A fresh look at the Ramachandran plot and the occurrence of standard structures in proteins

Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach

BACKGROUND

Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases.

METHODS

The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level.

RESULTS

Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses.

CONCLUSIONS

Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Subtractive genomics study for the identification of therapeutic targets against Cronobacter sakazakii: A threat to infants

Cronobacter sakazakii is an opportunistic pathogen that has been associated with severe infection in neonates such as necrotizing enterocolitis (NEC), neonatal meningitis, and bacteremia. This pathogen can survive in a relatively dry environment, especially in powdered infant formula (PIF). Unfortunately, conventional drugs that were once effective against C. sakazakii are gradually losing their efficacy due to rising antibiotic resistance. In this study, a subtractive genomic approach was followed in order to identify potential therapeutic targets in the pathogen. The whole proteome of the pathogen was filtered through a step-by-step process, which involved removing paralogous proteins, human homologs, sequences that are less essential for survival, proteins with shared metabolic pathways, and proteins that are located in cells other than the cytoplasmic membrane. As a result, nine novel drug targets were identified. Further, the analysis also unveiled that the FDA-approved drug Terbinafine can be repurposed against the Glutathione/l-cysteine transport system ATP-binding/permease protein CydC of C. sakazakii. Moreover, molecular docking and dynamics studies of Terbinafine and CydC suggested that this drug can be used to treat C. sakazakii infection in neonates. However, for clinical purposes further in vitro and in vivo studies are necessary.

Characterization of host receptor interaction with envelop protein of Kyasanur forest disease virus and predicting suitable epitopes for vaccine candidate

Kyasanur forest disease (KFD) is a zoonotic disease that is endemic to southern India and caused by KFD virus (KFDV) belonging to the family Flaviviridae. Humans are the dead-end host of the KFDV life cycle. The absence of effective treatment strategies against KFD can be attributed to a lack of studies on the mechanistic part of the spread of the disease. Hypothesizing molecular etiological similarity of KFDV to other well characterized flaviviruses, such as dengue virus (DENV), we focused on predicting the target receptor protein(s) in host and provided molecular basis of receptor-mediated recognition of the human host by KFDV envelop protein (EKFDV), drawing from the extant knowledge on the dengue counterpart, EDENV. Indeed, in silico approach helped to identify that the EKFDV structure closely resembles the EDENV structure and indicated DC-SIGN and/or Mannose receptors to be the plausible target host receptors. Immune-informatics approach aided in predicting 10 epitopes from E, NS1, NS2A, and NS2B proteins of the KFDV-P9605 genotype for vaccine design against KFDV. Further, molecular dynamics simulation (MDS) analyses of their complexes with human leukocyte antigens (HLAs) identified the epitopes DISLTCRVT and YAMEIRPVH as two high ranking candidates for vaccine design.Communicated by Ramaswamy H. Sarma.

On Protein Loops, Prior Molecular States and Common Ancestors of Life

The principle of continuity demands the existence of prior molecular states and common ancestors responsible for extant macromolecular structure. Here, we focus on the emergence and evolution of loop prototypes - the elemental architects of protein domain structure. Phylogenomic reconstruction spanning superkingdoms and viruses generated an evolutionary chronology of prototypes with six distinct evolutionary phases defining a most parsimonious evolutionary progression of cellular life. Each phase was marked by strategic prototype accumulation shaping the structures and functions of common ancestors. The last universal common ancestor (LUCA) of cells and viruses and the last universal cellular ancestor (LUCellA) defined stem lines that were structurally and functionally complex. The evolutionary saga highlighted transformative forces. LUCA lacked biosynthetic ribosomal machinery, while the pivotal LUCellA lacked essential DNA biosynthesis and modern transcription. Early proteins therefore relied on RNA for genetic information storage but appeared initially decoupled from it, hinting at transformative shifts of genetic processing. Urancestral loop types suggest advanced folding designs were present at an early evolutionary stage. An exploration of loop geometric properties revealed gradual replacement of prototypes with α-helix and β-strand bracing structures over time, paving the way for the dominance of other loop types. AlphFold2-generated atomic models of prototype accretion described patterns of fold emergence. Our findings favor a ‛processual' model of evolving stem lines aligned with Woese's vision of a communal world. This model prompts discussing the 'problem of ancestors' and the challenges that lie ahead for research in taxonomy, evolution and complexity.

Immunoinformatic based designing of potential immunogenic novel mRNA and peptide-based prophylactic vaccines against H5N1 and H7N9 avian influenza viruses

Influenza viruses are the most common cause of serious respiratory illnesses worldwide and are responsible for a significant number of annual fatalities. Therefore, it is crucial to look for new immunogenic sites that might trigger an effective immune response. In the present study, bioinformatics tools were used to design mRNA and multiepitope-based vaccines against H5N1 and H7N9 subtypes of avian influenza viruses. Several Immunoinformatic tools were employed to extrapolate T and B lymphocyte epitopes of HA and NA proteins of both subtypes. The molecular docking approach was used to dock the selected HTL and CTL epitopes with the corresponding MHC molecules. Eight (8) CTL, four (4) HTL, and Six (6) linear B cell epitopes were chosen for the structural arrangement of mRNA and of peptide-based prophylactic vaccine designs. Different physicochemical characteristics of the selected epitopes fitted with suitable linkers were analyzed. High antigenic, non-toxic, and non-allergenic features of the designed vaccines were noted at a neutral physiological pH. Codon optimization tool was used to check the GC content and CAI value of constructed MEVC-Flu vaccine, which were recorded to be 50.42% and 0.97 respectively. the GC content and CAI value verify the stable expression of vaccine in pET28a + vector. In-silico immunological simulation the MEVC-Flu vaccine construct revealed a high level of immune responses. The molecular dynamics simulation and docking results confirmed the stable interaction of TLR-8 and MEVC-Flu vaccine. Based on these parameters, vaccine constructs can be regarded as an optimistic choice against H5N1 and H7N9 strains of the influenza virus. Further experimental testing of these prophylactic vaccine designs against pathogenic avian influenza strains may clarify their safety and efficacy.Communicated by Ramaswamy H. Sarma.

Br - nanoconjugate enhances the antibacterial efficacy of nimboloide against Flavobacterium columnare infection in Labeo rohita: A nanoinformatics approach

BACKGROUND

The bacterial pathogen, Flavobacterium columnare causes columnaris disease in Labeo rohita globally. Major effects of this bacterial infection include skin rashes and gill necrosis. Nimbolide, the key ingredient of the leaf extract of Azadirachta indica possesses anti-bacterial properties effective against many microorganisms. Nano-informatics plays a promising role in drug development and its delivery against infections caused by multi-drug-resistant bacteria. Currently, studies in the disciplines of dentistry, food safety, bacteriology, mycology, virology, and parasitology are being conducted to learn more about the wide anti-virulence activity of nimbolide.

METHODS

The toxicity of nimbolide was predicted to determine its dosage for treating bacterial infection in Labeo rohita. Further, comparative 3-D structure prediction and docking studies are done for nimbolide conjugated nanoparticles with several key target receptors to determine better natural ligands against columnaris disease. The nanoparticle conjugates are being designed using in-silico approaches to study molecular docking interactions with the target receptor.

RESULTS

Bromine conjugated nimbolide shows the best molecular interaction with the target receptors of selected species ie L rohita. Nimbolide comes under the class III level of toxic compound so, attempts are made to reduce the dosage of the compound without compromising its efficiency. Further, bromine is also used as a common surfactant and can eliminate heavy metals from wastewater.

CONCLUSION

The dosage of bromine-conjugated nimbolide can be reduced to a non-toxic level and thus the efficiency of the Nimbolide can be increased. Moreover, it can be used to synthesize nanoparticle composites which have potent antibacterial activity towards both gram-positive and gram-negative bacteria. This material also forms a good coating on the surface and kills both airborne and waterborne bacteria.

Exploring host epigenetic enzymes as targeted therapies for visceral leishmaniasis: in silico design and in vitro efficacy of KDM6B and ASH1L inhibitors

In order to combat various infectious diseases, the utilization of host-directed therapies as an alternative to chemotherapy has gained a lot of attention in the recent past, since it bypasses the existing limitations of conventional therapies. The use of host epigenetic enzymes like histone lysine methyltransferases and lysine demethylases as potential drug targets has successfully been employed for controlling various inflammatory diseases like rheumatoid arthritis and acute leukemia. In our earlier study, we have already shown that the functional knockdown of KDM6B and ASH1L in the experimental model of visceral leishmaniasis has resulted in a significant reduction of organ parasite burden. Herein, we performed a high throughput virtual screening against KDM6B and ASH1L using > 53,000 compounds that were obtained from the Maybridge library and PubChem Database, followed by molecular docking to evaluate their docking score/Glide Gscore. Based on their docking scores, the selected inhibitors were later assessed for their in vitro anti-leishmanial efficacy. Out of all inhibitors designed against KDM6B and ASH1L, HTS09796, GSK-J4 and AS-99 particularly showed promising in vitro activity with IC50 < 5 µM against both extracellular promastigote and intracellular amastigote forms of L. donovani. In vitro drug interaction studies of these inhibitors further demonstrated their synergistic interaction with amphotericin-B and miltefosine. However, GSK-J4 makes an exception by displaying an in different mode of interaction with miltefosine. Collectively, our in silico and in vitro studies acted as a platform to identify the applicability of these inhibitors targeted against KDM6B and ASH1L for anti-leishmanial therapy.

Construction of an aerolysin-based multi-epitope vaccine against Aeromonas hydrophila: an in silico machine learning and artificial intelligence-supported approach

Aeromonas hydrophila, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis, and endocarditis. It frequently occurs in aquatic environments and readily contacts humans, leading to high infection rates. This bacterium has exhibited resistance to numerous commercial antibiotics, and no vaccine has yet been developed. Aiming to combat the alarmingly high infection rate, this study utilizes in silico techniques to design a multi-epitope vaccine (MEV) candidate against this bacterium based on its aerolysin toxin, which is the most toxic and highly conserved virulence factor among the Aeromonas species. After retrieval, aerolysin was processed for B-cell and T-cell epitope mapping. Once filtered for toxicity, antigenicity, allergenicity, and solubility, the chosen epitopes were combined with an adjuvant and specific linkers to create a vaccine construct. These linkers and the adjuvant enhance the MEV's ability to elicit robust immune responses. Analyses of the predicted and improved vaccine structure revealed that 75.5%, 19.8%, and 1.3% of its amino acids occupy the most favored, additional allowed, and generously allowed regions, respectively, while its ERRAT score reached nearly 70%. Docking simulations showed the MEV exhibiting the highest interaction and binding energies (-1,023.4 kcal/mol, -923.2 kcal/mol, and -988.3 kcal/mol) with TLR-4, MHC-I, and MHC-II receptors. Further molecular dynamics simulations demonstrated the docked complexes' remarkable stability and maximum interactions, i.e., uniform RMSD, fluctuated RMSF, and lowest binding net energy. In silico models also predict the vaccine will stimulate a variety of immunological pathways following administration. These analyses suggest the vaccine's efficacy in inducing robust immune responses against A. hydrophila. With high solubility and no predicted allergic responses or toxicity, it appears safe for administration in both healthy and A. hydrophila-infected individuals.

Riparin II-type benzamides as novel antibiofilm agents against dermatophytes: chemical synthesis, in vitro, ex vivo and in silico evaluation

BACKGROUND

The ability of dermatophytes to develop biofilms in host tissues confers physical and biochemical resistance to antifungal drugs. Therefore, research to find new compounds against dermatophyte biofilm is crucial.

OBJECTIVES

To evaluate the antifungal activity of riparin II (RIP2), nor-riparin II (NOR2) and dinor-riparin II (DINOR2) against Trichophyton rubrum, Microsporum canis and Nannizzia gypsea strains.

METHODS

Initially, we determined the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) of benzamides. We evaluated the inhibitory effects on the development of dermatophyte biofilms using in vitro and ex vivo models. Finally, we built three-dimensional models of the sulphite pump Ssu1 to investigate the interactions with the benzamides by molecular docking.

RESULTS

RIP2 showed a broad spectrum of activity against T. rubrum, M. canis and N. gypsea, whereas NOR2 and DINOR2 were more selective. Furthermore, the shortening of the carbon chain from RIP2 benzamide to NOR2 and DINOR2 homologs caused a decrease in the MIC values. The benzamides reduced biofilm production and viability in vitro (P < 0.05) at MIC. This result was similar ex vivo in human nail fragments tests, but NOR2 and DINOR2 showed significant results at 2xMIC (P < 0.05). We constructed a model of the Ssu1 protein for each dermatophyte with high similarity. Molecular docking showed that the benzamides obtained higher binding energy values than ciclopirox.

CONCLUSIONS

Our study shows the antibiofilm potential for riparin II-type benzamides as new drugs targeting dermatophytes by inhibiting the Ssu1 protein.

Escherichia coli FtsZ molecular dynamics simulations

Earlier molecular dynamics studies of the FtsZ protein revealed that the protein has high intrinsic flexibility which the crystal structures cannot reveal. However, the input structure in these simulation studies was based on the available crystal structure data and therefore, the effect of the C-terminal Intrinsically Disordered Region (IDR) of FtsZ could not be observed in any of these studies. Recent investigations have revealed that the C-terminal IDR is crucial for FtsZ assembly in vitro and Z ring formation in vivo. Therefore, in this study, we simulated FtsZ with the IDR. Simulations of the FtsZ monomer in different nucleotide bound forms (without nucleotide, GTP, GDP) were performed. In the conformations of FtsZ monomer with GTP, GTP binds variably with the protein. Such a variable interaction with the monomer has not been observed in any previous simulation studies of FtsZ and not observed in crystal structures. We found that central helix bends towards the C-terminal domain in the GTP bound form, hence, making way for polymerization. A nucleotide dependent shift/rotation of the C-terminal domain was observed in simulation time averaged structures.Communicated by Ramaswamy H. Sarma.

Dynamics and recognition of homeodomain containing protein-DNA complex of IRX4

Iroquois Homeobox 4 (IRX4) belongs to a family of homeobox TFs having roles in embryogenesis, cell specification, and organ development. Recently, large scale genome-wide association studies and epigenetic studies have highlighted the role of IRX4 and its associated variants in prostate cancer. No studies have investigated and characterized the structural aspect of the IRX4 homeodomain and its potential to bind to DNA. The current study uses sequence analysis, homology modeling, and molecular dynamics simulations to explore IRX4 homeodomain-DNA recognition mechanisms and the role of somatic mutations affecting these interactions. Using publicly available databases, gene expression of IRX4 was found in different tissues, including prostate, heart, skin, vagina, and the protein expression was found in cancer cell lines (HCT166, HEK293), B cells, ascitic fluid, and brain. Sequence conservation of the homeodomain shed light on the importance of N- and C-terminal residues involved in DNA binding. The specificity of IRX4 homodimer bound to consensus human DNA sequence was confirmed by molecular dynamics simulations, representing the role of conserved amino acids including R145, A194, N195, S190, R198, and R199 in binding to DNA. Additional N-terminal residues like T144 and G143 were also found to have specific interactions highlighting the importance of N-terminus of the homeodomain in DNA recognition. Additionally, the effects of somatic mutations, including the conserved Arginine (R145, R198, and R199) residues on DNA binding elucidated the importance of these residues in stabilizing the protein-DNA complex. Secondary structure and hydrogen bonding analysis showed the roles of specific residues (R145, T191, A194, N195, R198, and R199) in maintaining the homogeneity of the structure and its interaction with DNA. The differences in relative binding free energies of all the mutants shed light on the structural modularity of this protein and the dynamics behind protein-DNA interaction. We also have predicted that the C-terminal sequence of the IRX4 homeodomain could act as a potential cell-penetrating peptide, emphasizing the role these small peptides could play in targeting homeobox TFs.

Exploring the association of ESR1 and ESR2 gene SNPs with polycystic ovary syndrome in human females: a comprehensive association study

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.

METHODS

For this study, SNPs in ESR1 and ESR2 genes were retrieved from the ENSEMBL database and analyzed for their effect on mutated proteins using different bioinformatics tools including SIFT, PolyPhen, CADD, REVEL, MetaLR, I-Mutant, CELLO2GO, ProtParam, SOPMA, SWISS-MODEL and HDDOCK.

RESULTS

All the SNPs documented in the present study were deleterious. All the SNPs except rs1583384537, rs1450198518, and rs78255744 decreased protein stability. Two variants rs1463893698 and rs766843910 in the ESR2 gene altered the localization of mutated proteins i.e. in addition to the nucleus, proteins were also found in mitochondria and extracellular, respectively. SNPs rs104893956 in ESR1 and rs140630557, rs140630557, rs1596423459, rs766843910, rs1596405923, rs762454979 and rs1384121511 in ESR2 gene significantly changed the secondary structure of proteins (2D). SNPs that markedly changed 3D configuration included rs1554259481, rs188957694 and rs755667747 in ESR1 gene and rs1463893698, rs140630557, rs1596423459, rs766843910, rs1596405923, rs762454979 and rs1384121511 in ESR2 gene. Variants rs1467954450 (ESR1) and rs140630557 (ESR2) were identified to reduce the binding tendency of ESRα and β receptors with estradiol as reflected by the docking scores i.e. -164.97 and -173.23, respectively.

CONCLUSION

Due to the significant impact on the encoded proteins, these variants might be proposed as biomarkers to predict the likelihood of developing PCOS in the future and for diagnostic purposes.

Elucidation of the structural dynamics of mutations in PHB2 protein associated with growth suppression and cancer progression

Prohibitin is a multifunctional protein that plays an important role in numerous cellular processes. Membrane-associated mitochondrial prohibitin complex is made up of two subunits, PHB1 and PHB2 which are ubiquitously expressed and analogous to each other. High levels of prohibitin expression have consequently been found in esophageal cancer, endometrial adenocarcinoma, gastric cancer, hepatocellular carcinoma, breast cancer and bladder cancer. The aim of this study is to analyse two-point mutation PHB2_MT1(I → A) and PHB2_MT2(I → P), their effect on PHB2 protein and its effect on formation of mitochondrial complex. It is a residual level study, based on current experimental validation. To establish the effects of the two-point mutations, computational approaches such as molecular modelling, molecular docking, normal mode simulation, molecular dynamics simulations and MM/GBSA were used. An analysis of the energy dynamics of both unbound and complex proteins was conducted to elucidate how mutations impact the energy distribution of PHB2. Our study confirmed that the two mutations decreased the overall stability of PHB2. This was evidenced by heightened atomic fluctuations within the mutated region, accompanied by elevated deviations observed in RMSD and Rg values. Furthermore, these mutations were correlated with a decline in the organization of secondary structural elements. The mutations in PHB2_MT1 and PHB2_MT2 resulted in formation a less stable prohibitin complex. Thus, PHB1 and PHB2 may act as molecular target or novel biomarkers for therapeutic intervention in numerous forms of malignancies.

Comprehensive characterization of coding and non-coding single nucleotide polymorphisms of the Myoneurin (MYNN) gene using molecular dynamics simulation and docking approaches

Genome-wide association studies (GWAS) identified a coding single nucleotide polymorphism, MYNN rs10936599, at chromosome 3q. MYNN gene encodes myoneurin protein, which has been associated with several cancer pathogenesis and disease development processes. However, there needed to be a more detailed characterization of this polymorphism's (and other coding and non-coding polymorphisms) structural, functional, and molecular impact. The current study addressed this gap and analyzed different properties of rs10936599 and non-coding SNPs of MYNN via a thorough computational method. The variant, rs10936599, was predicted functionally deleterious by nine functionality prediction approaches, like SIFT, PolyPhen-2, and REVEL, etc. Following that, structural modifications were estimated through the HOPE server and Mutation3D. Moreover, the mutation was found in a conserved and active residue, according to ConSurf and CPORT. Further, the secondary structures were predicted, followed by tertiary structures, and there was a significant deviation between the native and variant models. Similarly, molecular simulation also showed considerable differences in the dynamic pattern of the wildtype and mutant structures. Molecular docking revealed that the variant binds with better docking scores with ligand NOTCH2. In addition to that, non-coding SNPs located at the MYNN locus were retrieved from the ENSEMBL database. These were found to disrupt the transcription factor binding regulatory regions; nonetheless, only two affect miRNA target sites. Again, eight non-coding variants were detected in the testes with normalized expression, whereas HaploReg v4.1 unveiled annotations for non-coding variants. In summary, in silico comprehensive characterization of coding and non-coding single nucleotide polymorphisms of MYNN gene will assist researchers to work on MYNN gene and establish their association with certain types of cancers.

Modes and model building in SHELXE

Density modification is a standard step to provide a route for routine structure solution by any experimental phasing method, with single-wavelength or multi-wavelength anomalous diffraction being the most popular methods, as well as to extend fragments or incomplete models into a full solution. The effect of density modification on the starting maps from either source is illustrated in the case of SHELXE. The different modes in which the program can run are reviewed; these include less well known uses such as reading external phase values and weights or phase distributions encoded in Hendrickson-Lattman coefficients. Typically in SHELXE, initial phases are calculated from experimental data, from a partial model or map, or from a combination of both sources. The initial phase set is improved and extended by density modification and, if the resolution of the data and the type of structure permits, polyalanine tracing. As a feature to systematically eliminate model bias from phases derived from predicted models, the trace can be set to exclude the area occupied by the starting model. The trace now includes an extension into the gamma position or hydrophobic and aromatic side chains if a sequence is provided, which is performed in every tracing cycle. Once a correlation coefficient of over 30% between the structure factors calculated from such a trace and the native data indicates that the structure has been solved, the sequence is docked in all model-building cycles and side chains are fitted if the map supports it. The extensions to the tracing algorithm brought in to provide a complete model are discussed. The improvement in phasing performance is assessed using a set of tests.

Targeting GluR3 in Depression and Alzheimer's Disease: Novel Compounds and Therapeutic Prospects

BACKGROUND

The present study investigates the interrelated pathophysiology of depression and Alzheimer's disease (AD), with the objective of elucidating common underlying mechanisms.

OBJECTIVE

Our objective is to identify previously undiscovered biogenic compounds from the NuBBE database that specifically interact with GluR3. This study examines the bidirectional association between depression and AD, specifically focusing on the role of depression as a risk factor in the onset and progression of the disease.

METHODS

In this study, we utilize pharmacokinetics, homology modeling, and molecular docking-based virtual screening techniques to examine the GluR3 AMPA receptor subunit.

RESULTS

The compounds, namely ZINC000002558953, ZINC000001228056, ZINC000000187911, ZINC000003954487, and ZINC000002040988, exhibited favorable pharmacokinetic profiles and drug-like characteristics, displaying high binding affinities to the GluR3 binding pocket.

CONCLUSIONS

These findings suggest that targeting GluR3 could hold promise for the development of therapies for depression and AD. Further validation through in vitro, in vivo, and clinical studies is necessary to explore the potential of these compounds as lead candidates for potent and selective GluR3 inhibitors. The shared molecular mechanisms between depression and AD provide an opportunity for novel treatment approaches that address both conditions simultaneously.

Design of a novel multi-epitopes vaccine against Escherichia fergusonii: a pan-proteome based in- silico approach

Escherichia fergusonii a gram-negative rod-shaped bacterium in the Enterobacteriaceae family, infect humans, causing serious illnesses such as urinary tract infection, cystitis, biliary tract infection, pneumonia, meningitis, hemolytic uremic syndrome, and death. Initially treatable with penicillin, antibiotic misuse led to evolving resistance, including resistance to colistin, a last-resort drug. With no licensed vaccine, the study aimed to design a multi-epitope vaccine against E. fergusonii. The study started with the retrieval of the complete proteome of all known strains and proceeded to filter the surface exposed virulent proteins. Seventeen virulent proteins (4 extracellular, 4 outer membranes, 9 periplasmic) with desirable physicochemical properties were identified from the complete proteome of known strains. Further, these proteins were processed for B-cell and T-cell epitope mapping. Obtained epitopes were evaluated for antigenicity, allergenicity, solubility, MHC-binding, and toxicity and the filtered epitopes were fused by specific linkers and an adjuvant into a vaccine construct. Structure of the vaccine candidate was predicted and refined resulting in 78.1% amino acids in allowed regions and VERIFY3D score of 81%. Vaccine construct was docked with TLR-4, MHC-I, and MHC-II, showing binding energies of -1040.8 kcal/mol, -871.4 kcal/mol, and -1154.6 kcal/mol and maximum interactions. Further, molecular dynamic simulation of the docked complexes was carried out resulting in a significant stable nature of the docked complexes (high B-factor and deformability values, lower Eigen and high variance values) in terms of intermolecular binding conformation and interactions. The vaccine was also reported to stimulate a variety of immunological pathways after administration. In short, the designed vaccine revealed promising predictions about its immune protective potential against E. fergusonii infections however experimental validation is needed to validate the results.

A glutathione S-transferase and a cytochrome P450 may confer cyhalofop-butyl resistance in Leptochloa chinensis (L.) Nees

BACKGROUND

Leptochloa chinensis (L.) Nees is a troublesome weed across China in rice fields, and a suspected L. chinensis resistant population (R) that has survived the recommended field dose of cyhalofop-butyl was collected in a rice field of Hunan Province, China. In this study, we aimed to determine the acetyl-CoA carboxylase-inhibiting herbicide resistance profile of this R population and to investigate its mechanisms of resistance to cyhalofop-butyl.

RESULTS

Compared with the susceptible population (S), the R population was confirmed to be 18.9-, 3.2-, 4.1-, 3.6- and 5.8- fold resistant to the APP herbicides cyhalofop-butyl, haloxyfop-P-methyl, clodinafop-propargyl, metamifop and fenoxaprop-P-ethyl, respectively. ACCase gene sequencing analysis revealed no known resistance mutations for TSR in the R population. Pretreatment with the glutathione S-transferase (GST) inhibitor 4-chloro-7-nitrobenzoxadiazole (NBD-Cl) and cytochrome P450 (CYP450) inhibitor malathion reversed resistance to cyhalofop-butyl. The GST gene GSTU1 and CYP450 gene CYP707A5 were constitutively upregulated in the R population according to RNA-seq analysis and RT-qPCR verification. The molecular docking results indicated a good affinity of the active site for five APP herbicides with GSTU1 and CYP707A5.

CONCLUSION

This study shows that the GSTU1 and CYP707A5 genes expressed highly in the R population may be responsible for cyhalofop-butyl resistance in L. chinensis.

Disallowed spots in protein structures

Ramachandran (ϕ, ψ) steric map was introduced in 1963 to describe available conformation space for protein structures. Subsequently, residues were observed in high-energy disallowed regions of the map. To unequivocally identify the locations of disallowed conformations of residues, we got 36 noise-free protein structures (resolution ≤1 Å, Rwork/Rfree ≤ 0.10). These stringent criteria were applied to rule out data or model errors or any crystallographic disorders. No disallowed conformation was found in the dataset. Further, we also examined disallowed conformations in a larger dataset (resolution ≤1.5 Å, devoid of any model errors, or disorders). The observed locations of disallowed residues are referred as disallowed spots. These spots include short loops of 3-5 residues, and locations where residues participate in disulfide bonding or intramolecular interactions or inter-molecular interactions with neighboring water, metals or ligands. Conformational sampling revealed that short loops in between secondary structures hardly have any opportunity to relieve from conformational strain. Residues involved in interactions, which provide energetic compensation for high-energy conformational states, were relieved from strain once the causative interaction was removed. The present study aims to identify disallowed spots in the native state of proteins, wherein residues are forced to be trapped in high-energy disallowed conformations. Moreover, it was also observed that pre-Pro, Ser, Asp, trans-Pro, Val, Asn & Gly have higher tendency to occur in disallowed conformation, which could be attributed to factors such as conformational restrictions, residue propensity of secondary structures and compensating sidechain and mainchain interactions, stabilizing turn-mimics.

A novel therapeutic approach to prevent Helicobacter pylori induced gastric cancer using networking biology, molecular docking, and simulation approaches

Helicobacter pylori infects 50% of the world population and in 80% of cases, the infection progresses to the point where an ulcer develops leading to gastric cancer (GC). This study aimed to prevent GC by predicting Hub genes that are inducing GC. Furthermore, the study objective was to screen inhibitory molecules that block the function of predicted genes through several biophysical approaches. These proteins, such as Mucin 4 (MUC4) and Baculoviral IAP repeat containing 3 (BIRC3), had LogFC values of 2.28 and 3.39, respectively, and were found to be substantially expressed in those who had H. pylori infection. The MUC4 and BIRC3 inhibit apoptosis of infected cells and promote cancerous cell survival. The proteins were examined for their Physico-chemical characteristics, 3D structure and secondary structure analysis, solvent assessable surface area (SASA), active site identification, and network analysis. The MUC4 and BIRC3 expression was inhibited by docking eighty different compounds collected from the ZINC database. Fifty-seven compounds were successfully docked into the active site resulting in the lowest binding energy scores. The ZINC585267910 and ZINC585268691 compounds showed the lowest binding energy of -8.5 kcal/mol for MUC4 and -7.1 kcal/mol for BIRC3, respectively, and were considered best-docked solutions for molecular dynamics simulations. The mean root mean square deviation (RMSD) value for the ZINC585267910-MUC4 complex was 0.86 Å and the ZINC585268691-BIRC3 complex was 1.01 Å. The net MM/GBSA energy value of the ZINC585267910-MUC4 complex estimated was -46.84 kcal/mol and that of the ZINC585268691-BIRC3 complex was -44.84 kcal/mol. In a nutshell, the compounds might be investigated further as an inhibitor of the said proteins to stop the progress of GC induced by H. pylori.Communicated by Ramaswamy H. Sarma.

Underpinning Endogeneous Damp EDA-Fibronectin in the Activation of Molecular Targets of Rheumatoid Arthritis and Identifcation of its Effective Inhibitors by Computational Methods

Rheumatoid arthritis (RA) is one of the most severe inflammatory diseases that cause swelling, stiffness and pain in the joints, which pose a significant threat worldwide. Damage-associated molecular patterns (DAMPs) are danger molecules of endogenous origin, released during cell injury or cell death, interacts with various Pattern recognition receptors (PRRs) and activates various inflammatory diseases. One of the DAMP molecules, so-called EDA-fibronectin (Fn) is also responsible for causing RA. EDA-Fn triggers RA through its interaction with TLR4. Apart from TLR4, it is divulged that certain other PRR's are also responsible for RA, but the identity and mechanism of those PRRs remain unknown until now. Hence, for the first time, we tried to reveal those PRR's interaction with EDA-Fn in RA through computational methods. Protein-protein interaction (PPI) was checked using ClusPro between EDA-Fn and certain Pattern recognition receptors (PRRs) to explore the binding affinities of the potential PRRs. Protein-protein docking unveiled that TLR5, TLR2 and RAGE has good interaction with EDA-Fn than the well-reported TLR4. Macromolecular simulation was performed for TLR5, TLR2 and RAGE complexes along with the control group TLR4 for 50 ns to further investigate the stability, leading to the identification of TLR2, TLR5 and RAGE as the stable complexes. Hence, TLR2, TLR5 and RAGE on interaction with EDA-Fn may lead to the progression of RA that may need additional validations through in vitro and in vivo animal models. Molecular docking was used to analyse the binding force of the top 33 active anti-arthritic compounds with the target protein EDA-Fn. Molecular docking study showed that withaferin A has a good binding activity with EDA-fibronectin target. Hence, it is emphasized that guggulsterone and berberine could modulate the EDA-Fn-mediated TLR5/TLR2/RAGE pathways, thereby it could inhibit the deteriorating effects of RA which needs further in vitro and in vivo experimental validations.

Identification of apposite antagonist for androgen receptor in prostate cancer: an in silico study of fenugreek compounds

Benign Prostate Cancer (BPC), a prevalent condition predominantly affecting elderly males, manifests with voiding difficulties and urinary retention. A library of compounds from Trigonella foenum-graecum, commonly known as fenugreek was used in this study. We aimed to explore its potential anti-cancer effects by computationally assessing its inhibitory activity on the androgen receptor (AR). For in-silico drug assessment, we employed Maestro 12.8, part of the Schrödinger Suite, to identify the most promising candidates acting as androgen receptor antagonists in the treatment of BPC. Subsequently, 59 fenugreek compounds were retrieved from the PubChem database and subjected to molecular docking against the active site of the target protein, 1E3G. 100-nanosecond molecular dynamics (MD) simulations were performed to assess the stability and compactness of the AR-ligand complexes. Notably, the AR-kaempferol complex exhibited the least fluctuation within the AR active site throughout the simulation trajectory, followed by chlorogenic acid and the reference ligand, hydroxyflutamide. The MM/GBSA values revealed the compounds' maximum free binding energy (-103.3 ± 6, -87.4 ± 23, -68.5 ΔGbind) for chlorogenic acid, kaempferol, and hydroxyflutamide, respectively. These findings suggest their potential as promising leads for drug development. Further lead optimization and comprehensive studies on the top-ranked ligands identified in this investigation are warranted to advance their potential as therapeutic agents for BPC treatment.Communicated by Ramaswamy H. Sarma.

Predicting 3D RNA structure from the nucleotide sequence using Euclidean neural networks

Fast and accurate 3D RNA structure prediction remains a major challenge in structural biology, mostly due to the size and flexibility of RNA molecules, as well as the lack of diverse experimentally determined structures of RNA molecules. Unlike DNA structure, RNA structure is far less constrained by basepair hydrogen bonding, resulting in an explosion of potential stable states. Here, we propose a convolutional neural network that predicts all pairwise distances between residues in an RNA, using a recently described smooth parametrization of Euclidean distance matrices. We achieve high-accuracy predictions on RNAs up to 100 nt in length in fractions of a second, a factor of 107 faster than existing molecular dynamics-based methods. We also convert our coarse-grained machine learning output into an all-atom model using discrete molecular dynamics with constraints. Our proposed computational pipeline predicts all-atom RNA models solely from the nucleotide sequence. However, this method suffers from the same limitation as nucleic acid molecular dynamics: the scarcity of available RNA crystal structures for training.

Nanoscale insights into the local structural rearrangements of amyloid-β induced by bexarotene

A better understanding of the abnormal protein aggregation and the effect of anti-aggregation agents on the fibrillation pathways and the secondary structure of aggregates can determine strategies for the early treatment of dementia. Herein, we present a combination of experimental and theoretical studies providing new insights into the influence of the anti-aggregation drug bexarotene on the secondary structure of individual amyloid-β aggregates and its primary aggregation. The molecular rearrangements and the spatial distribution of β-sheets within individual aggregates were monitored at the nanoscale with infrared nanospectroscopy. We observed that bexarotene limits the parallel β-sheets formation, known to be highly abundant in fibrils at later phases of the amyloid-β aggregation composed of in-register cross-β structure. Moreover, we applied molecular dynamics to provide molecular-level insights into the investigated system. Both theoretical and experimental results revealed that bexarotene slows down the protein aggregation process via steric effects, largely prohibiting the antiparallel to parallel β-sheet rearrangement. We also found that bexarotene interacts not only via the single hydrogen bond formation with the peptide backbone but also with the amino acid side residue via a hydrophobic effect. The studied model of the drug-amyloid-β interaction contributes to a better understanding of the inhibition mechanism of the amyloid-β aggregation by the small molecule drugs. However, our nanoscale findings need to meet in vivo research requiring different analytical approaches.

Improving Geometric Validation Metrics and Ensuring Consistency with Experimental Data through TrioSA: An NMR Refinement Protocol

Protein model refinement a the crucial step in improving the quality of a predicted protein model. This study presents an NMR refinement protocol called TrioSA (torsion-angle and implicit-solvation-optimized simulated annealing) that improves the accuracy of backbone/side-chain conformations and the overall structural quality of proteins. TrioSA was applied to a subset of 3752 solution NMR protein structures accompanied by experimental NMR data: distance and dihedral angle restraints. We compared the initial NMR structures with the TrioSA-refined structures and found significant improvements in structural quality. In particular, we observed a reduction in both the maximum and number of NOE (nuclear Overhauser effect) violations, indicating better agreement with experimental NMR data. TrioSA improved geometric validation metrics of NMR protein structure, including backbone accuracy and the secondary structure ratio. We evaluated the contribution of each refinement element and found that the torsional angle potential played a significant role in improving the geometric validation metrics. In addition, we investigated protein-ligand docking to determine if TrioSA can improve biological outcomes. TrioSA structures exhibited better binding prediction compared to the initial NMR structures. This study suggests that further development and research in computational refinement methods could improve biomolecular NMR structural determination.

Comparison, Analysis, and Molecular Dynamics Simulations of Structures of a Viral Protein Modeled Using Various Computational Tools

The structural analysis of proteins is a major domain of biomedical research. Such analysis requires resolved three-dimensional structures of proteins. Advancements in computer technology have led to progress in biomedical research. In silico prediction and modeling approaches have facilitated the construction of protein structures, with or without structural templates. In this study, we used three neural network-based de novo modeling approaches-AlphaFold2 (AF2), Robetta-RoseTTAFold (Robetta), and transform-restrained Rosetta (trRosetta)-and two template-based tools-the Molecular Operating Environment (MOE) and iterative threading assembly refinement (I-TASSER)-to construct the structure of a viral capsid protein, hepatitis C virus core protein (HCVcp), whose structure have not been fully resolved by laboratory techniques. Templates with sufficient sequence identity for the homology modeling of complete HCVcp are currently unavailable. Therefore, we performed domain-based homology modeling for MOE simulations. The templates for each domain were obtained through sequence-based searches on NCBI and the Protein Data Bank. Then, the modeled domains were assembled to construct the complete structure of HCVcp. The full-length structure and two truncated forms modeled using various computational tools were compared. Molecular dynamics (MD) simulations were performed to refine the structures. The root mean square deviation of backbone atoms, root mean square fluctuation of Cα atoms, and radius of gyration were calculated to monitor structural changes and convergence in the simulations. The model quality was evaluated through ERRAT and phi-psi plot analysis. In terms of the initial prediction for protein modeling, Robetta and trRosetta outperformed AF2. Regarding template-based tools, MOE outperformed I-TASSER. MD simulations resulted in compactly folded protein structures, which were of good quality and theoretically accurate. Thus, the predicted structures of certain proteins must be refined to obtain reliable structural models. MD simulation is a promising tool for this purpose.

New insights into the protein stabilizing effects of trehalose by comparing with sucrose

Disaccharides are well known to be efficient stabilizers of proteins, for example in the case of lyophilization or cryopreservation. However, although all disaccharides seem to exhibit bioprotective and stabilizing properties, it is clear that trehalose is generally superior compared to other disaccharides. The aim of this study was to understand this by comparing how the structural and dynamical properties of aqueous trehalose and sucrose solutions influence the protein myoglobin (Mb). The structural studies were based on neutron and X-ray diffraction in combination with empirical potential structure refinement (EPSR) modeling, whereas the dynamical studies were based on quasielastic neutron scattering (QENS) and molecular dynamics (MD) simulations. The results show that the overall differences in the structure and dynamics of the two systems are small, but nevertheless there are some important differences which may explain the superior stabilizing effects of trehalose. It was found that in both systems the protein is preferentially hydrated by water, but that this effect is more pronounced for trehalose, i.e. trehalose forms less hydrogen bonds to the protein surface than sucrose. Furthermore, the rotational motion around dihedrals between the two glucose rings of trehalose is slower than in the case of the dihedrals between the glucose and fructose rings of sucrose. This leads to a less perturbed protein structure in the case of trehalose. The observations indicate that an aqueous environment closest to the protein molecules is beneficial for an efficient bioprotective solution.

Anti-quorum sensing potential of selenium nanoparticles against LasI/R, RhlI/R, and PQS/MvfR in Pseudomonas aeruginosa: a molecular docking approach

Pseudomonas aeruginosa is an infectious pathogen which has the ability to cause primary and secondary contagions in the blood, lungs, and other body parts of immunosuppressed individuals, as well as community-acquired diseases, such as folliculitis, osteomyelitis, pneumonia, and others. This opportunistic bacterium displays drug resistance and regulates its pathogenicity via the quorum sensing (QS) mechanism, which includes the LasI/R, RhlI/R, and PQS/MvfR systems. Targeting the QS systems might be an excellent way to treat P. aeruginosa infections. Although a wide array of antibiotics, namely, newer penicillins, cephalosporins, and combination drugs are being used, the use of selenium nanoparticles (SeNPs) to cure P. aeruginosa infections is extremely rare as their mechanistic interactions are weakly understood, which results in carrying out this study. The present study demonstrates a computational approach of binding the interaction pattern between SeNPs and the QS signaling proteins in P. aeruginosa, utilizing multiple bioinformatics approaches. The computational investigation revealed that SeNPs were acutely 'locked' into the active region of the relevant proteins by the abundant residues in their surroundings. The PatchDock-based molecular docking analysis evidently indicated the strong and significant interaction between SeNPs and the catalytic cleft of LasI synthase (Phe105-Se = 2.7 Å and Thr121-Se = 3.8 Å), RhlI synthase (Leu102-Se = 3.7 Å and Val138-Se = 3.2 Å), transcriptional receptor protein LasR (Lys42-Se = 3.9 Å, Arg122-Se = 3.2 Å, and Glu124-Se = 3.9 Å), RhlR (Tyr43-Se = 2.9 Å, Tyr45-Se = 3.4 Å, and His61-Se = 3.5 Å), and MvfR (Leu208-Se = 3.2 Å and Arg209-Se = 4.0 Å). The production of acyl homoserine lactones (AHLs) was inhibited by the use of SeNPs, thereby preventing QS as well. Obstructing the binding affinity of transcriptional regulatory proteins may cause the suppression of LasR, RhlR, and MvfR systems to become inactive, thereby blocking the activation of QS-regulated virulence factors along with their associated gene expression. Our findings clearly showed that SeNPs have anti-QS properties against the established QS systems of P. aeruginosa, which strongly advocated that SeNPs might be a potent solution to tackle drug resistance and a viable alternative to conventional antibiotics along with being helpful in therapeutic development to cure P. aeruginosa infections.

Discovery of Multitarget-Directed Ligands from Piperidine Alkaloid Piperine as a Cap Group for the Management of Alzheimer's Disease

The naturally inspired multitarget-directed ligands (PC01-PC10 and PD01-PD26) were synthesized from piperine for the management of Alzheimer's disease (AD). The compound PD07 showed significant inhibitory activity on ChEs, BACE1, and Aβ1-42 aggregation in in vitro studies. Further, compound PD07 effectively displaced the propidium iodide at the AChE PAS site. The compound PD07 exhibited significant lipophilicity in PAMPA studies. Additionally, PD07 demonstrated neuroprotective properties in the Aβ1-42 induced SH-SY5Y cell line. Furthermore, DFT calculations were performed using B3LYP/6-311G(d,p) basis sets to explore the PD07 physical and chemical properties. The compound PD07 showed a similar binding interaction profile at active sites of AChE, BuChE, and BACE1 proteins as compared to reference ligands (donepezil, tacrine, and BSD) in molecular docking and dynamic simulation studies. In acute oral toxicity studies, compound PD07 exhibited no toxicity symptoms up to 300 mg/kg, po. The compound PD07 (10 mg/kg, po) improved memory and cognition in scopolamine-induced amnesia rats. Further, PD07 increased ACh levels in the brain by inhibiting the AChE activity. The results from in vitro, in silico, and in vivo studies suggested that compound PD07 is a potent multitarget-directed lead from piperine to overcome Alzheimer's disease.

Intrinsic proclivity of left-handed conformation in large Nest motif peptides inferred from molecular dynamics

The 'Nest' motif plays a functional role in protein owing to its ligand binding potential aided by geometric concavity. The presence of less favored left-handed conformation (L-state) in its structure makes this concavity possible and in shaping the native chemical environment amenable to stable binding interactions. To understand the persistent appearance of L-state torsion in the Nest motif, we analyzed 0.5μs Molecular Dynamics (MD) simulation trajectories of 35 six-residue peptides (out of a total of 50 large Nest sequences of ≥6 residues) identified in our previous study. Analysis of the MD trajectories of the individual peptides reveals initial L-state in 60% of the peptides persists for >40% of the trajectory. Further, Nests with different sequences appear to adopt a specific conformational state driven by the neighboring L-state residues. The sequences also possess short secondary structures and amino acid repeats, suggesting evolutionary conservation and the specific role of amino acids in locally predisposing the torsion angle to the L-state. These findings help us to understand how L-state conformation is an essential prerequisite in stabilizing the Nest motif and shed light on the sequence-structure-function paradigm in the rational design of peptides and peptidomimetics for therapeutics.Communicated by Ramaswamy H. Sarma.

Genome-wide identification and comparative in-silico characterization of β-galactosidase (GH-35) in ascomycetes and its role in germ tube development of Aspergillus fumigatus via RNA-seq analysis

β-galactosidase (Lactase), an enzyme belonging to the glycoside hydrolase family causing the hydrolysis and trans-glycosylation of β-D-galactosides, has a vital role in dairy industries. The current investigation emphasizes on in-silico identification and comparative analysis of different fungal lactases present in Aspergillus fumigatus, Aspergillus oryzae, Botrytis cinerea, and Fusarium fujikuroi. Prediction of motifs and domains, chromosomal positioning, gene structure, gene ontology, sub-cellular localization and protein modeling were performed using different bioinformatics tools to have an insight into the structural and functional characteristics of β-galactosidases. Evolutionary and homology relationships were established by phylogenetic and synteny analyses. A total of 14 β-gal genes (GH-35) were identified in these species. Identified lactases, having 5 domains, were predicted to be stable, acidic, non-polar and extracellularly localized with roles in polysaccharide catabolic process. Results showed variable exonic/intronic ratios of the gene structures which were randomly positioned on chromosomes. Moreover, synteny blocks and close evolutionary relationships were observed between Aspergillus fumigatus and Aspergillus oryzae. Structural insights allowed the prediction of best protein models based on the higher ERRAT and Q-MEAN values. And RNA-sequencing analysis, performed on A. fumigatus, elucidated the role of β-gal in germ tube development. This study would pave the way for efficient fungal lactase production as it identified β-gal genes and predicted their various features and also it would provide a road-way to further the understanding of A. fumigatus pathogenicity via the expression insights of β-gal in germ tube development.

Teraryl Braces in Macrocycles: Synthesis and Conformational Landscape Remodeling of Peptides

The three-dimensional structure of medium-sized cyclic peptides accounts for their biological activity and other important physiochemical properties. Despite significant advances in the past few decades, chemists' ability to fine-tune the structure, in particular, the backbone conformation, of short peptides made of canonical amino acids is still quite limited. Nature has shown that cross-linking the aromatic side chains of linear peptide precursors via enzyme catalysis can generate cyclophane-braced products with unusual structures and diverse activities. However, the biosynthetic path to these natural products is challenging to replicate in the synthetic laboratory using practical chemical modifications of peptides. Herein, we report a broadly applicable strategy to remodel the structure of homodetic peptides by cross-linking the aromatic side chains of Trp, His, and Tyr residues with various aryl linkers. The aryl linkers can be easily installed via copper-catalyzed double heteroatom-arylation reactions of peptides with aryl diiodides. These aromatic side chains and aryl linkers can be combined to form a large variety of assemblies of heteroatom-linked multi-aryl units. The assemblies can serve as tension-bearable multijoint braces to modulate the backbone conformation of peptides as an entry to previously inaccessible conformational space.

Peptides of a Feather: How Computation Is Taking Peptide Therapeutics under Its Wing

Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of in-silico peptide design involves the application of molecular docking, molecular dynamics simulations, and machine learning algorithms. Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.

Molecular dynamics-based structural insights of the first putative endoglucanase, PsGH5A of glycoside hydrolase family 5 from Pseudopedobacter saltans

CONTEXT

The putative endoglucanase, PsGH5A, from Pseudopedobacter saltans of family GH5 contains a catalytic module, PsGH5 (β/α)₈-TIM barrel), at N-terminal followed by a family 6 carbohydrate-binding module (CBM6, β-sandwich). Superposition of PsGH5A with PDB homologs revealed Glu220 and Glu318 as evolutionarily conserved and catalytic residues performing the hydrolysis through retaining-type mechanism, a canonical property of GH5 family. PsGH5A showed higher affinity for longer cellooligosaccharides, as long as cellodecaose with binding free energy (∆G) of - 13.72 kcal/mol upon the molecular docking, thereby indicating the endo-mode of hydrolysis. The radius of gyration, Rg (2.7 nm), and solvent accessible surface area, SASA (229.6 nm²), of PsGH5A-Cellotetraose complex were determined by MD simulation which was lower than that of PsGH5A (Rg, 2.8 nm, SASA, 267 nm²) demonstrating the compactness and affinity of PsGH5A with the cellulosic ligands. Cellulose compatibility of PsGH5A was further confirmed by MMPBSA and per-residue decomposition analysis, where notable ∆G of - 54.38 kcal/mol for PsGH5A-Cellotetraose complex was observed. Thus, PsGH5A could be potentially an efficient endoglucanase as it accommodated larger cellooligosaccharides at its active-site. PsGH5A is the first putative endoglucanase studied here from P. saltans which could be genome-mined for lignocellulosic biomass saccharification in the renewable energy sector.

METHODS

The 3-D structure of PsGH5A generated by AlphaFold2, RaptorX, SwissModel, Phyre2 and Robetta tool; YASARA was used for energy minimization of built models. UCLA SAVES-v6 was used for quality assessment of models. Molecular Docking was performed using SWISS-DOCK server and Chimera software. Molecular Dynamics simulations and MMPBSA analysis of PsGH5A and PsGH5A-Cellotetraose complex were performed on GROMACS 2019.6.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.

A class of peptides designed to replicate and enhance the Receptor for Hyaluronic Acid Mediated Motility binding domain

The extra-cellular matrix (ECM) is a complex and rich microenvironment that is exposed and over-expressed across several injury or disease pathologies. Biomaterial therapeutics are often enriched with peptide binders to target the ECM with greater specificity. Hyaluronic acid (HA) is a major component of the ECM, yet to date, few HA adherent peptides have been discovered. A class of HA binding peptides was designed using B(X₇)B hyaluronic acid binding domains inspired from the helical face of the Receptor for Hyaluronic Acid Mediated Motility (RHAMM). These peptides were bioengineered using a custom alpha helical net method, allowing for the enrichment of multiple B(X₇)B domains and the optimisation of contiguous and non-contiguous domain orientations. Unexpectedly, the molecules also exhibited the behaviour of nanofiber forming self-assembling peptides and were investigated for this characteristic. Ten 23-27 amino acid residue peptides were assessed. Simple molecular modelling was used to depict helical secondary structures. Binding assays were performed with varying concentrations (1-10 mg/mL) and extra-cellular matrices (HA, collagens I-IV, elastin, and Geltrex). Concentration mediated secondary structures were assessed using circular dichroism (CD), and higher order nanostructures were visualized using transmission electron microscopy (TEM). All peptides formed the initial apparent 3₁₀/alpha-helices, yet peptides 17x-3, 4, BHP3 and BHP4 were HA specific and potent (i.e., a significant effect) binders at increasing concentrations. These peptides shifted from apparent 3₁₀/alpha-helical structures at low concentration to beta-sheets at increasing concentration and also formed nanofibers which are noted as self-assembling structures. Several of the HA binding peptides outperformed our positive control (mPEP35) at 3-4 times higher concentrations, and were enhanced by self-assembly as each of these groups had observable nanofibers. STATEMENT OF SIGNIFICANCE: Specific biomolecules or peptides have played a crucial role in developing materials or systems to deliver key drugs and therapeutics to a broad spectrum of diseases and disorders. In these diseased tissues, cells build protein/sugar networks, which are uniquely exposed and great targets to deliver drugs to. Hyaluronic acid (HA) is involved in every stage of injury and is abundant in cancer. To date, only two HA specific peptides have been discovered. In our work, we have designed a way to model and trace binding regions as they appear on the face of a helical peptide. Using this method we have created a family of peptides enriched with HA binding domains that stick with 3-4 higher affinity than those previously discovered.

Conformational ensembles explain NMR spectra of frozen intrinsically disordered proteins

Protein regions which are intrinsically disordered, exist as an ensemble of rapidly interconverting structures. Cooling proteins to cryogenic temperatures for dynamic nuclear polarization (DNP) magic angle spinning (MAS) NMR studies suspends most of the motions, resulting in peaks that are broad but not featureless. To demonstrate that detailed conformational restraints can be retrieved from the peak shapes of frozen proteins alone, we developed and used a simulation framework to assign peak features to conformers in the ensemble. We validated our simulations by comparing them to spectra of α-synuclein acquired under different experimental conditions. Our assignments of peaks to discrete dihedral angle populations suggest that structural constraints are attainable under cryogenic conditions. The ability to infer ensemble populations from peak shapes has important implications for DNP MAS NMR studies of proteins with regions of disorder in living cells because chemical shifts are the most accessible measured parameter.

Stretching Peptides to Generate Small Molecule β-Strand Mimics

Advances in the modulation of protein-protein interactions (PPIs) enable both characterization of PPI networks that govern diseases and design of therapeutics and probes. The shallow protein surfaces that dominate PPIs are challenging to target using standard methods, and approaches for accessing extended backbone structures are limited. Here, we incorporate a rigid, linear, diyne brace between side chains at the i to i+2 positions to generate a family of low-molecular-weight, extended-backbone peptide macrocycles. NMR and density functional theory studies show that these stretched peptides adopt stable, rigid conformations in solution and can be tuned to explore extended peptide conformational space. The diyne brace is formed in excellent conversions (>95%) and amenable to high-throughput synthesis. The minimalist structure-inducing tripeptide core (<300 Da) is amenable to further synthetic elaboration. Diyne-braced inhibitors of bacterial type 1 signal peptidase demonstrate the utility of the technique.

The comparison between zein-anthocyanins complex and nanoparticle systems: Stability enhancement, interaction mechanism, and in silico approaches

This research aimed to compare and characterize the physicochemical properties and interaction mechanism of zein and anthocyanins (ACNs) from experimental and theoretical perspectives. Zein-ACNs complex (ZACP) was prepared by mixing ACNs with different concentrations of zein, and zein-ACNs nanoparticles (ZANPs) were formed using ultrasound-assisted antisolvent precipitation method. The hydrated particle sizes of the two systems were 590.83 nm and 99.86 nm, respectively, and observed to be spherical under transmission electron microscopy (TEM). The multi-spectroscopy approaches confirmed hydrogen bonding and hydrophobic forces were the dominant forces for stabilizing ACNs. The retention of ACNs, color stability and antioxidant activities were also improved in both systems. Furthermore, molecular simulation results were consistent with the multi-spectroscopy findings, which clarified the contribution of van der Waals forces to the binding of zein and ACNs. This study provided a practical approach for stabilizing ACNs and expanding the utilization of plant proteins as stabilization systems.

Characterization, protein modeling, and molecular docking of factor C from Indonesian horseshoe crab (Tachypleus gigas)

BACKGROUND

Horseshoe crab (Tachypleus gigas) amebocytes are useful biomedical components for endotoxin detection, and their growing needs for biomedical purposes cause the horseshoe crab population to decline. Factor C synthesis via genetic engineering offers a solution to replace natural horseshoe crab's factor C and prevent its excessive harvest from nature. In response to these concerns, this study aimed to characterize the amebocyte lysates and factor C protein modeling of T. gigas originated from Banyuasin South Sumatra Estuary.

METHODS AND RESULTS

Sampling of T. gigas was carried out in Banyuasin South Sumatra Estuary, Indonesia. The endotoxin test or TAL (Tachypleus amebocyte lysates) assay was performed using gel coagulation method. Protein characterization of protease enzyme was conducted by protease activity, SDS-PAGE, and zymogram analysis. The cDNA of mitochondrial COI gene was amplified for molecular identification followed by cDNA cloning of factor C. Protein modeling was investigated by molecular docking and molecular dynamic (MD) simulation. Endotoxin test results showed that TAL-35 had endotoxin sensitivity in a range of 0.0156-1 EU/ml, while TAL 36 had a sensitivity between 00,625 and 1 EU/ml. T. gigas amebocytes have protease activity in molecular mass sizes less than 60 kDa, with 367 U/ml for TAL 35 and 430 U/ml for TAL 36. The molecular identification revealed 98.68% identity similarity to T. gigas. The docking results suggested three ligands; i.e., diphosphoryl lipid A, core lipid A, and Kdo2 lipid A can be activators of the factor C protein by binding to the region of the receptor to form a ligand-receptor complex.

CONCLUSIONS

Endotoxins can be detected using horseshoe crab amebocytes. The presence of proteases is considered responsible for this ability, as evidenced by casein zymogram results. According to docking and MD analysis, we found that lipopolysaccharides (LPS) participate to the binding site of factor C.

Anti-Fungal Potential of Structurally Diverse FDA-Approved Therapeutics Targeting Secreted Aspartyl Proteinase (SAP) of Candida albicans: an In Silico Drug Repurposing Approach

In recent years, candidiasis attains major clinical importance due to its unique pathogenic strategy, which distinguishes it from other nosocomial infections. Secreted aspartyl proteinases (SAPs) is a hydrolytic enzyme secreted by Candida species that mediate versatile biological activity including hyphal formation, adherence, biofilm formation, phenotypic adaptation, etc. Emerging clinical evidence strongly suggested that conventional anti-fungal agent's are often prone to high level of resistance upon repeated exposure. Drug repurposing is an ideal strategy that shall impose the additional clinical benefits of the already approved molecules. Hence, through this realistic pathway, the potential of the suitable lead candidates will be explored in order to prolong the life span of existing molecules thereby need for newer therapeutics shall be avoided. The main aim of the present investigation is to determine the enzyme inhibitory potential of certain FDA-approved antibiotics and to validate its efficacy against the virulent enzyme secreted aspartyl proteinase (SAP) of Candida albicans via the AutoDock simulation program. The outcome of in silico dynamic simulations depicts that the drugs such as gentamicin, clindamycin, meropenem, metronidazole, and aztreonam emphasize superior binding affinity in terms of demonstrating considerable interaction with the core catalytic residues (Asp 32, Asp86, Asp 218, Gly220, Thr 221, and Thr 222). Data further indicates that the drug gentamicin exhibited best binding affinity of - 14.16 kcal/mol followed by meropenem (- 9.20 kcal/mol), clindamycin (- 9.00 kcal/mol), ciprofloxacin (- 8.95 kcal/mol), and imipenem (- 8.00 kcal/mol). In conclusion, repurposed antibiotics like gentamicin, clindamycin, meropenem, metronidazole, and aztreonam shall be considered an alternate drug of choice for the clinical management of drug resistant candida infections in the near future.

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

Immunoinformatics Study: Multi-Epitope Based Vaccine Design from SARS-CoV-2 Spike Glycoprotein

The coronavirus disease 2019 outbreak has become a huge challenge in the human sector for the past two years. The coronavirus is capable of mutating at a higher rate than other viruses. Thus, an approach for creating an effective vaccine is still needed to induce antibodies against multiple variants with lower side effects. Currently, there is a lack of research on designing a multiepitope of the COVID-19 spike protein for the Indonesian population with comprehensive immunoinformatic analysis. Therefore, this study aimed to design a multiepitope-based vaccine for the Indonesian population using an immunoinformatic approach. This study was conducted using the SARS-CoV-2 spike glycoprotein sequences from Indonesia that were retrieved from the GISAID database. Three SARS-CoV-2 sequences, with IDs of EIJK-61453, UGM0002, and B.1.1.7 were selected. The CD8+ cytotoxic T-cell lymphocyte (CTL) epitope, CD4+ helper T lymphocyte (HTL) epitope, B-cell epitope, and IFN-γ production were predicted. After modeling the vaccines, molecular docking, molecular dynamics, in silico immune simulations, and plasmid vector design were performed. The designed vaccine is antigenic, non-allergenic, non-toxic, capable of inducing IFN-γ with a population reach of 86.29% in Indonesia, and has good stability during molecular dynamics and immune simulation. Hence, this vaccine model is recommended to be investigated for further study.

Evaluation of the Antioxidant Properties of Carvacrol as a Prospective Replacement for Crude Essential Oils and Synthetic Antioxidants in Food Storage

The phenolic structural analogues of synthetic antioxidants such as butylated hydroxytoluene (BHT) in essential oils have been reported to exhibit antioxidant properties. Additionally, their lipophilicity makes them suitable for use in lipid-rich foods. This study evaluated the antioxidant capacity of carvacrol, a monoterpenoid antioxidant compound in the Monodora myristica (Gaertn.) seed essential oil, compared to the seed essential oil and BHT. In vitro studies (ferric reducing antioxidant power (FRAP), metal chelating activity (MCA), and nitric oxide scavenging activity (NOSA)) were conducted to ascertain if the antioxidant capacity of carvacrol was comparable to that of the seed essential oil. The potential binding affinity and molecular interactions between carvacrol and lipoxygenase (LOX) and its homologous model were investigated in silico. The molecular docking was performed using Autodock Vina, and the best poses were subjected to molecular dynamics simulation. The IC₅₀ for MCA and NOSA were: carvacrol 50.29 µL/mL, seed essential oil (SEO) 71.06 µL/mL; and carvacrol 127.61 µL/mL, SEO 165.18 µL/mL, respectively. The LOX model was Ramachandran favoured (97.75%) and the overall quality factor in the ERRAT plot was 95.392. The results of the molecular docking and molecular dynamics simulations revealed that lipoxygenase has a higher affinity (-22.79 kcal/mol) for carvacrol compared to BHT. In the LOX-BHT and LOX-carvacrol complexes, the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and the radius of gyration (RoG) were not significantly different, indicating similar molecular interactions. The results obtained from this study suggest that carvacrol exhibits an antioxidant capacity that may be explored as an alternative for crude essential oils and synthetic compounds during the storage of lipid-rich foods.

Non-covalent interactions reveal the protein chain δ conformation in a flexible single-residue model

The δ conformation is a local secondary structure in proteins that implicates a π_amide N-H⋯N interaction between a backbone N atom and the NH of the following residue. Small-molecule models thereof have been limited so far to rigid proline-type compounds. We show here that in derivatives of a cyclic amino acid with a sulphur atom in the γ-position, specific side-chain/backbone N-H⋯S interactions stabilize the δ conformation sufficiently to allow it to compete with classical C5 and C7 H-bonded conformers.

In silico investigation of uncoupling protein function in avian genomes

Introduction

The uncoupling proteins (UCPs) are involved in lipid metabolism and belong to a family of mitochondrial anionic transporters. In poultry, only one UCP homologue has been identified and experimentally shown to be associated with growth, feed conversion ratio, and abdominal fat according to its predominant expression in bird muscles. In endotherm birds, cell metabolic efficiency can be tuned by the rate of mitochondrial coupling. Thus, avUCP may be a key contributor to controlling metabolic rate during particular environmental changes.

Methods

This study aimed to perform a set of in-silico investigations primarily focused on the structural, biological, and biomimetic functions of avUCP. Thereby, using in silico genome analyses among 8 avian species (chicken, turkey, swallow, manakin, sparrow, wagtail, pigeon, and mallard) and a series of bioinformatic approaches, we provide phylogenetic inference and comparative genomics of avUCPs and investigate whether sequence variation can alter coding sequence characteristics, the protein structure, and its biological features. Complementarily, a combination of literature mining and prediction approaches was also applied to predict the gene networks of avUCP to identify genes, pathways, and biological crosstalk associated with avUCP function.

Results

The results showed the evolutionary alteration of UCP proteins in different avian species. Uncoupling proteins in avian species are highly conserved trans membrane proteins as seen by sequence alignment, physio-chemical parameters, and predicted protein structures. Taken together, avUCP has the potential to be considered a functional marker for the identification of cell metabolic state, thermogenesis, and oxidative stress caused by cold, heat, fasting, transfer, and other chemical stimuli stresses in birds. It can also be deduced that avUCP, in migrant or domestic birds, may increase heat stress resistance by reducing fatty acid transport/b-oxidation and thermoregulation alongside antioxidant defense mechanisms. The predicted gene network for avUCP highlighted a cluster of 21 genes involved in response to stress and 28 genes related to lipid metabolism and the proton buffering system. Finally, among 11 enriched pathways, crosstalk of 5 signaling pathways including MAPK, adipocytokine, mTOR, insulin, ErbB, and GnRH was predicted, indicating a possible combination of positive or negative feedback among pathways to regulate avUCP functions.

Discussion

Genetic selection for fast-growing commercial poultry has unintentionally increased susceptibility to many kinds of oxidative stress, and so avUCP could be considered as a potential candidate gene for balancing energy expenditure and reactive oxygen species production, especially in breeding programs. In conclusion, avUCP can be introduced as a pleiotropic gene that requires the contribution of regulatory genes, hormones, pathways, and genetic crosstalk to allow its finely-tuned function.

Molecular Insights into the Calcium Binding in Troponin C through a Molecular Dynamics Study

Calcium-binding proteins play critical roles in various biological processes such as signal transduction, cell growth, and transcription factor regulation. Ion binding and target binding of Ca²⁺-binding proteins are highly related. Therefore, understanding the ion binding mechanism will benefit the relevant inhibitor design toward the Ca²⁺-binding proteins. The EF-hand is the typical ion binding motif in Ca²⁺-binding proteins. Previous studies indicate that the ion binding affinity of the EF-hand increases with the peptide length, but this mechanism has not been fully understood. Herein, using molecular dynamics simulations, thermodynamic integration calculations, and molecular mechanics Poisson-Boltzmann surface area analysis, we systematically investigated four Ca²⁺-binding peptides containing the EF-hand loop in site III of rabbit skeletal troponin C. These four peptides have 13, 21, 26, and 34 residues. Our simulations reproduced the observed trend that the ion binding affinity increases with the peptide length. Our results implied that the E-helix motif preceding the EF-hand loop, likely the Phe99 residue in particular, plays a significant role in this regulation. The E-helix has a significant impact on the backbone and side-chain conformations of the Asp103 residue, rigidifying important hydrogen bonds in the EF-hand and decreasing the solvent exposure of the Ca²⁺ ion, hence leading to more favorable Ca²⁺ binding in longer peptides. The present study provides molecular insights into the ion binding in the EF-hand and establishes an important step toward elucidating the responses of Ca²⁺-binding proteins toward the ion and target availability.

Structure-Based Identification of Natural Compounds as Potential RET-Kinase Inhibitors for Therapeutic Targeting of Neurodegenerative Diseases

BACKGROUND

Tyrosine-protein kinase receptor Ret (RET), a proto-oncogene, is considered as an attractive drug target for cancer and neurodegenerative diseases, including Alzheimer's disease (AD).

OBJECTIVE

We aimed to identify potential inhibitors of RET kinase among natural compounds present in the ZINC database.

METHODS

A multistep structure-based virtual screening approach was used to identify potential RET kinase inhibitors based on their binding affinities, docking scores, and interactions with the biologically important residues of RET kinase. To further validate the potential of these compounds as therapeutic leads, molecular dynamics (MD) simulations for 100 ns were carried out and subsequently evaluated the stability, conformational changes, and interaction mechanism of RET in-complex with the elucidated compounds.

RESULTS

Two natural compounds, ZINC02092851 and ZINC02726682, demonstrated high affinity, specificity for the ATP-binding pocket of RET and drug-likeness properties. The MD simulation outputs indicated that the binding of both compounds stabilizes the RET structure and leads to fewer conformational changes.

CONCLUSIONS

The findings suggest that ZINC02092851 and ZINC02726682 may be potential inhibitors for RET, offering valuable leads for drug development against RET-associated diseases. Our study provides a promising avenue for developing new therapeutic strategies against complex diseases, including AD. Identifying natural compounds with high affinity and specificity for RET provides a valuable starting point for developing novel drugs that could help combat these debilitating diseases.

Proline C-H Bonds as Loci for Proline Assembly via C-H/O Interactions

Proline residues within proteins lack a traditional hydrogen bond donor. However, the hydrogens of the proline ring are all sterically accessible, with polarized C-H bonds at Hα and Hδ that exhibit greater partial positive character and can be utilized as alternative sites for molecular recognition. C-H/O interactions, between proline C-H bonds and oxygen lone pairs, have been previously identified as modes of recognition within protein structures and for higher-order assembly of protein structures. In order to better understand intermolecular recognition of proline residues, a series of proline derivatives was synthesized, including 4R-hydroxyproline nitrobenzoate methyl ester, acylated on the proline nitrogen with bromoacetyl and glycolyl groups, and Boc-4S-(4-iodophenyl)hydroxyproline methyl amide. All three derivatives exhibited multiple close intermolecular C-H/O interactions in the crystallographic state, with H⋅⋅⋅O distances as close as 2.3 Å. These observed distances are well below the 2.72 Å sum of the van der Waals radii of H and O, and suggest that these interactions are particularly favorable. In order to generalize these results, we further analyzed the role of C-H/O interactions in all previously crystallized derivatives of these amino acids, and found that all 26 structures exhibited close intermolecular C-H/O interactions. Finally, we analyzed all proline residues in the Cambridge Structural Database of small-molecule crystal structures. We found that the majority of these structures exhibited intermolecular C-H/O interactions at proline C-H bonds, suggesting that C-H/O interactions are an inherent and important mode for recognition of and higher-order assembly at proline residues. Due to steric accessibility and multiple polarized C-H bonds, proline residues are uniquely positioned as sites for binding and recognition via C-H/O interactions.