Hydrogen Bonds in Protein-Ligand Complexes

Development of human lactate dehydrogenase a inhibitors: high-throughput screening, molecular dynamics simulation and enzyme activity assay

Lactate dehydrogenase A (LDHA) is highly expressed in many tumor cells and promotes the conversion of pyruvate to lactic acid in the glucose pathway, providing energy and synthetic precursors for rapid proliferation of tumor cells. Therefore, inhibition of LDHA has become a widely concerned tumor treatment strategy. However, the research and development of highly efficient and low toxic LDHA small molecule inhibitors still faces challenges. To discover potential inhibitors against LDHA, virtual screening based on molecular docking techniques was performed from Specs database of more than 260,000 compounds and Chemdiv-smart database of more than 1,000 compounds. Through molecular dynamics (MD) simulation studies, we identified 12 potential LDHA inhibitors, all of which can stably bind to human LDHA protein and form multiple interactions with its active central residues. In order to verify the inhibitory activities of these compounds, we established an enzyme activity assay system and measured their inhibitory effects on recombinant human LDHA. The results showed that Compound 6 could inhibit the catalytic effect of LDHA on pyruvate in a dose-dependent manner with an EC50 value of 14.54 ± 0.83 µM. Further in vitro experiments showed that Compound 6 could significantly inhibit the proliferation of various tumor cell lines such as pancreatic cancer cells and lung cancer cells, reduce intracellular lactic acid content and increase intracellular reactive oxygen species (ROS) level. In summary, through virtual screening and in vitro validation, we found that Compound 6 is a small molecule inhibitor for LDHA, providing a good lead compound for the research and development of LDHA related targeted anti-tumor drugs.

Bioactive plant waste components targeting oral bacterial pathogens as a promising strategy for biofilm eradication

The significance of this study lies in its exploration of bioactive plant extracts as a promising avenue for combating oral bacterial pathogens, offering a novel strategy for biofilm eradication that could potentially revolutionize oral health treatments. Oral bacterial infections are common in diabetic patients; however, due to the development of resistance, treatment options are limited. Considering the excellent antimicrobial properties of phenolic compounds, we investigated them against isolated oral pathogens using in silico and in vitro models. We performed antibiogram studies and minimum inhibitory concentration (MIC), antibiofilm, and antiquorum sensing activities covering phenolic compounds. Bacterial strains were isolated from female diabetic patients and identified by using 16S rRNA sequencing as Pseudomonas aeruginosa, Bacillus chungangensis, Bacillus paramycoides, and Paenibacillus dendritiformis. Antibiogram studies confirmed that all strains were resistant to most tested antibiotics except imipenem and ciprofloxacin. Molecular docking analysis revealed the significant interaction of rutin, quercetin, gallic acid, and catechin with transcription regulator genes 1RO5, 4B2O, and 5OE3. All tested molecules followed drug-likeness rules except rutin. The MIC values of the tested compounds varied from 0.0625 to 0.5 mg/mL against clinical isolates. Significant antibiofilm activity was recorded in the case of catechin (73.5% ± 1.6% inhibition against B. paramycoides), cinnamic acid (80.9% ± 1.1% inhibition against P. aeruginosa), and vanillic acid and quercetin (65.5% ± 1.7% and 87.4% ± 1.4% inhibition, respectively, against B. chungangensis) at 0.25-0.125 mg/mL. None of the phenolic compounds presented antiquorum sensing activity. It was, therefore, concluded that polyphenolic compounds may have the potential to be used against oral bacterial biofilms, and further detailed mechanistic investigations should be performed.

Differing Effects of Nonlinearity around the Proton Acceptor on CH··O and NH··O H-Bond Strength within Proteins

The effects of deviations from nonlinearity around the carbonyl proton acceptor of an amide group are assessed by DFT quantum chemical calculations for both CH··O and NH··O H-bonds. The proton donors are the imidazole functional group of His and the indole of Trp, which are paired respectively with N-methylacetamide and acetamide. The displacement of either CH or NH group toward the carbonyl O sp2 lone pairs stabilizes the system and strengthens the H-bond. But the two donor groups differ in their response to a shift out of the amide plane. While the NH··O H-bond is weakened by this displacement, a substantial strengthening is observed when the CH donor is moved out of this plane, in one direction versus the other. This pattern is explained on the basis of simple Coulombic considerations.

Identification of FDA-approved drugs with triple targeting mode of action for the treatment of monkeypox: a high throughput virtual screening study

According to the Center for Disease Control and Prevention, as of August 23, 94 countries had confirmed 42,954 Monkeypox Virus cases. As specific monkeypox drugs are not yet developed, the treatment depends on repurposed FDA-approved drugs. According to a recent study, the Monkeypox outbreak is caused by a strain with a unique mutation, raising the likelihood that the virus will develop resistance to current drugs by acquiring mutations in the targets of currently used drugs. The probability of multiple mutations in two or more drug targets at a time is always low than mutation in a single drug target. Therefore, we identified 15 triple-targeting FDA-approved drugs that can inhibit three viral targets, including topoisomerase1, p37, and thymidylate kinase, using high throughput virtual screening approach. Further, the molecular dynamics simulation analysis of the top hits such as Naldemedine and Saquinavir with their respective targets reveals the formation of stable conformational changes of the ligand-protein complexes inside the dynamic biological environment. We suggest further research on these triple-targeting molecules to develop an effective therapy for the currently spreading Monkeypox.

Synthesis, Characterization, In Silico DFT, Molecular Docking, and Dynamics Simulation Studies of Phenylhydrazono Phenoxyquinolones for Their Hypoglycemic Efficacy

A series of novel 24 phenylhydrazono phenoxyquinoline derivatives were synthesized with moderate to excellent yield and screened for their efficacy against the α-amylase enzyme through in silico studies. The structures were characterized using spectroscopic techniques such as 1HNMR, 13CNMR, and HREI-MS. Comprehensive computational studies including, drug-likeness and ADMET profiling, quantum chemical calculations, molecular docking, and molecular dynamics (MD) simulation studies, were performed. A density functional theory study of the synthesized compounds indicated a favorable reactivity profile. The synthesized novel analogues were docked against α-amylase (PDB 6OCN) enzymes to investigate the binding interactions. Based on the docking studies, one of the compounds was found to be the hit with the highest negative binding affinity for α-amylase. A MD simulation study indicated stable binding throughout the simulation.

Xanthine oxidase inhibition study of isolated secondary metabolites from Dolichandrone spathacea (Bignoniaceae): In vitro and in silico approach

Xanthine oxidase (XO) has been widely recognized as a pivotal enzyme in developing hyperuricemia, primarily contributing to the excessive production of uric acid during purine metabolism in the liver. One of the standard treatment approaches involves reducing uric acid levels by inhibiting XO activity. In this study, the leaf extract of Dolichandrone spathacea, traditionally used in folk medicine, was found to inhibit XO activity in the ethyl acetate and butanol fractions at a concentration of 100 µg/mL, their values were 78.57 ± 3.85 % (IC50 = 55.93 ± 5.73 µg/ml) and 69.43 ± 8.68 % (IC50 = 70.17 ± 7.98 µg/ml), respectively. The potential XO inhibitory components were isolated by bioactivity assays and the HR-ESI-MS and NMR spectra system. The main constituents of leaf extracts of Dolichandrone spathacea, six compounds, namely trans-4-methoxycinnamic acid (3), trans-3,4-dimethoxycinnamic acid (4), p-coumaric acid (5), martynoside (6), 6-O-(p-methoxy-E-cinnamoyl)-ajugol (7), and scolymoside (17), were identified as potent XO inhibitors with IC50 values ranging from 19.34 ± 1.63 μM to 64.50 ± 0.94 μM. The enzyme kinetics indicated that compounds 3-5, 7, and 17 displayed competitive inhibition like allopurinol, while compound 6 displayed a mixed-type inhibition. Computational studies corroborated these experimental results, highlighting the interactions between potential metabolites and XO enzyme. The hydrogen bonds played crucial roles in the binding interaction, especially, scolymoside (17) forms a hydrogen bond with Mos3004, exhibited the lowest binding energy (-18.3286 kcal/mol) corresponding to the lowest IC50 (19.34 ± 1.63 μM). Furthermore, nine compounds were isolated for the first time from this plant. In conclusion, Dolichandrone spathacea and its constituents possess the potential to modulate the xanthine oxidase enzyme involved in metabolism.

Proposing lead compounds for the development of SARS-CoV-2 receptor-binding inhibitors

The COVID-19 pandemic has had deleterious effects on the world and demands urgent measures to find therapeutic agents to combat the current and related future outbreaks. The entry of SARS-CoV-2 into the host's cell is facilitated by the interaction between the viral spike receptor-binding domain (sRBD) and the human angiotensin-converting enzyme 2 (hACE2). Although the interface of sRBD involved in the sRBD-hACE2 interaction has been projected as a primary vaccine and drug target, currently no small-molecule drugs have been approved for covid-19 treatment targeting sRBD. Herein structure-based virtual screening and molecular dynamics (MD) simulation strategies were applied to identify novel potential small-molecule binders of the SARS-CoV-2 sRBD from an sRBD-targeted compound library as leads for the development of anti-COVID-19 drugs. The library was initially screened against sRBD by using the GOLD docking program whereby 19 compounds were shortlisted based on docking scores after using a control compound to set the selection cutoff. The stability of each compound in MD simulations was used as a further standard to select four hits namely T4S1820, T4589, E634-1449, and K784-7078. Analyses of simulations data showed that the four compounds remained stably bound to sRBD for ≥ 80 ns with reasonable affinities and interacted with pharmacologically important amino acid residues. The compounds exhibited fair solubility, lipophilicity, and toxicity-propensity characteristics that could be improved through lead optimization regimes. The overall results suggest that the scaffolds of T4S1820, E634-1449, and K784-7078 could serve as seeds for developing potent small-molecule inhibitors of SARS-CoV-2 receptor binding and cell entry.Communicated by Ramaswamy H. Sarma.

Structural and Dynamical Basis of VP35-RBD Inhibition by Marine Fungi Compounds to Combat Marburg Virus Infection

The Marburg virus (MBV), a deadly pathogen, poses a serious threat to world health due to the lack of effective treatments, calling for an immediate search for targeted and efficient treatments. In this study, we focused on compounds originating from marine fungi in order to identify possible inhibitory compounds against the Marburg virus (MBV) VP35-RNA binding domain (VP35-RBD) using a computational approach. We started with a virtual screening procedure using the Lipinski filter as a guide. Based on their docking scores, 42 potential candidates were found. Four of these compounds-CMNPD17596, CMNPD22144, CMNPD25994, and CMNPD17598-as well as myricetin, the control compound, were chosen for re-docking analysis. Re-docking revealed that these particular compounds had a higher affinity for MBV VP35-RBD in comparison to the control. Analyzing the chemical interactions revealed unique binding properties for every compound, identified by a range of Pi-cation interactions and hydrogen bond types. We were able to learn more about the dynamic behaviors and stability of the protein-ligand complexes through a 200-nanosecond molecular dynamics simulation, as demonstrated by the compounds' consistent RMSD and RMSF values. The multidimensional nature of the data was clarified by the application of principal component analysis, which suggested stable conformations in the complexes with little modification. Further insight into the energy profiles and stability states of these complexes was also obtained by an examination of the free energy landscape. Our findings underscore the effectiveness of computational strategies in identifying and analyzing potential inhibitors for MBV VP35-RBD, offering promising paths for further experimental investigations and possible therapeutic development against the MBV.

Computational Screening of Repurposed Drugs for HMG-CoA Synthase 2 in Alzheimer's Disease

Background

HMGCS2 (mitochondrial 3-hydroxy-3-methylglutaryl-COA synthase 2) plays a pivotal role as a control enzyme in ketogenesis, and its association with the amyloid-β protein precursor (AβPP) in mitochondria implicates a potential involvement in Alzheimer's disease (AD) pathophysiology.

Objective

Our study aimed at identifying repurposed drugs using the DrugBank database capable of inhibiting HMGCS2 activity.

Methods

Exploiting the power of drug repurposing in conjunction with virtual screening and molecular dynamic (MD) simulations against 'HMGCS2', we present new in-silico insight into structure-based drug repurposing.

Results

The initial molecules were screened for their binding affinity to HMGCS2. Subsequent interaction analyses and extensive 300 ns MD simulations were conducted to explore the conformational dynamics and stability of HMGCS2 in complex with the screened molecules, particularly Penfluridol and Lurasidone.

Conclusions

The study revealed that HMGCS2 forms stable protein-ligand complexes with Penfluridol and Lurasidone. Our findings indicate that Penfluridol and Lurasidone competitively bind to HMGCS2 and warrant their further exploration as potential repurposed molecules for anti-Alzheimer's drug development.

Sulfonamide Derivatives: Recent Compounds with Potent Anti-alzheimer's Disease Activity

Facile synthetic procedures and broad spectrum of biological activities are special attributes of sulfonamides. Sulfonamide derivatives have demonstrated potential as a class of compounds for the treatment of Alzheimer's disease (AD). Recent sulfonamide derivatives have been reported as prospective anti-AD agents, with a focus on analogues that significantly inhibit the function of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes and exhibit remarkable antioxidant and anti-inflammatory properties, all of which are critical for the treatment of AD. Sulfonamide- mediated activation of nuclear factor erythroid 2-related factor 2 (NRF2), a key regulator of the endogenous antioxidant response, has also been suggested as a potential therapeutic approach in AD. Additionally, it has been discovered that a number of sulfonamide derivatives show selectivity for the β- and γ-secretase enzymes and a significant reduction of amyloid B (Aβ) aggregation, which have been implicated in AD. The comparative molecular docking of benzenesulfonamide and donepezil, an AD reference drug showed comparable anti-AD activities. These suggest that sulfonamide derivatives may represent a new class of drugs for the treatment of AD. Thus, the current review will focus on recent studies on the chemical synthesis and evaluation of the anti-AD properties, molecular docking, pharmacological profile, and structure-activity relationship (SAR) of sulfonamide derivatives, as well as their potential anti-AD mechanisms of action. This paper offers a thorough assessment of the state of the art in this field of study and emphasizes the potential of sulfonamide derivatives synthesized during the 2012-2023 period as a new class of compounds for the treatment of AD.

Selection of a novel cell-internalizing RNA aptamer specific for CD22 antigen in B cell acute lymphoblastic leukemia

Despite improvements in B cell acute lymphoblastic leukemia (B-ALL) treatment, a significant number of patients experience relapse of the disease, resulting in poor prognosis and high mortality. One of the drawbacks of current B-ALL treatments is the high toxicity associated with the non-specificity of chemotherapeutic drugs. Targeted therapy is an appealing strategy to treat B-ALL to mitigate these toxic off-target effects. One such target is the B cell surface protein CD22. The restricted expression of CD22 on the B-cell lineage and its ligand-induced internalizing properties make it an attractive target in cases of B cell malignancies. To target B-ALL and the CD22 protein, we performed cell internalization SELEX (Systematic Evolution of Ligands by EXponential enrichment) followed by molecular docking to identify internalizing aptamers specific for B-ALL cells that bind the CD22 cell-surface receptor. We identified two RNA aptamers, B-ALL1 and B-ALL2, that target human malignant B cells, with B-ALL1 the first documented RNA aptamer interacting with the CD22 antigen. These B-ALL-specific aptamers represent an important first step toward developing novel targeted therapies for B cell malignancy treatments.

Exploring the structural, photophysical and optoelectronic properties of a diaryl heptanoid curcumin derivative and identification as a SARS-CoV-2 inhibitor

Developing modifiable natural products those having antiviral activities against SARS-CoV-2 is a key research area which is popular in current scenario of COVID pandemic. A diaryl heptanoid curcumin and its derivatives are already presenting promising candidates for anti-viral drug development. We have synthesized single crystals of a dimethylamino derivative of natural curcumin and structural characterization was done by single crystal XRD analysis. Using steady-state absorption and emission spectra and guided by complimentary ab initio calculations, we unraveled the solvent effects on the photophysical properties of the dimethyl amino curcumin derivative. Chemical reactivity of the compound has investigated using frontier molecular orbitals and molecular electrostatic potential surface. High stability of the curcumin derivative in water environment has evaluated by Radial Distributions Functions (RDF) calculated via Molecular Dynamics (MD) simulations. The inhibitory activity of the title compound was evaluated by in silico methods and the stability of the protein-ligand complexes were studied using Molecular Dynamics simulations and MM-PBSA analysis. With this detailed study, we hope to motivate scientific community to develop new curcumin derivatives against SARS-CoV-2 virus.

Natural fulvic acids inhibit non-small-cell lung cancer through the COX-2/PGE2/EP4 axis: In silico and in vivo assessments

Purpose

Non-small-cell lung cancer (NSCLC) is a major public health concern with a high incidence worldwide. Coal-derived fulvic acids (FAs) contain functional groups in their chemical structures. Overexpression of cyclooxygenases-2 (COX-2), prostaglandin E2 (PGE2), and the PGE2 receptor EP4 subtype (EP4) can have a potential link with the increased tumor incidence and promoted tumor growth and metastasis in NSCLC. This study aimed to assess the biological roles of coal-derived FAs in the growth and development of NSCLC and to elucidate the underlying molecular mechanisms.

Methods

A web-based tool for predicting small-molecule pharmacokinetics (pkCSM) was used to analyze the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of FAs. Molecular docking and dynamic simulations were performed to analyze the binding affinities of COX-2 and EP4 to FA. An acute toxicity test and an antitumor study were used to analyze the toxicity and anti-NSCLC effects of FAs. Thirty NSCLC-bearing nude mice were randomly divided into five groups (six mice per group): vehicle control, positive control with 20 mg/kg body weight (BW) 5-fluorouracil, and three treatments with 25, 50, and 100 mg/kg BW FAs. The BW and tumor volume were recorded, and the COX-2, PGE2, and EP4 protein expression were measured and analyzed.

Results

Using the predictive pkCSM algorithm, we found that FA did not cause developmental toxicity. Molecular simulations revealed that COX-2 and EP4 expression was inhibited by FA. An acute toxicity test conformed that the maximum tolerated FAs dose was >3.0 g/kg BW. The animal study demonstrated that FA treatment significantly downregulated the expression of COX-2, PGE2, and EP4 in NSCLC-bearing mice compared to that in vehicle control mice (p < 0.01).

Conclusions

Natural FAs may exert anti-NSCLC effects through the COX-2/PGE2/EP4 axis.

Repurposing FIASMAs against Acid Sphingomyelinase for COVID-19: A Computational Molecular Docking and Dynamic Simulation Approach

Over the past few years, COVID-19 has caused widespread suffering worldwide. There is great research potential in this domain and it is also necessary. The main objective of this study was to identify potential inhibitors against acid sphingomyelinase (ASM) in order to prevent coronavirus infection. Experimental studies revealed that SARS-CoV-2 causes activation of the acid sphingomyelinase/ceramide pathway, which in turn facilitates the viral entry into the cells. The objective was to inhibit acid sphingomyelinase activity in order to prevent the cells from SARS-CoV-2 infection. Previous studies have reported functional inhibitors against ASM (FIASMAs). These inhibitors can be exploited to block the entry of SARS-CoV-2 into the cells. To achieve our objective, a drug library containing 257 functional inhibitors of ASM was constructed. Computational molecular docking was applied to dock the library against the target protein (PDB: 5I81). The potential binding site of the target protein was identified through structural alignment with the known binding pocket of a protein with a similar function. AutoDock Vina was used to carry out the docking steps. The docking results were analyzed and the inhibitors were screened based on their binding affinity scores and ADME properties. Among the 257 functional inhibitors, Dutasteride, Cepharanthine, and Zafirlukast presented the lowest binding affinity scores of −9.7, −9.6, and −9.5 kcal/mol, respectively. Furthermore, computational ADME analysis of these results revealed Cepharanthine and Zafirlukast to have non-toxic properties. To further validate these findings, the top two inhibitors in complex with the target protein were subjected to molecular dynamic simulations at 100 ns. The molecular interactions and stability of these compounds revealed that these inhibitors could be a promising tool for inhibiting SARS-CoV-2 infection.

Identification of Natural Lead Compounds against Hemagglutinin-Esterase Surface Glycoprotein in Human Coronaviruses Investigated via MD Simulation, Principal Component Analysis, Cross-Correlation, H-Bond Plot and MMGBSA

The pandemic outbreak of human coronavirus is a global health concern that affects people of all ages and genders, but there is currently still no effective, approved and potential drug against human coronavirus, as many other coronavirus vaccines have serious side effects while the development of small antiviral inhibitors has gained tremendous attention. For this research, HE was used as a therapeutic target, as the spike protein displays a high binding affinity for both host ACE2 and viral HE glycoprotein. Molecular docking, pharmacophore modelling and virtual screening of 38,000 natural compounds were employed to find out the best natural inhibitor against human coronaviruses with more efficiency and fewer side effects and further evaluated via MD simulation, PCA, DCCR and MMGBSA. The lead compound ‘Calceolarioside B’ was identified on the basis of pharmacophoric features which depict favorable binding (ΔGbind −37.6799 kcal/mol) with the HE(5N11) receptor that describes positive correlation movements in active site residues with better stability, a robust H-bond network, compactness and reliable ADMET properties. The Fraxinus sieboldiana Blume plant containing the Calceolarioside B compound could be used as a potential inhibitor that shows a higher efficacy and potency with fewer side effects. This research work will aid investigators in the testing and identification of chemicals that are effective and useful against human coronavirus.

Structural evolution of Delta lineage of SARS-CoV-2

One of the main obstacles in prevention and treatment of COVID-19 is the rapid evolution of the SARS-CoV-2 Spike protein. Given that Spike is the main target of common treatments of COVID-19, mutations occurring at this virulent factor can affect the effectiveness of treatments. The B.1.617.2 lineage of SARS-CoV-2, being characterized by many Spike mutations inside and outside of its receptor-binding domain (RBD), shows high infectivity and relative resistance to existing cures. Here, utilizing a wide range of computational biology approaches, such as immunoinformatics, molecular dynamics (MD), analysis of intrinsically disordered regions (IDRs), protein-protein interaction analyses, residue scanning, and free energy calculations, we examine the structural and biological attributes of the B.1.617.2 Spike protein. Furthermore, the antibody design protocol of Rosetta was implemented for evaluation the stability and affinity improvement of the Bamlanivimab (LY-CoV55) antibody, which is not capable of interactions with the B.1.617.2 Spike. We observed that the detected mutations in the Spike of the B1.617.2 variant of concern can cause extensive structural changes compatible with the described variation in immunogenicity, secondary and tertiary structure, oligomerization potency, Furin cleavability, and drug targetability. Compared to the Spike of Wuhan lineage, the B.1.617.2 Spike is more stable and binds to the Angiotensin-converting enzyme 2 (ACE2) with higher affinity.

Dietary anthocyanins inhibit insulin fibril formation and cytotoxicity in 3T3-L1 preadipocytes

Insulin fibril formation decreases the effectiveness of insulin therapy and causes amyloidosis in diabetes. Studies suggest that phytochemicals are capable of inhibiting fibril formation. Herein, we investigated the inhibitory effects of anthocyanins, including cyanidin, cyanidin-3-glucoside (C3G), cyanidin-3-rutinoside (C3R), malvidin, and malvidin-3-glucoside (M3G) on fibril formation. Our results revealed that anthocyanins (50-200 μM) significantly reduced the formation of insulin fibrils by increasing lag times and decreasing ThT fluorescence at the plateau phase. These findings were confirmed by TEM images, which showed reduced fibril length and number. Furthermore, FTIR analysis indicated that anthocyanins reduced the secondary structure transition of insulin from α-helix to β-sheet. Anthocyanins interacted with monomeric insulin (residues B8-B30) via H-bonds, van der Waals, and hydrophobic interactions, covering the fibril-prone segments of insulin (residues B12-B17). Based on the structure-activity analysis, the presence of glycosides and hydroxyl groups on phenyl rings increased intermolecular interaction, mediating the inhibitory effect of anthocyanins on fibril formation in the order of malvidin < cyanidin < M3G < C3G < C3R. Moreover, anthocyanins formed H-bonds with preformed insulin fibrils, except for malvidin. In preadipocytes, C3R, C3G, and cyanidin attenuated insulin fibril-induced cytotoxicity. In conclusion, anthocyanins are effective inhibitors of insulin fibril formation and cytotoxicity.

Deciphering Isoniazid Drug Resistance Mechanisms on Dimeric Mycobacterium tuberculosis KatG via Post-molecular Dynamics Analyses Including Combined Dynamic Residue Network Metrics

Resistance mutations in Mycobacterium tuberculosis (Mtb) catalase peroxidase protein (KatG), an essential enzyme in isoniazid (INH) activation, reduce the sensitivity of Mtb to first-line drugs, hence presenting challenges in tuberculosis (TB) management. Thus, understanding the mutational imposed resistance mechanisms remains of utmost importance in the quest to reduce the TB burden. Herein, effects of 11 high confidence mutations in the KatG structure and residue network communication patterns were determined using extensive computational approaches. Combined traditional post-molecular dynamics analysis and comparative essential dynamics revealed that the mutant proteins have significant loop flexibility around the heme binding pocket and enhanced asymmetric protomer behavior with respect to wild-type (WT) protein. Heme contact analysis between WT and mutant proteins identified a reduction to no contact between heme and residue His270, a covalent bond vital for the heme-enabled KatG catalytic activity. Betweenness centrality calculations showed large hub ensembles with new hubs especially around the binding cavity and expanded to the dimerization domain via interface in the mutant systems, providing possible compensatory allosteric communication paths for the active site as a result of the mutations which may destabilize the heme binding pocket and the loops in its vicinity. Additionally, an interesting observation came from Eigencentrality hubs, most of which are located in the C-terminal domain, indicating relevance of the domain in the protease functionality. Overall, our results provide insight toward the mechanisms involved in KatG-INH resistance in addition to identifying key regions in the enzyme functionality, which can be used for future drug design.

Hydrogen Bonds with Fluorine in Ligand-Protein Complexes-the PDB Analysis and Energy Calculations

Fluorine is a common substituent in medicinal chemistry and is found in up to 50% of the most profitable drugs. In this study, a statistical analysis of the nature, geometry, and frequency of hydrogen bonds (HBs) formed between the aromatic and aliphatic C-F groups of small molecules and biological targets found in the Protein Data Bank (PDB) repository was presented. Interaction energies were calculated for those complexes using three different approaches. The obtained results indicated that the interaction energy of F-containing HBs is determined by the donor-acceptor distance and not by the angles. Moreover, no significant relationship between the energies of HBs with fluorine and the donor type was found, implying that fluorine is a weak HB acceptor for all types of HB donors. However, the statistical analysis of the PDB repository revealed that the most populated geometric parameters of HBs did not match the calculated energetic optima. In a nutshell, HBs containing fluorine are forced to form due to the stronger ligand-receptor neighboring interactions, which make fluorine the "donor's last resort".

Computational Prediction of Binding Affinity for CDK2-ligand Complexes. A Protein Target for Cancer Drug Discovery

BACKGROUND

CDK2 participates in the control of eukaryotic cell-cycle progression. Due to the great interest in CDK2 for drug development and the relative easiness in crystallizing this enzyme, we have over 400 structural studies focused on this protein target. This structural data is the basis for the development of computational models to estimate CDK2-ligand binding affinity.

OBJECTIVE

This work focuses on the recent developments in the application of supervised machine learning modeling to develop scoring functions to predict the binding affinity of CDK2.

METHOD

We employed the structures available at the protein data bank and the ligand information accessed from the BindingDB, Binding MOAD, and PDBbind to evaluate the predictive performance of machine learning techniques combined with physical modeling used to calculate binding affinity. We compared this hybrid methodology with classical scoring functions available in docking programs.

RESULTS

Our comparative analysis of previously published models indicated that a model created using a combination of a mass-spring system and cross-validated Elastic Net to predict the binding affinity of CDK2-inhibitor complexes outperformed classical scoring functions available in AutoDock4 and AutoDock Vina.

CONCLUSION

All studies reviewed here suggest that targeted machine learning models are superior to classical scoring functions to calculate binding affinities. Specifically for CDK2, we see that the combination of physical modeling with supervised machine learning techniques exhibits improved predictive performance to calculate the protein-ligand binding affinity. These results find theoretical support in the application of the concept of scoring function space.

Structure-based virtual screening and molecular dynamics of phytochemicals derived from Saudi medicinal plants to identify potential COVID-19 therapeutics

Coronavirus disease 2019 (COVID-19) has affected almost every country in the world by causing a global pandemic with a high mortality rate. Lack of an effective vaccine and/or antiviral drugs against SARS-CoV-2, the causative agent, has severely hampered the response to this novel coronavirus. Natural products have long been used in traditional medicines to treat various diseases, and purified phytochemicals from medicinal plants provide a valuable scaffold for the discovery of new drug leads. In the present study, we performed a computational screening of an in-house database composed of ~1000 phytochemicals derived from traditional Saudi medicinal plants with recognised antiviral activity. Structure-based virtual screening was carried out against three druggable SARS-CoV-2 targets, viral RNA-dependent RNA polymerase (RdRp), 3-chymotrypsin-like cysteine protease (3CL^pro) and papain like protease (PL^pro) to identify putative inhibitors that could facilitate the development of potential anti-COVID-19 drug candidates. Computational analyses identified three compounds inhibiting each target, with binding affinity scores ranging from -9.9 to -6.5 kcal/mol. Among these, luteolin 7-rutinoside, chrysophanol 8-(6-galloylglucoside) and kaempferol 7-(6″-galloylglucoside) bound efficiently to RdRp, while chrysophanol 8-(6-galloylglucoside), 3,4,5-tri-O-galloylquinic acid and mulberrofuran G interacted strongly with 3CL^pro, and withanolide A, isocodonocarpine and calonysterone bound tightly to PL^pro. These potential drug candidates will be subjected to further in vitro and in vivo studies and may assist the development of effective anti-COVID-19 drugs.

A mutant of Pseudoalteromonas carrageenovora arylsulfatase with enhanced enzyme activity and its potential application in improvement of the agar quality

Enzymatic desulfation using arylsulfatase provides an attractive approach to improve agar quality. We have previously characterized a functional arylsulfatase from Pseudoalteromonas carrageenovora. To further improve its enzymatic performance, we isolated a mutant arylsulfatase of K253Q with improved enzyme activity from a random mutant library. Compared to wild-type arylsulfatase (WT), K253Q showed 33% increase in enzyme activity, with optimal temperature and pH of 55 °C and 8.0, respectively. K253Q demonstrated better substrate binding ability with lower K_m value. Structure analysis indicated that a combination of the additional hydrogen bond and the enhanced substrate binding affinity could account for the improved enzyme activity of K253Q. K253Q exhibited about 54% sulfate removal against agar, resulting in additional 8% increase in 3,6-AG content and 20% increase in gel strength compared to WT. Scanning electron microscopy showed that K253Q treatment led to a stronger crosslinking structure of agar.