The equilibrium of cellular protein levels is pivotal for maintaining normal physiological functions. USP5 belongs to the deubiquitination enzyme (DUBs) family, controlling protein degradation and preserving cellular protein homeostasis. Aberrant expression of USP5 is implicated in a variety of diseases, including cancer, neurodegenerative diseases, and inflammatory diseases. In this paper, a multi-level virtual screening (VS) approach was employed to target the zinc finger ubiquitin-binding domain (ZnF-UBD) of USP5, leading to the identification of a highly promising candidate compound 0456-0049. Molecular dynamics (MD) simulations were then employed to assess the stability of complex binding and predict hotspot residues in interactions. The results indicated that the candidate stably binds to the ZnF-UBD of USP5 through crucial interactions with residues ARG221, TRP209, GLY220, ASN207, TYR261, TYR259, and MET266. Binding free energy calculations, along with umbrella sampling (US) simulations, underscored a superior binding affinity of the candidate relative to known inhibitors. Moreover, US simulations revealed conformational changes of USP5 during ligand dissociation. These insights provide a valuable foundation for the development of novel inhibitors targeting USP5.

Molecular dynamics (MD) simulation is a powerful computational tool used in biomolecular studies to investigate the dynamics, energetics, and interactions of a wide range of biological systems at the atomic level. GROMACS is a widely used free and open-source biomolecular MD simulation software recognized for its efficiency, accuracy, and extensive range of simulation options. However, the complexity of setting up, running, and analyzing MD simulations for diverse systems often poses a significant challenge, requiring considerable time, effort, and expertise. Here, we introduce CHAPERONg, a tool that automates the GROMACS MD simulation pipelines for protein and protein-ligand systems. CHAPERONg also integrates seamlessly with GROMACS modules and third-party tools to provide comprehensive analyses of MD simulation trajectories, offering up to 20 post-simulation processing and trajectory analyses. It also streamlines and automates established pipelines for conducting and analyzing biased MD simulations via the steered MD-umbrella sampling workflow. Thus, CHAPERONg makes MD simulations more accessible to beginner GROMACS users whilst empowering experts to focus on data interpretation and other less programmable aspects of MD simulation workflows. CHAPERONg is written in Bash and Python, and the source code is freely available at https://github.com/abeebyekeen/CHAPERONg. Detailed documentation and tutorials are available online at dedicated web pages accessible via https://abeebyekeen.com/chaperong-online.

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. In this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

Zearalenone (ZEN) is one of the most prevalent estrogenic mycotoxins, is produced mainly by the Fusarium family of fungi, and poses a risk to the health of animals. Zearalenone hydrolase (ZHD) is an important enzyme capable of degrading ZEN into a non-toxic compound. Although previous research has investigated the catalytic mechanism of ZHD, information on its dynamic interaction with ZEN remains unknown. This study aimed to develop a pipeline for identifying the allosteric pathway of ZHD. Using an identity analysis, we identified hub genes whose sequences can generalize a set of sequences in a protein family. We then utilized a neural relational inference (NRI) model to identify the allosteric pathway of the protein throughout the entire molecular dynamics simulation. The production run lasted 1 microsecond, and we analyzed residues 139-222 for the allosteric pathway using the NRI model. We found that the cap domain of the protein opened up during catalysis, resembling a hemostatic tape. We used umbrella sampling to simulate the dynamic docking phase of the ligand-protein complex and found that the protein took on a square sandwich shape. Our energy analysis, using both molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area (MMPBSA) and Potential Mean Force (PMF) analysis, showed discrepancies, with scores of -8.45 kcal/mol and -1.95 kcal/mol, respectively. MMPBSA, however, obtained a similar score to that of a previous report.

FGFR3 kinase mutations are associated with a variety of malignancies, but FGFR3 mutant inhibitors have rarely been studied. Furthermore, the mechanism of pan-FGFR inhibitors resistance caused by kinase domain mutations is still unclear. In this study, we try to explain the mechanism of drug resistance to FGFR3 mutation through global analysis and local analysis based on molecular dynamics simulation, binding free energy analysis, umbrella sampling and community network analysis. The results showed that FGFR3 mutations caused a decrease in the affinity between drugs and FGFR3 kinase, which was consistent with the reported experimental results. Possible mechanisms are that mutations affect drug-protein affinity by altering the environment of residues near the hinge region where the protein binds to the drug, or by affecting the A-loop and interfering with the allosteric communication networks. In conclusion, we systematically elucidated the underlying mechanism of pan-FGFR inhibitor resistance caused by FGFR3 mutation based on molecular dynamics simulation strategy, which provided theoretical guidance for the development of FGFR3 mutant kinase inhibitors.

Acetylcholinesterase (AChE) is a key target for the current symptomatic treatment of Alzheimer\'s disease, and galantamine is a clinical anticholinesterase drug with transiently acting characteristic and good selectivity for AChE. The present theoretical-experimental work improves the drug\'s residence time without reducing the inhibition effect, thus providing a crucial breakthrough for modifying the inhibitor of AChE with better kinetic behavior. The static binding and dynamic delivery properties acquired from atomic view reveal that the galantamine simply occupies a catalytic anionic site, and its release from AChE needs only ∼8.6 kcal/mol. Both of these may cause the short residence time of galantamine. The hotspots and most favorable transport mechanism are identified, and the hydrogen bond and aromatic stacking interactions are observed to play crucial roles for galantamine binding and release in AChE. The typical peripheral anionic site arisen at the delivery process would provide another key occupation to enhance the anti-release ability for inhibitors. The compound with \"specific-ring-chain-ring\" framework with detailed beneficial modification scheme is summarized, which may improve the residence time of the inhibitor in AChE. The thermodynamic and dynamic properties of galantamine derivatives are also studied. Based on dictamnine, a natural alkaloid, two novel eligible derivatives are designed, synthesized and evaluated, which verifies our prediction. Multiple computational approaches and experimental combinations probably provide a train of thought from both static and dynamic views to modify or design appropriate inhibitors on the basis of specific binding and transportation features.

Understanding drug selectivity mechanism is a long-standing issue for helping design drugs with high specificity. Designing drugs targeting cyclin-dependent kinases (CDKs) with high selectivity is challenging because of their highly conserved binding pockets. To reveal the underlying general selectivity mechanism, we carried out comprehensive analyses from both the thermodynamics and kinetics points of view on a representative CDK12 inhibitor. To fully capture the binding features of the drug-target recognition process, we proposed to use kinetic residue energy analysis (KREA) in conjunction with the community network analysis (CNA) to reveal the underlying cooperation effect between individual residues/protein motifs to the binding/dissociating process of the ligand. The general mechanism of drug selectivity in CDKs can be summarized as that the difference of structural cooperation between the ligand and the protein motifs leads to the difference of the energetic contribution of the key residues to the ligand. The proposed mechanisms may be prevalent in drug selectivity issues, and the insights may help design new strategies to overcome/attenuate the drug selectivity associated problems.

Cellulose/collagen composites have been widely used in biomedicine and tissue engineering. Interfacial interactions are crucial in determining the final properties of cellulose/collagen composite. Molecular dynamics simulations were carried out to gain insights into the interactions between cellulose and collagen. It has been found that the structure of collagen remained intact during adsorption. The results derived from umbrella sampling showed that (110) and ([Formula: see text]) faces exhibited the strongest affinity with collagen (100) face came the second and (010) the last, which could be attributed to the surface roughness and hydrogen-bonding linkers involved water molecules. Cellulose planes with flat surfaces and the capability to form hydrogen-bonding linkers produce stronger affinity with collagen. The occupancy of hydrogen bonds formed between cellulose and collagen was low and not significantly contributive to the binding affinity. These findings provided insights into the interactions between cellulose and collagen at the molecular level, which may guide the design and fabrication of cellulose/collagen composites.

As a key regulator for hormone activity, human aldo-keto reductase family 1 member C3 (AKR1C3) plays crucial roles in the occurrence of various hormone-dependent or independent malignancies. It is a promising target for treating castration-resistant prostate cancer (CRPC). However, the development of AKR1C3 specific inhibitors remains challenging due to the high sequence similarity to its isoform AKR1C2. Here, we performed a combined in silico study to illuminate the inhibitory preference of 3-(3,4-dihydroisoquinolin-2(1H)-ylsulfonyl)benzoic acids for AKR1C3 over AKR1C2, of which compound 38 can achieve up to 5000-fold anti-AKR1C3 selectivity. Our umbrella sampling (US) simulations together with end-point binding free energy calculation MM/GBSA uncover that the high inhibition selectivity originates from the different binding modes, namely \"Inward\" and \"Outward,\" of this compound series in AKR1C3 and AKR1C2, respectively. In AKR1C3/38, the tetrahydroquinoline moiety of 38 is accommodated inside the SP1 pocket and interacts favorably with surrounding residues, while, in AKR1C2/38, the SP1 pocket is too small to hold the bulky tetrahydroquinoline group that instead moves out of the pocket with 38 transitioning from an \"Inward\" to an \"Outward\" state. Further 3D-QSAR and energy decomposition analyses suggest that SP1 in AKR1C3 prefers to bind with a rigid bicyclic moiety and the modification of the R3 group has important implication for the compound\'s activity. This work is the first attempt to elucidate the selectivity mechanism of inhibitors toward AKR1C3 at the atomic level, which is anticipated to propel the development of next-generation AKR1C3 inhibitors with enhanced efficacy and reduced \"off-target\" effect for CRPC therapy.

Phthalic acid esters (PAEs) are typical environmental endocrine disrupters, interfering with the endocrine system of organisms at very low concentrations. The plasma membrane is the first barrier for organic pollutants to enter the organism, so membrane permeability is a key factor affecting their biological toxicity. In this study, based on computational approaches, we investigated the permeation and intramembrane aggregation of typical PAEs (dimethyl phthalate, DMP; dibutyl phthalate, DBP; di-2-ethyl hexyl phthalate, DEHP), as well as their effects on membrane properties, and related molecular mechanisms were uncovered. Our results suggested that PAEs could enter the membrane spontaneously, preferring the headgroup-acyl chain interface of the bilayer, and the longer the side chain (DEHP > DBP > DMP), the deeper the insertion. Compared with the shortest DMP, DEHP apparently increased membrane thickness, order, and rigidity, which might be due to its stronger hydrophobicity. Potential of means force (PMF) analysis revealed the presence of an energy barrier located at the water-membrane interface, with a maximum value of 2.14 kcal mol−1 obtained in the DEHP-system. Therefore, the difficulty of membrane insertion is also positively correlated with the side-chain length or hydrophobicity of PAE molecules. These findings will inspire our understanding of structure-activity relationship between PAEs and their effects on membrane properties, and provide a scientific basis for the formulation of environmental pollution standards and the prevention and control of small molecule pollutants.