Article
Biology
Bilal Shaker, Sajjad Ahmad, Jingyu Lee, Chanjin Jung, Dokyun Na
Summary: Traditional drug discovery strategies have long development times and high costs; recently, computational methods have attracted attention for their potential to accelerate drug discovery and successfully develop new drugs; this review introduces computational drug discovery strategies, tools, and successful examples.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Chemistry, Multidisciplinary
Vladimir Dordevic, Srdan Pesic, Jelena Zivkovic, Goran M. Nikolic, Aleksandar M. Veselinovic
Summary: Dopamine transporter inhibition is considered a promising approach for treating schizophrenia. This research paper presents various QSAR models for molecules acting as dopamine transporter inhibitors. Statistical methods were used to assess the developed models, and the best model was obtained through Monte Carlo optimization. Molecular docking studies were used for final evaluation of the designed inhibitors, which showed exceptional correlation with the QSAR modeling results. Physicochemical descriptors were computed to predict various parameters and properties relevant to drug discovery.
NEW JOURNAL OF CHEMISTRY
(2022)
Article
Chemistry, Medicinal
Narges Cheshmazar, Salar Hemmati, Maryam Hamzeh-Mivehroud, Babak Sokouti, Matthes Zessin, Mike Schutkowski, Wolfgang Sippl, Hojjatollah Nozad Charoudeh, Siavoush Dastmalchi
Summary: Histone deacetylases (HDACs), which are overexpressed in cancer, have shown promising results in cancer therapy when inhibited. This study used computational drug design to generate and filter potential HDAC inhibitors based on template structures and a diverse fragment library. Two new structures (3a and 3b) were proposed for synthesis and evaluation, and the compounds showed inhibition on HDAC isoforms.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Review
Pharmacology & Pharmacy
Yiqun Chang, Bryson A. Hawkins, Jonathan J. Du, Paul W. Groundwater, David E. Hibbs, Felcia Lai
Summary: The drug discovery process is full of challenges, with few candidates making it to a commercially available product due to various factors. Computer-aided drug design (CADD) has become vital in guiding and accelerating the process, and this review presents an overview of important CADD methods and applications commonly used, such as in silico structure prediction, refinement, modeling, and target validation.
Article
Chemistry, Multidisciplinary
Velimir Peric, Mladjan Golubovic, Milan Lazarevic, Vesna Marjanovic, Tomislav Kostic, Miodrag Dordevic, Dragan Milic, Aleksandar M. Veselinovic
Summary: Sigma 1 receptor antagonism is considered a promising pain treatment approach, and this study successfully developed QSAR models for a range of compounds using conformation-independent methods. The models showed good prediction ability, providing valuable information for the design of new analgesics.
NEW JOURNAL OF CHEMISTRY
(2021)
Review
Biochemistry & Molecular Biology
Yelena Guttman, Zohar Kerem
Summary: This article reviews the existing computational tools and databases relevant to predicting CYP-mediated food-drug interactions (FDIs). Computer-aided approaches and structure-based methods are used to narrow down potential targets and explore the structural nature of the interaction between compounds and CYP enzymes. However, ligand-based machine-learning approaches for virtual screening are still underutilized in this field.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Review
Pharmacology & Pharmacy
Yuzhen Niu, Ping Lin
Summary: Alzheimer's disease is a degenerative disease that progressively destroys memory and thinking skills. There is currently no treatment for AD, but targeting the direct cause of neuronal degeneration may offer better options. This paper provides an overview of the physiological and pathological mechanisms of AD, discusses potential drug candidates for targeted therapy, and reviews the use of computer-aided drug design in discovering anti-AD drugs.
DRUG DISCOVERY TODAY
(2023)
Editorial Material
Multidisciplinary Sciences
Carrie Arnold
Summary: Bioengineers are seeking more affordable and simpler methods to produce proteins and other biomolecules, rather than depending on yeast and bacteria.
Article
Biochemistry & Molecular Biology
A. S. Ben Geoffrey, Rafal Madaj, Pavan Preetham Valluri
Summary: This study uses deep learning algorithms to predict biological network data and generate scientifically useful predictions. By training on compound-drug target interaction network data, a classification and prediction model is built for PubChem compounds. Additionally, a deep learning-based optimization protocol is employed to optimize compounds for drug likeness. The tool also includes automated In Silico modeling to uncover interaction profiles between compounds and predicted drug targets.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Multidisciplinary Sciences
Moan J. F. Costa, Pedro H. Sette-De-Souza, Boniek C. D. Borges
Summary: Codeine and dexamethasone showed potential for reducing in-office tooth bleaching sensitivity by binding to the TRPA1 receptor.
ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS
(2023)
Review
Pharmacology & Pharmacy
Mariia Radaeva, Anh-Tien Ton, Michael Hsing, Fuqiang Ban, Artem Cherkasov
Summary: Transcription factors play crucial roles in many cancers as therapeutic targets, but their protein-DNA interactions have been challenging to target. Recent advances in computer-aided drug discovery have enabled successful interference with these interactions, offering promising avenues for therapeutic targeting of a wide range of human TFs implicated in various conditions, including cancer.
DRUG DISCOVERY TODAY
(2021)
Review
Oncology
Binsheng He, Fangxing Hou, Changjing Ren, Pingping Bing, Xiangzuo Xiao
Summary: Drug repositioning, the practice of using existing drugs for new disease indications, has become popular due to the high cost and failure rate of developing new drugs. With the aid of high-throughput sequencing techniques, efficient methods have been proposed and applied in drug repositioning and personalized tumor treatment. Computational methods for drug repositioning can be divided into four categories, with future directions focusing on more sensitive methods for individualized tumor treatment.
FRONTIERS IN ONCOLOGY
(2021)
Article
Toxicology
Michael F. Santillo, Robert L. Sprando
Summary: There has been a rise in cannabis-derived products being sold as food and dietary supplements. A study used an in silico tool to predict the binding between 55 cannabinoids and 4,799 biological targets. The predictions were validated with in vitro binding data, and clinical adverse effects associated with the predicted targets were identified.
JOURNAL OF APPLIED TOXICOLOGY
(2023)
Article
Nutrition & Dietetics
Qiuhai Qin, Lixiu Qin, Ruitang Xie, Shuihua Peng, Chao Guo, Bin Yang
Summary: This study explored the therapeutic mechanisms and core target genes of Vitamin A (VA) in the treatment of As-related dermatitis through network pharmacology and molecular docking. The results suggest that VA may regulate core target genes and immune responses to suppress inflammatory stress and enhance immunity against As-related dermatitis.
FRONTIERS IN NUTRITION
(2022)
Article
Biochemistry & Molecular Biology
Huifang Ge, Ting Zhang, Yuanhu Tang, Yan Zhang, Yue Yu, Fangbing Men, Jingbo Liu, Yiding Yu
Summary: This study used a computer-aided screening strategy and molecular docking to investigate the potential mechanism of food-derived tripeptides in relieving acute colitis. The results showed that these tripeptides exert their effects by influencing signaling pathways related to inflammation, immune modulation, and cell proliferation.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
