Perspectives on computational modeling of biological systems and the significance of the SysMod community.

Motivation: In recent years, applying computational modeling to systems biology has caused a substantial surge in both discovery and practical applications and a significant shift in our understanding of the complexity inherent in biological systems.

Results: In this perspective article, we briefly overview computational modeling in biology, highlighting recent advancements such as multi-scale modeling due to the omics revolution, single-cell technology, and integration of artificial intelligence and machine learning approaches. We also discuss the primary challenges faced: integration, standardization, model complexity, scalability, and interdisciplinary collaboration.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.

Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms.

Augusta: From RNA-Seq to gene regulatory networks and Boolean models.

Computational models of gene regulations help to understand regulatory mechanisms and are extensively used in a wide range of areas, e.g., biotechnology or medicine, with significant benefits.

COMO: a pipeline for multi-omics data integration in metabolic modeling and drug discovery.

Identifying potential drug targets using metabolic modeling requires integrating multiple modeling methods and heterogeneous biological datasets, which can be challenging without efficient tools. We developed Constraint-based Optimization of Metabolic Objectives (COMO), a user-friendly pipeline that integrates multi-omics data processing, context-specific metabolic model development, simulations, drug databases and disease data to aid drug discovery. COMO can be installed as a Docker Image or with Conda and includes intuitive instructions within a Jupyter Lab environment.

A multiscale mechanistic model of human dendritic cells for investigation of immune responses and novel therapeutics discovery.

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype.

Arginine Catabolism and Polyamine Biosynthesis Pathway Disparities Within Subpopulations.

is a highly infectious zoonotic pathogen with as few as 10 organisms causing tularemia, a disease that is fatal if untreated. Although subspecies (type A) and subspecies (type B) share over 99.5% average nucleotide identity, notable differences exist in genomic organization and pathogenicity.

A computational approach to investigate constitutive activation of NF-κB.

Nuclear factor kappa B (NF-κB) signaling is the master regulator of inflammatory pathways; therefore, its regulation has been the subject of investigation since last two decades. Multiple models have been published that describes the dynamics of NF-κB activity by stimulated activation and feedback loops. However, there is also paramount evidence of the critical role of posttranslational modifications (PTMs) in the regulation of NF-κB pathway.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources.

A multi-approach and multi-scale platform to model CD4+ T cells responding to infections.

Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells, which uses four modeling approaches to integrate processes at three spatial scales in different tissues. In each cell, signal transduction and gene regulation are described by a logical model, metabolism by constraint-based models.

An in silico, structural, and biological analysis of lactoferrin of different mammals.

Lactoferrin (LF) belongs to the family of transferrins having multifunctional roles associated with the immune system of animals. To follow the aims for this study was selected 20 sequences of LF from mammalian species to evaluate the chemical, biological, and structural properties. Bioinformatics approaches used programs such as MAFFT for sequence alignment; PartitionFinder and MrBayes for phylogenetic approaches; I-TASSER, PROCHECK, Molecular Operating Environment (MOE), SWISS Model server, Peptide DB and Expasy ProtParam to estimate the physicochemical properties, to model the protein and predicted secondary structures.

Integrative network analyses of transcriptomics data reveal potential drug targets for acute radiation syndrome.

Recent political unrest has highlighted the importance of understanding the short- and long-term effects of gamma-radiation exposure on human health and survivability. In this regard, effective treatment for acute radiation syndrome (ARS) is a necessity in cases of nuclear disasters. Here, we propose 20 therapeutic targets for ARS identified using a systematic approach that integrates gene coexpression networks obtained under radiation treatment in humans and mice, drug databases, disease-gene association, radiation-induced differential gene expression, and literature mining.

Integrative computational approach identifies drug targets in CD4 T-cell-mediated immune disorders.

CD4 T cells provide adaptive immunity against pathogens and abnormal cells, and they are also associated with various immune-related diseases. CD4 T cells' metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about possible target space in the context of a modeled disease.

Differences in Blood-derived Type B Strains from Clinical Cases of Tularemia.

can cause the zoonotic disease tularemia and is partitioned into subspecies due to differences in chromosomal organization and virulence. The subspecies (type B) is generally considered more clonal than the other subpopulations with moderate virulence compared to the hypervirulent A.I clade.

Combined TLR4 and TLR9 agonists induce distinct phenotypic changes in innate immunity in vitro and in vivo.

Toll-like receptor (TLR)4 and TLR9 agonists, MPL and CpG, are used as adjuvants in vaccines and have been investigated for their combined potential. However, how these two combined agonists regulate transcriptional changes in innate immune cells and cells at the site of vaccination has not been thoroughly investigated. Here, we utilized transcriptomics to investigate how CpG, MPL, and CpG + MPL impact gene expression in dendritic cells (DC) in vitro.

Identification of Biologically Essential Nodes via Determinative Power in Logical Models of Cellular Processes.

A variety of biological networks can be modeled as logical or Boolean networks. However, a simplification of the reality to binary states of the nodes does not ease the difficulty of analyzing the dynamics of large, complex networks, such as signal transduction networks, due to the exponential dependence of the state space on the number of nodes. This paper considers a recently introduced method for finding a fairly small subnetwork, representing a collection of nodes that determine the states of most other nodes with a reasonable level of entropy.

A Mechanistic Computational Model Reveals That Plasticity of CD4 T Cell Differentiation Is a Function of Cytokine Composition and Dosage.

CD4 T cells provide cell-mediated immunity in response to various antigens. During an immune response, naïve CD4 T cells differentiate into specialized effector T helper (Th1, Th2, and Th17) cells and induced regulatory (iTreg) cells based on a cytokine milieu. In recent studies, complex phenotypes resembling more than one classical T cell lineage have been experimentally observed.

T2DiACoD: A Gene Atlas of Type 2 Diabetes Mellitus Associated Complex Disorders.

We performed integrative analysis of genes associated with type 2 Diabetes Mellitus (T2DM) associated complications by automated text mining with manual curation and also gene expression analysis from Gene Expression Omnibus. They were analysed for pathogenic or protective role, trends, interaction with risk factors, Gene Ontology enrichment and tissue wise differential expression. The database T2DiACoD houses 650 genes, and 34 microRNAs associated with T2DM complications.

Integration of Metabolic Modeling with Gene Co-expression Reveals Transcriptionally Programmed Reactions Explaining Robustness in Mycobacterium tuberculosis.

Robustness of metabolic networks is accomplished by gene regulation, modularity, re-routing of metabolites and plasticity. Here, we probed robustness against perturbations of biochemical reactions of M. tuberculosis in the form of predicting compensatory trends.

Systems Perturbation Analysis of a Large-Scale Signal Transduction Model Reveals Potentially Influential Candidates for Cancer Therapeutics.

Dysregulation in signal transduction pathways can lead to a variety of complex disorders, including cancer. Computational approaches such as network analysis are important tools to understand system dynamics as well as to identify critical components that could be further explored as therapeutic targets. Here, we performed perturbation analysis of a large-scale signal transduction model in extracellular environments that stimulate cell death, growth, motility, and quiescence.

Structural and binding studies of SAP-1 protein with heparin.

SAP-1 is a low molecular weight cysteine protease inhibitor (CPI) which belongs to type-2 cystatins family. SAP-1 protein purified from human seminal plasma (HuSP) has been shown to inhibit cysteine and serine proteases and exhibit interesting biological properties, including high temperature and pH stability. Heparin is a naturally occurring glycosaminoglycan (with varied chain length) which interacts with a number of proteins and regulates multiple steps in different biological processes.