Current Drug Discovery Research Articles

Targeted Therapy in Breast Cancer: Advantages and Advancements of Antibody-Drug Conjugates, a Type of Chemo-Biologic Hybrid Drugs.

Cancer is a significant health challenge globally, with millions of people affected every year, resulting in high morbidity and mortality. Although other treatment options are available with limitations, chemotherapy, either standalone or combined with other therapeutic procedures, is the most commonly used practice of treating cancer. In chemotherapy, cancer cells/malignant tumors are targeted; however, due to less target specificity, along with malignant cells, normal cells are also affected, which leads to various off-target effects (side effects) that impact the patient quality of life. Out of all the different types of cancers, breast cancer is the most common type of cancer in humans worldwide. Current anticancer drug discovery research aims to develop therapeutics with higher potency and lower toxicity, which is only possible through target-specific therapy. Antibody-drug conjugates (ADCs) are explicitly designed to target malignant tumors and minimize off-target effects by reducing systemic cytotoxicity. Several ADCs have been approved for clinical use and have shown moderate to good efficacy so far. Considering various aspects, chemotherapy and ADCs are useful in treating cancer. However, ADCs provide a more focused and less toxic approach, which is especially helpful in cases where resistance to chemotherapy (drug resistance) occurs and in the type of malignancies in which specific antigens are overexpressed. Ongoing ADC research aims to develop more target-specific cancer treatments. In short, this study presents a concise overview of ADCs specific to breast cancer treatment. This study provides insight into the classifications, mechanisms of action, structural aspects, and clinical trial phases (current status) of these chemo-biologic drugs (ADCs).

Progress on the development of Class A GPCR-biased ligands.

Class A G protein-coupled receptors (GPCRs) continue to garner interest for their essential roles in cell signalling and their importance as drug targets. Although numerous drugs in the clinic target these receptors, over 60% GPCRs remain unexploited. Moreover, the adverse effects triggered by the available unbiased GPCR modulators, limit their use and therapeutic value. In this context, the elucidation of biased signalling has opened up new pharmacological avenues holding promise for safer therapeutics. Functionally selective ligands favour receptor conformations facilitating the recruitment of specific effectors and the modulation of the associated pathways. This review surveys the current drug discovery landscape of GPCR-biased modulators with a focus on recent advances. Understanding the biological effects of this preferential coupling is at different stages depending on the Class A GPCR family. Therefore, with a focus on individual GPCR families, we present a compilation of the functionally selective modulators reported over the past few years. In doing so, we dissect their therapeutic relevance, molecular determinants and potential clinical applications.

Exploring Tau Fibril-Disaggregating and Antioxidating Molecules Binding to Membrane-Bound Amyloid Oligomers Using Machine Learning-Enhanced Docking and Molecular Dynamics.

Intracellular tau fibrils are sources of neurotoxicity and oxidative stress in Alzheimer's. Current drug discovery efforts have focused on molecules with tau fibril disaggregation and antioxidation functions. However, recent studies suggest that membrane-bound tau-containing oligomers (mTCOs), smaller and less ordered than tau fibrils, are neurotoxic in the early stage of Alzheimer's. Whether tau fibril-targeting molecules are effective against mTCOs is unknown. The binding of epigallocatechin-3-gallate (EGCG), CNS-11, and BHT-CNS-11 to in silico mTCOs and experimental tau fibrils was investigated using machine learning-enhanced docking and molecular dynamics simulations. EGCG and CNS-11 have tau fibril disaggregation functions, while the proposed BHT-CNS-11 has potential tau fibril disaggregation and antioxidation functions like EGCG. Our results suggest that the three molecules studied may also bind to mTCOs. The predicted binding probability of EGCG to mTCOs increases with the protein aggregate size. In contrast, the predicted probability of CNS-11 and BHT-CNS-11 binding to the dimeric mTCOs is higher than binding to the tetrameric mTCOs for the homo tau but not for the hetero tau-amylin oligomers. Our results also support the idea that anionic lipids may promote the binding of molecules to mTCOs. We conclude that tau fibril-disaggregating and antioxidating molecules may bind to mTCOs, and that mTCOs may also be useful targets for Alzheimer's drug design.

NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics.

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.

Alcoholic Extracts of Eleusine indica as Alternative Diuretic Regimens: A Computational Based Investigation

Diuretics are widely used in current clinical practice to increase urine production and excrete electrolytes, particularly sodium and chloride ions, without affecting the absorption of protein, vitamins, carbohydrates, or amino acids. From the time of mercury chloride and organomercurials in ancient times to now (with sulphonamides, thiazides, and furosemide), a lot has changed in the field of diuretics. However, long-term use of such synthetic diuretic agents in clinical practice produces several adverse effects, such as blurred vision, loss of appetite, stomach upset, carcinomas, headaches, phototoxic impact, weakness., etc., as has been observed from recent investigations. Natural regimens can serve as potential alternatives to using nontoxic diuretic agents. Based on long-term ethnomedicinal and biological activity records, we have explored the diuretic effects of the widely known perennial herb in Pacific Islands regions and a weed in agricultural fields, Eleusine indica (L) Gaertn phytoconstituents, on a computation platform. Therefore, we conducted a bio-assay-guided crude extraction using ethanol, followed by further gas chromatography-mass spectrometry (GC-MS) analyses of the extracted crude extracts. Further selected nine constituents (EI_1 to EI_9) carried out the diuretic potency against three putative target enzymes (ACE, KCNJ1, and SLC12A1) along with three standard drugs (VU590, TSM, and FSM) through molecular docking studies using AutoDock 4.2 software. We also predict physicochemical profiles, or Lipinski Rule of Five profiles, toxicity, and pharmacokinetics using various bioinformatics and cheminformatics tools. Based on the overall investigation, it was revealed that EI_6 [Z, Z-6,28-Heptatriacontadien-2-one] was the most potential, nontoxic, and drug-able candidate. In summary, advanced computational tools play a crucial role in selecting potential preclinical candidates within limited resources to accelerate the current drug discovery process.

Digitalization of toxicology: improving preclinical to clinical translation.

Though the portfolio of medicines that are extending and improving the lives of patients continues to grow, drug discovery and development remains a challenging business on its best day. Safety liabilities are a significant contributor to development attrition where the costliest liabilities to both drug developers and patients emerge in late development or post-marketing. Animal studies are an important and influential contributor to the current drug discovery and development paradigm intending to provide evidence that a novel drug candidate can be used safely and effectively in human volunteers and patients. However, translational gaps-such as toxicity in patients not predicted by animal studies-have prompted efforts to improve their effectiveness, especially in safety assessment. More holistic monitoring and "digitalization" of animal studies has the potential to enrich study outcomes leading to datasets that are more computationally accessible, translationally relevant, replicable, and technically efficient. Continuous monitoring of animal behavior and physiology enables longitudinal assessment of drug effects, detection of effects during the animal's sleep and wake cycles and the opportunity to detect health or welfare events earlier. Automated measures can also mitigate human biases and reduce subjectivity. Reinventing a conservative, standardized, and traditional paradigm like drug safety assessment requires the collaboration and contributions of a broad and multi-disciplinary stakeholder group. In this perspective, we review the current state of the field and discuss opportunities to improve current approaches by more fully leveraging the power of sensor technologies, artificial intelligence (AI), and animal behavior in a home cage environment.

Abstract 1981: Profiling of protein interactome with cysteine-reactive libraries led to the discovery of EML4ALK dimerizers

Abstract Cysteine covalent binders enable direct interactions with previously deemed undruggable protein targets, revolutionizing cancer therapeutics development. The primary focus has been on tailoring single-warhead compounds to target specific cysteine residues within the functional domains of target proteins. However, the biochemical properties including dimerization, induced conformational changes, and interactome disruption have been underexplored, presenting an ongoing limitation in current drug discovery approaches. In this study, we generated a library of 32 cysteine-reactive warhead compounds using various combinations of scaffolds and warheads to represent diverse reactivities. A combinatory assay approach, including cysteine druggability mapping (CDM) to discover reactive residues and SDS-PAGE fractionation assays to identify disrupted protein interaction events, was employed. Characterization of the library revealed distinct reactive cysteines and dimerization profiles among the 32 unique compounds. Compound 1C9, identified as a lead compound, demonstrated significant dimerization of EML4, a common fusion gene partner in lung cancer. Using the EML4ALK fusion gene as a proof of concept, we explored potential mechanisms underlying the compound-induced dimerization of EML4. Subsequent structure-activity relationship (SAR) studies and screening of 70 additional compounds were conducted to optimize ALK dimerization and minimize off-target effects. The enhanced compound disrupted the ALK cellular signaling pathways AKT and ERK upon dimerization of the EML4ALK fusion gene. Additionally, we discovered that covalent dimerization induced EML4ALK degradation without requiring a ubiquitin ligase like a PROTAC. In conclusion, our work has uncovered a novel class of cysteine covalent binders, which we believe are valuable tools to modulate protein-protein interactions in previously undruggable proteins in cancer. This discovery holds significant therapeutic potential for future drug development. Citation Format: Diane Yang, Stefan Harry, Elizabeth Codd, Stefan T. Kaluziak, Alexander D. Carlin, Edwin Zhang, Zavontae Oppong-Holmes, Wenxin Yang, Abigail Smith, Dawn Mitchell, Mariko Hara, Siwen Zhang, Maristela Onozato, Liron Bar-Peled, Anthony J. Iafrate. Profiling of protein interactome with cysteine-reactive libraries led to the discovery of EML4ALK dimerizers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1981.

A Mini-Review on the Synthesis of Substituted Isatins: From Early Approaches to Recent Advances with a Specific Focus on Sulfamoyl and Amino Derivatives

Abstract: As a member of heterocyclic compounds, indole possesses a diverse set of biological activities. Studies on the structure-activity relationship of 2-indolinones have shown that they are important bioactive compounds in the field of pharmaceutical chemistry. Isatin and structures bearing isatin scaffold are derivatives of indole, which have shown to be of biological and pharmacological significance. This review focuses on different ways of obtaining compounds containing isatin structure, considering both earlier and recent methods of synthesis. The syntheses given herein were grouped into three categories, syntheses using anilines as their starting substance, synthetic methods based on the oxidation of indoles, and finally, due to the extensive research going on 5-substituted isatins and their possible pharmacological efficacy, pathways for synthesizing 5-amino and 5-sulfamoylisatins were gathered to underline the importance of 2-indolinone and isatin derivatives as prospective therapeutic compounds in current and future drug discovery studies.

Virtual Screening, Docking, and Designing of New VEGF Inhibitors as Anti-cancer Agents.

VEGFR-2 tyrosine kinase inhibitors are receiving a lot of attention as prospective anticancer medications in the current drug discovery process. This work aims to explore the PubChem library for novel VEGFR-2 kinase inhibitors. 1H-Indazole-containing drug AXITINIB, or AG-013736 (FDA approved), is chosen as a rational molecule for drug design. This scaffold proved its efficiency in treating cancer and other diseases as well. The present study used the virtual screening of the database, protein preparation, grid creation, and molecular docking analyses. The protein was validated on different parameters like the Ramachandran plot, the ERRAT score, and the ProSA score. The Ramachandran plot revealed that 92.1% of the amino acid residues were located in the most favorable region; this was complemented by an ERRAT score (overall quality factor) of 96.24 percent and a ProSA (Z score) of -9.24 percent. The Lipinski rule of five was used as an additional filter for screening molecules. The docking results showed values of binding affinity between -14.08 and -12.34 kcal/mol. The molecule C1 showed the highest docking value of -14.08 Kcal/mol with the maximum number of strong H-bonds by -NH of pyridine to amino acid Cys104 (4.22Å), -NH of indazole to Glu108 (4.72), and Glu70 to bridge H of -NH. These interactions are similar to Axitinib docking interactions like Glu70, Cys104, and Glu102. The docking studies revealed that pi-alkyl bonds are formed with unsubstituted pyridine, whereas important H-bonds are observed with different substitutions around -NH. Based on potential findings, we designed new molecules, and molecular docking studies were performed on the same protein along with ADMET studies. The designed molecules (M1-M4) also showed comparable docking results similar to Axitinib, along with a synthetic accessibility score of less than 4.5. The docking method employed in this work opens up new possibilities for the design and synthesis of novel compounds that can act as VEGFR-2 tyrosine kinase inhibitors and treat cancer.

Discovery of Novel NLRP3 Inflammasome Inhibitors Composed of an Oxazole Scaffold Bearing an Acylsulfamide.

The NLRP3 inflammasome plays an important role in the defense mechanism of the innate immune system and has recently attracted much attention as a drug target for various inflammatory disorders. Among the strategies for generating the novel chemotype in current drug discovery, scaffold hopping and bioisosteric replacement are known to be attractive approaches. As the results of our medicinal chemistry campaign, which involved exploration of core motifs using a ring closing approach, a five-membered oxazole-based scaffold was identified, and subsequent implementation of bioisosteric replacement led to discovery of a novel chemical class of NLRP3 inflammasome inhibitor bearing the acylsulfamide group. Further optimization of aniline and sulfamide moieties to improve potency in human whole blood assay led to the identification of the orally bioactive compound 32 in the LPS challenge model. Furthermore, compound 32 attenuated kidney injury in adriamycin-induced glomerulonephritis in mice. These investigations indicated that the NLRP3 inhibitor could be a potential therapeutic agent for glomerulonephritis.

ADCdb: the database of antibody-drug conjugates.

Antibody-drug conjugates (ADCs) are a class of innovative biopharmaceutical drugs, which, via their antibody (mAb) component, deliver and release their potent warhead (a.k.a. payload) at the disease site, thereby simultaneously improving the efficacy of delivered therapy and reducing its off-target toxicity. To design ADCs of promising efficacy, it is crucial to have the critical data of pharma-information and biological activities for each ADC. However, no such database has been constructed yet. In this study, a database named ADCdb focusing on providing ADC information (especially its pharma-information and biological activities) from multiple perspectives was thus developed. Particularly, a total of 6572 ADCs (359 approved by FDA or in clinical trial pipeline, 501 in preclinical test, 819 with in-vivo testing data, 1868 with cell line/target testing data, 3025 without in-vivo/cell line/target testing data) together with their explicit pharma-information was collected and provided. Moreover, a total of 9171 literature-reported activities were discovered, which were identified from diverse clinical trial pipelines, model organisms, patient/cell-derived xenograft models, etc. Due to the significance of ADCs and their relevant data, this new database was expected to attract broad interests from diverse research fields of current biopharmaceutical drug discovery. The ADCdb is now publicly accessible at: https://idrblab.org/adcdb/.

Triglyceride-filled albumin-based nanocapsules: A promising new system to avoid discarding poorly water-soluble drug candidates

Even though current drug discovery provides a variety of potential drug candidates, many of those substances are difficult to formulate due to their poor water-solubility. To overcome this obstacle a technological formulation is crucial. Albumin-based nanocarriers are a possible intravenous delivery system which is already approved and commercially available. However, no universal carrier for poorly water-soluble substances is found yet. In the present study, new preparation processes for nanocapsules consisting of a medium-chain triglyceride (MCT) core and a human serum albumin (HSA) shell were developed. The nanocarrier system exhibits desirable physicochemical properties with a hydrodynamic diameter of 150 nm and a polydispersity index of 0.1. Furthermore, the nanocapsules were stable towards the addition of electrolytes and also in basic to neutral pH range. The nanocapsules were storage stable for at least 7 months at 4 °C and could also be lyophilized to reach an even longer shelf life of at least 21 months. In addition, the nanocapsule system showed no cytotoxicity in cell culture. The developed system represents a suitable carrier for a variety of different poorly water-soluble drug substances (e.g., fenofibrate, naproxen, indomethacin) showing a high potential for a universal formulation platform for further lipophilic active pharmaceutical ingredients (APIs).

A Pillar and Perfusion Plate Platform for Robust Human Organoid Culture and Analysis.

Human organoids have the potential to revolutionize in vitro disease modeling by providing multicellular architecture and function that are similar to those in vivo. This innovative and evolving technology, however, still suffers from assay throughput and reproducibility to enable high-throughput screening (HTS) of compounds due to cumbersome organoid differentiation processes and difficulty in scale-up and quality control. Using organoids for HTS is further challenged by the lack of easy-to-use fluidic systems that are compatible with relatively large organoids. Here, these challenges are overcome by engineering "microarray three-dimensional (3D) bioprinting" technology and associated pillar and perfusion plates for human organoid culture and analysis. High-precision, high-throughput stem cell printing, and encapsulation techniques are demonstrated on a pillar plate, which is coupled with a complementary deep well plate and a perfusion well plate for static and dynamic organoid culture. Bioprinted cells and spheroids in hydrogels are differentiated into liver and intestine organoids for in situ functional assays. The pillar/perfusion plates are compatible with standard 384-well plates and HTS equipment, and thus may be easily adopted in current drug discovery efforts.

Failure, Success, and Future Direction of Alzheimer Drugs Targeting Amyloid-β Cascade: Pros and Cons of Chemical and Biological Modalities.

Alzheimer's disease (AD) is the most prevalent cause of dementia and has become a health concern worldwide urging for an effective therapeutic. The amyloid hypothesis, currently the most pursued basis of AD drug discovery, points the cause of AD to abnormal production and ineffective removal of pathogenic aggregated amyloid-β (Aβ). AD therapeutic research has been focused on targeting different species of Aβ in the amyloidogenic process to control Aβ content and recover cognitive decline. Among the different processes targeted, the clearance mechanism has been found to be the most effective, supported by the recent clinical approval of an Aβ-targeting immunotherapeutic drug which significantly slowed cognitive decline. Although the current AD drug discovery field is extensively researching immunotherapeutic drugs, there are numerous properties of immunotherapy in need of improvements that could be overcome by an equally performing chemical drug. Here, we review chemical and immunotherapy drug candidates, based on their mechanism of modulating the amyloid cascade, selected from the AlzForum database. Through this review, we aim to summarize and evaluate the prospect of Aβ-targeting chemical drugs.

A novel Hyperledger blockchain-enabled decentralized application for drug discovery chain management

The aim of the drug discovery process is to create a brand-new drug that is both safe and useful for treating disease in patients. The trustworthy collaboration of the organisations involved in the drug discovery process and the integrity of their contributions are essential for this process. Current drug discovery chains use centralised systems, which are susceptible to lockdown by cyberattacks. Blockchain, with its many characteristics such as accountability, immutability, integrity, privacy, and security, has the potential to be extremely useful in drug discovery chain management. The purpose of this work is to create a drug discovery framework utilizing the strengths of blockchain technology in combination with machine learning (ML). Such a system would provide a secure, efficient, and faster drug development life cycle. This study presents a novel Hyperledger fabric-based drug discovery application that empowers the permissioned organisations to upload, update, view, and verify contributions. ML is used to preprocess data and visualise features. In the proposed work, a unique identifier is assigned to each contribution asset using the secure hash algorithm (SHA-256). The proposed design also enables the regulatory authority to issue certificates proving the ownership of contributions to the contributing organisations. The blockchain ledger has been used to store the meta-data and InChIKey of drug contributions, and actual contributions are in off-chain storage. In this work, we have successfully built an end-to-end decentralised drug discovery application with a front-end interface and demonstrated chaincode algorithms. The end-to-end application is not available in any previous work. The Caliper tool has been used to investigate throughput, latency, and resource statistics. The performance and comparative analysis show that the proposed design is scalable and promising for drug discovery chain management.

Kinetic analysis of fluorescent ligand binding to cell surface receptors: Insights into conformational changes and allosterism in living cells.

Equilibrium binding assays are one of the mainstays of current drug discovery efforts to evaluate the interaction of drugs with receptors in membranes and intact cells. However, in recent years, there has been increased focus on the kinetics of the drug-receptor interaction to gain insight into the lifetime of drug-receptor complexes and the rate of association of a ligand with its receptor. Furthermore, drugs that act on topically distinct sites (allosteric) from those occupied by the endogenous ligand (orthosteric site) can induce conformational changes in the orthosteric binding site leading to changes in the association and/or dissociation rate constants of orthosteric ligands. Conformational changes in the orthosteric ligand binding site can also be induced through interaction with neighbouring accessory proteins and receptor homodimerisation and heterodimerisation. In this review, we provide an overview of the use of fluorescent ligand technologies to interrogate ligand-receptor kinetics in living cells and the novel insights that they can provide into the conformational changes induced by drugs acting on a variety of cell surface receptors including G protein-coupled receptors (GPCRs), receptor tyrosine kinases (RTKs) and cytokine receptors.

Importance of tautomerism in drugs.

Tautomerism is an important phenomenon exhibited by many drugs. As we discuss in this review, identifying the different tautomers of drugs and exploring their importance in the mechanisms of drug action are integral components of current drug discovery. Nuclear magnetic resonance (NMR), infrared (IR), ultraviolet (UV), Raman, and terahertz spectroscopic techniques, as well as X-ray diffraction, are useful for exploring drug tautomerism. Quantum chemical methods, in association with pharmacoinformatics tools, are being used to evaluate tautomeric preferences in terms of energy effects. Desmotropy (i.e., tautomeric polymorphism) of the drugs is particularly important in drug delivery studies.

Discovery of novel acetylcholinesterase inhibitors through integration of machine learning with genetic algorithm based in silico screening approaches.

Alzheimer's disease (AD) is the most studied progressive eurodegenerative disorder, affecting 40-50 million of the global population. This progressive neurodegenerative disease is marked by gradual and irreversible declines in cognitive functions. The unavailability of therapeutic drug candidates restricting/reversing the progression of this dementia has severed the existing challenge. The development of acetylcholinesterase (AChE) inhibitors retains a great research focus for the discovery of an anti-Alzheimer drug. This study focused on finding AChE inhibitors by applying the machine learning (ML) predictive modeling approach, which is an integral part of the current drug discovery process. In this study, we have extensively utilized ML and other in silico approaches to search for an effective lead molecule against AChE. The output of this study helped us to identify some promising AChE inhibitors. The selected compounds performed well at different levels of analysis and may provide a possible pathway for the future design of potent AChE inhibitors.

Natural products in pursuing novel therapies of nonalcoholic fatty liver disease and steatohepatitis.

Nonalcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH) are hepatic manifestations of systemic metabolic dysfunction, which affect one-quarter of the adult population worldwide as estimated, and exhibit high risk in progressing to hepatic fibrosis, cirrhosis, and hepatocellular carcinoma. Current drug discovery focuses on modifying homeostasis of lipids, carbohydrates, and cholesterol, as well as inhibiting inflammation and fibrogenesis. Many natural products show promising activities on various molecular targets involving these mechanisms; however, they have not been fully exploited. Since some compounds are components of healthy food, they may be employed in chemoprevention as adjuvants to lifestyle modification, while natural products such as alkaloids and sesquiterpenoids could serve as promising starting points for structural modifications and deserve further development.

Advances in Molecular Regulation of Prostate Cancer Cells by Top Natural Products of Malaysia

Prostate cancer (PCa) remains both a global health burden and a scientific challenge. We present a review of the molecular targets driving current drug discovery to fight this disease. Moreover, the preventable nature of most PCa cases represents an opportunity for phytochemicals as chemopreventive when adequately integrated into nutritional interventions. With a renovated interest in natural remedies as a commodity and their essential role in cancer drug discovery, Malaysia is looking towards capitalizing on its mega biodiversity, which includes the oldest rainforest in the world and an estimated 1200 medicinal plants. We here explore whether the list of top Malay plants prioritized by the Malaysian government may fulfill the potential of becoming newer, sustainable sources of prostate cancer chemotherapy. These include Andrographis paniculate, Centella asiatica, Clinacanthus nutans, Eurycoma longifolia, Ficus deltoidea, Hibiscus sabdariffa, Marantodes pumilum (syn. Labisia pumila), Morinda citrifolia, Orthosiphon aristatus, and Phyllanthus niruri. Our review highlights the importance of resistance factors such as Smac/DIABLO in cancer progression, the role of the CXCL12/CXCR4 axis in cancer metastasis, and the regulation of PCa cells by some promising terpenes (andrographolide, Asiatic acid, rosmarinic acid), flavonoids (isovitexin, gossypin, sinensetin), and alkylresorcinols (labisiaquinones) among others.