scholarly journals Advancing the activity cliff concept, part II

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 75 ◽  
Author(s):  
Dagmar Stumpfe ◽  
Antonio de la Vega de León ◽  
Dilyana Dimova ◽  
Jürgen Bajorath

We present a follow up contribution to further complement a previous commentary on the activity cliff concept and recent advances in activity cliff research. Activity cliffs have originally been defined as pairs of structurally similar compounds that display a large difference in potency against a given target. For medicinal chemistry, activity cliffs are of high interest because structure-activity relationship (SAR) determinants can often be deduced from them. Herein, we present up-to-date results of systematic analyses of the ligand efficiency and lipophilic efficiency relationships between activity cliff-forming compounds, which further increase their attractiveness for the practice of medicinal chemistry. In addition, we summarize the results of a new analysis of coordinated activity cliffs and clusters they form. Taken together, these findings considerably add to our evaluation and current understanding of the activity cliff concept. The results should be viewed in light of the previous commentary article.

Author(s):  
Bhupender Nehra ◽  
Bijo Mathew ◽  
Pooja A Chawla

Aim: To describe structure activity relationship of heterocyclic derivatives with multi-targeted anticancer activity. Objectives: With the following goals in mind, this review tries to describe significant recent advances in the medicinal chemistry of heterocycle-based compounds: (1) To shed light on recent literature focused on heterocyclic derivatives' anticancer potential; (2) To discuss recent advances in the medicinal chemistry of heterocyclic derivatives, as well as their biological implications for cancer eradication; (3) To summarise the comprehensive correlation of structure activity relationship (SAR) with pharmacological outcomes in cancer therapy. Background: Cancer remains one of the major serious health issues devastating the world today. Cancer is a complex disease in which improperly altered cells proliferate at an uncontrolled, rapid, and severe rate. Variables such as poor dietary habits, high stress, age, and smoking, can all contribute to the development of cancer. Cancer can affect almost any organ or tissue, although the brain, breast, liver, and colon are the most frequently affected organs. From several years, surgical operations and irradiation are in use along with chemotherapy as a primary treatment of cancer but still effective treatment of cancer remains a huge challenge. Chemotherapy is now one of the most effective strategies to eradicate cancer, although it has been shown to have a number of cytotoxic and unfavourable effects on normal cells. Despite all of these cancer treatments, there are several other targets for anticancer drugs. Cancer can be effectively eradicated by focusing on these targets, which include both cell-specific and receptor-specific targets such as tyrosine kinase receptors (TKIs). Heterocyclic scaffolds also have a variety of applications in drug development and are a common moiety in the pharmaceutical, agrochemical, and textile industries. Methods: The association between structural activity relationship data of many powerful compounds and their anticancer potential in vitro and in vivo has been studied. SAR of powerful heterocyclic compounds can also be generated using molecular docking simulations, as reported vastly in literature. Conclusions: Heterocycles have a wide range of applications, from natural compounds to synthesised derivatives with powerful anticancer properties. To avoid cytotoxicity or unfavourable effects on normal mammalian cells due to a lack of selectivity towards the target site, as well as to reduce the occurrence of drug resistance, safer anticancer lead compounds with higher potency and lower cytotoxicity are needed. This review emphasizes on design and development of heterocyclic lead compounds with promising anticancer potential.


Author(s):  
Javed Iqbal ◽  
Martin Vogt ◽  
Jürgen Bajorath

AbstractAn activity cliff (AC) is formed by a pair of structurally similar compounds with a large difference in potency. Accordingly, ACs reveal structure–activity relationship (SAR) discontinuity and provide SAR information for compound optimization. Herein, we have investigated the question if ACs could be predicted from image data. Therefore, pairs of structural analogs were extracted from different compound activity classes that formed or did not form ACs. From these compound pairs, consistently formatted images were generated. Image sets were used to train and test convolutional neural network (CNN) models to systematically distinguish between ACs and non-ACs. The CNN models were found to predict ACs with overall high accuracy, as assessed using alternative performance measures, hence establishing proof-of-principle. Moreover, gradient weights from convolutional layers were mapped to test compounds and identified characteristic structural features that contributed to successful predictions. Weight-based feature visualization revealed the ability of CNN models to learn chemistry from images at a high level of resolution and aided in the interpretation of model decisions with intrinsic black box character.


F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 36 ◽  
Author(s):  
Ye Hu ◽  
Antonio de la Vega de León ◽  
Bijun Zhang ◽  
Jürgen Bajorath

Matched molecular pairs (MMPs) are widely used in medicinal chemistry to study changes in compound properties including biological activity, which are associated with well-defined structural modifications. Herein we describe up-to-date versions of three MMP-based data sets that have originated from in-house research projects. These data sets include activity cliffs, structure-activity relationship (SAR) transfer series, and second generation MMPs based upon retrosynthetic rules. The data sets have in common that they have been derived from compounds included in the latest release of the ChEMBL database for which high-confidence activity data are available. Thus, the activity data associated with MMP-based activity cliffs, SAR transfer series, and retrosynthetic MMPs cover the entire spectrum of current pharmaceutical targets. Our data sets are made freely available to the scientific community.


2019 ◽  
Vol 05 ◽  
Author(s):  
Vikas Sharma ◽  
Raj Kamal ◽  
Dinesh Kumar ◽  
Vipan Kumar

: Alkaloids having indolizidine moiety are well known for their biological actions. In this review, indolizidine alkaloids like antofine, castanospermine, swainsonine, tylophorine, gephyrotoxins, lentiginosine, pergularinine etc and their derivatives have been discussed. Furthermore, important points related to the structure-activity relationship of selected alkaloids are also summarized. All these studies indicate the lead potential of indolizidine alkaloids that in turn could be effective for future drug discovery.


2015 ◽  
Vol 10 (5) ◽  
pp. 441-447 ◽  
Author(s):  
Dilyana Dimova ◽  
Dagmar Stumpfe ◽  
Ye Hu ◽  
Jürgen Bajorath

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