Papers by Rajan Chaudhari
It pays to ask: strategies to enhance the postdoctoral experience at MD Anderson Cancer Center
Expert Opinion on Drug Discovery
Introduction: In recent years, computational polypharmacology has gained significant attention to... more Introduction: In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success. Areas covered: In this article, the authors provide a comprehensive update on the current state-of-theart polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies. Expert opinion: Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multiomics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.
Chemical Science
SUPR peptide mRNA display was used to evolve a cell-permeable, macrocyclic peptide for autophagy ... more SUPR peptide mRNA display was used to evolve a cell-permeable, macrocyclic peptide for autophagy inhibition.
Conversion of RNA Aptamer into Modified DNA Aptamers Provides for Prolonged Stability and Enhanced Antitumor Activity
Journal of the American Chemical Society
Aptamers, synthetic single-strand oligonucleotides that are similar in function to antibodies, ar... more Aptamers, synthetic single-strand oligonucleotides that are similar in function to antibodies, are promising as therapeutics because of their minimal side effects. However, the stability and bioavailability of the aptamers pose a challenge. We developed aptamers converted from RNA aptamer to modified DNA aptamers that target phospho-AXL with improved stability and bioavailability. On the basis of the comparative analysis of a library of 17 converted modified DNA aptamers, we selected aptamer candidates, GLB-G25 and GLB-A04, that exhibited the highest bioavailability, stability, and robust antitumor effect in in vitro experiments. Backbone modifications such as thiophosphate or dithiophosphate and a covalent modification of the 5'-end of the aptamer with polyethylene glycol optimized the pharmacokinetic properties, improved the stability of the aptamers in vivo by reducing nuclease hydrolysis and renal clearance, and achieved high and sustained inhibition of AXL at a very low dose. Treatment with these modified aptamers in ovarian cancer orthotopic mouse models significantly reduced tumor growth and the number of metastases. This effective silencing of the phospho-AXL target thus demonstrated that aptamer specificity and bioavailability can be improved by the chemical modification of existing aptamers for phospho-AXL. These results lay the foundation for the translation of these aptamer candidates and companion biomarkers to the clinic.
Overview of Drug Polypharmacology and Multitargeted Molecular Design
Comprehensive Medicinal Chemistry III
The “one drug, one target, and one disease” model is partially contributing to the increased fail... more The “one drug, one target, and one disease” model is partially contributing to the increased failures of clinical trials due to its lacking consideration of side effects or toxicities in the early stage of drug discovery and development. To tackle this issue, an alternative approach is being adopted to study simultaneous interactions of small molecules with multiple specific targets, also known as polypharmacology. It allows exploration of drug multitargeting activities and facilitates potential repositioning. Although exhaustive polypharmacology studies in vitro or in vivo is not practical, computational methods are being developed and have significantly driven the field forward. In this article, we discuss the status of drug polypharmacology and review the current state-of-the-art in silico methods that are used for rational design of multitargeted therapeutics to treat complex diseases such as cancer.
Members of our early career panel highlight key research articles on the theme of computer-aided drug design
Future Drug Discovery
MotivationAccurate prediction of drug response in each patient is the holy grail in personalized ... more MotivationAccurate prediction of drug response in each patient is the holy grail in personalized medicine. Recently, deep learning techniques have been witnessed with revival in a variety of areas such as image processing and genomic data analysis, and they will be useful for the coming age of big data analysis in pharmaceutical research and chemogenomic applications. This provides us an impetus to develop a novel deep learning platform to accurately and reliably predict the response of cancer to different drug treatments.ResultsIn this study, we describe a Java-based implementation of deep neural network (DNN) method, termed JavaDL, to predict cancer responses to drugs solely based on their chemical features. To this end, we devised a novel cost function by adding a regularization term which suppresses overfitting. We also adopted an “early stopping” strategy to further reduce overfit and improve the accuracy and robustness of our models. Currently the software has been integrated ...
Abstract 122: Targeting forward and reverse EphB4/EFNB2 signaling by a peptide with dual functions
Immunology
Although chloroquine administration in vivo following haemorrhage in mice decreases tumour necros... more Although chloroquine administration in vivo following haemorrhage in mice decreases tumour necrosis factor-alpha (TNF-alpha) release by macrophage (M phi), the mechanism remains unknown. To study this, peritoneal M phi (pM phi) from unmanipulated, sham-operated and post-haemorrhage mice were isolated, treated with 0.13 mg/ml chloroquine for 2 hr, and then stimulated with lipopolysaccharide (LPS) for 48 hr. Pretreatment of pM phi from various groups of mice with chloroquine resulted in 75-90% inhibition of TNF-alpha release, determined by bioassay. Total RNA was isolated from pM phi and murine M phi-derived cell lines (P388D1 and RAW 264.7), stimulated with LPS for 0.5 or 1 hr, respectively, and Northern blot analysis for TNF-alpha mRNA performed. Chloroquine inhibited TNF-alpha mRNA expression without interfering with mRNA stability, suggesting that this agent reduces M phi TNF-alpha release by disrupting TNF-alpha gene transcription.
Scientific Reports
The tyrosine kinase receptor EphB4 is frequently overexpressed in ovarian and other solid tumors ... more The tyrosine kinase receptor EphB4 is frequently overexpressed in ovarian and other solid tumors and is involved in interactions between tumor cells and the tumor microenvironment, contributing to metastasis. Trans-interaction between EphB4 and its membrane-bound ligand ephrin B2 (EFNB2) mediates bi-directional signaling: forward EFNB2-to-EphB4 signaling suppresses tumor cell proliferation, while reverse EphB4-to-EFNB2 signaling stimulates the invasive and angiogenic properties of endothelial cells. Currently, no small molecule–based, dual-function, EphB4-binding peptides are available. Here, we report our discovery of a bi-directional ephrin agonist peptide, BIDEN-AP which, when selectively internalized via receptor-mediated endocytosis, suppressed invasion and epithelial-mesenchymal transition of ovarian cancer cells. BIDEN-AP also inhibited endothelial migration and tube formation. In vivo, BIDEN-AP and its nanoconjugate CCPM-BIDEN-AP significantly reduced growth of orthotopic ov...
Abstract 368: Next generation DNA aptamers with prolonged stability and antitumor activity
Experimental and Molecular Therapeutics
Aberrations in Gas6/AXL signaling is associated with many human diseases including ovarian cancer... more Aberrations in Gas6/AXL signaling is associated with many human diseases including ovarian cancer, where in patients expressing high levels of AXL have shorter overall survival than patients expressing low levels. Aptamers are short synthetic oligonucleotides (DNA or RNA) that can bind with highest specificity to various other macromolecules such as peptides, proteins and carbohydrates, based on their tertiary structures. Aptamers are similar in their functionality to antibodies in their specificity; easier to manufacture than antibodies; have minimal side effects; and thus hold a high promise as therapeutics. The typical issues with the use of aptamers as therapeutic agents are their selectivity, stability, and bioavailability. We present the development of the next generation DNA aptamers, targeting p-AXL specifically to as a therapeutic in ovarian cancer (OC) by chemical modifications to their primary sequence. Improved bioavailability and stability, based on the comparative analysis the library of 17 DNA aptamers that differed in the position and number of fluoro- and thio- modifications on their nucleotide sequence, were used as the criteria for the selection and characterization of the best aptamer candidates to target p-AXL. Two of the best candidates, GLB-G25 and GLB-A04 thus chosen with the highest bioavailability and stability, when tested in ovarian cancer cell lines, decreased the migration and invasion of cells in vitro. Treatment of ovarian cancer orthotopic murine model animals with modified DNA aptamer candidates chosen above significantly reduced tumor growth and the number of metastases. The candidates, GLB-G25 and GLB-A04 show highest potential to be developed into therapeutics to target p-AXL that is elevated in several cancers including ovarian cancer. Note: This abstract was not presented at the meeting. Citation Format: Paola AMERO, Cristian Rodriguez-Aguayo, Rajan R. Chaudhari, Shuxing Zhang, Anil K. Sood, Gabriel Lopez-Berestein. Next generation DNA aptamers with prolonged stability and antitumor activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 368.
Abstract 1854: Novel pateamine analogs to target the translation initiation factor eIF4A in chronic lymphocytic leukemia
Cancer Chemistry
Leukemia
This study analyses the Active Citizens program conducted in seven Czech elementary schools in 20... more This study analyses the Active Citizens program conducted in seven Czech elementary schools in 2017/2018. The data were obtained in a mixed-design research study containing pre/post experimental/control groups (N = 114), eight focus groups with selected students (N = 56), and group interviews with teachers (N = 14). The mean age of the students was 13.8 years. The study focuses on the students' and the teachers' perception of the process, the program's barriers and benefits, and on the impact of the program on the students' self-efficacy and on perceived democratic school culture. The analysis revealed that while the participants felt empowered because of their experience, they started to perceive their school environment as less democratic than before the program. The program also likely influenced girls more than boys as the latter seem to have been unaffected. Finally, the implications of the findings for the practice are discussed.
ACS Omega
The glucagon-like peptide 1 receptor (GLP-1R) belongs to the pharmaceutically important class B f... more The glucagon-like peptide 1 receptor (GLP-1R) belongs to the pharmaceutically important class B family of Gprotein-coupled receptors (GPCRs), and its incretin peptide ligand GLP-1 analogs are adopted drugs for the treatment of type 2 diabetes. Despite remarkable antidiabetic effects, GLP-1 peptide-based drugs are limited by the need of injection. On the other hand, developing nonpeptidic small-molecule drugs targeting GLP-1R remains elusive. Here, we first constructed a threedimensional structure model of the transmembrane (TM) domain of human GLP-1R using homology modeling and conformational sampling techniques. Next, a potential allosteric binding site on the TM domain was predicted computationally. In silico screening of druglike compounds against this predicted allosteric site has identified nine compounds as potential GLP-1R agonists. The independent agonistic activity of two compounds was subsequently confirmed using a cAMP response element-based luciferase reporting system. One compound was also shown to stimulate insulin secretion through in vitro assay. In addition, this compound synergized with GLP-1 to activate human GLP-1R. These results demonstrated that allosteric regulation potentially exists in GLP-1R and can be exploited for developing small-molecule agonists. The success of this work will help pave the way for small-molecule drug discovery targeting other class B GPCRs through allosteric regulations.
Bioconjugate chemistry, Jan 19, 2018
Quantitative imaging of apoptosis in vivo could enable real-time monitoring of acute cell death p... more Quantitative imaging of apoptosis in vivo could enable real-time monitoring of acute cell death pathologies such as traumatic brain injury, as well as the efficacy and safety of cancer therapy. Here, we describe the development and validation of F-18-labeled caspase-3 substrates for PET/CT imaging of apoptosis. Preliminary studies identified the O-benzylthreonine-containing substrate 2MP-TbD-AFC as a highly caspase 3-selective and cell-permeable fluorescent reporter. This lead compound was converted into the radiotracer [F]-TBD, which was obtained at 10% decay-corrected yields with molar activities up to 149 GBq/μmol on an automated radiosynthesis platform. [F]-TBD accumulated in ovarian cancer cells in a caspase- and cisplatin-dependent fashion. PET imaging of a Jo2-induced hepatotoxicity model showed a significant increase in [F]-TBD signal in the livers of Jo2-treated mice compared to controls, driven through a reduction in hepatobiliary clearance. A chemical control tracer that ...
Computational polypharmacology: a new paradigm for drug discovery
Expert Opinion on Drug Discovery
ABSTRACT Introduction: Over the past couple of years, the cost of drug development has sharply in... more ABSTRACT Introduction: Over the past couple of years, the cost of drug development has sharply increased along with the high rate of clinical trial failures. Such increase in expenses is partially due to the inability of the “one drug – one target” approach to predict drug side effects and toxicities. To tackle this issue, an alternative approach, known as polypharmacology, is being adopted to study small molecule interactions with multiple targets. Apart from developing more potent and effective drugs, this approach allows for studies of off-target activities and the facilitation of drug repositioning. Although exhaustive polypharmacology studies in-vitro or in-vivo are not practical, computational methods of predicting unknown targets or side effects are being developed. Areas covered: This article describes various computational approaches that have been developed to study polypharmacology profiles of small molecules. It also provides a brief description of the algorithms used in these state-of-the-art methods. Expert opinion: Recent success in computational prediction of multi-targeting drugs has established polypharmacology as a promising alternative approach to tackle some of the daunting complications in drug discovery. This will not only help discover more effective agents, but also present tremendous opportunities to study novel target pharmacology and facilitate drug repositioning efforts in the pharmaceutical industry.
Background: Tremendous amount of chemical and biological data are being generated by various hig... more Background: Tremendous amount of chemical and biological data are being generated by various high-throughput biotechnologies that could facilitate modern drug discovery. However, lack of integration makes it very challenging for individual scientists to access and understand all the data related to a specific protein of interest.
Findings: To overcome this challenge, we developed PyMine, a PyMOL plugin that retrieves chemical, structural, pathway and other related biological data of a receptor and small molecules from a variety of high-quality databases and presents them in a graphic and uniformed way.
Conclusions: Developed as an interactive and user-friendly tool, PyMine can be used as a central data-hub for users to access and visualize multiple types of data and to generate new ideas intuitively for structure-based molecule design.
Keywords: PyMOL, Data integration, Data visualization, Drug discovery
Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions
Journal of Computer-Aided Molecular Design, 2014
Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving ... more Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of "modeling first, refinement next". In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β2 adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of "refined restraints first, modeling next", provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins.
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Papers by Rajan Chaudhari
Findings: To overcome this challenge, we developed PyMine, a PyMOL plugin that retrieves chemical, structural, pathway and other related biological data of a receptor and small molecules from a variety of high-quality databases and presents them in a graphic and uniformed way.
Conclusions: Developed as an interactive and user-friendly tool, PyMine can be used as a central data-hub for users to access and visualize multiple types of data and to generate new ideas intuitively for structure-based molecule design.
Keywords: PyMOL, Data integration, Data visualization, Drug discovery