Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models

CORAL Models for Drug-Induced Nephrotoxicity

Drug-induced nephrotoxicity is a major cause of kidney dysfunction with potentially fatal consequences. The poor prediction of clinical responses based on preclinical research hampers the development of new pharmaceuticals. This emphasises the need for new methods for earlier and more accurate diagnosis to avoid drug-induced kidney injuries. Computational predictions of drug-induced nephrotoxicity are an attractive approach to facilitate such an assessment and such models could serve as robust and reliable replacements for animal testing. To provide the chemical information for computational prediction, we used the convenient and common SMILES format. We examined several versions of so-called optimal SMILES-based descriptors. We obtained the highest statistical values, considering the specificity, sensitivity and accuracy of the prediction, by applying recently suggested atoms pairs proportions vectors and the index of ideality of correlation, which is a special statistical measure of the predictive potential. Implementation of this tool in the drug development process might lead to safer drugs in the future.

NF-κB Signaling and Inflammation-Drug Repurposing to Treat Inflammatory Disorders?

Simple Summary

Since its first description 35 years ago, the transcription factor NF-κB (nuclear factor κ-light-chain-enhancer of activated B cells) has been shown to be a key mediator of immune cell responses to inflammatory mediators, oxidative stress and genotoxic injury. Dysregulated NF-κB signalling drives inflammation in inflammatory disorders such as multiple sclerosis, rheumatoid arthritis or inflammatory bowel disease. Thus, re-establishing the appropriate regulation of NF-κB activity seems like a promising approach to treat inflammatory diseases. Current anti-inflammatory drugs have many, often serious, side effects. Thus, there is an unmet clinical need for safe and effective anti-inflammatory medicines that both decrease inflammatory mediator production and enhance endogenous anti-inflammatory and prorepair pathways. So far, traditional de novo drug discovery has fallen short of satisfying this need. Drug repurposing is a cost- and time-effective alternative to de novo drug development for the identification of novel applications and has already resulted in the identification of effective anti-inflammatories in the ongoing COVID-19 pandemic. In this paper we critically review NF-κB as a potential target for the development of anti-inflammatory drugs with an emphasis on drug repurposing as a strategy to identify new approaches to treat inflammatory diseases.

Abstract

NF-κB is a central mediator of inflammation, response to DNA damage and oxidative stress. As a result of its central role in so many important cellular processes, NF-κB dysregulation has been implicated in the pathology of important human diseases. NF-κB activation causes inappropriate inflammatory responses in diseases including rheumatoid arthritis (RA) and multiple sclerosis (MS). Thus, modulation of NF-κB signaling is being widely investigated as an approach to treat chronic inflammatory diseases, autoimmunity and cancer. The emergence of COVID-19 in late 2019, the subsequent pandemic and the huge clinical burden of patients with life-threatening SARS-CoV-2 pneumonia led to a massive scramble to repurpose existing medicines to treat lung inflammation in a wide range of healthcare systems. These efforts continue and have proven to be controversial. Drug repurposing strategies are a promising alternative to de novo drug development, as they minimize drug development timelines and reduce the risk of failure due to unexpected side effects. Different experimental approaches have been applied to identify existing medicines which inhibit NF-κB that could be repurposed as anti-inflammatory drugs.

Screening of Clinically Approved and Investigation Drugs as Potential Inhibitors of SARS-CoV-2: A Combined in silico and in vitro Study

In the current study, we used 7922 FDA approved small molecule drugs as well as compounds in clinical investigation from NIH's NPC database in our drug repurposing study. SARS-CoV-2 main protease as well as Spike protein/ACE2 targets were used in virtual screening and top-100 compounds from each docking simulations were considered initially in short molecular dynamics (MD) simulations and their average binding energies were calculated by MM/GBSA method. Promising hit compounds selected based on average MM/GBSA scores were then used in long MD simulations. Based on these numerical calculations following compounds were found as hit inhibitors for the SARS-CoV-2 main protease: Pinokalant, terlakiren, ritonavir, cefotiam, telinavir, rotigaptide, and cefpiramide. In addition, following 3 compounds were identified as inhibitors for Spike/ACE2: Denopamine, bometolol, and rotigaptide. In order to verify the predictions of in silico analyses, 4 compounds (ritonavir, rotigaptide, cefotiam, and cefpiramide) for the main protease and 2 compounds (rotigaptide and denopamine) for the Spike/ACE2 interactions were tested by in vitro experiments. While the concentration-dependent inhibition of the ritonavir, rotigaptide, and cefotiam was observed for the main protease; denopamine was effective at the inhibition of Spike/ACE2 binding.

Synthesis and Aldose Reductase Inhibition Effects of Novel N-Benzyl-4-Methoxyaniline Derivatives

In the current study, starting from 4-methoxyaniline, four Schiff bases were synthesized from benzaldehydes with Br and OMe. Corresponding N-benzylanilines and their derivatives were obtained from reductions (by NaBH₄ ) and substitutions (by acyl and tosyl chlorides) of these bases, respectively. The inhibitory effects of the sixteen compounds, twelve of which were novel compounds are examined. Then, we conducted molecular docking and binary QSAR studies to determine inhibitory-enzyme interactions of compounds that show an inhibitory effect. Our results reveal that methoxyanilline-derived compounds show good biological activities. The most active compound (22) has IC₅₀ values of 2.83 μM. These novel AR enzyme inhibitors may open new avenues for better AR inhibitors in the future.

Identification of first-in-class plasmodium OTU inhibitors with potent anti-malarial activity

OTU proteases antagonize the cellular defense in the host cells and involve in pathogenesis. Intriguingly, P. falciparum, P. vivax, and P. yoelii have an uncharacterized and highly conserved viral OTU-like proteins. However, their structure, function or inhibitors have not been previously reported. To this end, we have performed structural modeling, small molecule screening, deconjugation assays to characterize and develop first-in-class inhibitors of P. falciparum, P. vivax, and P. yoelii OTU-like proteins. These Plasmodium OTU-like proteins have highly conserved residues in the catalytic and inhibition pockets similar to viral OTU proteins. Plasmodium OTU proteins demonstrated Ubiquitin and ISG15 deconjugation activities as evident by intracellular ubiquitinated protein content analyzed by western blot and flow cytometry. We screened a library of small molecules to determine plasmodium OTU inhibitors with potent anti-malarial activity. Enrichment and correlation studies identified structurally similar molecules. We have identified two small molecules that inhibit P. falciparum, P. vivax, and P. yoelii OTU proteins (IC50 values as low as 30 nM) with potent anti-malarial activity (IC50 of 4.1-6.5 µM). We also established enzyme kinetics, druglikeness, ADME, and QSAR model. MD simulations allowed us to resolve how inhibitors interacted with plasmodium OTU proteins. These findings suggest that targeting malarial OTU-like proteases is a plausible strategy to develop new anti-malarial therapies.

The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling

Fragment-Based Drug Design (FBDD) has established itself as a promising approach in modern drug discovery, accelerating and improving lead optimization, while playing a crucial role in diminishing the high attrition rates at all stages in the drug development process. On the other hand, FBDD has benefited from the application of computational methodologies, where the models derived from the Quantitative Structure-Activity Relationships (QSAR) have become consolidated tools. This mini-review focuses on the evolution and main applications of the QSAR paradigm in the context of FBDD in the last five years. This report places particular emphasis on the QSAR models derived from fragment-based topological approaches to extract physicochemical and/or structural information, allowing to design potentially novel mono- or multi-target inhibitors from relatively large and heterogeneous databases. Here, we also discuss the need to apply multi-scale modeling, to exemplify how different datasets based on target inhibition can be simultaneously integrated and predicted together with other relevant endpoints such as the biological activity against non-biomolecular targets, as well as in vitro and in vivo toxicity and pharmacokinetic properties. In this context, seminal papers are briefly analyzed. As huge amounts of data continue to accumulate in the domains of the chemical, biological and biomedical sciences, it has become clear that drug discovery must be viewed as a multi-scale optimization process. An ideal multi-scale approach should integrate diverse chemical and biological data and also serve as a knowledge generator, enabling the design of potentially optimal chemicals that may become therapeutic agents.

Transcription factor NF-κB as target for SARS-CoV-2 drug discovery efforts using inflammation-based QSAR screening model

NF-κB is a central regulator of immunity and inflammation. It is suggested that the inflammatory response mediated by SARS-CoV-2 is predominated by NF-κB activation. Thus, NF-κB inhibition is considered a potential therapeutic strategy for COVID-19. The aim of this study was to identify potential anti-inflammation lead molecules that target NF-κB using a quantitative structure-activity relationships (QSAR) model of currently used and investigated anti-inflammatory drugs as the basis for screening. We applied an integrated approach by starting with the inflammation-based QSAR model to screen three libraries containing more than 220,000 drug-like molecules for the purpose of finding potential drugs that target the NF-κB/IκBα p50/p65 (RelA) complex. We also used QSAR models to rule out molecules that were predicted to be toxic. Among screening libraries, 382 molecules were selected as potentially nontoxic and were analyzed further by short and long molecular dynamics (MD) simulations and free energy calculations. We have discovered five hit ligands with highly predicted anti-inflammation activity and nearly no predicted toxicities which had strongly favorable protein-ligand interactions and conformational stability at the binding pocket compared to a known NF-κB inhibitor (procyanidin B2). We propose these hit molecules as potential NF-κB inhibitors which can be further investigated in pre-clinical studies against SARS-CoV-2 and may be used as a scaffold for chemical optimization and drug development efforts.

Target-Driven Design of a Coumarinyl Chalcone Scaffold Based Novel EF2 Kinase Inhibitor Suppresses Breast Cancer Growth In Vivo

Eukaryotic elongation factor 2 kinase (eEF-2K) is an unusual alpha kinase involved in protein synthesis through phosphorylation of elongation factor 2 (EF2). eEF-2K is highly overexpressed in breast cancer, and its activity is associated with significantly shortened patient survival and proven to be a potential molecular target in breast cancer. The crystal structure of eEF-2K remains unknown, and there is no potent, safe, and effective inhibitor available for clinical applications. We designed and synthesized several generations of potential inhibitors. The effect of the inhibitors at the binding pocket of eEF-2K was analyzed after developing a 3D target model by using a domain of another α-kinase called myosin heavy-chain kinase A (MHCKA) that closely resembles eEF-2K. In silico studies showed that compounds with a coumarin-chalcone core have high predicted binding affinities for eEF-2K. Using in vitro studies in highly aggressive and invasive (MDA-MB-436, MDA-MB-231, and BT20) and noninvazive (MCF-7) breast cancer cells, we identified a lead compound that was highly effective in inhibiting eEF-2K activity at submicromolar concentrations and at inhibiting cell proliferation by induction of apoptosis with no toxicity in normal breast epithelial cells. In vivo systemic administration of the lead compound encapsulated in single lipid-based liposomal nanoparticles twice a week significantly suppressed growth of MDA-MB-231 tumors in orthotopic breast cancer models in nude mice with no observed toxicity. In conclusion, our study provides a highly potent and in vivo effective novel small-molecule eEF-2K inhibitor that may be used as a molecularly targeted therapy breast cancer or other eEF-2K-dependent tumors.

Exogenous melatonin alleviates hemorrhagic shock‑induced hepatic ischemic injury in rats by inhibiting the NF‑κB/IκBα signaling pathway

Melatonin (MT) is an indoleamine hormone that can counteract ischemia-induced organ injury through its antioxidant effects. The aim of the present study was to investigate the protective effects of exogenous MT against hemorrhagic shock (HS)-induced hepatic ischemic injury in rats, and the role of the nuclear factor (NF)-κB signaling pathway in this process. A rat model of HS-induced hepatic ischemic injury was established. The serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), glutamate dehydrogenase (GDH), tumor necrosis factor (TNF)-α, interferon (IFN)-γ, interleukin (IL)-6 and IL-1β were measured every 6 h, and the 24-h survival rate of the rats was analyzed. All surviving rats were sacrificed after 24 h. Pathological changes in the liver and the hepatocyte apoptosis rate were observed by hematoxylin and eosin staining and TUNEL assay, respectively, and the expression levels of NF-κB p65 and NF-κB inhibitor α (IκBα) were analyzed by reverse transcription-quantitative PCR analysis and western blotting. The results demonstrated that the serum levels of ALT, AST, LDH, GDH, TNF-α, IFN-γ, IL-6 and IL-1β gradually increased after HS compared with those in rats subjected to a sham procedure, but this increase was attenuated by MT. Furthermore, the survival rate of the MT group was significantly higher compared with that of the HS group. The degree of pathological hepatic injury, the hepatocyte apoptosis rate, and the hepatic levels of TNF-α, IFN-γ, IL-6 and IL-1β were significantly decreased in the MT group compared with the HS group. In addition, the mRNA expression of NF-κB p65 was significantly decreased and the mRNA expression of IκBα was significantly increased in the MT group compared with the sham group. Furthermore, the NF-κB p65 protein levels in the MT group were significantly increased in the cytosol but decreased in the nucleus, and the IκBα protein levels were increased while those of phosphorylated IκBα were decreased compared with those in the HS group. Therefore, it may be inferred that exogenous MT alleviates HS-induced hepatic ischemic injury in rats via the inhibition of NF-κB activation and IκBα phosphorylation.

Post-translational Modifications of IκBα: The State of the Art

The nuclear factor-kappa B (NF-κB) signaling pathway regulates a variety of biological functions in the body, and its abnormal activation contributes to the pathogenesis of many diseases, such as cardiovascular and respiratory diseases and cancers. Therefore, to ensure physiological homeostasis of body systems, this pathway is strictly regulated by IκBα transcription, IκBα synthesis, and the IκBα-dependent nuclear transport of NF-κB. Particularly, the post-translational modifications of IκBα including phosphorylation, ubiquitination, SUMOylation, glutathionylation and hydroxylation are crucial in the abovementioned regulatory process. Because of the importance of the NF-κB pathway in maintaining body homeostasis, understanding the post-translational modifications of IκBα can not only provide deeper insights into the regulation of NF-κB pathway but also contribute to the development of new drug targets and biomarkers for the diseases.

An Integrated in silico Approach and in vitro Study for the Discovery of Small-Molecule USP7 Inhibitors as Potential Cancer Therapies

The ubiquitin-specific protease 7 (USP7) is a highly promising well-validated target for a variety of malignancies. USP7 is critical in regulating the tumor suppressor p53 along with numerous epigenetic modifiers and transcription factors. Previous studies showed that USP7 inhibitors led to increased levels of p53 and anti-proliferative effects in hematological and solid tumor cell lines. Thus, this study aimed to identify potent and safe USP7 hit inhibitors as potential anti-cancer therapeutics via an integrated computational approach that combines pharmacophore modeling, molecular docking, molecular dynamics (MD) simulations and post-MD free energy calculations. In this study, the crystal structure of USP7 has been extensively investigated using a combination of three different chemical pharmacophore modeling approaches. We then screened ∼220.000 drug-like small molecule library and the hit ligands predicted to be nontoxic were evaluated further. The identified hits from each pharmacophore modeling study were further examined by 1-ns short MD simulations and MM/GBSA free energy analysis. In total, we ran 1 ns MD simulations for 1137 selected on small compounds. Based on their average MM/GBSA scores, 18 ligands were selected for 50 ns MD simulations along with one highly potent USP7 inhibitor used as a positive control. The in vitro enzymatic inhibition assay testing of our lead 18 molecules confirmed that 7 of these molecules were successful in USP7 inhibition. Screening results showed that within the used screening approaches, the most successful one was structure-based pharmacophore modeling with the success rate of 75 %. The identification of potent and safe USP7 small molecules as potential inhibitors is a step closer to finding appropriate effective therapies for cancer. Our lead ligands can be used as a scaffold for further structural optimization and development, enabling further research in this promising field.

Targeting Imd pathway receptor in Drosophila melanogaster and repurposing of phyto-inhibitors: structural modulation and molecular dynamics

Dysbiosis is a major cause of disease in an individual, generally initiated in the gastrointestinal tract. The gut, also known as the second brain, constitutes a major role in immune signaling. To study the immunity cascade, the Drosophila model was considered targeting the Imd pathway receptor (2F2L) located in the midgut. This receptor further initiates the immune signaling mechanism influenced by bacteria. To inhibit the Imd pathway, the crystal structure of Imd with PDB: 2F2L was considered for the screening of suitable ligand/inhibitor. In light of our previous studies, repurposing of anti-diabetic ligands from the banana plant namely lupeol (LUP), stigmasterol (STI), β-sitosterol (BST) and umbelliferone (UMB) were screened. This study identifies the potential inhibitor along with the tracheal toxin (TCT), a major peptidoglycan constituent of microbes. The molecular docking and molecular dynamics simulation of complexes 2F2L-MLD, 2F2L- CAP, 2F2L-LUP, 2F2L-BST, 2F2L-STI and 2F2L-UMB elucidates the intermolecular interaction into the inhibitory property of ligands. The results of this study infer LUP and UMB as better ligands with high stability and functionality among the screened candidates. This study provides insights into the dysbiosis and its amelioration by plant-derived molecules. The identified drugs (LUP & UMB) will probably act as an inhibitor against microbial dysbiosis and other related pathogenesis (diabetes and diabetic neuropathy). Further, this study will widen avenues in fly biology research and which could be used as a therapeutic model in the rapid, reliable and reproducible screening of phytobiologics in complementary and alternative medicine for various lifestyle associated complications.Communicated by Ramaswamy H. Sarma.

Drug Re-positioning Studies for Novel HIV-1 Inhibitors Using Binary QSAR Models and Multi-target-driven In Silico Studies

Current antiretroviral therapies against HIV involve the usage of at least two drugs that target different stages of HIV life cycle. However, potential drug interactions and side effects pose a problem. A promising concept for complex disease treatment is 'one molecule-multiple target' approach to overcome undesired effects of multiple drugs. Additionally, it is beneficial to consider drug re-purposing due to the cost of taking a drug into the market. Taking these into account, here potential anti-HIV compounds are suggested by virtually screening small approved drug molecules and clinical candidates. Initially, binary QSAR models are used to predict the therapeutic activity of around 7900 compounds against HIV and to predict the toxicity of molecules with high therapeutic activities. Selected compounds are considered for molecular docking studies against two targets, HIV-1 protease enzyme, and chemokine co-receptor CCR5. The top docking poses for all 549 molecules are then subjected to short (1 ns) individual molecular dynamics (MD) simulations and they are ranked based on their calculated relative binding free energies. Finally, 25 molecules are selected for long (200 ns) MD simulations, and 5 molecules are suggested as promising multi-target HIV agents. The results of this study may open new avenues for the designing of new dual HIV-1 inhibitor scaffolds.

Potent novel inhibitors against hepatitis C virus NS3 (HCV NS3 GT-3a) protease domain

HCV NS3, a non-structural hepatitis C viral protein is used as one of the potential targets for inhibition by direct-acting antivirals. It is known that the success rate for HCV genotype-1 treatment remained very high, however, treatment of genotype-3a (GT-3a), is still quite challenging. In the current study, the HCV GT-3a full-length NS3 gene was amplified and sequenced. The complete nucleotide sequence was translated into the amino acid sequence and homology models of HCV-NS3 GT-3a were generated by HCV-NS3 genotype-1b as a template. The objective of the study was to screen novel therapeutic hits from large databases. For this aim, various small molecule databases including, BindingDB (∼45.000 compounds), NCI (∼265.000 compounds), and Specs-SC (∼212.000 compounds) were used. Firstly, all of the compounds were screened using binary-QSAR models from the MetaCore/MetaDrug server, and compounds were filtered based on therapeutic activity predictions by the anti-viral QSAR model. Filtered molecules were used in 26 different toxicity QSAR models and active non-toxic compounds were identified. These selected molecules were then used in docking and molecular dynamics (MD) simulations studies at the binding cavities of the NS3 protease domain of the GT-3a. Results were compared with known inhibitors and novel molecules are proposed against HCV-NS3 GT-3a. These molecules have high ligand efficiencies as compared to the reference molecules suggesting a better alternate to the existing suite of inhibitors. Thus, this study will be a step ahead in the development of new potential compounds as antiviral drugs for the GT-3a target.

Integrating Ligand and Target-Driven Based Virtual Screening Approaches With in vitro Human Cell Line Models and Time-Resolved Fluorescence Resonance Energy Transfer Assay to Identify Novel Hit Compounds Against BCL-2

Antiapoptotic members of B-cell leukemia/lymphoma-2 (BCL-2) family proteins are one of the overexpressed proteins in cancer cells that are oncogenic targets. As such, targeting of BCL-2 family proteins raises hopes for new therapeutic discoveries. Thus, we used multistep screening and filtering approaches that combine structure and ligand-based drug design to identify new, effective BCL-2 inhibitors from a small molecule database (Specs SC), which includes more than 210,000 compounds. This database is first filtered based on binary “cancer-QSAR” model constructed with 886 training and 167 test set compounds and common 26 toxicity quantitative structure-activity relationships (QSAR) models. Predicted non-toxic compounds are considered for target-driven studies. Here, we applied two different approaches to filter and select hit compounds for further in vitro biological assays and human cell line experiments. In the first approach, a molecular docking and filtering approach is used to rank compounds based on their docking scores and only a few top-ranked molecules are selected for further long (100-ns) molecular dynamics (MD) simulations and in vitro tests. While docking algorithms are promising in predicting binding poses, they can be less prone to precisely predict ranking of compounds leading to decrease in the success rate of in silico studies. Hence, in the second approach, top-docking poses of each compound filtered through QSAR studies are subjected to initially short (1 ns) MD simulations and their binding energies are calculated via molecular mechanics generalized Born surface area (MM/GBSA) method. Then, the compounds are ranked based on their average MM/GBSA energy values to select hit molecules for further long MD simulations and in vitro studies. Additionally, we have applied text-mining approaches to identify molecules that contain “indol” phrase as many of the approved drugs contain indole and indol derivatives. Around 2700 compounds are filtered based on “cancer-QSAR” model and are then docked into BCL-2. Short MD simulations are performed for the top-docking poses for each compound in complex with BCL-2. The complexes are again ranked based on their MM/GBSA values to select hit molecules for further long MD simulations and in vitro studies. In total, seven molecules are subjected to biological activity tests in various human cancer cell lines as well as Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay. Inhibitory concentrations are evaluated, and biological activities and apoptotic potentials are assessed by cell culture studies. Four molecules are found to be limiting the proliferation capacity of cancer cells while increasing the apoptotic cell fractions.

Design, Synthesis, and Molecular Modeling Studies of Novel Coumarin Carboxamide Derivatives as eEF-2K Inhibitors

Eukaryotic elongation factor-2 kinase (eEF-2K) is an unusual alpha kinase commonly upregulated in various human cancers, including breast, pancreatic, lung, and brain tumors. We have demonstrated that eEF-2K is relevant to poor prognosis and shorter patient survival in breast and lung cancers and validated it as a molecular target using genetic methods in related in vivo tumor models. Although several eEF-2K inhibitors have been published, none of them have shown to be potent and specific enough for translation into clinical trials. Therefore, development of highly effective novel inhibitors targeting eEF-2K is needed for clinical applications. However, currently, the crystal structure of eEF-2K is not known, limiting the efforts for designing novel inhibitor compounds. Therefore, using homology modeling of eEF-2K, we designed and synthesized novel coumarin-3-carboxamides including compounds A1, A2, and B1-B4 and evaluated their activity by performing in silico analysis and in vitro biological assays in breast cancer cells. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) area results showed that A1 and A2 have interaction energies with eEF-2K better than those of B1-B4 compounds. Our in vitro results indicated that compounds A1 and A2 were highly effective in inhibiting eEF-2K at 1.0 and 2.5 μM concentrations compared to compounds B1-B4, supporting the in silico findings. In conclusion, the results of this study suggest that our homology modeling along with in silico analysis may be effectively used to design inhibitors for eEF-2K. Our newly synthesized compounds A1 and A2 may be used as novel eEF-2K inhibitors with potential therapeutic applications.

Identifying new piperazine-based PARP1 inhibitors using text mining and integrated molecular modeling approaches

One of the important molecular targets for antitumor drug discovery is the polyadenosine diphosphate-ribose polymerase-1 (PARP1) enzyme. It is linked with various biological functions including DNA repair and apoptosis. It is primarily a nuclear enzyme linked to chromatin, which is activated by DNA damage. Improved expression of PARP1 in melanomas, breast cancer, lung cancer and other neoplastic diseases is often observed. A tremendous PARP research concerning cancer and ischemia is progressing very rapidly. There are currently four PARP1 inhibitors approved by the FDA on the market, namely Olaparib, Rucaparib, Niraparib and Talazoparib. All of these molecules are non-selective inhibitors of PARP1. Currently there is an urgent need for novel and selective PARP1 inhibitors. In this work, asmall molecule database (Specs SC) were used to identify the new selective lead inhibitors of PARP1. Piperazine scaffold is an important fragment that is used in many currently used FDA approved drugs in different diseases including PARP1 inhibitor Olaparib. Thus, based on text mining studies, 4674 compounds thatinclude piperazine fragments were identified and virtually screened at the binding pocket of target protein PARP1. Compounds that have high docking scores were used in molecular dynamics (MD) simulations. Free energy calculations were also performed to compare the predicted binding energies with known PARP1 inhibitors. The critical amino acid interactions of these newly identified hits in the binding pocket were also investigated in detail for better understanding of the structural features required for next generation PARP1 inhibitors. Thus, here together with combination of text-mining and integrated molecular modeling approaches, we identified novel piperazine-based hits against PARP1 enzyme.Communicated by Ramaswamy H. Sarma.