Computational Biology and Chemistry This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Mining channel-regulated peptides from animal venom by integrating sequence semantics and structural information
Comput Biol Chem. 2024 Feb 6;109:108027. doi: 10.1016/j.compbiolchem.2024.108027. Online ahead of print.ABSTRACTChannel-regulated peptides (CRPs) derived from animal venom hold great promise as potential drug candidates for numerous diseases associated with channel proteins. However, discovering and identifying CRPs using traditional bio-experimental methods is a time-consuming and laborious process. While there were a few computational studies on CRPs, they were limited to specific channel proteins, relied heavily on complex feature engineering, and lacked the incorporation of multi-source information. To address these pr...
Source: Computational Biology and Chemistry - February 10, 2024 Category: Bioinformatics Authors: Jian-Ming Wang Rong-Kai Cui Zheng-Kun Qian Zi-Zhong Yang Yi Li Source Type: research

Pre-training molecular representation model with spatial geometry for property prediction
Comput Biol Chem. 2024 Feb 7;109:108023. doi: 10.1016/j.compbiolchem.2024.108023. Online ahead of print.ABSTRACTAI-enhanced bioinformatics and cheminformatics pivots on generating increasingly descriptive and generalized molecular representation. Accurate prediction of molecular properties needs a comprehensive description of molecular geometry. We design a novel Graph Isomorphic Network (GIN) based model integrating a three-level network structure with a dual-level pre-training approach that aligns the characteristics of molecules. In our Spatial Molecular Pre-training (SMPT) Model, the network can learn implicit geometri...
Source: Computational Biology and Chemistry - February 9, 2024 Category: Bioinformatics Authors: Yishui Li Wei Wang Jie Liu Chengkun Wu Source Type: research

Feature engineering from meta-data for prediction of differentially expressed genes: An investigation of Mus musculus exposed to space-conditions
Comput Biol Chem. 2024 Feb 6;109:108026. doi: 10.1016/j.compbiolchem.2024.108026. Online ahead of print.ABSTRACTTranscription profiling is a key process that can reveal those biological mechanisms driving the response to various exposure conditions or gene perturbations. In this work, we investigate the prediction of differentially expressed genes (DEGs) when exposed to conditions in space from a set of diverse engineered features. To do this, we collected DEGs and non-differentially expressed genes (NDEGs) of Mus musculus-based experiments on the GeneLab database. We engineered a diverse set of features from factors repor...
Source: Computational Biology and Chemistry - February 9, 2024 Category: Bioinformatics Authors: Michael Okwori Ali Eslami Source Type: research

Cytokine expression patterns: A single-cell RNA sequencing and machine learning based roadmap for cancer classification
Comput Biol Chem. 2024 Feb 6;109:108025. doi: 10.1016/j.compbiolchem.2024.108025. Online ahead of print.ABSTRACTCytokines are small protein molecules that exhibit potent immunoregulatory properties, which are known as the essential components of the tumor immune microenvironment (TIME). While some cytokines are known to be universally upregulated in TIME, the unique cytokine expression patterns have not been fully resolved in specific types of cancers. To address this challenge, we develop a TIME single-cell RNA sequencing (scRNA-seq) dataset, which is designed to study cytokine expression patterns for precise cancer class...
Source: Computational Biology and Chemistry - February 9, 2024 Category: Bioinformatics Authors: Zhixiang Ren Yiming Ren Pengfei Liu Huan Xu Source Type: research

Exploration of functional relations among differentially co-expressed genes identifies regulators in glioblastoma
Comput Biol Chem. 2024 Feb 5;109:108024. doi: 10.1016/j.compbiolchem.2024.108024. Online ahead of print.ABSTRACTThe conventional computational approaches to investigating a disease confront inherent constraints as they often need to improve in delving beyond protein functional associations and grasping their deeper contextual significance within the disease framework. Such context-specificity can be explored using clinical data by evaluating the change in interaction between the biological entities in different conditions by investigating the differential co-expression relationships. We believe that the integration and ana...
Source: Computational Biology and Chemistry - February 9, 2024 Category: Bioinformatics Authors: Shivam Kumar Dipanka Tanu Sarmah Abhijit Paul Samrat Chatterjee Source Type: research

Deep2Pep: A deep learning method in multi-label classification of bioactive peptide
Comput Biol Chem. 2024 Jan 22;109:108021. doi: 10.1016/j.compbiolchem.2024.108021. Online ahead of print.ABSTRACTFunctional peptides are easy to absorb and have low side effects, which has attracted increasing interest from pharmaceutical scientists. However, due to the limitations in the laboratory funding and human resources, it is difficult to screen the functional peptides from a large number of peptides with unknown functions. With the development of machine learning and Deep learning, the combination of computational methods and biological information provides an effective method for identifying peptide functions. To...
Source: Computational Biology and Chemistry - February 3, 2024 Category: Bioinformatics Authors: Lihua Chen Zhenkang Hu Yuzhi Rong Bao Lou Source Type: research

Computational prediction for designing novel ketonic derivatives as potential inhibitors for breast cancer: A trade-off between drug likeness and inhibition potency
Comput Biol Chem. 2024 Jan 17;109:108020. doi: 10.1016/j.compbiolchem.2024.108020. Online ahead of print.ABSTRACTUnlike simple molecular screening, a combined hybrid computational methodology has been applied which includes quantum chemical methods, molecular docking, and molecular dynamics simulations to design some novel ketonic derivatives. The current study contains the derivatives of an experimental ligand which are designed as a trade-off between drug likeness and inhibition strength. We investigate the interaction of various newly designed ketonic compounds with the breast cancer receptor known as the Estrogen Recep...
Source: Computational Biology and Chemistry - January 29, 2024 Category: Bioinformatics Authors: Shabbir Muhammad Nimra Zahir Shamsa Bibi Mohammad Y Alshahrani None Shafiq-urRehman Aijaz Rasool Chaudhry Fatima Sarwar Muhammad Imran Tousif Source Type: research

Effects of 1,4-dihydropyridine derivatives on cell injury and mTOR of HepG2 and 3D-QSAR study
Comput Biol Chem. 2023 Dec 29;109:108010. doi: 10.1016/j.compbiolchem.2023.108010. Online ahead of print.ABSTRACT1,4-dihydropyridine derivatives (1,4-DHPs) are a class of drugs used to treat cardiovascular diseases, but these drugs can cause liver injury. To reveal the toxicity characteristics of these compounds, we used a series of assays, including cell viability, enzyme activity detection, and western blotting, to investigate the toxicity of seven kinds of 1,4-DHPs (0-100 μM) on HepG2 cells and establish 3D-QSAR model based on relevant toxicity data. After HepG2 cells were treated with 1,4-DHPs for 24 h, high-dose (100...
Source: Computational Biology and Chemistry - January 17, 2024 Category: Bioinformatics Authors: Huan Liu Siyu Zhu Guiqiong Xia Zhuoquan Huang Wenna Han Zhongyi Li Chunhong Liu Source Type: research

MESBC: A novel mutually exclusive spectral biclustering method for cancer subtyping
In this study, we developed a novel mutually exclusive spectral biclustering (MESBC) algorithm based on spectral method to detect mutually exclusive biclusters. MESBC simultaneously detects relevant features (genes) and corresponding conditions (patients) subgroups and, therefore, automatically uses the signature features for each subtype to perform the clustering. Extensive simulations revealed that MESBC provided superior accuracy in detecting pre-specified biclusters compared with the non-negative matrix factorization (NMF) and Dhillon's algorithm, particularly in very noisy data. Further analysis of the algorithm on re...
Source: Computational Biology and Chemistry - January 14, 2024 Category: Bioinformatics Authors: Fengrong Liu Yaning Yang Xu Steven Xu Min Yuan Source Type: research

BactInt: A domain driven transfer learning approach for extracting inter-bacterial associations from biomedical text
CONCLUSION: This study attempts to demonstrate the applicability of transfer learning in a niche field of life sciences where understanding of inter bacterial relationships is crucial to obtain meaningful insights in comprehending microbial community structures across different ecosystems. The study further discusses how such a model can be further improved by fine tuning using limited training data. The results presented and the datasets made available are expected to be a valuable addition in the field of medical informatics and bioinformatics.PMID:38198963 | DOI:10.1016/j.compbiolchem.2023.108012 (Source: Computational ...
Source: Computational Biology and Chemistry - January 10, 2024 Category: Bioinformatics Authors: Krishanu Das Baksi Vatsala Pokhrel Anand Eruvessi Pudavar Sharmila S Mande Bhusan K Kuntal Source Type: research

In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia
Comput Biol Chem. 2023 Dec 27;109:108008. doi: 10.1016/j.compbiolchem.2023.108008. Online ahead of print.ABSTRACTStercularin is a coumarin, isolated from the ethyl acetate fraction of stem bark and leaves of S. diversifolia. Pharmacologically it is active against cancer, diabetes, and inflammation etc. The molecule is further screened for in vitro pharmacological activities. In addition, a detailed description on its drug likeness and pharmacokinetic profile has been established to further explore its fate as a drug candidate. Stercularin exhibited antiglycation, immunomodulatory, and leishmanicidal activity in three diffe...
Source: Computational Biology and Chemistry - January 10, 2024 Category: Bioinformatics Authors: Imad Ahmad Fazle Rabbi Amna Nisar Zaheer Ul-Haq Alamgir Khan Source Type: research

Optimization of virtual screening against phosphoinositide 3-kinase delta: Integration of common feature pharmacophore and multicomplex-based molecular docking
Comput Biol Chem. 2024 Jan 2;109:108011. doi: 10.1016/j.compbiolchem.2023.108011. Online ahead of print.ABSTRACTExtensive research has accumulated which suggests that phosphatidylinositol 3-kinase delta (PI3Kδ) is closely related to the occurrence and development of various human diseases, making PI3Kδ a highly promising drug target. However, PI3Kδ exhibits high homology with other members of the PI3K family, which poses significant challenges to the development of PI3Kδ inhibitors. Therefore, in the present study, a hybrid virtual screening (VS) approach based on a ligand-based pharmacophore model and multicomplex-bas...
Source: Computational Biology and Chemistry - January 10, 2024 Category: Bioinformatics Authors: Jingyu Zhu Huiqin Meng Xintong Li Lei Jia Lei Xu Yanfei Cai Yun Chen Jian Jin Li Yu Source Type: research

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations
Comput Biol Chem. 2024 Feb;108:108003. doi: 10.1016/j.compbiolchem.2023.108003. Epub 2023 Dec 12.ABSTRACTCDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0.53, 0.54...
Source: Computational Biology and Chemistry - December 30, 2023 Category: Bioinformatics Authors: Iffat Habib Tahir Ali Chohan Talha Ali Chohan Fakhra Batool Umair Khurshid Anjum Khursheed Ali Raza Mukhtar Ansari Arshad Hussain Sirajudheen Anwar Nasser A Awadh Ali Hammad Saleem Source Type: research

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations
Comput Biol Chem. 2023 Dec 12;108:108003. doi: 10.1016/j.compbiolchem.2023.108003. Online ahead of print.ABSTRACTCDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0....
Source: Computational Biology and Chemistry - December 30, 2023 Category: Bioinformatics Authors: Iffat Habib Tahir Ali Chohan Talha Ali Chohan Fakhra Batool Umair Khurshid Anjum Khursheed Ali Raza Mukhtar Ansari Arshad Hussain Sirajudheen Anwar Nasser A Awadh Ali Hammad Saleem Source Type: research

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations
Comput Biol Chem. 2023 Dec 12;108:108003. doi: 10.1016/j.compbiolchem.2023.108003. Online ahead of print.ABSTRACTCDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0....
Source: Computational Biology and Chemistry - December 30, 2023 Category: Bioinformatics Authors: Iffat Habib Tahir Ali Chohan Talha Ali Chohan Fakhra Batool Umair Khurshid Anjum Khursheed Ali Raza Mukhtar Ansari Arshad Hussain Sirajudheen Anwar Nasser A Awadh Ali Hammad Saleem Source Type: research