Geo-Measures: A PyMOL plugin for protein structure ensembles analysis

Exploration of comprehensive marine natural products database against dengue viral non-structural protein 1 using high-throughput computational studies

Dengue virus (DENV) non-structural protein 1 (NS1) is a versatile quasi-protein essential for the multiplication of the virus. This study applied high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulation to detect the potential marine natural compounds against the NS1 of DENV. The structure of the NS1 protein was retrieved from Protein Data Bank with (PDB ID: 4O6B). Missing residues were added using modeler software. Molecular operating environment (MOE) programme was used to prepare the protein before docking. Virtual screening was performed on PyRx software to identify natural compounds retrieved from Comprehensive Marine Natural Products Database (CMNPD) against the NS1 protein, and best-docked compounds were examined by molecular docking and molecular dynamic (MD) simulation. Out of 31,561 marine compounds, the top 10 compounds showed docking scores lesser than -8.0 kcal/mol. One of the best hit compounds, CMNPD6802, was further analyzed using MD simulation study at 100 nanoseconds and Molecular Mechanics with Generalized Born and Surface Area Solvation (MM/GBSA). Based on its total binding energy, determined using the MM/GBSA approach, CMNPD6802 was ranked first. Its pharmacokinetic properties concerning the target protein NS1 were also evaluated. The results of the MD simulation showed that CMNPD6802 remained in close contact with the protein throughout the activation period, mapped using principal component analysis. These findings suggest that CMNPD6802 could serve as an NS1 inhibitor and may be a potential candidate for treating DENV infections.

Ligand-based cheminformatics and free energy-inspired molecular simulations for prioritizing and optimizing G-protein coupled receptor kinase-6 (GRK6) inhibitors in multiple myeloma treatment

Multiple myeloma (MM) is the second most frequently diagnosed hematological malignancy, presenting limited treatment options with no curative potential and significant drug resistance. Recent studies involving genetic knockdown established the crucial role of GRK6 in upholding the viability of MM cells, emphasizing the need to identify potential inhibitors. Computational exploration of GRK6 inhibitors has not been attempted previously. Herein, the present study reports a multilayered lead prioritization and optimization framework using chemometrics and molecular simulations. 2D QSAR studies revealed that hydrogen bonding and polar interactions enhanced GRK6 inhibitory activity, while increased electron accessibility posed a risk of off-target effects. The pharmacophore hypothesis (DDHRRR_1) featured two hydrogen bond donors, one hydrophobic region, and three aromatic rings, laying the foundation for the 3D QSAR models. Hydrophobic groups, such as pyridine and pyrazole, were shown to enhance inhibition, while smaller groups, like ethyl and hydroxyl, reduced activity. 12,557 DrugBank compounds were screened using the developed chemometric models and molecular docking in tandem, which led to the identification of 7 potential parent leads for subsequent QSAR-guided structural optimizations. 350 lead analogs were generated and the top 4 were further analyzed using molecular docking, ADMET, molecular dynamics, and metadynamics analysis based on Principal Component Analysis (PCA), Probability Density Function (PDF), and Free Energy Landscapes (FEL). Upon cumulative retrospection, we propose a novel analog of DB07168 (DB07168-A13) (docking score: -11.2 kcal/mol, MM-GBSA binding energy: -55.2 kcal/mol) as the most promising GRK6 inhibitor, warranting further in vitro validation, for addressing prospective therapeutic intervention in MM.

Identification of novel influenza virus H3N2 nucleoprotein inhibitors using most promising epicatechin derivatives

Influenza A virus is a leading cause of acute respiratory tract infections, posing a significant global health threat. Current treatment options are limited and increasingly ineffective due to viral mutations. This study aimed to identify potential drug candidates targeting the nucleoprotein of the H3N2 subtype of Influenza A virus. We focused on epicatechin derivatives and employed a series of computational approaches, including ADMET profiling, drug-likeness evaluation, PASS predictions, molecular docking, molecular dynamics simulations, Principal Component Analysis (PCA), dynamic cross-correlation matrix (DCCM) analyses, and free energy landscape assessments. Molecular docking and dynamics simulations revealed strong and stable binding interactions between the derivatives and the target protein, with complexes 01 and 81 exhibiting the highest binding affinities. Additionally, ADMET profiling indicated favorable pharmacokinetic properties for these compounds, supporting their potential as effective antiviral agents. Compound 81 demonstrated exceptional quantum chemical descriptors, including a small HOMO-LUMO energy gap, high electronegativity, and significant softness, suggesting high chemical reactivity and strong electron-accepting capabilities. These properties enhance Compound 81's potential to interact effectively with the H3N2 nucleoprotein. Experimental validation is strongly recommended to advance these compounds toward the development of novel antiviral therapies to address the global threat of influenza.

A combined ligand-based and structure-based in silico molecular modeling approach to pinpoint the key structural attributes of hydroxamate derivatives as promising meprin β inhibitors

Human meprin β is a Zn2+-containing multidomain metalloprotease enzyme that belongs to the astacin family of the metzincin endopeptidase superfamily. Meprin β, with its diverse tissue expression pattern and wide substrate specificity, plays a significant role in various biological processes, including regulation of IL-6R pathways, lung fibrosis, collagen deposition, cellular migration, neurotoxic amyloid β levels, and inflammation. Again, meprin β is involved in Alzheimer's disease, hyperkeratosis, glomerulonephritis, diabetic kidney injury, inflammatory bowel disease, and cancer. Despite a crucial role in diverse disease processes, no such promising inhibitors of meprin β are marketed to date. Thus, it is an unmet requirement to find novel promising meprin β inhibitors that hold promise as potential therapeutics. In this study, a series of arylsulfonamide and tertiary amine-based hydroxamate derivatives as meprin β inhibitors has been analyzed through ligand-based and structure-based in silico approaches to pinpoint their structural and physiochemical requirements crucial for exerting higher inhibitory potential. This study identified different crucial structural features such as arylcarboxylic acid, sulfonamide, and arylsulfonamide moieties, as well as hydrogen bond donor and hydrophobicity, inevitable for exerting higher meprin β inhibition, providing valuable insight for their further future development.

The role of weak interactions in evaluation of inhibitory potential of Indinavir as an HIV protease inhibitor and its comparison with innovative drug candidates

Designing and employing enzyme inhibitors against viral enzymes is one of the innovative and efficient approaches to treating viral diseases. These inhibitors can disrupt the viral replication cycle by deactivating vital enzymes, thereby curbing the spread of viral infections by reducing their population. So far, inhibitors have been designed, validated, and introduced for these enzymes. In this study, we designed the drug Indinavir and 20 analogs using Hartree-Fock and DFT methods to enhance the design of more potent protease enzyme inhibitors. Frequency calculations were performed at similar computational levels for all examined drugs and their designed analogs, revealing no negative frequencies. The Pharmacokinetics of the inhibitors were assessed, and inhibitors were screened, with those exhibiting minimal toxicity introduced as drug candidates for further evaluation. The best binding mode of Indinavir and the designed drugs at the protein binding site were determined using molecular docking studies. For the IND20 inhibitor with the best binding mode, an energy of -13.03 (kcal/mol) was reported. Finally, molecular dynamics simulations were conducted to evaluate the inhibitory mechanism of the recommended inhibitor on the protease enzyme. The relevant analyses during the simulation period showed that the designed drug IND20 exhibited better performance in inhibiting the HIV-1 protease enzyme compared to Indinavir.

Computational insights into DC-SIGN's enhanced recognition of mannotriose CPS units via Ca2+ ion cross-talk

The Carbohydrate Recognition Domain (CRD) of immune system's c-type lectin receptors (CLRs) preferentially interacts with the Capsular Polysaccharides (CPS) units. Implicit Ca2+ ions are crucial to CRD function. Increment of the ionic concentration explicitly affects the CPS recognition by CRD many-fold. DC-SIGN is one such CLR that acts for the differential recognition of the microbial CPS. The CPS mannotriose had the lowest binding energy (ΔG -4.7 kcal/mol) and the maximum affinity for DC-SIGN with implicit Ca2+ ion. In the present investigation the ligand affinity increases with the rise of Ca2+ concentration up to 1.5 M. Again, within the CRD the residues viz; Glutamate (347), Proline (348), and Asparagine (349) (EPN) were reported previously as essential for CPS unit coordination. Our analysis demonstrated that besides the EPN residues, CPS unit interacts with the neighboring Asparagine (350), Glutamate (354) and Asparagine (355) residues. Thus, these residues were replaced one at a time with Alanine (a charge neutral residue) to test their effect on the contact event. The CRD loses its affinity for recognition on the N350A, E354A, and D355A substitutions. Thus, this heterogeneity of CRD recognition towards Carbohydrate provides fresh information about the immune system's theragnostic function. This new understanding of Ca2+-induced recognition may help design new theragnostic applications that boost our immune defenses against pathogenic evasion.

Selection and identification of DNA aptamer binding VDAC1 for tumor tissue imaging and targeted drug delivery

Hepatocellular carcinoma (HCC) represents a significant health concern. Identifying novel molecular targets is crucial for clinical diagnosis and targeted treatment of HCC. Aptamers are capable of binding specifically to cancer cells via target protein molecules. Consequently, aptamers are frequently employed to identify novel cancer biomarkers. The invasiveness of tumor cells is closely associated with the recurrence and metastasis of tumors. In this study, the highly invasive Huh7-P3 cells were initially constructed, and subsequently, several aptamers that could specifically recognize Huh7-P3 were developed using cell-based Systematic Evolution of Ligands by Exponential Enrichment (SELEX). The selected aptamer, designated S2-2, demonstrated the capacity to bind to multiple cancer cells. Furthermore, tissue imaging demonstrated that S2-2 exhibited a specific recognition of HCC tissue, while demonstrating no binding to normal tissue. Subsequently, voltage-dependent anion channel 1 (VDAC1) was identified as a potential target for S2-2. Furthermore, Doxorubicin (Dox)-loaded S2-2 was shown to specifically kill target Huh7-P3 cells. In vivo fluorescence imaging revealed that S2-2 was capable of specifically targeting tumors. Importantly, S2-2-Dox enhanced the anti-tumor efficacy of Dox in CDX model. This study may provide a promising biomarker and molecular target for the clinical diagnosis and targeted therapy of cancers with high VDAC1 expression.

CADD-based discovery of novel oligomeric modulators of PKM2 with antitumor activity in aggressive human glioblastoma models

Pyruvate kinase isoform M2 (PKM2) is a multifunctional enzyme capable of transitioning between monomeric, dimeric, and tetrameric states, with its oligomeric equilibrium playing a pivotal role in tumour progression and survival. The unique exon ten at the dimer-dimer interface represents an attractive target for isoform-specific modulation, offering opportunities for disrupting this equilibrium and altering tumour cell dynamics. This study identifies a novel druggable pocket at the PKM2 dimer interface through conformational analysis. This pocket was exploited in a virtual screening of a large small-molecule library, identifying two promising candidates, C599 and C998. Both compounds exhibited dose-dependent antiproliferative effects in glioblastoma cell lines and induced apoptosis, as evidenced by caspase 3/7 activation. These effects were directly linked to their inhibition of PKM2 enzymatic activity, validating the proposed mechanism of action in their rational design. ADMET studies further highlighted their strong potential as lead PKM2 inhibitors for GBM treatment. Molecular dynamics (MD) simulations and post-MD analyses, including Dynamic Cross-Correlation Maps (DCCM), Probability Density Function (PDF), and Free Energy Landscape (FEL), confirmed the stability of the protein-ligand interactions and highlighted critical residues at the dimer-dimer interface. The Steered MD simulations demonstrated the high affinity of the compounds for PKM2, as evidenced by the requirement of high rupture forces to induce an unbinding event. These results highlight the potential of the compounds as oligomeric modulators of PKM2. These findings position C599 and C998 as promising lead compounds for antitumor applications. Future studies will focus on optimising these candidates and assessing their efficacy in vivo glioblastoma models, reassuring the thoroughness of our research and the potential for further advancements.

Effect of cubebin against streptozotocin-induced diabetic nephropathy rats via inhibition TNF-α/NF-κB/TGF-β: in vivo and in silico study

Cubebin, a dibenzyl butyrolactone lignan belonging to several distinct families, including Aristolochiaceae, Myristicaceae, Piperaceae, and Rutaceae, and possesses several pharmacological activities, including analgesic, anti-inflammatory, antioxidant, and vasodilatory. The current study aimed to evaluate the effect of cubebin on streptozotocin (STZ)-evoked diabetic nephropathy (DN). DN is a well-identified complication of diabetes mellitus (DM) characterized by renal hypertrophy that progressively declines kidney function. Wistar rats were randomly divided into groups- normal, STZ control (65 mg/kg/body weight), and STZ + cubebin (10 and 20 mg/kg). Biochemical parameters such as glucose levels, kidney parameters, lipid profile, oxidative stress, endogenous antioxidant markers, inflammatory cytokines and histopathology were performed. Molecular docking [(PDB ID: TNF-α (7JRA), NF-κB (1SVC), TGF-β1 (3TZM)] and dynamic simulation (MDS) were also performed with the selected target. STZ-induced DN was changes in these parameters. In contrast, DN + cubebin at 10 and 20 mg/kg doses improved the biochemical parameters and histological changes. Furthermore, molecular docking and simulation studies showed a binding affinity with negative binding energy with TNF-α (7jra, - 11.342 kcal/mol), TGF-β1 (3tzm, - 9.162 kcal/mol) and NF-κB (1svc, - 6.665 kcal/mol). The results of MDS provided insight into the mechanisms that associate proteins TNF-α, NF-κB, and TGF-β1 in conformational dynamics upon binding to cubebin. In conclusion, these findings exhibit a potential effect of cubebin in STZ-evoked DN rats.

Exploring Echinacea angustifolia for anti-viral compounds against Zika virus RNA-dependent RNA polymerase: a computational study

The Zika virus (ZIKV), a member of the Flaviviridae family, has caused multiple widespread outbreaks, posing significant challenges to global health. This study explores the potential of compounds from Echinacea angustifolia (E. angustifolia) to inhibit the activity of ZIKV's RNA-dependent RNA polymerase (RDRP), a key enzyme in the viral replication process and an ideal candidate for antiviral therapy. Utilizing computational techniques, we conducted a thorough virtual examination using the MTi-OpenScreen tool to identify potential RDRP inhibitors among E. angustifolia compounds. The top four compounds were further examined through re-docking procedures. To assess the robustness and effectiveness of these interactions, we performed molecular dynamics simulations along with calculations of the binding free energy and PCA analysis. This investigation highlighted four naturally occurring compounds, viz., Echinacoside, Rutin, Echinacin, and Cynaroside, demonstrating a notable affinity for binding to the allosteric site of ZIKV RDRP. These compounds showed strong hydrogen bond formation with crucial residues of the RDRP and presented favorable binding free energies. Our research sheds light on the viability of these E. angustifolia compounds as ZIKV RDRP inhibitors, laying a foundation for further experimental research in developing novel antiviral treatments against ZIKV infections.

Investigating Pb2 CAP-binding domain inhibitors from marine bacteria for targeting the influenza A H5N1

The ongoing increase in the prevalence and mutation rate of the influenza virus remains a critical global health issue. A promising strategy for antiviral drug development involves targeting the RNA-dependent RNA polymerase, specifically the PB2-cap binding domain of Influenza A H5N1. This study employs an in-silico approach to inhibit this domain, crucial for viral replication, using potential inhibitors derived from marine bacterial compounds. Utilizing the MTi-OpenScreen web server, we screened a library of compounds to assess their molecular interactions with the target. This process identified four potential inhibitors: CMNPD25830, CMNPD18675, CMNPD18676, and CMNPD27216. Subsequent molecular dynamics simulations, conducted using the Amber software suite, evaluated their binding affinities and dynamic interactions with the PB2 protein. Notably, CMNPD25830 and CMNPD27216 emerged as the most promising candidates, exhibiting higher binding affinities and more favourable interaction profiles compared to the control molecule. Additional analyses, including post-simulation free energy calculations and free energy landscape analysis, strengthened the potential of these compounds as effective PB2-cap binding domain inhibitors. This comprehensive computational investigation identifies CMNPD27216 and CMNPD25830 as standout candidates due to their superior binding energies and dynamic stability, suggesting their strong potential as therapeutic agents against influenza. This research sets the stage for further in vitro validation and optimization of these lead compounds, potentially supporting the development of more effective influenza treatments.

Structural dynamic investigation of Wnt signalling activation through Co-receptor LRP6

Cancer sparks if the components of the cellular signaling network are aberrantly activated, leading to uncontrolled cell growth and proliferation. One of the most important players of this highly regulated network is the Wnt/β-catenin signaling, with a significant role in human health and disease. The critical co-receptor of this pathway, LRP6, is overexpressed in various cancer types and is a target for therapy. Therefore, understanding the details of the LRP6 structural activation mechanism is of tremendous importance. This research intended to compare the structural-dynamics features of the E3E4 functional domain of LRP6 induced by the activator Wnt3a and the inhibitor, Dkk1_C, compared with the receptor behavior in the apo-state. Using molecular docking, molecular dynamics simulation, and G_MMPBSA calculation, we characterized overlapping binding regions of Wnt3a and Dkk1_C on E3E4. Despite their overall similar interacting regions, Dkk1_C and Wnt induce remarkably different inter-blades hydrogen bonds, structural-dynamics behavior, and conformational energy landscape in E3E4. According to our findings, Dkk1_C stabilized the interaction. between BP3 blades 2-3, 3-4, and 4-5 and BP4 blades 1-6, 1-2, 2-3, and 3-4, aligned with apo-state. However, on the other hand, Wnt distinguishably destabilized the hydrogen bond networks of these blades. Our DCCM analysis also depicted a similar correlation pattern of apo and Dkk1-bound states, and dramatic differences in Wnt-bound state, with a specific enhancement of correlated movements in EGF4. These data provide atomistic-level clues of how natural regulators of Wnt signaling manipulate LRP6 dynamics and, therefore, guide the structure-based design of efficient artificial inhibitors/activators for the pathway.

Integrating machine learning and structural dynamics to explore B-cell lymphoma-2 inhibitors for chronic lymphocytic leukemia therapy

Chronic lymphocytic leukemia (CLL) is a malignancy caused by the overexpression of the anti-apoptotic protein B-cell lymphoma-2 (BCL-2), making it a critical therapeutic target. This study integrates computational screening, molecular docking, and molecular dynamics to identify and validate novel BCL-2 inhibitors from the ChEMBL database. Starting with 836 BCL-2 inhibitors, we performed ADME and Lipinski's Rule of Five (RO5) filtering, clustering, maximum common substructure (MCS) analysis, and machine learning models (Random Forest, SVM, and ANN), yielding a refined set of 124 compounds. Among these, 13 compounds within the most common substructure (MCS1) cluster showed promising features and were prioritized. A docking-based re-evaluation highlighted four lead compounds-ChEMBL464268, ChEMBL480009, ChEMBL464440, and ChEMBL518858-exhibiting notable binding affinities. Although a reference molecule outperformed in docking, molecular dynamics (MD), and binding energy analyses, it failed ADME and Lipinski criteria, unlike the selected leads. Further validation through MD simulations and MM/GBSA energy calculations confirmed stable binding interactions for the leads, with ChEMBL464268 showing the highest stability and binding affinity (ΔGtotal = - 80.35 ± 11.51 kcal/mol). Free energy landscape (FEL) analysis revealed stable energy minima for these complexes, underscoring conformational stability. Despite moderate activity (pIC₅₀ values from 4.3 to 5.82), the favorable pharmacokinetic profiles of these compounds position them as promising BCL-2 inhibitor leads, with ChEMBL464268 emerging as the most promising candidate for further CLL therapeutic development.

Microsporidian Nosema bombycis secretes serine protease inhibitor to suppress host cell apoptosis via Caspase BmICE

Microsporidia are a group of intracellular pathogens that actively manipulate host cell biological processes to facilitate their intracellular niche. Apoptosis is an important defense mechanism by which host cell control intracellular pathogens. Microsporidia modulating host cell apoptosis has been reported previously, however the molecular mechanism is not yet clear. In this report, we describe that the microsporidia Nosema bombycis inhibits apoptosis of Bombyx mori cells through a secreted protein NbSPN14, which is a serine protease inhibitor (Serpin). An immunofluorescent assay demonstrated that upon infection with N. bombycis, NbSPN14 was initially found in the B. mori cell cytoplasm and then became enriched in the host cell nucleus. Overexpression and RNA-interference (RNAi) of NbSPN14 in B. mori' embryo cell confirmed that NbSPN14 inhibited host cells apoptosis. Immunofluorescent and Co-IP assays verified the co-localization and interaction of NbSPN14 with the BmICE, the Caspase 3 homolog in B. mori. Knocking out of BmICE or mutating the BmICE-interacting P1 site of NbSPN14, eliminated the localization of NbSPN14 into the host nucleus and prevented the apoptosis-inhibiting effect of NbSPN14, which also proved that the interaction between BmICE and NbSPN14 occurred in host cytoplasm and the NbSPN14 translocation into host cell nucleus depends on BmICE. These data elucidate that N. bombycis secretory protein NbSPN14 inhibits host cell apoptosis by directly inhibiting the Caspase protease BmICE, which provides an important insight for understanding pathogen-host interactions and a potential therapeutic target for N. bombycis proliferation.

Potential VEGFR2 inhibitors for managing metastatic cervical cancer: insights from molecular dynamics and free energy landscape studies

Metastatic cervical cancer, the advanced stage where the cancer spreads beyond the cervix to other parts of the body, poses significant treatment challenges and is associated with poor survival rates. Vascular Endothelial Growth Factor Receptor 2 (VEGFR2), a critical angiogenic mediator, is upregulated in metastatic cervical cancer, driving the formation of new blood vessels that fuel tumor growth and spread, making it an attractive target for anti-angiogenic therapies aimed at halting metastasis. This study aims to determine the anti-angiogenic effects of natural compounds to identify new VEGFR2 inhibitors for managing metastatic cervical cancer. The potential effect of these compounds as VEGFR2 inhibitors at the structural level was assessed using various methods such as virtual screening, docking, MD simulations (1000 ns), binding free energy calculations, and free energy landscape analysis. Four compounds, including IMPHY007574, IMPHY004129, IMPHY008783, and IMPHY004928, were found to be potential VEGFR2 inhibitors. Among the structures analyzed in the present work, IMPHY007574 revealed the highest binding stability with VEGFR2 and the most favorable interaction pattern, thus proving the possibility of its use as an effective anti-angiogenic compound. The other three compounds also demonstrated a reasonably good promise in VEGFR2 inhibition. These findings provide a foundation for developing novel therapeutic strategies for metastatic cervical cancer, potentially overcoming drug resistance and improving patient survival rates.

Identification of phytomolecules as isoform and mutation specific PI3K-α inhibitor for protection against breast cancer using e-pharmacophore modeling and molecular dynamics simulations

PI3K-α mutation plays a critical role in cancer development, notably in breast cancer, particularly within HR + /HER2- subtypes. These mutations drive tumor growth and survival by activating the PI3K/AKT/mTOR pathway, which is essential for cell proliferation and survival. Our research aimed to identify natural compounds that can inhibit mutant and specific isoforms of PI3K-α to prevent tumor progression. e-Pharmacophore model was generated using Receptor-Ligand complex using the Inavolisib drug (PDB:8EXV) and phase screening was performed using the Molport database of natural compounds. Through molecular docking studies we identified seven promising compounds for further molecular dynamics simulations. Among these, three compounds-STOCK1N-85097, STOCK1N-85998, and STOCK1N-86060-showed significant stability and interaction with PI3K-α. These compounds demonstrated favorable results in several parameters, including RMSD, RMSF, Rg, SASA, PCA, FEL, and total energy evaluations. Therefore, these compounds are projected to function as PI3K-α inhibitors and because of its natural origin it can possess fewer side effects than the conventional medicine, which should be validated by proper in vivo and in vitro models.

Exploring the key structural attributes and chemico-biological interactions of pyridinone-based SARS-CoV-2 3CLpro inhibitors through validated structure-based drug design strategies

The global outbreak of COVID-19 infection is the first pandemic the world has experienced in this 21st century. The novel coronavirus 2019 (nCoV-19) also called the SARS-CoV-2 is the reason behind the severe acute respiratory syndrome (SARS) that led to this worldwide crisis. In this current post-pandemic situation, despite having effective vaccines, the paucity of orally administrable drug molecules for such infections is a major drawback in this current scenario. Among the different viral enzymes, the SARS-CoV-2 3CLpro is an encouraging target for effective drug discovery and development. In this context, the understanding of the requirements of the small molecules at the active site and their interactions is a crucial aspect of such drug candidate development. Here in this study, structure-based pharmacophore model development and molecular docking-dependent 2D-interaction-based and 3D-field-based QSAR studies have been carried out for a set of potential SARS-CoV-2 3CLpro inhibitors. This study exposed the importance of interactions with amino acids of the active site (such as Leu167 and Gln189 amino acid residues) as well as the importance of hydrogen bond acceptor groups at the S2 and S1' pockets. The presence of hydrophobic aromatic features as well as hydrophobic contacts at the S1 and S4 pockets were also found to have a key contribution to the SARS-CoV-2 3CLpro inhibition. Moreover, the screened drug candidate Elobixibat from the structure-based virtual screening also explored promising results as evidenced in MD simulation study and thus, can be a promising drug candidate that can be repurposed to assist in the development of effective anti-SARS-CoV-2 therapy.

Unraveling the potential of Epicatechin gallate from crataegus oxyacantha in targeting aberrant cardiac Ca2+ signalling proteins: an in-depth in-silico investigation for heart failure therapy

The cardiovascular sarcoplasmic reticulum (SR) calcium (Ca2+) ATPase is an imperative determinant of cardiac functionality. In addition, anomalies in Ca2+ handling protein and atypical energy metabolism are inherent in heart failure (HF). Moreover, Ca2+ overload in SR leads to mitochondrial matrix Ca2+ overload, which can trigger the generation of Reactive Oxygen Species (ROS), culminating in the triggering of the Permeability Transition Pore (PTP) and Cytochrome C release, resulting in apoptosis that leads to arrhythmias and numerous disorders. Although proteins involved in the molecular mechanism of Ca2+ dysfunction regarding mitochondrial dysfunction remains elusive, this study aims to assess the major Ca2+ handling proteins which may be involved in the Ca2+ malfunction that causes mitochondrial dysfunction and predicting the most effective drug by targeting the analyzed Ca2+ handling proteins through various insilico analyses. Thirteen proteins absorbed from interaction analysis were docked with four optimal phytochemicals from Crataegus oxyacantha (COC). Furthermore, The ADME profile of tyramine, vitexin, Epicatechin, and Epicatechin gallate was acclimated to evaluate potential drugability utilizing QikProp. So, molecular docking evaluations were performed using Glide (Maestro), autodock, and vina. Based on the results of 156 dockings by Maestro, auto-dock, and auto-dock vina, PKAC-a with Epicatechin gallate exhibits good interaction. Therefore, a 2000 ns molecular dynamics (MD) simulation was utilized to assess the feasible phytochemical Epicatechin gallate - PKAC-a complex binding stability utilizing Desmond and this study confirmed that Epicatechin gallate from COC has high possibilities to inhibit the aberrant cardiac Ca2+ signaling proteins due to its conformational rigidity.

Targeting Nudix Hydrolase 5 with Bioactive Flavonoids: Molecular Dynamics and Docking Studies for Breast Cancer Therapy

Breast cancer (BC) is the most prevalent malignancy among women globally and the leading cause of cancer-related mortality. Consequently, there is an urgent need for new, effective treatment strategies for breast cancer. Research has shown that the enzyme nudix hydrolase 5 (NUDT5) plays a critical role in promoting breast cancer aggressiveness and serves as a key regulator of oncogenic pathways. The development of NUDT5 inhibitors presents a viable strategy for enhancing treatment results in managing BC. The ability of the flavonoids to modulate key biochemical pathways and improve therapeutic outcomes highlights their promise in developing novel breast cancer treatments. Hence, the main objective of the present investigation is to identify the potential interaction of structurally diverse bioactive flavonoids with the active site of the target NUDT5. Our docking analysis revealed that the flavonoids such as naringin and genistein have shown a significant binding association with residues Arg51, Asp60, Gln82, Arg84, Ala96, Leu98, Glu112, Glu116, Met132, Cys139, Ile141, and Glu166 of NUDT5, suggesting its potential as a potent inhibitor. The stabilizing effects of these leads (naringin and genistein) were further validated using molecular dynamics investigations, including RMSD, RMRF, Rg, SASA, PCA, and FEL. The results of the MD simulation studies evidenced a more significant interaction between genistein and NUDT5, indicating a steady and robust affinity, making genistein a more promising inhibitor. In conclusion, the flavonoid genistein has a strong potential as a therapeutic agent for targeting NUDT5 in breast cancer treatment making it viable candidates for further preclinical and clinical investigations.

An Integrated Approach to Develop a Potent Vaccine Candidate Construct Against Prostate Cancer by Utilizing Machine Learning and Bioinformatics

BACKGROUND

Prostate cancer is the most common malignancy among males. Prostaglandin G/H synthase (PGHS) is an essential enzyme in the synthesis of prostaglandins, and its activation has been linked to many malignancies, including colorectal cancer.

AIMS

Due to the limited effectiveness and specificity of existing prostate cancer therapies, this study was designed to formulate improved treatment techniques.

METHODS

Several immunoinformatic, reverse vaccinology, and molecular modeling methodologies were used to discover B- and T-cell epitopes for the glioblastoma multiforme tumor PGH2_HUMAN. This research evaluated Prostaglandin G/H synthase 2 protein as a potential vaccine candidate against the malignancy. The multi-epitope vaccine architecture is engineered to activate the immune system, with each epitope docked to its respective HLAs. Further, MD simulations analysis was performed to validate the findings.

RESULTS

A multi-epitope subunit vaccine candidate was developed by concatenating the chosen B- and T-cell epitopes. Results yield a codon adaptive index (CAI) of 0.93 and a GC content of 56.77%. Thus, it conforms to a biological requirement for effective protein expression, suggesting competent vaccine efficacy inside the Escherichia coli system. Significant interleukin and cytokine responses were seen, characterized by elevated levels of IL-2 and IFN-γ in the immune system's response to the immunization. Molecular docking demonstrated an efficient binding affinity of -278 kcal/mol, with hydrogen bonding to several residues. Furthermore, the system total root mean square deviation (RMSD) reached 3.23 Å, with a maximum of up to 5.0 Å at the 100 ns time point but remains stable till 400 ns time intervals followed by stable root mean square fluctuation (RMSF) and radius of gyration values. The hydrogen bond cloud residues are the critical sites that significantly influence the binding energies of MMPBSA and MMGBSA via substantial van der Waals interactions.

CONCLUSION

It has been determined that these in silico analyses will further augment the comprehension necessary for advancing the creation of targeted therapies for chemotherapeutic cancer treatments.

Phosphorylation at the D56 residue of MtrA in Mycobacterium tuberculosis enhances its DNA binding affinity by modulating inter-domain interaction

The response regulator, MtrA, plays a major role in adaptation to the host environment, cell division, replication, and dormancy activation of Mycobacterium tuberculosis (Mtb). The phosphorylation of the response regulator MtrA alters the downstream activity, typically involving changes in DNA binding activity. However, there is a substantial knowledge gap in understanding the phosphorylation-mediated structural changes in MtrA. Additionally, the active conformation of the protein has yet to be determined. Therefore, in this study, we have investigated the phosphorylation-induced conformational changes of MtrA using all-atom molecular dynamics simulations under various phosphorylation conditions. The results from this study demonstrate that the phosphorylation at D56 (pD56-MtrA) increases the compactness of the MtrA protein by stabilizing the inter-domain interaction between the regulatory domain and DNA binding domain. Notably, the higher occupancy H-bond (over 95 %) between Arg200-Asn100 in case of the pD56-MtrA condition, which is otherwise absent in the non-phosphorylated (uMtrA) condition, suggests the importance of this interaction in the active conformation of the protein. The dynamic cross-correlation analysis reveals that phosphorylation (especially pD56-MtrA) reduces the anti-correlated motions and increases correlated motions between different domains. Moreover, the higher DNA binding affinity of pD56-MtrA compared to uMtrA supported by molecular docking and MD simulation followed by MMPBSA analysis suggests that pD56-MtrA is the possible active conformation of the MtrA protein. Overall, this investigation elucidates the key structural changes in MtrA under different phosphorylated conditions, which might help in designing novel therapeutics against tuberculosis.

Pharmacophore modeling, 3D-QSAR, and MD simulation-based overture for the discovery of new potential HDAC1 inhibitors

Histone deacetylases (HDACs) are important epigenetic regulators that modulate the activity of histone and non-histone proteins leading to various cancers. Histone deacetylase 1 (HDAC1) is a member of class 1 HDAC family related to different cancers. However, the nonselective profile of existing HDAC1 inhibitors restricted their clinical utility. Therefore, the identification of new HDAC1 selective inhibitors may be fruitful against cancer therapy. In this present work, a pharmacophore model was built using 60 benzamide-based known HDAC1 selective inhibitors and it was used further to filter the large epigenetic molecular database of small molecules. Further, the 3D-QSAR model was built using the best common pharmacophore hypothesis consisting of higher PLS statistics of R2 of 0.89, Q2 of 0.83, variance ratio (F) of 65.7 and Pearson-r value of 0.94 revealing the model reliability and its high predictive power. The screened hits of the pharmacophore model were then subjected to molecular docking against HDAC1 to identify high-affinity lead molecules. The top 10 hits were ranked from the docking studies using docking scores for lead optimization. The potential hit molecules M1 and M2 identified from the study showed promising interaction during HDAC1 docking and MD simulation studies with acceptable ADME properties. Also, the newly designed lead compounds M11 and M12 may be considered highly potential inhibitors against HDAC1. The 3D-QSAR analysis, conformational requirements, and observations noticed in the MD simulations study will enable the optimization of lead molecules and to design of novel effective, and selective HDAC1 inhibitors in the future.

Expression and functional study of DNA polymerases from Psychrobacillus sp. BL-248-WT-3 and FJAT-21963

The properties of DNA polymerases isolated from thermophilic and mesophilic microorganisms, such as the thermophilic Geobacillus stearothermophilus (Bst) and mesophilic Bacillus subtilis phage (Phi29), have been widely researched. However, DNA polymerases in psychrophilic microorganisms remain poorly understood. In this study, we present for the first time the expression and functional characterization of DNA polymerases PWT-WT and FWT-WT from Psychrobacillus sp. BL-248-WT-3 and FJAT-21963. Enzymatic activity assays revealed that FWT-WT possessed strand displacement but lacked exonuclease activity and high ionic strength tolerance, whereas PWT-WT lacked all these properties. Further protein engineering and biochemical analysis identified D423 and S490 as critical mutation sites for improving strand displacement and tolerance to high ionic strength, specifically in the presence of 0-0.3 M potassium chloride (KCl), sodium chloride (NaCl), and potassium acetate (KAc). Three-dimensional structural analysis demonstrated that the size and the electric charge of the single-stranded DNA (ssDNA) encapsulation entrance were pivotal factors in the binding of the ssDNA template.

Design, synthesis, biological evaluation, and molecular modeling studies of some quinazolin-4(3H)-one-benzenesulfonamide hybrids as potential α-glucosidase inhibitors

Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia, posing serious health risks and becoming increasingly prevalent. Prolonged hyperglycemia can lead to complications such as nephropathy, neuropathy, retinopathy, cardiovascular damage, and blindness. Controlling hyperglycemia through α-glucosidase inhibitors, which slow down carbohydrate breakdown, is an effective treatment strategy. However, current inhibitors like acarbose, voglibose, and miglitol while used to manage type 2 diabetes, have significant side effects. Therefore, developing new α-glucosidase inhibitors that are more effective and have fewer side effects is crucial. In this study, a series of novel quinazolin-4(3H)-one-benzenesulfonamide hybrid compounds were designed, synthesized, and evaluated for in vitro α-glucosidase inhibitory activity. The compounds showed higher enzyme inhibition potency, with IC50 values ranging between 129.2 ± 0.5 and 558.7 ± 13.7 µM, compared to acarbose (IC50=814.3 ± 13.5 µM). Among the tested compounds, compound 10, bearing a 4-chlorophenyl ring on the nitrogen atom of the sulfonamide group, was the most active, with an IC50 value of 129.2 ± 0.5 µM. Enzyme kinetics analyses and molecular modeling studies were conducted to understand their inhibition mechanisms and interactions with the enzyme. The kinetic studies revealed a mixed-type inhibition model, indicating that the compounds bind to the enzyme-substrate complex with higher affinity than to the free enzyme. Molecular modeling results confirmed these findings. Additionally, in silico prediction studies showed that the selected compounds have favourable physicochemical and drug-like properties. These results suggest these compounds have potential for further optimization and development as effective α-glucosidase inhibitors for diabetes treatment.

Molecular insights from structural dynamics of HER2-inhibitor complexes pave the way for new breast cancer drugs

The human epidermal growth factor receptor 2 (HER2) is closely associated with the development and progression of breast cancer, making it a critical target for therapeutic interventions. In this study, we employed a comprehensive computational drug discovery strategy to identify potential inhibitors of HER2. Our approach combined virtual screening, re-docking procedures, molecular dynamics (MD) simulations, and free energy landscape analysis using principal component analysis (PCA). From the extensive PubChem library, we initially screened 733 compounds for their binding potential to HER2, using docking scores as a primary filter. These scores ranged notably from -11.172 to -7.028 kcal/mol, indicating substantial binding capacities. Following this screening, we selected four promising compounds (PubChem CID 166029206, 166544027, 21031510, and 11712721) along with a control compound (70I) for in-depth analysis. Utilizing the Amber software suite for MD simulations, we conducted 200-nanosecond simulations to assess the interactions and binding efficiencies of these selected compounds with HER2. We analysed the molecular interactions through various parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), and hydrogen bond formation patterns, free binding energy calculations. The PCA-based free energy landscape analysis revealed that these compounds consistently occupied a distinct low-energy basin, indicating their high stability and strong binding affinity for the HER2. This detailed analysis provided insights into the stability and conformational dynamics of these potential inhibitors when bound to the HER2. Our findings pave the way for further experimental validation and development of these compounds as therapeutic agents in breast cancer treatment.

Networks of ion-pairs are responsible for the large differences in the thermal stability of two structurally similar aminopeptidases

Aminopeptidases are an important class of enzymes for protein metabolism. Leucyl aminopeptidase (PepL) preferably removes leucine from the N-terminus of small peptides. PepL of Lacticaseibacillus casei was observed to be thermally unstable, while a structurally similar aminopeptidase T (AmpT) of Thermus thermophilus is highly stable. To understand the molecular interaction responsible for the large difference in their stability, molecular dynamics simulations were carried out to study the thermal stability of PepL and AmpT at 300 K to 450 K temperature range over 100 ns. PepL sampled a larger conformational space with a rugged free-energy landscape, while AmpT navigated a smoother energy landscape to reach the global minimum. The RMSD, RMSF, radius of gyration and principal component analysis suggested large movements in PepL than in AmpT with an increase in temperature. Analysis of residue-interaction network revealed AmpT possessing a greater number of low, medium and high energy contacts in comparison to PepL. AmpT showed a higher abundance of ion-pair clusters and ionic residues per cluster compared to PepL. Moreover, AmpT retained a greater number of high-energy contacts at elevated temperatures. These findings showed that the inherently lower stability of PepL originates from a comparatively smaller number of contacts and can be pivotal in engineering PepL for higher stability.

Understanding the stability and dynamics of influenza a H5N1 polymerase PB2 CAP-Binding domain in complex with natural compounds for antiviral drug discovery

Influenza A virus, particularly the H5N1 strain, poses a significant threat to public health due to its ability to cause severe respiratory illness and its high mortality rate. Traditional antiviral drugs targeting influenza A virus have faced challenges such as drug resistance and limited efficacy. Therefore, new antiviral compounds are needed to be discovered and developed. This study concentrated on examining the stability and behavior of the H5N1 polymerase PB2 CAP-binding domain when interacting with natural compounds, aiming to identify potential candidates for antiviral drug discovery. Through the virtual screening process, four lead compounds, ZINC000096095464, ZINC000044404209, ZINC000001562130, and ZINC000059779788, were selected, and these compounds showed binding energies -9.6, -9.4, -9.3, and -9.2 kcal/mol, respectively. When complexed with PB2, the ligand showed acceptable binding stability due to significant bond formation. However, during the 200ns MD simulation analysis, three (ZINC000096095464, ZINC000044404209, and ZINC000059779788) showed significant stability, which was proven by the trajectory analysis. The Rg-RMSD-based FEL plot showed significant structural stability due to stable conformers. The free-binding energy calculation also validates the stability of these complexes. This study offers valuable insights into the stability and dynamics of the H5N1 polymerase PB2 CAP-binding domain in complexes with natural compounds. These findings highlight the potential of these natural compounds as antiviral agents against the H5N1 influenza virus. Furthermore, this research contributes to the broader field of influenza virus treatment by demonstrating the effectiveness of computational methods in predicting and evaluating the stability and dynamics of potential drug candidates.

Structural and free energy landscape analysis for the discovery of antiviral compounds targeting the cap-binding domain of influenza polymerase PB2

Influenza poses a significant threat to global health, with the ability to cause severe epidemics and pandemics. The polymerase basic protein 2 (PB2) of the influenza virus plays a crucial role in the viral replication process, making the CAP-binding domain of PB2 an attractive target for antiviral drug development. This study aimed to identify and evaluate potential inhibitors of the influenza polymerase PB2 CAP-binding domain using computational drug discovery methods. We employed a comprehensive computational approach involving virtual screening, molecular docking, and 500 ns molecular dynamics (MD) simulations. Compounds were selected from the Diverse lib database and assessed for their binding affinity and stability in interaction with the PB2 CAP-binding domain. The study utilized the generalized amber force field (GAFF) for MD simulations to further evaluate the dynamic behaviour and stability of the interactions. Among the screened compounds, compounds 1, 3, and 4 showed promising binding affinities. Compound 4 demonstrated the highest binding stability and the most favourable free energy profile, indicating strong and consistent interaction with the target domain. Compound 3 displayed moderate stability with dynamic conformational changes, while Compound 1 maintained robust interactions throughout the simulations. Comparative analyses of these compounds against a control compound highlighted their potential efficacy. Compound 4 emerged as the most promising inhibitor, with substantial stability and strong binding affinity to the PB2 CAP-binding domain. These findings suggest that compound 4, along with compounds 1 and 3, holds the potential for further development into effective antiviral agents against influenza. Future studies should focus on experimental validation of these compounds and exploration of resistance mechanisms to enhance their therapeutic utility.

Antifungal potential of marine bacterial compounds in inhibiting Candida albicans Yck2 to overcome echinocandin resistance: a molecular dynamics study

Candida albicans (C. albicans), a common fungal pathogen, poses a significant threat to immunocompromised individuals, particularly due to the emergence of resistance against echinocandins, a primary class of antifungal agents. Yck2 protein, a key regulator of cell wall integrity and signaling pathways in C. albicans, was targeted to overcome this resistance. A virtual screening was used to identify Yck2 inhibitors from marine bacterial compounds. Further re-docking, molecular dynamics simulations, and various analyses such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonding, free binding energy calculations, and RG-RMSD-based free energy landscape were conducted to evaluate the efficacy and stability of the identified compounds. Among the compounds screened, CMNPD27166 and CMNPD27283 emerged as the most promising candidates, demonstrating superior binding affinities, enhanced stability, and favorable interaction dynamics with Yck2, surpassing both the control and other compounds in efficacy. In contrast, CMNPD19660 and CMNPD24402, while effective, showed lesser potential. These findings highlight the utility of computational drug discovery techniques in identifying and optimizing potential therapeutic agents and suggest that marine-derived molecules could significantly impact the development of novel antifungal therapies. Further experimental validation of the leading candidates, CMNPD27166 and CMNPD27283, is recommended to confirm their potential as effective antifungal agents against echinocandin-resistant C. albicans infections.

Exploring the anti-protozoal mechanisms of Syzygium aromaticum phytochemicals targeting Cryptosporidium parvum lactate dehydrogenase through molecular dynamics simulations

Cryptosporidium parvum (C. parvum), a protozoan parasite, is known to induce significant gastrointestinal disease in humans. Lactate dehydrogenase (LDH), a protein of C. parvum, has been identified as a potential therapeutic target for developing effective drugs against infection. This study utilized a computational drug discovery approach to identify potential drug molecules against the LDH protein of C. parvum. In the present investigation, we conducted a structure-based virtual screening of 55 phytochemicals from the Syzygium aromaticum (S. aromaticum). This process identified four phytochemicals, including Gallotannin 23, Eugeniin, Strictinin, and Ellagitannin, that demonstrated significant binding affinity and dynamic stability with LDH protein. Interestingly, these four compounds have been documented to possess antibacterial, antiviral, anti-inflammatory, and antioxidant properties. The docked complexes were simulated for 100 ns using Desmond to check the dynamic stability. Finally, the free binding energy was computed from the last 10ns MD trajectories. Gallotannin 23 and Ellagitannin exhibited considerable binding affinity and stability with the target protein among all four phytochemicals. These findings suggest that these predicted phytochemicals from S. aromaticum could be further explored as potential hit candidates for developing effective drugs against C. parvum infection. The in vitro and in vivo experimental validation is still required to confirm their efficacy and safety as LDH inhibitors.

Exploring fingerprints for antidiabetic therapeutics related to peroxisome proliferator-activated receptor gamma (PPARγ) modulators: A chemometric modeling approach

This study demonstrated the correlation of molecular structures of Peroxisome proliferator-activated receptor gamma (PPARγ) modulators and their biological activities. Bayesian classification, and recursive partitioning (RP) studies have been applied to a dataset of 323 PPARγ modulators with diverse scaffolds. The results provide a deep insight into the important sub-structural features modulating PPARγ. The molecular docking analysis again confirmed the significance of the identified sub-structural features in the modulation of PPARγ activity. Molecular dynamics simulations further underscored the stability of the complexes formed by investigated modulators with PPARγ. Overall, the integration of many computational approaches unveiled key structural motifs essential for PPARγ modulatory activity that will shed light on the development of effective modulators in the future.

Investigation of small molecules disrupting dengue virus assembly by inhibiting capsid protein and blocking RNA encapsulation

Dengue fever is a significant global public health concern, causing substantial morbidity and mortality worldwide. The disease can manifest in various forms, from mild fever to potentially life-threatening complications. Developing effective treatments remains a critical challenge to healthcare systems. Despite extensive research, no antiviral drugs have been approved for either the prevention or treatment of dengue. Targeting the virus during its early phase of attachment is essential to inhibit viral replication. The capsid protein plays a crucial role in the virus's structural integrity, assembly, and viral genome release. In the present study, we employed a computational approach focused on the capsid protein to identify possible potent inhibitors against the dengue virus from a library of FDA-approved drugs. We employed high-throughput virtual screening on FDA-approved drugs to identify drug molecules that could potentially combat the disease and save both cost and time. The screening process identified four drug molecules (Nordihydroguaiaretic acid, Ifenprodil tartrate, Lathyrol, and Safinamide Mesylate) based on their highest binding affinity and MM/GBSA scores. Among these, Nordihydroguaiaretic acid showed higher binding affinity than the reference molecule with - 11.66 kcal/mol. In contrast, Ifenprodil tartrate and Lathyrol showed similar results to the reference molecule, with binding energies of - 9.42 kcal/mol and - 9.29 kcal/mol, respectively. Following the screening, molecular dynamic simulations were performed to explore the molecular stability and conformational possibilities. The drug molecules were further supported by post-molecular simulation analysis. Furthermore, binding energies were also computed using the MM/GBSA approach, and the free energy landscape was used to calculate the different transition states, revealing that the drugs exhibited significant transition states. Specifically, Nordihydroguaiaretic acid and Ifenprodil tartrate displayed higher flexibility, while Lathyrol and Safinamide Mesylate showed more predictable and consistent protein folding. This significant breakthrough offers new hope against dengue, highlighting the power of computational drug discovery in identifying potent inhibitors and paving the way for novel treatment approaches.

Identification of potential NUDT5 inhibitors from marine bacterial natural compounds via molecular dynamics and free energy landscape analysis

NUDIX hydrolase 5 (NUDT5) is an enzyme involved in the hydrolysis of nucleoside diphosphates linked to other moieties, such as ADP-ribose. This cofactor is vital in redox reactions and is essential for the activity of sirtuins and poly(ADP-ribose) polymerases, which are involved in DNA repair and genomic stability. It has been shown that NUDT5 activity can also influence NAD+ homeostasis, thereby affecting cancer cell metabolism and survival. In this regard, the discovery of NUDT5 inhibitors has emerged as a potential therapeutic approach in cancer treatment. In this study, we conducted a high-throughput virtual screening of marine bacterial compounds against the NUDT5 enzyme and four molecules were selected based on their docking scores. These compounds established strong interactions within the NUDT5 active site, with molecular analysis highlighting the key role of Trp28A and Trp46B residues. Molecular dynamics simulations over 200 ns indicated a stable behavior, in association with root mean square deviation values always below 3 Å, suggesting conformational stability. Free energy landscape analysis further supported their potential as NUDT5 inhibitors, offering avenues for novel therapeutic strategies against NUDT5-associated breast cancer.

pyGROMODS: a Python package for the generation of input files for molecular dynamic simulation with GROMACS

The pyGROMODS, an easy-to-use cross-platform python-based package, with a graphical user interface, for the generation of molecular dynamic (MD) input files and running MD simulation (MDS) of proteins, peptides, and protein-ligand complex using GROMACS, is here presented. Four routes, with underlining Python scripts, are implemented in pyGROMODS for the generation of MD input files. They are 'RLmulti' for processing multi-ligand protein complex, 'RLmany' for processing multiple ligands against a single protein target, 'RLsingle' for processing multiple pairs of proteins and ligands, and 'PPmore' for processing peptides or proteins without ligands or non-standard residues. In addition, using the package, the generated input files or appropriate input files from other sources can be uploaded to run MDS with GROMACS. The pyGROMODS is implemented with a unique ability to search the host machine systems for the installation of the required software, update and/or install required Python packages, allow the user to pre-define working directory, and generate unique workflow organization with well-defined folders and files in a well-organized manner. The pyGROMODS, which is released under the MIT License, is freely available for download via the GitHub (https://github.com/Dankem/pyGROMODS) and Zenodo (https://doi.org/10.5281/zenodo.7912747) repositories. The precompiled executables can also be downloaded from Zenodo (https://doi.org/10.5281/zenodo.8087090), and a video tutorial can be downloaded from https://youtu.be/I4OKc6uVx1M.Communicated by Ramaswamy H. Sarma.

Regulation of NS5B Polymerase Activity of Hepatitis C Virus by Target Specific Phytotherapeutics: An In-Silico Molecular Dynamics Approach

Chronic hepatitis caused by the hepatitis C virus (HCV) is closely linked with the advancement of liver disease. The research hypothesis suggests that the NS5B enzyme (non-structural 5B protein) of HCV plays a pivotal role in facilitating viral replication within host cells. Hence, the objective of the present investigation is to identify the binding interactions between the structurally diverse phytotherapeutics and those of the catalytic residue of the target NS5B polymerase protein. Results of our docking simulations reveal that compounds such as arjunolic acid, sesamin, arjungenin, astragalin, piperic acid, piperidine, piperine, acalyphin, adhatodine, amyrin, anisotine, apigenin, cuminaldehyde, and curcumin exhibit a maximum of three interactions with the catalytic residues (Asp 220, Asp 318, and Asp 319) present on the Hepatitis C virus NS5B polymerase of HCV. Molecular dynamic simulation, particularly focusing on the best binding lead compound, arjunolic acid (-8.78 kcal/mol), was further extensively analyzed using RMSD, RMSF, Rg, and SASA techniques. The results of the MD simulation confirm that the NS5B-arjunolic acid complex becomes increasingly stable from 20 to 100 ns. The orientation of both arjunolic acid and sofosbuvir triphosphate (standard) within the active site was investigated through DCCM, PCA, and FEL analysis, indicating highly stable interactions of the lead arjunolic acid with the catalytic region of the NS5B enzyme. The findings of our current investigation suggest that bioactive therapeutics like arjunolic acid could serve as promising candidates for limiting the NS5B polymerase activity of the hepatitis C virus, offering hope for the future of HCV treatment.

Structural analogs of 2-(4-fluorophenyl)-6-methyl-3-(pyridin-4-yl)pyrazolo[1,5-a]pyridine for targeting Candida albicans non-essential stress kinase Yck2 through protein-ligand binding and dynamics analysis

The rise in drug-resistant fungal infections poses a significant public health concern, necessitating the development of new antifungal therapies. We aimed to address this challenge by targeting a yeast casein kinase of Candida albicans for antifungal drug development. The compound library contained 589 chemical structures similar to the previously identified kinase inhibitor GW461484A. Through virtual screening, four compounds with the PubChem IDs 102583821, 12982634, 102487860, and 86260205 were selected based on their binding energies. Hydrophobic bonds and van der Waals interactions stabilised the docked complexes. Comprehensive interaction studies and a 200-nanosecond molecular dynamics simulation suggested that these molecules can maintain stable interactions with the target, as evidenced by satisfactory RMSD and RMSF values. The Rg-RMSD-based Free Energy Landscape of these complexes indicated thermodynamic stability due to the presence of conformers with global minima. These promising findings highlight the potential for developing novel antifungal therapies targeting Yck2 in C. albicans. Further experimental validation is required to assess the efficacy of these compounds as antifungal agents. This research provides a significant step towards combating antifungal resistance and opens up a new avenue for drug discovery.

Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery

Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (- 96.14 kcal/mol), CNP0176690 (- 93.79 kcal/mol), CNP0136537 (- 92.31 kcal/mol), CNP0398701 (- 91.96 kcal/mol), and CNP0043390 (- 91.60 kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

Predictive identification and design of potent inhibitors targeting resistance-inducing candidate genes from E. coli whole-genome sequences

Introduction: This work utilizes predictive modeling in drug discovery to unravel potential candidate genes from Escherichia coli that are implicated in antimicrobial resistance; we subsequently target the gidB, MacB, and KatG genes with some compounds from plants with reported antibacterial potentials. Method: The resistance genes and plasmids were identified from 10 whole-genome sequence datasets of E. coli; forty two plant compounds were selected, and their 3D structures were retrieved and optimized for docking. The 3D crystal structures of KatG, MacB, and gidB were retrieved and prepared for molecular docking, molecular dynamics simulations, and ADMET profiling. Result: Hesperidin showed the least binding energy (kcal/mol) against KatG (-9.3), MacB (-10.7), and gidB (-6.7); additionally, good pharmacokinetic profiles and structure-dynamics integrity with their respective protein complexes were observed. Conclusion: Although these findings suggest hesperidin as a potential inhibitor against MacB, gidB, and KatG in E. coli, further validations through in vitro and in vivo experiments are needed. This research is expected to provide an alternative avenue for addressing existing antimicrobial resistances associated with E. coli's MacB, gidB, and KatG.

Functional characterization and structural prediction of hypothetical proteins in monkeypox virus and identification of potential inhibitors

The excessive activation of the monkeypox virus (MPXV-Congo_8-156) is linked to various skin and respiratory disorders such as rashes, fluid-filled blisters, swollen lymph nodes and encephalitis (inflammation of the brain), highlighting MPXV-Congo_8-156 as a promising target for drug intervention. Despite the effectiveness of Cidofovir, in inhibiting MPXV activity, its limited ability to penetrate the skin and its strong side effects restrict its application. To address this challenge, we screened 500 compounds capable of penetrating the skin and gastrointestinal tract to identify potent MPXV inhibitors. Various characterization schemes and structural models of MPXV-Congo_8-156 were explored with bioinformatics tools like PROTPARAM, SOPMA, SWISS-MODEL and PROCHECK. Using molecular docking in PyRx, we evaluated the binding affinities of these compounds with MPXV-Congo_8-156 and identified the top five candidates ranging from - 9.2 to - 8.8 kcal/mol. ADMET analysis indicated that all five compounds were safer alternatives, showing no AMES toxicity or carcinogenicity in toxicological assessments. Molecular dynamics (MD) simulations, conducted for 100 ns each, confirmed the docking interactions of the top five compounds alongside the control (Cidofovir), validating their potential as MPXV inhibitors. The compounds with PubChem CID numbers 4061636, 4422538, 3583576, 4856107 and 4800629 demonstrated strong support in terms of root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA) value, hydrogen bond analysis, and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) analysis. Thus, our investigation identified these five compounds as promising inhibitors of MPXV, offering potential therapeutic avenues. However, further in vivo studies are necessary to validate our findings.

Genomic and computational-aided integrative drug repositioning strategy for EGFR and ROS1 mutated NSCLC

Non-small cell lung cancer (NSCLC) has been marked as the major cause of death in lung cancer patients. Due to tumor heterogeneity, mutation burden, and emerging resistance against the available therapies in NSCLC, it has been posing potential challenges in the therapy development. Hence, identification of cancer-driving mutations and their effective inhibition have been advocated as a potential approach in NSCLC treatment. Thereof, this study aims to employ the genomic and computational-aided integrative drug repositioning strategy to identify the potential mutations in the selected molecular targets and repurpose FDA-approved drugs against them. Accordingly, molecular targets and their mutations, i.e., EGFR (V843L, L858R, L861Q, and P1019L) and ROS1 (G1969E, F2046Y, Y2092C, and V2144I), were identified based on TCGA dataset analysis. Following, virtual screening and redocking analysis, Elbasvir, Ledipasvir, and Lomitapide drugs for EGFR mutants (>-10.8 kcal/mol) while Indinavir, Ledipasvir, Lomitapide, Monteleukast, and Isavuconazonium for ROS1 mutants (>-8.8 kcal/mol) were found as putative inhibitors. Furthermore, classical molecular dynamics simulation and endpoint binding energy calculation support the considerable stability of the selected docked complexes aided by substantial hydrogen bonding and hydrophobic interactions in comparison to the respective control complexes. Conclusively, the repositioned FDA-approved drugs might be beneficial alone or in synergy to overcome acquired resistance to EGFR and ROS1-positive lung cancers.

An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Structural and functional effects of the L84S mutant in the SARS-COV-2 ORF8 dimer based on microsecond molecular dynamics study

The L84S mutation has been observed frequently in the ORF8 protein of SARS-CoV-2, which is an accessory protein involved in various important functions such as virus propagation, pathogenesis, and evading the immune response. However, the specific effects of this mutation on the dimeric structure of ORF8 and its impacts on interactions with host components and immune responses are not well understood. In this study, we performed one microsecond molecular dynamics (MD) simulation and analyzed the dimeric behavior of the L84S and L84A mutants in comparison to the native protein. The MD simulations revealed that both mutations caused changes in the conformation of the ORF8 dimer, influenced protein folding mechanisms, and affected the overall structural stability. In particular, the 73YIDI76 motif has found to be significantly affected by the L84S mutation, leading to structural flexibility in the region connecting the C-terminal β4 and β5 strands. This flexibility might be responsible for virus immune modulation.  The free energy landscape (FEL) and principle component analysis (PCA) have also supported our investigation. Overall, the L84S and L84A mutations affect the ORF8 dimeric interfaces by reducing the frequency of protein-protein interacting residues (Arg52, Lys53, Arg98, Ile104, Arg115, Val117, Asp119, Phe120, and Ile121) in the ORF8 dimer.  Our findings provide detail insights for further research in designing structure-based therapeutics against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Marine alkaloid rigidin analogues as potential selective inhibitors of SHP1, a new strategy for cancer immunotherapeutics

SHP1 is a protein tyrosine phosphatase playing a central role in immunity, cell growth, development, and survival. The inhibition of SHP1 can help in better prognosis in various disorders like breast and ovarian cancer, melanoma, atherosclerosis, hypoxia, hypoactive immune response, and familial dysautonomia. The currently available inhibitors of SHP1 have the side effect of inhibiting the activity of SHP2, which shares >60% sequence similarity with SHP1 but has distinct biological functions. Thus, there is a need to search for novel specific inhibitors of SHP1. The current study uses a combination of virtual screening and molecular dynamic simulations, followed by PCA and MM-GBSA analysis, to screen about 35000 compounds; to predict that two rigidin analogues can potentially selectively inhibit SHP1 but not SHP2. Our studies demonstrate that these rigidin analogues are more potent at inhibiting SHP1 than the commercially available inhibitor NSC-87877. Further, cross-binding studies with SHP2 exhibited poor binding efficiency and lower stability of the complex, thus indicating a specificity of the rigidin analogues for SHP1, which is crucial in preventing side effects due to the diverse physiological functions of SHP2 in cellular signaling, proliferation, and hematopoiesis. Additionally, SHP1 is essential in mediating the inhibitory signaling in antitumor immune cells like NK and T cells. Hence, the rigidin analogues that inhibit SHP1 will potentiate the anti-tumor immune response by the release of inhibitory function of NK cells, thus driving NK activating response, in addition to their intrinsic anti-tumor function. Thus, SHP1 inhibition is a novel double-blade approach towards anti-cancer immunotherapeutics.Communicated by Ramaswamy H. Sarma.

Screening of Phytocompounds for Identification of Prospective Histone Deacetylase 1 (HDAC1) Inhibitor: An In Silico Molecular Docking, Molecular Dynamics Simulation, and MM-GBSA Approach

The upregulation of HDAC1 facilitate the induction of epigenetic repression of genes responsible for suppressing tumourigenesis, thereby triggering the development of cancer. HDAC1 inhibitors have thus emerged as possible therapeutic approaches against a variety of human malignancies, as they can inhibit the activity of certain HDACs, repair the overexpression of tumour suppressor genes, and induce cell differentiation, cell cycle arrest, and apoptosis. In this study, among 810 virtually screened compounds, Pinocembrin (PHUB000396) had a significant binding affinity (-7.99 kcal/mol). In molecular dynamics simulation (MD) studies for 200 ns time scale, the compound Pinocembrin effectively undergoes conformational optimization, thereby enabling its accommodation within the active site of the receptor. This outcome serves as a rational for the observed binding affinity. The optimal binding free energy calculations using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) (-35.86 ± 7.52 kcal/mol) showed the significant role of van der Waals forces and Coulomb interactions in the stability of the respective complex. The pharmacokinetic study showed its potential as a lead compound. The in-silico cytotoxicity prediction also confirmed its potential as an active anticancer phytocompound in lung and brain cancer. Therefore, it can be predicted that Pinocembrin could be a useful bioactive compound as an HDAC1 inhibitor and could be used in developing epigenetic therapy in cancer such as brain cancer and lung cancer to regulate gene expression.

Employing advanced computational drug discovery techniques to identify novel inhibitors against ML2640c protein: a potential therapeutic approach for combatting leprosy

Leprosy, caused by Mycobacterium leprae, remains a significant global health challenge, necessitating innovative approaches to therapeutic intervention. This study employs advanced computational drug discovery techniques to identify potential inhibitors against the ML2640c protein, a key factor in the bacterium's ability to infect and persist within host cells. Utilizing a comprehensive methodology, including virtual screening, re-docking, molecular dynamics simulations, and free energy calculations, we screened a library of compounds for their interaction with ML2640c. Four compounds (24349836, 26616083, 26648979, and 26651264) demonstrated promising inhibitory potential, each exhibiting unique binding energies and interaction patterns that suggest a strong likelihood of disrupting the protein function. The study highlights the efficacy of computational methods in identifying potential therapeutic candidates, presenting compound 26616083 as a notably potent inhibitor due to its excellent binding affinity and stability. Our findings offer a foundation for future experimental validation and optimization, marking a significant step forward in the development of new treatments for leprosy. This research not only advances the fight against leprosy but also showcases the broader applicability of computational drug discovery in tackling infectious diseases.

Computational Analysis of Albaflavenone Interaction with SlMAPK1 for Drought Resistance in Tomato

As global agricultural challenges intensify, particularly drought stress, the exploration of innovative strategies for crop resilience has become crucial. This study focuses on the role of the microbial endophyte metabolite Albaflavenone in enhancing drought resistance in tomato (Solanum lycopersicum L.) through the activation of the SlMAPK1 protein in the MAPK pathway. To computationally analyze the interaction between Albaflavenone and SlMAPK1 and to elucidate the potential enhancement of drought tolerance in tomato plants through this interaction. We utilized molecular docking, homology modeling, and molecular dynamics simulations to investigate the binding affinities and interaction dynamics between SlMAPK1 and Albaflavenone. Functional network analysis was employed to examine protein-protein interactions within the MAPK pathway, while the MM-GBSA method was used to calculate binding free energies. Our computational analyses revealed that Albaflavenone exhibited a high binding affinity to SlMAPK1 with a binding energy of - 8.9 kcal/mol. Molecular dynamics simulations showed this interaction significantly stabilized SlMAPK1, suggesting enhanced activity. Specifically, the root mean square deviation (RMSD) of the Albaflavenone-SlMAPK1 complex stabilized at around 3.1 Å, while the root mean square fluctuations (RMSF) indicated consistent amino acid conformations. Additionally, the radius of gyration (Rg) analysis demonstrated minimal variance, suggesting a compact and stable protein-ligand complex. The significant binding affinity between Albaflavenone and SlMAPK1 highlights the potential of leveraging plant-microbe interactions in developing sustainable agricultural practices. These findings also demonstrate the effectiveness of computational methods in dissecting complex biological interactions, contributing to a deeper understanding of plant resilience strategies against environmental stresses.

In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism

Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.

Targeting key players in Alzheimer's disease: bioactive compounds from Moringa oleifera, Desmodium gangeticum, and Centella asiatica as potential therapeutics

Alzheimer's Disease (AD) is one of the critical reasons for dementia around the world, with a huge number of cases being reported every year. The breakdown of Amyloid Precursor Protein (APP) plays a crucial role in AD development. The Beta-site APP Cleaving Enzyme 1 (BACE1) is a highly significant proteolytic enzyme found to be critically involved in the APP breakdown process and generates beta-amyloid plaques in the extracellular neuronal membrane. In this study, we have used natural compounds with cognitive and neuroprotective activities from three plants, Centella asiatica, Moringa oleifera, and Desmodium gangeticum to inhibit the activity of BACE1. We have identified nine compounds out of 73 compounds filtered out from the three plants showing high affinity with the catalytic dyad region of BACE1 through molecular docking studies. Interestingly, the 200 ns molecular dynamics simulation study further confirmed the stability of the complexes formed between 9 compounds and the BACE1 protein. Furthermore, the free energy calculations also revealed these complexes possess favorable energies. Astilbin, Delphinidin 3-glucoside, and kaempferol 7-O-glucoside showed good binding affinity and structural stability when compared to other compounds and the control CNP520. Following a preliminary screening, the Astilbin compound was chosen based on the grounds of binding affinity, ADMET Properties, Hbond formation, Molecular Dynamic simulation, and MM-PBSA studies. A subsequent 1microsecond molecular dynamics simulation was conducted for the Astilbin complex. Through microsecond simulation, it was found that Astilbin alters BACE1's behavior and induces conformational rearrangements. Thus, this study opens a gateway to inhibit the activity of BACE1 protein through Astilbin thereby disclosing the possibility of managing Alzheimer's Disease.Communicated by Ramaswamy H. Sarma.