Search results for "Computer simulation"
showing 10 items of 1054 documents
Towards patient stratification and treatment in the autoimmune disease lupus erythematosus using a systems pharmacology approach
2015
Drug development in Systemic Lupus Erythematosus (SLE) has been hindered by poor translation from successful preclinical experiments to clinical efficacy. This lack of success has been attributed to the high heterogeneity of SLE patients and to the lack of understanding of disease physiopathology. Modelling approaches could be useful for supporting the identification of targets, biomarkers and patient subpopulations with differential response to drugs. However, the use of traditional quantitative models based on differential equations is not justifiable in a sparse data situation. Boolean networks models are less demanding on the required data to be implemented and can provide insights into…
Suprathreshold stochastic resonance behind cancer
2018
Noise in gene expression is pervasive and, in some cases, even fulfills a functional role. Cancer cell populations exploit noise to increase heterogeneity as a defense against therapies. What lies behind this picture is a phenomenon of stochastic resonance led by the collective, rather than by individual cells.
In silico identification of small molecules as new cdc25 inhibitors through the correlation between chemosensitivity and protein expression pattern
2021
The cell division cycle 25 (Cdc25) protein family plays a crucial role in controlling cell proliferation, making it an excellent target for cancer therapy. In this work, a set of small molecules were identified as Cdc25 modulators by applying a mixed ligand-structure-based approach and taking advantage of the correlation between the chemosensitivity of selected structures and the protein expression pattern of the proposed target. In the first step of the in silico protocol, a set of molecules acting as Cdc25 inhibitors were identified through a new ligand-based protocol and the evaluation of a large database of molecular structures. Subsequently, induced-fit docking (IFD) studies allowed us…
Identification of biological targets through the correlation between cell line chemosensitivity and protein expression pattern.
2021
Matching biological data sequences is one of the most interesting ways to discover new bioactive compounds. In particular, matching cell chemosensitivity with a protein expression profile can be a useful approach to predict the activity of compounds against definite biological targets. In this review, we discuss this correlation. First, we analyze case studies in which some known drugs, acting on known targets, show a good correlation between their antiproliferative activities and protein expression when a large panel of tumor cells is considered. Then, we highlight how the application of in silico methods based on the correlation between cell line chemosensitivity and gene/protein expressi…
The Potential Role of Direct and Indirect Contacts on Infection Spread in Dairy Farm Networks.
2017
Animals’ exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy). We built between-farm contact networks using data on cattle exchange (direct contacts), and on-farm visits by veterinarians (indirect contacts). We compared the features of the contact structures by using measures on static and temporal networks. We assessed the d…
Multimodal determinants of phase-locked dynamics across deep-superficial hippocampal sublayers during theta oscillations
2020
Theta oscillations play a major role in temporarily defining the hippocampal rate code by translating behavioral sequences into neuronal representations. However, mechanisms constraining phase timing and cell-type-specific phase preference are unknown. Here, we employ computational models tuned with evolutionary algorithms to evaluate phase preference of individual CA1 pyramidal cells recorded in mice and rats not engaged in any particular memory task. We applied unbiased and hypothesis-free approaches to identify effects of intrinsic and synaptic factors, as well as cell morphology, in determining phase preference. We found that perisomatic inhibition delivered by complementary populations…
Search for a Minimal Set of Parameters by Assessing the Total Optimization Potential for a Dynamic Model of a Biochemical Network.
2017
Selecting an efficient small set of adjustable parameters to improve metabolic features of an organism is important for a reduction of implementation costs and risks of unpredicted side effects. In practice, to avoid the analysis of a huge combinatorial space for the possible sets of adjustable parameters, experience-, and intuition-based subsets of parameters are often chosen, possibly leaving some interesting counter-intuitive combinations of parameters unrevealed. The combinatorial scan of possible adjustable parameter combinations at the model optimization level is possible; however, the number of analyzed combinations is still limited. The total optimization potential (TOP) approach is…
Identification of estrogen receptor α ligands with virtual screening techniques.
2016
Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example,…
In silico and in vitro prediction of the toxicological effects of individual and combined mycotoxins.
2018
3-Acetyldeoxynivalenol (3-AcDON) and 15-acetyldeoxynivalenol (15-AcDON) are converted to deoxynivalenol (DON) in vivo and their simultaneous presence may increase DON intake. Mixtures of DON and its derivatives are a public health concern. In this study DON, 3-AcDON and 15-AcDON were evaluated in vitro and in silico. The in vitro cytotoxicity of DON and its derivatives individually and combined was determined by the Neutral Red (NR) assay in human hepatocarcinoma (HepG2) cells. The concentrations tested were from 1.25 to 15 μM (DON) and from 0.937 to 7.5 μM (DON derivatives). The IC50 values were from >15 to 2.55 μM (DON), from 1.77 to 1.02 μM (3-AcDON), and from 4.05 to 1.68 μM (15-AcDON).…
Mathematical model of T-cell lymphoblastic lymphoma: disease, treatment, cure or relapse of a virtual cohort of patients
2017
International audience; T lymphoblastic lymphoma (T-LBL) is a rare type of lymphoma with a good prognosis with a remission rate of 85%. Patients can be completely cured or can relapse during or after a 2-year treatment. Relapses usually occur early after the remission of the acute phase. The median time of relapse is equal to 1 year, after the occurrence of complete remission (range 0.2–5.9 years) (Uyttebroeck et al., 2008). It can be assumed that patients may be treated longer than necessary with undue toxicity. The aim of our model was to investigate whether the duration of the maintenance therapy could be reduced without increasing the risk of relapses and to determine the minimum treatm…