سجاد قرقانی

1. DNA binding, and apoptosis-inducing activities of a β-ionone-derived ester in human myeloid leukemia cells: multispectral and molecular dynamic simulation analyses

Jahanbakhsh Kamran، Ansari-Ahl Ramin، Mashhadi Benyamin، Zare Monireh، Sedghi Samarkhazan Nastaran، Kazemzadeh Hamid، Dehghan Gholamreza، Farajzadeh Dehkordi Mahvash، Gharaghani Sajjad، Majeid Mahdavi (2024)., Scientific Reports, 14(1).

2. Enhancing nutritional and potential antimicrobial properties of poultry feed through encapsulation of metagenome-derived multi-enzymes

Ariaeenejad Shohreh، Zeinalabedini Mehrshad، Sadeghi Akram، Gharaghani Sajjad، Mardi Mohsen (2024)., BMC BIOTECHNOLOGY, 24(1).

3. Targeting lon protease to inhibit persister cell formation in Salmonella Typhimurium: a drug repositioning approach

Narimisa Negar، Razavi Shabnam، Khoshbayan Amin، Gharaghani Sajjad، Masjedian Jazi Faramarz (2024)., Frontiers in Cellular and Infection Microbiology, 14(1).

4. Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme

Khachatryan Hamlet، Matevosyan Mher، Harutyunyan Vardan، Gevorgyan Smbat، Shavina Anastasiya، Tirosyan Irina، Gabrielyan Yeva، Ayvazyan Marusya، Bozdaganyan Marine، Fakhar Zeynab، Gharaghani Sajjad، Zakaryan Hovakim (2024)., Scientific Reports, 14(1).

5. Evaluation of antibacterial, cytotoxicity, and apoptosis activity of novel chromene-sulfonamide hybrids synthesized under solvent-free conditions and 3D-QSAR modeling studies

Ghomashi Shakila، Ghomashi Reihane، Damavandi Mohammad Sadegh، Fakhar Zeynab، Mousavi Seyedeh Yasaman، Salari-Jazi Azhar، Gharaghani Sajjad، Massah Ahmad Reza (2024)., Scientific Reports, 14(1).

6. Next-generation computational methods for peptide design

Gharaghani Sajjad (2024)., Iran’s 5th Conference on Protein and Peptide Science, 8-9 May, Tehran, Iran.

7. A comparative analysis of computational drug repurposing approaches: proposing a novel tensor-matrix-tensor factorization method

Zabihian Arash، Asghari Javad، Hooshmand Mohsen، Gharaghani Sajjad (2024)., MOLECULAR DIVERSITY, 1(1).

8. Docking-Based Virtual Screening Method for Selecting Natural Compounds with Synergistic Inhibitory Effects Against Cancer Signalling Pathways Using a Multi-Target Approach

Sardarpour Negar، Goodarzi Zahra، Gharaghani Sajjad (2024)., Iranian Journal of Biotechnology, 22(2).

1. CCL-DTI: contributing the contrastive loss in drug–target interaction prediction

Dehghan Alireza، Abbasi Karim، Razzaghi Parvin، Banadkuki Hossein، Gharaghani Sajjad (2024)., BMC BIOINFORMATICS, 25(1).

2. Revealing key structural features for developing new agonists targeting δ opioid receptor: Combined machine learning and molecular modeling perspective

Fakhar Zeynab، Hosseinpouran Ali، Munro Orde Q.، Sarmadi Sorena، Gharaghani Sajjad (2024)., Medicine in Drug Discovery, 21(1), 100176.

3. A Molecular Generative Model of COVID-19 Main Protease Inhibitors Using Long Short-Term Memory-Based Recurrent Neural Network

Mehrzadi Arash، Rezaee Elham، Gharaghani Sajjad، Fakhar Zeynab، Mirhosseini Seyed Mohsen (2024)., JOURNAL OF COMPUTATIONAL BIOLOGY, 31(1), 83-98.

4. TripletMultiDTI: Multimodal representation learning in drug-target interaction prediction with triplet loss function

Dehghan Alireza، Razzaghi Parvin، Abbasi Karim، Gharaghani Sajjad (2023)., EXPERT SYSTEMS WITH APPLICATIONS, 232(1), 120754.

5. In silico studies of anti-oxidative and hot temperament-based phytochemicals as natural inhibitors of SARS-CoV-2 Mpro

Naderi Beni Ramin، Elyasi-Ebli Parisa، Gharaghani Sajjad، Seyedarabi Arefeh (2023)., PLoS One, 18(11), e0295014.

6. DEDTI versus IEDTI: efficient and predictive models of drug-target interactions

Zabihian Arash، Zakaryapour Sayyad Faeze، Hashemi Seyyed Morteza، Shami Tanha Reza، Hooshmand Mohsen، Gharaghani Sajjad (2023)., Scientific Reports, 13(1).

7. Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies

Yazdani Mohsen، Jafari Ameneh، Mahdian Soodeh، Namazi Mohsen، Gharaghani Sajjad (2023)., JOURNAL OF MOLECULAR LIQUIDS, 375(1), 121345.

1. Virtual screening reveals aprepitant to be a potent inhibitor of neutral sphingomyelinase 2: implications in blockade of exosome release in cancer therapy

Moloudizargari Milad، Hekmatirad Shirin، Gharaghani Sajjad، Moghadamnia Ali Akbar، Najafzadehvarzi Hossein، Asghari Mohammad Hossein (2023)., JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 149(10), 7207-7216.

2. New insights into the inhibitory effect of phenol carboxylic acid antioxidants on mushroom tyrosinase by molecular dynamic studies and experimental assessment

Shojazadeh Tahereh، Zolghadr Leila، Gharaghani Sajjad، JafarKhani Saeed، Molaabasi Fatemeh، Piri Hossein، Gheibi Nematollah (2023)., JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 1(1), 1-11.

3. Finding a genomic pattern for classifying breast cancer patients by Random Forest and Linear Discriminant Analysis and cancer-specific biomarkers by Integrative analysis of DNA methylation and gene expression

Norouzi Romina، Gharaghani Sajjad (2023)., 2nd International & 11th Iranian Conference on Bioinformatics, 28 February-1 March, Tehran, Iran.

4. Using Proteochemometrics models to predict interaction between isoforms of caspase and their inhibitors

Bastami Zahra، Sheikhpour Razieh، Razzaghi Parvin، Ramazani Ali، Gharaghani Sajjad (2023)., 2nd International & 11th Iranian Conference on Bioinformatics, 28 February-1 March, Tehran, Iran.

5. DRaW: prediction of COVID-19 antivirals by deep learning—an objection on using matrix factorization

Hashemi S. Morteza، Zabihian Arash، Hooshmand Mohsen، Gharaghani Sajjad (2023)., BMC BIOINFORMATICS, 24(1).

6. Identification of new potent agonists for toll-like receptor 8 by virtual screening methods, molecular dynamics simulation, and MM-GBSA

Sadeghkhani Farideh، Hajihassan Zahra، Gharaghani Sajjad (2022)., JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, ****(****), 1-11.

7. Identification of repurposed drugs targeting significant long non-coding RNAs in the cross-talk between diabetes mellitus and Alzheimer’s disease

Ghiam Shokoofeh، Eslahchi Changiz، Shahpasand Koorosh، Habibi Rezaei Mehran، Gharaghani Sajjad (2022)., Scientific Reports, 12(1).

8. Exploring the role of non-coding RNAs as potential candidate biomarkers in the cross-talk between diabetes mellitus and Alzheimer’s disease

Ghiam Shokoofeh، Eslahchi Changiz، Shahpasand Koorosh، Habibi Rezaei Mehran، Gharaghani Sajjad (2022)., Frontiers in Aging Neuroscience, 14(1).

9. Matrix factorization with denoising autoencoders for prediction of drug–target interactions

Sajadi Zahra، ZareChahooki MohammadAli، Tavakol Maryam، Gharaghani Sajjad (2022)., MOLECULAR DIVERSITY, 1(1).

10. Drug-target interaction prediction using reliable negative samples and effective feature selection methods

Morovvati Mohammad، Sheikhpour Razieh، Gharaghani Sajjad (2022)., JOURNAL OF PHARMACOLOGICAL AND TOXICOLOGICAL METHODS, 116(1), 107191.