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Huang D, Chen Y, Yang J, Zhao B, Wang S, Chai T, Cui J, Zhou X, Shang Z. Design, Synthesis, and Biological Evaluation of 2-Substituted Aniline Pyrimidine Derivatives as Potent Dual Mer/c-Met Inhibitors. Molecules 2024; 29:475. [PMID: 38257391 PMCID: PMC10819570 DOI: 10.3390/molecules29020475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/04/2024] [Accepted: 01/13/2024] [Indexed: 01/24/2024] Open
Abstract
Mer and c-Met kinases, which are commonly overexpressed in various tumors, are ideal targets for the development of antitumor drugs. This study focuses on the design, synthesis, and evaluation of several 2-substituted aniline pyrimidine derivatives as highly potent dual inhibitors of Mer and c-Met kinases for effective tumor treatment. Compound 18c emerged as a standout candidate, demonstrating robust inhibitory activity against Mer and c-Met kinases, with IC50 values of 18.5 ± 2.3 nM and 33.6 ± 4.3 nM, respectively. Additionally, compound 18c displayed good antiproliferative activities on HepG2, MDA-MB-231, and HCT116 cancer cells, along with favorable safety profiles in hERG testing. Notably, it exhibited exceptional liver microsomal stability in vitro, with a half-life of 53.1 min in human liver microsome. Compound 18c also exhibited dose-dependent cytotoxicity and hindered migration of HCT116 cancer cells, as demonstrated in apoptosis and migration assays. These findings collectively suggest that compound 18c holds promise as a dual Mer/c-Met agent for cancer treatment.
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Affiliation(s)
- Daowei Huang
- School of Chemical and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; (D.H.); (Y.C.); (B.Z.); (T.C.)
- State Key Laboratory Breeding Base-Hebei Key Laboratory of Molecular Chemistry for Drug, Shijiazhuang 050018, China
| | - Ying Chen
- School of Chemical and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; (D.H.); (Y.C.); (B.Z.); (T.C.)
| | - Jixia Yang
- School of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China;
| | - Bingyang Zhao
- School of Chemical and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; (D.H.); (Y.C.); (B.Z.); (T.C.)
| | - Shouying Wang
- School of Food Science and Biology, Hebei University of Science and Technology, Shijiazhuang 050018, China;
| | - Tingting Chai
- School of Chemical and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; (D.H.); (Y.C.); (B.Z.); (T.C.)
| | - Jie Cui
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China;
| | - Xiaolei Zhou
- School of Food Science and Biology, Hebei University of Science and Technology, Shijiazhuang 050018, China;
| | - Zhenhua Shang
- School of Chemical and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; (D.H.); (Y.C.); (B.Z.); (T.C.)
- State Key Laboratory Breeding Base-Hebei Key Laboratory of Molecular Chemistry for Drug, Shijiazhuang 050018, China
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2
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Kotev M, Diaz Gonzalez C. Molecular Dynamics and Other HPC Simulations for Drug Discovery. Methods Mol Biol 2024; 2716:265-291. [PMID: 37702944 DOI: 10.1007/978-1-0716-3449-3_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
High performance computing (HPC) is taking an increasingly important place in drug discovery. It makes possible the simulation of complex biochemical systems with high precision in a short time, thanks to the use of sophisticated algorithms. It promotes the advancement of knowledge in fields that are inaccessible or difficult to access through experimentation and it contributes to accelerating the discovery of drugs for unmet medical needs while reducing costs. Herein, we report how computational performance has evolved over the past years, and then we detail three domains where HPC is essential. Molecular dynamics (MD) is commonly used to explore the flexibility of proteins, thus generating a better understanding of different possible approaches to modulate their activity. Modeling and simulation of biopolymer complexes enables the study of protein-protein interactions (PPI) in healthy and disease states, thus helping the identification of targets of pharmacological interest. Virtual screening (VS) also benefits from HPC to predict in a short time, among millions or billions of virtual chemical compounds, the best potential ligands that will be tested in relevant assays to start a rational drug design process.
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Affiliation(s)
- Martin Kotev
- Evotec SE, Integrated Drug Discovery, Molecular Architects, Campus Curie, Toulouse, France
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3
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Grottelli S, Annunziato G, Pampalone G, Pieroni M, Dindo M, Ferlenghi F, Costantino G, Cellini B. Identification of Human Alanine-Glyoxylate Aminotransferase Ligands as Pharmacological Chaperones for Variants Associated with Primary Hyperoxaluria Type 1. J Med Chem 2022; 65:9718-9734. [PMID: 35830169 PMCID: PMC9340776 DOI: 10.1021/acs.jmedchem.2c00142] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
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Primary hyperoxaluria type I (PH1) is a rare kidney disease
due
to the deficit of alanine:glyoxylate aminotransferase (AGT), a pyridoxal-5′-phosphate-dependent
enzyme responsible for liver glyoxylate detoxification, which in turn
prevents oxalate formation and precipitation as kidney stones. Many
PH1-associated missense mutations cause AGT misfolding. Therefore,
the use of pharmacological chaperones (PCs), small molecules that
promote correct folding, represents a useful therapeutic option. To
identify ligands acting as PCs for AGT, we first performed a small
screening of commercially available compounds. We tested each molecule
by a dual approach aimed at defining the inhibition potency on purified
proteins and the chaperone activity in cells expressing a misfolded
variant associated with PH1. We then performed a chemical optimization
campaign and tested the resulting synthetic molecules using the same
approach. Overall, the results allowed us to identify a promising
hit compound for AGT and draw conclusions about the requirements for
optimal PC activity.
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Affiliation(s)
- Silvia Grottelli
- Department of Medicine and Surgery, University of Perugia, P.le L. Severi 1, 06132 Perugia, Italy
| | - Giannamaria Annunziato
- Department of Food and Drug, University of Parma, Parco Area delle Scienze 27/A, 43124 Parma, Italy
| | - Gioena Pampalone
- Department of Medicine and Surgery, University of Perugia, P.le L. Severi 1, 06132 Perugia, Italy
| | - Marco Pieroni
- Department of Food and Drug, University of Parma, Parco Area delle Scienze 27/A, 43124 Parma, Italy
| | - Mirco Dindo
- Department of Medicine and Surgery, University of Perugia, P.le L. Severi 1, 06132 Perugia, Italy
| | - Francesca Ferlenghi
- Department of Food and Drug, University of Parma, Parco Area delle Scienze 27/A, 43124 Parma, Italy
| | - Gabriele Costantino
- Department of Food and Drug, University of Parma, Parco Area delle Scienze 27/A, 43124 Parma, Italy
| | - Barbara Cellini
- Department of Medicine and Surgery, University of Perugia, P.le L. Severi 1, 06132 Perugia, Italy
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Allosteric Modulation of the Main Protease (MPro) of SARS-CoV-2 by Casticin—Insights from Molecular Dynamics Simulations. CHEMISTRY AFRICA 2022. [PMCID: PMC9261893 DOI: 10.1007/s42250-022-00411-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Inhibition of the main protease (Mpro) of SARS-CoV-2 has been suggested to be vital in shutting down viral replication in a host. Most efforts aimed at inhibiting MPro activity have been channeled into competitive inhibition at the active site, but this strategy will require a high inhibitor concentration and impressive inhibitor-MPro binding affinity. Allosteric inhibition can potentially serve as an effective strategy for alleviating these limitations. In this study, the ability of antiviral natural products to inhibit MPro in an allosteric fashion was explored with in silico techniques. Molecular docking revealed a strong interaction between casticin, an antiviral flavonoid, and Mpro at a site distant from the active site. This site, characterized as a distal site, has been shown to have an interdependent dynamic effect with the active site region. Mpro only, Mpro-peptide (binary) and Mpro-peptide-casticin (ternary) complexes were subjected to molecular dynamics simulations for 50 ns to investigate the modulatory activity of casticin binding on Mpro. Molecular dynamic simulations revealed that binding of casticin at the distal site interferes with the proper orientation of the peptide substrate in the oxyanion hole of the active site, and this could lead to a halt or decrease in catalytic activity. This study therefore highlights casticin as a potential allosteric modulator of the SARS-CoV-2 main protease, which could be optimized and developed into a potential lead compound for anti-SARS-CoV-2 chemotherapy.
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An In Silico Study of the Interactions of Alkaloids from Cryptolepis sanguinolenta with Plasmodium falciparum Dihydrofolate Reductase and Dihydroorotate Dehydrogenase. J CHEM-NY 2022. [DOI: 10.1155/2022/5314179] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The Plasmodium falciparum dihydrofolate reductase (PfDHFR) and dihydroorotate dehydrogenase (PfDHODH) are essential for Plasmodium falciparum growth and development, and have been validated as targets for the development of new antimalarial agents. Several alkaloids isolated from Cryptolepis sanguinolenta have been reported to have antiplasmodial activity, but their protein targets are unknown. Therefore, molecular docking and molecular dynamics simulations were used to investigate the interactions and stability of the alkaloids with PfDHFR and PfDHODH. Based on physicochemical characteristics, alkaloids were grouped as sterically bulky (sb) or planar (pg). Docking results revealed strong binding affinities (−6.0 to −13.4 kcal/mol) of the alkaloids against PfDHODH and various strains of PfDHFR while interacting with key residues such as Asp54 and Phe58 in PfDHFR. The pg alkaloids had high binding affinity and preference for the inhibitor binding domain over the flavin mononucleotide (FMN) binding domain in PfDHODH due to size considerations. From the molecular dynamics trajectories, protein-alkaloid complexes were stable throughout the simulation, with supporting evidence from root mean square deviations, root mean square fluctuations, radius of gyration, free binding energies, and other parameters. We report herein that biscryptolepine and cryptomisrine (sb class), as well as cryptolepinone, cryptoheptine, cryptolepine, and neocryptolepine (pg class), are capable of inhibiting PfDHFR effectively in pyrimethamine sensitive and resistant cells. Also, our results show that alkaloids of the pg class can inhibit PfDHODH as FMN decoys, as well as direct enzyme inhibitors, thereby halting crucial protein function.
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6
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Fragment-to-lead tailored in silico design. DRUG DISCOVERY TODAY. TECHNOLOGIES 2021; 40:44-57. [PMID: 34916022 DOI: 10.1016/j.ddtec.2021.08.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 06/25/2021] [Accepted: 08/11/2021] [Indexed: 02/07/2023]
Abstract
Fragment-based drug discovery (FBDD) emerged as a disruptive technology and became established during the last two decades. Its rationality and low entry costs make it appealing, and the numerous examples of approved drugs discovered through FBDD validate the approach. However, FBDD still faces numerous challenges. Perhaps the most important one is the transformation of the initial fragment hits into viable leads. Fragment-to-lead (F2L) optimization is resource-intensive and is therefore limited in the possibilities that can be actively pursued. In silico strategies play an important role in F2L, as they can perform a deeper exploration of chemical space, prioritize molecules with high probabilities of being active and generate non-obvious ideas. Here we provide a critical overview of current in silico strategies in F2L optimization and highlight their remarkable impact. While very effective, most solutions are target- or fragment- specific. We propose that fully integrated in silico strategies, capable of automatically and systematically exploring the fast-growing available chemical space can have a significant impact on accelerating the release of fragment originated drugs.
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7
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Multiple Target Drug Design Using LigBuilder 3. Methods Mol Biol 2021. [PMID: 33759133 DOI: 10.1007/978-1-0716-1209-5_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Designing drugs that directly interact with multiple targets is a promising approach for treating complicated diseases. In order to successfully bind to multiple targets of different families and achieve the desired ligand efficiency, multi-target-directed ligands (MTDLs) require a higher level of diversity and complexity. De novo design strategies for creating more diverse chemical entities with desired properties may present an improved approach for developing MTDLs. In this chapter, we describe a computational protocol for developing MTDLs using the first reported multi-target de novo program, LigBuilder 3, which combines a binding site prediction module with de novo drug design and optimization modules. As an illustration of each detailed procedure, we design dual-functional compounds of two well-characterized virus enzymes, HIV protease and reverse transcriptase (PR and RT, respectively), using fragments extracted from known inhibitors. LigBuilder 3 is accessible at http://www.pkumdl.cn/ligbuilder3/ .
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Gumede NJ, Nxumalo W, Bisetty K, Escuder Gilabert L, Medina-Hernandez MJ, Sagrado S. Prospective computational design and in vitro bio-analytical tests of new chemical entities as potential selective CYP17A1 lyase inhibitors. Bioorg Chem 2019; 94:103462. [PMID: 31818479 DOI: 10.1016/j.bioorg.2019.103462] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 09/27/2019] [Accepted: 11/20/2019] [Indexed: 10/25/2022]
Abstract
The development and advancement of prostate cancer (PCa) into stage 4, where it metastasize, is a major problem mostly in elder males. The growth of PCa cells is stirred up by androgens and androgen receptor (AR). Therefore, therapeutic strategies such as blocking androgens synthesis and inhibiting AR binding have been explored in recent years. However, recently approved drugs (or in clinical phase) failed in improving the expected survival rates for this metastatic-castration resistant prostate cancer (mCRPC) patients. The selective CYP17A1 inhibition of 17,20-lyase route has emerged as a novel strategy. Such inhibition blocks the production of androgens everywhere they are found in the body. In this work, a three dimensional-quantitative structure activity relationship (3D-QSAR) pharmacophore model is developed on a diverse set of non-steroidal inhibitors of CYP17A1 enzyme. Highly active compounds are selected to define a six-point pharmacophore hypothesis with a unique geometrical arrangement fitting the following description: two hydrogen bond acceptors (A), two hydrogen bond donors (D) and two aromatic rings (R). The QSAR model showed adequate predictive statistics. The 3D-QSAR model is further used for database virtual screening of potential inhibitory hit structures. Density functional theory (DFT) optimization provides the electronic properties explaining the reactivity of the hits. Docking simulations discovers hydrogen bonding and hydrophobic interactions as responsible for the binding affinities of hits to the CYP17A1 Protein Data Bank structure. 13 hits from the database search (including five derivatives) are then synthesized in the laboratory as different scaffolds. Ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in vitro experiments reveals three new chemical entities (NCEs) with half maximal inhibitory concentration (IC50) values against the lyase route at mid-micromolar range with favorable selectivity to the lyase over the hydroxylase route (one of them with null hydroxylase inhibition). Thus, prospective computational design has enabled the design of potential lead lyase-selective inhibitors for further studies.
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Affiliation(s)
- N J Gumede
- Department of Chemistry, Mangosuthu University of Technology, PO Box 12363, Jacobs 4026, South Africa.
| | - W Nxumalo
- Department of Chemistry, University of Limpopo, Private Bag X 1106, Sovenga 0727, South Africa
| | - K Bisetty
- Department of Chemistry, Durban University of Technology, PO Box 1334, Durban 4000, South Africa
| | - L Escuder Gilabert
- Departamento de Química Analítica, Facultad de Farmacia, Universidad de Valencia, Avda. Vicent Andrés Estellés, s/n, E-46100 Burjassot, Valencia, Spain
| | - M J Medina-Hernandez
- Departamento de Química Analítica, Facultad de Farmacia, Universidad de Valencia, Avda. Vicent Andrés Estellés, s/n, E-46100 Burjassot, Valencia, Spain
| | - S Sagrado
- Departamento de Química Analítica, Facultad de Farmacia, Universidad de Valencia, Avda. Vicent Andrés Estellés, s/n, E-46100 Burjassot, Valencia, Spain; Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, Universitat de València, Avda. Vicent Andrés Estellés, s/n, E-46100 Burjassot, Valencia, Spain
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9
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Zhang J, Wang S, Ba Y, Xu Z. Tetrazole hybrids with potential anticancer activity. Eur J Med Chem 2019; 178:341-351. [PMID: 31200236 DOI: 10.1016/j.ejmech.2019.05.071] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 05/25/2019] [Accepted: 05/25/2019] [Indexed: 12/15/2022]
Abstract
Cancer is one of the main causes of death throughout the world. The anticancer agents are indispensable for the treatment of various cancers, but most of them currently on the market are not specific, resulting in series of side effects of chemotherapy. Moreover, the emergency of drug-resistance towards cancers has already increased up to alarming level in the recent decades. Therefore, it's imperative to develop novel anticancer candidates with excellent activity against both drug-susceptible and drug-resistant cancers, and low toxicity as well. Tetrazole is the bioisoster of carboxylic acid, and its derivatives demonstrated promising anticancer activity. Hybridization of tetrazole with other anticancer pharmacophores may provide novel candidates with anticancer potency. The present review described the anticancer activity of tetrazole hybrids, and the structure-activity relationship (SAR) is also discussed to provide an insight for rational designs of tetrazole anticancer candidates with higher efficiency.
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Affiliation(s)
- Jingyu Zhang
- Pharmacy College, Henan University of Chinese Medicine, 450046, Zhengzhou, PR China.
| | - Su Wang
- Pharmacy College, Henan University of Chinese Medicine, 450046, Zhengzhou, PR China
| | - Yanyan Ba
- Pharmacy College, Henan University of Chinese Medicine, 450046, Zhengzhou, PR China
| | - Zhi Xu
- Huanghuai University, College of Chemistry and Pharmaceutical Engineering, Zhumadian, PR China.
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10
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Schneider G, Clark DE. Automated De Novo Drug Design: Are We Nearly There Yet? Angew Chem Int Ed Engl 2019; 58:10792-10803. [PMID: 30730601 DOI: 10.1002/anie.201814681] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Indexed: 11/09/2022]
Abstract
Medicinal chemistry and, in particular, drug design have often been perceived as more of an art than a science. The many unknowns of human disease and the sheer complexity of chemical space render decision making in medicinal chemistry exceptionally demanding. Computational models can assist the medicinal chemist in this endeavour. Provided here is an overview of recent examples of automated de novo molecular design, a discussion of the concepts and computational approaches involved, and the daring prediction of some of the possibilities and limitations of drug design using machine intelligence.
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Affiliation(s)
- Gisbert Schneider
- ETH Zurich, Department of Chemistry and Applied Biosciences, RETHINK, Vladimir-Prelog-Weg 4, 8093, Zurich, Switzerland
| | - David E Clark
- Charles River, 6-9 Spire Green Centre, Harlow, Essex, CM19 5TR, UK
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11
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Schneider G, Clark DE. Automated De Novo Drug Design: Are We Nearly There Yet? Angew Chem Int Ed Engl 2019. [DOI: 10.1002/ange.201814681] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Gisbert Schneider
- ETH ZurichDepartment of Chemistry and Applied Biosciences, RETHINK Vladimir-Prelog-Weg 4 8093 Zurich Switzerland
| | - David E. Clark
- Charles River 6–9 Spire Green Centre Harlow Essex CM19 5TR UK
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12
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Slater O, Kontoyianni M. The compromise of virtual screening and its impact on drug discovery. Expert Opin Drug Discov 2019; 14:619-637. [PMID: 31025886 DOI: 10.1080/17460441.2019.1604677] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.
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Affiliation(s)
- Olivia Slater
- a Department of Pharmaceutical Sciences , Southern Illinois University Edwardsville , Edwardsville , IL , USA
| | - Maria Kontoyianni
- a Department of Pharmaceutical Sciences , Southern Illinois University Edwardsville , Edwardsville , IL , USA
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Abstract
Molegro Virtual Docker is a protein-ligand docking simulation program that allows us to carry out docking simulations in a fully integrated computational package. MVD has been successfully applied to hundreds of different proteins, with docking performance similar to other docking programs such as AutoDock4 and AutoDock Vina. The program MVD has four search algorithms and four native scoring functions. Considering that we may have water molecules or not in the docking simulations, we have a total of 32 docking protocols. The integration of the programs SAnDReS ( https://github.com/azevedolab/sandres ) and MVD opens the possibility to carry out a detailed statistical analysis of docking results, which adds to the native capabilities of the program MVD. In this chapter, we describe a tutorial to carry out docking simulations with MVD and how to perform a statistical analysis of the docking results with the program SAnDReS. To illustrate the integration of both programs, we describe the redocking simulation focused the cyclin-dependent kinase 2 in complex with a competitive inhibitor.
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Affiliation(s)
- Gabriela Bitencourt-Ferreira
- Escola de Ciências da Saúde, Pontifícia Universidade Católica do Rio Grande do Sul-PUCRS, Porto Alegre, RS, Brazil
| | - Walter Filgueira de Azevedo
- Escola de Ciências da Saúde, Pontifícia Universidade Católica do Rio Grande do Sul-PUCRS, Porto Alegre, RS, Brazil.
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Hameed R, Khan A, Khan S, Perveen S. Computational Approaches Towards Kinases as Attractive Targets for Anticancer Drug Discovery and Development. Anticancer Agents Med Chem 2018; 19:592-598. [PMID: 30306880 DOI: 10.2174/1871520618666181009163014] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Revised: 04/09/2018] [Accepted: 09/03/2018] [Indexed: 01/07/2023]
Abstract
BACKGROUND One of the major goals of computational chemists is to determine and develop the pathways for anticancer drug discovery and development. In recent past, high performance computing systems elicited the desired results with little or no side effects. The aim of the current review is to evaluate the role of computational chemistry in ascertaining kinases as attractive targets for anticancer drug discovery and development. METHODS Research related to computational studies in the field of anticancer drug development is reviewed. Extensive literature on achievements of theorists in this regard has been compiled and presented with special emphasis on kinases being the attractive anticancer drug targets. RESULTS Different approaches to facilitate anticancer drug discovery include determination of actual targets, multi-targeted drug discovery, ligand-protein inverse docking, virtual screening of drug like compounds, formation of di-nuclear analogs of drugs, drug specific nano-carrier design, kinetic and trapping studies in drug design, multi-target QSAR (Quantitative Structure Activity Relationship) model, targeted co-delivery of anticancer drug and siRNA, formation of stable inclusion complex, determination of mechanism of drug resistance, and designing drug like libraries for the prediction of drug-like compounds. Protein kinases have gained enough popularity as attractive targets for anticancer drugs. These kinases are responsible for uncontrolled and deregulated differentiation, proliferation, and cell signaling of the malignant cells which result in cancer. CONCLUSION Interest in developing drugs through computational methods is a growing trend, which saves equally the cost and time. Kinases are the most popular targets among the other for anticancer drugs which demand attention. 3D-QSAR modelling, molecular docking, and other computational approaches have not only identified the target-inhibitor binding interactions for better anticancer drug discovery but are also designing and predicting new inhibitors, which serve as lead for the synthetic preparation of drugs. In light of computational studies made so far in this field, the current review highlights the importance of kinases as attractive targets for anticancer drug discovery and development.
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Affiliation(s)
- Rabia Hameed
- Department of Chemistry, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan
| | - Afsar Khan
- Department of Chemistry, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan
| | - Sehroon Khan
- Key Laboratory of Economic Plants and Biotechnology, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 560201, Yunnan, China
| | - Shagufta Perveen
- Department of Pharmacognosy, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh 11451, Saudi Arabia
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