Identification of novel natural inhibitors targeting AKT Serine/Threonine Kinase 1 (AKT1) by computational study

In Silico Discovery of a Novel PI3Kδ Inhibitor Incorporating 3,5,7-Trihydroxychroman-4-one Targeting Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma, and it is highly aggressive and heterogeneous. Targeted therapy is still the main treatment method used in clinic due to its lower risk of side effects and personalized medication. Excessive activation of PI3Kδ in DLBCL leads to abnormal activation of the PI3K/Akt pathway, promoting the occurrence and development of DLBCL. The side effects of existing PI3Kδ inhibitors limit their clinical application. The discovery of PI3Kδ inhibitors with novel structures and minimal side effects is urgently needed. This study constructed a PI3Kδ inhibitor screening model to screen natural product libraries. Revealing the mechanism of natural product therapy for DLBCL through network pharmacology, kinase assays, and molecular dynamics. The results of molecular docking indicated that Silibinin had a high docking score and a good binding mode with PI3Kδ. The results of network pharmacology indicated that Silibinin could exert therapeutic effects on DLBCL by inhibiting PI3Kδ activity and affecting the PI3K/Akt pathway. The kinase assays indicated that Silibinin concentration dependently inhibited the activity of PI3Kδ. The results of molecular dynamics indicated that Silibinin could stably bind to PI3Kδ. Silibinin was a structurally novel 3,5,7-trihydroxychroman-4-one PI3Kδ inhibitor, providing valuable information for the subsequent discovery of PI3Kδ inhibitors.

Exploring Radioiodinated Anastrozole and Epirubicin as AKT1-Targeted Radiopharmaceuticals in Breast Cancer: In Silico Analysis and Potential Therapeutic Effect with Functional Nuclear Imagining Implications

This study evaluates radio-iodinated anastrozole ([125I]anastrozole) and epirubicin ([125I]epirubicin) for AKT1-targeted breast cancer therapy, utilizing radiopharmaceutical therapy (RPT) for personalized treatment. Through molecular docking and dynamics simulations (200 ns), it investigates these compounds' binding affinities and mechanisms to the AKT1 enzyme, compared to the co-crystallized ligand, a known AKT1 inhibitor. Molecular docking results show that [125I]epirubicin has the highest ΔGbind (-11.84 kcal/mol), indicating a superior binding affinity compared to [125I] anastrozole (-10.68 kcal/mol) and the co-crystallized ligand (-9.53 kcal/mol). Molecular dynamics (MD) simulations confirmed a stable interaction with the AKT1 enzyme, with [125I]anastrozole and [125I]epirubicin reaching stability after approximately 68 ns with an average RMSD of around 2.2 Å, while the co-crystallized ligand stabilized at approximately 2.69 Å after 87 ns. RMSF analysis showed no significant shifts in residues or segments, with consistent patterns and differences of less than 2 Å, maintaining enzyme stability. The [125I]epirubicin complex maintained an average of four H-bonds, indicating strong and stable interactions, while [125I]anastrozole consistently formed three H-bonds. The average Rg values for both complexes were ~16.8 ± 0.1 Å, indicating no significant changes in the enzyme's compactness, thus preserving structural integrity. These analyses reveal stable binding and minimal structural perturbations, suggesting the high potential for AKT1 inhibition. MM-PBSA calculations confirm the potential of these radio-iodinated compounds as AKT1 inhibitors, with [125I]epirubicin exhibiting the most favorable binding energy (-23.57 ± 0.14 kcal/mol) compared to [125I]anastrozole (-20.03 ± 0.15 kcal/mol) and the co-crystallized ligand (-16.38 ± 0.14 kcal/mol), highlighting the significant role of electrostatic interactions in stabilizing the complex. The computational analysis shows [125I]anastrozole and [125I]epirubicin may play promising roles as AKT1 inhibitors, especially [125I]epirubicin for its high binding affinity and dynamic receptor interactions. These findings, supported by molecular docking scores and MM-PBSA binding energies, advocate for their potential superior inhibitory capability against the AKT1 enzyme. Nevertheless, it is crucial to validate these computational predictions through in vitro and in vivo studies to thoroughly evaluate the therapeutic potential and viability of these compounds for AKT1-targeted breast cancer treatment.

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis

AIM

Computer-aided drug design (CADD) is a drug design technique for computing ligand-receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics.

METHODS

A systematic review of studies published between 2000 and 20 July 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analyzed using software such as Excel, VOSviewer, RStudio, and CiteSpace.

RESULTS

A total of 2031 publications were included. These publications primarily originated from 99 countries or regions led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and the greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications.

CONCLUSIONS

Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modeling, pharmacophore modeling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics that will influence future development. Furthermore, this paper will be helpful in better understanding the frontiers and hotspots of CADD.

Exposure estimation and neurotoxicity inhibition of dioxins in sensitive populations near domestic waste incineration plant through adverse outcome pathway

The neurotoxicity induced by dioxins has been recognized as a serious concern to sensitive population living near waste incineration plants. However, investigating the intracellular neurotoxicity of dioxin in humans and the corresponding mitigation strategies has been barely studied. Thus, a domestic waste incineration plant was selected in this study to characterize the neurotoxicity risks of sensitive populations by estimating the ratio of dioxin in human cells using membrane structure dynamics simulation; and constructing a complete dioxin neurotoxicity adverse outcome pathway considering the binding process of AhR/ARNT dimer protein and dioxin response element (DRE). Six dioxins with high neurotoxicity risk were identified. According to the composite neurotoxicity risk analysis, the highest composite neurotoxicity risk appeared when the six dioxins were jointly exposed. Dietary schemes were designed using 1/2 partial factor experimental design to mitigate the composite neurotoxicity risk of six dioxins and No. 16 was screened as the optimum combination which can effectively alleviate the composite neurotoxicity risk by 29.52%. Mechanism analysis shows that the interaction between AhR/ARNT dimer protein and DRE was inhibited under the optimal dietary scheme. This study provides theoretical feasibility and reference significance for assessing composite toxicity risks of pollutants and safety mitigation measures for toxic effects.

Integration of ligand and structure-based pharmacophore screening for the identification of novel natural leads against Euchromatic histone lysine methyltransferase 2 (EHMT2/G9a)

Herein, we report a blended ligand and structure-based pharmacophore screening approach to identify new natural leads against the Protein Lysine Methyltransferase 2 (EHMT2/G9a). The EHMT2/G9a has been associated with Cancer, Alzheimer's, and aging and is considered an emerging drug target having no clinically passed inhibitor. Purposefully, we developed the ligand-based pharmacophore (Pharmacophore-L) based on the common features of known inhibitors and the structure-based pharmacophore (Pharmacophore-S) based on the interaction profile of available crystal structures. The Pharmacophore-L and Pharmacophore-S were subjected to multiple tiers of validations and utilized in combination for the screening of total 741543 compounds coming from multiple databases. Additional layers of stringency were applied in the screening process to test drug-likeness (using Lipinski's rule, Veber's rule, SMARTS and ADMET filtration), to rule out any toxicity (TOPKAT analysis). The interaction profiles, stabilities, and comparative analysis against the reference were carried out by flexible docking, MD simulation, and MM-GBSA analysis, which finally led to three leads as potential inhibitors of G9a.Communicated by Ramaswamy H. Sarma.

Identification of potent inhibitors targeting Tribolium castaneum GSTe2 via structure-based screening and molecular dynamics simulation

Red flour beetle, Tribolium castaneum, has a major negative impact during storage of agricultural products and reveals the negative impacts on human health. Insect-specific epsilon glutathione S-transferase (GSTs) which requires reduced glutathione (GSH) as an essential substrate not only develop insecticide resistance but also play important role in insect metamorphosis. Inhibition of the insect metamorphosis and the development of insecticide resistance could play an important role in pest control, so T. castaneum GSTe2 (TcGSTe2) in our previous study could be an important target protein for this purpose. This study aimed to find a potential TcGSTe2 inhibitors through in silico mothods, including molecular modeling, molecular docking, ADMET assay, followed by molecular dynamics (MD) simulation, principal component analysis and MM/PBSA analysis. The results showed that ZINC000169293362 and ZINC000095566957 were selected as potential TcGSTe2 inhibitors with high-binding affinity and without any toxicity from 3618 of GSH-like compounds obtained from ZINC database. MD simulation results revealed that TcGSTe2-ZINC000169293362 had more stability than that of reference GSH. Moreover, TcGSTe2-ZINC000169293362 and TcGSTe2-ZINC000095566957 showed lower binding free energy (-27.53 ± 0.16 kcal/mol and -18.83 ± 0.15 kcal/mol, respectively) compared with TcGSTe2-GSH (-8.90 ± 0.30 kcal/mol). This study could provide new insight into reduction of insecticide resistance and be used to design new inhibitors of insect GSTs.Communicated by Ramaswamy H. Sarma.

Research progress on rodent models and its mechanisms of liver injury

The liver is the most important organ for biological transformation in the body and is crucial for maintaining the body's vital activities. Liver injury is a serious pathological condition that is commonly found in many liver diseases. It has a high incidence rate, is difficult to cure, and is prone to recurrence. Liver injury can cause serious harm to the body, ranging from mild to severe fatty liver disease. If the condition continues to worsen, it can lead to liver fibrosis and cirrhosis, ultimately resulting in liver failure or liver cancer, which can seriously endanger human life and health. Therefore, establishing an rodent model that mimics the pathogenesis and severity of clinical liver injury is of great significance for better understanding the pathogenesis of liver injury patients and developing more effective clinical treatment methods. The author of this article summarizes common chemical liver injury models, immune liver injury models, alcoholic liver injury models, drug-induced liver injury models, and systematically elaborates on the modeling methods, mechanisms of action, pathways of action, and advantages or disadvantages of each type of model. The aim of this study is to establish reliable rodent models for researchers to use in exploring anti-liver injury and hepatoprotective drugs. By creating more accurate theoretical frameworks, we hope to provide new insights into the treatment of clinical liver injury diseases.

Network pharmacology and experimental validation for deciphering the action mechanism of Fritillaria cirrhosa D. Don constituents in suppressing breast carcinoma

Fritillaria cirrhosa D. Don is a well-known medicinal plant of Kashmir Himalaya. Traditionally, it has been used to treat several diseases, including cancer. However, the molecular mechanism behind anticancer activity remains unclear. Therefore, in the present study, we have performed high performance-liquid chromatography-mass spectrometry (HR-LC/MS), network pharmacology, molecular docking and molecular dynamic (MD) simulation methods were used to explore the underlying molecular mechanism of F. cirrhosa for the treatment of breast cancer (BC). The targets of F. cirrhosa for treating BC were predicted using databases like SwissTargetPrediction, Gene Cards and OMIM. Protein-protein interaction analysis and network construction were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins programme, and analysis of Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment was done using the Cytoscape programme. In addition, molecular docking was used to investigate intermolecular interactions between the compounds and the proteins using the Autodock tool. MD simulations studies were also used to explore the stability of the representative AKT1 gene peiminine and Imperialine-3-β-glucoside. In addition, experimental treatment of F. cirrhosa was also verified. HR-LC/MS detected the presence of several secondary metabolites. Afterward, molecular docking was used to verify the effective activity of the active ingredients against the prospective targets. Additionally, Peiminine and Imperialine-3-β-glucoside showed the highest binding energy score against AKT-1 (-12.99 kcal/mol and -12.08 kcal/mol). AKT1 with Peiminine and Imperialine-3-β-glucoside was further explored for MD simulations. During the MD simulation study at 100 nanoseconds, a stable complex formation of AKT1 + Peiminine and Imperialine-3-β-glucoside was observed. The binding free energy calculations using MM/GBSA showed significant binding of the ligand with protein (ΔG: -79.83 ± 3.0 kcal/mol) between AKT1 + Peiminine was observed. The principal component analysis exhibited a stable converged structure by achieving global motion. Lastly, F. cirrhosa extracts also exhibited momentous anticancer activity through in vitro studies. Therefore, present study revealed the molecular mechanism of F. cirrhosa constituents for the effective treatment of BC by deactivating various multiple gene targets, multiple pathways particularly the PI3K-Akt signaling pathway. These findings emphasized the momentous anti-BC activity of F. cirrhosa constituents.Communicated by Ramaswamy H. Sarma.

Targeting Melanoma with a phytochemical pool: Tailing Makisterone C

BACKGROUND AND OBJECTIVE

According to World Health Organization, melanoma claims the lives of about 48000 people worldwide each year. The purpose of this study was to identify potential phytochemical pool from Diplazium esculentum against proteins that contribute to melanoma development.

METHODS

The research was carried to locate potentially bioactive molecules and conduct a theoretical analysis of active ingredients from DE to impact melanoma. Network pharmacology, pharmacokinetics, protein network interaction, gene enrichment, survival, and infiltration analysis were conducted. Furthermore, molecular docking and molecular dynamics simulation was carried out for makisterone C-MAPK1, MAPK3, and AKT1 complexes.

RESULTS

The potential phytochemical pool were identified (stigmast-5-en-3-ol, esculentic acid, rutin, and makisterone C) and based on network pharmacology and molecular docking studies, makisterone-C was proposed to be the most promising ingredient. Furthermore, the investigation revealed 14 genes as critical "hubs" involved in combating melanoma that are manipulated by the above-mentioned 4 active ingredients and modulate multiple signaling in melanoma development.

CONCLUSION

This study insights into the potential anti-melanoma effects of phytochemical pool from Diplazium esculentum using network pharmacology analysis, molecular docking, and simulation tailing makisterone C as a lead moiety and suggests the need for makisterone C further evaluation in intervening melanoma progression.

Exploring Covalent Bond Formation at Tyr-82 for Inhibition of Ral GTPase Activation

Ral RAS GTPases are directly activated by KRAS through a trimeric complex with a guanine exchange factor. Ral is considered undruggable and lacks an accessible cysteine for covalent drug development. Previously we had reported an aryl sulfonyl fluoride fragment that formed a covalent bond at Tyr-82 on Ral and created a deep and well-defined pocket. Here, we explore this pocket further through design and synthesis of several fragment derivatives. The fragment core is modified by introducing tetrahydronaphthalene or benzodioxane rings to enhance affinity and stability of the sulfonyl fluoride reactive group. The deep pocket in the Switch II region is also explored by modifying the aromatic ring of the fragment that is ensconced into the pocket. Compounds 19 (SOF-658) and 26 (SOF-648) formed a single robust adduct specifically at Tyr-82, inhibited Ral GTPase exchange in buffer and in mammalian cells, and blocked invasion of pancreatic ductal adenocarcinoma cancer cells. Compound 19 (SOF-658) was stable in buffer, mouse, and human microsomes suggesting that further optimization could lead to small molecules to probe Ral activity in tumor models.

Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma

Introduction: The effect of the conventional treatment methods of glioblastoma (GBM) is poor and the prognosis of patients is poor. The expression of MCL-1 in GBM is significantly increased, which shows a high application value in targeted therapy. In this study, we predicted the prognosis of glioblastoma patients, and therefore constructed MCL-1 related prognostic signature (MPS) and the development of MCL-1 small molecule inhibitors. Methods: In this study, RNA-seq and clinical data of 168 GBM samples were obtained from the TCGA website, and immunological analysis, differential gene expression analysis and functional enrichment analysis were performed. Subsequently, MCL-1-associated prognostic signature (MPS) was constructed and validated by LASSO Cox analysis, and a nomogram was constructed to predict the prognosis of patients. Finally, the 17931 small molecules downloaded from the ZINC15 database were screened by LibDock, ADME, TOPKAT and CDOCKER modules and molecular dynamics simulation in Discovery Studio2019 software, and two safer and more effective small molecule inhibitors were finally selected. Results: Immunological analysis showed immunosuppression in the MCL1_H group, and treatment with immune checkpoint inhibitors had a positive effect. Differential expression gene analysis identified 449 differentially expressed genes. Build and validate MPS using LASSO Cox analysis. Use the TSHR HIST3H2A, ARGE OSMR, ARHGEF25 build risk score, proved that low risk group of patients prognosis is better. Univariate and multivariate analysis proved that risk could be used as an independent predictor of patient prognosis. Construct a nomogram to predict the survival probability of patients at 1,2,3 years. Using a series of computer-aided techniques, two more reasonable lead compounds ZINC000013374322 and ZINC000001090002 were virtually selected. These compounds have potential inhibitory effects on MCL-1 and provide a basis for the design and further development of MCL-1 specific small molecule inhibitors. Discussion: This study analyzed the effect of MCL-1 on the prognosis of glioblastoma patients from the perspective of immunology, constructed a new prognostic model to evaluate the survival rate of patients, and further screened 2 MCL-1 small molecule inhibitors, which provides new ideas for the treatment and prognosis of glioblastoma.

Computer-Aided Identification of Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein

AKT (also known as PKB) is a serine/threonine kinase that plays a pivotal regulatory role in the PI3K/AKT/mTOR signaling pathway. Dysregulation of AKT activity, especially its hyperactivation, is closely associated with the development of various human cancers and resistance to chemotherapy. Over the years, a wide array of AKT inhibitors has been discovered through experimental and computational approaches. In this regard, herein we present a comprehensive overview of AKT inhibitors identified using computer-assisted drug design methodologies (including docking-based and pharmacophore-based virtual screening, machine learning, and quantitative structure-activity relationships) and successfully validated small molecules endowed with anticancer activity. Thus, this review provides valuable insights to support scientists focused on AKT inhibition for cancer treatment and suggests untapped directions for future computer-aided drug discovery efforts.

Inflammatory factors and risk of meningiomas: a bidirectional mendelian-randomization study

Background

Meningiomas are one of the most common intracranial tumors, and the current understanding of meningioma pathology is still incomplete. Inflammatory factors play an important role in the pathophysiology of meningioma, but the causal relationship between inflammatory factors and meningioma is still unclear.

Method

Mendelian randomization (MR) is an effective statistical method for reducing bias based on whole genome sequencing data. It's a simple but powerful framework, that uses genetics to study aspects of human biology. Modern methods of MR make the process more robust by exploiting the many genetic variants that may exist for a given hypothesis. In this paper, MR is applied to understand the causal relationship between exposure and disease outcome.

Results

This research presents a comprehensive MR study to study the association of genetic inflammatory cytokines with meningioma. Based on the results of our MR analysis, which examines 41 cytokines in the largest GWAS datasets available, we were able to draw the relatively more reliable conclusion that elevated levels of circulating TNF-β, CXCL1, and lower levels of IL-9 were suggestive associated with a higher risk of meningioma. Moreover, Meningiomas could cause lower levels of interleukin-16 and higher levels of CXCL10 in the blood.

Conclusion

These findings suggest that TNF-β, CXCL1, and IL-9 play an important role in the development of meningiomas. Meningiomas also affect the expression of cytokines such as IL-16 and CXCL10. Further studies are needed to determine whether these biomarkers can be used to prevent or treat meningiomas.

Therapeutic potential of natural molecules against Alzheimer's disease via SIRT1 modulation

Alzheimer's disease (AD) is a neurodegenerative disease mainly characterized by progressive cognitive dysfunction and memory impairment. Recent studies have shown that regulating silent information regulator 1 (SIRT1) expression has a significant neuroprotective effect, and SIRT1 may become a new therapeutic target for AD. Natural molecules are an important source of drug development for use in AD therapy and may regulate a wide range of biological events by regulating SIRT1 as well as other SIRT1-mediated signaling pathways. This review aims to summarize the correlation between SIRT1 and AD and to identify in vivo and in vitro studies investigating the anti-AD properties of natural molecules as modulators of SIRT1 and SIRT1-mediated signaling pathways. A literature search was conducted for studies published between January 2000 and October 2022 using various literature databases, including Web of Science, PubMed, Google Scholar, Science Direct, and EMBASE. Natural molecules, such as resveratrol, quercetin, icariin, bisdemethoxycurcumin, dihydromyricetin, salidroside, patchouli, sesamin, rhein, ligustilide, tetramethoxyflavanone, 1-theanine, schisandrin, curcumin, betaine, pterostilbene, ampelopsin, schisanhenol, and eriodictyol, have the potential to modulate SIRT1 and SIRT1 signaling pathways, thereby combating AD. The natural molecules modulating SIRT1 discussed in this review provide a potentially novel multi-mechanistic therapeutic strategy for AD. However, future clinical trials need to be conducted to further investigate their beneficial properties and to determine the safety and efficacy of SIRT1 natural activators against AD.

Synergistic Inhibitory Effects of Selected Amino Acids on the Formation of 2-Amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) in both Benzaldehyde- and Phenylacetaldehyde-Creatinine Model Systems

Although various inhibitors have been employed to react with phenylacetaldehyde to form adducts and thus interrupt the formation of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), high concentrations of PhIP remain in the final system. It remains unknown whether other critical aldehyde or ketone intermediates are involved in the generation of PhIP, and scavenging these reactive carbonyls simultaneously may achieve higher inhibitory efficiency of PhIP. In this study, reactive carbonyls in a glucose/creatinine/phenylalanine model system were first identified by gas chromatography-mass spectrometry (GC-MS), and then the single and synergistic effects of nonprecursor amino acids (cysteine, methionine, proline, histidine, arginine, and leucine) on scavenging reactive carbonyls were investigated to find out promising combination partners. The obtained results showed that the concentrations of benzaldehyde and phenylacetaldehyde in the glucose/creatinine/phenylalanine model system reached 0.49 ± 0.01 and 6.22 ± 0.21 μg/mL, respectively. Heating these carbonyl compounds in the presence of creatinine resulted in the quantity of PhIP produced increasing linearly with the added quantity of benzaldehyde (r = 0.9733, P = 0.0002) and phenylacetaldehyde (r = 0.9746, P = 0.0002), indicating that both compounds are key intermediates for PhIP generation. Among the investigated amino acids, histidine produced the maximum inhibition of PhIP formation (78-99%) in the benzaldehyde/creatinine model system, and proline produced the maximum inhibition of PhIP formation (13-97%) in the phenylacetaldehyde/creatinine model system, where both compounds decreased PhIP formation in a dose-dependent manner. Histidine in combination with proline enhanced the inhibitory effect against PhIP formation at a low addition level, where the highest inhibitory efficiency was obtained using a 1:3 mass ratio of histidine to proline (2 mg/mL in total), reducing PhIP formation by 96%. These findings suggest that histidine-proline combinations can scavenge benzaldehyde and phenylacetaldehyde simultaneously, enhancing the suppression of PhIP formation.

Potential Toxicity Risk Assessment and Priority Control Strategy for PAHs Metabolism and Transformation Behaviors in the Environment

In this study, 16 PAHs were selected as the priority control pollutants to summarize their environmental metabolism and transformation processes, including photolysis, plant degradation, bacterial degradation, fungal degradation, microalgae degradation, and human metabolic transformation. Meanwhile, a total of 473 PAHs by-products generated during their transformation and degradation in different environmental media were considered. Then, a comprehensive system was established for evaluating the PAHs by-products' neurotoxicity, immunotoxicity, phytotoxicity, developmental toxicity, genotoxicity, carcinogenicity, and endocrine-disrupting effect through molecular docking, molecular dynamics simulation, 3D-QSAR model, TOPKAT method, and VEGA platform. Finally, the potential environmental risk (phytotoxicity) and human health risks (neurotoxicity, immunotoxicity, genotoxicity, carcinogenicity, developmental toxicity, and endocrine-disrupting toxicity) during PAHs metabolism and transformation were comprehensively evaluated. Among the 473 PAH's metabolized and transformed products, all PAHs by-products excluding ACY, CHR, and DahA had higher neurotoxicity, 152 PAHs by-products had higher immunotoxicity, and 222 PAHs by-products had higher phytotoxicity than their precursors during biological metabolism and environmental transformation. Based on the TOPKAT model, 152 PAH by-products possessed potential developmental toxicity, and 138 PAH by-products had higher genotoxicity than their precursors. VEGA predicted that 247 kinds of PAH derivatives had carcinogenic activity, and only the natural transformation products of ACY did not have carcinogenicity. In addition to ACY, 15 PAHs produced 123 endocrine-disrupting substances during metabolism and transformation. Finally, the potential environmental and human health risks of PAHs metabolism and transformation products were evaluated using metabolic and transformation pathway probability and degree of toxic risk as indicators. Accordingly, the priority control strategy for PAHs was constructed based on the risk entropy method by screening the priority control pathways. This paper assesses the potential human health and environmental risks of PAHs in different environmental media with the help of models and toxicological modules for the toxicity prediction of PAHs by-products, and thus designs a risk priority control evaluation system for PAHs.