CADD

Chronic nonbacterial osteomyelitis (CNO), an autoinflammatory bone disease primarily affecting children, can cause pain, hyperostosis and fractures, affecting quality-of-life and psychomotor development. This study investigated CNO-associated variants in P2RX7, encoding for the ATP-dependent trans-membrane K+ channel P2X7, and their effects on NLRP3 inflammasome assembly. Whole exome sequencing in two related transgenerational CNO patients, and target sequencing of P2RX7 in a large CNO cohort (N = 190) were conducted...

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its companion disease, COVID-19, has reminded us of the importance of basic coronaviral research. In this study, a comprehensive approach using molecular docking, in vitro assays, and molecular dynamics simulations was applied to identify potential inhibitors for SARS-CoV-2 papain-like protease (PLpro ), a key and underexplored viral enzyme target. A focused protease inhibitor library was initially created and molecular docking was performed using CmDock software (v0...

The +33 C>G variant [NM_000518.5(HBB):c.-18C>G] in the 5' untranslated region (UTR) of the β-globin gene is described in the literature as both mild and silent, while it causes a phenotype of thalassemia intermedia in the presence of a severe β-thalassemia allele. Despite its potential clinical significance, the determination of its pathogenicity according to established standards requires a greater number of published cases and co-segregation evidence than what is currently available. The present study provides an extensive phenotypic characterization of +33 C>G using 26 heterozygous and 11 compound heterozygous novel cases detected in Cyprus and employs computational predictors (CADD, RegulomeDB) to better understand its impact on clinical severity...

BACKGROUND: De novo mutations (DNMs) are variants that occur anew in the offspring of noncarrier parents. They are not inherited from either parent but rather result from endogenous mutational processes involving errors of DNA repair/replication. These spontaneous errors play a significant role in the causation of genetic disorders, and their importance in the context of molecular diagnostic medicine has become steadily more apparent as more DNMs have been reported in the literature. In this study, we examined 46,489 disease-associated DNMs annotated by the Human Gene Mutation Database (HGMD) to ascertain their distribution across gene and disease categories...

A receptor-based pharmacophore model describing the binding features required for the multi-kinase inhibition of the target kinases (VEGFR-2, FGFR-1, and BRAF) were constructed and validated. It showed a good overall quality in discriminating between the active and the inactive in a compiled test set compounds with F1 score of 0.502 and Mathew's correlation coefficient of 0.513. It described the ligand binding to the hinge region Cys or Ala, the glutamate residue of the Glu-Lys αC helix conserved pair, the DFG motif Asp at the activation loop, and the allosteric back pocket next to the ATP binding site...

Visceral Leishmaniasis (VL) has a high death rate, with 500,000 new cases and 50,000 deaths occurring annually. Despite the development of novel strategies and technologies, there is no adequate treatment for the disease. Therefore, the purpose of this study is to find structural analogs of natural products as potential novel drugs to treat VL. We selected structural analogs from natural products that have shown antileishmanial activities, and that may impede the purine salvage pathway using computer-aided drug-design (CADD) approaches...

Protein hydrolysates from sea cucumber ( Apostichopus japonicus ) gonads are rich in active materials with remarkable angiotensin-converting enzyme (ACE) inhibitory activity. Alcalase was used to hydrolyze sea cucumber gonads, and the hydrolysate was separated by the ultrafiltration membrane to produce a low-molecular-weight peptide component (less than 3 kDa) with good ACE inhibitory activity. The peptide component (less than 3 kDa) was isolated and purified using a combination method of ACE gel affinity chromatography and reverse high-performance liquid chromatography...

Improving the drug development process can expedite the introduction of more novel drugs that cater to the demands of precision medicine. Accurately predicting molecular properties remains a fundamental challenge in drug discovery and development. Currently, a plethora of computer-aided drug discovery (CADD) methods have been widely employed in the field of molecular prediction. However, most of these methods primarily analyze molecules using low-dimensional representations such as SMILES notations, molecular fingerprints, and molecular graph-based descriptors...

Drug discovery and development constitute a laborious and costly undertaking. The success of a drug hinges not only good efficacy but also acceptable absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties. Overall, up to 50% of drug development failures have been contributed from undesirable ADMET profiles. As a multiple parameter objective, the optimization of the ADMET properties is extremely challenging owing to the vast chemical space and limited human expert knowledge. In this study, a freely available platform called Chemical Molecular Optimization, Representation and Translation (ChemMORT) is developed for the optimization of multiple ADMET endpoints without the loss of potency (https://cadd...

INTRODUCTION: Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments...

Predicting the binding affinity of protein-ligand complexes is crucial for computer-aided drug discovery (CADD) and the identification of potential drug candidates. The deep learning-based scoring functions have emerged as promising predictors of binding constants. Building on recent advancements in graph neural networks, we present graphLambda for protein-ligand binding affinity prediction, which utilizes graph convolutional, attention, and isomorphism blocks to enhance the predictive capabilities. The graphLambda model exhibits superior performance across CASF16 and CSAR HiQ NRC benchmarks and demonstrates robustness with respect to different types of train-validation set partitions...

BACKGROUND: Glyoxalase system detoxifies methylglyoxal and other ketoaldehydes to produce innocuous metabolites that allow the cells to function normally. Its inhibition in cancer cells causes these toxic metabolites to accumulate, and the cancer cells enter the apoptotic stage. METHODS: The techniques of Computer-Aided Drug Design (CADD) were used, and the compounds possessing a zinc-binding group from commercial databases were extracted, using the pharmacophore search protocol...

Background Masticatory Myofascial Pain Dysfunction Syndrome (MMPDS) is a musculoligamentous disorder that shares similarities with temporomandibular joint pain and odontogenic pain. It manifests as dull or aching pain in masticatory muscles, influenced by jaw movement. Computer-aided drug design (CADD) encompasses various theoretical and computational approaches used in modern drug discovery. Molecular docking is a prominent method in CADD that facilitates the understanding of drug-bimolecular interactions for rational drug design, mechanistic studies & the formation of stable complexes with increased specificity and potential efficacy...

BACKGROUND: Although national efforts are underway to document the genomic variability of the Saudi population relative to other populations, such variability remains largely unexplored. Genetic variability is known to impact the fate of cells and increase or decrease the risk of a variety of complex diseases including cancer forms. Therefore, the identification of variants associated with cancer susceptibility in Saudi population may protect individuals from cancer or aid in patient-tailored therapies...

We present a new highly interdisciplinary course in computer-aided drug discovery (CADD). This course was developed in response to a call for alternative pedagogical approaches during the COVID-19 pandemic, which caused the cancellation of a face-to-face summer research program sponsored by the Louisiana Louisiana Biomedical Research Network (LBRN). The course integrates guided research and educational experiences for chemistry, biology, and computer science students. We implement research-based methods with publicly available tools in bioinformatics and molecular modeling to identify and prioritize promising anti-viral drug candidates...

BACKGROUND: The Computer-Aided Drug Discovery (CADD) approach was used to develop a few Epidermal Growth Factor Receptor (EGFR) kinase inhibitors. EGFR kinase expression is highly associated with genomic instability, higher proliferation, lower hormone receptor levels, and HER2 over-expression. It is more common in breast cancer. Thus, EGFR Kinase is one of the main targets in discovering new cancer medicine. OBJECTIVE: To computationally validate some amides substituted β-amino enones as EGFR inhibitors and to carry out associated in vitro anticancer agents...

BACKGROUND: Polycystic Ovary Syndrome (PCOS) affects a significant proportion of human females worldwide and is characterized by hormonal, metabolic, and reproductive dysfunctions, including infertility, irregular menstrual cycles, acanthosis nigricans, and hirsutism. Mutations in the estrogen receptor genes ESR1 and ESR2, involved in normal follicular development and ovulation, can contribute to development of the PCOS. The present study focuses on investigating the potential correlation between single nucleotide polymorphisms (SNPs) of ESR1 and ESR2 genes and the incidence of this syndrome...

BACKGROUND: The aim of this study was to analyse the differences in the phenotypes of missing teeth between a pair of brothers with hypohidrotic ectodermal dysplasia (HED) and to investigate the underlying mechanism by comparing the mutated gene loci between the brothers with whole-exome sequencing. METHODS: The clinical data of the patients and their mother were collected, and genomic DNA was extracted from peripheral blood samples. By Whole-exome sequencing filtered for a minor allele frequency (MAF) ≤0...

Lysine-specific demethylase 1 (LSD1/KDM1A) has emerged as a promising therapeutic target for treating various cancers (such as breast cancer, liver cancer, etc.) and other diseases (blood diseases, cardiovascular diseases, etc.), owing to its observed overexpression, thereby presenting significant opportunities in drug development. Since its discovery in 2004, extensive research has been conducted on LSD1 inhibitors, with notable contributions from computational approaches. This review systematically summarizes LSD1 inhibitors investigated through computer-aided drug design (CADD) technologies since 2010, showcasing a diverse range of chemical scaffolds, including phenelzine derivatives, tranylcypromine (abbreviated as TCP or 2-PCPA) derivatives, nitrogen-containing heterocyclic (pyridine, pyrimidine, azole, thieno[3,2-b]pyrrole, indole, quinoline and benzoxazole) derivatives, natural products (including sanguinarine, phenolic compounds and resveratrol derivatives, flavonoids and other natural products) and others (including thiourea compounds, Fenoldopam and Raloxifene, (4-cyanophenyl)glycine derivatives, propargylamine and benzohydrazide derivatives and inhibitors discovered through AI techniques)...

Lead optimization is a crucial step in the drug discovery process, which aims to design potential drug candidates from biologically active hits. During lead optimization, active hits undergo modifications to improve their absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles. Medicinal chemists face key questions regarding which compound(s) should be synthesized next and how to balance multiple ADMET properties. Reliable transformation rules from multiple experimental analyses are critical to improve this decision-making process...