Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations

Modeling of FAK-PROTAC candidates from GSK2256098 analogs for targeted protein degradation

Protein inhibition via the traditional drug-designing approach has been shown to be an effective method for developing numerous small-molecule-based therapeutics. In the last decade, small inhibitors-guided protein degradation has arisen as an alternative method with the potential to fulfill the drug requirement for undruggable targets. Focal adhesion kinase (FAK) is a crucial modulator of the growth and spread of tumors, apart from it also acts as a scaffold for signaling of other proteins. FAK inhibitors have thus far had unsatisfactory results in clinical trials for cancer applications. Unlike prior attempts to control FAK expression, which were restricted to kinase domain inhibition with limited success in clinical research, protein degradation has the potential to concurrently disrupt FAK's kinase and scaffolding function. Recently, several FAK degraders were reported based on FAK Type I inhibitors using complex chemical synthesis approaches. Interestingly, recently a ternary complex was published revealing the binding mode of the FAK-PROTAC-E3 complex. This complex opens an avenue for the development of rational PROTAC design against FAK protein. Therefore, in the present study, we selected the most active Type I FAK inhibitor GSK2256098. The binding mode of the inhibitor prompted us to identify the most suitable analog for PROTAC design. We have identified a high-affinity analog that is suitable for PTOTAC design through the application of molecular docking (MD) and molecular dynamics simulations (MDS). Further based on the ternary FAK-PROTAC-E3 complex we build a binary complex FAK-Hit-E3-VHL between both proteins. Using the structure-based approach ten different potential FAK PROTACs candidates were designed. The stability of the complexes was analyzed using MDS and binding free energies were used to predict the binding affinity. Finally, based on desirable intermolecular interactions with the target and E3 ligase ProTAC4 was selected as the best candidate when compared with known FAK PROTAC GSK215.

Discovery of Novel Allosteric SHP2 Inhibitor Using Pharmacophore-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation, and Principal Component Analysis

SHP2 belongs to a cytoplasmic non-receptor protein tyrosine phosphatase class. It plays a critical role in the development of various cancers, such as gastric cancer, leukemia, and breast cancer. Thus, SHP2 has gained the interest of researchers as a potential target for inhibiting tumor cell proliferation in SHP2-dependent cancers. This study employed pharmacophore-based virtual screening, molecular docking, molecular dynamic (MD) simulations, MM/PBSA, and principal component analysis (PCA), followed by ADME prediction. We selected three potential hits from a collective database of more than one million chemical compounds. The stability of these selected hit-protein complexes was analyzed using 500 ns MD simulations and binding free energy calculations. The identified hits Lig_1, Lig_6, and Lig_14 demonstrated binding free energies of -161.49 kJ/mol, -151.28 kJ/mol, and -107.13 kJ/mol, respectively, compared to the reference molecule (SHP099) with a ΔG of -71.48 kJ/mol. Our results showed that the identified compounds could be used as promising candidates for selective SHP2 allosteric inhibition in cancer.

Epigenetic target identification strategy based on multi-feature learning

The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development.Communicated by Ramaswamy H. Sarma.

Computational insights into allosteric inhibition of focal adhesion kinase: A combined pharmacophore modeling and molecular dynamics approach

Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase that modulates integrin and growth factor signaling pathways and is implicated in cancer cell migration, proliferation, and survival. Over the past decade various, FAK kinase, FERM, and FAT domain inhibitors have been reported and a few kinase domain inhibitors are under clinical consideration. However, few of them were identified as multikinase inhibitors. In kinase drug design selectivity is always a point of concern, to improve selectivity allosteric inhibitor development is the best choice. The current research utilized a pharmacophore modeling (PM) approach to identify novel allosteric inhibitors of FAK. The all-available allosteric inhibitor bound 3D structures with PDB ids 4EBV, 4EBW, and 4I4F were utilized for the pharmacophore modeling. The validated PM models were utilized to map a database of 770,550 compounds prepared from ZINC, EXIMED, SPECS, ASINEX, and InterBioScreen, aiming to identify potential allosteric inhibitors. The obtained compounds from screening step were forwarded to molecular docking (MD) for the prediction of binding orientation inside the allosteric site and the results were evaluated with the known FAK allosteric inhibitor (REF). Finally, 14 FAK-inhibitor complexes were selected from the docking study and were studied under molecular dynamics simulations (MDS) for 500 ns. The complexes were ranked according to binding free energy (BFE) and those demonstrated higher affinity for allosteric site of FAK than REF inhibitors were selected. The selected complexes were further analyzed for intermolecular interactions and finally, three potential allosteric inhibitor candidates for the inhibition of FAK protein were identified. We believe that identified scaffolds may help in drug development against FAK as an anticancer agent.

Molecular dynamics of DNA repair and carcinogen interaction: Implications for cancer initiation, progression, and therapeutic strategies

The integrity of the genetic material in human cells is continuously challenged by environmental agents and endogenous stresses. Among these, environmental carcinogens are pivotal in initiating complex DNA lesions that can lead to malignant transformations if not properly repaired. This review synthesizes current knowledge on the molecular dynamics of DNA repair mechanisms and their interplay with various environmental carcinogens, providing a comprehensive overview of how these interactions contribute to cancer initiation and progression. We examine key DNA repair pathways including base excision repair, nucleotide excision repair, and double-strand break repair and their regulatory networks, highlighting how defects in these pathways can exacerbate carcinogen-induced damage. Further, we discuss how understanding these molecular interactions offers novel insights into potential therapeutic strategies. This includes leveraging synthetic lethality concepts and designing targeted therapies that exploit specific DNA repair vulnerabilities in cancer cells. By integrating recent advances in molecular biology, genetics, and oncology, this review aims to illuminate the complex landscape of DNA repair and carcinogen-induced carcinogenesis, setting the stage for future research and therapeutic innovations.

Recent Advances in the Discovery of Novel Drugs on Natural Molecules

Natural products (NPs) are always a promising source of novel drugs for tackling unsolved diseases [...].

Exploring isoindolin-1-ones as potential CDK7 inhibitors using cheminformatic tools

In women who die from cancer, breast cancer is the most common cause of death. The development of small molecular scaffolds as specific Cyclin-dependent kinase (CDK) inhibitors is a promising strategy in the discovery of anti-breast cancer drugs. Isoindolin-1-ones are heterocyclic compounds with useful therapeutic properties. In this study, a library of 48 isoindolinones has been virtually screened by molecular docking that showed high binding affinity up to - 10.1 kcal/mol and conventional hydrogen bonding interactions with active amino acid residues of CDK7. The molecular dynamics simulation (MDS), fragment molecular orbital (FMO), density functional theory (DFT), and pharmacokinetics studies of the best two docked scored ligands 7 and 14 have been studied. Examining the ligand root mean square deviation and hydrogen bonding occupancy of the 100 ns MDS trajectory, both ligands 7 and 14 showed docked pose stability. FMO calculations displayed that LYS139 and LYS41 are majorly contributing to the binding interactions with ligands 7 and 14 in the docked poses. DFT studies of ligands 7 and 14 showed high values of global softness and low values of global hardness and chemical potential thus displaying chemically reactive soft molecules and this influences their anti-cancer activity. Our hits exhibited superior qualities to known CDK7 inhibitors, according to the comprehensive pharmacokinetic parameters that were predicted. The results indicate that isoindolin-1-one moieties are good candidates for anti-cancer action and could serve as effective CDK7 inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00225-0.

Cancer therapy by cyclin-dependent kinase inhibitors (CDKIs): bench to bedside

A major characteristic of cancer is dysregulated cell division, which results in aberrant growth of cells. Consequently, medicinal targets that prevent cell division would be useful in the fight against cancer. The primary regulator of proliferation is a complex consisting of cyclin and cyclin-dependent kinases (CDKs). The FDA has granted approval for CDK inhibitors (CDKIs) to treat metastatic hormone receptor-positive breast cancer. Specifically, CDK4/6 CDKIs block the enzyme activity of CDK4 and CDK6. Unfortunately, the majority of first-generation CDK inhibitors, also known as pan-CDK inhibitors because they target multiple CDKs, have not been authorized for clinical use owing to their serious side effects and lack of selection. In contrast to this, significant advancements have been created to permit the use of pan-CDK inhibitors in therapeutic settings. Notably, the toxicity and negative consequences of pan-CDK inhibitors have been lessened in recent years thanks to the emergence of combination therapy tactics. Therefore, pan-CDK inhibitors have renewed promise for clinical use when used in a combination regimen. The members of the CDK family have been reviewed and their primary roles in cell cycle regulation were covered in this review. Next, we provided an overview of the state of studies on CDK inhibitors.

Recent advances in the area of plant-based anti-cancer drug discovery using computational approaches

Phytocompounds are a well-established source of drug discovery due to their unique chemical and functional diversities. In the area of cancer therapeutics, several phytocompounds have been used till date to design and develop new drugs. One of the desired interests of pharmaceutical companies and researchers globally is that new anti-cancer leads are discovered, for which phytocompounds can be considered a valuable source. Simultaneously, in recent years, the growth of computational approaches like virtual screening (VS), molecular dynamics (MD), pharmacophore modelling, Quantitative structure-activity relationship (QSAR), Absorption Distribution Metabolism Excretion and Toxicity (ADMET), network biology, and machine learning (ML) has gained importance due to their efficiency, reduced time-consuming nature, and cost-effectiveness. Therefore, the present review amalgamates the information on plant-based molecules identified for cancer lead discovery from in silico approaches. The mandate of this review is to discuss studies published in the last 5-6 years that aim to identify the phytomolecules as leads against cancer with the help of traditional computational approaches as well as newer techniques like network pharmacology and ML. This review also lists the databases and webservers available in the public domain for phytocompounds related information that can be harnessed for drug discovery. It is expected that the present review would be useful to pharmacologists, medicinal chemists, molecular biologists, and other researchers involved in the development of natural products (NPs) into clinically effective lead molecules.

In-silico bioprospecting of secondary metabolites from endophytic Streptomyces spp. against Magnaporthe oryzae, a cereal killer fungus

Rice blast disease, caused by Magnaporthe oryzae, is the most devastating cereal killer worldwide. Note that melanin pigment is an essential factor of M. oryzae virulence, thus fungicides interfering with melanin biosynthesizing enzymes would reduce the pathogenicity. Scytalone dehydratase (SDH) is the key target for commercial fungicides, like carpropamid, due to its role in the dehydration reaction of the fungal melanin pathway. However, a single-point mutation (V75M) in SDH elicits resistance to carpropamid. A lack of effective fungicides against this resistant strain expedited the quest for novel bioactive inhibitors. Currently, bacterial endophytes like Streptomyces have been heralded for synthesizing bioactive metabolites to protect plants from phytopathogens. The literature search led to the identification of 21 Streptomyces spp. symbionts of paddy that can suppress M. oryzae growth. An antiSMASH server was used to explore Streptomyces spp. gene clusters and found 4463 putative metabolites. Besides, 745 unique metabolites were subjected to a series of virtual screening techniques. Ideally, this process identified five potential SDH inhibitors. The docking result highlights that the metabolite pseudopyronine A interacted hydrophobically with both Val75 of SDHWT and Met75 of SDHV75M targets. Moreover, pseudopyronine A has a higher binding free energy with SDHWT (- 89.94 kcal/mol) and SDHV75M (- 71.95 kcal/mol). Interestingly, the pyranones scaffold of pseudopyronine A was reported for antifungal activity against phytopathogens. Dynamic behavior confirms that pseudopyronine A has excellent conformational states with both SDHWT and SDHV75M. Altogether, we hope that this study creates a new avenue for the discovery of novel phytopathogen inhibitors from endophytes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03859-7.

Insight into novel inhibitors from Sterculia urens against Cholera via pharmacoinformatics and molecular dynamics simulation approaches

The underdeveloped countries with large populations are facing a grave global threat in the form of cholera. Vibrio cholerae, the etiologic agent of Cholera has drawn attention recently due to antimicrobial resistance and resulting outbreaks that necessitates establishment of novel medications to counteract virulence and viability of the pathogen. Sterculia urens Roxb. (Malvaceae) is an ethnomedicinally important tree, which harbors a good number of bioactive phytocompounds. In the present study, 53 phytocompounds of S. urens were screened against the promising target ToxT of V. cholerae employing structure-based drug design approach that revealed three lead compounds, viz., 4,4,5,8-Tetramethylchroman-2-ol (-8.2 kcal/mol), Beta-Bisabolol (-8.2 kcal/mol) and Ledol (-8.7 kcal/mol) with satisfactory ADMET properties. Molecular dynamics simulation for 150 ns unveiled notable compactness and structural stability for the lead compounds considering RMSD, RMSF, Rg, MolSA, PSA and protein-ligand contacts parameters. Molecular mechanics-based MM/GBSA binding energy calculation revealed Beta-Bisabolol (-66.74 kcal/mol) to have better scores than 4,4,5,8-Tetramethylchroman-2-ol (-47.42 kcal/mol) and Ledol (-65.79 kcal/mol). Enzymes were mostly found as drug target class, and Nabilone was found as a structurally similar analog for 4,4,5,8-Tetramethylchroman-2-ol. These discoveries could aid in revealing new antibacterial medications targeting ToxT to combat Cholera.Communicated by Ramaswamy H. Sarma.

Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches

BACKGROUND

Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed.

METHODS

In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb's free energy landscape.

RESULTS

Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors.

Discovery of Pongol, the Furanoflavonoid, as an Inhibitor of CDK7/Cyclin H/MAT1 and Its Preliminary Structure-Activity Relationship

Natural products have been a great source of leads for cancer drug discovery. The cyclin-dependent kinases (CDKs) play a vital role in the initiation and progression of cancer. The CDK-activating kinase, CDK7/cyclin H/MAT1, has recently gained tremendous attention in targeted cancer drug discovery. Herein, we screened a small library of pure natural products in an ADP-Glo CDK7/H kinase assay that yielded a series of furano- and naphthoflavonoids among actives. Pongol (SBN-88), the hydroxy-substituted furanoflavonoid, inhibits CDK7/H as well as CDK9/T1 with IC₅₀ values of 0.93 and 0.83 μM, respectively, and >20-fold selectivity over CDK2/E1 (IC₅₀ > 20 μM). The molecular docking and molecular dynamics simulation revealed that the presence of phenolic -OH in pongol is vital for kinase inhibition, as its absence resulted in a significant loss in activity (e.g., lanceolatin B). The prime MM-GBSA calculations revealed the presence of strong lipophilic and H-bonding interactions of pongol with CDKs.

Pharmacophore-Oriented Identification of Potential Leads as CCR5 Inhibitors to Block HIV Cellular Entry

Cysteine-cysteine chemokine receptor 5 (CCR5) has been discovered as a co-receptor for cellular entry of human immunodeficiency virus (HIV). Moreover, the role of CCR5 in a variety of cancers and various inflammatory responses was also discovered. Despite the fact that several CCR5 antagonists have been investigated in clinical trials, only Maraviroc has been licensed for use in the treatment of HIV patients. This indicates that there is a need for novel CCR5 antagonists. Keeping this in mind, the present study was designed. The active CCR5 inhibitors with known IC₅₀ value were selected from the literature and utilized to develop a ligand-based common feature pharmacophore model. The validated pharmacophore model was further used for virtual screening of drug-like databases obtained from the Asinex, Specs, InterBioScreen, and Eximed chemical libraries. Utilizing computational methods such as molecular docking studies, molecular dynamics simulations, and binding free energy calculation, the binding mechanism of selected inhibitors was established. The identified Hits not only showed better binding energy when compared to Maraviroc, but also formed stable interactions with the key residues and showed stable behavior throughout the 100 ns MD simulation. Our findings suggest that Hit1 and Hit2 may be potential candidates for CCR5 inhibition, and, therefore, can be considered for further CCR5 inhibition programs.

Designing of kinase hinge binders: A medicinal chemistry perspective

Protein kinases are key regulators of cellular signaling and play a critical role in oncogenesis. Inhibitors of protein kinases are pursued by both industry and academia as a promising target for cancer therapy. Within the protein kinases, the ATP site has produced more than 40 FDA-approved drugs. The ATP site is broadly composed of a hinge region, gatekeeper residues, DFG-loop, ribose pocket, and other hydrophobic regions. The hinge region in the ATP site can be used for designing potent inhibitors. In this review, we discuss some representative studies that will highlight the interactions of heterocyclic compounds with hinge regions of different kinases like BRAF kinase, EGRF kinase, MAP kinase, and Mps1 kinase.

3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Dynamics Simulations for the Identification of Spleen Tyrosine Kinase Inhibitors

Spleen tyrosine kinase (SYK) is an essential mediator of immune cell signaling and has been anticipated as a therapeutic target for autoimmune diseases, notably rheumatoid arthritis, allergic rhinitis, asthma, and cancers. Significant attempts have been undertaken in recent years to develop SYK inhibitors; however, limited success has been achieved due to poor pharmacokinetics and adverse effects of inhibitors. The primary goal of this research was to identify potential inhibitors having high affinity, selectivity based on key molecular interactions, and good drug-like properties than the available inhibitor, fostamatinib. In this study, a 3D-QSAR model was built for SYK based on known inhibitor IC₅₀ values. The best pharmacophore model was then used as a 3D query to screen a drug-like database to retrieve hits with novel chemical scaffolds. The obtained compounds were subjected to binding affinity prediction using the molecular docking approach, and the results were subsequently validated using molecular dynamics (MD) simulations. The simulated compounds were ranked according to binding free energy (ΔG), and the binding affinity was compared with fostamatinib. The binding mode analysis of selected compounds revealed that the hit compounds form hydrogen bond interactions with hinge region residue Ala451, glycine-rich loop residue Lys375, Ser379, and DFG motif Asp512. Identified hits were also observed to form a desirable interaction with Pro455 and Asn457, the rare feature observed in SYK inhibitors. Therefore, we argue that identified hit compounds ZINC98363745, ZINC98365358, ZINC98364133, and ZINC08789982 may help in drug design against SYK.