The stability and dynamics of computationally designed proteins

Screening of phytoconstituents from Bacopa monnieri (L.) Pennell and Mucuna pruriens (L.) DC. to identify potential inhibitors against Cerebroside sulfotransferase

Cerebroside sulfotransferase (CST) is considered a target protein in developing substrate reduction therapy for metachromatic leukodystrophy. This study employed a multistep virtual screening approach for getting a specific and potent inhibitor against CST from 35 phytoconstituents of Bacopa monnieri (L.) Pennell and 31 phytoconstituents of Mucuna pruriens (L.) DC. from the IMPPAT 2.0 database. Using a binding score cutoff of -8.0 kcal/mol with ADME and toxicity screening, four phytoconstituents IMPHY009537 (Stigmastenol), IMPHY004141 (alpha-Amyrenyl acetate), IMPHY014836 (beta-Sitosterol), and IMPHY001534 (jujubogenin) were considered for in-depth analysis. In the binding pocket of CST, the major amino acid residues that decide the orientation and interaction of compounds are Lys85, His84, His141, Phe170, Tyr176, and Phe177. The molecular dynamics simulation with a 100ns time span further validated the stability and rigidity of the docked complexes of the four hits by exploring the structural deviation and compactness, hydrogen bond interaction, solvent accessible surface area, principal component analysis, and free energy landscape analysis. Stigmastenol from Bacopa monnieri with no potential cross targets was found to be the most potent and selective CST inhibitor followed by alpha-Amyrenyl acetate from Mucuna pruriens as the second-best performing inhibitor against CST. Our computational drug screening approach may contribute to the development of oral drugs against metachromatic leukodystrophy.

Phytoconstituents of Withania somnifera (L.) Dunal (Ashwagandha) unveiled potential cerebroside sulfotransferase inhibitors: insight through virtual screening, molecular dynamics, toxicity, and reverse pharmacophore analysis

Cerebroside sulfotransferase (CST) is considered as therapeutic target for substrate reduction therapy (SRT) for metachromatic leukodystrophy (MLD). The present study evaluates the therapeutic potential of 57 phytoconstituents of Withania somnifera against CST. Using binding score cutoff ≤-7.0 kcal/mol, top 10 compounds were screened and after ADME and toxicity-based screening, Withasomidienone, 2,4-methylene-cholesterol, and 2,3-Didehydrosomnifericin were identified as safe and potent drug candidates for CST inhibition. Key substrate binding site residues involved in interaction were LYS82, LYS85, SER89, TYR176, PHE170, PHE177. Four steroidal Lactone-based withanolide backbone of these compounds played a critical role in stabilizing their position in the active site pocket. 100 ns molecular dynamics simulation and subsequent trajectory analysis through structural deviation and compactness, principal components, free energy landscape and correlation matrix confirmed the stability of CST-2,3-Didehydrosomnifericin complex throughout the simulation and therefore is considered as the most potent drug candidate for CST inhibition and Withasomidienone as the second most potent drug candidate. The reverse pharmacophore analysis further confirmed the specificity of these two compounds towards CST as no major cross targets were identified. Thus, identified compounds in this study strongly present their candidature for oral drug and provide route for further development of more specific CST inhibitors.

Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence

The field of computational protein engineering has been transformed by recent advancements in machine learning, artificial intelligence, and molecular modeling, enabling the design of proteins with unprecedented precision and functionality. Computational methods now play a crucial role in enhancing the stability, activity, and specificity of proteins for diverse applications in biotechnology and medicine. Techniques such as deep learning, reinforcement learning, and transfer learning have dramatically improved protein structure prediction, optimization of binding affinities, and enzyme design. These innovations have streamlined the process of protein engineering by allowing the rapid generation of targeted libraries, reducing experimental sampling, and enabling the rational design of proteins with tailored properties. Furthermore, the integration of computational approaches with high-throughput experimental techniques has facilitated the development of multifunctional proteins and novel therapeutics. However, challenges remain in bridging the gap between computational predictions and experimental validation and in addressing ethical concerns related to AI-driven protein design. This review provides a comprehensive overview of the current state and future directions of computational methods in protein engineering, emphasizing their transformative potential in creating next-generation biologics and advancing synthetic biology.

NMR Dynamic View of the Stabilization of the WW4 Domain by Neutral NaCl and Kosmotropic Na2SO4 and NaH2PO4

The Hofmeister series categorizes ions based on their effects on protein stability, yet the microscopic mechanism remains a mystery. In this series, NaCl is neutral, Na2SO4 and Na2HPO4 are kosmotropic, while GdmCl and NaSCN are chaotropic. This study employs CD and NMR to investigate the effects of NaCl, Na2SO4, and Na2HPO4 on the conformation, stability, binding, and backbone dynamics (ps-ns and µs-ms time scales) of the WW4 domain with a high stability and accessible side chains at concentrations ≤ 200 mM. The results indicated that none of the three salts altered the conformation of WW4 or showed significant binding to the four aliphatic hydrophobic side chains. NaCl had no effect on its thermal stability, while Na2SO4 and Na2HPO4 enhanced the stability by ~5 °C. Interestingly, NaCl only weakly interacted with the Arg27 amide proton, whereas Na2SO4 bound to Arg27 and Phe31 amide protons with Kd of 32.7 and 41.6 mM, respectively. Na2HPO4, however, bound in a non-saturable manner to Trp9, His24, and Asn36 amide protons. While the three salts had negligible effects on ps-ns backbone dynamics, NaCl and Na2SO4 displayed no effect while Na2HPO4 significantly increased the µs-ms backbone dynamics. These findings, combined with our recent results with GdmCl and NaSCN, suggest a microscopic mechanism for the Hofmeister series. Additionally, the data revealed a lack of simple correlation between thermodynamic stability and backbone dynamics, most likely due to enthalpy-entropy compensation. Our study rationalizes the selection of chloride and phosphate as the primary anions in extracellular and intracellular spaces, as well as polyphosphate as a primitive chaperone in certain single-cell organisms.

NMR Dynamic View of the Destabilization of WW4 Domain by Chaotropic GdmCl and NaSCN

GdmCl and NaSCN are two strong chaotropic salts commonly used in protein folding and stability studies, but their microscopic mechanisms remain enigmatic. Here, by CD and NMR, we investigated their effects on conformations, stability, binding and backbone dynamics on ps-ns and µs-ms time scales of a 39-residue but well-folded WW4 domain at salt concentrations ≤200 mM. Up to 200 mM, both denaturants did not alter the tertiary packing of WW4, but GdmCl exerted more severe destabilization than NaSCN. Intriguingly, GdmCl had only weak binding to amide protons, while NaSCN showed extensive binding to both hydrophobic side chains and amide protons. Neither denaturant significantly affected the overall ps-ns backbone dynamics, but they distinctively altered µs-ms backbone dynamics. This study unveils that GdmCl and NaSCN destabilize a protein before the global unfolding occurs with differential binding properties and µs-ms backbone dynamics, implying the absence of a simple correlation between thermodynamic stability and backbone dynamics of WW4 at both ps-ns and µs-ms time scales.

Modulation of Krüppel-like factors (KLFs) interaction with their binding partners in cancers through acetylation and phosphorylation

Post-translational modifications (PTMs) of transcription factors regulate transcriptional activity and play a key role in essentially all biological processes and generate indispensable insight towards biological function including activity state, subcellular localization, protein solubility, protein folding, substrate trafficking, and protein-protein interactions. Amino acids modified chemically via PTMs, function as molecular switches and affect the protein function and characterization and increase the proteome complexity. Krüppel-like transcription factors (KLFs) control essential cellular processes including proliferation, differentiation, migration, programmed cell death and various cancer-relevant processes. We investigated the interactions of KLF group-2 members with their binding partners to assess the role of acetylation and phosphorylation in KLFs on their binding affinity. It was observed that acetylation and phosphorylation at different positions in KLFs have a variable effect on binding with specific partners. KLF2-EP300, KLF4-SP1, KLF6-ATF3, KLF6-JUN, and KLF7-JUN show stabilization upon acetylation or phosphorylation at variable positions. On the other hand, KLF4-CBP, KLF4-EP300, KLF5-CBP, KLF5-WWP1, KLF6-SP1, and KLF7-ATF3 show stabilization or destabilization due to acetylation or phosphorylation at variable positions in KLFs. This provides a molecular explanation of the experimentally observed dual role of KLF group-2 members as a suppressor or activator of cancers in a PTM-dependent manner.

Computer-aided design to enhance the stability of aldo-keto reductase KdAKR

The aldo-keto reductase (AKR) KdAKR from Kluyvermyces dobzhanskii can reduce t-butyl 6-chloro-(5S)-hydroxy-3-oxohexanoate ((5S)-CHOH) to t-butyl 6-chloro-(3R,5S)-dihydroxyhexanoate ((3R,5S)-CDHH), which is the key chiral intermediate of rosuvastatin. Herein, a computer-aided design that combined the use of PROSS platform and consensus design was employed to improve the stability of a previously constructed mutant KdAKRM6 . Experimental verification revealed that S196C, T232A, V264I and V45L produced improved thermostability and activity. The "best" mutant KdAKRM10 (KdAKRM6 -S196C/T232A/V264I/V45L) was constructed by combining the four beneficial mutations, which displayed enhanced thermostability. Its T50 15 and Tm values were increased by 10.2 and 10.0°C, respectively, and half-life (t1/2 ) at 40°C was increased by 17.6 h. Additionally, KdAKRM10 demonstrated improved resistance to organic solvents compared to that of KdAKRM6 . Structural analysis revealed that the increased number of hydrogen bonds and stabilized hydrophobic core contributed to the rigidity of KdAKRM10 , thus improving its stability. The results validated the feasibility of the computer-aided design strategy in improving the stability of AKRs.

The Potential Mechanism of Liujunzi Decoction in the Treatment of Breast Cancer based on Network Pharmacology and Molecular Docking Technology

BACKGROUND

Liujunzi Decoction (LJZD) is a potential clinical treatment for Breast Cancer (BC), but the active ingredients and mechanisms underlying its effectiveness remain unclear.

OBJECTIVE

The study aimed to investigate the target gene of LJZD compatibility and the possible mechanism of action in the treatment of breast cancer by using network pharmacology and molecular docking.

METHODS

Based on TCMSP, ETCM, and BATMAN database searching and screening to obtain the ingredients of LJZD, the related targets were obtained. Breast cancer-related targets were collected through GEO, Geencards, OMIM, and other databases, and drug-disease Venn diagrams were drawn by R. The PPI network map was constructed by using Cytoscape. The intersecting targets were imported into the STRING database, and the core targets were analyzed and screened. The intersected targets were analyzed by the DAVID database for GO and KEGG enrichment. AutoDock Vina and Gromacs were used for molecular docking and simulation of the core targets and active ingredients.

RESULTS

126 active ingredients of LJZD were obtained; 241 targets related to breast cancer were sought after screening, and 180 intersection targets were identified through Venn diagram analysis. The core targets were FOS and ESR1. KEGG enrichment analysis mainly involved PI3K/Akt, MAPK, and other signaling pathways.

CONCLUSION

This study has explored the possible targets and signaling pathways of LJZD in treating breast cancer through network pharmacology and bioinformatics analysis. Molecular docking and simulation have further validated the potential mechanism of action of LJZD in breast cancer treatment, providing essential experimental data for future studies.

Characterizing the combined effects of cytochrome P450 missense variation within star allele definitions

Background: Cytochrome P450 (CYP) genetic variation largely impacts drug response. However, many CYP star alleles (haplotypes) lack functional annotation, impeding our understanding of drug metabolism mechanisms. We aimed to investigate the impact of missense variant combinations on CYP protein structures. Methods: Normal mode analysis was conducted on 261 missense variants within 91 CYP haplotypes. CYP2D6*2 and CYP2D6*17 were prioritized for molecular dynamics simulation. Results: Normal mode analysis and molecular dynamics highlight the effects of known CYP missense variants on protein stability and conformational dynamics. Missense variants within haplotypes may have intermodulating effects on protein structure and function. Conclusion: This study highlights the utility of multiscale modeling in interpreting CYP missense variants and particularly their combinations within various star alleles.

Simultaneous enhancement of thermostability and catalytic activity of κ-carrageenase from Pseudoalteromonas tetraodonis by rational design

κ-Carrageenase provides an attractive enzymatic approach to preparation of κ-carrageenan oligosaccharides. Pseudoalteromonas tetraodonis κ-carrageenase is active at the alkaline conditions but displays low thermostability. To further improve its enzymatic performance, two mutants of Q42V and I51H exhibiting both improved thermostability and enzyme activity were screened by the PoPMuSiC algorithm. Compared with the wild-type κ-carrageenase (WT), Q42V and I51H increased the enzyme activity by 20.9% and 25.4%, respectively. After treatment at 50 ℃ for 40 min, Q42V and I51H enhanced the residual activity by 31.1% and 25.9%, respectively. The T_m values of Q42V, I51H, and WT determined by differential scanning calorimetry were 58.2 ℃, 54.8 ℃, and 51.2 ℃, respectively. Compared with untreated and HCl-treated κ-carrageenans, Q42V-treated κ-carrageenan exhibited higher pancreatic lipase inhibitory activity. Molecular docking analysis indicated that the additional pi-sigma force and hydrophobic interaction in the enzyme-substrate complex could account for the increased catalytic activity of Q42V and I51H, respectively. Molecular dynamics analysis indicated that the improved thermostability of mutants Q42V and I51H could be attributed to the less structural deviation and the flexible changes of enzyme conformation at high temperature. This study provides new insight into κ-carrageenase performance improvement and identifies good candidates for their industrial applications.

Using High-Throughput Molecular Dynamics Simulation to Enhance the Computational Design of Kemp Elimination Enzymes

Computational enzyme design has been successfully applied to identify new alternatives to natural enzymes for the biosynthesis of important compounds. However, the moderate catalytic activities of de novo designed enzymes indicate that the modeling accuracy of current computational enzyme design methods should be improved. Here, high-throughput molecular dynamics simulations were used to enhance computational enzyme design, thus allowing the identification of variants with higher activities in silico. Different time schemes of high-throughput molecular dynamics simulations were tested to identify the catalytic features of evolved Kemp eliminases. The 20 × 1 ns molecular dynamics simulation scheme was sufficiently accurate and computationally viable to screen the computationally designed massive variants of Kemp elimination enzymes. The developed hybrid computational strategy was used to redesign the most active Kemp eliminase, HG3.17, and five variants were generated and experimentally confirmed to afford higher catalytic efficiencies than that of HG3.17, with one double variant (D52Q/A53S) exhibiting a 55% increase. The hybrid computational enzyme design strategy is general and computationally economical, with which we anticipate the efficient creation of practical enzymes for industrial biocatalysis.

Enhanced Thermostability and Molecular Insights for l-Asparaginase from Bacillus licheniformis via Structure- and Computation-Based Rational Design

l-Asparaginase has gained much attention for effectively treating acute lymphoblastic leukemia (ALL) and mitigating carcinogenic acrylamide in fried foods. Due to high-dose dependence for clinical treatment and low mitigation efficiency for thermal food processes caused by poor thermal stability, a method to achieve thermostable l-asparaginase has become a critical bottleneck. In this study, a rational design including free energy combined with structural and conservative analyses was applied to engineer the thermostability of l-asparaginase from Bacillus licheniformis (BlAsnase). Two enhanced thermostability mutants D172W and E207A were screened out by site-directed saturation mutagenesis. The double mutant D172W/E207A exhibited highly remarkable thermostability with a 65.8-fold longer half-life at 55 °C and 5 °C higher optimum reaction temperature and melting temperature (T_m) than those of wild-type BlAsnase. Further, secondary structure, sequence, molecular dynamics (MD), and 3D-structure analysis revealed that the excellent thermostability of the mutant D172W/E207A was on account of increased hydrophobicity and decreased flexibility, highly rigid structure, hydrophobic interactions, and favorable electrostatic potential. As the first report of rationally designing l-asparaginase with improved thermostability from B. licheniformis, this study offers a facile and efficient process to improve the thermostability of l-asparaginase for industrial applications.

Engineering and Design of Programmable Genome Editors

Programmable genome editors are enzymes that can be targeted to a specific location in the genome for making site-specific alterations or deletions. The engineering, design, and development of sequence-specific editors has resulted in a dramatic increase in the precision of editing for nucleotide sequences. These editors can target specific locations in a genome, in vivo. The genome editors are being deployed for the development of genetically modified organisms for agriculture and industry, and for gene therapy of inherited human genetic disorders, cancer, and immunotherapy. Experimental and computational studies of structure, binding, activity, dynamics, and folding, reviewed here, have provided valuable insights that have the potential for increasing the functional efficiency of these gene/genome editors. Biochemical and biophysical studies of the specificities of natural and engineered genome editors reveal that increased binding affinity can be detrimental because of the increase of off-target effects and that the engineering and design of genome editors with higher specificity may require modulation and control of the conformational dynamics.

Thermostability engineering of an inulin fructotransferase for the biosynthesis of difructose anhydride I

The thermostability of enzymes is an essential factor that performs a vital role during practical applications. Inulin fructotransferases can efficiently convert inulin into bio-functional difructose anhydrides (DFAs). The present study aimed to improve the thermostability of a previously reported inulin fructotransferase, SpIFTase, and apply it to the biosynthesis of DFA I. In silico rational design was used to predict mutation sites, based on sequential and structural information. Two triple-site mutants, Q69L/Q234L/K310G and E201I/Q234L/K310G, were characterized and exhibited enhanced thermostability with approximately 5 °C higher in melting temperature (T_m), respectively, and a 45-fold longer half-life (t_1/2) at 70 °C, compared to that of SpIFTase. Molecular dynamic simulations and elaborate structural analysis suggested that the combinations of hydrophobic interaction, electrostatic potential distribution, and decreased flexibility via stabilization of loops and α-helix improved the thermostability of SpIFTase. Additionally, the promising mutants exhibited great potential to the industrial production of DFA I.

Integrating dynamics into enzyme engineering

Enzyme engineering has become a widely adopted practice in research labs and industry. In parallel, the past decades have seen tremendous strides in characterizing the dynamics of proteins, using a growing array of methodologies. Importantly, links have been established between the dynamics of proteins and their function. Characterizing the dynamics of an enzyme prior to, and following, its engineering is beginning to inform on the potential of 'dynamic engineering', i.e. the rational modification of protein dynamics to alter enzyme function. Here we examine the state of knowledge at the intersection of enzyme engineering and protein dynamics, describe current challenges and highlight pioneering work in the nascent area of dynamic engineering.