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Structural simulation and selective inhibitor discovery study for histone demethylases KDM4E/6B from a computational perspective
This study focuses on two members of the lysine demethylase (KDM) family, KDM4E and KDM6B, which are significant in gene regulation and disease pathogenesis. KDM4E demonstrates selectivity for gene regulation, particularly concerning cancer, while KDM6B is implicated in inflammation and cancer. The study utilizes specific inhibitors, DA-24905 and GSK-J1, showcasing their exceptional selectivity for KDM4E and KDM6B, respectively. Employing an array of computational simulations, including sequence alignment, molecular docking, dynamics simulations, and free energy calculations, we conclude that although the binding cavities ...
Source: Computational Biology and Chemistry - April 18, 2024 Category: Bioinformatics Authors: Chenxiao Wang Baichun Hu Yi Yang Yihan Wang Juyue Qin Xiaolian Wen Yikuan Li Hui Li Yutong Wang Jian Wang Yang Liu Source Type: research

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions
This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).PMID:38615420 | DOI:10.1016/j.compbiolchem.2024.108065 (Source: Computational Biology and Chemistry)
Source: Computational Biology and Chemistry - April 14, 2024 Category: Bioinformatics Authors: Manikandan Jayaraman Rajalakshmi Kumar Santhiya Panchalingam Jeyakanthan Jeyaraman Source Type: research

MMR: A Multi-view Merge Representation model for Chemical-Disease relation extraction
Comput Biol Chem. 2024 Apr 3;110:108063. doi: 10.1016/j.compbiolchem.2024.108063. Online ahead of print.ABSTRACTChemical-Disease relation (CDR) extraction aims to identify the semantic relations between chemical and disease entities in the unstructured biomedical document, which provides a basis for downstream tasks such as clinical medical diagnosis and drug discovery. Compared with general domain relation extraction, it needs a more effective representation of the whole document due to the specialized nature of texts in the biomedical domain, including the biomedical entity and entity-pair representation. In this paper, ...
Source: Computational Biology and Chemistry - April 13, 2024 Category: Bioinformatics Authors: Yi Zhang Jing Peng Baitai Cheng Yang Liu Chi Jiang Source Type: research

Antidiabetic potency and molecular insights of natural products bearing indole moiety: A systematic bioinformatics investigation targeting AKT1
Comput Biol Chem. 2024 Mar 23;110:108059. doi: 10.1016/j.compbiolchem.2024.108059. Online ahead of print.ABSTRACTDiabetic mellitus (DM) is a chronic disorder, and type 2 DM (T2DM) is the most prevalent among all categories (nearly 90%) across the globe every year. With the availability of potential drugs, the prevalence rate has remained uncontrollable, while natural resources showed a promising potency, and exploring such potential candidates at the preclinical stage is essential. An extensive literature search selected 89 marine and plant-derived indole derivatives with anti-inflammatory, antioxidant, lipid-lowering, etc...
Source: Computational Biology and Chemistry - April 12, 2024 Category: Bioinformatics Authors: Dhananjay K Tanty Prachi R Sahu Ranjit Mohapatra Susanta K Sahu Source Type: research

Advancing Drug-Target Interaction prediction with BERT and subsequence embedding
Comput Biol Chem. 2024 Apr 5;110:108058. doi: 10.1016/j.compbiolchem.2024.108058. Online ahead of print.ABSTRACTExploring the relationship between proteins and drugs plays a significant role in discovering new synthetic drugs. The Drug-Target Interaction (DTI) prediction is a fundamental task in the relationship between proteins and drugs. Unlike encoding proteins by amino acids, we use amino acid subsequence to encode proteins, which simulates the biological process of DTI better. For this research purpose, we proposed a novel deep learning framework based on Bidirectional Encoder Representation from Transformers (BERT), ...
Source: Computational Biology and Chemistry - April 9, 2024 Category: Bioinformatics Authors: Zhihui Yang Juan Liu Feng Yang Xiaolei Zhang Qiang Zhang Xuekai Zhu Peng Jiang Source Type: research

Accuracy of AlphaFold models: Comparison with short N < sup > < sub > … < /sub > < /sup > O contacts in atomic resolution protein crystal structures
Comput Biol Chem. 2024 Apr 4;110:108069. doi: 10.1016/j.compbiolchem.2024.108069. Online ahead of print.ABSTRACTArtificial intelligence (AI) has revolutionized structural biology by predicting protein 3D structures with near-experimental accuracy. Here, short backbone N-O distances in high-resolution crystal structures were compared to those in three-dimensional models based on AI AlphaFold/ColabFold, specifically considering their estimated standard errors. Experimental and computationally modeled distances very often differ significantly, showing that these models' precision is inadequate to reproduce experimental result...
Source: Computational Biology and Chemistry - April 6, 2024 Category: Bioinformatics Authors: Oliviero Carugo Source Type: research

FaissMolLib: An efficient and easy deployable tool for ligand-based virtual screening
Comput Biol Chem. 2024 Apr 1;110:108057. doi: 10.1016/j.compbiolchem.2024.108057. Online ahead of print.ABSTRACTVirtual screening-based molecular similarity and fingerprint are crucial in drug design, target prediction, and ADMET prediction, aiding in identifying potential hits and optimizing lead compounds. However, challenges such as lack of comprehensive open-source molecular fingerprint databases and efficient search methods for virtual screening are prevalent. To address these issues, we introduce FaissMolLib, an open-source virtual screening tool that integrates 2.8 million compounds from ChEMBL and ZINC databases. N...
Source: Computational Biology and Chemistry - April 6, 2024 Category: Bioinformatics Authors: Haihan Liu Peiying Chen Baichun Hu Shizun Wang Hanxun Wang Jiasi Luan Jian Wang Bin Lin Maosheng Cheng Source Type: research