scholarly journals Large-Scale Virtual Screening Against the MET Kinase Domain Identifies a New Putative Inhibitor Type

Molecules ◽  
2020 ◽  
Vol 25 (4) ◽  
pp. 938 ◽  
Author(s):  
Emmanuel Bresso ◽  
Alessandro Furlan ◽  
Philippe Noel ◽  
Vincent Leroux ◽  
Flavio Maina ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Binding Site ◽  
Large Scale ◽  
Cost Effective ◽  
Kinase Domain ◽  
Functional Method ◽  
Conformational Space ◽  
Classical Type ◽  
Type I ◽  
Ensemble Docking

By using an ensemble-docking strategy, we undertook a large-scale virtual screening campaign in order to identify new putative hits against the MET kinase target. Following a large molecular dynamics sampling of its conformational space, a set of 45 conformers of the kinase was retained as docking targets to take into account the flexibility of the binding site moieties. Our screening funnel started from about 80,000 chemical compounds to be tested in silico for their potential affinities towards the kinase binding site. The top 100 molecules selected—thanks to the molecular docking results—were further analyzed for their interactions, and 25 of the most promising ligands were tested for their ability to inhibit MET activity in cells. F0514-4011 compound was the most efficient and impaired this scattering response to HGF (Hepatocyte Growth Factor) with an IC 50 of 7.2 μ M. Interestingly, careful docking analysis of this molecule with MET suggests a possible conformation halfway between classical type-I and type-II MET inhibitors, with an additional region of interaction. This compound could therefore be an innovative seed to be repositioned from its initial antiviral purpose towards the field of MET inhibitors. Altogether, these results validate our ensemble docking strategy as a cost-effective functional method for drug development.

scholarly journals Ensemble Docking Coupled to Linear Interaction Energy Calculations for Identification of Coronavirus Main Protease (3CLpro) Non-Covalent Small-Molecule Inhibitors

Molecules ◽  
2020 ◽  
Vol 25 (24) ◽  
pp. 5808
Author(s):  
Marko Jukič ◽  
Dušanka Janežič ◽  
Urban Bren
Keyword(s):  
Virtual Screening ◽  
Interaction Energy ◽  
Binding Free Energy ◽  
Conformational Space ◽  
Binding Modes ◽  
Linear Interaction ◽  
Linear Interaction Energy ◽  
Ensemble Docking ◽  
Novel Approach ◽  
Screening Study

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential inhibitors of the SARS-CoV-2 main viral protease (3CLpro or Mpro). For this purpose, we developed a novel approach using ensemble docking high-throughput virtual screening directly coupled with subsequent Linear Interaction Energy (LIE) calculations to maximize the conformational space sampling and to assess the binding affinity of identified inhibitors. A large database of small commercial compounds was prepared, and top-scoring hits were identified with two compounds singled out, namely 1-[(R)-2-(1,3-benzimidazol-2-yl)-1-pyrrolidinyl]-2-(4-methyl-1,4-diazepan-1-yl)-1-ethanone and [({(S)-1-[(1H-indol-2-yl)methyl]-3-pyrrolidinyl}methyl)amino](5-methyl-2H-pyrazol-3-yl)formaldehyde. Moreover, we obtained a favorable binding free energy of the identified compounds, and using contact analysis we confirmed their stable binding modes in the 3CLpro active site. These compounds will facilitate further 3CLpro inhibitor design.

scholarly journals p38α MAPK and Type I Inhibitors: Binding Site Analysis and Use of Target Ensembles in Virtual Screening

Molecules ◽  
2015 ◽  
Vol 20 (9) ◽  
pp. 15842-15861 ◽  
Author(s):  
Andrea Astolfi ◽  
Nunzio Iraci ◽  
Stefano Sabatini ◽  
Maria Barreca ◽  
Violetta Cecchetti
Keyword(s):  
Virtual Screening ◽  
Binding Site ◽  
Type I ◽  
Site Analysis ◽  
P38α Mapk

scholarly journals Effective Use of Empirical Data for Virtual Screening against APJR GPCR Receptor

Molecules ◽  
2021 ◽  
Vol 26 (16) ◽  
pp. 4894
Author(s):  
Laura C. E. Manoliu ◽  
Eliza C. Martin ◽  
Adina L. Milac ◽  
Laurentiu Spiridon
Keyword(s):  
Virtual Screening ◽  
Binding Site ◽  
Large Scale ◽  
Neurodegenerative Disorder ◽  
Docking Simulation ◽  
Search Space ◽  
Design Strategies ◽  
Receptor Binding Site ◽  
In Silico Studies ◽  
The Central Nervous System

Alzheimer’s disease is a neurodegenerative disorder incompatible with normal daily activity, affecting one in nine people. One of its potential targets is the apelin receptor (APJR), a G-protein coupled receptor, which presents considerably high expression levels in the central nervous system. In silico studies of APJR drug-like molecule binding are in small numbers while high throughput screenings (HTS) are already sufficiently many to devise efficient drug design strategies. This presents itself as an opportunity to optimize different steps in future large scale virtual screening endeavours. Here, we ran a first stage docking simulation against a library of 95 known binders and 3829 generated decoys in an effort to improve the rescoring stage. We then analyzed receptor binding site structure and ligands binding poses to describe their interactions. As a result, we devised a simple and straightforward virtual screening Stage II filtering score based on search space extension followed by a geometric estimation of the ligand—binding site fitness. Having this score, we used an ensemble of receptors generated by Hamiltonian Monte Carlo simulation and reported the results. The improvements shown herein prove that our ensemble docking protocol is suited for APJR and can be easily extrapolated to other GPCRs.

scholarly journals Acquired Mutations within the JAK2 Kinase Domain Confer Resistance to JAK Inhibitors in an in Vitro model of a High-Risk Acute Lymphoblastic Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 5-6
Author(s):  
Charlotte EJ Downes ◽  
Barbara J McClure ◽  
Jacqueline Rehn ◽  
James Breen ◽  
John B Bruning ◽  
...  
Keyword(s):  
High Risk ◽  
Binding Site ◽  
Lymphoblastic Leukemia ◽  
Computational Modelling ◽  
Kinase Domain ◽  
Atp Binding ◽  
Type I ◽  
Type Ii ◽  
Jak Inhibitors ◽  
Atp Binding Site

Introduction Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) is a high-risk subtype of ALL associated with high relapse rates and poor survival. Rearrangements of Janus kinase 2 (JAK2r) are present in approximately 5% and 14% of pediatric and young adult Ph-like ALL cases respectively. The resultant JAK2 gene fusions drive leukemogenesis through constitutive activation of the JAK/STAT signaling pathway and are associated with very poor outcomes in patients with Ph-like ALL. All JAK inhibitors in clinical development are type I inhibitors, which bind in the ATP-binding site of JAK2. A phase II clinical trial is currently assessing the only FDA-approved JAK1/2 inhibitor, ruxolitinib in high-risk B-cell ALL cases harboring JAK2 alterations. The development of treatment resistance to targeted inhibitors in other diseases is well documented and often results in disease relapse. Elucidating mechanisms of ruxolitinib resistance in JAK2r ALL will inform approaches to monitor the emergence of resistance in ongoing clinical trials and enable the development of therapeutic strategies to overcome or avert resistance. Methods JAK2r B-ALL was modelled in the pro-B cell line, Ba/F3, by expressing the high-risk B-ALL fusion, ATF7IP-JAK2. Ruxolitinib resistance in three independent ATF7IP-JAK2 Ba/F3 cell lines was achieved following dose escalation to a clinically relevant dose of 1 μM ruxolitinib. Sanger sequencing of the RT-PCR amplified JAK2 fusion revealed each resistant line had acquired a different mutation within the JAK2 kinase domain. Therapeutic sensitives were assessed by staining with Fixable Aqua Dead Cell Stain (Invitrogen) and Annexin V, and analysis by flow cytometry. Alterations in signaling pathways were determined using phosphoflow cytometry and western blot analysis. Computational modelling of acquired JAK2 mutations and subsequent influence on ruxolitinib binding was performed using ICM-Pro (Molsoft L.C.C.). Results In addition to the identification of two known ruxolitinib resistant mutations, JAK2 p.Y931C and p.L983F, a novel p.G993A mutation was identified. All mutations localized to the ATP/ruxolitinib binding site and conferred resistance to multiple type-I JAK inhibitors, including ruxolitinib, BMS-911543, and AZD-1480 (Table 1). JAK2 p.G993A ATF7IP-JAK2 Ba/F3 cells were also resistant to the type-II JAK inhibitor, CHZ-868, which binds in an allosteric site of JAK2 in addition to the ATP-binding site. Ruxolitinib resistance correlated with sustained downstream STAT5 activation in the presence of 1 μM ruxolitinib compared with non-mutant ATF7IP-JAK2 Ba/F3 cells. Intracellular phosphoflow cytometry of ruxolitinib-resistant ATF7IP-JAK2 Ba/F3 cells confirmed constitutive activation of JAK/STAT signaling in the presence of 50 nM ruxolitinib, in contrast to non-mutant ATF7IP-JAK2 Ba/F3 cells. Computational modelling suggested that JAK2 p.L983F (Fig. 1D) sterically hinders ruxolitinib binding, while JAK2 p.Y931C may reduce ruxolitinib binding affinity by disruption of a critical hydrogen-bond (Fig. 1B). The novel JAK2 p.G993A mutation is predicted to alter DFG-loop dynamics by stabilizing the JAK2 activation loop (Fig1C). Conclusions This study demonstrates that the JAK2 ATP-binding site is susceptible to JAK inhibitor resistant mutations following ruxolitinib exposure in the setting of JAK2r ALL, highlighting the importance of monitoring the emergence of mutations within this region. In addition to previously described mutations we identified a novel JAK2 p.G993A mutation that conferred resistance to both type-I and type-II JAK inhibitors. The JAK2 p.G993A mutation was postulated to modulate the stability of a conserved domain. Understanding mechanisms of ruxolitinib resistance, as modelled here, has the potential to inform future drug design and the development therapeutic strategies for this high-risk cohort. Disclosures White: Amgen: Honoraria; Bristol-Myers Squibb: Honoraria, Research Funding.

Comprehensive in silico Study of GLUT10: Prediction of Possible Substrate Binding Sites and Interacting Molecules

2020 ◽  
Vol 21 (2) ◽  
pp. 117-130 ◽  
Author(s):  
Mohammad J. Hosen ◽  
Mahmudul Hasan ◽  
Sourav Chakraborty ◽  
Ruhshan A. Abir ◽  
Abdullah Zubaer ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Binding Site ◽  
Glucose Transporter ◽  
Substrate Binding ◽  
Mutation Screening ◽  
Homology Model ◽  
Connective Tissue Disorder ◽  
Crystallographic Structure ◽  
Substrate Binding Site

Objectives: The Arterial Tortuosity Syndrome (ATS) is an autosomal recessive connective tissue disorder, mainly characterized by tortuosity and stenosis of the arteries with a propensity towards aneurysm formation and dissection. It is caused by mutations in the SLC2A10 gene that encodes the facilitative glucose transporter GLUT10. The molecules transported by and interacting with GLUT10 have still not been unambiguously identified. Hence, the study attempts to identify both the substrate binding site of GLUT10 and the molecules interacting with this site. Methods: As High-resolution X-ray crystallographic structure of GLUT10 was not available, 3D homology model of GLUT10 in open conformation was constructed. Further, molecular docking and bioinformatics investigation were employed. Results and Discussion: Blind docking of nine reported potential in vitro substrates with this 3D homology model revealed that substrate binding site is possibly made with PRO531, GLU507, GLU437, TRP432, ALA506, LEU519, LEU505, LEU433, GLN525, GLN510, LYS372, LYS373, SER520, SER124, SER533, SER504, SER436 amino acid residues. Virtual screening of all metabolites from the Human Serum Metabolome Database and muscle metabolites from Human Metabolite Database (HMDB) against the GLUT10 revealed possible substrates and interacting molecules for GLUT10, which were found to be involved directly or partially in ATS progression or different arterial disorders. Reported mutation screening revealed that a highly emergent point mutation (c. 1309G>A, p. Glu437Lys) is located in the predicted substrate binding site region. Conclusion: Virtual screening expands the possibility to explore more compounds that can interact with GLUT10 and may aid in understanding the mechanisms leading to ATS.

Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Yan Pan ◽  
Shining Li ◽  
Qianwu Chen ◽  
Nan Zhang ◽  
Tao Cheng ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Load Capacity ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Promising Alternative ◽  
Logistics Industry ◽  
Last Mile ◽  
Delivery Scheduling ◽  
Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

scholarly journals Multi-Country Scale Assessment of Available Energy Recovery Potential Using Micro-Hydropower in Drinking, Pressurised Irrigation and Wastewater Networks, Covering Part of the EU

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 899
Author(s):  
Djordje Mitrovic ◽  
Miguel Crespo Chacón ◽  
Aida Mérida García ◽  
Jorge García Morillo ◽  
Juan Antonio Rodríguez Diaz ◽  
...  
Keyword(s):  
Drinking Water ◽  
Northern Ireland ◽  
Energy Recovery ◽  
Large Scale ◽  
Significant Proportion ◽  
Value Added ◽  
Cost Effective ◽  
Net Energy ◽  
Water Networks ◽  
Scale Assessment

Studies have shown micro-hydropower (MHP) opportunities for energy recovery and CO2 reductions in the water sector. This paper conducts a large-scale assessment of this potential using a dataset amassed across six EU countries (Ireland, Northern Ireland, Scotland, Wales, Spain, and Portugal) for the drinking water, irrigation, and wastewater sectors. Extrapolating the collected data, the total annual MHP potential was estimated between 482.3 and 821.6 GWh, depending on the assumptions, divided among Ireland (15.5–32.2 GWh), Scotland (17.8–139.7 GWh), Northern Ireland (5.9–8.2 GWh), Wales (10.2–8.1 GWh), Spain (375.3–539.9 GWh), and Portugal (57.6–93.5 GWh) and distributed across the drinking water (43–67%), irrigation (51–30%), and wastewater (6–3%) sectors. The findings demonstrated reductions in energy consumption in water networks between 1.7 and 13.0%. Forty-five percent of the energy estimated from the analysed sites was associated with just 3% of their number, having a power output capacity >15 kW. This demonstrated that a significant proportion of energy could be exploited at a small number of sites, with a valuable contribution to net energy efficiency gains and CO2 emission reductions. This also demonstrates cost-effective, value-added, multi-country benefits to policy makers, establishing the case to incentivise MHP in water networks to help achieve the desired CO2 emissions reductions targets.

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

scholarly journals A novel ligand of the translationally controlled tumor protein (TCTP) identified by virtual drug screening for cancer differentiation therapy

2021 ◽  
Author(s):  
Nicolas Fischer ◽  
Ean-Jeong Seo ◽  
Sara Abdelfatah ◽  
Edmond Fleischer ◽  
Anette Klinger ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Virtual Screening ◽  
Small Molecules ◽  
Large Scale ◽  
Differentiation Therapy ◽  
P53 Expression ◽  
Microscale Thermophoresis ◽  
Cycle Arrest ◽  
G1 Cell Cycle Arrest ◽  
Mcf 7

SummaryIntroduction Differentiation therapy is a promising strategy for cancer treatment. The translationally controlled tumor protein (TCTP) is an encouraging target in this context. By now, this field of research is still at its infancy, which motivated us to perform a large-scale screening for the identification of novel ligands of TCTP. We studied the binding mode and the effect of TCTP blockade on the cell cycle in different cancer cell lines. Methods Based on the ZINC-database, we performed virtual screening of 2,556,750 compounds to analyze the binding of small molecules to TCTP. The in silico results were confirmed by microscale thermophoresis. The effect of the new ligand molecules was investigated on cancer cell survival, flow cytometric cell cycle analysis and protein expression by Western blotting and co-immunoprecipitation in MOLT-4, MDA-MB-231, SK-OV-3 and MCF-7 cells. Results Large-scale virtual screening by PyRx combined with molecular docking by AutoDock4 revealed five candidate compounds. By microscale thermophoresis, ZINC10157406 (6-(4-fluorophenyl)-2-[(8-methoxy-4-methyl-2-quinazolinyl)amino]-4(3H)-pyrimidinone) was identified as TCTP ligand with a KD of 0.87 ± 0.38. ZINC10157406 revealed growth inhibitory effects and caused G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. ZINC10157406 (2 × IC50) downregulated TCTP expression by 86.70 ± 0.44% and upregulated p53 expression by 177.60 ± 12.46%. We validated ZINC10157406 binding to the p53 interaction site of TCTP and replacing p53 by co-immunoprecipitation. Discussion ZINC10157406 was identified as potent ligand of TCTP by in silico and in vitro methods. The compound bound to TCTP with a considerably higher affinity compared to artesunate as known TCTP inhibitor. We were able to demonstrate the effect of TCTP blockade at the p53 binding site, i.e. expression of TCTP decreased, whereas p53 expression increased. This effect was accompanied by a dose-dependent decrease of CDK2, CDK4, CDK, cyclin D1 and cyclin D3 causing a G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. Our findings are supposed to stimulate further research on TCTP-specific small molecules for differentiation therapy in oncology.

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