Effects of vinblastine and its metabolites on nausea and alopecia associated receptors

The effects of vinblastine (VLB) and its thirty-five known metabolites were investigated on nausea and alopecia associated receptors by means of molecular docking simulations. The in silico pharmacokinetics (PK) properties and binding affinities of VLB and its metabolites with the vinca site of tubulin were also elucidated in the present study. VLB and its metabolites have demonstrated binding affinities mainly for the muscarinic receptors M₁, M₄ and M₅ that display significant roles in the onset of nausea during chemotherapy. The metabolites of VLB interact with the binding site of acetylcholine and share similar binding interactions with residues involved with the endogenous substrate. Furthermore, VLB metabolites have also shown binding affinities for alopecia associated receptors such as vitamin D (VDR), androgen, smoothened and MDM2, which can trigger the death of hair follicle following cancer treatment. The predicted PK properties of VLB and its metabolites have revealed that they are all substrates and inhibitors of CYP3A4 and P-glycoprotein, and inhibitors of CYP2D6. The majority of metabolites do not cross the blood-brain barrier, do not undergo glucuronidation and have no affinity for the human ether-à-go-go-related gene receptor. Finally, VLB metabolites docked into the vinca site of tubulin have revealed that metabolites 8, 10 and 11 have binding affinities for tubulin and interact with the same residues involved with VLB. Taking into account the PK properties, metabolite 10 (20-Hydroxy-VLB) has shown to be a potential active analog of VLB. This research project has aimed to a better understanding of the VLB-induced off-targets events such as nausea and alopecia, and how the VLB metabolites can trigger these ADRs. These findings suggest that knowing which and how the metabolites of VLB are involved with off-targets receptors of nausea and alopecia, as well as their PK properties and effects on tubulin target, ADRs during chemotherapy could be eliminated or lessened. This is possible if modifications on the chemical structure of VLB and advances in drug discovery and medicinal chemistry fields are taken into consideration in future studies. It would enhance target specificity as it could decrease formation of many metabolites and hence minimize the number of off-target interactions. That could result in providing a less unpleasant treatment for cancer patients and a higher quality of life during chemotherapy

In silico approaches for drug repurposing in oncology: a scoping review

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology.Methods: The scoping review was conducted according to the Arksey and O’Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021.Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies.Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications

Drug Discovery

Natural products are a constant source of potentially active compounds for the treatment of various disorders. The Middle East and tropical regions are believed to have the richest supplies of natural products in the world. Plant derived secondary metabolites have been used by humans to treat acute infections, health disorders and chronic illness for tens of thousands of years. Only during the last 100 years have natural products been largely replaced by synthetic drugs. Estimates of 200 000 natural products in plant species have been revised upward as mass spectrometry techniques have developed. For developing countries the identification and use of endogenous medicinal plants as cures against cancers has become attractive. Books on drug discovery will play vital role in the new era of disease treatment using natural products

Establishing a Biophysical Assay for the Interactions of Calcitonin Family G Protein-Coupled Receptors with Receptor Activity Modifying Proteins And The Elucidation of the Structure-Based Signalling of G Protein-Coupled Receptors via the Novel Application of Geometric Morphometrics With Principal Component Analysis

GPCRs are implicated in a wide variety of diseases, making them particularly attractive drug targets; critical developments in structural and functional techniques have led to breakthrough discoveries, shifting paradigms of understanding with novel concepts. Select ligands are now known to induce biased signalling in GPCRs, differentially activating intracellular signalling pathways; conformational landscapes of GPCRs are heterogeneous, indicating diversity in the activation transition and intermediate states which likely correlate with biased signalling. Moreover, the majority of GPCRs signal via more than one G protein sub-type, preferentially coupling with ranked selectivity, and are allosterically modulated by a range of factors. In order to develop safe, effective and selective therapeutics against GPCRs, a holistic understanding of these concepts necessitates comprehensive, multidisciplinary approaches, combining enhanced biophysical and biochemical assays, determination and analyses of structure, and complementary computational techniques. This thesis presents the successful establishment of a FRET-based interaction assay for the calcitonin family of GPCRs and the RAMPs, with an average FRET efficiency of 87.78%, average interaction distance of 3.42 nm, and cAMP pEC50s in agreement with the literature. This promising assay will offer novel insights into GPCR-RAMP dynamics, forming the basis of a high-throughput biophysical drug discovery platform. Secondly, the structure-based signalling of GPCRs was explored with the novel application of geometric morphometrics and principal component analysis to resolved structures, consistently and reliably classifying GPCRs by their global shape morphology, supported by PERMANOVA and ANOSIM multivariate statistics. Case study examples of the β2-adrenergic, adenosine 2A, secretin-like and calcium-sensing receptors first proved this concept effective, before exploration of thermostabilisation, fusion proteins, the structural determinants of G protein coupling, and AlphaFold structures. Overall, this thesis provides novel contributions to fully elucidating the structure/function relationship of GPCRs, building a multidisciplinary model of understanding, which will enable the unprecedented discovery and development of safe, effective therapeutics

Prediction of Structure of Human WNT-CRD (FZD) Complex for Computational Drug Repurposing

<div><p>The observed genetic alterations of various extracellular and intracellular WNT (<em>Wingless</em>, <em>Int-1</em> proto-oncogene) signaling components can result in an increase or decrease in gene expression, and hence can be obstructed proficiently. These genetics target sites may include the prevention of WNT-FZD (Frizzled) binding, destruction of <em>β-catenin</em> and formation of <em>Axin</em>, <em>APC</em> and <em>GSK-3β</em> complex. Hence, the localized targeting of these interacting partners can help in devising novel inhibitors against WNT signaling. Our present study is an extension of our previous work, in which we proposed the co-regulated expression pattern of the WNT gene cluster (WNT-1, WNT-6, WNT-10A and WNT-10B) in human breast carcinoma. We present here the computationally modeled three dimensional structure of human WNT-1 in complex with the FZD-1 CRD (Cysteine Rich Domain) receptor. The dimeric cysteine-rich domain was found to fit into the evolutionarily conserved U-shaped groove of WNT protein. The two ends of the U- shaped cleft contain N-terminal and C-terminal hydrophobic residues, thus providing a strong hydrophobic moiety for the frizzled receptor and serving as the largest binding pocket for WNT-FZD interaction. Detailed structural analysis of this cleft revealed a maximum atomic distance of ∼28 Å at the surface, narrowing down to ∼17 Å and again increasing up to ∼27 Å at the bottom. Altogether, structural prediction analysis of WNT proteins was performed to reveal newer details about post-translational modification sites and to map the novel pharmacophore models for potent WNT inhibitors.</p> </div