AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors

Sulphated Fucooligosaccharide from Sargassum Horneri: Structural Analysis and Anti-Alzheimer Activity

In the present study, sulfated polysaccharides were obtained by digestion of Sargassum horneri and preparation with enzyme-assisted extraction using three food-grade enzymes, and their anti- Alzheimer's activities were investigated. The results demonstrated that the crude sulfated polysaccharides extracted using AMGSP, CSP and VSP dose-dependently (25-100 µg·mL- 1) raised the spontaneous alternating manner (%) in the Y maze experiment of mice and reduced the escape latency time in Morris maze test. AMGSP, CSP and VSP also exhibited good anti-AChE and moderate anti-BuChE activities. CSP displayed the best inhibitory efficacy against AChE. with IC50 values of 9.77 µM. And, CSP also exhibited good inhibitory selectivity of AChE over BuChE. Next, CSP of the best active crude extract was separated by the preparation type high performance liquid phase to obtain the sulphated fucooligosaccharide section: SFcup (→3-α-L-fucp(2-SO3-)-1→4-α-L-fucp(2,3-SO3-)-1→section), SFcup showed a best inhibitory efficacy against AChE with IC50 values of 4.03 µM. The kinetic research showed that SFcup inhibited AChE through dual binding sites. Moreover, the molecular docking of SFcup at the AChE active site was in accordance with the acquired pharmacological results.

Peptidomics-based identification of antihypertensive and antidiabetic peptides from sheep milk fermented using Limosilactobacillus fermentum KGL4 MTCC 25515 with anti-inflammatory activity: in silico, in vitro, and molecular docking studies

This study investigated the synthesis of bioactive peptides from sheep milk through fermentation with Limosilactobacillus fermentum KGL4 MTCC 25515 strain and assessed lipase inhibition, ACE inhibition, α-glucosidase inhibition, and α-amylase inhibition activities during the fermentation process. The study observed the highest activities, reaching 74.82%, 70.02%, 72.19%, and 67.08% (lipase inhibition, ACE inhibition, α-glucosidase inhibition, and α-amylase inhibition) after 48 h at 37°C, respectively. Growth optimization experiments revealed that a 2.5% inoculation rate after 48 h of fermentation time resulted in the highest proteolytic activity at 9.88 mg/mL. Additionally, fractions with less than 3 kDa of molecular weight exhibited superior ACE-inhibition and anti-diabetic activities compared to other fractions. Fermentation of sheep milk with KGL4 led to a significant reduction in the excessive production of NO, TNF-α, IL-6, and IL-1β produced in RAW 267.4 cells upon treatment with LPS. Peptides were purified utilizing SDS-PAGE and electrophoresis on 2D gels, identifying a maximum number of proteins bands ranging 10-70 kDa. Peptide sequences were cross-referenced with AHTPDB and BIOPEP databases, confirming potential antihypertensive and antidiabetic properties. Notably, the peptide (GPFPILV) exhibited the highest HPEPDOCK score against both α-amylase and ACE.

Rational Engineering of Escherichia coli Nissle 1917 as Live Biotherapeutic to Degrade Uremic Toxin Precursors

Uremic toxins (UTs) are microbiota-derived metabolites that accelerate the progression of kidney damage in patients with chronic kidney disease (CKD). One of the major UTs involved in CKD progression is p-cresol-sulfate (PCS), derived from dietary l-tyrosine (l-Tyr). Here, we engineered a probiotic strain of Escherichia coli Nissle 1917, to convert l-Tyr to the nontoxic compound p-coumaric acid via tyrosine ammonia lyase (TAL). First, a small metagenomic library was assessed to identify the TAL with the greatest whole-cell activity. Second, accessory genes implicated in the import of l-Tyr and export of PCA were overexpressed to enhance l-Tyr degradation by 106% and 56%, respectively. Last, random mutagenesis coupled to a novel selection and screening strategy was developed that identified a TAL variant with a 25% increase in whole-cell activity. Taken together, the final strain exhibits a 183% improvement over initial whole-cell activity and provides a promising candidate to degrade l-Tyr mediated PCS accumulation.

Computational investigation of turmeric phytochemicals targeting PTR1 enzyme of Leishmania species

In this study, we used in silico techniques to identify available parasite treatments, representing a promising therapeutic avenue. Building upon our computational initiatives aimed at discovering natural inhibitors for various target enzymes from parasites causing neglected tropical diseases (NTDs), we present novel findings on three turmeric-derived phytochemicals as inhibitors of Leishmania pteridine reductase I (PTR1) through in silico methodologies. PTR1, a crucial enzyme in the unique folate metabolism of trypanosomatid parasites, holds established therapeutic significance. Employing MOE software, a molecular docking analysis assesses the efficacy of turmeric phytochemicals against Leishmania PTR1. Validation of the docking protocol is confirmed with an RMSD value of 2. Post-docking, compounds displaying notable interactions with critical residues and binding affinities ranging between -6 and -8 kcal/mol are selected for interaction pattern exploration. Testing twelve turmeric phytochemicals, including curcumin, zingiberene, curcumol, curcumenol, eugenol, bisdemethoxycurcumin, tetrahydrocurcumin, tryethylcurcumin, turmerones, turmerin, demethoxycurcumin, and turmeronols, revealed binding affinities ranging from -5.5 to -8 kcal/mol. Notably, curcumin, demethoxycurcumin, and bisdemethoxycurcumin exhibit binding affinities within -6.5 to -8 kcal/mol and establish substantial interactions with catalytic residues. These phytochemicals hold promise as lead structures for rational drug design targeting Leishmania spp. PTR in future applications. This work underscores the potential of these identified phytochemicals in the development of more effective inhibitors, demonstrating their relevance in addressing neglected tropical diseases caused by parasites.

Shotgun proteomics and molecular simulations on multifunctional bioactive peptides derived from the whey of unexplored "Gaddi" goat of Himalayas

The very first time, whey protein from the Himalayan goat breed "Gaddi" was hydrolyzed with alcalase, flavourzyme, and a combination of both in this study. The degree of hydrolysis (DH) ranged from 28 to 53%, with sequential hydrolysis by combination achieving the highest DH. The sequential hydrolysis demonstrated antimicrobial activity against all pathogens used with 3 kDa permeate showed significantly higher (p < 0.05) activity against S. aureus, E. coli, B. cereus and C. sakazakii. The antioxidant activity was in the range of IC50 = 0.49 to 2.00 mg protein/mL, flavourzyme and sequential hydrolysates showed significant ABTS radical and FRAP inhibition. The α-amylase inhibitory activity was highest in 3 kDa permeate of flavourzyme with IC50 values of 0.34 mg protein/mL. Bioactive peptides DDSPDLPK, EMPFPK and TPEVDKEALEK were identified most significant in the hydrolysates. In molecular docking, the DDSPDLPK interacted most efficiently with enzymes involved in microbial growth, oxidative stress, and hyperglycemia.

Bioinformatics approaches and big data analytics opportunities in improving fisheries and aquaculture

Aquaculture has witnessed an excellent growth rate during the last two decades and offers huge potential to provide nutritional as well as livelihood security. Genomic research has contributed significantly toward the development of beneficial technologies for aquaculture. The existing high throughput technologies like next-generation technologies generate oceanic data which requires extensive analysis using appropriate tools. Bioinformatics is a rapidly evolving science that involves integrating gene based information and computational technology to produce new knowledge for the benefit of aquaculture. Bioinformatics provides new opportunities as well as challenges for information and data processing in new generation aquaculture. Rapid technical advancements have opened up a world of possibilities for using current genomics to improve aquaculture performance. Understanding the genes that govern economically relevant characteristics, necessitates a significant amount of additional research. The various dimensions of data sources includes next-generation DNA sequencing, protein sequencing, RNA sequencing gene expression profiles, metabolic pathways, molecular markers, and so on. Appropriate bioinformatics tools are developed to mine the biologically relevant and commercially useful results. The purpose of this scoping review is to present various arms of diverse bioinformatics tools with special emphasis on practical translation to the aquaculture industry.

Identification of HPr kinase/phosphorylase inhibitors: novel antimicrobials against resistant Enterococcus faecalis

Enterococcus faecalis, a gram-positive bacterium, is among the most common nosocomial pathogens due to its limited susceptibility to antibiotics and its reservoir of the genes coding for virulence factors. Bacterial enzymes such as kinases and phosphorylases play important roles in diverse functions of a bacterial cell and, thus, are potential antibacterial drug targets. In Gram-positive bacteria, HPr Kinase/Phosphorylase (HPrK/P), a bifunctional enzyme is involved in the regulation of carbon catabolite repression by phosphorylating/dephosphorylating the histidine-containing phosphocarrier protein (HPr) at Ser46 residue. Deficiencies in HPrK/P function leads to severe defects in bacterial growth. This study aimed at identifying novel inhibitors of E. faecalis HPrK/P from a commercial compound library using structure-based virtual screening. The hit molecules were purchased and their effect on enzyme activity and growth of resistant E. faecalis was evaluated in vitro. Furthermore, docking and molecular dynamics simulations were performed to study the interactions of the hit compounds with HPrK/P. Among the identified hit molecules, two compounds inhibited the phosphorylation of HPr as well as significantly reduced the growth of resistant E. faecalis in vitro. These identified potential HPrK/P inhibitors open new research avenues towards the development of novel antimicrobials against resistant Gram-positive bacteria.

Multi-stage transcriptome profiling of the neglected food-borne echinostome Artyfechinostomum sufrartyfex reveal potential diagnostic and drug targets

Lack of effective surveillance and control methods for neglected helminth diseases particularly in context of rural areas in India is a serious concern in terms of public health. With regard to the emerging food-borne echinostomid Artyfechinostomum sufrartyfex infection in the country, the current study is an in silico attempt to screen for plausible diagnostic and drug targets against the trematode. Transcriptome of adult, encysted and excysted metacercaria stages of the parasite was generated using Illumina sequencing platform. A de-novo assembly strategy utilizing transcriptome data generated from the three lifecycle stages was followed to generate the representative transcripts. Longest open reading frames identified for the transcripts were further conceptually translated into their respective protein sequences. Detailed analysis of this dataset through various bioinformatics pipelines and tools eventually identified 14 credible diagnostic and 10 drug targets along with their FDA-approved and ZINC molecules. Some of the important diagnostic candidates include thioredoxin peroxidase, haemoglobinase, cathepsin L, cathepsin L-like and B-like cysteine proteases. Among the drug targets, uncharacterized sodium dependent transporter and bifunctional protein Aas were identified as top targets exhibiting significant interaction with Rifamycin and ZINC02820058 molecule, respectively. Further, B-cell epitope analysis of the diagnostic targets revealed unique epitopes for 10 of them thus indicating their potential role in specific diagnosis of the parasite. The diagnostic candidates along with a number of lesser known drug targets and their ligand molecules identified in this study provides a reasonable basis for evaluation and development of future intervention strategies against A. sufrartyfex.

Evaluating the structural and immune mechanism of Interleukin-6 for the investigation of goat milk peptides as potential treatments for COVID-19

The function of Immune control, haematopoiesis, and inflammation all depend on the cytokine Interleukin 6 (IL-6), and higher expression of IL-6 is seen in COVID-19 and other diseases. The immune protein IL-6 activation is dependent on binding interactions with IL-6Rα, mIL-6R, and sIL-6R for its cellular function. Termination of these reaction could benefit for controlling the over-expression in COVID-19 patients and that may arise as inhibitors for controlling COVID-19. Traditionally, the goat milk has been prescribed as medicine in ayurvedic practice and through this work, we have explored the benefits of peptides from goat milk as IL-6 inhibitors, and it have the potential of inhibiting the over expression of IL-6 and control the COVID-19 disease. Computational experiments have shown that goat peptides had strong interactions with IL-6, with higher scoring profiles and energy efficiency ranging from −6.00 kcal/mol to −9.00 kcal/mol in docking score and −39.00 kcal/mol in binding energy. Especially the YLGYLEQLLR, VLVLDTDYK and AMKPWIQPK peptides from goat milk holds better scoring and shows strong interactions were identified as the most potential IL-6 inhibitor candidates in this study. Peptides from Goat proteins, which are capable of binding to the IL-6 receptor with strong binding conformations, have no negative effects on other immune system proteins.

Plant Source Derived Compound Exhibited In Silico Inhibition of Membrane Glycoprotein In SARS-CoV-2: Paving the Way to Discover a New Class of Compound For Treatment of COVID-19

SARS-CoV-2 is the virus responsible for causing COVID-19 disease in humans, creating the recent pandemic across the world, where lower production of Type I Interferon (IFN-I) is associated with the deadly form of the disease. Membrane protein or SARS-CoV-2 M proteins are known to be the major reason behind the lower production of human IFN-I by suppressing the expression of IFNβ and Interferon Stimulated Genes. In this study, 7,832 compounds from 32 medicinal plants of India possessing traditional knowledge linkage with pneumonia-like disease treatment, were screened against the Homology-Modelled structure of SARS-CoV-2 M protein with the objective of identifying some active phytochemicals as inhibitors. The entire study was carried out using different modules of Schrodinger Suite 2020-3. During the docking of the phytochemicals against the SARS-CoV-2 M protein, a compound, ZIN1722 from Zingiber officinale showed the best binding affinity with the receptor with a Glide Docking Score of −5.752 and Glide gscore of −5.789. In order to study the binding stability, the complex between the SARS-CoV-2 M protein and ZIN1722 was subjected to 50 ns Molecular Dynamics simulation using Desmond module of Schrodinger suite 2020-3, during which the receptor-ligand complex showed substantial stability after 32 ns of MD Simulation. The molecule ZIN1722 also showed promising results during ADME-Tox analysis performed using Swiss ADME and pkCSM. With all the findings of this extensive computational study, the compound ZIN1722 is proposed as a potential inhibitor to the SARS-CoV-2 M protein, which may subsequently prevent the immunosuppression mechanism in the human body during the SARS-CoV-2 virus infection. Further studies based on this work would pave the way towards the identification of an effective therapeutic regime for the treatment and management of SARS-CoV-2 infection in a precise and sustainable manner.

Destabilization of the Alzheimer's amyloid-β peptide by a proline-rich β-sheet breaker peptide: a molecular dynamics simulation study

The amyloid-β peptide exists in the form of fibrils in the plaques found in the brains of patients with Alzheimer's disease. One of the therapeutic strategies is the design of molecules which can destabilize these fibrils. We present a designed peptide KLVFFP₅ with two segments: the self-recognition sequence KLVFF and a β-sheet breaker proline pentamer. Molecular dynamics simulations and docking results showed that this peptide could bind to the protofibrils and destabilize them by establishing hydrophobic contacts and hydrogen bonds with a higher affinity than the KLVFF peptide. In the presence of the KLVFFP₅ peptide, the β-sheet content of the protofibrils was reduced significantly; the hydrogen bonding network and the salt bridges were disrupted to a greater extent than the KLVFF peptide. Our results indicate that the KLVFFP₅ peptide is an effective β-sheet disruptor which can be considered in the therapy of Alzheimer's disease.

Safe-in-Man Broad Spectrum Antiviral Agents

Emerging and re-emerging viral diseases occur with regularity within the human population. The conventional 'one drug, one virus' paradigm for antivirals does not adequately allow for proper preparedness in the face of unknown future epidemics. In addition, drug developers lack the financial incentives to work on antiviral drug discovery, with most pharmaceutical companies choosing to focus on more profitable disease areas. Safe-in-man broad spectrum antiviral agents (BSAAs) can help meet the need for antiviral development by already having passed phase I clinical trials, requiring less time and money to develop, and having the capacity to work against many viruses, allowing for a speedy response when unforeseen epidemics arise. In this chapter, we discuss the benefits of repurposing existing drugs as BSAAs, describe the major steps in safe-in-man BSAA drug development from discovery through clinical trials, and list several database resources that are useful tools for antiviral drug repositioning.

PvP01-DB: computational structural and functional characterization of soluble proteome of PvP01 strain of Plasmodium vivax

Despite Plasmodium vivax being the main offender in the majority of malarial infections, very little information is available about its adaptation and development in humans. Its capability for activating relapsing infections through its dormant liver stage and resistance to antimalarial drugs makes it as one of the major challenges in eradicating malaria. Noting the immediate necessity for the availability of a comprehensive and reliable structural and functional repository for P. vivax proteome, here we developed a web resource for the new reference genome, PvP01, furnishing information on sequence, structure, functions, active sites and metabolic pathways compiled and predicted using some of the state-of-the-art methods in respective fields. The PvP01 web resource comprises organized data on the soluble proteome consisting of 3664 proteins in blood and liver stages of malarial cycle. The current public resources represent only 163 proteins of soluble proteome of PvP01, with complete information about their molecular function, biological process and cellular components. Also, only 46 proteins of P. vivax have experimentally determined structures. In this milieu of extreme scarcity of structural and functional information, PvP01 web resource offers meticulously validated structures of 3664 soluble proteins. The sequence and structure-based functional characterization led to a quantum leap from 163 proteins available presently to whole soluble proteome offered through PvP01 web resource. We believe PvP01 web resource will serve the researchers in identifying novel protein drug targets and in accelerating the development of structure-based new drug candidates to combat malaria.

Database Availability: http://www.scfbio-iitd.res.in/PvP01

A novel piperazine derivative that targets hepatitis B surface antigen effectively inhibits tenofovir resistant hepatitis B virus

Chronic hepatitis B virus (HBV) infection is a global problem. The loss of hepatitis B surface antigen (HBsAg) in serum is a therapeutic end point. Prolonged therapy with nucleoside/nucleotide analogues targeting the HBV-polymerase may lead to resistance and rarely results in the loss of HBsAg. Therefore, inhibitors targeting HBsAg may have potential therapeutic applications. Here, we used computational virtual screening, docking, and molecular dynamics simulations to identify potential small molecule inhibitors against HBsAg. After screening a million molecules from ZINC database, we identified small molecules with potential anti-HBV activity. Subsequently, cytotoxicity profiles and anti-HBV activities of these small molecules were tested using a widely used cell culture model for HBV. We identified a small molecule (ZINC20451377) which binds to HBsAg with high affinity, with a KD of 65.3 nM, as determined by Surface Plasmon Resonance spectroscopy. Notably, the small molecule inhibited HBsAg production and hepatitis B virion secretion (10 μM) at low micromolar concentrations and was also efficacious against a HBV quadruple mutant (CYEI mutant) resistant to tenofovir. We conclude that this small molecule exhibits strong anti-HBV properties and merits further testing.

Trends in predictive biodegradation for sustainable mitigation of environmental pollutants: Recent progress and future outlook

The feasibility of in-silico techniques, together with the computational framework, has been applied to predictive bioremediation aiming to clean-up contaminants, toxicity evaluation, and possibilities for the degradation of complex recalcitrant compounds. Emerging contaminants from different industries have posed a significant hazard to the environment and public health. Given current bioremediation strategies, it is often a failure or inadequate for sustainable mitigation of hazardous pollutants. However, clear-cut vital information about biodegradation is quite incomplete from a conventional remediation techniques perspective. Lacking complete information on bio-transformed compounds leads to seeking alternative methods. Only scarce information about the transformed products and toxicity profile is available in the published literature. To fulfill this literature gap, various computational or in-silico technologies have emerged as alternating techniques, which are being recognized as in-silico approaches for bioremediation. Molecular docking, molecular dynamics simulation, and biodegradation pathways predictions are the vital part of predictive biodegradation, including the Quantitative Structure-Activity Relationship (QSAR), Quantitative structure-biodegradation relationship (QSBR) model system. Furthermore, machine learning (ML), artificial neural network (ANN), genetic algorithm (GA) based programs offer simultaneous biodegradation prediction along with toxicity and environmental fate prediction. Herein, we spotlight the feasibility of in-silico remediation approaches for various persistent, recalcitrant contaminants while traditional bioremediation fails to mitigate such pollutants. Such could be addressed by exploiting described model systems and algorithm-based programs. Furthermore, recent advances in QSAR modeling, algorithm, and dedicated biodegradation prediction system have been summarized with unique attributes.

Computational Screening of Potential Inhibitors of Desulfobacter postgatei for Pyrite Scale Prevention in Oil and Gas Wells

Sulfate-reducing bacteria (SRB), such as Desulfobacter postgatei are found in oil wells. However, they lead to the release of hydrogen sulfide. This in turn leads to the iron sulfide scale formation (pyrite). ATP sulfurylase is an enzyme present in SRB, which catalyzes the formation of adenylyl sulfate (APS) and inorganic pyrophosphatase (PPi) from ATP and sulfate. This reaction is the first among many in hydrogen sulfide production by D. postgatei . Consensus scoring using molecular docking and machine learning was used to identify three potential inhibitors of ATP sulfurylase from a database of about 40 million compounds. These selected hits ((S,E)-1-(4-methoxyphenyl)-3-(9-((m-tolylimino)methyl)-9,10-dihydroanthracen-9-yl)pyrrolidine-2,5-dione; methyl 2-[[(1S)-5-cyano-2-imino-1-(4-phenylthiazol-2-yl)-3-azaspiro[5.5]undec-4-en-4-yl]sulfanyl]acetate; and (4S)-4-(3-chloro-4-hydroxy-phenyl)-1-(6-hydroxypyridazin-3-yl)-3-methyl-4,5-dihydropyrazolo[3,4-b]pyridin-6-ol), known as A, B, and C, respectively) all had good binding affinities with ATP sulfurylase and were further analyzed for their toxicological properties. Compound A had the highest docking score. However, based on the physicochemical and toxicological properties, only compound C was predicted to be both safe and effective as a potential inhibitor of ATP sulfurylase, hence the preferred choice. The molecular interactions of compound C revealed favorable interactions with the following residues: LEU213, ASP308, ARG307, TRP347, LEU224, GLN212, MET211, and HIS309.

A review targeting the infection by CHIKV using computational and experimental approaches

The rise of normal body temperature of 98.6 °F beyond 100.4 °F in humans indicates fever due to some illness or infection. Viral infections caused by different viruses are one of the major causes of fever. One of such viruses is, Chikungunya virus (CHIKV) is known to cause Chikungunya fever (CHIKF) which is transmitted to humans through the mosquitoes, which actually become the primary source of transmission of the virus. The genomic structure of the CHIKV consists of the two open reading frames (ORFs). The first one is a 5' end ORF and it encodes the nonstructural protein (nsP1-nsP4). The second is a 3' end ORF and it encodes the structural proteins, which is consisted of capsid, envelope (E), accessory peptides, E3 and 6 K. Till date, there is no effective vaccine or medicine available for early detection of the CHIKV infection and appropriate diagnosis to cure the patients from the infection. NSP3 of CHIKV is the prime target of the researchers as it is responsible for the catalytic activity. This review has updates of literature on CHIKV; pathogenesis of CHIKV; inhibition of CHIKV using theoretical and experimental approaches.Communicated by Ramaswamy H. Sarma.

Enhancing the binding of the β-sheet breaker peptide LPFFD to the amyloid-β fibrils by aromatic modifications: A molecular dynamics simulation study

Alzheimer's is a fatal neurodegenerative disease for which there is no cure at present. The disease is characterized by the presence of plaques in the brains of a patient, which are composed mainly of aggregates of the amyloid-β peptide in the form of β-sheet fibrils. Here, we investigated the possibility of exploiting the superior binding ability of aromatic amino acids to a particular model of the amyloid-β fibrils. which is a difficult target for drug design. The β-sheet breaker peptide LPFFD was modified with aromatic amino acids and its binding to these fibrils was studied. We found that the orientation and the electrostatic complementarity of the modified peptide with respect to the fibrils played a crucial role in determining whether its binding was improved by the aromatic amino acids. The modified LPFFD peptides were able to bind to those fibril residues. which are important in the aggregation of amyloid-β peptides and thus can potentially inhibit the further aggregation of the amyloid-beta peptides by blocking their interactions. We found that the tryptophan modified LPFFD peptides had the best binding affinities. In most cases, the aromatic amino acids in the N-terminus of the modified peptides made more contacts with the fibrils than those in the C-terminus. We also found that increasing the aromatic content did not significantly improve the binding of the LPFFD peptide to the fibrils. Our study can serve as a basis for the design of novel peptide-based drugs for Alzheimer's disease in which aromatic interactions play an important role.

Atomistic simulation on flavonoids derivatives as potential inhibitors of bacterial gyrase of Staphylococcus aureus

The bacterial DNA gyrase is an attractive target to identify the novel antibacterial agents. The flavonoid derivatives possess various biological activities such as antimicrobial, anti-inflammatory and anticancer activities. The aim of present study is to identify the potential molecule from flavonoid derivatives against Staphylococcus aureus using atomistic simulation namely Molecular Docking, Quantum Chemical and Molecular Dynamics. The molecules Cpd58, Cpd65 and Cpd70 are identified as potential molecules through molecular docking approaches by exploring through the N - H…O hydrogen bonding interactions with Asn31 and Glu35 of Gyrase B. To confirm the intramolecular charge transfer in the flavonoid derivatives, Frontier Molecular Orbital (FMO) calculation was performed at M06/6-31g(d) level in gas phase. The lowest HOMO-LUMO gap was calculated for Cpd58, Cpd65 and Cpd70 among the selected compounds used in this study. Molecular dynamics simulation were carried out for Cpd58 and Cpd70 for a time period of 50 ns and found to be stable throughout the analysis. Therefore, the identified compounds are found to be a potent inhibitor for GyrB of S. aureus that can be validated by experimental studies. Communicated by Ramaswamy H. Sarma.

Peptide modelling and screening against human ACE2 and spike glycoprotein RBD of SARS-CoV-2

Outbreak of Coronavirus Disease 2019 (COVID-19) has become a great challenge for scientific community globally. Virus enters cell through spike glycoprotein fusion with ACE2 (Angiotensin-Converting Enzyme 2) human receptor. Hence, spike glycoprotein of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a potential target for diagnostics, vaccines, and antibodies. Also, virus entry can be prevented by blocking ACE2 thus, ACE2 can be considered potential target for therapeutics. As being highly specific, safe and efficacious, peptides hold their place in therapeutics. In present study, we retrieved sequence of 70 peptides from Antiviral Peptide Database (AVPdb), modelled them using 3D structure predicting web tool and docked them with receptor binding domain (RBD) of spike protein and human host receptor ACE2 using peptide-protein docking. It was observed that peptides have more affinity towards ACE2 in comparison with spike RBD. Interestingly it was noticed that most of the peptides bind to RBM (residue binding motif) which is responsible for ACE2 binding at the interface of RBD while, for ACE2, peptides prefer to bind the core cavity rather than RBD binding interface. To further investigate how peptides at the interface of RBD or ACE2 alter the binding between RBD and ACE2, protein-protein docking of RBD and ACE2 with and without peptides was performed. Peptides, AVP0671 at RBD and AVP1244 at ACE2 interfaces significantly reduce the binding affinity and change the orientation of RBD and ACE2 binding. This finding suggests that peptides can be used as a drug to inhibit virus entry in cells to stop COVID-19 pandemic in the future after experimental evidences.

In silico identification of strong binders of the SARS-CoV-2 receptor-binding domain

The world is currently witnessing the spread of the deadly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes the coronavirus disease 2019 (COVID-19). In less than three months since the first cases were reported, the World Health Organization declared it a pandemic disease. Although several treatment and prevention strategies are currently under investigation, a continuous effort to investigate and develop effective cures is urgently needed. Thus, we performed molecular docking and structure-based virtual screening of libraries of approved drugs, antivirals, inhibitors of protein-protein interactions, and one million other small molecules to identify strong binders of the SARS-CoV-2 receptor-binding domain (RBD) that might interfere with the receptor recognition process, so as to inhibit the viral cellular entry. According to our screening and selection criteria, three approved antivirals (elbasvir, grazoprevir, and sovaprevir) and 4 other drugs (hesperidin, pamaqueside, diosmin, and sitogluside) were identified as potent binders of the RBD. The binding of these molecules involved several RBD residues required for the interaction of the virus with its cellular receptor. Furthermore, this study also discussed the pharmacological action of the 4 non-antiviral drugs on hematological and neurological disorders that, in addition to inhibiting the viral entry, could be beneficial against the neurological disorders identified in COVID-19 patients. Besides, six other small-molecules were identified, with no pharmacological description so far, exhibiting strong binding affinities to the RBD that we believe worth being investigated as inhibitors of the SARS-CoV-2-receptor interaction.

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We aimed to identify strong binders of the SARS-CoV-2 RBD to be used as inhibitors of virus-receptor interaction.

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Accordingly, 3 antivirals, 4 other approved drugs and 6 small-molecules have been identified as potential ligands of the RBD.

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The binding of these selected compounds involves several RBD residues crucial for the virus-receptor interaction.

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Besides RBD-binding, we discussed the possible effects of the selected drugs on the COVID-19- related neurological disorders.

Sequence Analysis and Structure Prediction of SARS-CoV-2 Accessory Proteins 9b and ORF14: Evolutionary Analysis Indicates Close Relatedness to Bat Coronavirus

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a single-stranded RNA genome that encodes 14 open reading frames (ORFs), eight of which encode accessory proteins that allow the virus to infect the host and promote virulence. The genome expresses around 29 structural and nonstructural protein products. The accessory proteins of SARS-CoV-2 are not essential for virus replication but do affect viral release, stability, and pathogenesis and finally contribute to virulence. This paper has attempted the structure prediction and functional analysis of two such accessory proteins, 9b and ORF14, in the absence of experimental structures. Sequence analysis, structure prediction, functional characterization, and evolutionary analysis based on the UniProtKB reviewed the amino acid sequences of SARS-CoV-2 9b (P0DTD2) and ORF14 (P0DTD3) proteins. Modeling has been presented with the introduction of hybrid comparative and ab initio modeling. QMEANDisCo 4.0.0 and ProQ3 for global and local (per residue) quality estimates verified the structures as high quality, which may be attributed to structure-based drug design targets. Tunnel analysis revealed the presence of 1-2 highly active tunneling sites, perhaps which will able to provide certain inputs for advanced structure-based drug design or to formulate potential vaccines in the absence of a complete experimental structure. The evolutionary analysis of both proteins of human SARS-CoV-2 indicates close relatedness to the bat coronavirus. The whole-genome phylogeny indicates that only the new bat coronavirus followed by pangolin coronaviruses has a close evolutionary relationship with the novel SARS-CoV-2.

Homology Modeling and Probable Active Site Cavity Prediction of Uncharacterized Arsenate Reductase in Bacterial spp

The arsC gene-encoded arsenate reductase is a vital catalytic enzyme for remediation of environmental arsenic (As). Microorganisms containing the arsC gene can convert pentavalent arsenate (As[V]) to trivalent arsenite (As[III]) to be either retained in the bacterial cell or released into the air. The molecular mechanism governing this process is unknown. Here we present an in silico model of the enzyme to describe their probable active site cavities using SCFBio servers. We retrieved the amino acid sequence of bacterial arsenate reductase enzymes in FASTA format from the NCBI database. Enzyme structure was predicted using the I-TASSER server and visualized using PyMOL tools. The ProSA and the PROCHECK servers were used to evaluate the overall significance of the predicted model. Accordingly, arsenate reductase from Streptococcus pyogenes, Oligotropha carboxidovorans OM5, Rhodopirellula baltica SH 1, and Serratia ureilytica had the highest quality scores with statistical significance. The plausible cavities of the active site were identified in our examined arsenate reductase enzymes which were abundant in glutamate and lysine residues with 6 to 16 amino acids. This in silico experiment may contribute greatly to the remediation of arsenic pollution through the utilization of microbial species.

Evaluation of novobiocin and telmisartan for anti-CHIKV activity

Chikungunya has re-emerged as an epidemic with global distribution and high morbidity, necessitating the need for effective therapeutics. We utilized already approved drugs with a good safety profile used in other diseases for their new property of anti-chikungunya activity. It provides a base for a fast and efficient approach to bring a novel therapy from bench to bedside by the process of drug-repositioning. We utilized an in-silico drug screening with FDA approved molecule library to identify inhibitors of the chikungunya nsP2 protease, a multifunctional and essential non-structural protein required for virus replication. Telmisartan, an anti-hypertension drug, and the antibiotic novobiocin emerged among top hits on the screen. Further, SPR experiments revealed strong in-vitro binding of telmisartan and novobiocin to nsP2 protein. Additionally, small angle x-ray scattering suggested binding of molecules to nsP2 and post-binding compaction and retention of monomeric state in the protein-inhibitor complex. Protease activity measurement revealed that both compounds inhibited nsP2 protease activity with IC₅₀ values in the low micromolar range. More importantly, plaque formation assays could show the effectiveness of these drugs in suppressing virus propagation in host cells. We propose novobiocin and telmisartan as potential inhibitors of chikungunya replication. Further research is required to establish the molecules as antivirals of clinical relevance against chikungunya.

Deciphering the structural basis of the broad substrate specificity of myo-inositol monophosphatase (IMP) from Cicer arietinum

Myo-inositol monophosphatase (IMP) is a crucial enzyme in the inositol biosynthetic pathway that dephosphorylates myo-inositol 1-phosphate and other inositol phosphate derivative compounds to maintain the homeostasis of cellular inositol pool. In our previous research, we have biochemically and functionally characterized IMP enzyme from chickpea (CaIMP), which was able to catalyze diverse substrates. We cloned, overexpressed recombinant CaIMP protein and purified it and further characterized the CaIMP with its three main substrates viz. galactose 1-P, inositol 6-P and fructose 1,6-bisP. Homology model of CaIMP was generated to elucidate the factors contributing to the broad substrate specificity of the protein. The active site of the CaIMP protein was analysed with respect to its interactions with the proposed substrates. Structural features such as, high B-factor and flexible loop regions in the active site, inspired further investigation into the static and dynamic behaviour of the active site of CaIMP protein. The electrostatic biding of each of the key substrates was assessed through molecular docking. Furthermore, molecular dynamics simulations showed that these interactions indeed were stable for extended periods of time under physiological conditions. These experiments conclusively allowed us to establish the primary factors contributing to the promiscuity in substrate binding by CaIMP protein.

Discovery of small molecule inhibitors of chikungunya virus proteins (nsP2 and E1) using in silico approaches

Chikungunya virus (CHIKV) has emerged as a major viral threat, affecting over a million people worldwide per year. It is a vector borne disease transmitted to the human by Ades mosquitoes and primarily affect people by causing viral fever, severe joint pain and other symptoms, like rash, joint swelling, muscle pain and in rare cases can be fatal. CHIKV is a deadly virus, with its mutation rate found to be significantly higher as compared to other viruses. To date, there has been no reported FDA approved drug against this virus. Thus, keeping in mind the urgent need to scrutinize potential therapies against CHIKV, the present study identified twenty plant bioactive compounds that are available at low price and do not have associated adverse effect. For identification of active potentials molecules the pharmacoinformatics-based perspective was applied against CHIKV structural (E1) and non-structural (nsP2) proteins using molecular docking and scoring. The selected compounds were further studied for pharmacokinetics (PK) and pharmacodynamics (PD) associated parameters such as initial absorption, then distribution and later on metabolism excretion and toxicity (ADMET) profiles based on in silico study. The results reveal five potential lead compounds having high binding energy that can help in the development of commercial drugs with favorable ADMET characteristic.Communicated by Ramaswamy H. Sarma.

Modulations in the ATPases during ketamine-induced schizophrenia and regulatory effect of "3-(3, 4-dimethoxy phenyl) -1- (4-methoxyphenyl) prop-2-en-1-one": an in vivo and in silico studies

Schizophrenia is a devastating illness and displays a wide range of psychotic symptoms. Accumulating evidence indicate impairment of bioenergetic pathways including energy storage and usage in the pathogenesis of schizophrenia. Although well-established synthetic drugs are being used for the management of schizophrenia, most of them have several adverse effects. Hence, natural products derived from medicinal plants represent a continuous major source for ethnomedicine-derived pharmaceuticals for different neurological disorders including schizophrenia. In the present study, we have investigated the neuroprotective effect of the novel bioactive compound i.e. "3-(3,4-dimethoxy phenyl) -1- (4-methoxyphenyl) prop-2-en-1-one" of Celastrus paniculata against ketamine-induced schizophrenia with particular reference to the activities of ATPase using in vivo and in silico methods. Ketamine-induced schizophrenia caused significant reduction in the activities of all three ATPases (Na⁺/K⁺, Ca²⁺ and Mg²⁺) in different regions of brain which reflects the decreased turnover of ATP, presumably due to the inhibition of oxidoreductase system and uncoupling of the same from the electron transport system. On par with the reference compound, clozapine, the activity levels of all three ATPases were restored to normal after pretreatment with the compound suggesting recovery of energy loss that was occurred during ketamine-induced schizophrenia. Besides, the compound has shown strong interaction and exhibited highest binding energies against all the three ATPases with a lowest inhibition constant value than the clozapine. The results of the present study clearly imply that the compound exhibit significant neuroprotective and antischizophrenic effect by modulating bioenergietic pathways that were altered during induced schizophrenia.

Identification of potential therapeutic targets in Neisseria gonorrhoeae by an in-silico approach

Neisseria gonorrhoeae is a gram negative diplococcus bacterium and the causative agent of the sexually transmitted disease Gonorrhea. It has been recently given the status of "superbug" by World Health Organization because of the increasing antibiotic resistance and unavailability of a viable vaccine candidate. Over recent years, there have been increasing reports about the use of subtractive genomics to identify potential drug and vaccine targets. Our study utilizes codon biasing, a tool to identify the essential genes, in N. gonorrhoeae that could be utilized as novel therapeutic targets for drug or vaccine development. Through the screening of 2350 total genes, we present a list of 29 such drug candidate genes based on codon adaptation. Through the data-mining with BLAST2GO and InterProScan databases, we could predict the function of these 29 genes. These genes are involved in pivotal cellular functions like DNA replication, energy synthesis and metabolites production. This study also shortlists the essential genes of N. gonorrhoeae that could be used to target Neisseria. We identified a molecule/drug which can be used to target essential protein DapD (succinyltransferase).

Computational approach to study the synthesis of noscapine and potential of stereoisomers against nsP3 protease of CHIKV

Chikungunya fever is a major public health issue in India affecting millions of people and occurs due to Chikungunya. Chikungunya virus (CHIKV) is a single stranded RNA virus from the family of Togaviridae and genus alpha virus. It contain three structural proteins: glycosylated E1 and E2, embedded in the viral envelope, and a non-glycosylated nucleocapsid protein. Till date, researchers are working on inhibition of CHIKV but till now no cheap and effective medicine is available in the market. Therefore, the authors of this work thought of isoquinoline based noscapine to inhibit the nsP3 protease of CHIKV. The aim of the work is to understand the mechanism for the synthesis of noscapine theoretically using DFT. Further study the potential of all four isomers of noscapines {(13 (S,R), 14 (R,R), 15 (R,S) and 16 (S,S)} against nsP3 protease of CHIKV with the help of docking and MD simulation. The integrated e-pharmacophore binding affinity based virtual screening, docking and molecular dynamics simulation recognized four hits isomers as inhibition nsP3 protease of CHIKV. The docking energies of all the isomers of noscapine (13–16) with nsP3 protease CHIKV was found out to be more negative than baicalin (−8.06 kcal/mol) on selected sites. Amongst the isomers of noscapine, CMPD 13 possessed best binding affinity with four hydrogen bonding interactions. Further, ADME properties and blood-brain barrier permeability properties have been calculated. DFT studies of all the isomers of noscapine was investigated.

In silico characterization of hypothetical proteins from Orientia tsutsugamushi str. Karp uncovers virulence genes

Scrub typhus also known as bush typhus is a disease with symptoms similar to Chikungunya infection. It is caused by a gram-negative bacterium Orientia tsutsugamushi which resides in its vertebrate host, Mites. The genome of Orientia tsutsugamushi str. Karp encodes for 1,563 proteins, of which 344 are characterized as hypothetical ones. In the present study, we tried to identify the probable functions of these 344 hypothetical proteins (HPs). All the characterized hypothetical proteins (HPs) belong to the various protein classes like enzymes, transporters, binding proteins, metabolic process and catalytic activity and kinase activity. These hypothetical proteins (HPs) were further analyzed for virulence factors with 62 proteins identified as the most virulent proteins among these hypothetical proteins (HPs). In addition, we studied the protein sequence similarity network for visualizing functional trends across protein superfamilies from the context of sequence similarity and it shows great potential for generating testable hypotheses about protein structure-function relationships. Furthermore, we calculated toplogical properties of the network and found them to obey network power law distributions showing a fractal nature. We also identifed two highly interconnected modules in the main network which contained five hub proteins (KJV55465, KJV56211, KJV57212, KJV57203 and KJV57216) having 1.0 clustering coefficient. The structural modeling (2D and 3D structure) of these five hub proteins was carried out and the catalytic site essential for its functioning was analyzed. The outcome of the present study may facilitate a better understanding of the mechanism of virulence, pathogenesis, adaptability to host and up-to-date annotations will make unknown genes easy to identify and target for experimentation. The information on the functional attributes and virulence characteristic of these hypothetical proteins (HPs) are envisaged to facilitate effective development of novel antibacterial drug targets of Orientia tsutsugamushi.

Structure-Guided Approach to Identify Potential Inhibitors of Large Envelope Protein to Prevent Hepatitis B Virus Infection

Hepatitis B virus (HBV) infection is one of the major causes of liver diseases, which can lead to hepatocellular carcinoma. The role of HBV envelope proteins is crucial in viral morphogenesis, infection, and propagation. Thus, blocking the pleiotropic functions of these proteins especially the PreS1 and PreS2 domains of the large surface protein (LHBs) is a promising strategy for designing efficient antivirals against HBV infection. Unfortunately, the structure of the LHBs protein has not been elucidated yet, and it seems that any structure-based drug discovery is critically dependent on this. To find effective inhibitors of LHBs, we have modeled and validated its three-dimensional structure and subsequently performed a virtual high-throughput screening against the ZINC database using RASPD and ParDOCK tools. We have identified four compounds, ZINC11882026, ZINC19741044, ZINC00653293, and ZINC15000762, showing appreciable binding affinity with the LHBs protein. The drug likeness was further validated using ADME screening and toxicity analysis. Interestingly, three of the four compounds showed the formation of hydrogen bonds with amino acid residues lying in the capsid binding region of the PreS1 domain of LHBs, suggesting the possibility of inhibiting the viral assembly and maturation process. The identification of potential lead molecules will help to discover more potent inhibitors with significant antiviral activities.

Development of a theoretical model for the inhibition of nsP3 protease of Chikungunya virus using pyranooxazoles

Chikungunya virus (CHIKV) causes Chikungunya fever (CHIKF) and till date no effective medicine for its cure is available in market. Different research groups find various possible interactions between small molecules and non-structural proteins, viz. nsP3, one of the most important viral elements in CHIKV. In this work, authors have studied the interactions of nsP3 protease of CHIKV with pyranooxazoles. Initially, a one-pot three-component reaction was designed using oxazolidine-2,4-dione, benzaldehyde and cyanoethylacetate to get a proposed biological active molecule, i.e. based on pyranooxazoles. The mechanism for the synthesis of the product based on pyranooxazole was studied through density functional theory (DFT) using Gaussian. Then, a library of the obtained pyranooxazole was created through computational tools by varying the substituents. Further, virtual screening of the designed library of pyranooxazoles (200 compounds) against nsP3 protease of CHIKV was performed. Herein, CMPD 104 showed strongest binding affinity toward the targeted nsP3 protease of CHIKV, based on the least binding energy obtained from docking. Based on docking results, the pharmacological, toxicity, biological score and Lipinski's filters were studied. Further, DFT studies of top five compounds were done using Gaussian. Molecular dynamics (MD) simulation of nsP3 protease of CHIKV with and without 104 was performed using AMBER18 utilizing ff14SB force field in three steps (minimization, equilibration and production). This work is emphasized to designing of one-pot three-component synthesis and to develop a theoretical model to inhibit the nsP3 protease of CHIKV. AbbreviationsCHIKFChikungunya feverCHIKVChikungunya virusDFTdensity functional theoryDSDiscovery StudioMDmolecular dynamicsMM-GBSAmolecular mechanics-generalized born surface areaMMVMolegro molecular viewerCommunicated by Ramaswamy H. Sarma.

Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites

Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites through effector molecules. Owing to their significance in determining protein function, the identification of protein functional and regulatory binding sites is widely acknowledged as an important biological problem. In this work, we present a novel binding site prediction method, Active and Regulatory site Prediction (AR-Pred), which supplements protein geometry, evolutionary, and physicochemical features with information about protein dynamics to predict putative active and allosteric site residues. As the intrinsic dynamics of globular proteins plays an essential role in controlling binding events, we find it to be an important feature for the identification of protein binding sites. We train and validate our predictive models on multiple balanced training and validation sets with random forest machine learning and obtain an ensemble of discrete models for each prediction type. Our models for active site prediction yield a median area under the curve (AUC) of 91% and Matthews correlation coefficient (MCC) of 0.68, whereas the less well-defined allosteric sites are predicted at a lower level with a median AUC of 80% and MCC of 0.48. When tested on an independent set of proteins, our models for active site prediction show comparable performance to two existing methods and gains compared to two others, while the allosteric site models show gains when tested against three existing prediction methods. AR-Pred is available as a free downloadable package at https://github.com/sambitmishra0628/AR-PRED_source.

Naphthalene-triazolopyrimidine hybrid compounds as potential multifunctional anti-Alzheimer's agents

In an attempt to construct potential anti-Alzheimer's agents Naphthalene-triazolopyrimidine hybrids were synthesized and screened in vitro against the two cholinesterases (ChE)s, amyloid β aggregation and for antioxidation activity. Single-crystal X-ray crystallography was utilized for crystal structure determination of one of the compounds. In vitro study of compounds revealed that most of the compounds are capable of inhibiting acetylcholinesterase and Butyrylcholinesterase activity. Particularly, the compounds 4e and 4d exhibited IC₅₀ values ranging from 8.6 to 14 nM against AChE lower than the standard drug Donepezil (IC₅₀ 49 nM). Best result was found for compound 4e with IC₅₀ of 8.6 nM (for AChE) and 150 nM (for BuChE). Selectivity upto that of Donepezil and even more was observed for 4a, 4c and 4h. Investigation by electron microscopy, transmission electron microscopy and ThT fluorescence assay unveils the fact that synthesized hybrids exhibit amyloid β self-aggregation inhibition. The compounds 4i and 4j revealed highest inhibitory potential, 85.46% and 72.77% at 50 μM respectively; above the standard Aβ disaggregating agent, Curcumin. Their antioxidation profile was also analyzed. Studies from DPPH free radical scavenging assay and ORAC assay depicts molecules to possess low antioxidation profile. Results suggest that triazolopyrimidines are potential candidate for Acetylcholinesterase (AChE), Butyrylcholinesterase (BuChE), and amyloid β aggregation inhibition. In silico ADMET profiling indicates drug-like properties with a very low toxic influence. Such synthesized compounds provide a strong vision for further development of potential anti-Alzheimer's agents.

Toward development of generic inhibitors against the 3C proteases of picornaviruses

Development of novel antivirals, which requires knowledge of the viral life cycle in molecular detail, is a daunting task, involving extensive investments, and frequently resulting in failure. As there exist significant commonalities among virus families in the manner of host interaction, identifying and targeting common rather than specific features may lead to the development of broadly useful antivirals. Here, we have targeted the 3C protease of Hepatitis A Virus (HAV), a feco-orally transmitted virus of the family Picornaviridae, for identification of potential antivirals. The 3C protease is a viable drug target as it is required by HAV, as well as by other picornaviruses, for post-translational proteolysis of viral polyproteins and for inhibiting host innate immune pathways. Computational screening, followed by chemical synthesis and experimental validation resulted in identification of a few compounds which, at low micromolar concentrations, could inhibit HAV 3C activity. These compounds were further tested experimentally against the 3C protease of Human Rhinovirus, another member of the Picornaviridae family, with comparable results. Computational studies on 3C proteases from other members of the picornavirus family have indicated that the compounds identified could potentially be generic inhibitors for picornavirus 3C proteases.

Design, synthesis and glycosidase inhibition studies of novel triazole fused iminocyclitol-δ-lactams

Synthesis of novel triazole fused iminocyclitol-δ-lactams, from tri-O-benzyl-d-glucal, involving intermolecular [3 + 2]cycloaddition and intramolecular lactamisation reactions as key steps is described.

Quinoline-triazole hybrids inhibit falcipain-2 and arrest the development ofPlasmodium falciparumat the trophozoite stage

The present study involves development of novel quinoline triazole-containing cysteine protease inhibitors which arrest the development ofP. falciparumat the trophozoite stage.

Toward a better understanding of the interaction between somatostatin receptor 2 and its ligands: a structural characterization study using molecular dynamics and conceptual density functional theory

This study is a part of the extensive research intending to provide the structural insights on somatostatin and its receptor. Herein, we have studied the structural complexity involved in the binding of somatostatin receptor 2 (SSTR2) with its agonists and antagonist. A 3D QSAR study based on comparative molecular field analysis and comparative molecular similarity analysis (CoMSIA) discerned that a SSTR2 ligand with electronegative, less-bulkier, and hydrogen atom donating/accepting substitutions is important for their biological activity. A conceptual density functional theory (DFT) study was followed to study the chemical behavior of the ligands based on the molecular descriptors derived using the Fukui's molecular orbital theory. We have performed molecular dynamics simulations of receptor-ligand complexes for 100 ns to analyze the dynamic stability of the backbone Cα atoms of the receptor and strength and approachability of the receptor-ligand complex. The findings of this study could be efficacious in the further studies understanding intricate structural features of the somatostatin receptors and in discovering novel subtype-specific ligands with higher affinity. Communicated by Ramaswamy H. Sarma.

Comparative genomic analysis of Rickettsia rickettsii for identification of drug and vaccine targets: tolC as a proposed candidate for case study

BACKGROUND

Antibiotic resistance is increasing rapidly in pathogenic organisms, creating more complications for treatment of diseases. Rocky Mountain spotted fever (RMSF) is a neglected tropical disease in humans caused by Rickettsia rickettsii for which no effective therapeutic is available. Subtractive genomics methods facilitate the characterization of non-homologous essential proteins that could be targeted for the discovery of potential therapeutic compounds against R. rickettsii to combat RMSF. Present study followed an in-silico based methodology, involving scanning and filtering the complete proteome of Rickettsia rickettsii by using several prioritization parameters in the search of potential candidates for drug development. Further the putative targets were subjected to series of molecular dockings with ligands obtained from PDB ligand database to identify suitable potential inhibitors. The comparative genomic analysis revealed 606 non-homologous proteins and 233 essential non-homologous proteins of R. rickettsii. The metabolic pathway analysis predicted 120 proteins as putative drug targets, out of which 56 proteins were found to be associated with metabolic pathways unique to the bacteria and further subcellular localization analysis revealed that 9 proteins as potential drug targets which are secretion proteins, involved in peptidoglycan biosynthesis, folate biosynthesis and bacterial secretion system. As secretion proteins are more feasible as vaccine candidates, we have selected a most potential target i.e. tolC, an outer membrane efflux protein that belongs to type I secretion system and has major role in pathogen survival as well as MDR persistence. So for case study, we have modelled the three dimensional structure of tolC (tunnel protein). The model was further subjected to virtual screening and in-silico docking. The study identified three potential inhibitors having PDB Id 19V, 6Q8 and 39H. Further we have suggested that the above study would be most important while considering the selection of candidate targets and drug or vaccine designing against R. rickettsii.

Computational Approaches to Matrix Metalloprotease Drug Design

Matrix metalloproteinases (MMPs) are a family of zinc-containing enzymes required for homeostasis. These enzymes are an important class of drug targets as their over expression is associated with many disease states. Most of the inhibitors reported against this class of proteins have failed in clinical trials due to lack of specificity. In order to assist in drug design endeavors for MMP targets, a computationally tractable pathway is presented, comprising, (1) docking of small molecule inhibitors against the target MMPs, (2) derivation of quantum mechanical charges on the zinc ion in the active site and the amino acids coordinating with zinc including the inhibitor molecule, (3) molecular dynamics simulations on the docked ligand-MMP complexes, and (4) evaluation of binding affinities of the ligand-MMP complexes via an accurate scoring function for zinc containing metalloprotein-ligand complexes. The above pathway was applied to study the interaction of the inhibitor Batimastat with MMPs, which resulted in a high correlation between the predicted and experimental binding free energies, suggesting the potential applicability of the pathway.

PvaxDB: a comprehensive structural repository of Plasmodium vivax proteome

The severity of malaria caused by Plasmodium vivax worldwide and its resistance against the available general antimalarial drugs has created an urgent need for a comprehensive insight into its biology and biochemistry for developing some novel potential vaccines and therapeutics. P.vivax comprises 5392 proteins mostly predicted, out of which 4211 are soluble proteins and 2205 of these belong to blood and liver stages of malarial cycle. Presently available public resources report functional annotation (gene ontology) of only 28% (627 proteins) of the enzymatic soluble proteins and experimental structures are determined for only 42 proteins P. vivax proteome. In this milieu of severe paucity of structural and functional data, we have generated structures of 2205 soluble proteins, validated them thoroughly, identified their binding pockets (including active sites) and annotated their function increasing the coverage from the existing 28% to 100%. We have pooled all this information together and created a database christened as PvaxDB, which furnishes extensive sequence, structure, ligand binding site and functional information. We believe PvaxDB could be helpful in identifying novel protein drug targets, expediting development of new drugs to combat malaria. This is also the first attempt to create a reliable comprehensive computational structural repository of all the soluble proteins of P. vivax.

Database URL: http://www.scfbio-iitd.res.in/PvaxDB

Systematic Identification of Machine-Learning Models Aimed to Classify Critical Residues for Protein Function from Protein Structure

Protein structure and protein function should be related, yet the nature of this relationship remains unsolved. Mapping the critical residues for protein function with protein structure features represents an opportunity to explore this relationship, yet two important limitations have precluded a proper analysis of the structure-function relationship of proteins: (i) the lack of a formal definition of what critical residues are and (ii) the lack of a systematic evaluation of methods and protein structure features. To address this problem, here we introduce an index to quantify the protein-function criticality of a residue based on experimental data and a strategy aimed to optimize both, descriptors of protein structure (physicochemical and centrality descriptors) and machine learning algorithms, to minimize the error in the classification of critical residues. We observed that both physicochemical and centrality descriptors of residues effectively relate protein structure and protein function, and that physicochemical descriptors better describe critical residues. We also show that critical residues are better classified when residue criticality is considered as a binary attribute (i.e., residues are considered critical or not critical). Using this binary annotation for critical residues 8 models rendered accurate and non-overlapping classification of critical residues, confirming the multi-factorial character of the structure-function relationship of proteins.

Linear epitope prediction in HPV type 16 E7 antigen and their docked interaction with human TMEM 50A structural model

Human Papilloma Virus (HPV) HPV type 16 E7 antigen is a known target in cervical cancer. We report the predicted potential epitopes in the E7 antigen. We further describe the subsequent interaction of these linear epitope peptides with the human TMEM 50 A structural model using molecular docking. This data finds application in the development of components towards HPV associated disease prevention.

Rational design, synthesis and biological screening of triazine-triazolopyrimidine hybrids as multitarget anti-Alzheimer agents

In our endeavor towards the development of potent multitarget ligands for the treatment of Alzheimer's disease, a series of triazine-triazolopyrimidine hybrids were designed, synthesized and characterized by various spectral techniques. Docking and scoring techniques were used to design the inhibitors and to display their interaction with key residues of active site. Organic synthesis relied upon convergent synthetic routes were mono and di-substituted triazines were connected with triazolopyrimidine using piperazine as a linker. In total, seventeen compounds were synthesized in which the di-substituted triazine-triazolopyrimidine derivatives 9a-d showed better acetylcholinesterase (AChE) inhibitory activity than the corresponding tri-substituted triazine-triazolopyrimidine derivatives 10a-f. Out of the disubstituted triazine-triazolopyrimidine based compounds, 9a and 9b showed encouraging inhibitory activity on AChE with IC₅₀ values 0.065 and 0.092 μM, respectively. Interestingly, 9a and 9b also demonstrated good inhibition selectivity towards AChE over BuChE by ∼28 folds. Furthermore, kinetic analysis and molecular modeling studies showed that 9a and 9b target both catalytic active site as well as peripheral anionic site of AChE. In addition, these derivatives effectively modulated Aβ self-aggregation as investigated through CD spectroscopy, ThT fluorescence assay and electron microscopy. Besides, these compounds exhibited potential antioxidants (2.15 and 2.91 trolox equivalent by ORAC assay) and metal chelating properties. In silico ADMET profiling highlighted that, these novel triazine derivatives have appropriate drug like properties and possess very low toxic effects in the primarily pharmacokinetic study. Overall, the multitarget profile exerted by these novel triazine molecules qualified them as potential anti-Alzheimer drug candidates in AD therapy.

An Improved Protein Surface Extraction Method Using Rotating Cylinder Probe

For extraction of information on binding sites of a protein, the commonly known geometry-based methods utilize the corresponding PDB file to extract its surface as a first step. Finally, the surface is used to find the binding site atoms. As shown in this paper work, since none of the mostly used surface extraction methods can retrieve a sizeable percentage of the binding site atoms, the scope of development of a better method remains. In this direction, this paper presents a new benchmarking criteria based on utilization of binding site information to compare performance of these surface extraction methods. Also, a new surface extraction method is introduced based on the use of a rotating cylinder probe adapting from the work of Weisel et al. (Chem Cent J 1:7-23, 2007. doi: 10.1186/1752-153X-1-7 ). The result of the new method shows a significant improvement of performance in comparison to the existing methods.