Pub Date : 2025-11-15DOI: 10.1016/j.jmgm.2025.109220
Karma Wangchuk , Mudassar Fareed Awan , Syeda Nazish Sohaib , Abdul Basit , Biniyam Prince Danan , Laiba Nadeem , Guendouzi Abdelkrim , Aisha Khalid , Khursheed Muzammil
Mycobacterium tuberculosis causes tuberculosis (TB), which remains a significant health problem worldwide. The rise of multidrug-resistant bacteria has worsened the situation, and current treatments are becoming less effective. InhA, a key enzyme involved in mycolic acid biosynthesis, is a validated therapeutic target in anti-TB therapy. This study aimed to explore the chemical diversity of natural substances from mushrooms against TB. Experimentally validated inhibitors from ChEMBL were retrieved to generate machine learning–based QSAR models combining nine chemical fingerprints and rigorous feature selection. The optimal RF–SVM-RFE model displayed high prediction performance (accuracy = 0.953, ROC_AUC = 0.971) and led virtual screening of mushroom metabolites. Six top-ranked compounds, including Inoscavin A and Schizine A, displayed substantial binding affinities (−11.7 to −10.5 kcal/mol) and stable interaction networks in molecular docking and MD simulations. Explainable AI (SHAP and LIME) showed fundamental structural motifs that drive activity and enhance chemical interpretability. These findings suggest promising natural scaffolds for anti-TB drug development and underscore the importance of AI-driven strategies in accelerating natural product–based therapeutics.
{"title":"Machine Learning–Driven discovery of mushroom-derived inhibitors targeting InhA of Mycobacterium tuberculosis: An integrated QSAR, molecular docking and molecular dynamic simulation approach","authors":"Karma Wangchuk , Mudassar Fareed Awan , Syeda Nazish Sohaib , Abdul Basit , Biniyam Prince Danan , Laiba Nadeem , Guendouzi Abdelkrim , Aisha Khalid , Khursheed Muzammil","doi":"10.1016/j.jmgm.2025.109220","DOIUrl":"10.1016/j.jmgm.2025.109220","url":null,"abstract":"<div><div><em>Mycobacterium tuberculosis</em> causes tuberculosis (TB), which remains a significant health problem worldwide. The rise of multidrug-resistant bacteria has worsened the situation, and current treatments are becoming less effective. InhA, a key enzyme involved in mycolic acid biosynthesis, is a validated therapeutic target in anti-TB therapy. This study aimed to explore the chemical diversity of natural substances from mushrooms against TB. Experimentally validated inhibitors from ChEMBL were retrieved to generate machine learning–based QSAR models combining nine chemical fingerprints and rigorous feature selection. The optimal RF–SVM-RFE model displayed high prediction performance (accuracy = 0.953, ROC_AUC = 0.971) and led virtual screening of mushroom metabolites. Six top-ranked compounds, including Inoscavin A and Schizine A, displayed substantial binding affinities (−11.7 to −10.5 kcal/mol) and stable interaction networks in molecular docking and MD simulations. Explainable AI (SHAP and LIME) showed fundamental structural motifs that drive activity and enhance chemical interpretability. These findings suggest promising natural scaffolds for anti-TB drug development and underscore the importance of AI-driven strategies in accelerating natural product–based therapeutics.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109220"},"PeriodicalIF":3.0,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-14DOI: 10.1016/j.jmgm.2025.109215
Sumanta Pal , Narendra Nath Ghosh , Soumen Kumar Pati , Manab Mandal
Nanomedicine has transformed cancer therapy by introducing and developing nanocarriers to enhance drug delivery. Herein, we have executed a computational investigation of the efficiency of two anti-breast cancer drugs viz. Exemestane (EXE) and Ruxolitinib (RUX) are delivered through armchair CNT (10,10). The encapsulation process of drugs in CNTs has been investigated through an analysis of various structural and electrical parameters viz. atom centered density matrix(ADMP), adsorption energy, electrostatic potential map(ESPM), molecular orbital(MO) analysis, natural bond orbital (NBO) analysis, non-covalent index (NCI) plot, and projected density of state (PDOS). The higher adsorption value of RUX -72.42 kcal/mol(-3.14 eV) with CNT and CNT-EXE -63.29 kcal/mol(-2.75 eV) indicates a stronger binding affinity of RUX and EXE. The electronic properties of the CNT were examined and compared before and after the adsorption process.Study of several thermodynamic parameters revealed that the whole encapsulation process is exothermic and spontaneous in nature. The stabilizing interaction of drugs and CNT has been established and validated from ADMP molecular dynamics simulation and NCI analysis was performed through the encapsulation procedure of the drugs within CNT at room temperature. The best docking score showed the CNT with EXE (−7.6 kcal/mol) followed by CNT with RUX (−7.5 kcal/mol), higher than the studied drugs i.e. EXE (−7.3 kcal/mol) and RUX (−7.2 kcal/mol). The docking score indicates that the inclusion complex has a better interaction and pave the way for unlimited opportunities for the delivery vehicle of CNT for the studied drugs within the biological systems.
{"title":"CNT as a robust delivery vehicle for anti-breast cancer drugs: A combined DFT and in-silico study","authors":"Sumanta Pal , Narendra Nath Ghosh , Soumen Kumar Pati , Manab Mandal","doi":"10.1016/j.jmgm.2025.109215","DOIUrl":"10.1016/j.jmgm.2025.109215","url":null,"abstract":"<div><div>Nanomedicine has transformed cancer therapy by introducing and developing nanocarriers to enhance drug delivery. Herein, we have executed a computational investigation of the efficiency of two anti-breast cancer drugs viz. Exemestane (EXE) and Ruxolitinib (RUX) are delivered through armchair CNT (10,10). The encapsulation process of drugs in CNTs has been investigated through an analysis of various structural and electrical parameters viz. atom centered density matrix(ADMP), adsorption energy, electrostatic potential map(ESPM), molecular orbital(MO) analysis, natural bond orbital (NBO) analysis, non-covalent index (NCI) plot, and projected density of state (PDOS). The higher adsorption value of RUX -72.42 kcal/mol(-3.14 eV) with CNT and CNT-EXE -63.29 kcal/mol(-2.75 eV) indicates a stronger binding affinity of RUX and EXE. The electronic properties of the CNT were examined and compared before and after the adsorption process.Study of several thermodynamic parameters revealed that the whole encapsulation process is exothermic and spontaneous in nature. The stabilizing interaction of drugs and CNT has been established and validated from ADMP molecular dynamics simulation and NCI analysis was performed through the encapsulation procedure of the drugs within CNT at room temperature. The best docking score showed the CNT with EXE (−7.6 kcal/mol) followed by CNT with RUX (−7.5 kcal/mol), higher than the studied drugs i.e. EXE (−7.3 kcal/mol) and RUX (−7.2 kcal/mol). The docking score indicates that the inclusion complex has a better interaction and pave the way for unlimited opportunities for the delivery vehicle of CNT for the studied drugs within the biological systems.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109215"},"PeriodicalIF":3.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145556980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-14DOI: 10.1016/j.jmgm.2025.109225
Somayeh Behzad
This theoretical study investigates the properties of T-GeNRs using tight-binding formalism, Green's function, and the Kubo formula. Our research examines the temperature dependence of thermodynamic functions under varying external parameters, including electric bias and magnetic fields and chemical potential. The application of bias voltage induces a band gap, the magnetic field enhances the density of states (DOS) and the chemical potential modulates the charge carrier concentration, leading to distinct modifications in the electrical and thermal properties across different temperature ranges. The electrical property analysis reveals that the unperturbed structure exhibits metallic behavior. This feature remains unchanged under magnetic field, with increasing field strength leading to significant enhancing DOS spectrum intensity. In contrast, the introduction of voltage bias induces a metal-to-semiconductor transition, with the band gap size being directly correlated to the bias strength. The thermodynamic properties, including electrical and thermal conductivity, Magnetic susceptibility and the Lorenz number, demonstrate distinct responses to external fields, while bias voltage reduces these properties, the magnetic field enhances them. A particularly notable feature in the temperature dependence of thermodynamic functions is emergence a zero-intensity region attributed to the energy gap formation. The occurrence of this zero-intensity temperature region is closely related to field strength, increasing with bias voltage and decreasing with the magnetic field. To optimize thermodynamic performance in the selected structures, the simultaneous application of voltage bias and a magnetic field can be employed, making T-GeNRs promising candidates for nanoelectronic and thermophotonic applications.
{"title":"Tunable field-dependent electronic and thermal conductivity of tetragonal germanene nanoribbons under temperature, chemical potential and external fields","authors":"Somayeh Behzad","doi":"10.1016/j.jmgm.2025.109225","DOIUrl":"10.1016/j.jmgm.2025.109225","url":null,"abstract":"<div><div>This theoretical study investigates the properties of T-GeNRs using tight-binding formalism, Green's function, and the Kubo formula. Our research examines the temperature dependence of thermodynamic functions under varying external parameters, including electric bias and magnetic fields and chemical potential. The application of bias voltage induces a band gap, the magnetic field enhances the density of states (DOS) and the chemical potential modulates the charge carrier concentration, leading to distinct modifications in the electrical and thermal properties across different temperature ranges. The electrical property analysis reveals that the unperturbed structure exhibits metallic behavior. This feature remains unchanged under magnetic field, with increasing field strength leading to significant enhancing DOS spectrum intensity. In contrast, the introduction of voltage bias induces a metal-to-semiconductor transition, with the band gap size being directly correlated to the bias strength. The thermodynamic properties, including electrical and thermal conductivity, Magnetic susceptibility and the Lorenz number, demonstrate distinct responses to external fields, while bias voltage reduces these properties, the magnetic field enhances them. A particularly notable feature in the temperature dependence of thermodynamic functions is emergence a zero-intensity region attributed to the energy gap formation. The occurrence of this zero-intensity temperature region is closely related to field strength, increasing with bias voltage and decreasing with the magnetic field. To optimize thermodynamic performance in the selected structures, the simultaneous application of voltage bias and a magnetic field can be employed, making T-GeNRs promising candidates for nanoelectronic and thermophotonic applications.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109225"},"PeriodicalIF":3.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145556953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Heptazethrene derivatives have garnered significant interest due to their potential applications in photovoltaics and optics. Building on previous studies that explored the structure-property relationship for photovoltaic applications, this research delves into a detailed analysis of infrared spectral examination, electron density difference, and non-covalent interactions. Directly linking optical absorption profiles, oscillator strength, and excited state data, such as dipole moment and transition energy, with linear and nonlinear optical polarizability, it is observed that heptazethrene derivatives exhibit desirable average diradical characteristics. These characteristics enhance the linear polarizability by 30–50 % and the nonlinear polarizability by 6–12 times compared to the reference. This investigation positions heptazethrene derivatives as promising materials to enhance optical and photonic technologies in optoelectronic devices.
{"title":"Quantum chemical investigation of Z-shaped Diradicaloid heptazethrene derivatives towards linear and nonlinear optical polarizability","authors":"Rao Aqil Shehzad , Javed Iqbal , Shaukat Ali , Hafeez Anwar","doi":"10.1016/j.jmgm.2025.109221","DOIUrl":"10.1016/j.jmgm.2025.109221","url":null,"abstract":"<div><div>Heptazethrene derivatives have garnered significant interest due to their potential applications in photovoltaics and optics. Building on previous studies that explored the structure-property relationship for photovoltaic applications, this research delves into a detailed analysis of infrared spectral examination, electron density difference, and non-covalent interactions. Directly linking optical absorption profiles, oscillator strength, and excited state data, such as dipole moment and transition energy, with linear and nonlinear optical polarizability, it is observed that heptazethrene derivatives exhibit desirable average diradical characteristics. These characteristics enhance the linear polarizability by 30–50 % and the nonlinear polarizability by 6–12 times compared to the reference. This investigation positions heptazethrene derivatives as promising materials to enhance optical and photonic technologies in optoelectronic devices.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109221"},"PeriodicalIF":3.0,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145564216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The design and development of efficient and responsive drug carriers always remain a challenge in targeted cancer treatment, where the traditional nanocarriers suffer the drawbacks of limited stability, a lack of selectivity, and slow release of the drug. In this perspective, the oxygenated triaryl methyl (oxTAM) nanocarrier is known for its tunability, and redox activity offers a promising alternative. In the present work, we hypothesize that the oxTAM carrier can function as an efficient and effective drug carrier for selected anticancer drugs like Fludarabine (Flu) and Cytarabine (Cyt) due to its ability to make stable noncovalent interactions and release of drugs in acidic conditions. The potential application of oxTAM as drug carrier is explored by using ωB97XD/6-31+G(d,p) functional. The interaction in energy analysis (Eint) and interacting distances (Edis) reveal that oxTAM shows excellent interaction for Flu (−1.77 eV, 1.92 Å) drug. Non-covalent interaction index (NCI) indicates the existence of van der Waals interaction and hydrogen bonding (O—H bond) between the interacting moieties. The results of dipole moment and quantum chemical descriptors show the high reactivities of oxTAM for Flu and Cyt drugs. Electronic analysis including natural bond orbital (NBO) charge transfer demonstrates the higher response of Flu drug towards oxTAM. In addition, the reduced adsorption stability upon protonation in an acidic environment can quickly release drug molecules from the carrier. Short recovery time indicates easy drug delivery at the targeted site. From all these results, we concluded that oxTAM can be a potential candidate for further experimental exploration in drug delivery systems.
{"title":"Oxo-triaryl methyl (oxTAM) as targeted drug delivery vehicle for fludarabine and cytarabine anticancer drugs: A first-principles insight","authors":"Misbah Asif , Tariq Mahmood , Mazhar Amjad Gilani , Nadeem S. Sheikh , Imene Bayach , Khurshid Ayub","doi":"10.1016/j.jmgm.2025.109224","DOIUrl":"10.1016/j.jmgm.2025.109224","url":null,"abstract":"<div><div>The design and development of efficient and responsive drug carriers always remain a challenge in targeted cancer treatment, where the traditional nanocarriers suffer the drawbacks of limited stability, a lack of selectivity, and slow release of the drug. In this perspective, the oxygenated triaryl methyl (oxTAM) nanocarrier is known for its tunability, and redox activity offers a promising alternative. In the present work, we hypothesize that the oxTAM carrier can function as an efficient and effective drug carrier for selected anticancer drugs like Fludarabine (Flu) and Cytarabine (Cyt) due to its ability to make stable noncovalent interactions and release of drugs in acidic conditions. The potential application of oxTAM as drug carrier is explored by using ωB97XD/6-31+G(d,p) functional. The interaction in energy analysis (E<sub>int</sub>) and interacting distances (E<sub>dis</sub>) reveal that oxTAM shows excellent interaction for Flu (−1.77 eV, 1.92 Å) drug. Non-covalent interaction index (NCI) indicates the existence of van der Waals interaction and hydrogen bonding (O—H bond) between the interacting moieties. The results of dipole moment and quantum chemical descriptors show the high reactivities of oxTAM for Flu and Cyt drugs. Electronic analysis including natural bond orbital (NBO) charge transfer demonstrates the higher response of Flu drug towards oxTAM. In addition, the reduced adsorption stability upon protonation in an acidic environment can quickly release drug molecules from the carrier. Short recovery time indicates easy drug delivery at the targeted site. From all these results, we concluded that oxTAM can be a potential candidate for further experimental exploration in drug delivery systems.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109224"},"PeriodicalIF":3.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145549555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) is a crucial post-transcriptional regulator in mRNA localization, stability, and translation. While IGF2BP3 overexpression is widely studied in cancer, recent evidence highlights its role in diabetic retinopathy (DR), a significant cause of blindness. In DR, IGF2BP3 regulates pro-angiogenic and pro-inflammatory factors, such as VEGF, contributing to retinal vascular damage, neovascularization, and inflammation. These effects make IGF2BP3 a potential therapeutic target for DR. Henceforth, in this study, high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulations were implemented to identify potential IGF2BP3 inhibitors, focusing on its KH3 and KH4 RNA-binding domains. The KH4 domain was selected as the optimal target with a higher druggability score. HTVS of the ChemDiv database identified three promising candidates: Y040–1954, C200-9224, and 1761-0723, which showed strong interactions with the GXXG motif within the KH4 domain, critical for RNA binding. Density Functional Theory (DFT) and molecular docking analysis confirmed these candidates' reactivity and binding affinity to IGF2BP3. MD simulations conducted over 200 ns showed that IGF2BP3-inhibitor complexes retained structural stability with consistent hydrogen bonding, particularly involving key residues Ser624, Ser627, and Thr628. These findings suggest that the identified compounds could disrupt IGF2BP3's interaction with m6A-modified RNA, potentially blocking its role in stabilizing pro-angiogenic and pro-inflammatory mRNAs in DR. With experimental validation and optimization, these compounds could significantly advance the treatment landscape for DR, offering hope for better outcomes in this leading cause of blindness.
{"title":"Mechanistic exploration of IGF2BP3-mediated m6A dynamics in diabetic retinopathy for therapeutic interventions through in silico approaches","authors":"Hemavathy Nagarajan , Nishath Fathima Majid , Sharada Ramasubramanyan , Sampathkumar Ranganathan","doi":"10.1016/j.jmgm.2025.109222","DOIUrl":"10.1016/j.jmgm.2025.109222","url":null,"abstract":"<div><div>Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) is a crucial post-transcriptional regulator in mRNA localization, stability, and translation. While IGF2BP3 overexpression is widely studied in cancer, recent evidence highlights its role in diabetic retinopathy (DR), a significant cause of blindness. In DR, IGF2BP3 regulates pro-angiogenic and pro-inflammatory factors, such as VEGF, contributing to retinal vascular damage, neovascularization, and inflammation. These effects make IGF2BP3 a potential therapeutic target for DR. Henceforth, in this study, high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulations were implemented to identify potential IGF2BP3 inhibitors, focusing on its KH3 and KH4 RNA-binding domains. The KH4 domain was selected as the optimal target with a higher druggability score. HTVS of the ChemDiv database identified three promising candidates: Y040–1954, C200-9224, and 1761-0723, which showed strong interactions with the GXXG motif within the KH4 domain, critical for RNA binding. Density Functional Theory (DFT) and molecular docking analysis confirmed these candidates' reactivity and binding affinity to IGF2BP3. MD simulations conducted over 200 ns showed that IGF2BP3-inhibitor complexes retained structural stability with consistent hydrogen bonding, particularly involving key residues Ser624, Ser627, and Thr628. These findings suggest that the identified compounds could disrupt IGF2BP3's interaction with m6A-modified RNA, potentially blocking its role in stabilizing pro-angiogenic and pro-inflammatory mRNAs in DR. With experimental validation and optimization, these compounds could significantly advance the treatment landscape for DR, offering hope for better outcomes in this leading cause of blindness.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109222"},"PeriodicalIF":3.0,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Angiogenesis is a critical pathway for cancer; The formation of new blood vessels is essential for the growth and metastasis of tumors. VEGF and its receptor VEGFR also play important roles in angiogenesis. VEGFR2 stands out as an important therapeutic target for breast cancer treatment. In this study, the interaction between benzopyrazine derivatives and VEGFR2 was evaluated using computer-based drug design (CADD) models, bioinformatics analyses and complementary computational methods. Biological activity predictions were made by developing the interaction data of 49 benzopyrazine-derived compounds in a virtual environment and by developing a QSAR model. Binding stability of proteins in newly designed structures was demonstrated with molecular dynamics simulations. ADMET predictions reveal that these tables have appropriate pharmacokinetic metabolism. Synthesizability of compounds with the best docking scores was calculated with artificial intelligence using the Retroscheme software. For compound number 46, which has the highest potential, molecular dynamics simulation data for 500 ns were calculated via the Desmond interface and its binding was interpreted. The study particularly shows that compound 46 may be an effective VEGFR2 inhibitor in the treatment of breast cancer.
{"title":"In silico investigation of the efficacy of benzopyrazine derivatives on breast cancer by VEGFR2 inhibition using ML/DL based CADD software","authors":"İrem Bozbey Merde , Okan Aykaç , Ceylan Hepokur , Muzammil Kabi̇er , Ahmet Buğra Ortaakarsu","doi":"10.1016/j.jmgm.2025.109219","DOIUrl":"10.1016/j.jmgm.2025.109219","url":null,"abstract":"<div><div>Angiogenesis is a critical pathway for cancer; The formation of new blood vessels is essential for the growth and metastasis of tumors. VEGF and its receptor VEGFR also play important roles in angiogenesis. VEGFR2 stands out as an important therapeutic target for breast cancer treatment. In this study, the interaction between benzopyrazine derivatives and VEGFR2 was evaluated using computer-based drug design (CADD) models, bioinformatics analyses and complementary computational methods. Biological activity predictions were made by developing the interaction data of 49 benzopyrazine-derived compounds in a virtual environment and by developing a QSAR model. Binding stability of proteins in newly designed structures was demonstrated with molecular dynamics simulations. ADMET predictions reveal that these tables have appropriate pharmacokinetic metabolism. Synthesizability of compounds with the best docking scores was calculated with artificial intelligence using the Retroscheme software. For compound number 46, which has the highest potential, molecular dynamics simulation data for 500 ns were calculated via the Desmond interface and its binding was interpreted. The study particularly shows that compound 46 may be an effective VEGFR2 inhibitor in the treatment of breast cancer.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109219"},"PeriodicalIF":3.0,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145523644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-08DOI: 10.1016/j.jmgm.2025.109218
Ali Harchani
A first study of the organic solvents influence on the organo-halides such as chloromercurate, chlorostannate and chlorocadmate compounds by using a new theoretical method was reported in the present work. A lot of discussions concerning the solvation properties, sorption, adsorption simulation and blends mixing analysis have been presented in this paper to show the interesting role of the organic solvents and their impact in the chemistry of the organo-metal halides and organo-mercuric halides compounds. The results of chemical calculations leads to conclude that solvents such as water, dimethyl sulfoxide, acetonitrile, ethanol, methylene chloride and diethyl ether are very important for the solvation and chemical synthesis of the title compounds but to varying degrees.
{"title":"The first study of the organic solvents influence on the organo-halides compounds using a new theoretical approach of solvation properties","authors":"Ali Harchani","doi":"10.1016/j.jmgm.2025.109218","DOIUrl":"10.1016/j.jmgm.2025.109218","url":null,"abstract":"<div><div>A first study of the organic solvents influence on the organo-halides such as chloromercurate, chlorostannate and chlorocadmate compounds by using a new theoretical method was reported in the present work. A lot of discussions concerning the solvation properties, sorption, adsorption simulation and blends mixing analysis have been presented in this paper to show the interesting role of the organic solvents and their impact in the chemistry of the organo-metal halides and organo-mercuric halides compounds. The results of chemical calculations leads to conclude that solvents such as water, dimethyl sulfoxide, acetonitrile, ethanol, methylene chloride and diethyl ether are very important for the solvation and chemical synthesis of the title compounds but to varying degrees.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109218"},"PeriodicalIF":3.0,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145495769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Novel antineoplastic therapies focus on the inhibition of various protein kinases, creating an important need for new molecules capable of regulating their abnormal activity. Here, we introduce a specific hybrid Machine Learning (ML) architecture that combines an eXtreme Gradient Boosting (XGBoost) as a base model, and a deep neural network (DNN) to improve prediction accuracy in kinase inhibition QSARs. The approach utilizes XGBoost to process structured data features, while employing the DNN to refine and calibrate the probability estimates. The predictive probabilities from XGBoost are incorporated as new input features for a DNN to enhance classification performance. For the prediction of kinase inhibition, 40 reliable QSAR models were trained on large datasets (559–5675 compounds and 400–500 descriptors). As a result, the approach achieved a marked improvement in accuracy and robustness compared to the standalone XGBoost algorithm and various descriptors-based state-of-the-art methods, including Random Forest (RF) and Support Vector Machine (SVM). The accuracy enhancement reaches up to 14% for JAK2, BRAF and TRK-, 13% for VEGFR2 and PIK3C, and ranges between 5 and 12% for 30 other kinase datasets. Performance is thus analyzed through the discussion of several evaluation metrics. The proposed method will be useful for building accurate prediction models, either specific to the neoplastic drug design or QSAR modeling in general. Models constructed in this study are available at GitHub.
{"title":"Enhancing predictive modeling with XGBoost-engineered probabilities and deep neural networks: A hybrid approach for building reliable kinase inhibition QSAR models","authors":"Mohamed Oussama Mousser , Brahim Matougui , Fouad Chafaa , Mohamed Abdesselem Dems","doi":"10.1016/j.jmgm.2025.109216","DOIUrl":"10.1016/j.jmgm.2025.109216","url":null,"abstract":"<div><div>Novel antineoplastic therapies focus on the inhibition of various protein kinases, creating an important need for new molecules capable of regulating their abnormal activity. Here, we introduce a specific hybrid Machine Learning (ML) architecture that combines an eXtreme Gradient Boosting (XGBoost) as a base model, and a deep neural network (DNN) to improve prediction accuracy in kinase inhibition QSARs. The approach utilizes XGBoost to process structured data features, while employing the DNN to refine and calibrate the probability estimates. The predictive probabilities from XGBoost are incorporated as new input features for a DNN to enhance classification performance. For the prediction of kinase inhibition, 40 reliable QSAR models were trained on large datasets (559–5675 compounds and <span><math><mo>∼</mo></math></span> 400–500 descriptors). As a result, the approach achieved a marked improvement in accuracy and robustness compared to the standalone XGBoost algorithm and various descriptors-based state-of-the-art methods, including Random Forest (RF) and Support Vector Machine (SVM). The accuracy enhancement reaches up to 14% for JAK2, BRAF and TRK-<span><math><mi>α</mi></math></span>, 13% for VEGFR2 and PIK3C<span><math><mi>δ</mi></math></span>, and ranges between 5 and 12% for 30 other kinase datasets. Performance is thus analyzed through the discussion of several evaluation metrics. The proposed method will be useful for building accurate prediction models, either specific to the neoplastic drug design or QSAR modeling in general. Models constructed in this study are available at <span><span>GitHub</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"142 ","pages":"Article 109216"},"PeriodicalIF":3.0,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145495819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-08DOI: 10.1016/j.jmgm.2025.109213
Changwei Ge , Haojing Li , Chaochun Wei , Xiaokun Zhang , Hong Yan
Eleven 1,4-dihydropyrazine derivatives were selected for theoretical investigation into the structural effects on photophysical properties and photochemical reactivity using Density Functional Theory (DFT) and Time-Dependent Density Functional Theory (TDDFT). They are divided into three distinct Series (1–3), each characterized by a unique substitution pattern: Series 1 features different acyl groups attached to the N,N′ - positions of the 1,4-dihydropyrazine ring; Series 2 includes various substituents on the 1,4-dihydropyrazine ring itself; and Series 3 combines modifications on both the nitrogen atoms and the 1,4-dihydropyrazine ring. All ground-state geometries were optimized at the M06-2XD3/def2-TZVP level to ensure structural stability, and vibrational frequency analysis was performed to confirm the absence of imaginary frequencies. Simulated ultraviolet–visible (UV–Vis) absorption spectra were used to characterize the electronic excitation behavior. Molecular orbital diagrams (HOMO–1, HOMO, LUMO, and LUMO+1) corresponding to the first singlet excited-state (S1) were analyzed to elucidate the property of the electronic transitions. Electron-hole analysis was applied to qualitatively assess the direction of charge transfer upon excitation. Additionally, the electron localization function (ELF) was calculated to evaluate how substituents and conjugation affect electron distribution within the molecule. The root-mean-square deviation (RMSD) between the excited-state and ground-state geometries was also calculated to quantify structural changes induced by excitation. Collectively, these analyses provide valuable insights into how structural modifications affect the photophysical properties of 1,4-dihydropyrazines and their subsequent photochemical reactivity. All the findings are intended to provide theoretical basis for understanding the experimental observations related to the photocycloaddition reactions of 1,4-dihydropyrazines.
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