibition mechanisms for CPL‐306, CPL‐374, and CPL‐390. Moreover, pharmacokinetic analysis indicated that CPL‐306, CPL‐374, and CPL‐390 possessed favorable absorption, distribution, metabolism, and excretion (ADME) properties, positioning them as promising candidates for further drug development. In contrast, GC376 exhibited less favorable pharmacological characteristics, emphasizing the need for novel compounds with improved profiles. [ABSTRACT FROM AUTHOR]

In the present work, phytoconstituents from Citrus limon are computationally tested against SARS‐CoV‐2 target protein such as Mpro ‐ (5R82.pdb), Spike ‐ (6YZ5.pdb) &RdRp ‐ (7BTF.pdb) for COVID‐19. Docking was done by glide model, QikProp was performed by in silico ADMET screening & Prime MM‐GB/SA modules were used to define binding energy. When compared with approved COVID‐19 drugs such as Remdesivir, Ritonavir, Lopinavir, and Hydroxychloroquine, plant‐based constituents such as Quercetin, Rutoside, Naringin, Eriocitrin, and Hesperidin. bind with significant G‐scores to the active SARS‐CoV‐2 place. The constituents Rutoside and Eriocitrin were studied in each MD simulation in 100 ns against 3 proteins 5R82.pdb, 6YZ5.pdb and 7BTF.pdb.We performed an assay with significant natural compounds from contacts and in silico results (Rutin, Eriocitrin, Naringin, Hesperidin) using 3CL protease assay kit (B.11529 Omicron variant). This kit contained 3CL inhibitor GC376 as Control. The IC50 value of the test compound was found to be Rutin −17.50 μM, Eriocitrin−37.91 μM, Naringin−39.58 μM, Hesperidine−140.20 μM, the standard inhibitory concentration of GC376 was 38.64 μM. The phytoconstituents showed important interactions with SARS‐CoV‐2 targets, and potential modifications could be beneficial for future development. [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of the metabolic syndrome, posing risks to cardiovascular and hepatic health worldwide. Non-alcoholic steatohepatitis (NASH) which is a severe form of NAFLD, has a global prevalence. Therapeutic targets for NASH include THR-β, GLP-1 receptor, PPARα/δ/γ, FGF21 analogs, and FXR, a bile acid nuclear receptor pivotal for regulating bile acid synthesis and excretion. Our study aims to design the non-steroidal FXR agonist for NASH treatment, as FXR's role in the regulation of bile acid processes, rendering it a promising drug target for NASH therapy. Utilizing tropifexor as a reference molecule, we generated a shape-based pharmacophore model with seven features, identifying key binding requirements within the FXR active site. Virtual screening using this model, coupled with molecular docking studies, helped pinpoint potential ligands from diverse small molecule databases. Further analysis via MM/GBSA revealed 12 molecules with binding affinities comparable to tropifexor. Among them, DB15416 exhibited the lowest binding free energy and superior docking scores. To assess its dynamic stability, we subjected DB15416 to molecular dynamics simulations, confirming its suitability as a FXR agonist. These findings suggest that DB15416 holds promise as a FXR agonist for NASH treatment, which can be evaluated by experimental studies. [ABSTRACT FROM AUTHOR]

Abstract Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

Nipah virus (NiV) is known to be a highly pathogenic zoonotic virus, which is included in the World Health Organization Research & Development Blueprint list of priority diseases with up to 70% mortality rate. Due to its high pathogenicity and outbreak potency, a therapeutic countermeasure against NiV is urgently needed. As NiV needs to be handled within a Biological Safety Level (BSL) 4 facility, we had developed a safe drug screening platform utilizing a baculovirus expression vector system (BEVS) based on a NiV-induced syncytium formation that could be handled within a BSL-1 facility. To reconstruct the NiV-induced syncytium formation in BEVS, two baculoviruses were generated to express recombinant proteins that are responsible for inducing the syncytium formation, including one baculovirus exhibiting co-expressed NiV fusion protein (NiV-F) and NiV attachment glycoprotein (NiV-G) and another exhibiting human EphrinB2 protein. Interestingly, syncytium formation was observed in infected insect cells when the medium was modified to have a lower pH level and supplemented with cholesterol. Fusion inhibitory properties of several compounds, such as phytochemicals and a polysulfonated naphthylamine compound, were evaluated using this platform. Among these compounds, suramin showed the highest fusion inhibitory activity against NiV-induced syncytium in the baculovirus expression system. Moreover, our in silico results provide a molecular-level glimpse of suramin's interaction with NiV-G's central hole and EphrinB2's G-H loop, which could be the possible reason for its fusion inhibitory activity. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) caused by the Mycobacterium tuberculosis (MTB) pathogen is a serious contagious illness that endangers the public's health. However, TB is treatable but due to the result of ineffective and protracted medication, MDR‐MTB and XDR‐MTB were able to develop, making their eradication highly challenging and necessitating potential treatments to be cured. This study aimed to identify the novel inhibitor for the InhA enzyme, a potential target of MTB. Initially, 2721 phytochemicals libraries were screened for ADME/Tox profiling and 49 phytochemicals were filtered out. Moreover, these phytochemicals with reference inhibitor triclosan were docked against InhA (PDB ID: 1BVR)., were showing binding energies ranging from −9.16–−6.3 kcal/mol, whereas triclosan showed −6.90 kcal/mol of binding energy. The docking results reveal that irilone (−9.16 kcal/mol) and aurantio‐obtusin (−8.84 kcal/mol) exhibit promising binding energy and perfectly occupy the binding site of InhA. Furthermore, molecular dynamics simulation (MDS) and MMGBSA studies showed better affinities of selected compounds in terms of stability, compactness, flexibility, and total BFE in complexes with InhA. This study concluded that irilone and aurantio‐obtusin could be promising InhA inhibitors based on their impressive pharmacokinetic profiling, toxicity, binding affinity, and stability. However experimental validation is a subject of further research. [ABSTRACT FROM AUTHOR]

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell proliferation, resistance to cell death, blood vessel development, and metastasis (spread to other organs). One of the several routes that play an important role in the development and progression of cancer is the phosphoinositide 3-kinase (PI3K) signaling pathway. Moreover, the gene PIK3CG encodes the catalytic subunit gamma (p110γ) of phosphoinositide 3-kinase (PI3Kγ), a member of the PI3K family. Therefore, in this study, PIK3CG was targeted to inhibit cancer by identifying a novel inhibitor through computational methods. The study screened 1015 chemical fragments against PIK3CG using machine learning-based binding estimation and docking to select the potential compounds. Later, the analogues were generated from the selected hits, and 414 analogues were selected, which were further screened, and as most potential candidates, three compounds were obtained: (a) 84,332, 190,213, and 885,387. The protein–ligand complex's stability and flexibility were then investigated by dynamic modeling. The 100 ns simulation revealed that 885,387 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 885,387 demonstrated a superior binding free energy (ΔG = −18.80 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 885,387 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the PIK3CG target implicated in cancer. [ABSTRACT FROM AUTHOR]

The β-secretase, sometimes referred to as BACE1 or Asp2, is the enzyme responsible for initiating the production of Aβ by breaking down the amyloid precursor protein. Hence, BACE is a pivotal target for pharmacological intervention aimed at diminishing the production of Aβ in Alzheimer's disease (AD). We did a quantitative structure-activity relationship (QSAR) study on 1235 compounds that had been experimentally reported as BACE-1 inhibitors (Ki) to find the target molecule and structural patterns linked to blocking the BACE-1 receptor. The OECD-recommended genetic algorithm-multiple linear regression (GA-MLR) QSAR model strikes a good balance between being able to make accurate predictions and understanding how things work. It achieves high values for many evaluation metrics, including R2tr = 0.8047, Q2LMO = 0.802, R2ex = 0.805, CCCex = 0.891, Q2-F1=0.801, Q2-F2=0.799, and Q2-F3=0.815. The mechanistic interpretation of QSAR has identified some nitrogen atoms that are required to block beta-secretase and make it less effective at doing its job. A positively charged aromatic carbon atom has a more significant impact on beta-secretase-1 inhibition. The docking study showed that the catalytic dye residues Asp32 and Asp228 become protonated when compound 27 is present, but they stay unprotonated when compound 27 is not present. These rings of pyrazine and pyridine interact hydrophobically with Tyr71 and Ile118 residues, confirming the pharmacophoric features seen in the QSAR data. We examined the stability of both the protein-ligand complex and the apo-protein. The apoprotein had an average gyration radius of 22.13, whereas the protein-ligand complex had an average gyration radius of 22.91. No changes were made to the results from the molecular docking, molecular dynamics (MD) simulation, MMGBSA (Molecular Mechanics Generalized Born Surface Area), or DFT analyses. Therefore, the current work could effectively contribute to the future development of BACE inhibitors in medication design.

Many human disorders include NF-kB signaling pathways, making IKK a therapeutic target in cancer treatment. Inflammatory illnesses and cancer are examples. COVID-19 is one of several triggers that stimulate NF-kB signaling. The activation of the NF-kB pathway is necessary for COVID-19 to cease its development. To learn more about the mechanism and structural features essential to IKK inhibition (IC50), molecular modeling studies have been undertaken on experimentally reported 503. QSAR analysis explores certain reported and hidden structural features critical for IKKβ inhibition. The OECD guidelines guided the construction of the QSAR model, which achieved all the endorsed threshold values for all validation parameters (R2tr:0.81, R2LMO:0.80, and R2ext:0.78). The present QSAR study shows that IKK inhibitory activity is linked to the following structural features: lipophilic hydrogen atoms within 2 A units of the molecule's center of mass; ring nitrogen atoms within one bond of planar nitrogen atoms; ring carbon atoms exactly four bonds from the non-ring nitrogen atoms; planar nitrogen atoms exactly four bonds from sp2 hybridized carbon atoms; and so on. Pharmacophore modeling highlighted QSAR-identified structural characteristics. To investigate binding, we docked all 503 molecules. The observation indicates that the QSAR and molecular docking/pharmacophore modeling findings are in agreement. Following this, we conducted 200 ns of molecular dynamics simulation to validate the molecular docking protocol. MMGBSA analysis determined the binding energy of the dock complex. Thus, the current study found unique pharmacophoric properties that may assist in optimizing lead/hit compounds for anti-IKKβ activity.

Oncology research progresses, yet cancer remains the largest medical need. The use of a medication with an accessible lead molecule shows great potential for long-term cancer therapy. It may help target cancer therapy and drug resistance. This work uses FDA-approved, clinically proven compounds to build novel cancer therapeutic ligands to prevent treatment resistance. Based on the reported findings, an in-silico docking experiment was performed using FDA-licensed fungus medication posaconazole. The ALK TK pdb:4cmu ligand and posaconazole docked similarly in the research. Posaconazole's in silico docking findings were then tested against A549 lung cancer cells. Posaconazole, the lead, underwent an ADME investigation. Given in silico and experimental confirmation, acetyl, benzyl, and benzoyl derivatives of the lead molecule posaconazole was synthesized. IR, mass, 1H NMR, 13C NMR, and elemental analysis were performed on the synthesized compounds. Next, the three variants were evaluated against A549 lung cancer cells. They were then examined by utilizing computational approaches such as molecular docking, DFT analysis, MD simulation, and MMGBSA analysis. The ADME studies were conducted on posaconazole and its derivatives based on the in-vitro cell line investigation. Based on the results of an ADME study, two new ALK TK inhibitors that don't work as Pgp substrates are good lead candidates. Thus, the present investigation fruitfully reported two lead drug candidates against the issue of resistance in cancer therapy.

Abstract In the present work, phytoconstituents from Citrus limon are computationally tested against SARS‐CoV‐2 target protein such as Mpro ‐ (5R82.pdb), Spike ‐ (6YZ5.pdb) &RdRp ‐ (7BTF.pdb) for COVID‐19. Docking was done by glide model, QikProp was performed by in silico ADMET screening & Prime MM‐GB/SA modules were used to define binding energy. When compared with approved COVID‐19 drugs such as Remdesivir, Ritonavir, Lopinavir, and Hydroxychloroquine, plant‐based constituents such as Quercetin, Rutoside, Naringin, Eriocitrin, and Hesperidin. bind with significant G‐scores to the active SARS‐CoV‐2 place. The constituents Rutoside and Eriocitrin were studied in each MD simulation in 100 ns against 3 proteins 5R82.pdb, 6YZ5.pdb and 7BTF.pdb.We performed an assay with significant natural compounds from contacts and in silico results (Rutin, Eriocitrin, Naringin, Hesperidin) using 3CL protease assay kit (B.11529 Omicron variant). This kit contained 3CL inhibitor GC376 as Control. The IC50 value of the test compound was found to be Rutin −17.50 μM, Eriocitrin−37.91 μM, Naringin−39.58 μM, Hesperidine−140.20 μM, the standard inhibitory concentration of GC376 was 38.64 μM. The phytoconstituents showed important interactions with SARS‐CoV‐2 targets, and potential modifications could be beneficial for future development.

Abstract Background Cucurbitacins are present in some common vegetables as secondary metabolites and are used by the plants against harmful microbes. Exploration of this capability of natural product based substances against wide variety of microbes seems relevant due to the ease of availability of the resources and safety. In this regard, considering the current pandemic, the antiviral properties of these molecules with a subset of Cucurbitacin I structural derivatives have been screened. The inhibition potential of the phytochemicals was assessed by the stability of the protein–ligand complex formed with the nucleocapsid protein (PDB ID: 7CDZ) of SARS-CoV-2 by computational methods. The proposition of an alternate antiviral candidate that is cost-effective and efficient relative to existing formulations is the main objective of this work. Results Server-based molecular docking experiments revealed CBN19 (PubChem CID: 125125068) as a hit candidate among 101 test compounds, a reference molecule (K31), and 5 FDA-approved drugs in terms of binding affinities sorted out based on total energies. The molecular dynamics simulations (MDS) showed moderate stability of the protein-CBN19 complex as implied by various geometrical parameters RMSD, Rg, RMSF, SASA and hydrogen bond count. The ligand RMSD of 3.0 ± 0.5 Å, RMSF of Cα of protein with less than 5 Å, and smooth nature of SASA and Rg curves were calculated for the adduct. The binding free energy (− 47.19 ± 6.24 kcal/mol) extracted from the MDS trajectory using the MMGBSA method indicated spontaneity of the reaction between CBN19 and the protein. The multiple ADMET studies of the phytochemicals predicted some drug-like properties with minimal toxicity that mandate experimental verification. Conclusions Based on all the preliminary in silico results, Cucurbitacin, CBN19 could be proposed as a potential inhibitor of nucleocapsid protein theoretically capable of curing the disease. The proposed molecule is recommended for further in vitro and in vivo trials in the quest to develop effective and alternate therapeutics from plant-based resources against COVID-19.

Prioritizing molecules for synthesis is a key role of computational methods within medicinal chemistry. Multiple tools exist for ranking molecules, from the cheap and popular molecular docking methods to more computationally expensive molecular-dynamics (MD)-based methods. It is often questioned whether the accuracy of the more rigorous methods justifies the higher computational cost and associated calculation time. Here, we compared the performance on ranking the binding of small molecules for seven scoring functions from five docking programs, one end-point method (MM/GBSA), and two MD-based free energy methods (PMX, FEP+). We investigated 16 pharmaceutically relevant targets with a total of 423 known binders. The performance of docking methods for ligand ranking was strongly system dependent. We observed that MD-based methods predominantly outperformed docking algorithms and MM/GBSA calculations. Based on our results, we recommend the application of MD-based free energy methods for prioritization of molecules for synthesis in lead optimization, whenever feasible.

Allergic rhinitis (AR) is a prevalent inflammatory condition affecting millions globally, with current treatments often associated with significant side effects. To seek safer and more effective alternatives, natural sources like Urtica dioica (UD) are being explored. However, UD's mechanism of action remains unknown. Therefore, to elucidate it, we conducted an in silico evaluation of UD phytochemicals' effects on known therapeutic targets of allergic rhinitis: histamine receptor 1 (HR1), neurokinin 1 receptor (NK1R), cysteinyl leukotriene receptor 1 (CLR1), chemoattractant receptor-homologous molecule expressed on type 2 helper T cells (CRTH2), and bradykinin receptor type 2 (BK2R). The docking analysis identified amentoflavone, alpha-tocotrienol, neoxanthin, and isorhamnetin 3-O-rutinoside as possessing a high affinity for all the receptors. Subsequently, molecular dynamics (MD) simulations were used to analyze the key interactions; the free energy of binding was calculated through Generalized Born and Surface Area Solvation (MMGBSA), and the conformational changes were evaluated. Alpha-tocotrienol exhibited a high affinity while also inducing positive conformational changes across all targets. Amentoflavone primarily affected CRTH2, neoxanthin targeted NK1R, CRTH2, and BK2R, and isorhamnetin-3-O-rutinoside acted on NK1R. These findings suggest UD's potential to treat AR symptoms by inhibiting these targets. Notably, alpha-tocotrienol emerges as a promising multi-target inhibitor. Further in vivo and in vitro studies are needed for validation. [ABSTRACT FROM AUTHOR]

Background: Cucurbitacins are present in some common vegetables as secondary metabolites and are used by the plants against harmful microbes. Exploration of this capability of natural product based substances against wide variety of microbes seems relevant due to the ease of availability of the resources and safety. In this regard, considering the current pandemic, the antiviral properties of these molecules with a subset of Cucurbitacin I structural derivatives have been screened. The inhibition potential of the phytochemicals was assessed by the stability of the protein–ligand complex formed with the nucleocapsid protein (PDB ID: 7CDZ) of SARS-CoV-2 by computational methods. The proposition of an alternate antiviral candidate that is cost-effective and efficient relative to existing formulations is the main objective of this work. Results: Server-based molecular docking experiments revealed CBN19 (PubChem CID: 125125068) as a hit candidate among 101 test compounds, a reference molecule (K31), and 5 FDA-approved drugs in terms of binding affinities sorted out based on total energies. The molecular dynamics simulations (MDS) showed moderate stability of the protein-CBN19 complex as implied by various geometrical parameters RMSD, Rg, RMSF, SASA and hydrogen bond count. The ligand RMSD of 3.0 ± 0.5 Å, RMSF of Cα of protein with less than 5 Å, and smooth nature of SASA and Rg curves were calculated for the adduct. The binding free energy (− 47.19 ± 6.24 kcal/mol) extracted from the MDS trajectory using the MMGBSA method indicated spontaneity of the reaction between CBN19 and the protein. The multiple ADMET studies of the phytochemicals predicted some drug-like properties with minimal toxicity that mandate experimental verification. Conclusions: Based on all the preliminary in silico results, Cucurbitacin, CBN19 could be proposed as a potential inhibitor of nucleocapsid protein theoretically capable of curing the disease. The proposed molecule is recommended for further in vitro and in vivo trials in the quest to develop effective and alternate therapeutics from plant-based resources against COVID-19. [ABSTRACT FROM AUTHOR]

Oncology research progresses, yet cancer remains the largest medical need. The use of a medication with an accessible lead molecule shows great potential for long-term cancer therapy. It may help target cancer therapy and drug resistance. This work uses FDA-approved, clinically proven compounds to build novel cancer therapeutic ligands to prevent treatment resistance. Based on the reported findings, an in-silico docking experiment was performed using FDA-licensed fungus medication posaconazole. The ALK TK pdb:4cmu ligand and posaconazole docked similarly in the research. Posaconazole’s in silico docking findings were then tested against A549 lung cancer cells. Posaconazole, the lead, underwent an ADME investigation. Given in silico and experimental confirmation, acetyl, benzyl, and benzoyl derivatives of the lead molecule posaconazole was synthesized. IR, mass, 1H NMR, 13C NMR, and elemental analysis were performed on the synthesized compounds. Next, the three variants were evaluated against A549 lung cancer cells. They were then examined by utilizing computational approaches such as molecular docking, DFT analysis, MD simulation, and MMGBSA analysis. The ADME studies were conducted on posaconazole and its derivatives based on the in-vitro cell line investigation. Based on the results of an ADME study, two new ALK TK inhibitors that don’t work as Pgp substrates are good lead candidates. Thus, the present investigation fruitfully reported two lead drug candidates against the issue of resistance in cancer therapy [ABSTRACT FROM AUTHOR]

We investigated 1012 molecules from natural products previously isolated from the South African biodiversity (SANCDB, https://sancdb.rubi.ru.ac.za/), for putative inhibition of Onchocerca volvulus pi-class glutathione S-transferase (Ov-GST2) by virtual screening, MMGBSA, and molecular dynamics approaches. ADMET, docking, and MMGBSA shortlisted 12 selected homoisoflavanones-type hit molecules, among which two namely SANC00569, and SANC00689 displayed high binding affinities of −46.09 and −46.26 kcal mol−1, respectively towards π-class Ov-GST2, respectively. The molecular dynamics results of SANC00569 showed the presence of intermolecular H-bonding, hydrophobic interactions between the ligand and key amino acids of Ov-GST2, throughout the simulation period. This hit molecule had a stable binding pose and occupied the binding pockets throughout the 200 ns simulation. To the best of our knowledge, there is no report of any alleged anti–onchocerciasis activity referring to homoisoflavanones or flavonoids. Nevertheless, homoisoflavanones, which are a subclass of flavonoids, exhibit a plethora of biological activities. All these results led to the conclusion that SANC00569 is the most hypothetical Ov-GST2, which could lead the development of new drugs against Onchocerca volvulus pi-class glutathione S-transferase. Further validation of these findings through in vitro and in vivo studies is required.

Abstract Objective This study aims to find the most promising Ganoderma lucidium targeting LRRK2 involved in PD. Methods First ADMET analysis was performed for five compounds followed by molecular docking of each compound. Then, we perform molecular dynamics simulation of all five compounds and finally MMGBSA of all five compounds. Results Based on molecular dynamics and MMGBSA result we reach the conclusion that Ganoderic Acid A (GAA) is the most promising compound targeting LRRK2. Therefore, GAA needs further validation through in vitro and in vivo studies. Conclusion Ganoderma lucidum exhibits cytotoxic, hepatoprotective, antioxidative, anticancer, and antinociceptive activities. This study predicted that Ganoderma lucidum could even be used to treat neurological disorders like PD. This study suggest that the best‐identified molecule against LRRK2 is GAA and it needs rigorous in vitro and in vivo validations.

Pneumonia, an infectious lung disease, is a significant global health concern, claiming the lives of 740,180 children in 2019, which accounts for 14 % of pediatric deaths. Recently, the management of pediatric pneumonia has become complex due to exposure to indoor and outdoor environmental toxins. Notably, exposure to pollutants and antibiotic-resistant bacteria during community and hospital-acquired pneumonia poses a serious threat to patient outcomes. The development of antibiotic resistance against Streptococcus pneumoniae is driven by the DinF efflux pump protein, which expels antibiotics from bacterial cells, leading to multidrug resistance. Therefore, blocking DinF could serve as a strategy to combat antibiotic resistance. This study aimed to identify DinF inhibitors from compounds analogous to verapamil, a well-known DinF inhibitor, through computational techniques including molecular docking, molecular dynamics simulations, ADMET analysis, MMGBSA, quantum mechanics, and Network Pharmacology. After considering docking scores, results of MMGBSA, quantum mechanics, Molecular Dynamics Simulations, ADMET analysis and network pharmacology profiling four compounds namely netarsudil, rimegepant, GSK-1521498 and tariquidar were found as the most promising DinF inhibitors. Therefore, these compounds hold a great promise as leads to the development of potent DinF inhibitors; however, further studies are needed to warrant their clinical uses against antibiotic resistant Streptococcus pneumoniae-induced pneumonia.

Govaniadine, an isoquinoline alkaloid first isolated from Corydalis govaniana Wall., has been reported to possess multiple biological properties. Its potential as a possible dopamine receptor D1 modulator has been assessed in this research work along with its 3D similar structures for hit molecule optimization by in silico methods. Server-based molecular docking calculations were performed to find the best docked pose of the top molecules in terms of binding affinity and total energy. The molecular level details of the ligand molecules interacting with the amino acid residues near the orthosteric site of the dopamine receptor D1 (PDB ID: 7X2F) were elaborated. The stability of the protein-ligand adduct as determined from 200 ns molecular dynamics simulation in terms of structural parameters like root mean square deviation, root mean square fluctuation, radius of gyration, solvent accessible surface area, and hydrogen bond count was reasonable and free energy change from −35.46 ± 2.91 kcal/mol to −16.87 ± 2.91 kcal/mol from molecular mechanics generalized Born surface area method hinted at the spontaneity of the forward reaction for the top molecules. Ligand 626 (PubChem CID: 71109986) could be chosen as a hit candidate with better geometrical and thermodynamic stability and could be a possible modulator. The preliminary results point towards the need for further characterization of govaniadine scaffold-derived hit molecules for their development as effective and safe drug candidates by various experimental and computational techniques.

The enzyme Heme O Synthase (HOS) is essential for producing heme A and heme O, which are critical for defense against reactive oxygen species, drug detoxification, gas synthesis, transport, and electron transport in Plasmodium species. It has become vital to discover inhibitory molecules/compounds/medicines that target the synthesis of heme due to the emergence of drug‐resistant strains of Plasmodium falciparum. Therefore, in this study, we employed molecular mechanics with Generalized Born surface area (MMGBSA) calculations and docking studies to investigate potential antimalarial compounds targeting HOS from antimalarial botanicals. Screening these compounds, we have identified 2 compounds; Meliantrol and Tamarixetin with better binding affinities (−8.4 Kcal/mol and −8.3 Kcal/mol respectively) than the current standard inhibitor(Inabenfide) of HOS (−8.0 Kcal/mol). The MMGBSA calculations provided insight into the thermodynamics of the binding process and helped identify key interactions responsible for the stability of the HOS‐ligand complex. In addition, the 2 compounds were further screened comparatively with the standard HOS inhibitor considering their protein‐ligand interaction profile and ADMET profile and these 2 selected compounds outperformed Inabenfide. Our results predict that these compounds are potential drug candidates with domiciled therapeutic functions against Malaria therefore, open doors for more experimental validations for drug development. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 pandemic, caused by the novel coronavirus, has posed a significant global health threat since its emergence in late 2019. The World Health Organization declared the outbreak a pandemic on March 11, 2020, due to its rapid global spread and impact on public health. New variants have raised concerns about their potential impact on the transmission of the virus and the effectiveness of current diagnostic tools, treatments, and vaccines. This study aims to investigate the effect of new variants in Pakistani virus strains on human receptors, specifically ACE2 and NRP1. In-silico analysis provides a powerful tool to analyze the potential impact of new variants on protein structure, function, and interactions. The SARS-CoV-2 virus is evolving quickly. After being exposed in Wuhan, SARS-CoV-2 underwent numerous mutations, leading to several variants' emergence. These variants stabilize the interaction of spike protein with human receptors ACE2 and NRP1. The study aims to check the molecular effect of these variants on human receptors using the in-silico approach. We use in-silico mutational tools to analyze new variants in SARS-CoV-2 and to check the molecular interaction of spike protein with human receptors (ACE2 and NRP1). Genomic sequences of 41 SARS-CoV-2 strains were sequenced using Ion Torrent (NGS) and submitted to the GISAID database. Spike protein of SARS-CoV-2 sequence trimmed and translated into a protein sequence using ExPasy. We used multiple sequence alignments to check for variants in the spike protein of strains. We utilized mutation tools such as Mupro, SIFT, SNAP2, and Mutpred2.3D structures of SARS-CoV-2 spike proteins (wild and mutated) to analyze further the mutations, ACE2 and NRP1 modelled by the ITASSER protein modelling server. Interactions of spike proteins (wild and mutant) analyzed by MD Docking, Simulation, and MMGBSA Variants I210T, V213G, S371F, S373P, T478K, F486V, Y505H, and D796Y were identified in SARS-CoV-2 Pakistani strains' spike protein. Variant Y505H were found to affect protein function. MD Docking, MMGBSA and MD simulation revealed that these variants increased spike protein's binding affinity with human receptors (ACE2 and NRP1). MD simulation revealed that mutated spike protein stabilized earlier than wild when interacting with ACE2 after 40 ns and interaction with NRP1 stabilized after 30 ns for mutated spike protein compared to wild. These variants in Pakistani strains of SARS-CoV-2 are increasing the stability of spike protein with human receptors. These findings provide insight into how the SARS-CoV-2 virus evolves and adapts to human hosts. This information may help develop strategies to control the virus's spread and develop effective treatments and vaccines in the future. [ABSTRACT FROM AUTHOR]

Abstract Objective Alzheimer's disease (AD) is one of the most prevalent neurological ailments, affecting around 50 million individuals globally. The condition is characterized by nerve cell damage due to the formation of amyloid‐beta plaques and neurofibrillary tangles. Only a few US Food and Drug Administration (FDA)‐approved medications are available in the market which are devoid of side effects, thus, making it imperative to investigate new alternatives for countering this disease. According to a recent study, microtubule affinity regulation kinase 4 (MARK4) is attributed as one of the most promising drug targets for AD, thus, being selected for this study. Compounds from Ganoderma lucidum (Reishi mushroom) extracts were selected to be used as ligands for this study. Methods In this study, the five most potent compounds from Ganoderma lucidum were selected and their absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis was performed, followed by molecular docking, and molecular dynamics simulation of each compound with MARK4 and supported by molecular mechanics generalized born surface area (MMGBSA) binding free energy calculations. Results The promising compounds were selected based on their ADMET profile and interactions with the active site residues of MARK4. Based on docking scores of −9.1 and −10.3 kcal/ mol, respectively, stability assessment by molecular dynamics simulation, and MMGBSA calculations, ganoderic acid A and ganoderenic acid B were found to be the most promising compounds against MARK4 which will require further in vitro and in vivo validations. Conclusion Through this study, it is suggested that ganoderic acid A and ganoderenic acid B might be a class of promising compounds against AD, based on computational research, and can be further studied for preclinical and clinical studies.

Allergic rhinitis (AR) is a prevalent inflammatory condition affecting millions globally, with current treatments often associated with significant side effects. To seek safer and more effective alternatives, natural sources like Urtica dioica (UD) are being explored. However, UD’s mechanism of action remains unknown. Therefore, to elucidate it, we conducted an in silico evaluation of UD phytochemicals’ effects on known therapeutic targets of allergic rhinitis: histamine receptor 1 (HR1), neurokinin 1 receptor (NK1R), cysteinyl leukotriene receptor 1 (CLR1), chemoattractant receptor-homologous molecule expressed on type 2 helper T cells (CRTH2), and bradykinin receptor type 2 (BK2R). The docking analysis identified amentoflavone, alpha-tocotrienol, neoxanthin, and isorhamnetin 3-O-rutinoside as possessing a high affinity for all the receptors. Subsequently, molecular dynamics (MD) simulations were used to analyze the key interactions; the free energy of binding was calculated through Generalized Born and Surface Area Solvation (MMGBSA), and the conformational changes were evaluated. Alpha-tocotrienol exhibited a high affinity while also inducing positive conformational changes across all targets. Amentoflavone primarily affected CRTH2, neoxanthin targeted NK1R, CRTH2, and BK2R, and isorhamnetin-3-O-rutinoside acted on NK1R. These findings suggest UD’s potential to treat AR symptoms by inhibiting these targets. Notably, alpha-tocotrienol emerges as a promising multi-target inhibitor. Further in vivo and in vitro studies are needed for validation.

CB2R are fascinating targets for neuropathic pain and mood disorders because of their improved biological characteristics. Experimental data on 1296 cannabinoid-2 receptor inhibitors with different structural properties were used to develop a QSAR model following OECD guidelines. This study selected the best-predicted model (80:20 splitting ratio) with fitting parameters, such as R2:0.78; F:623.6, Internal validation parameters, such as Q2Loo:0.78; CCCcv: 0.87 and external validation parameters, such as R2ext:0.77; Q2F1:0.7730; Q2F2:0.7730; Q2F3:0.76; CCCext:0.87. Following this, another QSAR model was developed by using a 50:50 split ratio for thetraining and the prediction sets, which were then swapped to evaluate the robustness of the built QSAR model by the 50:50 ratio, which also gives a deeper understanding of the chemical space. In addition, we have confirmed the QSAR result with pharmacophore modelling, and supported by molecular docking, MD simulation, MMGBSA and ADME studies. Thus, this work may enable cannabinoid 2 receptor inhibsitor development.

2-phenoxyanline was thoroughly examined using several spectroscopy nuclear magnetic resonance, IR, UV–vis, and quantum mechanical methodologies. D F T with basis set is employed to determine structural optimization and distinct vibration modes. The optimum binding parameters agree closely with the observed binding characteristics. VEDA performed the duties relating to potential energy distribution (PED) satisfactorily. The G I A O approach was adopted to compute chemical shifts in the 13C, 1H- N.M.R and the outcomes were compared to experimental spectra. TD-DFT with PCM model was used to calculate UV–vis with different solvents that, when assessed against observational spectra. The FMO energy provides sufficient proof of such. Molecular docking and dynamic simulations gave a better idea of the interaction of ligands with receptors.

Aldose reductase (AR) is an important target in the development of therapeutics against hyper-glycemia-induced health complications such as retinopathy, etc. In this study, we employed a combination of structure-based drug design, molecular simulation, and free energy calculation approaches to identify potential hit molecules against anti-diabetic (anti-hyperglycemic)-induced health complications. The 3D structure of aldoreductase was screened for multiple compound libraries (1,00,000 compounds) and identified as ZINC35671852, ZINC78774792 from the ZINC database, Diamino-di nitro-methyl dioctyl phthalate, and Penta-o-galloyl-glucose from the South African natural compounds database, and Bisindolylmethane thiosemi-carbazides and Bisindolylme-thane-hydrazone from the Inhouse database for this study. The mode of binding interactions of the selected compounds later predicted their aldose reductase inhibitory potential. These com-pounds interact with the key active site residues through hydrogen bonds, salt bridges, and π-π interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. The structures of the lead inhibitors can serve as templates for developing novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is warranted. The current study is the first to design small molecule inhibitors for the aldoreductase protein that can be used in the development of therapeutic agents to treat diabetes.

Objective: This study aims to find the most promising Ganoderma lucidium targeting LRRK2 involved in PD. Methods: First ADMET analysis was performed for five compounds followed by molecular docking of each compound. Then, we perform molecular dynamics simulation of all five compounds and finally MMGBSA of all five compounds. Results: Based on molecular dynamics and MMGBSA result we reach the conclusion that Ganoderic Acid A (GAA) is the most promising compound targeting LRRK2. Therefore, GAA needs further validation through in vitro and in vivo studies. Conclusion: Ganoderma lucidum exhibits cytotoxic, hepatoprotective, antioxidative, anticancer, and antinociceptive activities. This study predicted that Ganoderma lucidum could even be used to treat neurological disorders like PD. This study suggest that the best‐identified molecule against LRRK2 is GAA and it needs rigorous in vitro and in vivo validations. [ABSTRACT FROM AUTHOR]

Objective: Alzheimer's disease (AD) is one of the most prevalent neurological ailments, affecting around 50 million individuals globally. The condition is characterized by nerve cell damage due to the formation of amyloid‐beta plaques and neurofibrillary tangles. Only a few US Food and Drug Administration (FDA)‐approved medications are available in the market which are devoid of side effects, thus, making it imperative to investigate new alternatives for countering this disease. According to a recent study, microtubule affinity regulation kinase 4 (MARK4) is attributed as one of the most promising drug targets for AD, thus, being selected for this study. Compounds from Ganoderma lucidum (Reishi mushroom) extracts were selected to be used as ligands for this study. Methods: In this study, the five most potent compounds from Ganoderma lucidum were selected and their absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis was performed, followed by molecular docking, and molecular dynamics simulation of each compound with MARK4 and supported by molecular mechanics generalized born surface area (MMGBSA) binding free energy calculations. Results: The promising compounds were selected based on their ADMET profile and interactions with the active site residues of MARK4. Based on docking scores of −9.1 and −10.3 kcal/ mol, respectively, stability assessment by molecular dynamics simulation, and MMGBSA calculations, ganoderic acid A and ganoderenic acid B were found to be the most promising compounds against MARK4 which will require further in vitro and in vivo validations. Conclusion: Through this study, it is suggested that ganoderic acid A and ganoderenic acid B might be a class of promising compounds against AD, based on computational research, and can be further studied for preclinical and clinical studies. [ABSTRACT FROM AUTHOR]

Mutations in P53 cause a loop unfolding, resulting in loss of activity and finally leading to cancer. One strategically reported way to arrest such oncogenesis is the restoration of tertiary structure as well as the function of mutant P53. In this attempt, we have designed a benzo-pyrazole-based novel ligand starting from a carbazole compound (EYB or PK9324) reported earlier to reinstate such function in mutant P53 (Y220C mutant, PDB: 6GGD). Assuming PK9324 as the template scaffold, de novo technique (Genetic algorithm, eLEA3D) was adopted within the binding pocket of 6GGD and our ligand DLIG1 was designed after several rounds of mutations. Docking and molecular dynamics (MD) simulation revealed significant interactions with key amino acid residues such as Cys220, Asp228, Leu145, Trp146, Val147, Thr150, Pro151, Pro152, Pro222, Pro223, Asp228, and Thr230. Along with sufficient binding stability, the MMGBSA analysis revealed its comparable binding free energy with other reported reference ligands (i.e. PK9324 and PK9318). Similar to these reference ligands, DLIG1 exhibited specificity in binding towards the Y220C mutant rather than towards wild-type P53. Finally, DLIG1 displayed a reorientation of a hydrophobic cavity in Y220C that hinted restoration of electrostatic interactions within the key loops of P53 favoring regain of its function. [ABSTRACT FROM AUTHOR]

The pandemic outbreak of human coronavirus is a global health concern that affects people of all ages and genders, but there is currently still no effective, approved and potential drug against human coronavirus, as many other coronavirus vaccines have serious side effects while the development of small antiviral inhibitors has gained tremendous attention. For this research, HE was used as a therapeutic target, as the spike protein displays a high binding affinity for both host ACE2 and viral HE glycoprotein. Molecular docking, pharmacophore modelling and virtual screening of 38,000 natural compounds were employed to find out the best natural inhibitor against human coronaviruses with more efficiency and fewer side effects and further evaluated via MD simulation, PCA, DCCR and MMGBSA. The lead compound 'Calceolarioside B' was identified on the basis of pharmacophoric features which depict favorable binding (ΔGbind −37.6799 kcal/mol) with the HE(5N11) receptor that describes positive correlation movements in active site residues with better stability, a robust H-bond network, compactness and reliable ADMET properties. The Fraxinus sieboldiana Blume plant containing the Calceolarioside B compound could be used as a potential inhibitor that shows a higher efficacy and potency with fewer side effects. This research work will aid investigators in the testing and identification of chemicals that are effective and useful against human coronavirus. [ABSTRACT FROM AUTHOR]

Vernonia amygdalina, a widely consumed West African food herb, can be a boon in the discovery of safe anti-obesity agents given the extensive reports on its anti-obesity and antidiabetic potentials. The main aim of this study was to screen 78 Vernonia—Derived Phytocompounds (VDPs) against the active site regions of Human Pancreatic Lipase (HPL), Human Pancreatic Amylase and Human Glucosidase (HG) as drug targets associated with obesity in silico. Structure-based virtual screening helped to identify Luteolin 7-O-glucuronoside and Andrographidoid D2 as hit compounds with dual targeting tendency towards the HPL and HG. Analysis of the molecular dynamic simulation trajectory files of the ligand-receptor complexes as computed from the thermodynamic parameters plots showed not only increased flexibility and greater interaction potential of the active site residues of the receptor towards the VDPs as indicated by the root mean square fluctuation but also higher stability as indicated by the root mean square deviation, radius of gyration and number of hydrogen bonds. The cluster analysis further showed that the interactions with important residues were preserved in the dynamic environment. These observations were further verified from Molecular Mechanics Generalized Born Surface Area Analysis, which also showed that residual contributions to the binding free energies were mainly from catalytic residues at the active sites of the enzymes. The hit compounds also feature desirable physicochemical properties and drug-likeness. This study provides in silico evidence for the inhibitory potential of phytochemicals from Vernonia amygdalina against two target enzymes in obesity. [ABSTRACT FROM AUTHOR]

CB2R are fascinating targets for neuropathic pain and mood disorders because of their improved biological characteristics. Experimental data on 1296 cannabinoid-2 receptor inhibitors with different structural properties were used to develop a QSAR model following OECD guidelines. This study selected the best-predicted model (80:20 splitting ratio) with fitting parameters, such as R2:0.78; F:623.6, Internal validation parameters, such as Q2Loo:0.78; CCCcv: 0.87 and external validation parameters, such as R2ext:0.77; Q2F1:0.7730; Q2F2:0.7730; Q2F3:0.76; CCCext:0.87. Following this, another QSAR model was developed by using a 50:50 split ratio for thetraining and the prediction sets, which were then swapped to evaluate the robustness of the built QSAR model by the 50:50 ratio, which also gives a deeper understanding of the chemical space. In addition, we have confirmed the QSAR result with pharmacophore modelling, and supported by molecular docking, MD simulation, MMGBSA and ADME studies. Thus, this work may enable cannabinoid 2 receptor inhibsitor development. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, caused by SARS-CoV-2, emerges as a global health problem, as the viral genome is evolving rapidly to form several variants. Advancement and progress in the development of effective vaccines and neutralizing monoclonal antibodies are promising to combat viral infections. In the current scenario, several lineages containing "co-mutations" in the receptor-binding domain (RBD) region of the spike (S) protein are imposing new challenges. Co-occurrence of some co-mutations includes delta (L452R/T478K), kappa (L452R/E484Q), and a common mutation in both beta and gamma variants (E484K/N501Y). The effect of co-mutants (L452R/E484Q) on human angiotensin-converting enzyme 2 (hACE2) binding has already been elucidated. Here, for the first time, we investigated the role of these RBD co-mutations (L452R/E484Q) on the binding affinity of mAbs by adopting molecular dynamics (MD) simulation and free-energy binding estimation. The results obtained from our study suggest that the structural and dynamic changes introduced by these co-mutations reduce the binding affinity of the viral S protein to monoclonal antibodies (mAbs). The structural changes imposed by L452R create a charged patch near the interfacial surface that alters the affinity towards mAbs. In E484Q mutation, polar negatively charged E484 helps in the formation of electrostatic interaction, while the neutrally charged Q residue affects the interaction by forming repulsive forces. MD simulations along with molecular mechanics-generalized Born surface area (MMGBSA) studies revealed that the REGN 10933, BD-368-2, and S2M11 complexes have reduced binding affinity towards the double-mutant RBD. This indicates that their mutant (MT) structures have a stronger ability to escape from most antibodies than the wild type (WT). However, EY6A Ab showed higher affinity towards the double MT-RBD complex as compared to the WT. However, no significant effect of the per-residue contribution of double-mutated residues was observed, as this mAb does not interact with the region harboring L452 and E484 residues. [ABSTRACT FROM AUTHOR]

• Triple-negative breast cancer (TNBC), is the most aggressive breast cancer subtype, resistant to HER2-targeted and hormonal therapies. • Developed a highly accurate 2D-QSAR model with a regression coefficient (r²) of 0.86 and a cross-validated r² (q²) of 0.8448 to predict IC 50 of triterpene derivatives against TNBC cell line MDA-MB231. • Key molecular descriptors contributing to cytotoxicity against the TNBC MDA-MB231 cell line include electronegativity (Epsilon-3), five-bond carbon separation (T_C_C_5), –CH2 group electrotopological indices (SssCH2count), z-coordinate dipole moment (Zcomp Dipole), and distance between highest positive and negative electrostatic potential on van-der Waals surface area (Most +ve & -ve potential Distance). • Developed an R-package and software tool for virtual screening, available for download on GitHub, aiding in the optimization and development of potent anti-cancer inhibitors against TNBC. Triple-negative breast cancer (TNBC) is the most aggressive cancer type that tests negative for progesterone, estrogen, and HER2 protein receptors. Therefore, TNBC is unlikely to respond either to drugs that target HER2 receptors or to hormonal therapy drugs. In the present study, 2D-QSAR model was developed to predict the inhibitory concentration (IC 50) of terpene derivatives against human breast cancer metastatic cell line MDA-MB231, using V-Life MDS v4.5, module. The model was developed using the forward stepwise multiple linear regression method, with a regression coefficient (r 2) of 0.86, and a cross-validated r 2 (q 2) of 0.8448. Molecular descriptors namely electronegativity (Epsilon-3), carbon atoms separated through five bond distances (T_C_C_5), Sum of Electrotopological state indices of –CH2 group (SssCH2count), Dipole moment of coordinate-z (Zcomp Dipole), and Distance between highest positive and negative electrostatic potential on van-der Waals surface area (Most +ve & -ve Potential Distance) were found to be the most potent contributing chemical descriptors for cytotoxicity against TNBC MDA-MB231 cell line. Additionally, binding affinities and interaction patterns revealed that the proposed compounds exhibit good binding affinities and substantial stability with c-Met-and β-tubulin receptors, as assessed by docking studies. Molecular dynamics simulations (100 ns) and binding free energy calculations were also performed using the MMGBSA method. The pharmacokinetic and eADME/T analysis of predicted compounds were assessed through Discovery Studio software. These findings may be of immense importance in the optimization and development of dual inhibitory potent anti-cancer inhibitors against the MDA-MB231 TNBC cell line. Moreover, this novel QSAR based prediction model/method is implemented in R-package and software tool developed for virtual screening purposes and available online for download through the public repository GitHub. [Display omitted] [ABSTRACT FROM AUTHOR]

There is an urgent need to develop new, safer, and more effective drugs against Chagas disease (CD) as well as related kinetoplastid diseases. Targeting and inhibiting the Trypanosoma cruzi proteasome has emerged as a promising therapeutic approach in this context. To expand the chemical space for this class of inhibitors, we performed virtual screening campaigns with emphasis on shape-based similarity and ADMET prioritization. We describe the ideation and application of robustly validated shape queries for these campaigns, which furnished 44 compounds for biological evaluation. Five hit compounds demonstrated in vitro antitrypanosomal activity by potential inhibition of T. cruzi proteasome and notable chemical diversities, particularly, LCQFTC11. Structural insights were achieved by homology modeling, sequence/structure alignment, proteasome-species comparison, docking, molecular dynamics, and MMGBSA binding affinity estimations. These methods confirmed key interactions as well as the stability of LCQFTC11 at the β4/β5 subunits' binding site of the T. cruzi proteasome, consistent with known inhibitors. Our results warrant future assay confirmation of our hit as a T. cruzi proteasome inhibitor. Importantly, we also shed light into dynamic details for a proteasome inhibition mechanism that shall be further investigated. We expect to contribute to the development of viable CD drug candidates through such a relevant approach. • T. cruzi proteasome inhibition is a promising therapeutic approach for Chagas disease • Shape-based virtual screening to expand the chemical space of T. cruzi proteasome inhibitors • 44 compounds tested in vitro , from which 5 hits showed EC 50 < 50 μM; particularly, LCQFTC11 with EC 50 = 8.15 μM and high SI • Structural analysis by homology model, sequence/structure alignment/comparison, docking, molecular dynamics, and MMGBSA • Hypotheses onto dynamic details for a proteasome inhibition mechanism [ABSTRACT FROM AUTHOR]

A C-terminal fragment of the adhesion protein Fibulin7 (Fbln7-C) binds to monocytes and neutrophils via integrin α5β1, regulating their adhesion and immunological functions through Erk and STAT signaling pathways. It also inhibits cell binding, spreading, and migration on fibronectin. However, the precise structural components of Fbln7-C that interact with various domains of integrin α5β1 and contribute to its regulatory effects are not entirely understood. This study investigated the structural dynamics of Fibulin7 fragments and the mechanisms by which Fbln7-C regulates α5β1 integrin activation using protein modeling, protein-protein docking, molecular dynamics simulation (MDS), and binding free energy calculations. An energy-minimized model of α5β1 integrin, Fibulin7 full length (Fbln7-FL), and Fbln7-C was developed and validated using 100 ns MDS. Additionally, protein-protein docking was used to confirm Fbln7-C's better integrin binding ability over Fbln7-FL. A 500 ns MDS on the docked Fbln7-C integrin complex revealed the regulatory effects of Fbln7-C on arginine-glycine-aspartic acid (RGD) bound integrin α5β1. The simulation studies showed that Fbln7-C's attachment to activated α5β1 integrin increased the distance between the RGD and its interacting residues on both integrin subunits, shifting the RGD ligand from its original binding position and inactivating the integrin. Further analysis using free energy landscape (FEL), principal component analysis (PCA), and binding energy calculation validated the alteration in α5β1 integrin's structural dynamics following Fbln7-C binding. This could relate to obstruction in the outward swing of the integrin's hybrid domain and result in the low-affinity, inactive headpiece conformation of the α5β1 integrin.

The triggering receptor expressed on myeloid cells 2 (TREM2) is an immunoreceptor that interacts with a wide range of non-protein ligands, and it has been implicated in infectious and non-infectious diseases. However, there is a limited understanding on how this receptor interacts with non-protein ligands and the potential of such information to develop new therapeutic drugs. Therefore, our study aimed to elucidate the interactions between TREM2 and its non-protein ligands. First, we searched PubChem and Protein Data Bank (PDB) for TREM2 structures and their corresponding non-protein ligands. Subsequently, these structures were employed in molecular docking and MM/GBSA simulations with the Maestro software and molecular dynamics in GROMACS software. TREM2 was subsequently subjected to druggable site prediction using CavityPlus and receptor-based drug repositioning via the DrugRep server. TREM2 interacts with high affinity with its 12 non-protein ligands, with affinity values ranging from -33.01 kcal/mol for phosphatidylserine to -80.87 kcal/mol for cardiolipin (CLP). In molecular dynamics simulations, homodimeric TREM2 bound more stably to its lipid ligands, such as CLP and PSF, whereas it was unstable when unbound. The interactions between the receptor and its non-protein ligands were driven by the complementarity determining regions (CDR) 1 and 2, that are present in the hydrophobic and positively charged regions, highlighting that the Y38-R98 region is fundamental for drugs targeting TREM2. Our data underscore the significance of TREM2's CDRs in recognizing its ligands, suggesting they as promising targets for prospective drug design studies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Fibroblast Growth Receptor Factor (FGFR) are a family of proteins which are, in addition to their biological role, are involved in various pathological functions, such as cancer cellular proliferation, and metastasis. Deregulation of FGFRs at various points could result in malignancy. A conformational transition of the DFG (Asp-Phe-Gly) motif can switch the enzyme from a catalytically active (DFG-in) to an inactive (DFG-out) state. There are a few FDFR inhibitors which have received approval from the FDA, but these have adverse side effects. Hence, there is a demand for safer alternatives. With this aim, Ligand and Structure based virtual screening was carried to identify suitable lead molecule. In this process, Four Featured atom-based 3D Pharmacophore with quantitative structure-activity relationship analysis (3D-QSAR) was developed. The External validation of the hypothesis was carried invoking criteria such as Area under the ROC curve. Natural plant compound databases such as the Traditional Chinese medicine, NPACT and the ZINC Natural databases were chosen for pharmacophore filtering, which was followed by virtual screening against FGFR isoforms. The compound Sanggenol B was identified as the most suitable lead molecule. Structural stability of the protein-ligand complex and interactions of the ligand (Sanggenol B & the reference compound Ponatinib) with FGFR were analysed for 1000 ns (triplicate) by means of molecular simulation and the binding free energy was calculated using MMGBSA. Sanggenol B (PubChem CID: 15233694) binds effectively at the active site with favourable energies and is proposed as a safe alternative from a natural source.Communicated by Ramaswamy H. Sarma.

The heterodimeric complex between retinoic X receptor alpha (RXRα) and peroxisome proliferator-activated receptor gamma (PPARγ) is one of the most important and predominant regulatory systems, controlling lipid metabolism by binding to specific DNA promoter regions. X-ray and molecular dynamics (MD) simulations have revealed the average conformation adopted by the RXRα-PPARγ heterodimer bound to DNA, providing information about how multiple domains communicate to regulate receptor properties. However, knowledge of the energetic basis of the protein-ligand and protein-protein interactions is still lacking. Here we explore the structural and energetic mechanism of RXRα-PPARγ heterodimer bound or unbound to DNA and forming complex with co-crystallized ligands (rosiglitazone and 9-cis-retinoic acid) through microsecond MD simulations, molecular mechanics generalized Born surface area binding free energy calculations, principal component analysis, the free energy landscape, and correlated motion analysis. Our results suggest that DNA binding alters correlated motions and conformational mobility within RXRα–PPARγ system that impact the dimerization and the binding affinity on both receptors. Intradomain correlated motions denotes a stronger correlation map for RXRα-PPARγ-DNA than RXRα-PPARγ, involving residues at the ligand binding site. In addition, our results also corroborated the greater role of PPARγ in regulation of the free and bound DNA state. [ABSTRACT FROM AUTHOR]

Hypertension has been a significant cause of death due to elevated blood pressure worldwide. The results of molecular docking showed out of selected 40 compounds, chasmanthin (-11.05 kcal/mol), and palmarin (-11.22 kcal/mol) showed strong binding with angiotensin-converting enzyme (ACE) target. The inhibitory action of the selected phytocompounds for ACE protein was also validated by comparing it with the reference drugs, lisinopril (-9.42 kcal/mol), and enalapril (-5.07 kcal/mol). MD simulations study of 100 ns also demonstrated stability of chasmanthin, and palmarin within the active sites of ACE protein. Molecular mechanics generalised born surface area (MMGBSA) analysis of MD trajectories exhibited significant binding of palmarin with ACE (dG Bind= −38.65 ± 2.59 kcal/mol) and chasmanthin (dG Bind= −37.64 ± 2.67 kcal/mol). Drug likeness and pharmacokinetics properties of palmarin and chasmanthin was also found to be permissible, thereby suggesting the use of chasmanthin and palmarin as a novel target inhibitor against ACE protein to combat hypertension. [ABSTRACT FROM AUTHOR]

Poly [adenosine diphosphate (ADP)-ribose] polymerases (PARPs) are members of a family of 17 enzymes that performs several fundamental cellular processes. Aberrant activity (mutation) in PARP12 has been linked to various diseases including inflammation, cardiovascular disease, and cancer. Herein, a large library of compounds (ZINC-FDA database) has been screened virtually to identify potential PARP12 inhibitor(s). The best compounds were selected on the basis of binding affinity scores and poses. Molecular dynamics (MD) simulation and binding free energy calculation (MMGBSA) were carried out to delineate the stability and dynamics of the resulting complexes. To this end, root means deviations, relative fluctuation, atomic gyration, compactness, covariance, residue-residue contact map, and free energy landscapes were studied. These studies have revealed that compounds ZINC03830332, ZINC03830554, and ZINC03831186 are promising agents against mutated PARP12. [ABSTRACT FROM AUTHOR]

ALK tyrosine kinase ALK TK is an important target in the development of anticancer drugs. In the present work, we have performed a QSAR analysis on a dataset of 224 molecules in order to quickly predict anticancer activity on query compounds. Double cross validation assigns an upward plunge to the genetic algorithm–multi linear regression (GA-MLR) based on robust univariate and multivariate QSAR models with high statistical performance reflected in various parameters like, fitting parameters; R2 = 0.69–0.87, F = 403.46–292.11, etc., internal validation parameters; Q2LOO = 0.69–0.86, Q2LMO = 0.69–0.86, CCCcv = 0.82–0.93, etc., or external validation parameters Q2F1 = 0.64–0.82, Q2F2 = 0.63–0.82, Q2F3 = 0.65–0.81, R2ext = 0.65–0.83 including RMSEtr < RMSEcv. The present QSAR evaluation successfully identified certain distinct structural features responsible for ALK TK inhibitory potency, such as planar Nitrogen within four bonds from the Nitrogen atom, Fluorine atom within five bonds beside the non-ring Oxygen atom, lipophilic atoms within two bonds from the ring Carbon atoms. Molecular docking, MD simulation, and MMGBSA computation results are in consensus with and complementary to the QSAR evaluations. As a result, the current study assists medicinal chemists in prioritizing compounds for experimental detection of anticancer activity, as well as their optimization towards more potent ALK tyrosine kinase inhibitor. [ABSTRACT FROM AUTHOR]

Naltrexone is a potent opioid antagonist with good blood–brain barrier permeability, targeting different endogenous opioid receptors, particularly the mu-opioid receptor (MOR). Therefore, it represents a promising candidate for drug development against drug addiction. However, the details of the molecular interactions of naltrexone and its derivatives with MOR are not fully understood, hindering ligand-based drug discovery. In the present study, taking advantage of the high-resolution X-ray crystal structure of the murine MOR (mMOR), we constructed a homology model of the human MOR (hMOR). A solvated phospholipid bilayer was built around the hMOR and submitted to microsecond (µs) molecular dynamics (MD) simulations to obtain an optimized hMOR model. Naltrexone and its derivatives were docked into the optimized hMOR model and submitted to µs MD simulations in an aqueous membrane system. The MD simulation results were submitted to the molecular mechanics–generalized Born surface area (MMGBSA) binding free energy calculations and principal component analysis. Our results revealed that naltrexone and its derivatives showed differences in protein–ligand interactions; however, they shared contacts with residues at TM2, TM3, H6, and TM7. The binding free energy and principal component analysis revealed the structural and energetic effects responsible for the higher potency of naltrexone compared to its derivatives. [ABSTRACT FROM AUTHOR]

Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm–multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R2 = 0.83–0.81, F = 61.22–67.96, internal validation parameters such as Q2LOO = 0.79–0.77, Q2LMO = 0.78–0.76, CCCcv = 0.89–0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound's binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads. [ABSTRACT FROM AUTHOR]

Background. Dengue and Zika are two major vector-borne diseases. Dengue causes up to 25,000 deaths and nearly a 100 million cases worldwide per year, while the incidence of Zika has increased in recent years. Although Zika has been associated to fetal microcephaly and Guillain-Barré syndrome both it and dengue have common clinical symptoms such as severe headache, retroocular pain, muscle and join pain, nausea, vomiting, and rash. Currently, vaccines have been designed and antivirals have been identified for these diseases but there still need for more options for treatment. Our group previously obtained some fractions from medicinal plants that blocked dengue virus (DENV) infection in vitro. In the present work, we explored the possible targets by molecular docking a group of molecules contained in the plant fractions against DENV and Zika virus (ZIKV) NS3-helicase (NS3-hel) and NS3-protease (NS3-pro) structures. Finally, the best ligands were evaluated by molecular dynamic simulations. Methods. To establish if these molecules could act as wide spectrum inhibitors, we used structures from four DENV serotypes and from ZIKV. ADFR 1.2 rc1 software was used for docking analysis; subsequently molecular dynamics analysis was carried out using AMBER20. Results. Docking suggested that 3,5-dicaffeoylquinic acid (DCA01), quercetin 3-rutinoside (QNR05) and quercetin 3,7-diglucoside (QND10) can tightly bind to both NS3-hel and NS3-pro. However, after a molecular dynamics analysis, tight binding was not maintained for NS3-hel. In contrast, NS3-pro from two dengue serotypes, DENV3 and DENV4, retained both QNR05 and QND10 which converged near the catalytic site. After the molecular dynamics analysis, both ligands presented a stable trajectory over time, in contrast to DCA01. These findings allowed us to work on the design of a molecule called MOD10, using the QND10 skeleton to improve the interaction in the active site of the NS3-pro domain, which was verified through molecular dynamics simulation, turning out to be better than QNR05 and QND10, both in interaction and in the trajectory. Discussion. Our results suggests that NS3-hel RNA empty binding site is not a good target for drug design as the binding site located through docking is too big. However, our results indicate that QNR05 and QND10 could block NS3-pro activity inDENVand ZIKV. In the interaction with these molecules, the sub-pocket-2 remained unoccupied in NS3-pro, leaving opportunity for improvement and drug design using the quercetin scaffold. The analysis of the NS3-pro in complex with MOD10 show a molecule that exerts contact with sub-pockets S1, S1', S2 and S3, increasing its affinity and apparent stability on NS3-pro. [ABSTRACT FROM AUTHOR]

SARS-CoV-2, the virus that caused the widespread COVID-19 pandemic, is homologous to SARS-CoV. It would be ideal to develop antivirals effective against SARS-CoV-2. In this study, we chose one therapeutic target known as the main protease (Mpro) of SARS-CoV-2. A crystal structure (Id: 6LU7) from the protein data bank (PDB) was used to accomplish the screening and docking studies. A set of phytocompounds was used for the docking investigation. The nature of the interaction and the interacting residues indicated the molecular properties that are essential for significant affinity. Six compounds were selected, based on the docking as well as the MM-GBSA score. Pentagalloylglucose, Shephagenin, Isoacteoside, Isoquercitrin, Kappa-Carrageenan, and Dolabellin are the six compounds with the lowest binding energies (−12 to −8 kcal/mol) and show significant interactions with the target Mpro protein. The MMGBSA scores of these compounds are highly promising, and they should be investigated to determine their potential as Mpro inhibitors, beneficial for COVID-19 treatment. In this study, we highlight the crucial role of in silico technologies in the search for novel therapeutic components. Computational biology, combined with structural biology, makes drug discovery studies more rigorous and reliable, and it creates a scenario where researchers can use existing drug components to discover new roles as modulators or inhibitors for various therapeutic targets. This study demonstrated that computational analyses can yield promising findings in the search for potential drug components. This work demonstrated the significance of increasing in silico and wetlab research to generate improved structure-based medicines. [ABSTRACT FROM AUTHOR]