How Does Chirality Determine the Selective Inhibition of Histone Deacetylase 6? A Lesson from Trichostatin A Enantiomers Based on Molecular Dynamics

Discovery of Novel Small Molecule Dual Inhibitor Targeting Toll-Like Receptors 7 and 9

The aberrant secretion of proinflammatory cytokines by immune cells is the principal cause of inflammatory diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Toll-like receptor 7 (TLR7) and TLR9, sequestered to the endosomal compartment of dendritic cells and macrophages, are closely associated with the initiation and progression of these diseases. Therefore, the development of drugs targeting dysregulated endosomal TLRs is imperative to mitigate systemic inflammation. Here, we applied the principles of computer-aided drug discovery to identify a novel low-molecular-weight compound, TLR inhibitory compound 10 (TIC10), and its potent derivative (TIC10g), which demonstrated dual inhibition of TLR7 and TLR9 signaling pathways. Compared to TIC10, TIC10g exhibited a more pronounced inhibition of the TLR7- and TLR9-mediated secretion of the proinflammatory cytokine tumor necrosis factor-α in a mouse macrophage cell line and mouse bone marrow dendritic cells in a concentration-dependent manner. While TIC10g slightly prevented TLR3 and TLR8 activation, it had no impact on cell surface TLRs (TLR1/2, TLR2/6, TLR4, or TLR5), indicating its selectivity for TLR7 and TLR9. Additionally, mechanistic studies suggested that TIC10g interfered with TLR9 activation by CpG DNA and suppressed downstream pathways by directly binding to TLR9. Western blot analysis revealed that TIC10g downregulated the phosphorylation of the p65 subunit of nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) and mitogen-activated protein kinases (MAPKs), including extracellular-signal-regulated kinase, p38-MAPK, and c-Jun N-terminal kinase. These findings indicate that the novel ligand, TIC10g, is a specific dual inhibitor of endosomal TLRs (TLR7 and TLR9), disrupting MAPK- and NF-κB-mediated proinflammatory gene expression.

Chalcone derivatives' interaction with human serum albumin and cyclooxygenase-2

Chalcone derivatives are an extremely valuable class of compounds, primarily due to the keto-ethylenic group, CO-CH[double bond, length as m-dash]CH-, they contain. Moreover, the presence of a reactive α,β-unsaturated carbonyl group confers upon them a broad range of pharmacological properties. Recent developments in heterocyclic chemistry have led to the synthesis of chalcone derivatives, which have been biologically investigated for their activity against certain diseases. In this study, we investigated the binding of new chalcone derivatives with COX-2 (cyclooxygenase-2) and HSA (Human Serum Albumin) using spectroscopic and molecular modeling studies. COX-2 is commonly found in cancer and plays a role in the production of prostaglandin E (2), which can help tumors grow by binding to receptors. HSA is the most abundant protein in blood plasma, and it transports various compounds, including hormones and fatty acids. The conformation of chalcone derivatives in the HSA complex system was established through fluorescence steady and excited state spectroscopy techniques and FTIR analyses. To gain a more comprehensive understanding, molecular docking, and dynamics were conducted on the target protein (COX-2) and transport protein (HSA). In addition, we conducted density-functional theory (DFT) and single-point DFT to understand intermolecular interaction in protein active sites.

Technologies of targeting histone deacetylase in drug discovery: Current progress and emerging prospects

Histone deacetylases (HDACs) catalyze the hydrolysis of acetyl-l-lysine side chains in histones and non-histones, which are key to epigenetic regulation in humans. Targeting HDACs has emerged as a promising strategy for treating various types of cancer, including myeloma and hematologic malignancies. At present, numerous small molecule inhibitors targeting HDACs are actively being investigated in clinical trials. Despite their potential efficacy in cancer treatment, HDAC inhibitors suffer from multi-directional selectivity and preclinical resistance issues. Hence, developing novel inhibitors based on cutting-edge medicinal chemistry techniques is essential to overcome these limitations and improve clinical outcomes. This manuscript presents an extensive overview of the properties and biological functions of HDACs in cancer, provides an overview of the current state of development and limitations of clinical HDAC inhibitors, and analyzes a range of innovative medicinal chemistry techniques that are applied. These techniques include selective inhibitors, dual-target inhibitors, proteolysis targeting chimeras, and protein-protein interaction inhibitors.

Molecular insights and optimization strategies for the competitive binding of engineered ACE2 proteins: a multiple replica molecular dynamics study

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to spread globally, and rapid viral evolution and the emergence of new variants pose challenges to pandemic control. During infection, the spike protein of SARS-CoV-2 interacts with the human ACE2 protein via its receptor binding domain (RBD), and it is known that engineered forms of ACE2 can compete with wild-type (WT) ACE2 for binding to inhibit infection. Here, we conducted multiple replica molecular dynamics (MRMD) simulations to study the mechanisms of the engineered ACE2 variants 3N39 and 3N94 and provide directions for optimization. Our findings reveal that engineered ACE2 is notably more efficacious in systems that show weaker binding to WT ACE2 (i.e., WT and BA.1 RBD), but also faces immune escape as the virus evolves. Moreover, by modifying residue types near the binding interface, engineered ACE2 alters the electrostatic potential distribution and reconfigures the hydrogen bonding network, which results in modified binding to the RBD. However, this structural rearrangement does not occur in all RBD variants. In addition, we identified potentially engineerable beneficial residues and potentially engineerable detrimental residues in both ACE2 and RBD. Functional conservation can thus enable the optimization of these residues and improve the binding competitiveness of engineered ACE2, which therefore provides additional immune escape prevention. Finally, we conclude that these findings have implications for understanding the mechanisms responsible for engineered ACE2 and can help us to develop engineered ACE2 proteins that show superior performance.

Cupressus sempervirens L. flavonoids as potent inhibitors to xanthine oxidase: in vitro, molecular docking, ADMET and PASS studies

Excessive intake of purine-rich foods such as seafood and red meat leads to excess xanthine oxidase activity and provokes gout attacks. The aim of this paper is to evaluate in vitro and in silico, the inhibition effect of Cupressus sempervirens plant extracts (flavonoids (Cae) and alkaloids (CaK)) and its six derivative compounds on bovine xanthine oxidase (BXO). The in silico study consists of molecular docking with GOLD v4.0 based on the best PLPchem score (PLP) and prediction of biological activity with the PASS server tool. The inhibitors used were lignan (cp1), Amentoflavone (cp2), Cupressuflavone (cp3), Isocryptomerin (cp4), Hinokiflavone (cp5), and Neolignan (cp6). The in vitro results showed that CaK gives an IC50 of 3.52 ± 0.04 μg/ml. Similarly, Cae saved an IC50 of 8.46 ± 1.98 μg/ml compared with the control (2.82 ± 0.10 μg/ml). The in silico results show that cp1 was the best inhibitor model (PLP of 88.09) with approved pharmacokinetics. These findings suggest that cp1 and cp2 may offer good alternatives for the treatment of hyperuricemia; cp3 was moderate, while the others (cp4 to cp6) were considered weak inhibitors according to their PLP.Communicated by Ramaswamy H. Sarma.

Recent development of selective inhibitors targeting the HDAC6 as anti-cancer drugs: Structure, function and design

HDAC6, a member of the histone deacetylase family, mainly is a cytosolic protein and regulates cell growth by acting on non-histone substrates, such as α -tubulin, cortactin, heat shock protein HSP90, programmed death 1 (PD-1) and programmed death ligand 1 (PD-L1), that are closely related to the proliferation, invasion, immune escape and angiogenesis of cancer tissues. The approved drugs targeting the HDACs are all pan-inhibitors and have many side effects due to their lack of selectivity. Therefore, development of selective inhibitors of HDAC6 has attracted much attention in the field of cancer therapy. In this review, we will summarize the relationship between HDAC6 and cancer, and discuss the design strategies of HDAC6 inhibitors for cancer treatment in recent years.

Discovery of selective HDAC6 inhibitors based on a multi-layer virtual screening strategy

The abnormal enhancement of histone deacetylase 6 (HDAC6) has been demonstrated to be closely related to the occurrence and development of various malignant tumors, attracting extensive attention as a promising target for cancer therapy. Currently, only limited selective HDAC6 inhibitors have entered clinical trials, making the rapid discovery of selective HDAC6 inhibitors with safety profiles particularly urgent. In this study, a multi-layer virtual screening workflow was established, and the representative compounds screened were biologically evaluated in combination with enzyme inhibitory and anti-tumor cell proliferation experiments. The experimental results showed that the screened compounds L-25, L-32, L-45 and L-81 exhibited nanomolar inhibitory activity against HDAC6, and exerted a certain degree of anti-proliferative activities against tumor cells, especially the cytotoxicity of L-45 to A375 (IC₅₀ = 11.23 ± 1.27 μM) and the cytotoxicity of L-81 against HCT-116 (IC₅₀ = 12.25 ± 1.13 μM). Additionally, the molecular mechanisms underlying the subtype selective inhibitory activities of the selected compounds were further elucidated using computational approaches, and the hotspot residues on HDAC6 contributing to the ligands' binding were identified. In summary, this study established a multi-layer screening scheme to quickly and effectively screen out hit compounds with enzyme inhibitory activity and anti-tumor cell proliferation, providing novel scaffolds for the subsequent anti-tumor drug design based on HDAC6 target.

Deciphering the intrinsic dynamics of unphosphorylated IRAK4 kinase bound to type I and type II inhibitors

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a vital protein involved in Toll-like and interleukin-1 receptor signal transduction. Several studies have reported regarding the crystal structure, dynamic properties, and interactions with inhibitors of the phosphorylated form of IRAK4. However, no dynamic properties of inhibitor-bound unphosphorylated IRAK4 have been previously studied. Herein, we report the intrinsic dynamics of unphosphorylated IRAK4 (uIRAK4) bound to type I and type II inhibitors. The corresponding apo and inhibitor-bound forms of uIRAK4 were subjected to three independent simulations of 500 ns (total 1.5 μs) each, and their trajectories were analyzed. The results indicated that all three systems were relatively stable, except for the type II inhibitor-bound form of uIRAK4, which exhibited less compact folding and higher solvent surface area. The intra-hydrogen bonds corroborated the structural deformation of the type-II inhibitor-bound complex, which could be attributed to the long molecular structure of the type-II inhibitor. Moreover, the type II inhibitor bound to uIRAK4 showed higher binding free energy with uIRAK4 than the type I inhibitor. The free energy landscape analysis showed a reorientation of Phe330 side chain from the DFG motif at different metastable states for all the systems. The intra-residual distance between residues Lys213, Glu233, Tyr262, and Phe330 suggests a functional interplay when the inhibitors are bound to uIRAK4, thereby hinting at their crucial role in the inhibition mechanism. Ultimately, the intrinsic dynamics study observed between type I/II inhibitor-bound forms of uIRAK4 may assist in better understanding the enzyme and designing therapeutic compounds.

Virtual screening, molecular simulations and bioassays: Discovering novel microsomal prostaglandin E Synthase-1 (mPGES-1) inhibitors

Microsomal prostaglandin E synthase-1 (mPGES-1) is an inducible prostaglandin E synthase expressed following exposure to pro-inflammatory stimuli. The mPGES-1 enzyme represents a new target for the therapeutic treatment of acute and chronic inflammatory disorders and cancer. In the present study, compounds from the ZINC15 database with an indole scaffold were docked at the mPGES-1 binding site using Glide (high-throughput virtual screening [HTVS], standard precision [SP] and extra precision [XP]), and the stabilities of the complexes were determined by molecular simulation studies. Following HTVS, the top 10% compounds were retained and further screened by SP. Again, the top 10% of these compounds were retained. Finally, the Glide XP scores of the compounds were determined, 20% were analyzed, and the Prime MM-GBSA total free binding energies of the compounds were calculated. The molecular simulations (100 ns) of the reference ligand, LVJ, and the two best-scoring compounds were performed with the Desmond program to analyze the dynamics of the target protein-ligand complexes. In human lung cells treated with the hit compounds, cell viability by colorimetric method and PGE₂ levels by immunoassay method were determined. These in vitro experiments demonstrated that the two indole-containing hit compounds are potential novel inhibitors of mPGES-1 and are, therefore, potential therapeutic agents for cancer/inflammation therapies. Moreover, the compounds are promising lead mPGES-1 inhibitors for novel molecule design.

In Vitro and In Silico Studies of Kinase Inhibitor of MAPK3 Protein to Determine Leishmania martiniquensis Treatment

PURPOSE

Leishmaniasis is a parasitic disease transmitted by the bite of the phlebotomine female sand fly. Currently, no reported effective vaccines are available for the treatment of leishmaniasis; consequently, restricting this disease completely depends on controlling its transmission. Mitogen-activated protein (MAP) kinases have been reported to be involved in the regulation of the flagellum length and hence play an important role in disease transmission, especially the MAPK3 protein. Therefore, the current work focused on identifying approved drugs that can inhibit the MAPK3 protein.

METHODS

First, the recombinant plasmid (pET28b( +) MAPK3) was cloned into E. coli strain BL21 using the heatshock method. Afterward, E. coli was induced using IPTG, and cells were harvested for protein purification in the next step. After that, the MAPK3 protein was purified using Ni-NTA column. Then, the inhibition kinase activity of the purified MAPK3 protein was performed using an ADP-Glo^™ Kinase Assay kit. Furthermore, the cytotoxicity of Leishmania cells were detected by alamarBlue^™ Cell Viability Reagent. Finally, the binding affinity within the binding site of MAPK3 protein was performed by computational methods.

RESULTS

Purification of the MAPK3 protein was done using an Ni-NTA column and a protein band was identified at the expected 44 kDa molecular weight. Afterward, the ability of commercial drugs (afatinib and lapatinib) to inhibit the purified MAPK3 kinase activity was performed using an ADP-Glo^™ Kinase Assay kit. The half-maximal inhibitory concentrations (IC₅₀) of two drugs inhibited the MAPK3 protein within the same range of IC₅₀ values (3.27 and 2.22 µM for afatinib and lapatinib, respectively). Furthermore, the cytotoxicity assay of compounds toward the extracellular promastigote and intracellular amastigote stages was investigated using alamarBlue^™ Cell Viability Reagent. The results showed that both drugs were more efficient against extracellular promastigotes and intracellular amastigotes of both Leishmania donovani and Leishmania martiniquensis. Finally, the molecular dynamics simulation (MD) was performed to study the intermolecular interactions of both drugs with MAPK3 protein. From 100 ns molecular dynamics simulation, the structural stability of both drugs in a complex with MAPK3 was quite stable.

CONCLUSION

This work was suggesting that afatinib and lapatinib act as MAPK3 inhibitors and might be developed for leishmaniasis treatment.

Discovering potential stabilizers for KRAS22RT G-quadruplex DNA: an alternative next generation approach to treat pancreatic cancer

KRAS is the signature gene responsible for the occurrence of pancreatic cancer, which is a complex, multifactorial and intractable lethal malignancy. Prevention and treatment of the ailment have always been a key motivation behind the search for new therapeutic drug molecules. G-quadruplexes are non-canonical guanine-rich secondary structures, commonly formed at eukaryotic telomeric ends, oncogenic promotors and G-rich regions of the DNA. These G-quadruplexes play a crucial role in the regulation of gene expression and maintenance of genome integrity, therefore, they are considered as emerging potential therapeutic drug targets. The present study is concerned with the discovery of a potential stabilizer for KRAS22RT G-quadruplex DNA, located in the NHE region of the promotor, while inhibiting the upregulation of KRAS proto-oncogene, as an alternative approach for the treatment of pancreatic cancer. Various chemical libraries have been virtually screened against the targeted G4 structure and 143 compounds showed promising results. However, molecular dynamic studies, ADME and toxicity analyses predicted that three compounds belonging to the class of tetra-substituted phenanthrolines (i.e., 7i, 7j and 7k) can not only effectively stabilize KRAS22RT G4 structure but also have least toxic effects in the in vivo system. Therefore, it is highly recommended to further investigate their effectiveness and efficacy through experimental analysis in laboratory.Communicated by Ramaswamy H. Sarma.

Molecular dynamics study on the behavior and binding mechanism of target protein Transgelin-2 with its agonist TSG12 for anti-asthma drug discovery

Transgelin-2 (TG2) is a novel promising therapeutic target for the treatment of asthma as it plays an important role in relaxing airway smooth muscles and reducing pulmonary resistance in asthma. The compound TSG12 is the only reported TG2 agonist with in vivo anti-asthma activity. However, the dynamic behavior and ligand binding sites of TG2 and its binding mechanism with TSG12 remain unclear. In this study, we performed 12.6 μs molecular dynamics (MD) simulations for apo-TG2 and TG2-TSG12 complex, respectively. The results suggested that the apo-TG2 has 4 most populated conformations, and that its binding of the agonist could expand the conformation distribution space of the protein. The simulations revealed 3 potential binding sites in 3 most populated conformations, one of which is induced by the agonist binding. Free energy decomposition uncovered 8 important residues with contributions stronger than -1 kcal/mol. Computational alanine scanning for the important residues by 100 ns conventional MD simulation for each mutated TG2-TSG12 complexes demonstrated that E27, R49 and F52 are essential residues for the agonist binding. These results should be helpful to understand the dynamic behavior of TG2 and its binding mechanism with the agonist TSG12, which could provide some structural insights into the novel mechanism for anti-asthma drug development.

Discovery of Mcl-1 inhibitors through virtual screening, molecular dynamics simulations and in vitro experiments

As a member of the B-cell lymphoma 2 (Bcl-2) protein family, the myeloid leukemia cell differentiation protein (Mcl-1) can inhibit apoptosis and plays an active role in the process of tumor escape from apoptosis. Therefore, inhibition of Mcl-1 protein can effectively promote the apoptosis of tumor cells and may also reduce tumor cell resistance to drugs targeting other anti-apoptotic proteins. This research is dedicated to the development of Mcl-1 inhibitors, aiming to provide more references for lead compounds with different scaffolds for the development of targeted anticancer drugs. We obtained a series of small molecules with a common core skeleton through molecular docking from Specs database and searched the core structure in ZINC database for more similar small molecules. Collecting these small molecules for preliminary experimental screening, we found a batch of active compounds, and selected two small molecules with the strongest inhibitory activity on B16F10 cells: compound 7 and compound 1. Their IC₅₀s are 7.86 ± 1.25 and 24.72 ± 1.94 μM, respectively. These two compounds were also put into cell scratch test for B16F10 cells and cell viability assay of other cell lines. Furthermore, through molecular dynamics (MD) simulation analysis, we found that compound 7 formed strong binding with the key P2, P3 pocket and ARG 263 of Mcl-1. Finally, ADME results showed that compound 7 performs well in terms of drug similarity. In conclusion, this study provides hits with co-scaffolds that may aid in the design of effective clinical drugs targeting Mcl-1 and the future drug development.

Do biological activities of selective histone deacetylase 6 (HDAC6) inhibitors rely on the modification of cap group?

Nowadays, significant progress has been made in the development of selective histone deacetylase 6 (HDAC6) inhibitors, exerting great potential in the treatment of various malignant tumors and neurodegenerative diseases. Previously, selective inhibitory activities of HDAC inhibitors were generally considered sensitive to the interactions between the Cap group and the binding site of HDAC6, and a large number of selective HDAC6 inhibitors have been designed and synthesized based on the strategy. However, some inhibitors without Cap group could also exhibit excellent potency and selective inhibition towards HDAC6, and in this study, BRD9757 and compound 8, as capless selective HDAC6 inhibitors, were selected as molecular probes to explore the difference of their binding interactions in HDAC1&6. Through the analysis of binding-free energies and conformational rearrangements after 1 μs molecular dynamics simulation, it could be learned that although the residues in the binding site remained highly consistent, the binding mechanisms of BRD9757 and compound 8 in HDAC1&6 were different, which will provide valuable hints for the discovery of novel selective HDAC6 inhibitors.

Evaluation of decursin and its isomer decursinol angelate as potential inhibitors of human glutamate dehydrogenase activity through in silico and enzymatic assay screening

Glutaminolysis is a typical hallmark of malignant tumors across different cancers. Glutamate dehydrogenase (GDH, GLUD1) is one such enzyme involved in the conversion of glutamate to α-ketoglutarate. High levels of GDH are associated with numerous diseases and is also a prognostic marker for predicting metastasis in colorectal cancer. Therefore, inhibiting GDH can be a crucial therapeutic target. Here in this study, we performed molecular docking analysis of 8 different plants derived single compounds collected from pubChem database for screening and selected decursin (DN) and decursinol angelate (DA). We performed molecular dynamics simulation (MD), monitored the stability, interaction for protein and docked ligand at 50 ns, and evaluated the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculation on the twoselected compounds along with a standard inhibitor epigallocatechin gallate (EGCG) as reference. The final results showed the formation of stable hydrogen bond interactions by DN and DA in the residues of R400 and Y386 at the ADP activation site of GDH, which was important for the selective inhibition of GDH activity. Additionally, the total binding energy of DN and DA were -115.5 kJ/mol and -106.2 kJ/mol, which was higher than the standard reference GDH inhibitor EGCG (-92.8 kJ/mol). Furthermore, biochemical analysis for GDH inhibition substantiated our computational results and established DN and DA as novel GDH inhibitor. The percentage of IC₅₀ inhibition for DN and DA were 1.035 μM and 1.432 μM. Conclusively, DN and DA can be a novel therapeutic drug for inhibition of glutamate dehydrogenase.

Computational approach investigation bioactive molecules from Saussurea Costus plant as SARS-CoV-2 main protease inhibitors using reverse docking, molecular dynamics simulation, and pharmacokinetic ADMET parameters

SARS-COV-2 virus causes (COVID-19) disease; it has become a global pandemic since 2019 and has negatively affected all aspects of human life. Scientists have made great efforts to find a reliable cure, vaccine, or treatment for this emerging disease. Efforts have been directed towards using medicinal plants as alternative medicines, as the active chemical compounds in them have been discovered as potential antiviral or anti-inflammatory agents. In this research, the potential of Saussurea costus (S. Costus) or QUST Al Hindi chemical consistent as potential antiviral agents was investigated by using computational methods such as Reverse Docking, ADMET, and Molecular Dynamics with different proteases COVID-19 such as PDB: 2GZ9; 6LU7; 7AOL, 6Y2E, 6Y84. The results of Reverse Docking the complex between 6LU7 proteases and Cynaropicrin compound being the best complex, as the same result, is achieved by molecular dynamics. Also, the toxicity testing result from ADMET method proved that the complex is the least toxic and the safest possible drug. In addition, 6LU7-Cynaropicrin complex obeyed Lipinski rule; it formed ≤5 H-bond donors and ≤10 H bond acceptors, MW < 500 Daltons, and octanol/water partition coefficient <5.

Transcriptomic discovery of a theranostic signature (SERPINE1/MMP3/COL1A1/SPP1) for head and neck squamous cell carcinomas and identification of antrocinol as a candidate drug

Head and neck squamous cell carcinomas (HNSCC) are prevalent malignancies with a disappointing prognosis, necessitating the search for theranostic biomarkers for better management. Based on a meta-analysis of transcriptomic data containing ten clinical datasets of HNSCC and matched nonmalignant samples, we identified SERPINE1/MMP3/COL1A1/SPP1 as essential hub genes as the potential theranostic biomarkers. Our analysis suggests these hub genes are associated with the extracellular matrix, peptidoglycans, cell migration, wound-healing processes, complement and coagulation cascades, and the AGE-RAGE signaling pathway within the tumor microenvironment. Also, these hub genes were associated with tumor-immune infiltrating cells and immunosuppressive phenotypes of HNSCC. Further investigation of The Cancer Genome Atlas (TCGA) cohorts revealed that these hub genes were associated with staging, metastasis, and poor survival in HNSCC patients. Molecular docking simulations were performed to evaluate binding activities between the hub genes and antrocinol, a novel small-molecule derivative of an anticancer phytochemical antrocin previously discovered by our group. Antrocinol showed high affinities to MMP3 and COL1A1. Notably, antrocinol presented satisfactory drug-like and ADMET properties for therapeutic applications. These results hinted at the potential of antrocinol as an anti-HNSCC candidate via targeting MMP3 and COL1A1. In conclusion, we identified hub genes: SERPINE1/MMP3/COL1A1/SPP1 as potential diagnostic biomarkers and antrocinol as a potential new drug for HNSCC.

Computational molecular interaction between SARS-CoV-2 main protease and theaflavin digallate using free energy perturbation and molecular dynamics

Our objective was to identify the molecule which can inhibit SARS-CoV-2 main protease and can be easily procured. Natural products may provide such molecules and can supplement the current custom chemical synthesis-based drug discovery for this objective. A combination of docking approaches, scoring functions, classical molecular dynamic simulation, binding pose metadynamics, and free energy perturbation calculations have been employed in this study. Theaflavin digallate has been observed in top-scoring compounds after the three independent virtual screening simulations of 598435 compounds (unique 27256 chemical entities). The main protease-theaflavin digallate complex interacts with critical active site residues of the main protease in molecular dynamics simulation independent of the explored computational framework, simulation time, initial structure, and force field used. Theaflavin digallate forms approximately three hydrogen bonds with Glutamate166 of main protease, primarily through hydroxyl groups in the benzene ring of benzo(7)annulen-6-one, along with other critical residues. Glu166 is the most critical amino acid for main protease dimerization, which is necessary for catalytic activity. The estimated binding free energy, calculated by Amber and Schrodinger MMGBSA module, reflects a high binding free energy between theaflavin digallate and main protease. Binding pose metadynamics simulation shows the highly persistent H-bond and a stable pose for the theaflavin digallate-main protease complex. Using method control, experimental controls, and test set, alchemical transformation studies confirm high relative binding free energy of theaflavin digallate with the main protease. Computational molecular interaction suggests that theaflavin digallate can inhibit the main protease of SARS-CoV-2.

DRESIS: the first comprehensive landscape of drug resistance information

Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named 'DRESIS' was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/.

DrugMAP: molecular atlas and pharma-information of all drugs

The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studied drugs. However, our understanding of such information is neither comprehensive nor precise, which necessitates the construction of a new database providing a network containing a large number of drugs and their interacting molecules. Here, a new database describing the molecular atlas and pharma-information of drugs (DrugMAP) was therefore constructed. It provides a comprehensive list of interacting molecules for >30 000 drugs/drug candidates, gives the differential expression patterns for >5000 interacting molecules among different disease sites, ADME (absorption, distribution, metabolism and excretion)-relevant organs and physiological tissues, and weaves a comprehensive and precise network containing >200 000 interactions among drugs and molecules. With the great efforts made to clarify the complex mechanism underlying drug pharmacokinetics and pharmacodynamics and rapidly emerging interests in artificial intelligence (AI)-based network analyses, DrugMAP is expected to become an indispensable supplement to existing databases to facilitate drug discovery. It is now fully and freely accessible at: https://idrblab.org/drugmap/.

Molecular dynamics simulations highlight the altered binding landscape at the spike-ACE2 interface between the Delta and Omicron variants compared to the SARS-CoV-2 original strain

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.529 variant (Omicron), represents a significant deviation in genetic makeup and function compared to previous variants. Following the BA.1 sublineage, the BA.2 and BA.3 Omicron subvariants became dominant, and currently the BA.4 and BA.5, which are quite distinct variants, have emerged. Using molecular dynamics simulations, we investigated the binding characteristics of the Delta and Omicron (BA.1) variants in comparison to wild-type (WT) at the interface of the spike protein receptor binding domain (RBD) and human angiotensin converting enzyme-2 (ACE2) ectodomain. The primary aim was to compare our molecular modelling systems with previously published observations, to determine the robustness of our approach for rapid prediction of emerging future variants. Delta and Omicron were found to bind to ACE2 with similar affinities (−39.4 and −43.3 kcal/mol, respectively) and stronger than WT (−33.5 kcal/mol). In line with previously published observations, the energy contributions of the non-mutated residues at the interface were largely retained between WT and the variants, with F456, F486, and Y489 having the strongest energy contributions to ACE2 binding. Further, residues N440K, Q498R, and N501Y were predicted to be energetically favourable in Omicron. In contrast to Omicron, which had the E484A and K417N mutations, intermolecular bonds were detected for the residue pairs E484:K31 and K417:D30 in WT and Delta, in accordance with previously published findings. Overall, our simplified molecular modelling approach represents a step towards predictive model systems for rapidly analysing arising variants of concern.

GC-MS profiling of Bauhinia variegata major phytoconstituents with computational identification of potential lead inhibitors of SARS-CoV-2 Mpro

Severe acute respiratory syndrome coronavirus 2 was originally identified in Wuhan city of China in December 2019 and it spread rapidly throughout the globe, causing a threat to human life. Since targeted therapies are deficient, scientists all over the world have an opportunity to develop novel drug therapies to combat COVID-19. After the declaration of a global medical emergency, it was established that the Food and Drug Administration (FDA) could permit the use of emergency testing, treatments, and vaccines to decrease suffering, and loss of life, and restore the nation's health and security. The FDA has approved the use of remdesivir and its analogs as an antiviral medication, to treat COVID-19. The primary protease of SARS-CoV-2, which has the potential to regulate coronavirus proliferation, has been a viable target for the discovery of medicines against SARS-CoV-2. The present research deals with the in silico technique to screen phytocompounds from a traditional medicinal plant, Bauhinia variegata for potential inhibitors of the SARS-CoV-2 main protease. Dried leaves of the plant B. variegata were used to prepare aqueous and methanol extract and the constituents were analyzed using the GC-MS technique. A total of 57 compounds were retrieved from the aqueous and methanol extract analysis. Among these, three lead compounds (2,5 dimethyl 1-H Pyrrole, 2,3 diphenyl cyclopropyl methyl phenyl sulphoxide, and Benzonitrile m phenethyl) were shown to have the highest binding affinity (−5.719 to −5.580 kcal/mol) towards SARS-CoV-2 M^pro. The post MD simulation results also revealed the favorable confirmation and stability of the selected lead compounds with M^pro as per trajectory analysis. The Prime MM/GBSA binding free energy supports this finding, the top lead compound 2,3 diphenyl cyclopropyl methyl phenyl sulphoxide showed high binding free energy (−64.377 ± 5.24 kcal/mol) towards M^pro which reflects the binding stability of the molecule with M^pro. The binding free energy of the complexes was strongly influenced by His, Gln, and Glu residues. All of the molecules chosen are found to have strong pharmacokinetic characteristics and show drug-likeness properties. The lead compounds present acute toxicity (LD50) values ranging from 670 mg/kg to 2500 mg/kg; with toxicity classifications of 4 and 5 classes. Thus, these compounds could behave as probable lead candidates for treatment against SARS-CoV-2. However further in vitro and in vivo studies are required for the development of medication against SARS-CoV-2.

Structural dynamics and kinase inhibitory activity of three generations of tyrosine kinase inhibitors against wild-type, L858R/T790M, and L858R/T790M/C797S forms of EGFR

Mutations in the tyrosine kinase domain of epidermal growth factor receptor (EGFR), including L858R/T790M double and L858R/T790M/C797S triple mutations, are major causes of acquired resistance towards EGFR targeted drugs. In this work, a combination of comprehensive molecular modeling and in vitro kinase inhibition assay was used to unravel the mutational effects of EGFR on the susceptibility of three generations of EGFR tyrosine kinase inhibitors (erlotinib, gefitinib, afatinib, dacomitinib, and osimertinib) in comparison with the wild-type EGFR. The binding affinity of all studied inhibitors towards the double and triple EGFR mutations was in good agreement with the experimental data, ranked in the order of osimertinib > afatinib > dacomitinib > erlotinib > gefitinib. Three hot-spot residues at the hinge region (M790, M793, and C797) were involved in the binding of osimertinib and afatinib, enhancing their inhibitory activity towards mutated EGFRs. Both double and triple EGFR mutations causing erlotinib and gefitinib resistance are mainly caused by the low number of H-bond occupations, the low number of surrounding atoms, and the high number of water molecules accessible to the enzyme active site. According to principal component analysis, the molecular complexation of osimertinib against the two mutated EGFRs was in a closed conformation, whereas that against wild-type EGFR was in an open conformation, resulting in drug resistance. This work paves the way for further design of the novel EGFR inhibitors to overcome drug resistance mechanisms.

REGLIV: Molecular regulation data of diverse living systems facilitating current multiomics research

Multiomics is a powerful technique in molecular biology that facilitates the identification of new associations among different molecules (genes, proteins & metabolites). It has attracted tremendous research interest from the scientists worldwide and has led to an explosive number of published studies. Most of these studies are based on the regulation data provided in available databases. Therefore, it is essential to have molecular regulation data that are strictly validated in the living systems of various cell lines and in vivo models. However, no database has been developed yet to provide comprehensive molecular regulation information validated by living systems. Herein, a new database, Molecular Regulation Data of Living System Facilitating Multiomics Study (REGLIV) is introduced to describe various types of molecular regulation tested by the living systems. (1) A total of 2996 regulations describe the changes in 1109 metabolites triggered by alterations in 284 genes or proteins, and (2) 1179 regulations describe the variations in 926 proteins induced by 125 endogenous metabolites. Overall, REGLIV is unique in (a) providing the molecular regulation of a clearly defined regulatory direction other than simple correlation, (b) focusing on molecular regulations that are validated in a living system not simply in an in vitro test, and (c) describing the disease/tissue/species specific property underlying each regulation. Therefore, REGLIV has important implications for the future practice of not only multiomics, but also other fields relevant to molecular regulation. REGLIV is freely accessible at: https://idrblab.org/regliv/.

Exploration and validation of Taraxacum mongolicum anti-cancer effect

Taraxacum mongolicum gained a lot of concern and was applied in 93 formulas in China due to its fame as a traditional Chinese medicine. The earliest recorded application of Taraxacum mongolicum was traced back to the Han dynasty. Generations of doctors boosted the usage and enriched the pharmacological mechanism. Clinical application of the Taraxacum mongolicum is flourishing as it treats multiple diseases. This study aims to explore the anti-cancer effect, retrieve the active ingredients and screen the key targets of Taraxacum mongolicum in cancer therapy. We collected and evaluated 10 key active compounds to investigate the anti-cancer effect via 69 significant targets and a variety of biological processes and pathways. Gene Ontology (GO) enrichment analysis uncovered targets associated with protein phosphorylation, cell proliferation and apoptotic processes via regulation of kinases, ATP and enzyme binding activities. Half of the top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were directly involved in cancer. Based on standard selection criteria, seven hub targets were obtained. These targets functioned through distinct patterns and pathways in realizing the anti-cancer effect. Molecular docking was conducted to validate the potential combination between compounds and hub targets to explore the pharmacological mechanism of key compounds in Taraxacum mongolicum against cancer. In summary, our findings indicate that the famous and widely used Chinese herb, Taraxacum mongolicum, shows good anti-cancer effect through its active compounds, targeted genes, and multiple involved biological processes. The results may provide a theoretical basis for subsequent experimental validation and drug development of Taraxacum mongolicum extract against cancer.

Benchmarking the ability of novel compounds to inhibit SARS-CoV-2 main protease using steered molecular dynamics simulations

BACKGROUND

The SARS-CoV-2 main protease (M^pro) is an attractive target in the COVID-19 drug development process. It catalyzes the polyprotein's translation from viral RNA and specifies a particular cleavage site. Due to the absence of identical cleavage specificity in human cell proteases, targeting M^pro with chemical compounds can obstruct the replication of the virus.

METHODS

To explore the potential binding mechanisms of 1,2,3-triazole scaffolds in comparison to co-crystallized inhibitors 11a and 11b towards M^pro, we herein utilized molecular dynamics and enhanced sampling simulation studies.

RESULTS AND CONCLUSION

All the 1,2,3-triazole scaffolds interacted with catalytic residues (Cys145 and His41) and binding pocket residues of M^pro involving Met165, Glu166, Ser144, Gln189, His163, and Met49. Furthermore, the adequate binding free energy and potential mean force of the topmost compound 3h was comparable to the experimental inhibitors 11a and 11b of M^pro. Overall, the current analysis could be beneficial in developing the SARS-CoV-2 M^pro potential inhibitors.

E2UbcH5B-derived peptide ligands target HECT E3-E2 binding site and block the Ub-dependent SARS-CoV-2 egression: A computational study

Homologous to E6AP carboxyl-terminus (HECT)-type E3 ligase performs ubiquitin (Ub)-proteasomal protein degradation via forming a complex with E2∼Ub. Enveloped viruses including SARS-CoV-2 escape from the infected cells by harnessing the E-class vacuolar protein-sorting (ESCRT) machinery and mimic the cellular system through PPAY motif-based linking to HECT Ub ligase activity. In the present study, we have characterized the binding pattern of E2^UbcH5B to HECT domains of NEDD4L, WWP1, WWP2, HECW1, and HECW2 through in silico analysis to isolate the E2^UbcH5B-specific peptide inhibitors that may target SARS-CoV-2 viral egression. Molecular dynamics analysis revealed more opening of E2^UbcH5B-binding pocket upon binding to HECT^NEDD4L, HECT^WWP1, HECT^WWP2, HECT^HECW1, and HECT^HECW2. We observed similar binding pattern for E2^UbcH5B and mentioned HECT domains as previously reported for HECT^NEDD4L where Trp762, Trp709, and Trp657 residues of HECT^NEDD4L, HECT^WWP1, and HECT^WWP2 are involved in making contacts with Ser94 residue of E2^UbcH5B. Similarly, corresponding to HECT^NEDD4L Tyr756 residue, HECT^WWP1, HECT^WWP2, HECT^HECW1, and HECT^HECW2-specific Phe703, Phe651, Phe1387, and Phe1353 residues execute interaction with E2^UbcH5B. Our analysis suggests that corresponding to Cys942 of HECT^NEDD4L, Cys890, Cys838, Cys1574, and Cys1540 residues of HECT^WWP1, HECT^WWP2, HECT^HECW1, and HECT^HECW2, respectively are involved in E2-to-E3 Ub transfer. Furthermore, MM-PBSA free energy calculations revealed favorable energy values for E2^UbcH5B-HECT complexes along with the individual residue contributions. Subsequently, two E2^UbcH5B-derived peptides (His55-Phe69 and Asn81-Ala96) were tested for their binding abilities against HECT domains of NEDD4L, WWP1, WWP2, HECW1, and HECW2. Their binding was validated through substitution of Phe62, Pro65, Ile84, and Cys85 residues into Ala, which revealed an impaired binding, suggesting that the proposed peptide ligands may selectively target E2-HECT binding and Ub-transfer. Collectively, we propose that peptide-driven blocking of E2-to-HECT Ub loading may limit SARS-CoV-2 egression and spread in the host cells.

ConSIG: consistent discovery of molecular signature from OMIC data

The discovery of proper molecular signature from OMIC data is indispensable for determining biological state, physiological condition, disease etiology, and therapeutic response. However, the identified signature is reported to be highly inconsistent, and there is little overlap among the signatures identified from different biological datasets. Such inconsistency raises doubts about the reliability of reported signatures and significantly hampers its biological and clinical applications. Herein, an online tool, ConSIG, was constructed to realize consistent discovery of gene/protein signature from any uploaded transcriptomic/proteomic data. This tool is unique in a) integrating a novel strategy capable of significantly enhancing the consistency of signature discovery, b) determining the optimal signature by collective assessment, and c) confirming the biological relevance by enriching the disease/gene ontology. With the increasingly accumulated concerns about signature consistency and biological relevance, this online tool is expected to be used as an essential complement to other existing tools for OMIC-based signature discovery. ConSIG is freely accessible to all users without login requirement at https://idrblab.org/consig/.

Computational approach to decode the mechanism of curcuminoids against neuropathic pain

BACKGROUND

Curcumin (CUR), demethoxycurcumin (DMC) and bisdemethoxycurcumin (BDMC) are the main components of turmeric that commonly used to treat neuropathic pain (NP). However, the mechanism of the therapy is not sufficiently clarified. Herein, network pharmacology, molecular docking and molecular dynamics (MD) approaches were used to investigate the mechanism of curcuminoids for NP treatment.

METHODS

Active targets of curcuminoids were obtained from the Swiss Target database, and NP-related targets were retrieved from GeneCards, OMIM, Drugbank and TTD databases. A protein-protein interaction (PPI) network was built to screen the core targets. Furthermore, DAVID was used for GO and KEGG pathway enrichment analyses. Interactions between potential targets and curcuminoids were assessed by molecular docking and the MD simulations were run for 100ns to validate the docking results on the top six complexes.

RESULTS

CUR, DMC, and BDMC had 100, 99 and 100 targets respectively. After overlapping with NP there were 33, 33 and 31 targets respectively. PPI network analysis of TOP 10 core targets, TNF, GSK3β were common targets of curcuminoids. Molecular docking and MD results indicated that curcuminoids bind strongly with the core targets. The GO and KEGG showed that curcuminoids regulated nitrogen metabolism, the serotonergic synapse and ErbB signaling pathway to alleviate NP. Furthermore, specific targets in these three compounds were also analysed at the same time.

CONCLUSIONS

This study systematically explored and compared the anti-NP mechanism of curcuminoids, providing a novel perspective for their utilization.

Mechanism of drug resistance of BVDV induced by F224S mutation in RdRp: A case study of VP32947

Bovine viral diarrhea virus (BVDV) is an enveloped virus with an RNA genome, causing serious economic losses to the areas dominated by livestock industry. Currently, although several compounds with biological activities of inhibiting virus replication have been reported, amino acid mutations (especially F224S mutation) frequently occurring in the RNA-dependent RNA polymerase (RdRp) have greatly reduce their value of further research. In this study, we introduced an effective and rapid in silico strategy to explore the differences in the binding modes of VP32947 between the wild/mutant-type RdRp at the molecular level, and further explained the main reasons for the variations in the inhibitory activities of VP32947 against the two types of enzymes. Firstly, the binding site of VP32947 in the finger domain was determined based on the previously reported experimental data, and the initial conformation of VP32947 in the wild RdRp was constructed using molecular docking. Then, the mutant research system was obtained directly by artificial mutation strategy. Afterwards, the built research systems were subjected to microsecond-timescale molecular dynamic simulation, and the conformational and energic profile analyses were performed according to the simulation trajectories. It was found that after 1 μs simulation, VP32947 in the mutant system was transferred to the left side of Loop α, and its interactions with the residues in the loop region were weakened. However, VP32947 in the wild system remained at the right side of Loop α, and could have a good fit with the sub-pocket formed by F224, I261, P262, N264, S532, which was conducive to maintaining its stable binding conformation in the wild RdRp. The illustration of the difference in the binding mechanisms of VP32947 in the wild/mutant RdRp would provide a theoretical basis for the rational design of innovative inhibitors based on the enzyme.

Structural basis of Omicron immune evasion: A comparative computational study

Background

The vaccines used against SARS-CoV-2 by now have been able to develop some neutralising antibodies in the vaccinated population and their effectiveness has been challenged by the emergence of the new strains with numerous mutations in the spike protein of SARS-CoV-2. Since S protein is the major immunogenic protein of the virus which contains Receptor Binding Domain (RBD) that interacts with the human Angiotensin-Converting Enzyme 2 (ACE2) receptors, any mutations in this region should affect the neutralisation potential of the antibodies leading to the immune evasion. Several variants of concern of the virus have emerged so far, amongst which the most critical are Delta and recently reported Omicron. In this study, we have mapped and reported mutations on the modelled RBD and evaluated binding affinities of various human antibodies with it.

Method

Docking and molecular dynamics simulation studies have been used to explore the effect of mutations on the structure of RBD and RBD-antibody interaction.

Results

These analyses show that the mutations mostly at the interface of a nearby region lower the binding affinity of the antibody by ten to forty percent, with a downfall in the number of interactions formed as a whole. It implies the generation of immune escape variants.

Conclusions

Notable mutations and their effect was characterised that explain the structural basis of antibody efficacy in Delta and a compromised neutralisation effect for the Omicron variant. Thus, our results pave the way for robust vaccine design that can be effective for many variants.

Statistics and network-based approaches to identify molecular mechanisms that drive the progression of breast cancer

Breast cancer (BC) is one of the most malignant tumors and the leading cause of cancer-related death in women worldwide. So, an in-depth investigation on the molecular mechanisms of BC progression is required for diagnosis, prognosis and therapies. In this study, we identified 127 common differentially expressed genes (cDEGs) between BC and control samples by analyzing five gene expression profiles with NCBI accession numbers GSE139038, GSE62931, GSE45827, GSE42568 and GSE54002, based-on two statistical methods LIMMA and SAM. Then we constructed protein-protein interaction (PPI) network of cDEGs through the STRING database and selected top-ranked 7 cDEGs (BUB1, ASPM, TTK, CCNA2, CENPF, RFC4, and CCNB1) as a set of key genes (KGs) by cytoHubba plugin in Cytoscape. Several BC-causing crucial biological processes, molecular functions, cellular components, and pathways were significantly enriched by the estimated cDEGs including at-least one KGs. The multivariate survival analysis showed that the proposed KGs have a strong prognosis power of BC. Moreover, we detected some transcriptional and post-transcriptional regulators of KGs by their regulatory network analysis. Finally, we suggested KGs-guided three repurposable candidate-drugs (Trametinib, selumetinib, and RDEA119) for BC treatment by using the GSCALite online web tool and validated them through molecular docking analysis, and found their strong binding affinities. Therefore, the findings of this study might be useful resources for BC diagnosis, prognosis and therapies.

A multidrug efflux protein in Mycobacterium tuberculosis; tap as a potential drug target for drug repurposing

Tuberculosis (TB) is a serious communicative disease caused by Mycobacterium tuberculosis. Although there are vaccines and drugs available to treat the disease, they are not efficient, moreover, multidrug-resistant TB (MDR-TB) become a major hurdle in its therapy. These MDR strains utilize the multidrug efflux pump as a decisive weapon to fight against antitubercular drugs. Tap membrane protein was observed as a crucial multidrug efflux pump in M. tuberculosis and its critical implication in MDR-MTB development makes it an effective drug target. In the present study, we have utilized various in silico approaches to predict the applicability of FDA-approved ion channel inhibitors and blockers as therapeutic leads against Tuberculosis by targeting multidrug efflux protein; Tap in MTB. Tap protein structure is predicted by Phyre2 server followed by model refinement, validation, physio-chemical catheterization and target prediction. Further, the interaction between Tap protein and ligands were analysed by molecular docking and MD simulation run of 100 ns. Based on implication and compatibility, 18 FDA-approved ion channel inhibitors and blockers are selected as a ligand against the Tap protein and eventually observed five ligands; Glimepiride, Flecainide, Flupiritine, Nimodipine and Amlodipine as promising compounds which have exhibited the significant stable interaction with Tap protein and are proposed to modulate or interfere with its activity. These compounds illustrated the substantial docking score and total binding enthalpy more than -7 kcal/mol and -42 kcal/mol respectively which implies that the selected FDA-approved compounds can spontaneously interact with the Tap protein to modulate its function. This study proposed Tap protein as a prominent drug target in MTB and investigated compounds that show considerable interaction with the Tap protein as potential therapeutic molecules. These interactions may lead to modulating or inhibit the activity of drug efflux protein thereby making MTB susceptible to antitubercular drugs.

Biological activities of drug inactive ingredients

In a drug formulation (DFM), the major components by mass are not Active Pharmaceutical Ingredient (API) but rather Drug Inactive Ingredients (DIGs). DIGs can reach much higher concentrations than that achieved by API, which raises great concerns about their clinical toxicities. Therefore, the biological activities of DIG on physiologically relevant target are widely demanded by both clinical investigation and pharmaceutical industry. However, such activity data are not available in any existing pharmaceutical knowledge base, and their potentials in predicting the DIG-target interaction have not been evaluated yet. In this study, the comprehensive assessment and analysis on the biological activities of DIGs were therefore conducted. First, the largest number of DIGs and DFMs were systematically curated and confirmed based on all drugs approved by US Food and Drug Administration. Second, comprehensive activities for both DIGs and DFMs were provided for the first time to pharmaceutical community. Third, the biological targets of each DIG and formulation were fully referenced to available databases that described their pharmaceutical/biological characteristics. Finally, a variety of popular artificial intelligence techniques were used to assess the predictive potential of DIGs' activity data, which was the first evaluation on the possibility to predict DIG's activity. As the activities of DIGs are critical for current pharmaceutical studies, this work is expected to have significant implications for the future practice of drug discovery and precision medicine.

Discovery of novel Glutaminase allosteric inhibitors through drug repurposing and comparative MMGB/PBSA and molecular dynamics simulation

GLS1 enzymes (Glutaminase C (GAC) and kidney-type Glutaminase (KGA)) are gaining prominence as a target for tumor treatment including lung, breast, kidney, prostate, and colorectal. To date, several medicinal chemistry studies are being conducted to develop new and effective inhibitors against GLS1 enzymes. Telaglenastat, a drug that targets the allosteric site of GLS1, has undergone clinical trials for the first time for the therapy of solid tumors and hematological malignancies. A comprehensive computational investigation is performed to get insights into the inhibition mechanism of the Telaglenastat. Some novel inhibitors are also proposed against GLS1 enzymes using the drug repurposing approach using 2D-fingerprinting virtual screening method against 2.4 million compounds, application of pharmacokinetics, Molecular Docking, and Molecular Dynamic (MD) Simulations. A TIP3P water box of 10 Å was defined to solvate both enzymes to improve MD simulation reliability. The dynamics results were validated further by the MMGB/PBSA binding free energy method, RDF, and AFD analysis. Results of these computational analysis revealed a stable binding affinity of Telaglenastat, as well as an FDA approved drug Astemizole (IC₅₀ ∼ 0.9 nM) and a novel para position oriented methoxy group containing Chembridge compound (Chem-64284604) that provides an effective inhibitory action against GAC and KGA.

Computational investigation of benzalacetophenone derivatives against SARS-CoV-2 as potential multi-target bioactive compounds

Benzalacetophenones, precursors of flavonoids are aromatic ketones and enones and possess the immunostimulant as well as antiviral activities. Thus, benzalacetophenones were screened against the COVID-19 that could be lethal in patients with compromised immunity. We considered ChEBI recorded benzalacetophenone derivative(s) and evaluated their activity against 3C-like protease (3CL^pro), papain-like protease (PL^pro), and spike protein of SARS-Cov-2 to elucidate their possible role as antiviral agents. The probable targets for each compound were retrieved from DIGEP-Pred at 0.5 pharmacological activity and all the modulated proteins were enriched to identify the probably regulated pathways, biological processes, cellular components, and molecular functions. In addition, molecular docking was performed using AutoDock 4 and the best-identified hits were subjected to all-atom molecular dynamics simulation and binding energy calculations using molecular mechanics Poisson-Boltzmann surface area (MMPBSA). The compound 4-hydroxycordoin showed the highest druglikeness score and regulated nine proteins of which five were down-regulated and four were upregulated. Similarly, enrichment analysis identified the modulation of multiple pathways concerned with the immune system as well as pathways related to infectious and non-infectious diseases. Likewise, 3'-(3-methyl-2-butenyl)-4′-O-β-d-glucopyranosyl-4,2′-dihydroxychalcone with 3CL^pro, 4-hydroxycordoin with PL^pro and mallotophilippen D with spike protein receptor-binding domain showed highest binding affinity, revealed stable interactions during the simulation, and scored binding free energy of −26.09 kcal/mol, −16.28 kcal/mol, and −39.2 kcal/mol, respectively. Predicted anti-SARS-CoV-2 activities of the benzalacetophenones reflected the requirement of wet lab studies to develop novel antiviral candidates.

The Potential Role of Nigella sativa Seed Oil as Epigenetic Therapy of Cancer

Nigella sativa oil, commonly known as black seed oil (BSO), is a well-known Mediterranean food, and its consumption is associated with beneficial effects on human health. A large number of BSO's therapeutic properties is attributed to its pharmacologically active compound, thymoquinone (TQ), which inhibits cell proliferation and induces apoptosis by targeting several epigenetic players, including the ubiquitin-like, containing plant homeodomain (PHD) and an interesting new gene, RING finger domains 1 (UHRF1), and its partners, DNA methyltransferase 1 (DNMT1) and histone deacetylase 1 (HDAC1). This study was designed to compare the effects of locally sourced BSO with those of pure TQ on the expression of the epigenetic complex UHRF1/DNMT1/HDAC1 and the related events in several cancer cells. The gas chromatographs obtained from GC-MS analyses of extracted BSO showed that TQ was the major volatile compound. BSO significantly inhibited the proliferation of MCF-7, HeLa and Jurkat cells in a dose-dependent manner, and it induced apoptosis in these cell lines. BSO-induced inhibitory effects were associated with a significant decrease in mRNA expression of UHRF1, DNMT1 and HDAC1. Molecular docking and MD simulation showed that TQ had good binding affinity to UHRF1 and HDAC1. Of note, TQ formed a stable metal coordinate bond with zinc tom, found in the active site of the HDAC1 protein. These findings suggest that the use of TQ-rich BSO represents a promising strategy for epigenetic therapy for both solid and blood tumors through direct targeting of the trimeric epigenetic complex UHRF1/DNMT1/ HDAC1.

PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods

Bioinformatic annotation of protein function is essential but extremely sophisticated, which asks for extensive efforts to develop effective prediction method. However, the existing methods tend to amplify the representativeness of the families with large number of proteins by misclassifying the proteins in the families with small number of proteins. That is to say, the ability of the existing methods to annotate proteins in the 'rare classes' remains limited. Herein, a new protein function annotation strategy, PFmulDL, integrating multiple deep learning methods, was thus constructed. First, the recurrent neural network was integrated, for the first time, with the convolutional neural network to facilitate the function annotation. Second, a transfer learning method was introduced to the model construction for further improving the prediction performances. Third, based on the latest data of Gene Ontology, the newly constructed model could annotate the largest number of protein families comparing with the existing methods. Finally, this newly constructed model was found capable of significantly elevating the prediction performance for the 'rare classes' without sacrificing that for the 'major classes'. All in all, due to the emerging requirements on improving the prediction performance for the proteins in 'rare classes', this new strategy would become an essential complement to the existing methods for protein function prediction. All the models and source codes are freely available and open to all users at: https://github.com/idrblab/PFmulDL.

Theoretical investigations on the effects of mutations in important residues of NS1B on its RNA-binding using molecular dynamics simulations

NS1B protein plays an important role in countering host antiviral defense and virulence of influenza virus B, considered as the promising target. The first experimental structure of the NS1B protein has recently been determined, was able to bind to double-stranded RNA (dsRNA). However, few studies attempt to investigate the RNA-binding mechanism of the NS1B. In this study, we provide our understanding of the structure-function relationship, dynamics and RNA-binding mechanism of the NS1B protein by performing molecular dynamics simulations combined and MM-GBSA calculations on the NS1B-dsRNA complex. 12 key residues are identified for RNA-binding by forming hydrogen bonds with the. Our results also demonstrate that mutations (R156A, K160A, R208A and K221A) can cause the local structure changes of NS1B CTD and the hydrogen bonds between NS1B CTD and RNA disappearance, which may be the main reasons for the decrease in RNA-binding affinity. These results mentioned will help us understanding the RNA-binding mechanism and could provide some medicinal chemistry insights chances for rational drug design targeting NS1B protein.

POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability

Mass spectrometry-based proteomic technique has become indispensable in current exploration of complex and dynamic biological processes. Instrument development has largely ensured the effective production of proteomic data, which necessitates commensurate advances in statistical framework to discover the optimal proteomic signature. Current framework mainly emphasizes the generalizability of the identified signature in predicting the independent data but neglects the reproducibility among signatures identified from independently repeated trials on different sub-dataset. These problems seriously restricted the wide application of the proteomic technique in molecular biology and other related directions. Thus, it is crucial to enable the generalizable and reproducible discovery of the proteomic signature with the subsequent indication of phenotype association. However, no such tool has been developed and available yet. Herein, an online tool, POSREG, was therefore constructed to identify the optimal signature for a set of proteomic data. It works by (i) identifying the proteomic signature of good reproducibility and aggregating them to ensemble feature ranking by ensemble learning, (ii) assessing the generalizability of ensemble feature ranking to acquire the optimal signature and (iii) indicating the phenotype association of discovered signature. POSREG is unique in its capacity of discovering the proteomic signature by simultaneously optimizing its reproducibility and generalizability. It is now accessible free of charge without any registration or login requirement at https://idrblab.org/posreg/.

Deciphering the Mechanism of Binding Selectivity of Chlorofluoroacetamide-Based Covalent Inhibitors toward L858R/T790M Resistance Mutation

Covalent modification of the oncogenic mutant epidermal growth factor receptor (EGFR) by small molecules is an efficient strategy for achieving an enhanced and sustained pharmacological effect in the treatment of non-small-cell lung cancer. NSP-037 (18), an irreversible inhibitor of the L858R/T790M double-mutant EGFR (EGFR^DM) using α-chlorofluoroacetamide (CFA) as a novel warhead, has seven times the inhibition selectivity for EGFR^DM over the wild type (EGFR^WT), as compared to clinically approved osimertinib (7). Here, we employ multiple computational approaches to elucidate the mechanism underlining this improved selectivity, as well as the effect of CFA on the selectivity enhancement of inhibitor 18 over 7. We find that EGFR^DM undergoes significantly larger conformational changes than EGFR^WT upon binding to 18. The conformational stability of the diamine side chain and the CFA motif of 18 in the orthosteric site of EGFR^DM is identified as key for the disparate binding mechanism and inhibitory prowess of 18 with respect to EGFR^WT and EGFR^DM and 18's higher selectivity than 7. The binding free energy of the 18-bound complexes is -6.38 kcal/mol greater than that of the 7-bound complexes, explaining the difference in selectivity of these inhibitors. Further, free energy decomposition analysis indicates that the electrostatic contribution of key residues plays an important role in the 18-bound complexes. QM/MM calculations show that the most favored mechanism for the Cys797 alkylation reaction is the direct displacement mechanism through a CFA-based inhibitor, producing a reaction with the lowest energy barrier and most stable product.

Molecular Mechanism for the Allosteric Inhibition of the Human Serotonin Transporter by Antidepressant Escitalopram

Human serotine transporter (hSERT) is one of the most influential drug targets, and its allosteric modulators (e.g., escitalopram) have emerged to be the next-generation medication for psychiatric disorders. However, the molecular mechanism underlying the allosteric modulation of hSERT is still elusive. Here, the simulation strategies of conventional (cMD) and steered (SMD) molecular dynamics were applied to investigate this molecular mechanism from distinct perspectives. First, cMD simulations revealed that escitalopram's binding to hSERT's allosteric site simultaneously enhanced its binding to the orthosteric site. Then, SMD simulation identified that the occupation of hSERT's allosteric site by escitalopram could also block its dissociation from the orthosteric site. Finally, by comparing the simulated structures of two hSERT-escitalopram complexes with and without allosteric modulation, a new conformational coupling between an extracellular (Arg104-Glu494) and an intracellular (Lys490-Glu494) salt bridge was identified. In summary, this study explored the mechanism underlying the allosteric modulation of hSERT by collectively applying two MD simulation strategies, which could facilitate our understanding of the allosteric modulations of not only hSERT but also other clinically important therapeutic targets.