Josimary Morais Vasconcelos Oliveira, Amauri Duarte da Silva, Alexandra Martins Dos Santos Soares, Walter Filgueira de Azevedo
{"title":"Molegro Virtual Docker for Docking Screens.","authors":"Josimary Morais Vasconcelos Oliveira, Amauri Duarte da Silva, Alexandra Martins Dos Santos Soares, Walter Filgueira de Azevedo","doi":"10.1007/978-1-0716-4949-7_10","DOIUrl":"10.1007/978-1-0716-4949-7_10","url":null,"abstract":"<p><p>Docking screens aim at scanning large datasets of small molecules to find potential binders to protein targets related to pathologies. The main computational workhorse of this approach is protein-ligand docking. This chapter focuses on an integrated workflow to perform docking screens using Molegro Virtual Docker (MVD). We describe how to proceed with a target structure and integrate all necessary binding affinity data available at BindingDB to build a regression model to predict inhibition of cyclin-dependent kinase 2 (CDK2) using Molegro Data Modeller (MDM), a machine learning tool integrated into MVD. CDK2 is a protein target for anticancer drug development. Our regression model built with MDM shows superior predictive performance compared with classical scoring functions employed in docking programs. This MDM-built model is ready to use for virtual screening purposes. The integration relies on Jupyter Notebooks at Google Colab. All CDK2 datasets and Jupyter Notebooks discussed in this work are available at GitHub: https://github.com/azevedolab/docking#readme .</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2984 ","pages":"139-152"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145274972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amauri Duarte da Silva, Nelson José Freitas da Silveira, Patrícia Rufino Oliveira, Walter Filgueira de Azevedo
{"title":"Molegro Data Modeller for Machine Learning.","authors":"Amauri Duarte da Silva, Nelson José Freitas da Silveira, Patrícia Rufino Oliveira, Walter Filgueira de Azevedo","doi":"10.1007/978-1-0716-4949-7_11","DOIUrl":"10.1007/978-1-0716-4949-7_11","url":null,"abstract":"<p><p>Machine learning methods have great potential to build models to address protein-ligand interactions obtained through docking simulations. Molegro Data Modeller (MDM) has an intuitive interface with Molegro Virtual Docker (MVD), which allows us to integrate docking results and machine learning. Here, we present a tutorial on how to build a regression model using a support vector machine to predict the inhibition of cyclin-dependent kinase 2 with MDM. Our model relies on docked poses of CDK2 inhibitors obtained with MVD and employs the support vector machine implemented in the MDM program. We focus on ligands for which binding affinity data is available at the BindingDB and the structure of a CDK2-Cyclin complex determined using crystallography. Our approach explores the concept of scoring function space to build targeted models. We take descriptors, energy terms, and scoring functions determined with MVD to build our machine learning model. All CDK2 datasets and Jupyter Notebooks discussed in this work are available at GitHub: https://github.com/azevedolab/docking#readme .</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2984 ","pages":"153-166"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145274948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eito Ichihashi, Mai Kubota, Yusuke Shiromoto, Masayuki Sakurai
{"title":"ADAR1 RNA-Editing Enzyme Regulates Telomeric R-Loop Formation.","authors":"Eito Ichihashi, Mai Kubota, Yusuke Shiromoto, Masayuki Sakurai","doi":"10.1007/978-1-0716-4670-0_6","DOIUrl":"10.1007/978-1-0716-4670-0_6","url":null,"abstract":"<p><p>The enzyme adenosine deaminase acting on RNA (ADAR) plays a key role in editing RNA by converting adenosine to inosine, a process known as A-to-I RNA editing. Initially, ADAR was identified as an enzyme responsible for converting adenosine to inosines, specifically in dsRNA. However, recent studies indicate that ADAR1 can also edit DNA on hybrid strands composed of DNA:RNA strands. One of the representative structures in cells is the R-loop, which is formed at open DNA regions with single-stranded DNA and DNA:RNA hybrid strands, through hybridization of the cis-transcript or an invading RNA strand with the template DNA. In the previous study, authors have shown that ADAR1 regulates the R-loop formation and genome stability at telomeres in cancer cells carrying noncanonical variants of telomeric repeats.In this chapter, the latest and basic protocols to measure the accumulation and formation of the R-loop are described.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2949 ","pages":"109-127"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145422059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Multilocus Variable-Number Tandem-Repeat Analysis (MLVA) Scheme for Epidemiological Investigations of Cryptosporidium parvum.","authors":"Harriet Risby, Guy Robinson, Rachel M Chalmers","doi":"10.1007/978-1-0716-4824-7_8","DOIUrl":"10.1007/978-1-0716-4824-7_8","url":null,"abstract":"<p><p>A multi-locus variable-number tandem-repeat analysis (MLVA) scheme has been validated and used for subtyping Cryptosporidium parvum, to infer linkage between cases, and suspected sources, in outbreaks and for epidemiological surveillance. Here, we describe the multiplex polymerase chain reaction (PCR) assays, fragment sizing, and bioinformatics to identify alleles and create a seven-locus MLVA profile for each specimen. The PCRs to produce amplicons for Sanger sequencing to confirm new alleles are also described.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2978 ","pages":"99-116"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145377948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimized Genome Assembly Protocol for Cryptosporidium.","authors":"Wanyi Huang, Lihua Xiao","doi":"10.1007/978-1-0716-4824-7_9","DOIUrl":"10.1007/978-1-0716-4824-7_9","url":null,"abstract":"<p><p>Whole-genome sequence data have made significant contributions to studies of the biology and transmission of Cryptosporidium spp. Well-assembled genomes, free of sequence ambiguity and structural errors, are critical for comparative genomic analysis at the species and subtype levels. The optimized method for Cryptosporidium genome assembly described here comprises several individual protocols to generate chromosome- and contig-level genomes.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2978 ","pages":"117-125"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145377984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Imtiaj Uddin Bhuiyan, Fiifi Agyabeng-Dadzie, Amanda H Sullivan, Megan S Beaudry, Kelly N Petersen, Piotr T Tuczapski, Michael E Grigg, Jessica C Kissinger, Travis C Glenn
{"title":"Genomic Characterization of Cryptosporidium spp. via iNextEra Library Preparation and Hybridization Bait Capture.","authors":"Mohammad Imtiaj Uddin Bhuiyan, Fiifi Agyabeng-Dadzie, Amanda H Sullivan, Megan S Beaudry, Kelly N Petersen, Piotr T Tuczapski, Michael E Grigg, Jessica C Kissinger, Travis C Glenn","doi":"10.1007/978-1-0716-4824-7_4","DOIUrl":"10.1007/978-1-0716-4824-7_4","url":null,"abstract":"<p><p>Next-generation DNA sequencing (NGS) is used to study the genome sequences of Cryptosporidium spp., but NGS is challenging when pure Cryptosporidium oocysts are limited in number or not available. Varying levels of parasites present in fecal samples, combined with the abundance of host cells, bacterial and other microbial cells, and undigested food particles, often result in fecal DNA samples with ~0.1% Cryptosporidium DNA, making genome-scale sequencing of Cryptosporidium from such samples cost-prohibitive. DNA extractions from fecal samples are, however, widely available and commonly used for polymerase chain reaction (PCR)-based diagnostics which can detect fg levels of Cryptosporidium DNA in complex DNA mixtures. Here, we describe an Illumina NGS sample preparation protocol (iNextEra) that can generate libraries from a wide range of DNA input (<1 ng to >60 ng). We then use those libraries within a modified myBaits capture hybridization protocol using CryptoCap_100K baits to enrich Cryptosporidium genomic DNA from a complex DNA background to increase the percentage of generated sequence reads that map to target Cryptosporidium reference genome sequences. Thus, iNextEra libraries and capture hybridization facilitate genome-level sequencing of this critical pathogen from widely available samples with less cost, thereby opening new opportunities to understand the complex biology of this important pathogen.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2978 ","pages":"41-64"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145378061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Method for the Dissection of Genomic Loci Associated with Chickpea Root Penetration Traits in Compact Soil.","authors":"Jahanvi Ganotra, Mandavi Pandey, Ravindra Donde, Jitender Giri","doi":"10.1007/978-1-0716-4820-9_9","DOIUrl":"10.1007/978-1-0716-4820-9_9","url":null,"abstract":"<p><p>Mechanical impedance in agricultural land is a significant constraint in modern agriculture. It dramatically affects seed germination, plant growth, development, and grain yield. Soil compaction hinders root growth and the ability to access deeper nutrients and water resources, impacting climate resilience, crop productivity, and global food security. Crops display variations in root system architecture (RSA) traits when grown in compacted soils. We can better understand the mechanisms behind soil compaction by examining root-related traits and their associated genes. Our recently published study investigated RSA traits across different soil compaction levels and identified significant genomic associations in chickpeas. We developed reliable methods for creating soils with varying bulk densities (i.e., compaction levels), growing chickpea seedlings, and harvesting the roots. We also conducted high-throughput phenotyping and screening of root-related traits using winRHIZO software. By integrating these phenotypic data with available genotypic data through Genome-Wide Association Studies (GWAS), we could identify genetic loci influencing root penetration in response to increasing soil compaction. These methods will help us identify key architectural traits of roots that can be targeted in crop breeding efforts to enhance resilience and productivity in compacted soils. By improving the root system and understanding the genes involved, we aim to develop plants more responsive to root penetration.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2977 ","pages":"119-133"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145200356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Berta Barnadas-Carceller, Dolors Tàssies, Irene Losada Galván, Julio Alonso-Padilla, Joan Carles Reverter, Carmen Fernandez-Becerra, María-Jesús Pinazo
{"title":"Host-Derived Molecules as Novel Chagas Disease Biomarkers: Hypercoagulability Markers and Extracellular Vesicles.","authors":"Berta Barnadas-Carceller, Dolors Tàssies, Irene Losada Galván, Julio Alonso-Padilla, Joan Carles Reverter, Carmen Fernandez-Becerra, María-Jesús Pinazo","doi":"10.1007/978-1-0716-4848-3_19","DOIUrl":"10.1007/978-1-0716-4848-3_19","url":null,"abstract":"<p><p>Diagnostic methods for Chagas disease rely primarily on serological and molecular tests to detect anti-T cruzi antibodies or parasite-derived DNA. However, these tests do not predict clinical outcomes or treatment responses, as serological results may take years to turn negative, making them impractical for monitoring treatment progress. Molecular tests, though highly sensitive, can identify parasites but cannot rule out the presence of dormant forms or low levels of parasitemia, which may later reactivate. Due to the lack of reliable biomarkers for disease prognosis and treatment monitoring, there has been growing interest in host-derived markers as alternatives. One area of focus is the hypercoagulability observed in T. cruzi-infected individuals, which increases the risk of thrombotic events due to factors like chronic inflammation, dysregulation of immunothrombosis, and vasculitis. In addition, extracellular vesicles (EVs), i.e., double-membrane-enclosed particles found in various biological fluids, have emerged as a potential source of biomarkers for disease detection, prognosis, and monitoring. EVs contain proteins, lipids, and nucleic acids that can provide valuable molecular information about a patient's condition. This chapter outlines procedures for detecting host-derived biomarkers of Chagas disease, particularly those related to hypercoagulability, such as F1 + 2 and endogenous thrombin potential assays, and the isolation and characterization of EVs as biomarkers for response to treatment and disease progression.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2982 ","pages":"285-307"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145438382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Computer-Aided Discovery of Drugs Against Chagas Disease.","authors":"Carolina L Bellera, Lucas N Alberca, Alan Talevi","doi":"10.1007/978-1-0716-4848-3_1","DOIUrl":"10.1007/978-1-0716-4848-3_1","url":null,"abstract":"<p><p>Chagas disease affects around 6-8 million people worldwide. The available treatments have considerable limitations, including their uncertain efficacy in the chronic phase of the disease in adults, their unfavorable safety profile that usually compromises adherence to treatment, their long duration, and the emergence of resistant strains. All these considerations justify the continuous search for improved therapies.Informatics has been increasingly integrated into all levels of biomedical sciences, including the discovery and development of new drugs. In silico methods are relevant in all domains of therapeutics, but especially in the field of neglected diseases, in which their adoption can leverage the active participation of low- and middle-income countries (the ones historically affected by these diseases) in the development of new diagnostic and therapeutic options.This chapter describes the in silico methodologies that can be used to validate new pharmacological targets, compile data sets to train and/or validate computational models to apply in in silico screening campaigns, and implement retrospective and prospective in silico screening experiments.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2982 ","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145438417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Use of B-cell Tetramers for the Study of Trypanosoma cruzi-Specific B cells.","authors":"Damián Pérez-Mazliah","doi":"10.1007/978-1-0716-4848-3_17","DOIUrl":"10.1007/978-1-0716-4848-3_17","url":null,"abstract":"<p><p>Tracking, isolating, and studying antigen-specific B cells is challenging due to their low frequencies. Here, I describe a protocol to study enriched Trypanosoma cruzi (T. cruzi)-specific B cells by flow cytometry. Compared to alternative strategies (e.g., ELISA and ELISPOT), this approach allows detailed phenotyping and/or cell sorting for downstream analysis of T. cruzi-specific B cells.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2982 ","pages":"263-274"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145438543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}