Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

ACS Omega, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 8, 2024

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey field computational enzymology, highlighting key principles governing and discussing ongoing challenges promising advances. Over years, computer simulations have become indispensable in study mechanisms, with integration experimental exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies demonstrated power characterizing reaction pathways, transition states, substrate selectivity, product distribution, dynamic conformational changes various enzymes. Nevertheless, significant remain investigating multistep reactions, large-scale changes, allosteric regulation. Beyond mechanistic studies, modeling has emerged an tool computer-aided design rational discovery covalent drugs targeted therapies. Overall, design/engineering drug development can greatly benefit from our understanding detailed enzymes, such protein dynamics, entropy contributions, allostery, revealed by studies. Such convergence different research approaches expected continue, creating synergies research. This outlining ever-expanding research, aims provide guidance future directions facilitate new developments important evolving field.

Language: Английский

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Assessments of protodioscin’s antinociceptive and antidiarrheal properties: in vivo and in silico investigations on macromolecule binding affinity and modulatory effects

Naunyn-Schmiedeberg s Archives of Pharmacology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 8, 2025

Language: Английский

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Assessment of Antidiarrheal Effect of Oleuropein Through µ‐Oopioid Receptor Interaction Pathway: In Vivo and in Silico Studies

Drug Development Research, Journal Year: 2025, Volume and Issue: 86(1)

Published: Feb. 1, 2025

Oleuropein (OLP), a compound predominantly found in olive leaves, has been known for its numerous biological activities, including antioxidant, anti-inflammatory, and antimicrobial properties. Despite established therapeutic potential, role treating diarrhea not extensively explored. This study aimed to evaluate the antidiarrheal effects of OLP an vivo model investigate molecular interactions using silico docking studies, pharmacokinetic predictions, toxicity analysis. In study, castor oil was used induce 3-day-old chicks, effect tested at doses 10 20 mg/kg. The standard drug, loperamide (LOP) 3 mg/kg, comparison. results showed that both significantly (p < 0.05) reduced diarrheal secretions increased latency, with mg/kg dose demonstrating most effective results. combination (20 mg/kg) LOP (3 further enhanced effect. revealed exhibited strong binding affinities (BAs) key receptor, μ-opioid receptor associated diarrhea, while higher BA (‒8.9 kcal/mol) compared (‒8.7 kcal/mol). Pharmacokinetic analysis favorable properties studies no acute toxicity, LD50 2000 conclusion, findings suggest possesses significant potential through interaction, positioning it as promising natural agent managing diarrhea. Further are warranted fully elucidate mechanisms action clinical applicability.

Language: Английский

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Catalytic Mechanism and Heterologous Biosynthesis Application of Sesquiterpene Synthases

Journal of Agricultural and Food Chemistry, Journal Year: 2024, Volume and Issue: 72(13), P. 6871 - 6888

Published: March 25, 2024

Sesquiterpenes comprise a diverse group of natural products with wide range applications in cosmetics, food, medicine, agriculture, and biofuels. Heterologous biosynthesis is increasingly employed for sesquiterpene production, aiming to overcome the limitations associated chemical synthesis extraction. Sesquiterpene synthases (STSs) play crucial role heterologous sesquiterpene. Under catalysis STSs, over 300 skeletons are produced through various cyclization processes (C1-C10 closure, C1-C11 C1-C6 C1-C7 closure), which responsible diversity sesquiterpenes. According types, we gave an overview advances understanding mechanism STSs from aspects protein crystal structures site-directed mutagenesis. We also summarized engineering Finally, bottlenecks potential research directions related application modified were presented.

Language: Английский

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Machine Learning Guided AQFEP: A Fast and Efficient Absolute Free Energy Perturbation Solution for Virtual Screening

Journal of Chemical Theory and Computation, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 15, 2024

Structure-based methods in drug discovery have become an integral part of the modern process. The power virtual screening lies its ability to rapidly and cost-effectively explore enormous chemical spaces select promising ligands for further experimental investigation. Relative free energy perturbation (RFEP) similar are gold standard binding affinity prediction hit-to-lead lead optimization phases, but high computational cost requirement a structural analog with known activity. Without reference molecule requirement, absolute FEP (AFEP) has, theory, better accuracy hit ID, practice, slow throughput is not compatible VS, where fast docking unreliable scoring functions still standard. Here, we present integrated workflow virtually screen large diverse libraries efficiently, combining active learning physics-based function based on method. We validated performance approach ranking structurally related ligands, rate enrichment, space exploration; disclosing largest reported collection simulations date.

Language: Английский

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Apprehensions and emerging solutions in ML-based protein structure prediction

Current Opinion in Structural Biology, Journal Year: 2024, Volume and Issue: 86, P. 102819 - 102819

Published: April 16, 2024

The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the is known, molecular mechanism protein can be understood more detail and obtained information utilized biotechnological, diagnostics, therapeutic applications. Over past five years, machine learning (ML)-based modeling has pushed prediction to next level with AlphaFold front line, predicting for hundreds millions proteins. Further advances recently report promising ML-based approaches solving remaining challenges by incorporating functionally important metals, co-factors, post-translational modifications, structural dynamics, interdomain multimer interactions process.

Language: Английский

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Structural Tailoring of Etoricoxib: A spectrochemical, medicinal and pharmacological study

Chemical Physics Impact, Journal Year: 2025, Volume and Issue: unknown, P. 100830 - 100830

Published: Jan. 1, 2025

Language: Английский

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Identification and validation of palmitoylation-related biomarkers in gestational diabetes mellitus

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 7, 2025

Palmitoylation plays a crucial role in the pathophysiology of diabetes, and an increase palmitoylation may inhibit function insulin receptors, thereby affecting progression gestational diabetes mellitus (GDM). However, its involvement (GDM) remains underexplored. This study analyzed GDM-related datasets 30 palmitoylation-related genes (PRGs), identifying MNDA, FCGR3B, AQP9 as significantly upregulated biomarkers GDM samples. Consistent with dataset analysis, reverse transcription-polymerase chain reaction (RT-qPCR) confirmed elevated expression. Comprehensive analyses, including nomogram construction, enrichment immune infiltration assessment, molecular regulatory network generation, drug prediction, docking, were conducted. The biomarker-based demonstrated excellent predictive performance for risk. enriched pathways such "Myc-targets-v1" "TNFA signaling via NFkB." Additionally, eosinophil showed strong positive correlation these biomarkers. Regulatory networks involving SH3BP5-AS1-hsa-miR-182-5p-AQP9 hsa-miR-182-5p-AQP9-ELF5 identified, stable binding energies observed between corresponding drugs. These findings provide promising avenues early screening diagnosis.

Language: Английский

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Rational Proteolysis Targeting Chimera Design Driven by Molecular Modeling and Machine Learning

Wiley Interdisciplinary Reviews Computational Molecular Science, Journal Year: 2025, Volume and Issue: 15(2)

Published: March 1, 2025

ABSTRACT Proteolysis targeting chimera (PROTAC) induces specific protein degradation through the ubiquitin–proteasome system and offers significant advantages over small molecule drugs. They are emerging as a promising avenue, particularly in previously “undruggable” targets. Traditional PROTACs have been discovered large‐scale experimental screening. Extensive research efforts focused on unraveling biological pharmacological functions of PROTACs, with strides made toward transitioning from empirical discovery to rational, structure‐based design strategies. This review provides an overview recent representative computer‐aided drug studies PROTACs. We highlight how utilization targeted database, molecular modeling techniques, machine learning algorithms, computational methods contributes facilitating PROTAC discovery. Furthermore, we conclude achievements field explore challenges future directions. aim offer insights references for rational

Language: Английский

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Enhanced Binding Site Identification in Protein–Ligand Complexes with a Combined Blind Docking and Dipolar Electron Paramagnetic Resonance Approach

Journal of the American Chemical Society, Journal Year: 2025, Volume and Issue: unknown

Published: April 11, 2025

Understanding protein-drug complex structures is crucial for elucidating therapeutic mechanisms and side effects. Blind docking facilitates site identification but hindered by computational complexity imprecise scoring, causing ambiguity. Dipolar electron paramagnetic resonance (EPR) provides spin-spin distances struggles to determine relative positions within complexes. We present a novel approach combining GPU-accelerated blind with EPR distance constraints enhance binding detection. Our algorithm uses single distribution filter validate results. Ligand poses from are clustered, filtered expected distances, refined through focused docking. To illustrate our approach, we investigated human serum albumin porphyrin-based photosensitizers used in photodynamic therapy. Combining EPR, identified possible sites, demonstrating that data significantly reduce configurations provide experimentally validated information. This strategy produces detailed map of photoligand revealing may occur away standard sites often involves multiple locations. Furthermore, it overcomes key limitations fluorescence-based methods, which prone misinterpretation studies due non one-to-one donor-acceptor relationships. By resolving ambiguities both framework versatile platform investigating EPR-active ligands.

Language: Английский

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