S. Gharaghani

发表

Docking, molecular dynamics simulation studies, and structure-based QSAR model on cytochrome P450 2A6 inhibitors

S. Gharaghani, T. Khayamian, F. Keshavarz, 2012, Structural Chemistry.

A novel proteochemometrics model for predicting the inhibition of nine carbonic anhydrase isoforms based on supervised Laplacian score and k-nearest neighbour regression

M. A. Sarram, S. Gharaghani, E. Nazarshodeh, 2018, SAR and QSAR in environmental research.

Constraint score for semi-supervised feature selection in ligand-and receptor-based QSAR on serine/threonine-protein kinase PLK3 inhibitors

S. Gharaghani, R. Sheikhpour, M. Sarram, 2017 .

Chemometric studies of thymol binding with bovine serum albumin: A developing strategy for the successful investigation of pharmacological activity.

Sajjad Gharaghani, Ali Benvidi, S. Gharaghani, 2018, Bioelectrochemistry.

Spectrophotometric determination of synthetic colorants using PSO-GA-ANN.

Sajjad Gharaghani, Ali Benvidi, S. Gharaghani, 2017, Food chemistry.

New insights into the efficiency of thymol synergistic effect with p-cymene in inhibiting advanced glycation end products: A multi-way analysis based on spectroscopic and electrochemical methods in combination with molecular docking study.

S. Gharaghani, A. Benvidi, Saleheh Abbasi, 2018, Journal of pharmaceutical and biomedical analysis.

An in-depth view of potential dual effect of thymol in inhibiting xanthine oxidase activity: Electrochemical measurements in combination with four way PARAFAC analysis and molecular docking insights.

S. Gharaghani, A. Saboury, A. Benvidi, 2018, International journal of biological macromolecules.

Novel insights into the effect of folate–albumin binding on the transport of ascorbic acid as an anticancer agent: chemometric analysis based on combined spectroscopic and electrochemical studies

S. Gharaghani, A. Benvidi, Saleheh Abbasi, 2018 .

Interactions between Activin-Like Kinase 5 (ALK5) receptor and its inhibitors and the construction of a Docking Descriptor-Based QSAR model

S. Gharaghani, T. Khayamian, M. Ebrahimi, 2012 .

Molecular dynamics simulation study and molecular docking descriptors in structure-based QSAR on acetylcholinesterase (AChE) inhibitors

S. Gharaghani, T. Khayamian, M. Ebrahimi, 2013, SAR and QSAR in environmental research.

Synthesis and Antibacterial Evaluation of Novel Xanthone Sulfonamides

S. Gharaghani, M. Malekpoor, A. Sharifzadeh, 2015 .

Melatonin Therapy Modulates Cerebral Metabolism and Enhances Remyelination by Increasing PDK4 in a Mouse Model of Multiple Sclerosis

S. Gharaghani, S. Mondello, K. Zibara, 2019, Front. Pharmacol..

Drug-Target Binding Affinity Prediction Using Transformers

S. Gharaghani, F. Zare-Mirakabad, Mahsa Saadat, 2021, bioRxiv.

QSAR prediction of HIV-1 protease inhibitory activities using docking derived molecular descriptors.

S. Gharaghani, M. Fatemi, A. Heidari, 2015, Journal of theoretical biology.

An in silico approach to design peptide mimetics based on docking and molecular dynamics simulation of EGFR–matuzumab complex

S. Gharaghani, T. Khayamian, A. Mani-Varnosfaderani, 2016, Journal of the Iranian Chemical Society.

Monitoring the protective ability of thymoquinone mixture with p-cymene against bovine serum albumin (BSA) glycation: MCR-ALS analysis based on combined spectroscopic and electrochemical methods.

S. Gharaghani, A. Benvidi, Saleheh Abbasi, 2018, International journal of biological macromolecules.

Synthesis of new triazole tethered derivatives of curcumin and their antibacterial and antifungal properties

S. Gharaghani, P. Salehi, M. Bararjanian, 2018, Journal of the Iranian Chemical Society.

Proteochemometrics modeling for prediction of the interactions between caspase isoforms and their inhibitors

S. Gharaghani, A. Ramazani, R. Sheikhpour, 2022, Molecular Diversity.

Multi experimental and computational studies for DNA and HSA interaction of new nano-scale ultrasound-assisted synthesized Pd(II) complex as a potent anticancer drug

S. Gharaghani, H. A. Rudbari, M. Sahihi, 2018, Journal of Molecular Liquids.

Studies of DNA- and HSA-binding properties of new nano-scale green synthesized Ni (II) complex as anticancer agent using spectroscopic methods, viscosity measurement, molecular docking, MD simulation and QM/MM

S. Gharaghani, H. A. Rudbari, M. Sahihi, 2017 .

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

S. Gharaghani, M. A. Zare Chahooki, M. Tavakol, 2022, Molecular Diversity.

Chiral halogenated Schiff base compounds: green synthesis, anticancer activity and DNA-binding study

S. Gharaghani, Z. Kazemi, M. Sahihi, 2018, Journal of Molecular Structure.

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

S. Gharaghani, C. Eslahchi, Koorosh Shahpasand, 2022, Frontiers in Aging Neuroscience.

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

S. Gharaghani, Z. Hajihassan, Farideh Sadeghkhani, 2022, Journal of biomolecular structure & dynamics.

Synthesis of novel norsufentanil analogs via a four‐component Ugi reaction and in vivo, docking, and QSAR studies of their analgesic activity

S. Gharaghani, M. Dabiri, P. Salehi, 2018, Chemical biology & drug design.

Studies on DNA binding properties of new Schiff base ligands using spectroscopic, electrochemical and computational methods: Influence of substitutions on DNA-binding

S. Gharaghani, R. Keshavarzi, H. A. Rudbari, 2018 .

A Structure‐based QSAR and Docking Study on Imidazo[1,5‐a][1,2,4]‐triazolo[1,5‐d][1,4,]benzodiazepines as Selective GABAAα5 Inverse Agonists

S. Gharaghani, T. Khayamian, F. Keshavarz, 2011, Chemical biology & drug design.

A novel QSAR model for prediction of apoptosis-inducing activity of 4-aryl-4-H-chromenes based on support vector machine.

Sajjad Gharaghani, Mohammad Hossein Fatemi, S. Gharaghani, 2007, Bioorganic & medicinal chemistry.

Synthesis, characterization and biological application of four novel metal-Schiff base complexes derived from allylamine and their interactions with human serum albumin: Experimental, molecular docking and ONIOM computational study.

S. Gharaghani, H. A. Rudbari, S. Tangestaninejad, 2016, Journal of photochemistry and photobiology. B, Biology.

Pharmacophore model, docking, QSAR, and molecular dynamics simulation studies of substituted cyclic imides and herbal medicines as COX-2 inhibitors

S. Gharaghani, Ahmad Hassan, Nathalie Moussa, 2021, Heliyon.

Experimental and theoretical investigation of interaction between bovine serum albumin and the mixture of caffeic acid and salicylic acid as the antioxidants

S. Gharaghani, H. Zare, A. Benvidi, 2017 .

Investigation of the interaction between amodiaquine and human serum albumin by fluorescence spectroscopy and molecular modeling.

M. Shamsipur, S. Gharaghani, T. Khayamian, 2012, European journal of medicinal chemistry.

Synthesis, characterization and separation of chiral and achiral diastereomers of Schiff base Pd(II) complex: A comparative study of their DNA- and HSA-binding.

S. Gharaghani, V. Mirkhani, I. Mohammadpoor‐Baltork, 2016, Journal of photochemistry and photobiology. B, Biology.

Identifying the novel natural antioxidants by coupling different feature selection methods with nonlinear regressions and gas chromatography-mass spectroscopy

S. Gharaghani, A. Latif, A. Benvidi, 2018, Microchemical Journal.

Biomolecular interactions and binding dynamics of inhibitor arachidonic acid, with tyrosinase enzyme

S. Gharaghani, N. Gheibi, A. Farasat, 2022, Journal of biomolecular structure & dynamics.

In silico drug repositioning of FDA-approved drugs to predict new inhibitors for alpha-synuclein aggregation

Ali Akbar Saboury, Sedighe Sadat Jafaripour, Sajjad Gharaghani, 2020, Comput. Biol. Chem..

Sparse feature selection in multi-target modeling of carbonic anhydrase isoforms by exploiting shared information among multiple targets

Sajjad Gharaghani, Elmira Nazarshodeh, Razieh Sheikhpour, 2020 .

Toward a hierarchical virtual screening and toxicity risk analysis for identifying novel CA XII inhibitors

Sajjad Gharaghani, Elmira Nazarshodeh, S. Gharaghani, 2017, Biosyst..

A robust graph-based semi-supervised sparse feature selection method

Mohammad Ali Zare Chahooki, Sajjad Gharaghani, Razieh Sheikhpour, 2020, Inf. Sci..

A Survey on semi-supervised feature selection methods

Mohammad Ali Zare Chahooki, Sajjad Gharaghani, Razieh Sheikhpour, 2017, Pattern Recognit..

In Silico Drug-Designing Studies on Sulforaphane Analogues: Pharmacophore Mapping, Molecular Docking and QSAR Modeling.

S. Gharaghani, S. F. Farsani, Neda Vaghefinezhad, 2019, Current drug discovery technologies.

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

S. Gharaghani, A. Moghadamnia, M. Moloudizargari, 2023, Journal of Cancer Research and Clinical Oncology.

Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

S. Gharaghani, J. Zahiri, K. Rahimian, 2020, BMC Bioinform..

Structural systems pharmacology: A framework for integrating metabolic network and structure-based virtual screening for drug discovery against bacteria

S. Gharaghani, S. Marashi, E. Nazarshodeh, 2021, PloS one.

Structural stability of β-lactoglobulin in the presence of cetylpyridinum bromide: spectroscopic and molecular docking studies

S. Gharaghani, M. Sahihi, Zahra Chavoshpour-Natanzi, 2018, Journal of biomolecular structure & dynamics.

Multitarget fragment‐based design of novel inhibitors for AChE and SSAO/VAP‐1 enzymes

S. Gharaghani, T. Khayamian, M. Ebrahimi, 2013 .

NDDSA: A network- and domain-based method for predicting drug-side effect associations

Sayed-Amir Marashi, Sajjad Gharaghani, Soheila Shabani-Mashcool, 2020, Inf. Process. Manag..

BRNS + SSFSM-DTI: A hybrid method for drug-target interaction prediction based on balanced reliable negative samples and semi-supervised feature selection

S. Gharaghani, R. Sheikhpour, Mohammad Morovvati Sharifabad, 2021, Chemometrics and Intelligent Laboratory Systems.

Electrochemical investigation of the inhibition effect of carvacrol on xanthine oxidase activity merging with theoretical studies

S. Gharaghani, H. Zare, A. Benvidi, 2019, Process Biochemistry.

Chemometrics approaches based on electrochemical methods for the investigation of interaction between bovine serum albumin and carvacrol with the aim of its application to protein sensing

S. Gharaghani, H. Zare, A. Benvidi, 2019, Journal of Electroanalytical Chemistry.

Deciphering the inhibition effect of thymoquinone on xanthine oxidase activity using differential pulse voltammetry in combination with theoretical studies.

S. Gharaghani, H. Zare, A. Benvidi, 2019, Enzyme and microbial technology.

Prediction of selectivity coefficients of univalent anions for anion-selective electrode using support vector machine

Sajjad Gharaghani, Mohammad Hossein Fatemi, S. Gharaghani, 2008 .

An efficient nano-biocatalyst for lignocellulosic biomass hydrolysis: Xylanase immobilization on organically modified biogenic mesoporous silica nanoparticles.

S. Gharaghani, G. Salekdeh, L. Ma'mani, 2020, International journal of biological macromolecules.

Inhibition of GSK_3β by Iridoid Glycosides of Snowberry (Symphoricarpos albus) Effective in the Treatment of Alzheimer’s Disease Using Computational Drug Design Methods

S. Gharaghani, Javad Khalili Fard, Parastou Kordestani-Moghadam, 2021, Frontiers in Chemistry.

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

S. Gharaghani, C. Eslahchi, Koorosh Shahpasand, 2022, Scientific Reports.

Hybrid docking-QSAR studies of DPP-IV inhibition activities of a series of aminomethyl-piperidones

Sajjad Gharaghani, Mohammad Hossein Fatemi, Zohreh Amini, 2016, Comput. Biol. Chem..

Design of potential anti-tumor PARP-1 inhibitors by QSAR and molecular modeling studies

S. Gharaghani, S. Riahi, Zeinab Abbasi-Radmoghaddam, 2020, Molecular Diversity.

Design of potential anti-tumor PARP-1 inhibitors by QSAR and molecular modeling studies

S. Gharaghani, S. Riahi, Zeinab Abbasi-Radmoghaddam, 2020, Molecular Diversity.

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

S. Gharaghani, A. Jafari, M. Namazi, 2023, Journal of Molecular Liquids.

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR

Ali Masoudi-Nejad, Yosef Masoudi-Sobhanzadeh, Sajjad Gharaghani, 2017, Iranian journal of pharmaceutical research : IJPR.

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

S. Gharaghani, A. Zabihian, S. M. Hashemi, 2023, BMC Bioinformatics.

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

S. Gharaghani, Parvin Razzaghi, Karim Abbasi, 2023, Expert Syst. Appl..

AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders

S. Gharaghani, M. Chahooki, S. Z. Sajadi, 2021, BMC Bioinform..

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

S. Gharaghani, A. Zabihian, S. M. Hashemi, 2023, Scientific reports.

AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders

Mohammad Ali Zare Chahooki, Sajjad Gharaghani, Karim Abbasi, 2021, BMC Bioinformatics.

Scoring multiple features to predict drug disease associations using information fusion and aggregation

H Moghadam, M Rahgozar, S Gharaghani, 2016, SAR and QSAR in environmental research.

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: from pharmacophore-based virtual screening to molecular dynamics

Sajjad Gharaghani, Mohsen Yazdani, Ameneh Jafari, 2021 .

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

S. Gharaghani, N. Gheibi, H. Piri, 2023, Journal of biomolecular structure & dynamics.

Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

S. Gharaghani, J. Zahiri, K. Rahimian, 2021, BMC Bioinformatics.