Displaying publications 21 - 40 of 146 in total

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  1. Comparative analysis of an anthraquinone and chalcone derivatives-based virtual combinatorial library. A cheminformatics "proof-of-concept" study
    Moshawih S, Hadikhani P, Fatima A, Goh HP, Kifli N, Kotra V, et al.
    J Mol Graph Model, 2022 Dec;117:108307.
    PMID: 36096064 DOI: 10.1016/j.jmgm.2022.108307
    A Laplacian scoring algorithm for gene selection and the Gini coefficient to identify the genes whose expression varied least across a large set of samples were the state-of-the-art methods used here. These methods have not been trialed for their feasibility in cheminformatics. This was a maiden attempt to investigate a complete comparative analysis of an anthraquinone and chalcone derivatives-based virtual combinatorial library. This computational "proof-of-concept" study illustrated the combinatorial approach used to explain how the structure of the selected natural products (NPs) undergoes molecular diversity analysis. A virtual combinatorial library (1.6 M) based on 20 anthraquinones and 24 chalcones was enumerated. The resulting compounds were optimized to the near drug-likeness properties, and the physicochemical descriptors were calculated for all datasets including FDA, Non-FDA, and NPs from ZINC 15. UMAP and PCA were applied to compare and represent the chemical space coverage of each dataset. Subsequently, the Laplacian score and Gini coefficient were applied to delineate feature selection and selectivity among properties, respectively. Finally, we demonstrated the diversity between the datasets by employing Murcko's and the central scaffolds systems, calculating three fingerprint descriptors and analyzing their diversity by PCA and SOM. The optimized enumeration resulted in 1,610,268 compounds with NP-Likeness, and synthetic feasibility mean scores close to FDA, Non-FDA, and NPs datasets. The overlap between the chemical space of the 1.6 M database was more prominent than with the NPs dataset. A Laplacian score prioritized NP-likeness and hydrogen bond acceptor properties (1.0 and 0.923), respectively, while the Gini coefficient showed that all properties have selective effects on datasets (0.81-0.93). Scaffold and fingerprint diversity indicated that the descending order for the tested datasets was FDA, Non-FDA, NPs and 1.6 M. Virtual combinatorial libraries based on NPs can be considered as a source of the combinatorial compound with NP-likeness properties. Furthermore, measuring molecular diversity is supposed to be performed by different methods to allow for comparison and better judgment.
    Matched MeSH terms: Drug Design
  2. Fulltext In Silico Drug Design of Anti-Breast Cancer Agents
    Rajagopal K, Kalusalingam A, Bharathidasan AR, Sivaprakash A, Shanmugam K, Sundaramoorthy M, et al.
    Molecules, 2023 May 18;28(10).
    PMID: 37241915 DOI: 10.3390/molecules28104175
    Cancer is a condition marked by abnormal cell proliferation that has the potential to invade or indicate other health issues. Human beings are affected by more than 100 different types of cancer. Some cancer promotes rapid cell proliferation, whereas others cause cells to divide and develop more slowly. Some cancers, such as leukemia, produce visible tumors, while others, such as breast cancer, do not. In this work, in silico investigations were carried out to investigate the binding mechanisms of four major analogs, which are marine sesquiterpene, sesquiterpene lactone, heteroaromatic chalcones, and benzothiophene against the target estrogen receptor-α for targeting breast cancer using Schrödinger suite 2021-4. The Glide module handled the molecular docking experiments, the QikProp module handled the ADMET screening, and the Prime MM-GB/SA module determined the binding energy of the ligands. The benzothiophene analog BT_ER_15f (G-score -15.922 Kcal/mol) showed the best binding activity against the target protein estrogen receptor-α when compared with the standard drug tamoxifen which has a docking score of -13.560 Kcal/mol. TRP383 (tryptophan) has the highest interaction time with the ligand, and hence it could act for a long time. Based on in silico investigations, the benzothiophene analog BT_ER_15f significantly binds with the active site of the target protein estrogen receptor-α. Similar to the outcomes of molecular docking, the target and ligand complex interaction motif established a high affinity of lead candidates in a dynamic system. This study shows that estrogen receptor-α targets inhibitors with better potential and low toxicity when compared to the existing market drugs, which can be made from a benzothiophene derivative. It may result in considerable activity and be applied to more research on breast cancer.
    Matched MeSH terms: Drug Design
  3. Fulltext Promising Natural Products in New Drug Design, Development, and Therapy for Skin Disorders: An Overview of Scientific Evidence and Understanding Their Mechanism of Action
    Mohd Zaid NA, Sekar M, Bonam SR, Gan SH, Lum PT, Begum MY, et al.
    Drug Des Devel Ther, 2022;16:23-66.
    PMID: 35027818 DOI: 10.2147/DDDT.S326332
    The skin is the largest organ in the human body, composed of the epidermis and the dermis. It provides protection and acts as a barrier against external menaces like allergens, chemicals, systemic toxicity, and infectious organisms. Skin disorders like cancer, dermatitis, psoriasis, wounds, skin aging, acne, and skin infection occur frequently and can impact human life. According to a growing body of evidence, several studies have reported that natural products have the potential for treating skin disorders. Building on this information, this review provides brief information about the action of the most important in vitro and in vivo research on the use of ten selected natural products in inflammatory, neoplastic, and infectious skin disorders and their mechanisms that have been reported to date. The related studies and articles were searched from several databases, including PubMed, Google, Google Scholar, and ScienceDirect. Ten natural products that have been reported widely on skin disorders were reviewed in this study, with most showing anti-inflammatory, antioxidant, anti-microbial, and anti-cancer effects as the main therapeutic actions. Overall, most of the natural products reported in this review can reduce and suppress inflammatory markers, like tumor necrosis factor-alpha (TNF-α), scavenge reactive oxygen species (ROS), induce cancer cell death through apoptosis, and prevent bacteria, fungal, and virus infections indicating their potentials. This review also highlighted the challenges and opportunities of natural products in transdermal/topical delivery systems and their safety considerations for skin disorders. Our findings indicated that natural products might be a low-cost, well-tolerated, and safe treatment for skin diseases. However, a larger number of clinical trials are required to validate these findings. Natural products in combination with modern drugs, as well as the development of novel delivery mechanisms, represent a very promising area for future drug discovery of these natural leads against skin disorders.
    Matched MeSH terms: Drug Design
  4. Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors
    Shiammala PN, Duraimutharasan NKB, Vaseeharan B, Alothaim AS, Al-Malki ES, Snekaa B, et al.
    Methods, 2023 Nov;219:82-94.
    PMID: 37778659 DOI: 10.1016/j.ymeth.2023.09.010
    Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but it has the potential to revolutionize the way new drugs are discovered and developed. As AI technology continues to evolve, it is likely that AI will play an even greater role in the future of drug discovery. AI is used to identify new drug targets, design new molecules, and predict the efficacy and safety of potential drugs. The inclusion of AI in drug discovery can screen millions of compounds in a matter of hours, identifying potential drug candidates that would have taken years to find using traditional methods. AI is highly utilized in the pharmaceutical industry by optimizing processes, reducing waste, and ensuring quality control. This review covers much-needed topics, including the different types of machine-learning techniques, their applications in drug discovery, and the challenges and limitations of using machine learning in this field. The state-of-the-art of AI-assisted pharmaceutical discovery is described, covering applications in structure and ligand-based virtual screening, de novo drug creation, prediction of physicochemical and pharmacokinetic properties, drug repurposing, and related topics. Finally, many obstacles and limits of present approaches are outlined, with an eye on potential future avenues for AI-assisted drug discovery and design.
    Matched MeSH terms: Drug Design
  5. Worldwide trend discovery of structural and functional relationship of metallo-β-lactamase for structure-based drug design: A bibliometric evaluation and patent analysis
    Azman AA, Leow ATC, Noor NDM, Noor SAM, Latip W, Ali MSM
    Int J Biol Macromol, 2024 Jan;256(Pt 2):128230.
    PMID: 38013072 DOI: 10.1016/j.ijbiomac.2023.128230
    Metallo-β-lactamase (MBL) is an enzyme produced by clinically important bacteria that can inactivate many commonly used antibiotics, making them a significant concern in treating bacterial infections and the risk of having high antibiotic resistance issues among the community. This review presents a bibliometric and patent analysis of MBL worldwide research trend based on the Scopus and World Intellectual Property Organization databases in 2013-2022. Based on the keywords related to MBL in the article title, abstract, and keywords, 592 research articles were retrieved for further analysis using various tools such as Microsoft Excel to determine the frequency analysis, VOSviewer for bibliometric networks visualization, and Harzing's Publish or Perish for citation metrics analysis. Standard bibliometric parameters were analysed to evaluate the field's research trend, such as the growth of publications, topographical distribution, top subject area, most relevant journal, top cited documents, most relevant authors, and keyword trend analysis. Within 10 years, MBL discovery has shown a steady and continuous growth of interest among the community of researchers. United States of America, China, and the United Kingdom are the top 3 countries contribute high productivity to the field. The patent analysis also shows several impactful filed patents, indicating the significance of development research on the structural and functional relationship of MBL for an effective structure-based drug design (SBDD). Developing new MBL inhibitors using SBDD could help address the research gap and provide new successful therapeutic options for treating MBL-producing bacterial infections.
    Matched MeSH terms: Drug Design
  6. PASS-assisted design, synthesis and antioxidant evaluation of new butylated hydroxytoluene derivatives
    Ariffin A, Rahman NA, Yehye WA, Alhadi AA, Kadir FA
    Eur J Med Chem, 2014 Nov 24;87:564-77.
    PMID: 25299680 DOI: 10.1016/j.ejmech.2014.10.001
    New multipotent antioxidants (MPAOs), namely 1,3,4-thiadiazoles and 1,2,4-triazoles bearing the well-known free radical scavenger butylated hydroxytoluene (BHT), were designed and synthesized using an acid-(base-) catalyzed intramolecular dehydrative cyclization reaction of the corresponding 1-acylthiosemicarbazides. The structure-activity relationship (SAR) of the designed antioxidants was performed along with the prediction of activity spectra for substances (PASS) training set. Experimental studies based on antioxidant activity using DPPH and lipid peroxidation assays verified the predictions obtained by the PASS-assisted design strategy. Compounds 4a-b, 5a-b and 6a-b showed an inhibition of stable DPPH free radicals at a 10(-4) M more than the well-known standard antioxidant BHT. Compounds with p-methoxy substituents (4b, 5b and 6b) were more active than o-methoxy substituents (4a, 5a and 6a). With an IC50 of 2.85 ± 1.09 μM, compound 6b exhibited the most promising in vitro inhibition of lipid peroxidation, inhibiting Fe(2+)-induced lipid peroxidation of essential oils derived from the egg yolk-based lipid-rich medium by 86.4%. The parameters for the drug-likeness of these BHT derivatives were also evaluated according to Lipinski's 'rule-of-five'. All of the BHT derivatives were found to violate one of Lipinski's parameters (Log P ≥ 5) even though they have been found to be soluble in protic solvents. The predictive TPSA and %ABS data allow for the conclusion that these compounds could have a good capacity for penetrating cell membranes. Therefore, these novel MPAOs containing lipophilic and hydrophilic groups can be proposed as potential antioxidants for tackling oxidative stress and lipid peroxidation processes.
    Matched MeSH terms: Drug Design*
  7. Fulltext Design, synthesis and cytotoxic evaluation of o-carboxamido stilbene analogues
    Azmi MN, Din MF, Kee CH, Suhaimi M, Ping AK, Ahmad K, et al.
    Int J Mol Sci, 2013;14(12):23369-89.
    PMID: 24287912 DOI: 10.3390/ijms141223369
    Resveratrol, a natural stilbene found in grapes and wines exhibits a wide range of pharmacological properties. Resveratrol is also known as a good chemopreventive agent for inhibiting carcinogenesis processes that target kinases, cyclooxygenases, ribonucleotide reductase and DNA polymerases. A total of 19 analogues with an amide moiety were synthesized and the cytotoxic effects of the analogues on a series of human cancer cell lines are reported. Three compounds 6d, 6i and 6n showed potent cytotoxicity against prostate cancer DU-145 (IC50=16.68 µM), colon cancer HT-29 (IC50=7.51 µM) and breast cancer MCF-7 (IC50=21.24 µM), respectively, which are comparable with vinblastine. The resveratrol analogues were synthesized using the Heck method.
    Matched MeSH terms: Drug Design*
  8. Site-directed fragment-based generation of virtual sialic acid databases against influenza A hemagglutinin
    Al-qattan MN, Mordi MN
    J Mol Model, 2010 May;16(5):975-91.
    PMID: 19856192 DOI: 10.1007/s00894-009-0606-y
    In this study fragment-based drug design is combined with molecular docking simulation technique, to design databases of virtual sialic acid (SA) analogues with new substitutions at C2, C5 and C6 positions of SA scaffold. Using spaces occupied by C2, C5 and C6 natural moieties of SA when bound to hemagglutinin (HA) crystallographic structure, new fragments that are commercially available were docked independently in all the pockets. The oriented fragments were then connected to the SA scaffold with or without incorporation of linker molecules. The completed analogues were docked to the whole SA binding site to estimate their binding conformations and affinities, generating three databases of HA-bound SA analogues. Selected new analogues showed higher estimated affinities than the natural SA when tested against H3N2, H5N1 and H1N1 subtypes of influenza A. An improvement in the binding energies indicates that fragment-based drug design when combined with molecular docking simulation is capable to produce virtual analogues that can become lead compound candidates for anti-flu drug discovery program.
    Matched MeSH terms: Drug Design*
  9. Drug-like and non drug-like pattern classification based on simple topology descriptor using hybrid neural network
    Wan-Mamat WM, Isa NA, Wahab HA, Wan-Mamat WM
    Annu Int Conf IEEE Eng Med Biol Soc, 2009;2009:6424-7.
    PMID: 19964424 DOI: 10.1109/IEMBS.2009.5333747
    An intelligent prediction system has been developed to discriminate drug-like and non drug-like molecules pattern. The system is constructed by using the application of advanced version of standard multilayer perceptron (MLP) neural network called Hybrid Multilayer Perceptron (HMLP) neural network and trained using Modified Recursive Prediction Error (MRPE) training algorithm. In this work, a well understood and easy excess Rule of Five + Veber filter properties are selected as the topological descriptor. The main idea behind the selection of this simple descriptor is to assure that the system could be used widely, beneficial and more advantageous regardless at all user level within a drug discovery organization.
    Matched MeSH terms: Drug Design*
  10. Design, synthesis and biological evaluation of novel carbamates as potential inhibitors of acetylcholinesterase and butyrylcholinesterase
    Wu J, Pistolozzi M, Liu S, Tan W
    Bioorg Med Chem, 2020 03 01;28(5):115324.
    PMID: 32008882 DOI: 10.1016/j.bmc.2020.115324
    Rivastigmine, a dual inhibitor of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), has been approved by U.S. Food and Drug Administration to treat Alzheimer's disease (AD) and Parkinson's disease (PD) dementia. In the current work, a bambuterol derivative lacking one of the carbamoyloxy groups on the benzene ring (BMC-1) and its analogues were synthesized using 1-(3-hydroxyphenyl) ethan-1-one and 1-(4-hydroxyphenyl) ethan-1-one as starting materials. In-vitro cholinesterase assay established that nine compounds were more potent to inhibit both electric eel AChE and equine serum BChE than rivastigmine under the same experimental conditions. Further study confirmed that among the nine carbamates, BMC-3 (IC50(AChE) = 792 nM, IC50(BChE) = 2.2 nM) and BMC-16 (IC50(AChE) = 266 nM, IC50(BChE) = 10.6 nM) were excellent cholinesterase inhibitors with potential of permeating through the blood-brain barrier. These carbamates could be used as potential dual inhibitors of AChE and BChE and to discover novel drugs for the treatment of AD and PD dementia.
    Matched MeSH terms: Drug Design*
  11. Design, synthesis, in vitro cytotoxicity evaluation and structure-activity relationship of goniothalamin analogs
    Mohideen M, Zulkepli S, Nik-Salleh NS, Zulkefeli M, Weber JF, Weber JF, et al.
    Arch Pharm Res, 2013 Jul;36(7):812-31.
    PMID: 23543632 DOI: 10.1007/s12272-013-0099-1
    A series of six/five member (E/Z)-Goniothalamin analogs were synthesized from commercially available (3,4-dihydro-2H-pyran-2-yl)methanol/5-(hydroxymethyl)dihydrofuran-2(3H)-one in three steps with good to moderate overall yields and their cytotoxicity against lymphoblastic leukemic T cell line (Jurkat E6.1) have been evaluated. Among the synthesized analogs, (Z)-Goniothalamin appeared to be the most active in cytotoxicity (IC50 = 12 μM). Structure-activity relationship study indicates that introducing substituent in phenyl ring or replacing phenyl ring by pyridine/naphthalene, or decreasing the ring size of lactones (from six to five member) do not increase the cytotoxicity.
    Matched MeSH terms: Drug Design*
  12. Computer-Aided Antibody Design: An Overview
    Choong YS, Lee YV, Soong JX, Law CT, Lim YY
    Adv Exp Med Biol, 2017;1053:221-243.
    PMID: 29549642 DOI: 10.1007/978-3-319-72077-7_11
    The use of monoclonal antibody as the next generation protein therapeutics with remarkable success has surged the development of antibody engineering to design molecules for optimizing affinity, better efficacy, greater safety and therapeutic function. Therefore, computational methods have become increasingly important to generate hypotheses, interpret and guide experimental works. In this chapter, we discussed the overall antibody design by computational approches.
    Matched MeSH terms: Drug Design*
  13. Anti- COVID-19 drug discovery by flavonoid derivatives: an extensive computational drug design approach
    Banerjee S, Mukherjee S, Mohsin Kazi, Sen KK, Das A, Hasan R, et al.
    Cell Mol Biol (Noisy-le-grand), 2024 Sep 08;70(8):39-49.
    PMID: 39262264 DOI: 10.14715/cmb/2024.70.8.5
    The present study deals with the in-silico analyses of several flavonoid derivatives to explore COVID-19 through pharmacophore modelling, molecular docking, molecular dynamics, drug-likeness, and ADME properties. The initial literature study revealed that many flavonoids, including luteolin, quercetin, kaempferol, and baicalin may be useful against SARS β-coronaviruses, prompting the selection of their potential derivatives to investigate their abilities as inhibitors of COVID-19. The findings were streamlined using in silico molecular docking, which revealed promising energy-binding interactions between all flavonoid derivatives and the targeted protein. Notably, compounds 8, 9, 13, and 15 demonstrated higher potency against the coronavirus Mpro protein (PDB ID 6M2N). Compound 8 has a -7.2 Kcal/mol affinity for the protein and binds to it by hydrogen bonding with Gln192 and π-sulfur bonding with Met-165. Compound 9 exhibited a significant interaction with the main protease, demonstrating an affinity of -7.9 kcal/mol. Gln-192, Glu-189, Pro-168, and His-41 were the principle amino acid residues involved in this interaction. The docking score for compound 13 is -7.5 Kcal/mol, and it binds to the protease enzyme by making interactions with Leu-41, π-sigma, and Gln-189. These interactions include hydrogen bonding and π-sulfur. The major protease and compound 15 were found to bind with a favourable affinity of -6.8 Kcal/mol. This finding was further validated through molecular dynamic simulation for 1ns, analysing parameters such as RMSD, RMSF, and RoG profiles. The RoG values for all four of the compounds varied significantly (35.2-36.4). The results demonstrated the stability of the selected compounds during the simulation. After passing the stability testing, the compounds underwent screening for ADME and drug-likeness properties, fulfilling all the necessary criteria. The findings of the study may support further efforts for the discovery and development of safe drugs to treat COVID-19.
    Matched MeSH terms: Drug Design*
  14. Alkaloids of Kopsia
    Kam TS, Lim KH
    Alkaloids Chem Biol, 2008;66:1-111.
    PMID: 19025097
    Matched MeSH terms: Drug Design
  15. Fulltext Synthesis and Crystallographic Insight into the Structural Aspects of Some Novel Adamantane-Based Ester Derivatives
    Kumar CS, Kwong HC, Mah SH, Chia TS, Loh WS, Quah CK, et al.
    Molecules, 2015;20(10):18827-46.
    PMID: 26501248 DOI: 10.3390/molecules201018827
    Adamantyl-based compounds are commercially important in the treatments for neurological conditions and type-2 diabetes, aside from their anti-viral abilities. Their values in drug design are chronicled as multi-dimensional. In the present study, a series of 2-(adamantan-1-yl)-2-oxoethyl benzoates, 2(a-q), and 2-(adamantan-1-yl)-2-oxoethyl 2-pyridinecarboxylate, 2r, were synthesized by reacting 1-adamantyl bromomethyl ketone with various carboxylic acids using potassium carbonate in dimethylformamide medium at room temperature. Three-dimensional structures studied using X-ray diffraction suggest that the adamantyl moiety can serve as an efficient building block to synthesize 2-oxopropyl benzoate derivatives with synclinal conformation with a looser-packed crystal packing system. Compounds 2a, 2b, 2f, 2g, 2i, 2j, 2m, 2n, 2o, 2q and 2r exhibit strong antioxidant activities in the hydrogen peroxide radical scavenging test. Furthermore, three compounds, 2p, 2q and 2r, show good anti-inflammatory activities in the evaluation of albumin denaturation.
    Matched MeSH terms: Drug Design
  16. Understanding the chemistry behind the antioxidant activities of butylated hydroxytoluene (BHT): a review
    Yehye WA, Rahman NA, Ariffin A, Abd Hamid SB, Alhadi AA, Kadir FA, et al.
    Eur J Med Chem, 2015 Aug 28;101:295-312.
    PMID: 26150290 DOI: 10.1016/j.ejmech.2015.06.026
    Hindered phenols find a wide variety of applications across many different industry sectors. Butylated hydroxytoluene (BHT) is a most commonly used antioxidant recognized as safe for use in foods containing fats, pharmaceuticals, petroleum products, rubber and oil industries. In the past two decades, there has been growing interest in finding novel antioxidants to meet the requirements of these industries. To accelerate the antioxidant discovery process, researchers have designed and synthesized a series of BHT derivatives targeting to improve its antioxidant properties to be having a wide range of antioxidant activities markedly enhanced radical scavenging ability and other physical properties. Accordingly, some structure-activity relationships and rational design strategies for antioxidants based on BHT structure have been suggested and applied in practice. We have identified 14 very sensitive parameters, which may play a major role on the antioxidant performance of BHT. In this review, we attempt to summarize the current knowledge on this topic, which is of significance in selecting and designing novel antioxidants using a well-known antioxidant BHT as a building-block molecule. Our strategy involved investigation on understanding the chemistry behind the antioxidant activities of BHT, whether through hydrogen or electron transfer mechanism to enable promising anti-oxidant candidates to be synthesized.
    Matched MeSH terms: Drug Design
  17. Fulltext [Corrigendum] Antiproliferative effects of imatinib mesylate on ZR‑75‑1 and MDA‑MB‑231 cell lines via PDGFR‑β, PDGF‑BB, c‑Kit and SCF expression
    Kadivar A, Noordin MI, Aditya A, Kamalidehghan B, Davoudi ET, Sedghi R, et al.
    Int J Mol Med, 2019 05;43(5):2259.
    PMID: 30864679 DOI: 10.3892/ijmm.2019.4119
    An interested reader drew to our attention that the above study appeared to contain a high level of overlap with an article by the same authors published in the journal Drug Design, Development and Therapy [Kadivar A, Kamalidehghan B, Akbari Javar H, Karimi B, Sedghi R and Noordin MI: Antiproliferation effect of imatinib mesylate on MCF7, T‑47D tumorigenic and MCF 10A nontumorigenic breast cell lines via PDGFR‑β, PDGF‑BB, c‑Kit and SCF genes. Drug Des Devel Ther 11: 469‑481, 2017]. Following an internal investigation and also in liaison with the authors, it was established that, although the studies were conducted along broadly similar lines, the papers contained entirely different data involving two different subsets of cell lines; the submission to Drug Des Devel Ther aimed to explore the effects of imatinib mesylate on three different groups, with each group being represented by a cell line, whereas the submission to Int J Mol Med explored the effectiveness of imatinib mesylate in breast cancer cell lines. In spite of this, considering the relatedness of the articles and the fact that the paper to Drug Des Devel Ther was submitted first and published while the Int J Mol Med paper was passing through the peer‑review process, the authors concede that they should have properly referenced their paper submitted to Drug Des Devel Ther in the Int J Mol Med paper. Note that the publishers of Drug Des Devel Ther, with whom we were liaising, agreed with the decision to issue a Corrigendum for this paper that acknowledges the article published in Drug Des Devel Ther. The authors regret their failure to acknowledge the related paper in this instance, and apologize to the readership for this oversight. [the original article was published in International Journal of Molecular Medicine 14: 414‑424, 2018; DOI: 10.3892/ijmm.2018.3590].
    Matched MeSH terms: Drug Design
  18. Evaluating the performance of MM/PBSA for binding affinity prediction using class A GPCR crystal structures
    Yau MQ, Emtage AL, Chan NJY, Doughty SW, Loo JSE
    J Comput Aided Mol Des, 2019 05;33(5):487-496.
    PMID: 30989574 DOI: 10.1007/s10822-019-00201-3
    The recent expansion of GPCR crystal structures provides the opportunity to assess the performance of structure-based drug design methods for the GPCR superfamily. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA)-based methods are commonly used for binding affinity prediction, as they provide an intermediate compromise of speed and accuracy between the empirical scoring functions used in docking and more robust free energy perturbation methods. In this study, we systematically assessed the performance of MM/PBSA in predicting experimental binding free energies using twenty Class A GPCR crystal structures and 934 known ligands. Correlations between predicted and experimental binding free energies varied significantly between individual targets, ranging from r = - 0.334 in the inactive-state CB1 cannabinoid receptor to r = 0.781 in the active-state CB1 cannabinoid receptor, while average correlation across all twenty targets was relatively poor (r = 0.183). MM/PBSA provided better predictions of binding free energies compared to docking scores in eight out of the twenty GPCR targets while performing worse for four targets. MM/PBSA binding affinity predictions calculated using a single, energy minimized structure provided comparable predictions to sampling from molecular dynamics simulations and may be more efficient when computational cost becomes restrictive. Additionally, we observed that restricting MM/PBSA calculations to ligands with a high degree of structural similarity to the crystal structure ligands improved performance in several cases. In conclusion, while MM/PBSA remains a valuable tool for GPCR structure-based drug design, its performance in predicting the binding free energies of GPCR ligands remains highly system-specific as demonstrated in a subset of twenty Class A GPCRs, and validation of MM/PBSA-based methods for each individual case is recommended before prospective use.
    Matched MeSH terms: Drug Design
  19. Fulltext Computational approaches: discovery of GTPase HRas as prospective drug target for 1,3-diazine scaffolds
    Kumar S, Sharma D, Narasimhan B, Ramasamy K, Shah SAA, Lim SM, et al.
    BMC Chem, 2019 Dec;13(1):96.
    PMID: 31355369 DOI: 10.1186/s13065-019-0613-8
    Heterocyclic 1,3-diazine nucleus is a valuable pharmacophore in the field of medicinal chemistry and exhibit a wide spectrum of biological activities. PharmMapper, a robust online tool used for establishing the target proteins based on reverse pharmacophore mapping. PharmMapper study is carried out to explore the pharmacological activity of 1,3-diazine derivatives using reverse docking program. PharmMapper, an open web server was used to recognize for all the feasible target proteins for the developed compounds through reverse pharmacophore mapping. The results were analyzed via molecular docking with maestro v11.5 (Schrodinger 2018-1) using GTPase HRas as possible target. The molecular docking studies displayed the binding behavior of 1,3-diazine within GTP binding pocket. From the docking study compounds s3 and s14 showed better docked score with anticancer potency against cancer cell line (HCT116). Hence, the GTPase HRas may be the possible target of 1,3-diazine derivatives for their anticancer activity where the retrieved information may be quite useful for developing rational drug designing. Furthermore the selected 1,3-diazine compounds were evaluated for their in vitro anticancer activity against murine macrophages cell line. 1,3-Diazine compounds exhibited good selectivity of the compounds towards the human colorectal carcinoma cell line instead of the murine macrophages. The toxicity study of the most active compounds was also performed on non cancerous HEK-293 cell line.
    Matched MeSH terms: Drug Design
  20. Tuberculosis Treated by Multiple Drugs: An Overview
    Singh G, Kesharwani P, Srivastava AK
    Curr Drug Deliv, 2018;15(3):312-320.
    PMID: 29165080 DOI: 10.2174/1567201814666171120125916
    BACKGROUND: Tuberculosis is an infection and caused by gentle growing bacteria. The Internet provides opportunities for people with tuberculosis (TB) to connect with one another to address these challenges.

    OBJECTIVE: The aim of this paper is to introduce readers to the platforms on which Tuberculosis participants interact, to discuss reasons for and risks associated with TB-related activity, and to review research related to the potential impact of individual participation on TB outcomes.

    METHODS: Research and online content related to Tuberculosis online activity is reviewed, however, the difficulty in accurate prescribing and adhering to these protocols and the emergence of M. tuberculosis strains resistant to multiple drugs and drug-drug interactions that interfere with optimal treatment of Tuberculosis and co-infected patients with the different disease has generated a pressing need for improved Tuberculosis therapies.

    RESULTS: Together with the ominous global burden of Tuberculosis, those shortcomings of current medication have contributed to a renewed interest in the development of improved drugs and protocols for the medication of Tuberculosis. This article features obstacles related with the enhanced utilization of existing drugs and difficulties related with the advancement of enhanced products, concentrating on perspectives characteristic in Tuberculosis drug clinical improvement. The participation includes peer support, advocacy, self-expression, seeking and sharing TB information, improving approaches to Tuberculosis data management, and humour.

    CONCLUSION: This article highlights hurdles related to the optimised use of existing drugs and challenges related to the development of improved products, focusing on aspects inherent in Tuberculosis drug clinical development. Concluding comments offer processes for more efficient development of Tuberculosis therapies and increase the quality of life.

    Matched MeSH terms: Drug Design
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