Docking Score ML: Target-Specific Machine Learning Models Improving Docking-Based Virtual Screening in 155 Targets.

In drug discovery, molecular docking methods face challenges in accurately predicting energy. Scoring functions used in molecular docking often fail to simulate complex protein-ligand interactions fully and accurately leading to biases and inaccuracies in virtual screening and target predictions. We introduce the "Docking Score ML", developed from an analysis of over 200,000 docked complexes from 155 known targets for cancer treatments. The scoring functions used are founded on bioactivity data sourced from ChEMBL and have been fine-tuned using both supervised machine learning and deep learning techniques. We validated our approach extensively using multiple data sets such as validation of selectivity mechanism, the DUDE, DUD-AD, and LIT-PCBA data sets, and performed a multitarget analysis on drugs like sunitinib. To enhance prediction accuracy, feature fusion techniques were explored. By merging the capabilities of the Graph Convolutional Network (GCN) with multiple docking functions, our results indicated a clear superiority of our methodologies over conventional approaches. These advantages demonstrate that Docking Score ML is an efficient and accurate tool for virtual screening and reverse docking.

Discovery of novel CDK9 inhibitor with tridentate ligand: Design, synthesis and biological evaluation.

Cyclin-dependent kinase 9 (CDK9) plays a role in transcriptional regulation, which had become an attractive target for discovery of antitumor agent. In this work, beyond traditional CDK9 inhibitor with bidentate ligands in ATP binding domain, a series of novel CDK9 inhibitor with tridentate ligand were designed and synthesized. Surprisingly, this unique tridentate ligand structure endows better CDK9 inhibition selectivity compared to other CDK subtypes, and the lead candidate compound Z4-7a showed effective proliferation inhibition in HCT116 cells with acceptable pharmacokinetic properties. Research on the mechanism indicated that Z4-7a could induce apoptosis in the HCT116 cell line by inhibiting phosphorylation of RNA polymerase II at Ser2, which resulted in the inhibition of apoptosis-related genes and proteins expression. In brief, introduction of tridentate ligand might work as a promising strategy for the development of novel selective CDK9 inhibitor.

Structural simulation and selective inhibitor discovery study for histone demethylases KDM4E/6B from a computational perspective.

The methylation and demethylation of lysine and arginine side chains are fundamental processes in gene regulation and disease development. Histone lysine methylation, controlled by histone lysine methyltransferases (KMTs) and histone lysine demethylases (KDMs), plays a vital role in maintaining cellular homeostasis and has been implicated in diseases such as cancer and aging. This study focuses on two members of the lysine demethylase (KDM) family, KDM4E and KDM6B, which are significant in gene regulation and disease pathogenesis. KDM4E demonstrates selectivity for gene regulation, particularly concerning cancer, while KDM6B is implicated in inflammation and cancer. The study utilizes specific inhibitors, DA-24905 and GSK-J1, showcasing their exceptional selectivity for KDM4E and KDM6B, respectively. Employing an array of computational simulations, including sequence alignment, molecular docking, dynamics simulations, and free energy calculations, we conclude that although the binding cavities of KDM4E and KDM6B has high similarity, there are still some different crucial amino acid residues, indicating diverse binding forms between protein and ligands. Various interaction predominates when proteins are bound to different ligands, which also has significant effect on selective inhibition. These findings provide insights into potential therapeutic strategies for diseases by selectively targeting these KDM members.

Uncovering the selectivity mechanism of phosphodiesterase 7A/8A inhibitors through computational studies.

The expression of phosphodiesterase 7A (PDE7A) and phosphodiesterase 8A (PDE8) genes is integral to human signaling pathways, and the inhibition of PDE7A has been associated with the onset of various diseases, including effects on the immune system and nervous system. The development of PDE7 selective inhibitors can promote research on immune and nervous system diseases, such as multiple sclerosis, chronic inflammation, and autoimmune responses. PDE8A is expressed alongside PDE8B, and its inhibitory mechanism is still unclear. Studying the mechanisms of selective inhibitors against different PDE subtypes is crucial to prevent potential side effects, such as nausea and cardiac toxicity, and the sequence similarity of the two protein subtypes was 55.9%. Therefore, it is necessary to investigate the differences of both subtypes' ligand binding sites. Selective inhibitors of two proteins were chosen to summarize the reason for their selectivity through molecular docking, molecular dynamics simulation, alanine scanning mutagenesis, and MM-GBSA calculation. We found that Phe384PDE7A, Leu401PDE7A, Gln413PDE7A, Tyr419PDE7A, and Phe416PDE7A in the active site positively contribute to the selectivity towards PDE7A. Additionally, Asn729PDE8A, Phe767PDE8A, Gln778PDE8A, and Phe781PDE8A positively contribute to the selectivity towards PDE8A.

FaissMolLib: An efficient and easy deployable tool for ligand-based virtual screening.

Virtual screening-based molecular similarity and fingerprint are crucial in drug design, target prediction, and ADMET prediction, aiding in identifying potential hits and optimizing lead compounds. However, challenges such as lack of comprehensive open-source molecular fingerprint databases and efficient search methods for virtual screening are prevalent. To address these issues, we introduce FaissMolLib, an open-source virtual screening tool that integrates 2.8 million compounds from ChEMBL and ZINC databases. Notably, FaissMolLib employs the highly efficient Faiss search algorithm, outperforming the Tanimoto algorithm in identifying similar molecules with its tighter clustering in scatter plots and lower mean, standard deviation, and variance in key molecular properties. This feature enables FaissMolLib to screen 2.8 million compounds in just 0.05 seconds, offering researchers an efficient, easily deployable solution for virtual screening on laptops and building unique compound databases. This significant advancement holds great potential for accelerating drug discovery efforts and enhancing chemical data analysis. FaissMolLib is freely available at http://liuhaihan.gnway.cc:80. The code and dataset of FaissMolLib are freely available at https://github.com/Superhaihan/FiassMolLib.

Identification of a Novel Selective CDK9 Inhibitor for the Treatment of CRC: Design, Synthesis, and Biological Activity Evaluation.

Cyclin-dependent kinase 9 (CDK9) is a member of the transcription CDK subfamily. In this work, we preliminarily demonstrated the feasibility of CDK9 as a potent target of treatment for colorectal cancer, and a series of novel CDK9 inhibitors were rationally designed and synthesized based on the structure of AZD5438 (a pan CDKs inhibitor reported by AstraZeneca). A novel selective CDK9 inhibitor named CLZX-205, which possessed significant CDK9 inhibitory activity (IC50 = 2.9 nM) with acceptable pharmacokinetic properties and antitumor efficacy in vitro and in vivo, was developed. Research on the mechanism indicated that CLZX-205 could induce apoptosis in the HCT116 cell line by inhibiting phosphorylation of RNA polymerase II at Ser2, which resulted in the inhibition of apoptosis-related genes and proteins expression, and these results were validated at the cellular and tumor tissue levels. Currently, CLZX-205 is undergoing further research as a promising candidate for CRC treatment.

Insights into the selective mechanism of PDE2/9a inhibitors from silico aspects.

The selective design of competitive enzyme inhibitors is an extremely difficult task but necessary work for certain types of systems, such as the phosphodiesterase (PDE) system addressed in this article. In the PDE family, PDE2A and PDE9 respectively target the central nervous system and heart failure, and share many conserved amino acids at their binding sites. Therefore, gaining a deep understanding of the selective mechanisms of PDE2A/9A is crucial for designing highly selective drugs. In this study, various computer-aided drug design (CADD) methods, including molecular docking, molecular dynamics simulations (MD), and binding free energy calculations, are employed to explore the selective mechanisms of PDE2A/9A. Overall, our research results indicate a selective design strategy for PDE2A, which involves incorporating hydrophobic or aromatic moieties into the molecular structure to better accommodate the hydrophobic pocket of PDE2A. Additionally, it is recommended to introduce functional groups capable of forming connections with selective residues, such as Phe830 and Gln812 for PDE2A, or Ala452 and Tyr424 for PDE9A, to enhance the selectivity of inhibitors targeting PDE2A/9A. This achievement is anticipated to pave the way for the development of innovative and selective small molecules targeting PDE2A/9A.Communicated by Ramaswamy H. Sarma.

Insights into ß3-adrenoceptor agonism through comprehensive in silico investigation.

Research onß3-AR, the new member of the adrenoceptor family, is in its infancy and few ß3-AR agonists have been approved for marketing to date. Meanwhile, ß3-AR exhibited obvious species differences in pharmacological properties, such as between human and animals, however, the 3D structure of human ß3-AR has not been published, which makes it difficult to understand the interaction between human ß3-AR and its agonists. Herein, binding patterns of ß3-AR agonists are explored starting from the Alphafold predicted structural model, and the obtained model was optimized by using molecular dynamics simulations. Moreover, the human ß3-AR and its agonists were subjected to molecular docking, dynamics simulations, binding free energy calculations and pharmacophore modeling to elucidate the characteristics of human ß3-AR activity pockets and agonist conformational relationships, including a hydrophobic group, a positively charged group as well as two hydrogen-bonded donors, which provide comprehensive insights into the interactions between human ß3-AR and its agonists.

Structural requirement of RARγ agonism through computational aspects.

CONTEXT: RARγ is a therapeutic target for many skin diseases and has potential in cancer treatment. In the current study, we put forward a comprehensive structure-activity relationship study of third and fourth generations of RARγ agonists, addressing multiple crystal structures of RARγ complexes and approved drugs. Adapalene and Trifarotene, through hybrid strategies including protein contacts Atlas analysis, molecular docking, dynamics simulations, MM-GBSA, ASM, and pharmacophore modeling. Our result revealed crucial amino acids Arg267, Ser278, Phe288, Phe230, Met272, Leu271, and Leu268 within the RARγ pocket, as well as pharmacophore features such as two hydrophobic groups, two aromatic rings, and negative ionic features, which are essential for the binding of RARγ agonists. Based on this study, the binding mechanism of RARγ agonists was elucidated, which will be helpful for the rational design of new RARγ agonists for skin diseases and cancer treatment. METHODS: In this study, Schrödinger suite 2021-2 with OPLS_4 force field, Discovery Studio program 3.0, LigandScout 4.3, and PyMOL are utilized in the investigation.

Selectivity mechanism of GRK2/5 inhibition through in silico investigation.

As two representative isoforms of G protein-coupled receptor kinases family, the largest known membrane receptor family, GRK2 and GRK5 are ubiquitously distributed in human heart, brain, lung, kidney, skeletal muscle and other tissues. GRK2 and GRK5 have common functions implicated in the regulation of heart failure, though GRK5 has also been involved in diseases like hypertension, cancer, diabetes and Alzheimer's disease. Therefore, to clarify the selectivity mechanism towards GRK2 and GRK5 will be of great significance for the discovery of effective and selective inhibitors. To this end, the structures and chemical properties of key residues were analyzed among GRK2 and GRK5 derived from their respective protein crystal structures. Furthermore, a combination of multiple computational strategies, including sequence superposition, receptor-ligand docking, molecular dynamics, MM-GBSA calculation, QM/MM approach and pharmacological modeling, were integrated to validated and elucidate their unique binding modes towards highly selective inhibitors. In addition, the specific amino acid distribution within the GRK2/5 target site is also analyzed in this paper, which can guide future research and development of selective inhibitors in a more targeted manner. Overall, our study comprehensively clarifies the selectivity mechanism of GRK2/5 inhibition, thereby providing guidance for further rational design of selective inhibitors targeting GRK2/5.

Selectivity mechanism of muscarinic acetylcholine receptor antagonism through in silico investigation.

Structures of muscarinic acetylcholine receptors illustrate the strikingly high degree of homology of the residues among isoforms, thus leading to difficulty in achieving subtype selectivity when targeting these receptors and causing undesired side effects when treating the corresponding diseases. Considering the urgent need for more selective and potency therapies, this study is aimed at revealing the selectivity mechanism against M4/5 via in silico strategies, revealing crucial molecular interactions such as hydrogen bonds and pi-cation interaction formed between the key residues TYR416, ASN417, and TRP435 of M4, respectively, hydrophobic pocket formed by the key residues, especially CYS484 of M5. Besides, the water around TYR416M4 and ASN459M5, which can be replaced by substituent groups which can form the hydrogen bond interaction network by simulated bridging water and the water around ASP112M4, whose replacement maybe not contribute to the increase in binding affinity of the compound, may affect the inhibitory selectivity among M4/5 in the aspect of the solvent. Moreover, from the point of inhibitors, compounds with a positively ionizable group could selectively bind to M4 receptors, while hydrophobic molecules may bind preferably to M5. We believe that the current study would provide a basis for the design of subsequent M4/5 selective antagonists.

Selectivity mechanism of BCL-XL/2 inhibition through in silico investigation.

The BCL-XL protein is among the most important members of the anti-apoptotic subfamily of the BCL-2 protein family, and is currently a promising new target for anti-tumor drug research. However, the BCL-XL/2 proteins have similar structures and functions, which could lead to undesirable side effects because of inhibitors that can bind to both BCL-XL and BCL-2. Therefore, it is crucial to expound on the structural basis of the selective mechanism towards BCL-XL/2 inhibition. In the current study, we employed hybrid computational methods including molecular docking and dynamics simulation, MM/GBSA energy calculation, alanine scanning mutagenesis and Hirshfeld surface analysis to comprehensively reveal the selectivity mechanism towards BCL-XL/2 from multiple perspectives, revealing the significant effects of the BCL-XL residues SER106 and LEU108 as well as the BCL-2 residue ASP103 on the inhibitory selectivity. Overall, our findings provide useful references for the rational design of BCL-XL/2 selective inhibitors with better affinity.

Stable H-bond networks are crucial for selective CDK4 inhibition revealed from comprehensive in silico investigation.

CDK1 and CDK4 are highly similar isoforms but with apparently diverse cellular functions, which makes it fundamental to discover selective CDK4 inhibitors that could accurately control the process of cell cycle of the specific organization so as to restore normal physiological state. In current research, interaction modes of CDK1 and CDK4 inhibitors were investigated through combined in silico strategies to elucidate the selectivity mechanism against CDK4 over CDK1, revealing that H-bond networks formed with key amino acids such as LYS33 and LEU83 of CDK1 and VAL93 of CDK4 are crucial for CDK4 selective inhibition, which would provide a theoretical basis for the design of selective CDK4 inhibitors.

Exploring the Resistance Mechanisms of Distal D835V Mutation in FLT3 to Inhibitors.

Objective: FMS-like tyrosine kinase 3 (FLT3) is an attractive therapeutic target in acute myeloid leukemia. Unfortunately, secondary FLT3 mutations that developed resistance to inhibitors have become a severe problem. Specifically, ASP-835 (D835F/H/V/Y) mutant within the activation loop of FLT3 is the most commonly encountered drug-resistant and observed secondary FLT3 mutations. In this study, we carried out a set of computational approaches to explore how this mutation influenced the conformation and dynamics of DFG motif in a manner altered inhibitors' susceptibility. Methods: Molecular dynamics (MD) simulation, dynamic cross-correlation (DCC) analysis, surface area (SASA), binding free energy (MM-GBSA), and structural analysis were used to compare the severe and minor D835V mutation-induced impact to sorafenib and crenolanib, respectively. Results: The A-loop of the FLT3 protein may experience conformational change in the presence of the resistant mutation, which were mainly positioned at PHE-830. The protein-inhibitor interactions displayed that the motions of PHE-830 influenced that of sorafenib, but not to crenolanib. Conclusions: These findings indicated that the structural impact brought by D835V mutation should be considered in designing novel drugs to overcome resistance to FLT3-D835V.

Molecular recognition-driven supramolecular nanoassembly of a hydrophobic uracil prodrug and hydrophilic cytarabine for precise combination treatment of solid and non-solid tumors.

Combination chemotherapy has shown distinct therapeutic advantages over monotherapy in clinical cancer treatment, especially for two chemotherapeutic drugs with different mechanisms of action. However, how to achieve efficient co-delivery of two or more drugs with different physicochemical and pharmacokinetic properties for synergistic therapy is still a huge challenge. In particular, it is even more difficult to efficiently co-deliver a hydrophilic drug and a hydrophobic drug into one nanosystem. Herein, inspired by the natural Watson-Crick base pair molecular recognition in nucleic acids, a reduction-sensitive uracil prodrug of doxorubicin (U-SS-DOX) is synthesized and performs supramolecular co-assembly with cytarabine (Ara-C). Interestingly, the hydrophilic Ara-C molecules could readily co-assemble with U-SS-DOX, and multiple hydrogen bonds are found in the nanoassembly with an ultra-high drug loading rate. Moreover, 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR) is used as a fluorescent probe to investigate the pharmacokinetics of U : C NPs. It turns out that the DiR-labeled U : C NPs significantly prolong the systemic circulation and promote the tumor-specific accumulation of DiR when compared with DiR solution. Furthermore, the supramolecular nanoassembly demonstrates potent satisfactory therapeutic effects in treating both solid and non-solid tumors in vivo. This study provides a novel molecular co-assembly nanoplatform for efficient co-delivery of hydrophilic and hydrophobic drugs.

Identification of raloxifene as a novel α-glucosidase inhibitor using a systematic drug repurposing approach in combination with cross molecular docking-based virtual screening and experimental verification.

α-Glucosidase is a promising target for the treatment of diabetes. Drug repurposing can increase the chances of discovering an active inhibitor. Therefore, this study aimed to identify potential α-glucosidase inhibitor using drug repurposing and in silico strategies. We identified critical amino acid residues of the three α-glucosidase proteins. Based on cross molecular docking studies of three α-glucosidase proteins and drugs in the FDA database, we screened hits with the favorable binding affinities and modes targeting the three proteins. Subsequently, an in vitro activity assay showed that raloxifene was an excellent inhibitor of α-glucosidase. Moreover, molecular dynamics simulations of raloxifene and three proteins were performed to assess the stability of the protein-hit systems in physiological conditions and clarify protein-hit interactions. We also performed the binding free energy calculation, Hirshfeld surface and alanine scanning mutagenesis analyses. These results demonstrated that binding between raloxifene and the three proteins was stable, and the critical amino acid residues of the three proteins formed stable contacts with raloxifene. The molecular mechanisms agree well with its activity, reinforcing that raloxifene is a candidate α-glucosidase inhibitor. Our study smoothes the path for the development of novel a-glucosidase inhibitors with high efficacy and low toxicity for the treatment of diabetes.

Selectivity mechanism of phosphodiesterase isoform inhibitor through in silico investigations.

Understanding the selectivity mechanism of inhibitors towards homology proteins helps to design selective candidates. Phosphodiesterase (PDE) family members act in the degradation of cAMP and cGMP, among which some isoforms such as PDE9A are attracting interest for Alzheimer's disease treatment, while PDE10A is used as target for treating schizophrenia. In this study, computational methods were used to investigate the major features of PDE9A/10A, with the purpose to provide deep understanding of the molecular mechanism of selective inhibition towards these two isoforms. Our result revealed that two conserved residues Gln453 and Phe456 were proven to be crucial for the binding affinity and inhibitory selectivity of PDE9A inhibitors. In addition, the high-affinity PDE9A inhibitors always interact with the conservative hydrophobic pocket as well as Tyr424 and Ala452 of PDE9A, while PDE10A selective inhibitors need to have two hydrophobic groups and two hydrogen bond donors to interact with the conservative Tyr693, Gln726, and Phe729 of PDE10A. This study provides valuable insights into the underlying mechanism of selective inhibition targeting PDE9A and PDE10A, for further search for potent and highly selective PDE9A/10A inhibitors.

Perspective of structural flexibility on selective inhibition towards CYP1B1 over CYP1A1 by α-naphthoflavone analogs.

Research on action selectivity between CYP1A1 and CYP1B1 is particularly valuable for cancer chemoprevention and chemotherapy. However, they share a very close similarity in their ligand-binding pockets that α-naphthoflavone (ANF) is the co-crystal ligand for both isoforms, which poses a major challenge in revealing their selectivity mechanism. Therefore, three selective CYP1B1 inhibitors derived from ANF were selected to illustrate the structural basis for the selectivity between the two isoforms via a comprehensive computational strategy. It was found that the sustainability of the π-π stacking interactions with the phenylalanine residues of the two isoforms, namely, Phe123, Phe224, and Phe258 for CYP1A1, and Phe134, Phe231, and Phe268 for CYP1B1, played a crucial role in determining the selectivity of ligands with a classic aromatic conjugation system like ANF and its derivatives for CYP1B1 versus CYP1A1. Of note, the structural flexibility of the corresponding protein domains mainly orchestrated the sustainability of the corresponding π-π stacking interactions, thereby determining the binding selectivity. Therefore, the structure modification of naphthoflavone lead compounds into preferable binding configurations to satisfy the π-π stacking interactions of the key phenylalanine residues within CYP1B1 would be an inspiring strategy devised to improve the inhibitory selectivity towards CYP1B1. Collectively, this study revealed valuable insight into understanding the selective mechanism between CYP1A1 and CYP1B1 from the perspective of structural flexibility, which sheds light on the future rational design of CYP1B1 selective inhibitors.

Rational design of selective HDAC2 inhibitors for liver cancer treatment: computational insights into the selectivity mechanism through molecular dynamics simulations and QM/MM calculations.

The rational design of selective histone deacetylase 2 (HDAC2) inhibitors is beneficial for the therapeutic treatment of liver cancer, though HDAC2 is highly homologous to HDAC8, which may lead to undesired side effects due to the pan-inhibition towards HDAC2 and HDAC8. To clarify the structural basis of selective inhibition towards HDAC2 over HDAC8, we utilized multiple in silico strategies, including sequence alignment, structural comparison, molecular docking, molecular dynamics simulations, free energy calculations, alanine scanning mutagenesis, pharmacophore modeling, protein contacts atlas analysis and QM/MM calculations to study the binding patterns of HDAC2/8 selective inhibitors. Through the whole process described above, it is found that although HDAC2 has conserved GLY154 and PHE210 that also exist within HDAC8, namely GLY151 and PHE208, the two isoforms exhibit diverse binding modes towards their inhibitors. Typically, HDAC2 inhibitors interact with the Zn2+ ions through the core chelate group, while HDAC8 inhibitors adopt a bent conformation within the HDAC8 pocket that inclines to be in contact with the Zn2+ ions through the terminal hydroxamic acid group. In summary, our data comprehensively elucidate the selectivity mechanism towards HDAC2 over HDAC8, which would guide the rational design of selective HDAC2 inhibitors for liver cancer treatment.

CK-3, A Novel Methsulfonyl Pyridine Derivative, Suppresses Hepatocellular Carcinoma Proliferation and Invasion by Blocking the PI3K/AKT/mTOR and MAPK/ERK Pathways.

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis that highly expresses phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase (ERK). The PI3K/AKT/mTOR and MAPK/ERK signaling pathways play a crucial role in HCC tumor formation, cell cycle, apoptosis and survival. However, no effective targeted therapies against these pathways is available, mainly due to the extensive and complex negative feedback loops between them. Here we used CK-3, a dual blocker of the PI3K/AKT/mTOR and MAPK/ERK pathways, against HCC cell lines to verify its anti-tumor activity in vitro. CK-3 exhibited cytotoxic activity against HCC, as demonstrated with MTT and colony formation assays. The anti-metastatic potential of CK-3 was demonstrated with wound healing and cell invasion assays. The ability of CK-3 to block both the PI3K/AKT/mTOR and MAPK/ERK pathways was also confirmed. CK-3 induced the apoptosis of Hep3B cells, while Bel7402 cells died via mitotic catastrophe (MC). Oral administration of CK-3 also inhibited the subcutaneous growth of BEL7402 cells in nude mice. Simultaneous PI3K/AKT/mTOR and MAPK/ERK pathway inhibition with CK-3 may be superior to single pathway monotherapies by inhibiting their feedback-regulation, and represents a potential treatment for HCC.