Virtual screening

Targeting polo-box domain (PBD) small molecule for polo-like kinase 1 (PLK1) inhibition is a viable alternative to target kinase domain (KD), which could avoid pan-selectivity and dose-limiting toxicity of ATP-competitive inhibitors. However, their efficacy in these settings is still low and inaccessible to clinical requirement. Herein, we utilized a structure-based high-throughput virtual screen to find novel chemical scaffold capable of inhibiting PLK1 via targeting PBD and identified an initial hit molecule compound 1a...

BACKGROUND: Digital health technologies (DHTs) are increasingly used in physical stroke rehabilitation to support individuals in successfully engaging with the frequent, intensive, and lengthy activities required to optimize recovery. Despite this, little is known about behavior change within these interventions. OBJECTIVE: This scoping review aimed to identify if and how behavior change approaches (ie, theories, models, frameworks, and techniques to influence behavior) are incorporated within physical stroke rehabilitation interventions that include a DHT...

No abstract text is available yet for this article.

Discovering effective anti-cancer agents poses a formidable challenge given the limited efficacy of current therapeutic modalities against various cancer types due to intrinsic resistance mechanisms. Cancer immunochemotherapy is an alternative strategy for breast cancer treatment and overcoming cancer resistance. Human Indoleamine 2,3-dioxygenase (hIDO1) and human Tryptophan 2,3-dioxygenase 2 (hTDO2) play pivotal roles in tryptophan metabolism, leading to the generation of kynurenine and other bioactive metabolites...

Drug repurposing is promising in multiple scenarios, such as emerging viral outbreak controls and cost reductions of drug discovery. Traditional graph-based drug repurposing methods are limited to fast, large-scale virtual screens, as they constrain the counts for drugs and targets and fail to predict novel viruses or drugs. Moreover, though deep learning has been proposed for drug repurposing, only a few methods have been used, including a group of pre-trained deep learning models for embedding generation and transfer learning...

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane...

Melanin is the major pigment responsible for the coloring of mammalian skin, hair, and eyes to defend against ultraviolet radiation. However, excessive melanin production has resulted in numerous types of hyperpigmentation disorders. Tyrosinase-related protein 1 (TYRP1) is a transmembrane glycoprotein enzyme found in many organisms, including humans, that plays an important role in melanogenesis. Thus, controlling the enzyme activity of TYRP1 with tyrosinase inhibitors is a vital step in the treatment of hyperpigmentation problems in humans...

Antimicrobial resistance (AMR) is a pressing global issue exacerbated by the abuse of antibiotics and the formation of bacterial biofilms, which cause up to 80% of human bacterial infections. This study presents a computational strategy to address AMR by developing three novel quantitative structure-activity relationship (QSAR) models based on molecular topology to identify potential anti-biofilm and antibacterial agents. The models aim to determine the chemo-topological pattern of Gram (+) antibacterial, Gram (-) antibacterial, and biofilm formation inhibition activity...

In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. In recent years, two computational techniques, machine learning (ML) and physics-based methods, have evolved substantially and are now frequently incorporated into the medicinal chemist's toolbox to enhance the efficiency of both hit optimization and candidate design. Both computational methods come with their own set of limitations, and they are often used independently of each other...

The engineered human cystathionine-γ-lyase (hCGL) resulting in enhanced activity toward both cysteine and cystine unveils a potential robust antitumor activity. However, the presence of cysteine residues has the potential to induce oligomerization or incorrect disulfide bonding, which may decrease the bioavailability of biopharmaceuticals. Through a meticulous design process targeting the cysteine residues within engineered hCGL, a set of potential beneficial mutants were obtained by virtual screening employing Rosetta and ABACUS...

INTRODUCTION: Virtual reality (VR) exercises are reportedly beneficial as a physical activity tool for health promotion and rehabilitation, and can also help individuals exercise under professional supervision. We developed and investigated the potential feasibility of a VR-based aerobic exercise program using the XBOX ONE console and Kinect sensor with real-time pulse rate monitoring. The VR setting consisted of two-dimensional (2D) environments via computer, laptop, or television screens...

Syndecan-binding protein (SDCBP) was reported to stimulate the advancement of esophageal squamous cell carcinoma (ESCC) and could potentially be a target for ESCC treatment. There is a growing corpus of research on the anti-tumor effects of iron chelators; however, very few studies have addressed the involvement of dexrazoxane in cancer. In this study, structure-based virtual screening was employed to select drugs targeting SDCBP from the Food and Drug Administration (FDA)-approved drug databases. The sepharose 4B beads pull-down assay revealed that dexrazoxane targeted SDCBP by interacting with its PDZ1 domain...

Alzheimer's disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aβ) peptides. The extracellular deposition of Aβ peptides in human AD brain causes neuronal death. Therefore, it has been found that Aβ peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD's active site residues and substrate binding mode...

Hepatitis B and C viruses (HBV and HCV) are significant causes of chronic liver diseases, with approximately 350 million infections globally. To accelerate the finding of effective treatment options, we introduce HBCVTr, a novel ligand-based drug design (LBDD) method for predicting the inhibitory activity of small molecules against HBV and HCV. HBCVTr employs a hybrid model consisting of double encoders of transformers and a deep neural network to learn the relationship between small molecules' simplified molecular-input line-entry system (SMILES) and their antiviral activity against HBV or HCV...

PURPOSE: Breast density is a significant risk factor for breast cancer and can impact the sensitivity of screening mammography. Area-based breast density measurements may not provide an accurate representation of the tissue distribution, therefore volumetric breast density (VBD) measurements are preferred. Dual-energy mammography enables volumetric measurements without additional assumptions about breast shape. In this work we evaluated the performance of a dual-energy decomposition technique for determining VBD by applying it to virtual anthropomorphic phantoms...

Host-microbe systems are evolutionary niches that produce coevolved biological interactions and are a key component of global health. However, these systems have historically been a difficult field of biological research due to their experimental intractability. Impactful advances in global health will be obtained by leveraging in silico screens to identify genes involved in mediating interspecific interactions. These predictions will progress our understanding of these systems and lay the groundwork for future in vitro and in vivo experiments and bioengineering projects...

Human norovirus (HuNoV), a primary cause of non-bacterial gastroenteritis, currently lacks approved treatment. RdRp is vital for virus replication, making it an attractive target for therapeutic intervention. By application of structure-based virtual screening procedure, we present CX-6258 hydrochloride hydrate as a potent RdRp non-nucleoside inhibitor, effectively inhibiting HuNoV RdRp activity with an IC50 of 3.61 μM. Importantly, this compound inhibits viral replication in cell culture, with an EC50 of 0...

Application of retinol (Vitamin A, VA) in skincare is limited for instability, poor water solubility, and skin intolerance that combats skin aging. We employed computer-aided virtual screening and cell experiments with transcriptomics, thereby unveiling the comprehensive gene expression and regulation pathway of photoaging HaCaT cell treated with ferulic acid (FA) in synergizing with VA. Through network pharmacology analysis, the combined use of VA and FA exhibited highly correlated cross-targets with skin aging acting on EGFR, PTPN1, ESR2, GSK3B, BACE1, PYGL, PTGS2 and APP...

Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and the second most common among children. AML is characterized by aberrant proliferation of myeloid blasts in the bone marrow and impaired normal hematopoiesis. Despite the introduction of new drugs and allogeneic bone marrow transplantation, patients have poor overall survival rate with relapse as the major challenge, driving the demand for new therapeutic strategies. AML patients with high expression of the very long/long chain fatty acid transporter CD36 have poorer survival and very long chain fatty acid metabolism is critical for AML cell survival...

Active learning (AL) is an iterative feedback process that efficiently identifies valuable data within vast chemical space, even with limited labeled data. This characteristic renders it a valuable approach to tackle the ongoing challenges faced in drug discovery, such as the ever-expanding explore space and the limitations of labeled data. Consequently, AL is increasingly gaining prominence in the field of drug development. In this paper, we comprehensively review the application of AL at all stages of drug discovery, including compounds-target interaction prediction, virtual screening, molecular generation and optimization, as well as molecular properties prediction...