Displaying publications 1 - 20 of 29 in total

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  1. Abdo A, Salim N
    J Chem Inf Model, 2011 Jan 24;51(1):25-32.
    PMID: 21155550 DOI: 10.1021/ci100232h
    Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in the Bayesian network are encoded using a set of conditional probability distributions, which can be estimated by the fragment weighting function, a function of the frequencies of the fragments in the molecule or the reference structure as well as throughout the collection. The weighting function combines one or more fragment weighting schemes. In this paper, we have investigated five different weighting functions and present a new fragment weighting scheme. Later on, these functions were modified to combine the new weighting scheme. Simulated virtual screening experiments with the MDL Drug Data Report (23) and maximum unbiased validation data sets show that the use of new weighting scheme can provide significantly more effective screening when compared with the use of current weighting schemes.
  2. Abdo A, Chen B, Mueller C, Salim N, Willett P
    J Chem Inf Model, 2010 Jun 28;50(6):1012-20.
    PMID: 20504032 DOI: 10.1021/ci100090p
    A Bayesian inference network (BIN) provides an interesting alternative to existing tools for similarity-based virtual screening. The BIN is particularly effective when the active molecules being sought have a high degree of structural homogeneity but has been found to perform less well with structurally heterogeneous sets of actives. In this paper, we introduce an alternative network model, called a Bayesian belief network (BBN), that seeks to overcome this limitation of the BIN approach. Simulated virtual screening experiments with the MDDR, WOMBAT and MUV data sets show that the BIN and BBN methods allow effective screening searches to be carried out. However, the results obtained are not obviously superior to those obtained using a much simpler approach that is based on the use of the Tanimoto coefficient and of the square roots of fragment occurrence frequencies.
  3. Al-Madhagi WM, Hashim NM, Awadh Ali NA, Taha H, Alhadi AA, Abdullah AA, et al.
    J Chem Inf Model, 2019 05 28;59(5):1858-1872.
    PMID: 31117526 DOI: 10.1021/acs.jcim.8b00969
    Bioassay-guided isolation protocol was performed on petroleum ether extract of Peperomia blanda (Jacq.) Kunth using column chromatographic techniques. Five compounds were isolated and their structures were elucidated via one-dimensional (1D) and two-dimensional (2D) NMR, gas chromatography mass sectroscopy (GCMS), liquid chromatography mass spectroscopy (LCMS), and ultraviolet (UV) and infrared (IR) analyses. Dindygulerione E (a new compound), and two compounds isolated from P. blanda for the first time-namely, dindygulerione A and flavokawain A-are reported herein. Antimicrobial activity was screened against selected pathogenic microbes, and minimum inhibitory concentrations (MIC) were recorded within the range of 62-250 μg/mL. Assessment of the pharmacotherapeutic potential has also been done for the isolated compounds, using the Prediction of Activity spectra for Substances (PASS) software, and different activities of compounds were predicted. Molecular docking, molecular dynamics simulation and molecular mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) calculations have proposed the binding affinity of these compounds toward methylthioadenosine phosphorylase enzyme, which may explain their inhibitory actions.
  4. Aljabal G, Teh AH, Yap BK
    J Chem Inf Model, 2023 Sep 11;63(17):5619-5630.
    PMID: 37606921 DOI: 10.1021/acs.jcim.3c00791
    14-3-3σ plays an important role in controlling tumor metabolic reprogramming and cancer cell growth. However, its function is often compromised in many cancers due to its downregulation. Previous studies found that homodimerization of 14-3-3σ is critical for its activity. However, to date, it is not known if stabilization of 14-3-3σ homodimers can improve its activity or prevent its degradation. In our previous work, we have showed that GCP-Lys-OMe is a potential 14-3-3σ homodimer stabilizer. However, its stabilizing effect was not experimentally validated. Therefore, in this study, we have attempted to predict few potential peptides that can stabilize the dimeric form of 14-3-3σ using similar in silico techniques as described previously for GCP-Lys-OMe. Subsequent [1H]-CPMG NMR experiments confirmed the binding of the peptides (peptides 3, 5, 9, and 16) on 14-3-3σ, with peptide 3 showing the strongest binding. Competitive [1H]-CPMG assays further revealed that while peptide 3 does not compete with a 14-3-3σ binding peptide (ExoS) for the protein's amphipathic groove, it was found to improve ExoS binding on 14-3-3σ. When 14-3-3σ was subjected to dynamic light scattering experiments, the 14-3-3σ homodimer was found to undergo dissociation into monomers prior to aggregation. Intriguingly, the presence of peptide 3 increased 14-3-3σ stability against aggregation. Overall, our findings suggest that (1) docking accompanied by MD simulations can be used to identify potential homodimer stabilizing compounds of 14-3-3σ and (2) peptide 3 can slow down 14-3-3σ aggregation (presumably by preventing its dissociation into monomers), as well as improving the binding of 14-3-3σ to ExoS protein.
  5. Arif SM, Holliday JD, Willett P
    J Chem Inf Model, 2010 Aug 23;50(8):1340-9.
    PMID: 20672867 DOI: 10.1021/ci1001235
    This paper discusses the weighting of two-dimensional fingerprints for similarity-based virtual screening, specifically the use of weights that assign greatest importance to the substructural fragments that occur least frequently in the database that is being screened. Virtual screening experiments using the MDL Drug Data Report and World of Molecular Bioactivity databases show that the use of such inverse frequency weighting schemes can result, in some circumstances, in marked increases in screening effectiveness when compared with the use of conventional, unweighted fingerprints. Analysis of the characteristics of the various schemes demonstrates that such weights are best used to weight the fingerprint of the reference structure in a similarity search, with the database structures' fingerprints unweighted. However, the increases in performance resulting from such weights are only observed with structurally homogeneous sets of active molecules; when the actives are diverse, the best results are obtained using conventional, unweighted fingerprints for both the reference structure and the database structures.
  6. Chee Wezen X, Chandran A, Eapen RS, Waters E, Bricio-Moreno L, Tosi T, et al.
    J Chem Inf Model, 2022 May 23;62(10):2586-2599.
    PMID: 35533315 DOI: 10.1021/acs.jcim.2c00300
    Lipoteichoic acid synthase (LtaS) is a key enzyme for the cell wall biosynthesis of Gram-positive bacteria. Gram-positive bacteria that lack lipoteichoic acid (LTA) exhibit impaired cell division and growth defects. Thus, LtaS appears to be an attractive antimicrobial target. The pharmacology around LtaS remains largely unexplored with only two small-molecule LtaS inhibitors reported, namely "compound 1771" and the Congo red dye. Structure-based drug discovery efforts against LtaS remain unattempted due to the lack of an inhibitor-bound structure of LtaS. To address this, we combined the use of a molecular docking technique with molecular dynamics (MD) simulations to model a plausible binding mode of compound 1771 to the extracellular catalytic domain of LtaS (eLtaS). The model was validated using alanine mutagenesis studies combined with isothermal titration calorimetry. Additionally, lead optimization driven by our computational model resulted in an improved version of compound 1771, namely, compound 4 which showed greater affinity for binding to eLtaS than compound 1771 in biophysical assays. Compound 4 reduced LTA production in S. aureus dose-dependently, induced aberrant morphology as seen for LTA-deficient bacteria, and significantly reduced bacteria titers in the lung of mice infected with S. aureus. Analysis of our MD simulation trajectories revealed the possible formation of a transient cryptic pocket in eLtaS. Virtual screening (VS) against the cryptic pocket led to the identification of a new class of inhibitors that could potentiate β-lactams against methicillin-resistant S. aureus. Our overall workflow and data should encourage further drug design campaign against LtaS. Finally, our work reinforces the importance of considering protein conformational flexibility to a successful VS endeavor.
  7. Chen J, Cheong HH, Siu SWI
    J Chem Inf Model, 2021 Aug 23;61(8):3789-3803.
    PMID: 34327990 DOI: 10.1021/acs.jcim.1c00181
    Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radiotherapy and chemotherapy, but both methods bring severe side effects to patients, as these therapies not only attack cancer cells but also damage normal cells. Anticancer peptides (ACPs) are a promising alternative as therapeutic agents that are efficient and selective against tumor cells. Here, we propose a deep learning method based on convolutional neural networks to predict biological activity (EC50, LC50, IC50, and LD50) against six tumor cells, including breast, colon, cervix, lung, skin, and prostate. We show that models derived with multitask learning achieve better performance than conventional single-task models. In repeated 5-fold cross validation using the CancerPPD data set, the best models with the applicability domain defined obtain an average mean squared error of 0.1758, Pearson's correlation coefficient of 0.8086, and Kendall's correlation coefficient of 0.6156. As a step toward model interpretability, we infer the contribution of each residue in the sequence to the predicted activity by means of feature importance weights derived from the convolutional layers of the model. The present method, referred to as xDeep-AcPEP, will help to identify effective ACPs in rational peptide design for therapeutic purposes. The data, script files for reproducing the experiments, and the final prediction models can be downloaded from http://github.com/chen709847237/xDeep-AcPEP. The web server to directly access this prediction method is at https://app.cbbio.online/acpep/home.
  8. Cheng Z, Hwang SS, Bhave M, Rahman T, Chee Wezen X
    J Chem Inf Model, 2023 Nov 13;63(21):6912-6924.
    PMID: 37883148 DOI: 10.1021/acs.jcim.3c01252
    Polo-like kinase 1 (PLK1) and p38γ mitogen-activated protein kinase (p38γ) play important roles in cancer pathogenesis by controlling cell cycle progression and are therefore attractive cancer targets. The design of multitarget inhibitors may offer synergistic inhibition of distinct targets and reduce the risk of drug-drug interactions to improve the balance between therapeutic efficacy and safety. We combined deep-learning-based quantitative structure-activity relationship (QSAR) modeling and hybrid-based consensus scoring to screen for inhibitors with potential activity against the targeted proteins. Using this combination strategy, we identified a potent PLK1 inhibitor (compound 4) that inhibited PLK1 activity and liver cancer cell growth in the nanomolar range. Next, we deployed both our QSAR models for PLK1 and p38γ on the Enamine compound library to identify dual-targeting inhibitors against PLK1 and p38γ. Likewise, the identified hits were subsequently subjected to hybrid-based consensus scoring. Using this method, we identified a promising compound (compound 14) that could inhibit both PLK1 and p38γ activities. At nanomolar concentrations, compound 14 inhibited the growth of human hepatocellular carcinoma and hepatoblastoma cells in vitro. This study demonstrates the combined screening strategy to identify novel potential inhibitors for existing targets.
  9. Cournia Z, Soares TA, Wahab HA, Amaro RE
    J Chem Inf Model, 2021 11 22;61(11):5305-5306.
    PMID: 34668709 DOI: 10.1021/acs.jcim.1c01185
  10. Hariono M, Nuwarda RF, Yusuf M, Rollando R, Jenie RI, Al-Najjar B, et al.
    J Chem Inf Model, 2020 01 27;60(1):349-359.
    PMID: 31825614 DOI: 10.1021/acs.jcim.9b00630
    Previous studies have reported that compounds bearing an arylamide linked to a heterocyclic planar ring have successfully inhibited the hemopexin-like domain (PEX9) of matrix metalloproteinase 9 (MMP9). PEX9 has been suggested to be more selectively targeted than MMP9's catalytic domain in a degrading extracellular matrix under some pathologic conditions, especially in cancer. In this study, we aim to synthesize and evaluate 10 arylamide compounds as MMP9 inhibitors through an enzymatic assay as well as a cellular assay. The mechanism of inhibition for the most active compounds was investigated via molecular dynamics simulation (MD). Molecular docking was performed using AutoDock4.0 with PEX9 as the protein model to predict the binding of the designed compounds. The synthesis was carried out by reacting aniline derivatives with 3-bromopropanoyl chloride using pyridine as the catalyst at room temperature. The MMP9 assay was conducted using the FRET-based MMP9 kits protocol and gelatin zymography assay. The cytotoxicity assay was done using the MTT method, and the MD simulation was performed using AMBER16. Assay on MMP9 demonstrated activities of three compounds (2, 7, and 9) with more than 50% inhibition. Further inhibition on MMP9 expressed by 4T1 showed that two compounds (7 and 9) inhibited its gelatinolytic activity more than 50%. The cytotoxicity assay against 4T1 cells results in the inhibition of the cell growth with an EC50 of 125 μM and 132 μM for 7 and 9, respectively. The MD simulation explained a stable interaction of 7 and 9 in PEX9 at 100 ns with a free energy of binding of -8.03 kcal/mol and -6.41 kcal/mol, respectively. Arylamides have potential effects as selective MMP9 inhibitors in inhibiting breast cancer cell progression.
  11. Ikram NK, Durrant JD, Muchtaridi M, Zalaludin AS, Purwitasari N, Mohamed N, et al.
    J Chem Inf Model, 2015 Feb 23;55(2):308-16.
    PMID: 25555059 DOI: 10.1021/ci500405g
    Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the 12 isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources.
  12. Lee YV, Choi SB, Wahab HA, Lim TS, Choong YS
    J Chem Inf Model, 2019 05 28;59(5):2487-2495.
    PMID: 30840452 DOI: 10.1021/acs.jcim.8b00963
    Isocitrate lyase (ICL) is a persistent factor for the survival of dormant stage Mycobacterium tuberculosis (MTB), thus a potential drug target for tuberculosis treatment. In this work, ensemble docking approach was used to screen for potential inhibitors of ICL. The ensemble conformations of ICL active site were obtained from molecular dynamics simulation on three dimer form systems, namely the apo ICL, ICL in complex with metabolites (glyoxylate and succinate), and ICL in complex with substrate (isocitrate). Together with the ensemble conformations and the X-ray crystal structures, 22 structures were used for the screening against Malaysian Natural Compound Database (NADI). The top 10 compounds for each ensemble conformation were selected. The number of compounds was then further narrowed down to 22 compounds that were within the Lipinski's Rule of Five for drug-likeliness and were also docked into more than one ensemble conformation. Theses 22 compounds were furthered evaluate using whole cell assay. Some compounds were not commercially available; therefore, plant crude extracts were used for the whole cell assay. Compared to itaconate (the known inhibitor of ICL), crude extracts from Manilkara zapota, Morinda citrifolia, Vitex negundo, and Momordica charantia showed some inhibition activity. The MIC/MBC value were 12.5/25, 12.5/25, 0.78/1.6, and 0.39/1.6 mg/mL, respectively. This work could serve as a preliminary study in order to narrow the scope for high throughput screening in the future.
  13. Lee YV, Choi SB, Wahab HA, Choong YS
    J Chem Inf Model, 2017 09 25;57(9):2351-2357.
    PMID: 28820943 DOI: 10.1021/acs.jcim.7b00265
    Tuberculosis (TB) still remains a global threat due to the emergence of a drug-resistant strain. Instead of focusing on the drug target of active stage TB, we are highlighting the isocitrate lyase (ICL) at the dormant stage TB. ICL is one of the persistent factors for Mycobacterium tuberculosis (MTB) to survive during the dormant phase. In addition, the absence of ICL in human has made ICL a potential drug target for TB therapy. However, the dynamic details of ICL which could give insights to the ICL-ligand interaction have yet to be solved. Therefore, a series of ICL dimer dynamics studies through molecular dynamics simulation were performed in this work. The ICL active site entrance gate closure is contributed to by hydrogen bonding and electrostatic interactions with the C-terminal. Analysis suggested that the open-closed behavior of the ICL active site entrance depends on the type of ligand present in the active site. We also observed four residues (Ser91, Asp108, Asp153, and Cys191) which could possibly be the nucleophiles for nucleophilic attack on the cleavage of isocitrate at the C2-C3bond. We hope that the elucidation of ICL dynamics can benefit future works such as lead identification or antibody design against ICL for TB therapeutics.
  14. Mazzolari A, Nunes-Alves A, Wahab HA, Amaro RE, Cournia Z, Merz KM
    J Chem Inf Model, 2020 07 27;60(7):3328-3330.
    PMID: 32623887 DOI: 10.1021/acs.jcim.0c00636
    In this Viewpoint, we provide a commentary on the impact of the Journal of Chemical Information and Modeling Special Issue on Women in Computational Chemistry published in May 2019 and the feedback we received.
  15. Ng HW, Laughton CA, Doughty SW
    J Chem Inf Model, 2014 Feb 24;54(2):573-81.
    PMID: 24460123 DOI: 10.1021/ci400463z
    Analysis of 300 ns (ns) molecular dynamics (MD) simulations of an adenosine A2a receptor (A2a AR) model, conducted in triplicate, in 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) and 1-palmitoyl-2-oleoylphosphatidylethanolamine (POPE) bilayers reveals significantly different protein dynamical behavior. Principal component analysis (PCA) shows that the dissimilarities stem from interhelical rather than intrahelical motions. The difference in the hydrophobic thicknesses of these simulated lipid bilayers is potentially a significant reason for the observed difference in results. The distinct lipid headgroups might also lead to different molecular interactions and hence different protein loop motions. Overall, the A2a AR shows higher mobility and flexibility in POPC as compared to POPE.
  16. Ng HW, Laughton CA, Doughty SW
    J Chem Inf Model, 2013 May 24;53(5):1168-78.
    PMID: 23514445 DOI: 10.1021/ci300610w
    Molecular dynamics (MD) simulations of membrane-embedded G-protein coupled receptors (GPCRs) have rapidly gained popularity among the molecular simulation community in recent years, a trend which has an obvious link to the tremendous pharmaceutical importance of this group of receptors and the increasing availability of crystal structures. In view of the widespread use of this technique, it is of fundamental importance to ensure the reliability and robustness of the methodologies so they yield valid results and enable sufficiently accurate predictions to be made. In this work, 200 ns simulations of the A2a adenosine receptor (A2a AR) have been produced and evaluated in the light of these requirements. The conformational dynamics of the target protein, as obtained from replicate simulations in both the presence and absence of an inverse agonist ligand (ZM241385), have been investigated and compared using principal component analysis (PCA). Results show that, on this time scale, convergence of the replicates is not readily evident and dependent on the types of the protein motions considered. Thus rates of inter- as opposed to intrahelical relaxation and sampling can be different. When studied individually, we find that helices III and IV have noticeably greater stability than helices I, II, V, VI, and VII in the apo form. The addition of the inverse agonist ligand greatly improves the stability of all helices.
  17. Ng WC, Lim TL, Yoon TL
    J Chem Inf Model, 2017 03 27;57(3):517-528.
    PMID: 28178783 DOI: 10.1021/acs.jcim.6b00553
    Melting dynamics of hafnium clusters are investigated using a novel approach based on the idea of the chemical similarity index. Ground state configurations of small hafnium clusters are first derived using Basin-Hopping and Genetic Algorithm in the parallel tempering mode, employing the COMB potential in the energy calculator. These assumed ground state structures are verified by using the Low Lying Structures (LLS) method. The melting process is carried out either by using the direct heating method or prolonged simulated annealing. The melting point is identified by a caloric curve. However, it is found that the global similarity index is much more superior in locating premelting and total melting points of hafnium clusters.
  18. Othman R, Kiat TS, Khalid N, Yusof R, Newhouse EI, Newhouse JS, et al.
    J Chem Inf Model, 2008 Aug;48(8):1582-91.
    PMID: 18656912 DOI: 10.1021/ci700388k
    A group of flavanones and their chalcones, isolated from Boesenbergia rotunda L., were previously reported to show varying degrees of noncompetitive inhibitory activities toward Dengue virus type 2 (Den2) protease. Results obtained from automated docking studies are in agreement with experimental data in which the ligands were shown to bind to sites other than the active site of the protease. The calculated K(i) values are very small, indicating that the ligands bind quite well to the allosteric binding site. Greater inhibition by pinostrobin, compared to the other compounds, can be explained by H-bonding interaction with the backbone carbonyl of Lys74, which is bonded to Asp75 (one of the catalytic triad residues). In addition, structure-activity relationship analysis yields structural information that may be useful for designing more effective therapeutic drugs against dengue virus infections.
  19. Saeed F, Salim N, Abdo A
    J Chem Inf Model, 2013 May 24;53(5):1026-34.
    PMID: 23581471 DOI: 10.1021/ci300442u
    The goal of consensus clustering methods is to find a consensus partition that optimally summarizes an ensemble and improves the quality of clustering compared with single clustering algorithms. In this paper, an enhanced voting-based consensus method was introduced and compared with other consensus clustering methods, including co-association-based, graph-based, and voting-based consensus methods. The MDDR and MUV data sets were used for the experiments and were represented by three 2D fingerprints: ALOGP, ECFP_4, and ECFC_4. The results were evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster using four criteria: F-measure, Quality Partition Index (QPI), Rand Index (RI), and Fowlkes-Mallows Index (FMI). The experiments suggest that the consensus methods can deliver significant improvements for the effectiveness of chemical structures clustering.
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