Success Stories of Computer‐Aided Design

Kubinyi, Hugo

doi:10.1002/0470037237.ch16

Cited by 77 publications

(49 citation statements)

References 156 publications

(372 reference statements)

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“…Then modellers try to modify the ligand by adding or removing substituents, fusing rings or changing atom types to alter the binding energetics, conformational preferences and physicochemical properties and thereby hopefully also enhance the potency of new analogs. This approach is working very well as documented by numerous examples from literature [1,2] and also by many successful applications of manual molecular design in supporting in-house Novartis projects.…”

Section: Introductionmentioning

confidence: 87%

IADE: a system for intelligent automatic design of bioisosteric analogs

Ertl

Lewis

2012

J Comput Aided Mol Des

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IADE, a software system supporting molecular modellers through the automatic design of non-classical bioisosteric analogs, scaffold hopping and fragment growing, is presented. The program combines sophisticated cheminformatics functionalities for constructing novel analogs and filtering them based on their drug-likeness and synthetic accessibility using automatic structure-based design capabilities: the best candidates are selected according to their similarity to the template ligand and to their interactions with the protein binding site. IADE works in an iterative manner, improving the fitness of designed molecules in every generation until structures with optimal properties are identified. The program frees molecular modellers from routine, repetitive tasks, allowing them to focus on analysis and evaluation of the automatically designed analogs, considerably enhancing their work efficiency as well as the area of chemical space that can be covered. The performance of IADE is illustrated through a case study of the design of a nonclassical bioisosteric analog of a farnesyltransferase inhibitor--an analog that has won a recent "Design a Molecule" competition.

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Section: Introductionmentioning

confidence: 87%

IADE: a system for intelligent automatic design of bioisosteric analogs

Ertl

Lewis

2012

J Comput Aided Mol Des

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“…The larger value means the higher similarity and probability that the particular molecule will be active. The drug likeness score is calculated from the combined score of several bioactivity parameters similarity such as GPCR (G-protein coupled receptor) ligand, ion channel modulator, kinase inhibitor, nuclear receptor ligand, protease inhibitor and enzyme inhibitor properties (Kubinyi, 2006). From Table 3, it is shown that all best ligands have a larger drug likeness value than standards, except Bb38 ligand which has a little lower drug likeness value than TSA standards.…”

Section: Pharmacology Analysismentioning

confidence: 99%

In silico identification of 2-oxo-1,3-thiazolidine derivatives as novel inhibitor candidate of class II histone deacetylase (HDAC) in cervical cancer treatment

Tambunan

Parikesit

Ghifari

et al. 2019

Arabian Journal of Chemistry

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Cervical cancer ranks third among the most prevalent deadly cancer in women worldwide and ranks first in developing countries. It is caused by human papilloma virus (HPV) infection. Thus HDACs have become prominent inhibition target for cervical cancer treatment. In order to discover the new alternative HDAC inhibitors (HDACIs), we conducted a computer-aided drug discovery and development (CADDD) based on de novo approach. The compound library is based on 4-[(2-oxo-1,3-thiazolidin-3-yl)carbonyl] aniline. Screening of the best drug leads was evaluated from several parameters, such as docking and interaction analysis, pharmacology, in silico preclinical trial and molecular dynamics analysis. The inhibitory activity of these new designed ligands against Homo sapiens class II HDAC was determined by molecular docking simulation. Docking analysis yielded eight best ligands which have better binding affinity than the standards. Therefore, interaction analysis indicated that all best ligands performed coordination with Zn 2+ cofactor in HDAC charge-relay system which are essential for HDAC inhibitory activities of these inhibitors. Pharmacology analysis and preclinical trials of these compounds including pharmacology properties, bioactivity, mutagenicity-carcinogenicity, absorption, distribution, metabolism, excretion and toxicity (ADMET) properties were done through in silico methods. Through this analysis, the best ligands meet Lipinski's rule of five, have a better drug score than standards, and show good bioactivities, oral bioavailability and ADMET properties. All best ligands also have good synthetic accessibility and were proved to be new compounds that have never been synthesized

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“…[33] IUPAC has described a pharmacophore as an ensemble of steric and electronic features which is necessary to ensure the optimal intermolecular interactions with a specific biological target and to trigger (or to block) its biological response. [34] The modeling involves creating a conformational space for the ligands and aligning them together to identify common pharmacophoric features to construct a model, or called the pharmacophore hypothesis.…”

Section: Cheminfomatic Approaches To Discover Rtk Inhibitorsmentioning

confidence: 99%

Cheminfomatic-based Drug Discovery of Human Tyrosine Kinase Inhibitors

Reid¹,

Fortunak²,

Wutoh³

et al. 2016

CTMC

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Receptor Tyrosine Kinases (RTKs) are essential components for regulating cell-cell signaling and communication events in cell growth, proliferation, differentiation, survival and metabolism. Deregulation of RTKs and their associated signaling pathways can lead to a wide variety of human diseases such as immunodeficiency, diabetes, arterosclerosis, psoriasis and cancer. Thus RTKs have become one of the most important drug targets families in recent decade. Pharmaceutical companies have dedicated their research efforts towards the discovery of small-molecule inhibitors of RTKs, many of which had been approved by the U.S. Food and Drug Administration (US FDA) or are currently in clinical trials. The great successes in the development of small-molecule inhibitors of RTKs are largely attributed to the use of modern cheminformatic approaches to identifying lead scaffolds. Those include the quantitative structure-activity relationship (QSAR) modeling, as well as the structure-, and ligand-based pharmacophore modeling techniques in this case. Herein we inspected the literature thoroughly in an effort to conduct a comparative analysis of major findings regarding the essential structure-activity relationships (SARs)/pharmacophore features of known active RTK inhibitors, most of which were collected from cheminformatic modeling approaches.

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Success Stories of Computer‐Aided Design

Cited by 77 publications

References 156 publications

IADE: a system for intelligent automatic design of bioisosteric analogs

IADE: a system for intelligent automatic design of bioisosteric analogs

In silico identification of 2-oxo-1,3-thiazolidine derivatives as novel inhibitor candidate of class II histone deacetylase (HDAC) in cervical cancer treatment

Cheminfomatic-based Drug Discovery of Human Tyrosine Kinase Inhibitors

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