Journal of Computational Biophysics and Chemistry最新文献

Mayer-Homology Learning Prediction of Protein-Ligand Binding Affinities. 蛋白质-配体结合亲和力的mayer -同源学习预测。

IF 2.3 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2025-03-01 Epub Date: 2024-11-06 DOI: 10.1142/s2737416524500613

Hongsong Feng, Li Shen, Jian Liu, Guo-Wei Wei

{"title":"Mayer-Homology Learning Prediction of Protein-Ligand Binding Affinities.","authors":"Hongsong Feng, Li Shen, Jian Liu, Guo-Wei Wei","doi":"10.1142/s2737416524500613","DOIUrl":"10.1142/s2737416524500613","url":null,"abstract":"Artificial intelligence-assisted drug design is revolutionizing the pharmaceutical industry. Effective molecular features are crucial for accurate machine learning predictions, and advanced mathematics plays a key role in designing these features. Persistent homology theory, which equips topological invariants with persistence, provides valuable insights into molecular structures. The standard homology theory is based on a differential rule for the boundary operator that satisfies <math> <msup><mrow><mi>d</mi></mrow> <mrow><mn>2</mn></mrow> </msup> <mo>=</mo> <mn>0</mn></math> . Our recent work has extended this rule by employing Mayer homology with generalized differentials that satisfy <math> <msup><mrow><mi>d</mi></mrow> <mrow><mi>N</mi></mrow> </msup> <mo>=</mo> <mn>0</mn></math> for <math><mi>N</mi> <mo>≥</mo> <mn>2</mn></math> , leading to the development of persistent Mayer homology (PMH) theory and richer topological information across various scales. In this study, we utilize PMH to create a novel multiscale topological vectorization for molecular representation, offering valuable tools for descriptive and predictive analyses in molecular data and machine learning prediction. Specifically, benchmark tests on established protein-ligand datasets, including PDBbind-v2007, PDBbind-v2013, and PDBbind-v2016, demonstrate the superior performance of our Mayer homology models in predicting protein-ligand binding affinities.","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":"24 2","pages":"253-266"},"PeriodicalIF":2.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12463301/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145185924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph-Based Bidirectional Transformer Decision Threshold Adjustment Algorithm for Class-Imbalanced Molecular Data. 基于图的类不平衡分子数据双向互感器决策阈值调整算法。

IF 2.3 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2024-12-01 Epub Date: 2024-09-19 DOI: 10.1142/s2737416524500479

Nicole Hayes, Ekaterina Merkurjev, Guo-Wei Wei

{"title":"Graph-Based Bidirectional Transformer Decision Threshold Adjustment Algorithm for Class-Imbalanced Molecular Data.","authors":"Nicole Hayes, Ekaterina Merkurjev, Guo-Wei Wei","doi":"10.1142/s2737416524500479","DOIUrl":"10.1142/s2737416524500479","url":null,"abstract":"Data sets with imbalanced class sizes, where one class size is much smaller than that of others, occur exceedingly often in many applications, including those with biological foundations, such as disease diagnosis and drug discovery. Therefore, it is extremely important to be able to identify data elements of classes of various sizes, as a failure to do so can result in heavy costs. Nonetheless, many data classification procedures do not perform well on imbalanced data sets as they often fail to detect elements belonging to underrepresented classes. In this work, we propose the BTDT-MBO algorithm, incorporating Merriman-Bence-Osher (MBO) approaches and a bidirectional transformer, as well as distance correlation and decision threshold adjustments, for data classification tasks on highly imbalanced molecular data sets, where the sizes of the classes vary greatly. The proposed technique not only integrates adjustments in the classification threshold for the MBO algorithm in order to help deal with the class imbalance, but also uses a bidirectional transformer procedure based on an attention mechanism for self-supervised learning. In addition, the model implements distance correlation as a weight function for the similarity graph-based framework on which the adjusted MBO algorithm operates. The proposed method is validated using six molecular data sets and compared to other related techniques. The computational experiments show that the proposed technique is superior to competing approaches even in the case of a high class imbalance ratio.","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":"23 10","pages":"1339-1358"},"PeriodicalIF":2.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145186004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Juxtaposition of Allosteric and Catalytic Inhibition in PLK1: Tradeoff for Chemotherapy and Thermodynamic Profiles of KBJK557 and BI 6727 PLK1 中异位抑制与催化抑制的并存：KBJK557 和 BI 6727 的化疗权衡与热力学特征

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-12-15 DOI: 10.1142/s2737416523500680

Ernest Oduro-Kwateng, Ali H. Rabbad, M. E. Soliman

引用次数: 0

Computational approach to identify the Key Genes for Invasive Lobular Carcinoma (ILC) Diagnosis and Therapies 用计算方法确定浸润性小叶癌 (ILC) 诊断和治疗的关键基因

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-12-15 DOI: 10.1142/s2737416523500692

S. Anitha, S. Nandhini, D. Premnath, M. Indiraleka

引用次数: 0

Molecular Dynamics Study on the Binding Characteristics and Transport Mechanism of Polysaccharides with Different Molecular Weights in Camellia Oleifera Abel 油茶中不同分子量多糖的结合特性和迁移机制的分子动力学研究

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-12-08 DOI: 10.1142/s2737416523500679

Jihang Zhai, Fangfang Fan, Chaojie Wang, Zhiyang Zhang, Sheng Zhang, Yuan Zhao

引用次数: 0

Fragment-Based Protein Structure Prediction, Where Are We Now? 基于片段的蛋白质结构预测，我们现在在哪里？

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-12-08 DOI: 10.1142/s2737416523300018

Qudsia Noor, Raheem Kayode, Rizwan Riaz, Areeba Siddiqui, Aiza Hassan Mirza, Abdul Rauf Siddiqi

引用次数: 0

Computational studies of multi-target directed ligands against acetylcholinesterase, butyrylcholinesterase and amyloid beta as potential anti-Alzheimer's agents 针对乙酰胆碱酯酶、丁酰胆碱酯酶和淀粉样蛋白 beta 的多靶向配体作为潜在抗老年痴呆药物的计算研究

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-12-01 DOI: 10.1142/s2737416523500667

Neha Maurya, Mareechika Gaddam, Abha Sharma

引用次数: 0

Antifibromyalgic activity of Phytomolecule Niranthin: In-Vivo analysis, Molecular docking, Dynamics and DFT 植物大分子 Niranthin 的抗纤维肌痛活性：体内分析、分子对接、动力学和 DFT

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-12-01 DOI: 10.1142/s2737416523500655

A. Chopade, Vikram H. Potdar, Suraj N. Mali, Susmita Yadav, Anima Pandey, Chin-Hung Lai, Essa M. Saied, Oberdan Oliveira Ferreira, M. D. de Oliveira, S. S. Gurav, Eloísa Helena de Aguiar Andrade

引用次数: 0

MLBKFD: probabilistic model methods to infer pseudo trajectories from single-cell data MLBKFD：从单细胞数据推断伪轨迹的概率模型方法

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-11-17 DOI: 10.1142/s2737416524400015

Changfeng Han, Wenjie Cao, Cheng Li, Yanbing Guo, Yuebin Wang, Yazhou Shi, Ben-Gong Zhang

引用次数: 0

Spatially Resolved Transcriptomics Reveals Local Invasion-Related Genes in Liver Hepatocellular Carcinoma: Exploring the Therapeutic Potential of a Chimeric Protein Targeting Glypican-3 空间解析转录组学揭示肝脏肝细胞癌中与局部侵袭相关的基因：探索靶向 Glypican-3 的嵌合蛋白的治疗潜力

IF 2.2 4区化学

Journal of Computational Biophysics and Chemistry Pub Date : 2023-11-17 DOI: 10.1142/s2737416523500643

M. Naveed, Hamza Jamil, Tariq Aziz, Syeda Izma Makhdoom, A. Alamri, M. Alhomrani, Roaa Mohammed Tahir Kassim, Nehad A. Shaer, Aminah A. Barqawi, N. Al-Abbas

引用次数: 0