Computational Biology and Chemistry This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Tensor improve equivariant graph neural network for molecular dynamics prediction
Comput Biol Chem. 2024 Mar 15;110:108053. doi: 10.1016/j.compbiolchem.2024.108053. Online ahead of print.ABSTRACTMolecular dynamics(MD) simulations are essential for molecular structure optimization, drug-drug interactions, and other fields of drug discovery by simulating the motion of microscopic particles to calculate their macroscopic properties (e.g., energy). The main problems of the existing work are as follows: (1) Failure to fully consider the chemical bonding constraints between atoms, (2) Group equivariance can help achieve robust and accurate predictions of MD under arbitrary reference transformations and should...
Source: Computational Biology and Chemistry - March 23, 2024 Category: Bioinformatics Authors: Chi Jiang Yi Zhang Yang Liu Jing Peng Source Type: research

An assessment of crucial structural contributors of HDAC6 inhibitors through fragment-based non-linear pattern recognition and molecular dynamics simulation approaches
Comput Biol Chem. 2024 Mar 11;110:108051. doi: 10.1016/j.compbiolchem.2024.108051. Online ahead of print.ABSTRACTAmidst the Zn2+-dependant isoforms of the HDAC family, HDAC6 has emerged as a potential target associated with an array of diseases, especially cancer and neuronal disorders like Rett's Syndrome, Alzheimer's disease, Huntington's disease, etc. Also, despite the availability of a handful of HDAC inhibitors in the market, their non-selective nature has restricted their use in different disease conditions. In this situation, the development of selective and potent HDAC6 inhibitors will provide efficacious therapeut...
Source: Computational Biology and Chemistry - March 23, 2024 Category: Bioinformatics Authors: Suvankar Banerjee Sandeep Jana Tarun Jha Balaram Ghosh Nilanjan Adhikari Source Type: research

In silico exploration of CB2 receptor agonist in the management of neuroinflammatory conditions by pharmacophore modeling
Comput Biol Chem. 2024 Mar 10;110:108049. doi: 10.1016/j.compbiolchem.2024.108049. Online ahead of print.ABSTRACTEndocannabinoid system plays a pivotal role in controlling neuroinflammation, and modulating this system may not only aid in managing symptoms of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, Multiple sclerosis, Epilepsy, Central and Peripheral neuropathic pain, but also, have the potential to target these diseases at an early-stage. In the present study, six different pharmacophore hypotheses were generated from Cannabidiol (CBD)-Cannabinoid Receptor subtype-2 (CB2) and then Zinc ...
Source: Computational Biology and Chemistry - March 20, 2024 Category: Bioinformatics Authors: Shlok Bodke Nachiket Joshi Rajasekhar Reddy Alavala Divya Suares Source Type: research

Mammalian maltase-glucoamylase and sucrase-isomaltase inhibitory effects of Artocarpus heterophyllus: An in vitro and in silico approach
Comput Biol Chem. 2024 Mar 12;110:108052. doi: 10.1016/j.compbiolchem.2024.108052. Online ahead of print.ABSTRACTAlpha-glucosidase (maltase, sucrase, isomaltase and glucoamylase) activities which are involved in carbohydrate metabolism are present in human intestinal maltase-glucoamylase (MGAM) and sucrase-isomaltase (SI). Hence, these proteins are important targets to identify drugs against postprandial hyperglycemia thereby for diabetes. To find natural-based drugs against MGAM and SI, Artocarpus heterophyllus leaf was explored for MGAM and SI inhibition in in vitro and in silico. A. heterophyllus leaf aqueous active fra...
Source: Computational Biology and Chemistry - March 16, 2024 Category: Bioinformatics Authors: Parveen Abdulhaniff Penislusshiyan Sakayanathan Chitra Loganathan Ancy Iruthayaraj Ramesh Thiyagarajan Palvannan Thayumanavan Source Type: research

Elucidation of escitalopram oxalate and related antidepressants as putative inhibitors of PTP4A3/PRL-3 protein in hepatocellular carcinoma: A multi-computational investigation
Comput Biol Chem. 2024 Feb 29;110:108039. doi: 10.1016/j.compbiolchem.2024.108039. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) persists to be one of the most devastating and deadliest malignancies globally. Recent research into the molecular signaling networks entailed in many malignancies has given some prominent insights that can be leveraged to create molecular therapeutics for combating HCC. Therefore, in the current communication, an in-silico drug repurposing approach has been employed to target the function of PTP4A3/PRL-3 protein in HCC using antidepressants: Fluoxetine hydrochloride, Citalopram, A...
Source: Computational Biology and Chemistry - March 12, 2024 Category: Bioinformatics Authors: Ishfaq Hassan Mir Kankipati Teja Shyam Susmida Seni Balakrishnan Muthuvel Suresh Kumar Thiyagarajan Ramesh Chinnasamy Thirunavukkarasu Source Type: research

Unveiling potential repurposed drug candidates for Plasmodium falciparum through in silico evaluation: A synergy of structure-based approaches, structure prediction, and molecular dynamics simulations
Comput Biol Chem. 2024 Mar 2;110:108048. doi: 10.1016/j.compbiolchem.2024.108048. Online ahead of print.ABSTRACTThe rise of drug resistance in Plasmodium falciparum, rendering current treatments ineffective, has hindered efforts to eliminate malaria. To address this issue, the study employed a combination of Systems Biology approach and a structure-based pharmacophore method to identify a target against P. falciparum. Through text mining, 448 genes were extracted, and it was discovered that plasmepsins, found in the Plasmodium genus, play a crucial role in the parasite's survival. The metabolic pathways of these proteins w...
Source: Computational Biology and Chemistry - March 12, 2024 Category: Bioinformatics Authors: Abhichandan Das Sanchaita Rajkhowa Subrata Sinha Magdi E A Zaki Source Type: research

HKFGCN: A novel multiple kernel fusion framework on graph convolutional network to predict microbe-drug associations
Comput Biol Chem. 2024 Mar 2;110:108041. doi: 10.1016/j.compbiolchem.2024.108041. Online ahead of print.ABSTRACTAccumulating clinical studies have consistently demonstrated that the microbes in the human body closely interact with the human host, actively participating in the regulation of drug effectiveness. Identifying the associations between microbes and drugs can facilitate the development of drug discovery, and microbes have become a new target in antimicrobial drug development. However, the discovery of microbe-drug associations relies on clinical or biological experiments, which are not only time-consuming but also...
Source: Computational Biology and Chemistry - March 12, 2024 Category: Bioinformatics Authors: Ziyu Wu Shasha Li Lingyun Luo Pingjian Ding Source Type: research