Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell development and activation. Dysregulation of LCK signaling has been demonstrated to drive the oncogenesis of T-cell acute lymphoblastic leukemia (T-ALL), thus providing a therapeutic target for leukemia treatment. In this study, we introduced a sophisticated virtual screening strategy combined with biological evaluations to discover potent LCK inhibitors. Our initial approach involved utilizing the PLANET algorithm to assess and contrast various scoring methodologies suitable for LCK inhibitor screening. After effectively evaluating PLANET, we progressed to devise a virtual screening workflow that synergistically combines the strengths of PLANET with the capabilities of Schrödinger's suite. This integrative strategy led to the efficient identification of four potential LCK inhibitors. Among them, compound 1232030-35-1 stood out as the most promising candidate with an IC50 of 0.43 nM. Further in vitro bioassays revealed that 1232030-35-1 exhibited robust antiproliferative effects on T-ALL cells, which was attributed to its ability to suppress the phosphorylations of key molecules in the LCK signaling pathway. More importantly, 1232030-35-1 treatment demonstrated profound in vivo antileukemia efficacy in a human T-ALL xenograft model. In addition, complementary molecular dynamics simulations provided deeper insight into the binding kinetics between 1232030-35-1 and LCK, highlighting the formation of a hydrogen bond with Met319. Collectively, our study established a robust and effective screening strategy that integrates AI-driven and conventional methodologies for the identification of LCK inhibitors, positioning 1232030-35-1 as a highly promising and novel drug-like candidate for potential applications in treating T-ALL.

Discovery and characterization of novel FGFR1 inhibitors in triple-negative breast cancer via hybrid virtual screening and molecular dynamics simulations.

The overexpression of FGFR1 is thought to significantly contribute to the progression of triple-negative breast cancer (TNBC), impacting aspects such as tumorigenesis, growth, metastasis, and drug resistance. Consequently, the pursuit of effective inhibitors for FGFR1 is a key area of research interest. In response to this need, our study developed a hybrid virtual screening method. Utilizing KarmaDock, an innovative algorithm that blends deep learning with molecular docking, alongside Schrödinger's Residue Scanning. This strategy led us to identify compound 6, which demonstrated promising FGFR1 inhibitory activity, evidenced by an IC50 value of approximately 0.24 nM in the HTRF bioassay. Further evaluation revealed that this compound also inhibits the FGFR1 V561M variant with an IC50 value around 1.24 nM. Our subsequent investigations demonstrate that Compound 6 robustly suppresses the migration and invasion capacities of TNBC cell lines, through the downregulation of p-FGFR1 and modulation of EMT markers, highlighting its promise as a potent anti-metastatic therapeutic agent. Additionally, our use of molecular dynamics simulations provided a deeper understanding of the compound's specific binding interactions with FGFR1.

Discovery of potent CSK inhibitors through integrated virtual screening and molecular dynamic simulation.

Oncogenic overexpression or activation of C-terminal Src kinase (CSK) has been shown to play an important role in triple-negative breast cancer (TNBC) progression, including tumor initiation, growth, metastasis, drug resistance. This revelation has pivoted the focus toward CSK as a potential target for novel treatments. However, until now, there are few inhibitors designed to target the CSK protein. Responding to this, our research has implemented a comprehensive virtual screening protocol. By integrating energy-based screening methods with AI-driven scoring functions, such as Attentive FP, and employing rigorous rescoring methods like Glide docking and molecular mechanics generalized Born surface area (MM/GBSA), we have systematically sought out inhibitors of CSK. This approach led to the discovery of a compound with a potent CSK inhibitory activity, reflected by an IC50 value of 1.6 nM under a homogeneous time-resolved fluorescence (HTRF) bioassay. Subsequently, molecule 2 exhibits strong growth inhibition of MD anderson - metastatic breast (MDA-MB) -231, Hs578T, and SUM159 cells, showing a level of growth inhibition comparable to that observed with dasatinib. Treatment with molecule 2 also induced significant G1 phase accumulation and cell apoptosis. Furthermore, we have explored the explicit binding interactions of the compound with CSK using molecular dynamics simulations, providing valuable insights into its mechanism of action.

Identification and assessment of new PIM2 inhibitors for treating hematologic cancers: A combined approach of energy-based virtual screening and machine learning evaluation.

PIM2, part of the PIM kinase family along with PIM1 and PIM3, is often overexpressed in hematologic cancers, fueling tumor growth. Despite its significance, there are no approved drugs targeting it. In response to this challenge, we devised a thorough virtual screening workflow for discovering novel PIM2 inhibitors. Our process includes molecular docking and diverse scoring methods like molecular mechanics generalized born surface area, XGBOOST, and DeepDock to rank potential inhibitors by binding affinities and interaction potential. Ten compounds were selected and subjected to an adequate evaluation of their biological activity. Compound 2 emerged as the most potent inhibitor with an IC50 of approximately 135.7 nM. It also displayed significant activity against various hematological cancers, including acute myeloid leukemia, mantle cell lymphoma, and anaplastic large cell lymphoma (ALCL). Molecular dynamics simulations elucidated the binding mode of compound 2 with PIM2, offering insights for drug development. These results highlight the reliability and efficacy of our virtual screening workflow, promising new drugs for hematologic cancers, notably ALCL.

LCK-SafeScreen-Model: An Advanced Ensemble Machine Learning Approach for Estimating the Binding Affinity between Compounds and LCK Target.

The lymphocyte-specific protein tyrosine kinase (LCK) is a critical target in leukemia treatment. However, potential off-target interactions involving LCK can lead to unintended consequences. This underscores the importance of accurately predicting the inhibitory reactions of drug molecules with LCK during the research and development stage. To address this, we introduce an advanced ensemble machine learning technique designed to estimate the binding affinity between molecules and LCK. This comprehensive method includes the generation and selection of molecular fingerprints, the design of the machine learning model, hyperparameter tuning, and a model ensemble. Through rigorous optimization, the predictive capabilities of our model have been significantly enhanced, raising test R2 values from 0.644 to 0.730 and reducing test RMSE values from 0.841 to 0.732. Utilizing these advancements, our refined ensemble model was employed to screen an MCE -like drug library. Through screening, we selected the top ten scoring compounds, and tested them using the ADP-Glo bioactivity assay. Subsequently, we employed molecular docking techniques to further validate the binding mode analysis of these compounds with LCK. The exceptional predictive accuracy of our model in identifying LCK inhibitors not only emphasizes its effectiveness in projecting LCK-related safety panel predictions but also in discovering new LCK inhibitors. For added user convenience, we have also established a webserver, and a GitHub repository to share the project.

Advances in research on 3C-like protease (3CLpro) inhibitors against SARS-CoV-2 since 2020.

COVID-19 caused by SARS-CoV-2 in late 2019 is still threatening global human health. Although some vaccines and drugs are available in the market, controlling the spread of the SARS-CoV-2 virus remains a huge challenge. 3C-like protease (3CLpro) is a highly conserved key protease for SARS-CoV-2 replication, and no relevant homologous protein with a similar cleavage site to 3CLpro has been identified in humans, highlighting that development of 3CLpro inhibitors exhibits great promise for treatment of COVID-19. In this review, the authors describe the structure and function of 3CLpro. To better understand the characteristics of SARS-CoV-2 3CLpro inhibitors, the SARS-CoV-2 3CLpro inhibitors reported since 2020 are classified into peptidomimetic covalent inhibitors, non-peptidomimetic covalent inhibitors and non-covalent small molecule inhibitors, and the representative inhibitors, their biological activities and binding models are highlighted. Collectively, we hope that all the information presented here will provide new insights into the design and development of more effective 3CLpro inhibitors against SARS-CoV-2 as novel anti-coronavirus drugs.

Discovery of potential WEE1 inhibitors via hybrid virtual screening.

G2/M cell cycle checkpoint protein WEE1 kinase is a promising target for inhibiting tumor growth. Although various WEE1 inhibitors have entered clinical investigations, their therapeutic efficacy and safety profile remain unsatisfactory. In this study, we employed a comprehensive virtual screening workflow, which included Schrödinger-Glide molecular docking at different precision levels, as well as the utilization of tools such as MM/GBSA and Deepdock to predict the binding affinity between targets and ligands, in order to identify potential WEE1 inhibitors. Out of ten molecules screened, 50% of these molecules exhibited strong inhibitory activity against WEE1. Among them, compounds 4 and 5 showed excellent inhibitory activity with IC50 values of 1.069 and 3.77 nM respectively, which was comparable to AZD1775. Further investigations revealed that compound 4 displayed significant anti-proliferative effects in A549, PC9, and HuH-7 cells and could also induce apoptosis and G1 phase arrest in PC9 cells. Additionally, molecular dynamics simulations unveiled the binding details of compound 4 with WEE1, notably the crucial hydrogen bond interactions formed with Cys379. In summary, this comprehensive virtual screening workflow, combined with in vitro testing and computational modeling, holds significant importance in the development of promising WEE1 inhibitors.

Advances of biphenyl small-molecule inhibitors targeting PD-1/PD-L1 interaction in cancer immunotherapy.

Immunotherapy inhibiting the programmed death-1/programmed death ligand-1 (PD-1/PD-L1) interaction has emerged as one of the most attractive cancer treatment strategies. So far, the clinically used PD-1/PD-L1 inhibitors are monoclonal antibodies, but monoclonal antibodies have several limitations, such as poor pharmacokinetic properties, unchecked immune responses and high production cost. The development of small-molecule inhibitors targeting PD-1/PD-L1 interaction is showing great promise as a potential alternative or complementary therapeutic approach of monoclonal antibodies. In this article, the authors classify the reported biphenyl small-molecule inhibitors into symmetrical and asymmetrical types based on their structural features and further review their representative inhibitors and biological activities, as well as the binding models for providing insight into further exploration of more potent biphenyl small-molecule inhibitors targeting PD-1/PD-L1 interaction.

Discovery of quinazoline derivatives as novel small-molecule inhibitors targeting the programmed cell death-1/programmed cell death-ligand 1 (PD-1/PD-L1) interaction.

Development of small molecule PD-1/PD-L1 inhibitors as a novel immunotherapy strategy exhibits great promise. Herein, a novel series of quinazoline derivatives were designed, synthesized and their inhibitory activity against the PD-1/PD-L1 interaction was evaluated through a homogenous time-resolved fluorescence (HTRF) assay. Among them, the compound 39 exhibited the most potent inhibitory activity with an IC50 value of 1.57 nM. Furthermore, the cellular level assays revealed that 39 could inhibit the PD-1/PD-L1 interaction and restore T-cell function, and showed low toxicity on the PBMCs. In addition, the structure-activity relationships (SARs) of the novel quinazoline derivatives were explored and the binding mode of 39 with dimeric PD-L1 was analyzed by molecular docking. This work demonstrates that incorporation of pyrimidine group between the 2 and 3-positions of the biphenyl structure is an effective strategy for designing novel and more potent small molecule PD-1/PD-L1 inhibitors, and 39 can be regarded as a promising lead compound for further investigation.

Identification and biological evaluation of novel benzothiazole derivatives bearing a pyridine-semicarbazone moiety as apoptosis inducers via activation of procaspase-3 to caspase-3.

Three series of compounds were designed, synthesized and evaluated for their in vitro anticancer activity against a procaspase-3 over-expression cancer cell line (U937) and a procaspase-3 no-expression cancer cell line (MCF-7) to rule out off-target effects. Biological evaluation led to the identification of a series of benzothiazole derivatives bearing a pyridine-semicarbazone moiety, 8j and 8k, with promising anticancer activity and remarkable selectivity. Further mechanism studies revealed that compounds 8j and 8k could induce apoptosis of cancer cells by activating procaspase-3 to caspase-3, and compound 8k exhibited the strongest procaspase-3 activation activity. Structure-activity relationships (SARs) revealed that the presence of benzothiazole and an N,N,O-donor set is crucial for the anticancer activity and selectivity, and reducing the electron density of the N,N,O-donor set results in a dramatic decline in the anticancer activity and selectivity. Furthermore, toxicity evaluation (zebrafish) in vivo and metabolic stability studies (human, rat and mouse liver microsomes) were performed to provide reliable guidance for further PK/PD studies in vivo.