LEADOPT: An automatic tool for structure-based lead optimization, and its application in structural optimizations of VEGFR2 and SYK inhibitors

doi:10.1016/j.ejmech.2015.02.019

European Journal of Medicinal Chemistry

Volume 93, 26 March 2015, Pages 523-538

https://doi.org/10.1016/j.ejmech.2015.02.019 Get rights and content

Highlights

•
We built a new automatic tool for structure-based lead optimization called LEADOPT.
•
Ligand efficiency is used as a measure to sort the generated molecules in LEADOPT.
•
Twelve ADMET properties are evaluated in LEADOPT.
•
We obtained some new potent VEGFR2 and SYK inhibitors using LEADOPT.

Abstract

Lead optimization is one of the key steps in drug discovery, and currently it is carried out mostly based on experiences of medicinal chemists, which often suffers from low efficiency. In silico methods are thought to be useful in improving the efficiency of lead optimization. Here we describe a new in silico automatic tool for structure-based lead optimization, termed LEADOPT. The structural modifications in LEADOPT mainly include two operations: fragment growing and fragment replacing, which are restricted to carry out in the active pocket of target protein with the core scaffold structure of ligand kept unchanged. The bioactivity of the newly generated molecules is estimated by ligand efficiency rather than a commonly used scoring function. Twelve important pharmacokinetic and toxic properties are evaluated using SCADMET, a program for the prediction of pharmacokinetic and toxic properties. LEADOPT was first evaluated using two retrospective cases, in which it showed a very good performance. LEADOPT was then applied to the structural optimizations of the VEGFR2 inhibitor, sorafenib, and the SYK inhibitor, R406. Though just several compounds were synthesized, we have obtained some compounds that are more potent than sorafenib and R406 in enzymatic and functional assays. All of these have validated, at least to some extent, the effectiveness of LEADOPT.

Graphical abstract

A new in silico automatic tool for structure-based lead optimization termed LEADOPT was developed. It was successfully applied to the structural optimizations of the VEGFR2 inhibitor, sorafenib, and the SYK inhibitor, R406.

Introduction

Discovery of drug candidates is a bottleneck in drug research and development (R&D). The whole procedure for the discovery of drug candidates often includes two phases: lead discovery and lead optimization [1]. Currently the lead discovery is no longer a big problem or at least not a key challenge due to that many new technologies for the lead discovery have been well established and applied, such as high-throughput screening, biophysical screening, combinatorial chemistry, as well as virtual screening [2], [3], [4], [5], [6]. However, at present the lead optimization is carried out mostly based on experiences of medicinal chemists, which often suffers from low efficiency. The lead optimization has now become a key challenge in not only the discovery of drug candidates but also the whole process of drug R&D.

Computational methods are often thought to be helpful in improving the efficiency of lead optimization [7], [8], [9], [10]. Thus, some in silico methods have been established and applied in the lead optimization. Among these methods, three-dimensional quantitative structure activity relationship (3D-QSAR) methods, for example, comparative molecular field analysis (CoMFA) [11] and comparative molecular similarity indices analysis (CoMSIA) [12], are the most widely used ones. Numerous studies have demonstrated that 3D-QSAR methods are very useful in lead optimization [13], [14], [15], [16]. Nevertheless, the current 3D-QSAR methods as well as other commonly used in silico methods for lead optimization are often just based on small-molecule ligands, implying ignoring structural information of target protein. This situation may lead to the theoretically optimized molecules having no activity due to bumps between molecules and target protein atoms. Structure-based lead optimization approaches are expected to be able to overcome these shortcomings, in which the structure of ligand is modified to enhance the binding affinity based on the known interaction mode between target protein and ligand [17], [18], [19], [20], [21]. Although these approaches have been applied in lead optimization for a long time, they are often used manually by medicinal chemists, which still suffer inevitably from low efficiency. We also noticed that very recently a commercial module for structure-based ligand optimization has been issued in MOE by Chemical Computing Group Inc. However, its implementation details are not known, and it likely does not include the evaluation of pharmacokinetic and toxic properties for the generated molecules, which is also important for lead optimization.

Here we present an automatic tool for structure-based lead optimization, termed LEADOPT. LEADOPT has the following characteristics that make it a practical tool in lead optimization. First, a large number of derivatives of lead compound that have the same binding mode with the active pocket of target protein can be created. These compounds can be accommodated in the active pocket without any atom bump with the target protein. Second, LEADOPT builds up new molecules using an efficient fragment-based strategy. Such a strategy can help avoid producing unreasonable molecular structures and to some extent keep the synthetic accessibility of the derived compounds. Third, ligand efficiency (LE) rather than scoring function is used as a measure to sort the newly generated molecules; LE has been considered as an effective strategy to help narrow focus to lead compounds with optimal combinations of physicochemical properties and pharmacological properties [22], [23]. Fourth, a number of pharmacokinetic and toxic properties of the generated molecules are evaluated, which makes the lead candidates pharmacologically acceptable. We shall in the following describe the details for the algorithm of LEADOPT. Then, LEADOPT will be evaluated with two retrospective cases. Finally, it will be applied to the structural optimizations of sorafenib, an inhibitor of vascular endothelial growth factor receptor 2 (VEGFR2), and R406, an inhibitor of spleen tyrosine kinase (SYK).

Section snippets

Fragment library construction

Since LEADOPT adopts a fragment-based approach for structural modifications to derive new molecular structures, a good fragment library is quite important for the quality of derived molecules. To establish such a fragment library, we first collected a total of 17,858 drug or drug-like molecules from CMC database, ChEMBL database [24], and DrugBank database [25]. Then, an in-house program written by us in C/C++ programming language was used to automatically build the fragment library. The

Development of LEADOPT

LEADOPT is an automatic tool developed for structure-based lead optimization. The overall workflow of LEADOPT is schematically depicted in Fig. 1. A detailed description of the algorithms of LEADOPT has been given in the Methods and Materials section. Here we just make a short summary for the workflow of LEADOPT. LEADOPT is started through input of the structure of ligand–receptor complex, which can be from either experimental X-ray crystal structure or molecule docking. Firstly, LEADOPT

Concluding remarks

In this investigation, we developed an automatic tool for structure-based lead optimization, termed LEADOPT. LEADOPT starts its work from an input structure of ligand–receptor complex, which can come from either x-ray crystal structure or molecular docking. The structural modifications in LEADOPT mainly include two operations: fragment growing and fragment replacing, which are restricted to carry out in the active pocket of target protein with the core scaffold structure of ligand kept

Acknowledgments

This work was supported by the 973 Program (2013CB967204), the 863 Hi-Tech Programs (2012AA020301, 2012AA020308), the National Natural Science Funds for Distinguished Young Scholar (81325021), the National S&T Major Project (2012ZX09501001-003), and partly by PCSIRT (NO: IRT13031).

References (46)

L.M. Mayr et al.
Novel trends in high-throughput screening
Curr. Opin. Pharmacol.
(2009)
C. McInnes
Virtual screening strategies in drug discovery
Curr. Opin. Chem. Biol.
(2007)
L.-L. Yang et al.
Discovery of N6-phenyl-1H-pyrazolo[3,4-d]pyrimidine-3,6- diamine derivatives as novel CK1 inhibitors using common-feature pharmacophore model based virtual screening and hit-to-lead optimization
Eur. J. Med. Chem.
(2012)
A. Politi et al.
Application of 3D QSAR CoMFA/CoMSIA and in silico docking studies on novel renin inhibitors against cardiovascular diseases
Eur. J. Med. Chem.
(2009)
C. Abad-Zapatero et al.
Ligand efficiency indices as guideposts for drug discovery
Drug Discov. Today
(2005)
S.Y. Yang et al.
An integrated scheme for feature selection and parameter setting in the support vector machine modeling and its application to the prediction of pharmacokinetic properties of drugs
Artif. Intell. Med.
(2009)
H. Zhang et al.
In silico prediction of mitochondrial toxicity by using GA-CG-SVM approach
Toxicol. Vitro
(2009)
H. Zhang et al.
Three-class classification models of logS and logP derived by using GA-CG-SVM approach
Mol. Divers.
(2009)
C.Y. Ma et al.
Prediction models of human plasma protein binding rate and oral bioavailability derived by using GA-CG-SVM method
J. Pharm. Biomed. Anal.
(2008)
A. Puissant et al.
SYK is a critical regulator of FLT3 in acute myeloid leukemia
Cancer Cell
(2014)

T. Kenakin

Predicting therapeutic value in the lead optimization phase of drug discovery

Nat. Rev. Drug Discov.

(2003)

G.M. Keseru et al.

The influence of lead discovery strategies on the properties of drug candidates

Nat. Rev. Drug Discov.

(2009)

C.W. Murray et al.

The rise of fragment-based drug discovery

Nat. Chem.

(2009)

J.P. Kennedy et al.

Application of combinatorial chemistry science on modern drug discovery

J. Comb. Chem.

(2008)

U. Rester

From virtuality to reality – virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective

Curr. Opin. Drug Discov. Devel.

(2008)

V.M. Popov et al.

Towards in silico lead optimization: scores from ensembles of protein/ligand conformations reliably correlate with biological activity

Proteins

(2007)

W.L. Jorgensen

Efficient drug lead discovery and optimization

Acc. Chem. Res.

(2009)

R.D. Cramer et al.

Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins

J. Am. Chem. Soc.

(1988)

G. Klebe et al.

Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity

J. Med. Chem.

(1994)

C.L. Kuo et al.

Application of CoMFA and CoMSIA 3D-QSAR and docking studies in optimization of mercaptobenzenesulfonamides as HIV-1 integrase inhibitors

J. Med. Chem.

(2004)

B.M. Baron et al.

CoMFA, synthesis, and pharmacological evaluation of (E)-3-(2-carboxy-2-arylvinyl)-4,6-dichloro-1H-indole-2-carboxylic acids: 3-[2-(3-aminophenyl)-2-carboxyvinyl]-4,6-dichloro-1H-indole-2-carboxylic acid, a potent selective glycine-site NMDA receptor antagonist

J. Med. Chem.

(2005)

B. Wendt et al.

Toluidinesulfonamide hypoxia-induced factor 1 inhibitors: alleviating drug-drug interactions through use of PubChem data and comparative molecular field analysis guided synthesis

J. Med. Chem.

(2011)

S. Sartini et al.

Structure-based optimization of tyrosine kinase inhibitor CLM3. Design, synthesis, functional evaluation and molecular modeling studies

J. Med. Chem.

(2014)

Cited by (22)

Discovery of 3,4-dihydropyrimido[4,5-d]pyrimidin-2(1H)-one and 3,4-dihydropyrido[2,3-d]pyrimidin-2(1H)-one derivatives as novel ENPP1 inhibitors
2022, Bioorganic and Medicinal Chemistry Letters
Ectonucleotide pyrophosphatase/phosphodiesterase-1 (ENPP1) negatively regulates the anti-cancer Stimulator of Interferon Genes (STING) pathway. We discovered that 3,4-dihydropyrimido[4,5-d]pyrimidin-2(1H)-one and 3,4-dihydropyrido[2,3-d]pyrimidin-2(1H)-one derivatives possessed inhibitory activities on ENPP1. A structure–activity relationship (SAR) study led to the identification of 46 and 23 as potent ENPP1 inhibitors. Also, compounds 46 and 23 possessed high microsomal stabilities in human, rat, and mouse liver microsome. Additionally, CYPs (1A2, 2C9, 2C19, 2D6, and 3A4) were not inhibited by 46 and 23. Molecular dynamics simulations provided an insight of binding modes between ENPP1 and compounds (46 and 23).
Synthesis and biological evaluation of diaryl urea derivatives designed as potential anticarcinoma agents using de novo structure-based lead optimization approach
2020, European Journal of Medicinal Chemistry
Citation Excerpt :
Additionally the unpredictable pharmacokinetic properties and adverse side effects like fatigue, anemia, diarrhea, hypertension and hand-foot skin reaction [10] affect its clinical efficacy [11,12]. Discovery of new chemical entities (NCEs) as a focal point in drug research and development (R&D) includes lead discovery and optimization [13]. Lead discovery may be achieved by large-scale screening of chemical libraries or simply by chance.
To develop inhibitors blocking VEGFR2 and the Raf/MEK/ERK mitogen-activated protein kinase signaling pathway new compounds based on sorafenib were designed, synthesized and biologically evaluated. Using de novo design method, a library of new ligands was generated and expanded. Considering in silico binding affinity towards VEGFR2, synthetic feasibility, and drug-likeness property, some of the designed ligands were selected for synthesis and screening for their in vitro antiproliferative activities against two cancer cell lines (HT-29 and A549). Four compounds (13a, 14a, 14l and 15b) exhibited stronger antiproliferative activity (with IC₅₀ values of 13.27, 6.62, 12.74, 3.38 μM, respectively) against HT-29 cells compared to that of the positive reference drug sorafenib (IC₅₀ = 17.28 μM). Notably, compound 15b demonstrated the highest activity, and in particular, it induced HT-29 apoptosis, increased intracellular reactive oxygen species level, arrested cell cycle at G0/G1 phase, and influenced the expression of apoptosis- and cell cycle-related proteins. 15b compound can effectively block the Raf/MEK/ERK pathway and inhibit VEGFR2 phosphorylation. Molecular docking revealed that 15b can bind well to the active site of VEGFR2 receptor. Collectively, 15b may be considered as a promising compound amenable for further investigation for the development of new anticancer agents.
New techniques and strategies in drug discovery
2020, Chinese Chemical Letters
Great success has been witnessed in last decades, some new techniques and strategies have been widely used in drug discovery. In this roadmap, several representative techniques and strategies are highlighted to show recent advances in this filed. (A) A DOX protocol has been developed for accurate protein-ligand binding structure prediction, in which first principle method was used to rank the binding poses. Validation against crystal structures have found that DOX prediction achieved an impressive success rate of 99%, indicating significant improvement over molecular docking method. (B) Virtual target profiling is a compound-centric strategy enabling a parallel implementation of interrogating compounds against various targets in a single screen, which has been used in hit/lead identification, drug repositioning, and mechanism-of-action studies. Current and emerging methods for virtual target profiling are briefly summarized herein. (C) Research on targeted autophagy to treat diseases has received encouraging progress. However, due to the complexity of autophagy and disease, experimental and in silico methods should be performed synergistically for the entire process. This part focuses on in silico methods in autophagy research to promote their use in medicinal research. (D) Histone deacetylases (HDACs) play important roles in various biological functions through the deacetylation of lysine residues. Recent studies demonstrated that HDACs, which possess low deacetylase activities, exhibited more efficient defatty-acylase activities. Here, we review the defatty-acylase activity of HDACs and describe examples for the design of isoform selective HDAC inhibitor. (E) The FDA approval of three kinase allosteric inhibitors and some others entering clinical study has spurred considerable interests in this targeted drug discovery area. (F) Recent advances are reviewed in structure-based design of novel antiviral agents to combat drug resistance. (G) Since nitric oxide (NO) exerts anticancer activity depending on its concentration, optimal levels of NO in cancer cells is desirable. In this minireview, we briefly describe recent advances in the research of NO-based anticancer agents by our group and present some opinions on the future development of these agents. (H) The field of photoactivation strategies have been extensively developed for controlling chemical and biological processes with light. This review will summarize and provide insight into recent research advances in the understanding of photoactivatable molecules including photoactivatable caged prodrugs and photoswitchable molecules.
X-ray crystal structure guided discovery of new selective, substrate-mimicking sirtuin 2 inhibitors that exhibit activities against non-small cell lung cancer cells
2018, European Journal of Medicinal Chemistry
Citation Excerpt :
Notably, aminothiazoles and thienopyrimidinones were discovered as new types of selective SIRT2 inhibitors, which work via inducing the formation of an allosteric hydrophobic binding pocket, hence providing new insights into inhibitor design [21–24]. With the aid of LEADOPT [25], an automatic structure-based molecule design tool, we successfully identified the N-(3-(phenoxymethyl)phenyl)acetamide derivatives (Fig. 1b and Fig. S2) as selective SIRT2 inhibitors, which exhibited inhibitory activity against human breast cancer cell growth [26]. Here we describe the X-ray crystal structure guided structure-activity relationship (SAR) studies of new N-(3-(phenoxymethyl)phenyl)acetamide derivatives and their activities against non-small cell lung cancer.
Human sirtuin 2 (SIRT2) is a nicotinamide adenine dinucleotide (NAD⁺)-dependent deacylase, and is implicated in human diseases including cancer. Selective small-molecule inhibitors for SIRT2 are sought as chemical tools and potential therapeutics. Here we report the X-ray crystal structure guided structure-activity relationship studies of new N-(3-(phenoxymethyl)phenyl)acetamide derivatives with SIRT2, which led to the identification of potent, selective SIRT2 inhibitors. Crystallographic analyses reveal that the new inhibitors act via inducing the formation of an enlarged hydrophobic pocket and particularly mimicking the interactions made by myristoylated-lysine substrates. The most potent inhibitor 24a could dose-dependently elevate the acetylation level of α-tubulin in the non-small cell lung cancer H441 cells, which have a high expression level of SIRT2 as determinated by Western blotting analyses. Further cellular assays reveal that 24a restrains cell growth mainly through inhibiting cellular proliferation rather than inducing apoptosis. Moreover, 24a could suppress the migration and invasion of H441 cells. These results provide an excellent basis for further development of new potent, selective, and cell active SIRT2 inhibitors as chemical tools and potential therapeutics for SIRT2-driven non-small cell lung cancers.
Structure-based discovery of new maternal embryonic leucine zipper kinase inhibitors
2018, Organic and Biomolecular Chemistry
Maternal embryonic leucine zipper kinase (MELK), a serine/threonine protein kinase, has oncogenic properties and plays a key functional role in various cancer cells. Although MELK may not be a cancer addiction target, the development of specific MELK inhibitors would provide useful chemical tools for synthetic lethal investigation. Herein, we identified several hit compounds using a customized structure-based virtual screening, among which compounds 4 and 16 showed the most potent inhibition to MELK with IC₅₀ values of 3.52 μM and 178.3 nM, respectively. In vitro cell-based assays revealed that 16 has no effect on the growth of various types of cancer cells, but has the potential to inhibit cancer cell migration and invasion. Western blotting analyses revealed that 16 suppresses the phosphorylation of focal adhesion kinase (FAK), a downstream molecule of MELK, which is a key kinase in regulating cancer cell migration and invasion.
Total Synthesis and Evaluation of B-Homo Palmatine and Berberine Derivatives as p300 Histone Acetyltransferase Inhibitors
2018, European Journal of Organic Chemistry
Palmatine and berberine, structurally similar isoquinoline alkaloids exhibiting a broad range of biological activities, were recently found to inhibit p300 histone acetyltransferase (HAT), a potential therapeutic target for treating transcriptional activator‐driven malignancies and diseases. Here, we report the first total synthesis of B‐homo palmatine (11a) and berberine (11b) derivatives, which were synthesized from 3,4‐dimethoxybenzaldehyde (1a) and benzo[d][1,3]dioxole‐5‐carbaldehyde (1b) in nine steps in 13.8 and 16.9 % overall yields, respectively. A number of other new B‐homo palmatine and berberine derivatives were also prepared. These derivatives display good inhibitory activity against p300 HAT; compound 12a manifests the most potent inhibition with an IC₅₀ value of 0.42 µm. Cell‐based assays revealed that 12a exhibits certain inhibitory activity against HCG27, HT1080, and Z‐138 cell lines, and no visible activity towards other cancer cell lines tested, reflecting that 12a has low cytotoxicity and acts against some types of cancer cells.

View all citing articles on Scopus

¹: These authors contributed equally to this work.

View full text

Original articleLEADOPT: An automatic tool for structure-based lead optimization, and its application in structural optimizations of VEGFR2 and SYK inhibitors

Highlights

Abstract

Graphical abstract

Introduction

Section snippets

Fragment library construction

Development of LEADOPT

Concluding remarks

Acknowledgments

Curr. Opin. Pharmacol.

Curr. Opin. Chem. Biol.

Eur. J. Med. Chem.

Eur. J. Med. Chem.

Drug Discov. Today

Artif. Intell. Med.

Toxicol. Vitro

Mol. Divers.

J. Pharm. Biomed. Anal.

Cancer Cell

Predicting therapeutic value in the lead optimization phase of drug discovery

Nat. Rev. Drug Discov.

The influence of lead discovery strategies on the properties of drug candidates

Nat. Rev. Drug Discov.

The rise of fragment-based drug discovery

Nat. Chem.

Application of combinatorial chemistry science on modern drug discovery

J. Comb. Chem.

From virtuality to reality – virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective

Curr. Opin. Drug Discov. Devel.

Towards in silico lead optimization: scores from ensembles of protein/ligand conformations reliably correlate with biological activity

Proteins

Efficient drug lead discovery and optimization

Acc. Chem. Res.

Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins

J. Am. Chem. Soc.

Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity

J. Med. Chem.

Application of CoMFA and CoMSIA 3D-QSAR and docking studies in optimization of mercaptobenzenesulfonamides as HIV-1 integrase inhibitors

J. Med. Chem.

CoMFA, synthesis, and pharmacological evaluation of (E)-3-(2-carboxy-2-arylvinyl)-4,6-dichloro-1H-indole-2-carboxylic acids: 3-[2-(3-aminophenyl)-2-carboxyvinyl]-4,6-dichloro-1H-indole-2-carboxylic acid, a potent selective glycine-site NMDA receptor antagonist

J. Med. Chem.

Toluidinesulfonamide hypoxia-induced factor 1 inhibitors: alleviating drug-drug interactions through use of PubChem data and comparative molecular field analysis guided synthesis

J. Med. Chem.

Structure-based optimization of tyrosine kinase inhibitor CLM3. Design, synthesis, functional evaluation and molecular modeling studies

J. Med. Chem.

Original article
LEADOPT: An automatic tool for structure-based lead optimization, and its application in structural optimizations of VEGFR2 and SYK inhibitors