In silico pharmacology最新文献

{"title":"Protein-protein interaction network study of metallo-beta-lactamase-L1 present in <i>Stenotrophomonas maltophilia</i> and identification of potential drug targets.","authors":"K H Sreenithya, Shobana Sugumar","doi":"10.1007/s40203-024-00270-9","DOIUrl":"10.1007/s40203-024-00270-9","url":null,"abstract":"<p><p>Microorganisms are evolving to withstand the effect of antimicrobial agents and thereby pose a global threat known as antimicrobial resistance. Resistance towards multiple drugs due to various intrinsic as well environmental factors leads to an even more dangerous drug resistance property known as multi-drug resistance (MDR). WHO has recognized MDR bacteria as a top global threat as they complicate the treatment and augment mortality and morbidity risks. Gram-negative bacteria produce beta-lactamase enzymes that can hydrolyze beta-lactam antibiotics, impacting drug susceptibility. <i>Stenotrophomonas maltophilia</i>, an opportunistic pathogen, exemplifies MDR due to the production of two types of beta-lactamases. The metallo-beta-lactamase (MBL) L1 produced by the bacteria is a class B1 zinc-dependent MBL that is broadly substrate-specific and is a challenge to the currently available treatment options. This study constructs and analyzes a protein-protein interaction network of L1 beta-lactamase to comprehend its role in the MDR property of the bacteria. The network encompasses 51 proteins including L1 MBL (Smlt2667) and 382 interactions, revealing key players in MDR and potential drug targets. The network analysis aids the discernment of antimicrobial gene impact on cellular function, informing drug discovery strategies. This research addresses the emerging challenge of antibiotic resistance and identifies pathways for therapeutic intervention.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00270-9.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"94"},"PeriodicalIF":0.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11519282/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142549790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A pan-genomic analysis based multi-epitope vaccine development by targeting <i>Stenotrophomonas maltophilia</i> using reverse vaccinology method: an in-silico approach.","authors":"Md Hasan Jafre Shovon, Md Imtiaz, Partha Biswas, Md Mohaimenul Islam Tareq, Md Nazmul Hasan Zilani, Md Nazmul Hasan","doi":"10.1007/s40203-024-00271-8","DOIUrl":"10.1007/s40203-024-00271-8","url":null,"abstract":"<p><p>Antibiotic resistance in bacteria leads to high mortality rates and healthcare costs, a significant concern for public health. A colonizer of the human respiratory system, <i>Stenotrophomonas maltophilia</i> is frequently associated with hospital-acquired infections in individuals with cystic fibrosis, cancer, and other chronic illnesses. The importance of this study is underscored by its capacity to meet the critical demand for effective preventive strategies against this pathogen, particularly among susceptible groups of cystic fibrosis and those undergoing cancer treatment. In this study, we engineered a multi-epitope vaccine targeting <i>S. maltophilia</i> through genomic analysis, reverse vaccination strategies, and immunoinformatic techniques by examining a total of 81 complete genomes of S. maltophilia strains. Our investigation revealed 1945 core protein-coding genes alongside their corresponding proteomic sequences, with 191 of these genes predicted to exhibit virulence characteristics. Out of the filtered proteins, three best antigenic proteins were selected for epitope prediction while seven epitopes each from CTL, HTL, and B cell were chosen for vaccine development. The vaccine was refined and validated, showing highly antigenic and desirable physicochemical features. Molecular docking assessments revealed stable binding with TLR-4. Molecular dynamic simulation demonstrated stable dynamics with minor alterations. The originality of this investigation is rooted in the thorough techniques aimed at designing a vaccine that directly targets <i>S. maltophilia</i>, a microorganism of considerable clinical relevance that currently lacks an available vaccine. This study not only responds to a pressing public health crisis but also lays the groundwork for subsequent research endeavors focused on the prevention of <i>S. maltophilia</i> outbreaks. Further evidence from studies in mice models is needed to confirm immune protection against <i>S. maltophilia</i>.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"93"},"PeriodicalIF":0.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142515310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"First report on exploration of structural features of natural compounds (NPACT database) for anti-breast cancer activity (MCF-7): QSAR-based virtual screening, molecular docking, ADMET, MD simulation, and DFT studies.","authors":"Lomash Banjare, Anjali Murmu, Nilesh Kumar Pandey, Balaji Wamanrao Matore, Purusottam Banjare, Arijit Bhattacharya, Shovanlal Gayen, Jagadish Singh, Partha Pratim Roy","doi":"10.1007/s40203-024-00266-5","DOIUrl":"10.1007/s40203-024-00266-5","url":null,"abstract":"<p><p>Due to the high toxicity, poor efficacy and resistance associated with current anti-breast cancer drugs, there's growing interest in natural products (NPs) for their potential anti-cancer properties. Computational modelling of NPs to identify key structural features can aid in developing novel natural inhibitors. In this study, we developed statistically significant QSAR models based on NPs from the NPACT database, which have shown potential anticancer activity against the MCF-7 cancer cell lines. All the developed QSAR models were statistically robust, meeting both internal (<i>R</i> ^<i>2</i>  = 0.666-0.669, <i>R</i> ^<i>2</i> _<i>adj</i>  = 0.657-0.660, <i>Q</i> ^<i>2</i> _<i>Loo</i>  = 0.636-0.638) and external (<i>Q</i> ^<i>2</i> <i>F</i> _<i>n</i>  = 0.686-0.714, <i>CCC</i> _<i>ext</i> = 0.830-0.847) validation criteria. Consequently, they were utilized to virtually screen a series of NPs from the COCONUT database in the search for novel natural inhibitors. Molecular docking studies were conducted on the identified compounds against the human HER2 protein (PDB ID: 3PP0), which is a crucial target in breast cancer. Molecular docking analysis demonstrated that compounds 4608 and 2710 achieved the highest docking scores, with CDOCKER interaction energies of -72.67 kcal/mol and - 72.63 kcal/mol respectively. Compounds 4608 and 2710 were identified as the most promising candidates upon performing triplicate 100 ns MD simulation study using the CHARMM36 force field. DFT studies was performed to evaluate their stability and reactivity as potential drug molecules. This research contributes to the development of new natural inhibitors for breast cancer.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00266-5.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"92"},"PeriodicalIF":0.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11490471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network analysis and molecular modeling studies of pinocembrin a bioactive phytochemical of <i>Dodonaea viscosa</i> against Parkinson's disease.","authors":"Mohana Priya, Azar Zochedh, Yoga Soundarya Mohan, Kaliraj Chandran, Karthick Arumugam, Asath Bahadur Sultan","doi":"10.1007/s40203-024-00268-3","DOIUrl":"https://doi.org/10.1007/s40203-024-00268-3","url":null,"abstract":"<p><p>Parkinson's disease, a neurodegenerative disorder, is quickly progressing and accounts for 15% of dementia cases. Parkinson's disease is the second most frequent form of neuronal degeneration after Alzheimer's, with an average age of 55 years for individuals exhibiting neuropsychiatric and physiological symptoms. Due to the effectiveness, low toxicity, and low side effects, bioactive compounds from plants have received increased attention recently as therapeutic drugs. In the current study, effective anti-neurodegenerative phytochemicals from <i>Dodonaea viscosa</i> were screened using in silico methods and have been proposed to be further investigated for the treatment of Parkinson's disease. The structures of twenty bioactive chemicals were screened and graph theoretical network analysis revealed alpha-synuclein as a potent therapeutic target. Based on docking scores, an effective bioactive molecule was selected, and its energy values, electrostatic potential surface and drug-like qualities were examined using molecular orbitals, pharmacokinetics and toxicity studies. Pinocembrin was found as a superior binder based on molecular docking as it demonstrated stronger binding with - 10.2 kcal/mol. An investigation using Ramachandran plot validated the protein-ligand complex secondary structure's stability. Pinocembrin, a bioactive phytochemical from <i>Dodonaea viscosa</i>, may be a viable lead molecule that may be developed as a candidate medicine for anti-neurodegenerative therapy against Parkinson's disease.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"91"},"PeriodicalIF":0.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11466969/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational targeting of iron uptake proteins in Covid-19 induced mucormycosis to identify inhibitors via molecular dynamics, molecular mechanics and density function theory studies.","authors":"Manjima Sen, B M Priyanka, D Anusha, S Puneetha, Anagha S Setlur, Chandrashekar Karunakaran, Amulya Tandur, C S Prashant, Vidya Niranjan","doi":"10.1007/s40203-024-00264-7","DOIUrl":"10.1007/s40203-024-00264-7","url":null,"abstract":"<p><p>Mucormycosis is a concerning invasive fungal infection with difficult diagnosis, high mortality rates, and limited treatment options. Iron availability is crucial for fungal growth that causes this disease. This study aimed to computationally target iron uptake proteins in <i>Rhizopus arrhizus, Lichtheimia corymbifera,</i> and <i>Mucor circinelloides</i> to identify inhibitors, thereby halting fungal growth and intervening in mucormycosis pathogenesis. Seven important iron uptake proteins were identified, modeled, and validated using Ramachandran plots. An in-house antifungal library of ~ 15,401 compounds was screened in molecular docking studies with these proteins. The best small molecule-protein complexes were simulated at 100 ns using Maestro, Schrodinger. Toxicity predictions suggested all six molecules, identified as the best binding compounds to seven proteins, belonged to lower toxicity levels per GHS classification. A molecular mechanics GBSA study for all seven complexes indicated low standard deviations after calculating free binding energies every 10 ns of the 100 ns trajectory. Density functional theory via quantum mechanics approaches highlighted the HOMO, LUMO, and other properties of the six best-bound molecules, revealing their binding capabilities and behaviour. This study sheds light on the molecular mechanisms and protein-ligand interactions, providing a multi-dimensional view towards the use of FDBD01920, FDBD01923, and FDBD01848 as stable antifungal ligands.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00264-7.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"90"},"PeriodicalIF":0.0,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142362601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular docking and dynamics simulation of farnesol as a potential anticancer agent targeting mTOR pathway.","authors":"Tabasum Ali, Ifat Jan, Rajath Ramachandran, Rabiah Bashir, Khurshid Iqbal Andrabi, Ghulam Nabi Bader","doi":"10.1007/s40203-024-00259-4","DOIUrl":"10.1007/s40203-024-00259-4","url":null,"abstract":"<p><p>Farnesol is a natural acyclic sesquiterpene alcohol, found in various essential oils such as, lemon grass, citronella, tuberose, neroli, and musk. It has a molecular mass of 222.372 g/mol and chemical formula of C₁₅H₂₆O. The main objective of this study was to assess the effect of farnesol on mTOR and its two downstream effectors, p70S6K and eIF4E, which are implicated in the development of cancer, via molecular dynamic simulation, and docking analysis in an in silico study. A multilayer, primarily computer-based analysis was conducted to assess farnesol's anticancer potential, with a focus on primary cancer targets. From the calculations performed, farnesol showed a binding affinity of - 9.66 kcal/mol, followed by binding affinity of - 7.4 kcal/mol and - 7.8 kcal/mol for mTOR, p70S6K and eIF4E respectively. Rapamycin showed the binding affinity of - 10.45 kcal/mol for mTOR, for p70S6K and eIF4E the calculated binding affinity was - 10.65 kcal/mol and 8.16 kcal/mol respectively. The binding affinity of farnesol was comparable to the standard drug rapamycin indicating its potential as an mTOR inhibitor. Molecular dynamics simulations suggest that the ligands (farnesol and rapamycin) were well trapped within the active site of the protein over a time gap of 50 ns. It is clear that farnesol showed relatively stable MD simulation results, with minor fluctuations and maintains a consistent binding orientation, suggesting a strong and stable interaction with the target proteins when compared to simulation data of standard drug. This study explores the potential of farnesol as an anticancer agent through an in-silico approach, focusing on its interaction with mTOR and its downstream effectors. Inhibition of mTOR signaling pathway may be responsible for the anticancer effect of farnesol. As this pathway plays a crucial role in cell proliferation and survival, making it a significant target in cancer research.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"89"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438742/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative multi-target analysis of <i>Urtica dioica</i> for gout arthritis treatment: a network pharmacology and clustering approach.","authors":"Maryam Qasmi, Muhammad Mazhar Fareed, Haider Ali, Zarmina Khan, Sergey Shityakov","doi":"10.1007/s40203-024-00254-9","DOIUrl":"10.1007/s40203-024-00254-9","url":null,"abstract":"<p><p><i>Urtica dioica</i> (stinging nettle) has been traditionally used in Chinese medicine for the treatment of joint pain and rheumatoid arthritis. This study aims to elucidate the active compounds and mechanisms by which it acts against gout arthritis (GA). Gout-related genes were identified from the DisGeNet, GeneCards, and OMIM databases. These genes may play a role in inhibiting corresponding proteins targeted by the active compounds identified from the literature, which have an oral bioavailability of ≥ 30% and a drug-likeness score of ≥ 0.18. A human protein-protein interaction network was constructed, resulting in sixteen clusters containing plant-targeted genes, including ABCG2, SLC22A12, MAP2K7, ADCY10, RELA, and TP53. The key bioactive compounds, apigenin-7-O-glucoside and kaempferol, demonstrated significant binding to SLC22A12 and ABCG2, suggesting their potential to reduce uric acid levels and inflammation. Pathway enrichment analysis further identified key metabolic pathways involved, highlighting a dual mechanism of anti-inflammatory and urate-lowering effects. These findings underscore the potential of <i>U. dioica</i> in targeting multiple pathways involved in GA, combining traditional medicine with modern pharmacology. This integrated approach provides a foundation for future research and the development of multi-target therapeutic strategies for managing gout arthritis.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00254-9.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"88"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438756/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico fragment-based design and pharmacophore modelling of therapeutics against dengue virus envelope protein.","authors":"Dwaipayan Chaudhuri, Satyabrata Majumder, Joyeeta Datta, Kalyan Giri","doi":"10.1007/s40203-024-00262-9","DOIUrl":"10.1007/s40203-024-00262-9","url":null,"abstract":"<p><p>Dengue virus, an arbovirus of genus Flavivirus, is an infectious disease causing organisms in the tropical environment leading to numerous deaths every year. No therapeutic is available against the virus till date with only symptomatic relief available. Here, we have tried to design therapeutic compounds from scratch by fragment based method followed by pharmacophore based modelling to find suitable similar structure molecules and validated the same by MD simulation, followed by binding energy calculations and ADMET analysis. The receptor binding region of the dengue envelope protein was considered as the target for prevention of viral host cell entry and thus infection. This resulted in the final selection of kanamycin as a stable binding molecule against the Dengue virus envelope protein receptor binding domain. This study results in selection of a single molecule having high binding energy and prominent stable interactions as determined by post simulation analyses. This study aims to provide a direction for development of small molecule therapeutics against the dengue virus in order to control infection. This study may open a new avenue in the arena of structure based and fragment based therapeutic design to obtain novel molecules with therapeutic potential.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00262-9.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"87"},"PeriodicalIF":0.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11415559/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Marine natural compounds as potential CBP bromodomain inhibitors for treating cancer: an in-silico approach using molecular docking, ADMET, molecular dynamics simulations and MM-PBSA binding free energy calculations.","authors":"Md Liakot Ali, Fabiha Noushin, Eva Azme, Md Mahmudul Hasan, Neamul Hoque, Afroz Fathema Metu","doi":"10.1007/s40203-024-00258-5","DOIUrl":"10.1007/s40203-024-00258-5","url":null,"abstract":"<p><p>The cAMP-responsive element binding protein (CREB) binding protein (CBP), a bromodomain-containing protein, engages with multiple transcription factors and enhances the activation of many genes. CBP bromodomain acts as an epigenetic reader and plays an important role in the CBP-chromatin interaction which makes it an important drug target for treating many diseases. Though inhibiting CBP bromodomain was reported to have great potential in cancer therapeutics, approved CBP bromodomain inhibitor is yet to come. We utilized various in silico approaches like molecular docking, ADMET, molecular dynamics (MD) simulations, MM-PBSA calculations, and in silico PASS predictions to identify potential CBP bromodomain inhibitors from marine natural compounds as they have been identified as having distinctive chemical structures and greater anticancer activities. To develop a marine natural compound library for this investigation, Lipinski's rule of five was used. Sequential investigations utilizing molecular docking, ADMET studies, 100 ns MD simulations, and MM-PBSA calculations revealed that three marine compounds-ascididemin, neoamphimedine, and stelletin A-demonstrated superior binding affinity compared to the standard inhibitor, 69 A. These compounds also exhibited suitable drug-like properties, a favorable safety profile, and formed stable protein-ligand complexes. The in-silico PASS tool predicted that these compounds have significant potential for anticancer activity. Among them, ascididemin demonstrated the highest binding affinity in both molecular docking and MM-PBSA calculations, as well as a better stability profile in MD simulations. Hence, ascididemin can be a potential inhibitor of CBP bromodomain. However, in vitro and in vivo validation is required for further confirmation of these findings.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00258-5.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"85"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11411048/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of therapeutic potential of the Il24-p20 fusion protein against breast cancer: an in-silico approach.","authors":"Shahnila Qureshi, Nadeem Ahmed, Hafiz Muhammad Rehman, Muhammad Imran Amirzada, Fiza Saleem, Kainat Waheed, Afeefa Chaudhry, Iram Kafait, Muhammad Akram, Hamid Bashir","doi":"10.1007/s40203-024-00252-x","DOIUrl":"https://doi.org/10.1007/s40203-024-00252-x","url":null,"abstract":"<p><p>Targeted delivery of therapeutic anticancer chimeric molecules enhances drug efficacy. Numerous studies have focused on developing novel treatments by employing cytokines, particularly interleukins, to inhibit the growth of cancer cells. In the present study, we fused interleukin 24 with the tumor-targeting peptide P20 through a rigid linker to selectively target cancer cells. The secondary structure, tertiary structure, and physicochemical characteristics of the constructed chimeric IL-24-P20 protein were predicted by using bioinformatics tools. In-silico analysis revealed that the fusion construct has a basic nature with 175 amino acids and a molecular weight of 20 kDa. By using the Rampage and ERRAT2 servers, the validity and quality of the fusion protein were evaluated. The results indicated that 93% of the chimeric proteins contained 90.1% of the residues in the favoured region, resulting in a reliable structure. Finally, docking and simulation studies were conducted via ClusPro and Desmond Schrödinger, respectively. Our results indicate that the constructed fusion protein exhibits excellent quality, interaction capabilities, validity, and stability. These findings suggest that the fusion protein is a promising candidate for targeted cancer therapy.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"84"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11408464/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142304819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}