A computational insight into binding modes of inhibitors XD29, XD35, and XD28 to bromodomain-containing protein 4 based on molecular dynamics simulations

Computational Exploration of Naturally Occurring Flavonoids as TGF-β Inhibitors in Breast Cancer: Insights from Docking and Molecular Dynamics Simulations and In-vitro Cytotoxicity Study

Breast cancer is a global health concern, demanding innovative treatments. Targeting the Transforming Growth Factor-beta (TGF-β) signaling pathway, pivotal in breast cancer, is a promising approach. TGF-β inhibits proliferation via G1 phase cell cycle arrest, acting as a suppressor initially, but in later stages, it promotes progression by enhancing motility, invasiveness, and metastasis formation. This study explores naturally occurring flavonoids' interactions with TGF-β. Using molecular docking against the protein's crystal structure (PDB Id: 1PY5), Gossypin showed the highest docking score and underwent molecular dynamics simulation, revealing complex flexibility and explaining how flavonoids impede TGF-β signaling in breast cancer. ADMET predictions adhered to Lipinski's rule of Five. Insights into flavonoid-TGF-β binding offer a novel angle for breast cancer treatment. Flavonoids having a good docking score like gossypin, morin, luteolin and taxifolin shown potent cytotoxic effect on breast cancer cell line, MCF-7. Understanding these interactions could inspire flavonoid-based therapies targeting TGF-β to halt breast cancer growth. These findings pave the way for personalized, targeted breast cancer therapies, offering hope against this formidable disease.

Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members.

Antimicrobial activity of Geranyl acetate against cell wall synthesis proteins of P. aeruginosa and S. aureus using molecular docking and simulation

Incidences of Methicillin-Resistant Staphylococcus aureus and Multi-Drug Resistant Pseudomonas aeruginosa causing skin and soft tissue infections are becoming more prevalent due to repeated mutations and changes in the environment. Coriandrum sativum, a well-known Indian herbal medicinal plant, is shown to have antioxidant, antibacterial, and anti-inflammatory activity. This comparative study focuses on the molecular docking (PyRx v0.9.8) of ligand binding domains of WbpE Aminotransferase involved in O-antigen assembly in Pseudomonas aeruginosa (3NU7) and Beta-Lactamase found in Staphylococcus aureus (1BLC) with selected phytocompounds of Coriandrum sativum along with a known binder and a clinical reference drug. This was followed by molecular dynamics simulation studies (GROMACS v2019.4) for the docked complexes (with Geranyl acetate) with the best binding affinities (-23.4304 kJ/mol with Beta-Lactamase and -28.4512 kJ/mol with WbpE Aminotransferase) and maximum hydrogen bonds. Molecular dynamics simulation studies for both the proteins demonstrated that the complex with Geranyl acetate showed stability comparable to the complex with reference drug observed via Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) and H-bond analyses. Changes in the secondary structural elements indicated that Geranyl acetate could possibly cause improper functioning of WbpE Aminotransferase leading to disrupted cell wall formation. Further, MM/PBSA analyses showed significant binding affinity of Geranyl acetate with WbpE Aminotransferase and Beta-Lactamase. This study aims to provide rationale for further studies of Coriandrum sativum as an antimicrobial, and to contextualise the results in the current scenario of growing antimicrobial resistance. HIGHLIGHTSPhytoconstituents present in Coriandrum sativum show significant binding affinity to the proteins in Pseudomonas aeruginosa and Staphylococcus aureus.Geranyl acetate exhibited the highest binding affinity with WbpE Aminotransferase involved in O-antigen assembly in Pseudomonas aeruginosa (PDB ID:3NU7) and Beta-Lactamase found in Staphylococcus aureus (PDB ID: 1BLC)Molecular dynamics simulation analyses show that the phytoconstituent, Geranyl acetate has an effect similar to the clinical reference drug, thus exhibiting potential antibacterial activity.Communicated by Ramaswamy H. Sarma.

Discovery of novel bromodomain-containing protein 4 (BRD4-BD1) inhibitors combined with 3d-QSAR, molecular docking and molecular dynamics in silico

Bromine-containing domain protein 4 (BRD4) plays a crucial role in regulating transcription and genome stability. Selective inhibitors of BRD4-BD1 can specifically target specific bromine domains to affect cell proliferation, apoptosis, and differentiation. In this work, 43 selective benzoazepinone BRD4-BD1 inhibitors were studied using molecular simulations and three-dimensional quantitative conformation relationships (3D-QSAR). A reliable 3D-QSAR model was established based on COMFA (Q2 = 0.532, R2 = 0.981) and COMSIA (S + E + H (Q2 = 0.536, R2 = 0.979) two different analysis methods. Through 3D-QSAR model prediction and quantum chemical analysis, 15 small molecules with stronger inhibitory activity than the template compounds were constructed, and 5 new compounds with higher predictive activity and binding affinity were screened by molecular docking and ADMET methods. According to the molecular dynamics simulation, the key residues that can interact with BRD4-BD1 protein and molecular docking results are consistent, including ASN140, MET132, GLN85, MET105, ASN135 and TYR97. From the MD trajectory, we calculated and analyzed RMSD, RMSF, free binding energy, FECM, DCCM and PCA, the loop region formed by amino acids VAL45∼PRO62 showed α-helix, β-folding and clustering towards the active center with the extension of simulation time. Further optimization of the structure of active candidate compounds A6, A11, A14, and A15 will provide the necessary theoretical basis for the synthesis and activity evaluation of novel BRD4-BD1 inhibitors.Communicated by Ramaswamy H. Sarma.

Prediction of interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins from dihedral angles

Intrinsically disordered proteins (IDPs) are proteins that do not form uniquely defined three-dimensional (3-D) structures. Experimental research on IDPs is difficult since they go against the traditional protein structure-function paradigm. Although there are several predictors of disorder based on amino acid sequences, but very limited based on the 3-D structures of proteins. Dihedral angles have a significant role in predicting protein structure because they establish a protein's backbone, which, coupled with its side chain, establishes its overall shape. Here, we have carried out atomistic Molecular Dynamics (MD) simulations on four different proteins: one ordered protein (Monellin), two partially disordered proteins (p53-TAD and Amyloid beta (Aβ1-42) peptide), and one completely disordered protein (Histatin 5). The MD simulation trajectories for the corresponding four proteins were used to conduct dihedral angle (ϕ and ѱ) analysis. Then, the average dihedral angles for each of the residues were calculated and plotted against the residue index. We noticed steep rises or falls in the average ϕ value at certain locations in the plot. These sudden shifts in the average ϕ value reflect the interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins. Using this method, the probable conformer of a protein with a higher degree of disorder can be found among the ensembles of structures sampled during the MD simulations. The results of our study offer new understandings on precisely identifying regions of various degrees of disorder in intrinsically disordered proteins.Communicated by Ramaswamy H. Sarma.

Identification of novel natural product inhibitors of BRD4 using high throughput virtual screening and MD simulation

Bromodomains are evolutionarily conserved structural motifs that recognize acetylated lysine residues on histone tails. They play a crucial role in shaping chromatin architecture and regulating gene expression in various biological processes. Mutations in bromodomains containing proteins lead to multiple human diseases, which makes them attractive target for therapeutic intervention. Extensive studies have been done on BRD4 as a target for several cancers, such as Acute Myeloid Leukemia (AML) and Burkitt Lymphoma. Several potential inhibitors have been identified against the BRD4 bromodomain. However, most of these inhibitors have drawbacks such as non-specificity and toxicity, decreasing their appeal and necessitating the search for novel non-toxic inhibitors. This study aims to address this need by virtually screening natural compounds from the NPASS database against the Kac binding site of BRD4-BD1 using high throughput molecular docking followed by similarity clustering, pharmacokinetic screening, MD simulation and MM-PBSA binding free energy calculations. Using this approach, we identified five natural product inhibitors having a similar or better binding affinity to the BRD4 bromodomain compared to JQ1 (previously reported inhibitor of BRD4). Further systematic analysis of these inhibitors resulted in the top three hits: NPC268484 (Palodesangren-B), NPC295021 (Candidine) and NPC313112 (Buxifoliadine-D). Collectively, our in silico results identified some promising natural products that have the potential to act as potent BRD4-BD1 inhibitors and can be considered for further validation through future in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

The role of loop dynamics in the prediction of ligand-protein binding enthalpy

The enthalpic and entropic components of ligand-protein binding free energy reflect the interactions and dynamics between ligand and protein. Despite decades of study, our understanding and hence our ability to predict these individual components remains poor. In recent years, there has been substantial effort and success in the prediction of relative and absolute binding free energies, but the prediction of the enthalpic (and entropic) contributions in biomolecular systems remains challenging. Indeed, it is not even clear what kind of performance in terms of accuracy could currently be obtained for such systems. It is, however, relatively straight-forward to compute the enthalpy of binding. We thus evaluated the performance of absolute enthalpy of binding calculations using molecular dynamics simulation for ten inhibitors against a member of the bromodomain family, BRD4-1, against isothermal titration calorimetry data. Initial calculations, with the AMBER force-field showed good agreement with experiment (R² = 0.60) and surprisingly good accuracy with an average of root-mean-square error (RMSE) = 2.49 kcal mol^-1. Of the ten predictions, three were obvious outliers that were all over-predicted compared to experiment. Analysis of various simulation factors, including parameterization, buffer concentration and conformational dynamics, revealed that the behaviour of a loop (the ZA loop on the periphery of the binding site) strongly dictates the enthalpic prediction. Consistent with previous observations, the loop exists in two distinct conformational states and by considering one or the other or both states, the prediction for the three outliers can be improved dramatically to the point where the R² = 0.95 and the accuracy in terms of RMSE improves to 0.90 kcal mol^-1. However, performance across force-fields is not consistent: if OPLS and CHARMM are used, different outliers are observed and the correlation with the ZA loop behaviour is not recapitulated, likely reflecting parameterization as a confounding problem. The results provide a benchmark standard for future study and comparison.

New molecular insights for 4H-1,2,4-triazole derivatives as inhibitors of tankyrase and Wnt-signaling antagonist: a molecular dynamics simulation study

Tankyrase (TNKS) enzymes remained central biotargets to treat Wnt-driven colorectal cancers. The success of Olaparib posited the druggability of PARP family enzymes depending on their role in tumor proliferation. In this work, an MD-simulation-based comparative assessment of the protein-ligand interactions using the best-docked poses of three selected compounds (two of the designed and previously synthesized molecules obtained through molecular docking and one reported TNKS inhibitor) was performed for a 500 ns period. The PDB:ID-7KKP and 3U9H were selected for TNKS1 and TNKS2, respectively. The Molecular Mechanics Generalized Born Surface Area (MM-GBSA) based binding energy data exhibited stronger binding of compound-15 (average values of -102.92 and -104.32 kcal/mol for TNKS1 and TNKS2, respectively) as compared to compound-22 (average values of -82.99 and -85.68 kcal/mol for TNKS1 and TNKS2, respectively) and the reported compound-32 (average values of -81.89 and -74.43 kcal/mol for TNKS1 and TNKS2, respectively). Compound-15 and compound-22 exhibited comparable or superior binding to both receptors forming stable complexes when compared to that of compound-32 upon examining their MD trajectories. The key contributors were hydrophobic stacking and optimum hydrogen bonding allowing these molecules to occupy the adenosine pocket by interfacing D-loop residues. The results of bond distance analysis, radius of gyration, root mean square deviation, root mean square fluctuation, snapshots at different time intervals, LUMO-HUMO energy differences, electrostatic potential calculations, and binding free energy suggested better binding efficiency for compound-15 to TNKS enzymes. The computed physicochemical and ADMET properties of compound-15 were encouraging and could be explored further for drug development.Communicated by Ramaswamy H. Sarma.

Theoretical exploration of the binding selectivity of inhibitors to BRD7 and BRD9 with multiple short molecular dynamics simulations

Bromodomain-containing proteins 7 and 9 (BRD7 and BRD9) have been considered as potential targets of clinical drug design toward treatment of human cancers and other diseases. Multiple short molecular dynamics simulations and binding free energy predictions were carried out to decipher the binding selectivity of three inhibitors 4L2, 5U6, and 6KT toward BRD7 and BRD9. The results show that 4L2 has more favorable binding ability to BRD7 over BRD9 compared to 5U6 and 6KT, while 5U6 and 6KT possess more favorable associations with BRD9 than BRD7. Furthermore, estimations of residue-based free energy decompositions further identify that four common residue pairs, including (F155, F44), (V160, V49), (Y168, Y57) and (Y217, Y106) in (BRD7, BRD9) generate obvious binding differences with 4L2, 5U6, and 6KT, which mostly drives the binding selectivity of 4L2, 5U6, and 6KT to BRD7 and BRD9. Dynamic information arising from trajectory analysis also suggests that inhibitor bindings affect structural flexibility and motion modes, which is responsible for the partial selectivity of 4L2, 5U6, and 6KT toward BRD7 and BRD9. As per our expectation, this study theoretically provides useful hints for design of dual inhibitors with high selectivity on BRD7 and BRD9.

Bromodomains (BRDs) are structurally conserved epigenetic reader modules observed in numerous chromatin- and transcription-associated proteins that have a capability to identify acetylated lysine residues.

The binding mechanism of NHWD-870 to bromodomain-containing protein 4 based on molecular dynamics simulations and free energy calculation

Bromodomain and extra-terminal (BET) proteins (BRD2, BRD3, BRD4, and BRDT) are epigenetic readers with tandem bromodomains.

BRD4: quantum mechanical protein–ligand binding free energies using the full-protein DFT-based QM-PBSA method

Fully quantum mechanical approaches to calculating protein–ligand free energies of binding have the potential to reduce empiricism and explicitly account for all physical interactions responsible for protein–ligand binding.

Molecular Dynamic Simulations of Bromodomain and Extra-Terminal Protein 4 Bonded to Potent Inhibitors

Bromodomain and extra-terminal domain (BET) subfamily is the most studied subfamily of bromodomain-containing proteins (BCPs) family which can modulate acetylation signal transduction and produce diverse physiological functions. Thus, the BET family can be treated as an alternative strategy for targeting androgen-receptor (AR)-driven cancers. In order to explore the effect of inhibitors binding to BRD4 (the most studied member of BET family), four 150 ns molecular dynamic simulations were performed (free BRD4, Cpd4-BRD4, Cpd9-BRD4 and Cpd19-BRD4). Docking studies showed that Cpd9 and Cpd19 were located at the active pocket, as well as Cpd4. Molecular dynamics (MD) simulations indicated that only Cpd19 binding to BRD4 can induce residue Trp81-Ala89 partly become α-helix during MD simulations. MM-GBSA calculations suggested that Cpd19 had the best binding effect with BRD4 followed by Cpd4 and Cpd9. Computational alanine scanning results indicated that mutations in Phe83 made the greatest effects in Cpd9-BRD4 and Cpd19-BRD4 complexes, showing that Phe83 may play crucial roles in Cpd9 and Cpd19 binding to BRD4. Our results can provide some useful clues for further BCPs family search.

Atomistic insights into the selective therapeutic activity of 6-(2,4-difluorophenoxy)-5-((ethylmethyl)pyridine-3-yl)-8-methylpyrrolo[1,2-a]pyrazin-1(2H)-one towards bromodomain-containing proteins

Cross-target effect has been one of the major mechanisms of drug toxicity, this has necessitated the design of inhibitors that are specifically tailored to target particular biomolecules. 6-(2,4-difluorophenoxy)-5-((ethylmethyl)pyridine-3-yl)-8-methylpyrrolo[1,2-a] pyrazin-1(2H)-one (Cpd38) is an inhibitor possessing high inhibition rate and tailored specificity towards bromodomain-containing protein 4 (BRD4). In this research, we used an array of computational techniques to provide insight at the atomistic level the specific targeting of BRD4 by Cpd38 relative to the binding of Cpd38 with E1A binding protein P300 (EP300); another bromodomain-containing protein (BCP). Comparatively, binding of Cpd38 improved the conformational stability and compactness of BRD4 protein when compared to the Cpd38 bound EP300. Also, Cpd38 induced a conformational change in the active site of BRD4 that facilitated a complementary pose between Cpd38 and BRD4 suitable for effective atomistic interactions. Expectedly, thermodynamic calculations revealed that the Cpd38-BRD4 system had higher binding energy (-36.11 Kcal/mol) than the Cpd38-EP300 system with a free binding energy of -15.86 Kcal/mol. Noteworthy is the opposing role Trp81 (acting as hydrogen bond acceptor) and Pro1074 (acting as hydrogen bond donor) found on the WPF and LPF loops respectively play in maintaining Cpd38 stability. Furthermore, the hydrogen bond acceptor/donator ratio was approximately 4:1 in Cpd38-BRD4 system compared with 2:1 in Cpd38-EP300 system. Taken together, atomistic insights and structural perspectives detailed in this report supplements the experimental report supporting the improved selectivity of Cpd38 for BRD4 ahead of other BCPs while providing leeway for the future design of BET selective agents with better pharmacological profile.

Molecular mechanism concerning conformational changes of CDK2 mediated by binding of inhibitors using molecular dynamics simulations and principal component analysis

Cyclin-dependent kinase 2 (CDK2) has been regarded as a promising drug target for anti-tumour agents. In this study, molecular dynamics (MD) simulations and principal component (PC) analysis were used to explore binding mechanism of three inhibitors 1PU, CDK, 50Z to CDK2 and influences of their bindings on conformational changes of CDK2. The results show that bindings of inhibitors yield obvious impacts on internal dynamics, movement patterns and conformational changes of CDK2. In addition, molecular mechanics generalized Born surface area (MM-GBSA) was applied to calculate binding free energies between three inhibitors and CDK2 and evaluate their binding ability to CDK2. The results show that CDK has the strongest binding to CDK2 among the current three inhibitors. Residue-based free energy decomposition method was further utilized to decode the contributions of a single residue to binding of inhibitors, and it was found that three inhibitors not only produce hydrogen bonding interactions and hydrophobic interactions with key residues of CDK2, which promotes binding of three inhibitors to CDK2, but also share similar binding modes. This work is expected to be helpful for design of efficient drugs targeting CDK2.

Discovery of a hidden transient state in all bromodomain families

Bromodomains (BDs) are small protein modules that interact with acetylated marks in histones. These posttranslational modifications are pivotal to regulate gene expression, making BDs promising targets to treat several diseases. While the general structure of BDs is well known, their dynamical features and their interplay with other macromolecules are poorly understood, hampering the rational design of potent and selective inhibitors. Here, we combine extensive molecular dynamics simulations, Markov state modeling, and available structural data to reveal a transiently formed state that is conserved across all BD families. It involves the breaking of two backbone hydrogen bonds that anchor the ZA-loop with the αA helix, opening a cryptic pocket that partially occludes the one associated to histone binding. By analyzing more than 1,900 experimental structures, we unveil just two adopting the hidden state, explaining why it has been previously unnoticed and providing direct structural evidence for its existence. Our results suggest that this state is an allosteric regulatory switch for BDs, potentially related to a recently unveiled BD-DNA-binding mode.

Binding selectivity of inhibitors toward the first over the second bromodomain of BRD4: theoretical insights from free energy calculations and multiple short molecular dynamics simulations

Bromodomain-containing protein 4 (BRD4) plays an important role in mediating gene transcription involved in cancers and non-cancer diseases such as acute heart failure and inflammatory diseases. In this work, multiple short molecular dynamics (MSMD) simulations are integrated with a molecular mechanics generalized Born surface area (MM-GBSA) approach to decipher binding selectivity of three inhibitors 8NS, 82Y, and 837 toward two domains BD1 and BD2 of BRD4. The results demonstrate that the enthalpy effects play critical roles in selectivity identification of inhibitors toward BD1 and BD2, determining that 8NS has better selectivity toward BD2 than BD1, while 82Y and 837 more favorably bind to BD1 than BD2. A residue-based free-energy decomposition method was used to calculate an inhibitor-residue interaction spectrum and unveil contributions of separate residues to binding selectivity. The results identify six common residues, containing (P82, P375), (V87, V380), (L92, L385), (L94, L387), (N140, N433), and (I146, V439) individually belonging to (BD1, BD2) of BRD4, and yield a considerable binding difference of inhibitors to BD1 and BD2, suggesting that these residues play key roles in binding selectivity of inhibitors toward BD1 and BD2 of BRD4. Therefore, these results provide useful dynamics information and a structure affinity relationship for the development of highly selective inhibitors targeting BD1 and BD2 of BRD4.

Probing molecular mechanism of inhibitor bindings to bromodomain-containing protein 4 based on molecular dynamics simulations and principal component analysis

It is well known that bromodomain-containing protein 4 (BRD4) has been thought as a promising target utilized for treating various human diseases, such as inflammatory disorders, malignant tumours, acute myelogenous leukaemia (AML), bone diseases, etc. For this study, molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA) were integrated together to uncover binding modes of inhibitors 8P9, 8PU, and 8PX to BRD4(1). The results obtained from binding free energy calculations show that van der Waals interactions act as the main regulator in bindings of inhibitors to BRD4(1). The information stemming from PCA reveals that inhibitor associations extremely affect conformational changes, internal dynamics, and movement patterns of BRD4(1). Residue-based free energy decomposition method was wielded to unveil contributions of independent residues to inhibitor bindings and the data signify that hydrogen bonding interactions and hydrophobic interactions are decisive factors affecting bindings of inhibitors to BRD4(1). Meanwhile, eight residues Trp81, Pro82, Val87, Leu92, Leu94, Cys136, Asn140, and Ile146 are recognized as the common hot interaction spots of three inhibitors with BRD4(1). The results from this work are expected to provide a meaningfully theoretical guidance for design and development of effective inhibitors inhibiting of the activity of BRD4.

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

BACKGROUND

Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world's highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics.

OBJECTIVE

In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed.

RESULTS

Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design.

CONCLUSION

This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

Revealing binding selectivity of inhibitors toward bromodomain-containing proteins 2 and 4 using multiple short molecular dynamics simulations and free energy analyses

Emerging evidences indicate bromodomain-containing proteins 2 and 4 (BRD2 and BRD4) play critical roles in cancers, inflammations, cardiovascular diseases and other pathologies. Multiple short molecular dynamics (MSMD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were applied to investigate the binding selectivity of three inhibitors 87D, 88M and 89G towards BRD2 over BRD4. The root-mean-square fluctuation (RMSF) analysis indicates that the structural flexibility of BRD4 is stronger than that of BRD2. Moreover the calculated distances between the C_α atoms in the centres of the ZA_loop and BC_loop of BRD4 are also bigger than that of BRD2. The rank of binding free energies calculated using MM-GBSA method agrees well with that determined by experimental data. The results show that 87D can bind more favourably to BRD2 than BRD4, while 88M has better selectivity on BRD4 over BRD2. Residue-based free-energy decomposition method was utilized to estimate the inhibitor-residue interaction spectrum and the results not only identify the hot interaction spots of inhibitors with BRD2 and BRD4, but also demonstrate that several common residues, including (W370, W374), (P371, P375), (V376, V380) and (L381, L385) belonging to (BRD2, BRD4), generate significant binding difference of inhibitors to BRD2 and BRD4.

Computational investigation on the effect of Oleuropein aglycone on the α-synuclein aggregation

Parkinson's disease (PD) is considered to be the second most common progressive neurodegenerative brain disorder after Alzheimer's disease, which is caused by misfolding and aggregation of Alpha-synuclein (α-synuclein). It is characterized by distinct aggregated fibrillary form of α-synuclein known as the Lewy bodies and Lewy neurites. The most promising approach to combat PD is to prevent the misfolding and subsequent aggregation of α-synuclein. Recently, Oleuropein aglycone (OleA) has been reported to stabilize the monomeric structure of α-synuclein, subsequently favoring the growth of nontoxic aggregates. Therefore, understanding the conformational dynamics of α-synuclein monomer in the presence of OleA is significant. Here, we have investigated the effect of OleA on the conformational dynamics and the aggregation propensity of α-synuclein using molecular dynamics simulation. From molecular dynamics trajectory analysis, we noticed that when OleA is bound to α-synuclein, the intramolecular distance between non-amyloid-β component domain and C-terminal domain of α-synuclein was increased, whereas long-range hydrophobic interactions between the two region were reduced. Oleuropein aglycone was found to interact with the N-terminal domain of α-synuclein, making this region unavailable for interaction with membranes and lipids for the formation of cellular toxic aggregates. From the binding-free energy analysis, we found binding affinity between α-synuclein and OleA to be indeed high (ΔG_bind = -12.56 kcal mol^-1 from MM-PBSA and ΔG_bind = -27.41 kcal mol^-1from MM-GBSA). Our findings in this study thus substantiate the effect of OleA on the structure and stabilization of α-synuclein monomer that subsequently favors the growth of stable and nontoxic aggregates.Communicated by Ramaswamy H. Sarma.

Molecular mechanism of inhibitor bindings to bromodomain-containing protein 9 explored based on molecular dynamics simulations and calculations of binding free energies

Recently, bromodomain-containing protein 9 (BRD9) has been a prospective therapeutic target for anticancer drug design. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were adopted to explore binding modes of three inhibitors (5SW, 5U2, and 5U6) to BRD9 and identify the hot spot of the inhibitor-BRD9 binding. The results indicate that the inhibitor 5SW has the strongest binding ability to BRD9 among the current three inhibitors. Furthermore, the rank of the binding free energies predicted by MM-GBSA approach agrees with that determined by the experimental values. In addition, inhibitor-residue interactions were computed by using residue-based free-energy decomposition method and the results suggest that residue His42 produces the CH-H interactions, residues Asn100, Ile53 and Val49 produce the CH-[Formula: see text] interactions with three inhibitors and Tyr106, Phe45 and Phe44 generate the π-π interactions with inhibitors. Notably, the residue Asn140 forms hydrogen bonding interactions with three inhibitors. This research is expected to provide useful molecular basis and dynamics information at atomic levels for the design of potent inhibitors inhibiting the activity of BRD9.

Revealing binding selectivity of ligands toward murine double minute 2 and murine double minute X based on molecular dynamics simulations and binding free energy calculations

It is well known that the interactions of p53 with murine double minute 2 and murine double minute X, namely MDM2 and MDMX, have been significant targets of efficient anti-cancer drug design. In this study, molecular dynamics (MD) simulations, principal component (PC) analysis and binding free energy calculations are combined to recognize binding selectivity of three ligands to MDM2 and MDMX. The binding free energies were estimated by using molecular mechanics generalized Born surface area (MM-GBSA) method and the obtained results display that the increase in the binding enthalpy of three ligands to MDM2 relative to MDMX mainly drives the binding selectivity of them toward MDM2 and MDMX. The information obtained from PC analysis shows that the associations of ligands exert important impacts on internal dynamics of MDM2 and MDMX. Meanwhile, the calculations of residue-based free energy decomposition not only identify the hot interaction spots of ligands with MDM2 and MDMX, but also show the residues (L54, M53), (Y67, Y66), (V93, V92), (H96, P95), (I99, I98) and (Y100, Y99) in (MDM2, MDMX) are responsible for most contributions to the binding selectivity of three ligands toward MDM2 and MDMX. It is believed that this work can provide useful information for design of highly selective and dual inhibitors targeting MDM2 and MDMX.Communicated by Ramaswamy H. Sarma.

Understanding conformational diversity of heat shock protein 90 (HSP90) and binding features of inhibitors to HSP90 via molecular dynamics simulations

Heat shock protein 90 (HSP90) is a promising target for treatment of cancer, and inhibitor bindings can generate efficient suppression on tumor in multiple ways. In this work, 140-ns molecular dynamics simulations were performed on six systems. Principal component analysis was subsequently carried out to explore the conformational diversity of HSP90. The results suggest that inhibitor bindings induce large conformational changes of HSP90, which tends to enlarge the volume of the binding pocket to facilitate the entrance of inhibitors. Hierarchical clustering analyses, the calculation of the energy contribution of each atom, and the analyses of hydrogen-bonding interactions were performed. The results indicate that 20 residues in group A of the hierarchical tree are responsible for major contributions, and van der Waals interactions as well as hydrogen-bonding interactions between important residues in HSP90 and key regions of inhibitors are the main force for promoting inhibitor bindings. We expect that this work can provide useful theoretical information for development of efficient inhibitors targeting HSP90.

Design, synthesis, biological evaluation and molecular dynamics studies of 4-thiazolinone derivatives as protein tyrosine phosphatase 1B (PTP1B) inhibitors

Protein tyrosine phosphatase 1B (PTP1B) is a key negative regulator of insulin signaling pathway, and more and more studies have shown that it is a potential target for the treatment of type 2 diabetes mellitus (T2DM). In this study, 17 new 4-thiazolinone derivatives were designed and synthesized as novel PTP1B inhibitors, and ADMET prediction confirmed that these compounds were to be drug-like. In vitro enzyme activity experiments were performed on these compounds, and it was found that a plurality of compounds had good inhibitory activity and high selectivity against PTP1B protein. Among them, compound 7p exhibited the best inhibitory activity with an IC₅₀ of 0.92 μM. The binding mode of compound 7p and PTP1B protein was explored, revealing the reason for its high efficiency. In addition, molecular dynamics simulations for the PTP1B^WT and PTP1B^comp#7p systems revealed the effects of compound 7p on PTP1B protein at the molecular level. In summary, the study reported for the first time that 4-thiazolinone derivatives as a novel PTP1B inhibitor had good inhibitory activity and selectivity for the treatment of T2DM, providing more options for the development of PTP1B inhibitors. AbbreviationsBBBblood-brain barrierCDC25Bcell division cycle 25 homolog BCYP2D6Cytochrome P450 2D6 bindingDCCMdynamic cross-correlation mapDSDiscovery StudioH bondhydrogen bondHIAhuman intestinal absorptionLARleukocyte antigen-related phosphataseMDmolecular dynamicsMEG-2maternal-effect germ-cell defective 2MM-PBSAmolecular mechanics Poisson Boltzmann surface area)PCAprincipal component analysisPDBProtein Data BankpNPPp-nitrophenyl phosphatePPBplasma protein bindingPTP1Bprotein tyrosine phosphotase 1BRMSDroot mean square deviationRMSFroot mean square fluctuationSHP-1src homologous phosphatase-1SHP-2src homologous phosphatase-2SPCsingle-point chargeTCPTPT cell protein tyrosine phosphataseT2DMType 2 diabetes mellitusVDWvan der WaalsCommunicated by Ramaswamy H. Sarma.

Decoding molecular mechanism of inhibitor bindings to CDK2 using molecular dynamics simulations and binding free energy calculations

CDK2 can be used as an attractive target for development of efficient inhibitors curing multiple disease relating with CDK2. In this work, molecular dynamics (MD) simulations and binding free energy calculations were coupled to probe conformational changes of CDK2 due to inhibitor associations and binding mechanisms of inhibitors PM1, FMD and X64 to CDK2. The results suggest that the binding strength of FMD and X64 to CDK2 is stronger than that of PM1. Principal component (PC) analysis and cross-correlation map calculations based on the equilibrated MD trajectories demonstrate that the structural difference in inhibitors exerts important impact on motion modes and dynamics behavior of CDK2. Residue-based free energy decomposition method was adopted to estimate the inhibitor-residue spectrum. The results not only efficiently identify the hot interaction spot of inhibitors with CDK2 but also show that the hydrophobic rings R1, R2 and R3 as well as polar groups of three inhibitors play key roles in favorably binding of inhibitors to CDK2. This work is expected to contribute energetic basis and dynamics information to development of promising inhibitors toward CDK2.Communicated by Ramaswamy H. Sarma.

In silico study directed towards identification of novel high-affinity inhibitors targeting an oncogenic protein: BRD4-BD1

Bromodomain-containing protein 4 (BRD4) is a member of the bromodomain and extra-terminal domain (BET) family of proteins. It epigentically regulates the transcription of growth-promoting genes and has become an attractive target for the development of anticancer and anti-inflammatory agents. In the current study, we performed an in silico screening of a small-molecule chemical library against the acetyl-lysine binding site of the first bromodomain (BD1) in BRD4 protein. Potential inhibitors identified through virtual screening were further studied through molecular dynamics simulations, water entrapment analysis and Molecular Mechanics (MM)/Poisson-Boltzmann surface area (PBSA) binding free energy calculations. Many of the identified compounds exhibit better G-score (-11.64 kcal∙mol^-1 to -10.31 kcal∙mol^-1) and predicted binding affinity (-9.66 kcal∙mol^-1 to -6.63 kcal∙mol^-1) values towards BRD4-BD1 than that of the reference compound (+)-JQ1. Molecular dynamics simulation studies show that in free-form BRD4 the reported conserved water molecules are not retained at their specific positoins due to flexibiliy in the ZA-loop. In BRD4-ligand complexes the number and positions of conserved water molecules depends on the bound ligand. Identified potential inhibitors bind stably at the acetyl-lysine binding pocket of BRD4 and form direct and water-mediated hydrogen bonds with higher occupancy which may contribute to ligand specificity towards BRD4-BD1. Further, through MM/PBSA we calculated the binding free energies of selected compounds, which shows that they have comparable energies to that of (+)-JQ1, while NSC744713 shows better binding free energy.

From bench to bedside, via desktop. Recent advances in the application of cutting-edge in silico tools in the research of drugs targeting bromodomain modules

The discipline of drug discovery has greatly benefited by computational tools and in silico algorithms aiming at rationalization of many related processes, from the stage of early hit identification to the preclinical phases of drug candidate validation. The various methodologies referred to as molecular modeling tools span a broad spectrum of applications, from straightforward approaches such as virtual screening of compound libraries to more advanced techniques involving the precise estimation of free energy upon binding of the candidate drug to its macromolecular target. To this end, we report an overview of specific studies where implementation of such sophisticated modeling algorithms has shown to be indispensable for addressing challenging systems and biological questions otherwise difficult to answer. We focus our attention on the emerging field of bromodomain inhibitors. Bromodomains are small modules involved in epigenetic signaling and currently comprise high-priority targets for developing both drug candidates and chemical probes for basic biomedical research. We attempt a critical presentation of selected cases utilizing cutting-edge in silico methodologies, with our main emphasis being on absolute or relative free energy simulations, on implementation of quantum-mechanics level calculations and on characterization of solvent thermodynamics. We discuss the advantages and strengths as well as the drawbacks and weaknesses of computational tools utilized in those works and we attempt to comment on specific issues related to their integration into the regular medicinal chemistry practice. Our conclusion is that while such methods indeed represent highly promising resources for further advancing the discipline, their application is not always trivial.

Insight into selective mechanism of class of I-BRD9 inhibitors toward BRD9 based on molecular dynamics simulations

Recently, bromodomain-containing protein 9 (BRD9), 7 (BRD7), and 4 (BRD4) have been potential targets of anticancer drug design. Molecular dynamic simulations followed by molecular mechanics Poisson-Boltzmann surface area calculation were performed to study the selective mechanism of I-BRD9 inhibitor H1B and its derivatives N1D, TVU, and 5V2 toward BRD9 and BRD4. The rank of our calculated binding free energies agrees with that of the experimental data. The results show that binding free energy of H1B to BRD7 is slightly lower than that of H1B to BRD9, and all four inhibitors bind more tightly to BRD9 than to BRD4. Decomposition of binding free energies into individual residues implies that Ile164 and Asn211 in BRD7 and Ile53 and Asn100 in BRD9 play a significant role in the selectivity of H1B toward BRD7 and BRD9. Besides, several key residues Phe44, Ile53, Asn100, Thr104 in BRD9 and Pro82, Lys91, Asn140, Asp144 in BRD4 that are located in the ZA-loop and BC-loop provide significant contributions to binding selectivity of inhibitors to BRD9 and BRD4. This study is expected to provide important theoretical guidance for rational designs of highly selective inhibitors targeting BRD9 and BRD4.

Dynamics revelation of conformational changes and binding modes of heat shock protein 90 induced by inhibitor associations

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment. The current work integrates molecular dynamics (MD) simulations, calculations of binding free energy, and principal component (PC) analysis with scanning of inhibitor–residue interaction to probe the binding modes of inhibitors YK9, YKJ and YKI to Hsp90 and identify the hot spot of the inhibitor–Hsp90 binding. The results suggest that the introductions of two groups G1 and G2 into YKJ and YKI strengthen the binding ability of YKJ and YKI to Hsp90 compared to YK9. PC analysis based MD trajectories prove that inhibitor bindings exert significant effects on the conformational changes, internal dynamics and motion modes of Hsp90, especially for the helix α2 and the loops L1 and L2. The calculations of residue-based free energy decomposition and scanning of the inhibitor–Hsp90 interaction suggest that six residues L107, G108, F138, Y139, W162 and F170 construct the common hot spot of the inhibitor–residue interactions. Moreover the substitutions of the groups G1 and G2 in YKJ and YKI lead to two additional hydrogen bonding interactions and multiple hydrophobic interactions for bindings of YKJ and YKI to Hsp90. This work is also expected to contribute theoretical hints for the design of potent inhibitors toward Hsp90.

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment.