Needle in a haystack: microdissecting the proteome of a tissue

Summary. Laser-assisted microdissection is a recent technology that enables cells to be harvested from tissue sections. Proteins can be extracted from the dissected cells for molecular analysis. This enables the analysis of proteins in specific cell types in an in vivo system. Although quantities of protein obtained from the dissected material can be small, it is possible to use established methods such as Western Blotting and 2D-PAGE, as well as newer technologies such as SELDI-MS, to analyse the proteins. This review describes the applications and technical considerations for using laser-assisted dissected cells in proteomics research.     

Needle in a haystack: Antibacterial activity-guided fractionation of a potato wound tissue extract

Erwinia carotovora is a major cause of potato tuber infection, which results in disastrous failures of this important food crop. There is currently no effective antibiotic treatment against E. carotovora. Recently we reported antibacterial assays of wound tissue extracts from four potato cultivars that exhibit a gradient of russeting character, finding the highest potency against this pathogen for a polar extract from the tissue formed immediately after wounding by an Atlantic cultivar. In the current investigation, antibacterial activity-guided fractions of this extract were analyzed by liquid chromatography-mass spectrometry (LC-MS) utilizing a quadrupole-time-of-flight (QTOF) mass spectrometer. The most active chemical compounds identified against E. carotovora were: 6-O-nonyl glucitol, Lyratol C, n-[2-(4-Hydroxyphenyl)] ethyldecanamide, α-chaconine and α-solanine. Interactions among the three compounds, ferulic acid, feruloyl putrescine, and α-chaconine, representing metabolite classes upregulated during initial stages of wound healing, were also evaluated, offering possible explanations for the burst in antibacterial activity after tuber wounding and a chemical rationale for the temporal resistance phenomenon.     

Needle from a haystack. Optimal signaling by a nonlinear synapse

Commonly, a neuron must separate a small, rare event carried by one of its inputs from the noise carried by many others. In this issue of Neuron, demonstrate that to solve this problem, the rod bipolar neuron in mouse retina selectively amplifies a rod's single-photon signal only when it is larger than average. This nonlinearity rejects nearly three-fourths of the single-photon signals. Yet, by also rejecting noise, it provides nearly optimal filtering near absolute visual threshold.     

Protein targets for structure-based anti-Mycobacterium tuberculosis drug discovery

Mycobacterium tuberculosis, which belongs to the genus Mycobacterium, is the pathogenic agent for most tuberculosis (TB). As TB remains one of the most rampant infectious diseases, causing morbidity and death with emergence of multi-drug-resistant and extensively-drug-resistant forms, it is urgent to identify new drugs with novel targets to ensure future therapeutic success. In this regards, the structural genomics of M. tuberculosis provides important information to identify potential targets, perform biochemical assays, determine crystal structures in complex with potential inhibitor(s), reveal the key sites/residues for biological activity, and thus validate drug targets and discover novel drugs. In this review, we will discuss the recent progress on novel targets for structure-based anti-M. tuberculosis drug discovery.     

The genesis of high-throughput structure-based drug discovery using protein crystallography

Over the past 12 years, drugs have been developed using structure-based drug design relying upon traditional crystallographic methods. Established successes, such as the drugs designed against HIV-1 protease and neuraminidase, demonstrate the utility of a structure-based approach in the drug-discovery process. However, the approach has historically lacked throughput and reliability capabilities; these bottlenecks are being overcome by breakthroughs in high-throughput structural biology. Recent technological innovations such as submicroliter high-throughput crystallization, high-performance synchrotron beamlines and rapid binding-site analysis of de novo targets using virtual ligand screening and small molecule co-crystallization have resulted in a significant advance in structure-based drug discovery.     

In silico structure-based discovery of a SARS-CoV-2 main protease inhibitor

The Coronavirus Disease 2019 (COVID-19) pandemic caused by the novel lineage B betacoroanvirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in significant mortality, morbidity, and socioeconomic disruptions worldwide. Effective antivirals are urgently needed for COVID-19. The main protease (M^pro) of SARS-CoV-2 is an attractive antiviral target because of its essential role in the cleavage of the viral polypeptide. In this study, we performed an in silico structure-based screening of a large chemical library to identify potential SARS-CoV-2 M^pro inhibitors. Among 8,820 compounds in the library, our screening identified trichostatin A, a histone deacetylase inhibitor and an antifungal compound, as an inhibitor of SARS-CoV-2 M^pro activity and replication. The half maximal effective concentration of trichostatin A against SARS-CoV-2 replication was 1.5 to 2.7µM, which was markedly below its 50% effective cytotoxic concentration (75.7µM) and peak serum concentration (132µM). Further drug compound optimization to develop more stable analogues with longer half-lives should be performed. This structure-based drug discovery platform should facilitate the identification of additional enzyme inhibitors of SARS-CoV-2.     

Molecular dynamic simulations and structure-based pharmacophore development for farnesyltransferase inhibitors discovery

Farnesyltransferase is one of the enzyme targets for the development of drugs for diseases, including cancer, malaria, progeria, etc. In the present study, the structure-based pharmacophore models have been developed from five complex structures (1LD7, 1NI1, 2IEJ, 2ZIR and 2ZIS) obtained from the protein data bank. Initially, molecular dynamic (MD) simulations were performed for the complexes for 10?ns using AMBER 12 software. The conformers of the complexes (75) generated from the equilibrated protein were undergone protein–ligand interaction fingerprint (PLIF) analysis. The results showed that some important residues, such as LeuB96, TrpB102, TrpB106, ArgB202, TyrB300, AspB359 and TyrB361, are predominantly present in most of the complexes for interactions. These residues form side chain acceptor and surface (hydrophobic or π–π) kind of interactions with the ligands present in the complexes. The structure-based pharmacophore models were generated from the fingerprint bits obtained from PLIF analysis. The pharmacophore models have 3–4 pharmacophore contours consist of acceptor and metal ligation (Acc & ML), hydrophobic (HydA) and extended acceptor (Acc2) features with the radius ranging between 1–3?Å for Acc & ML and 1–2?Å for HydA. The excluded volumes of the pharmacophore contours radius are between 1–2?Å. Further, the distance between the interacting groups, root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radial distribution function (RDF) analysis were performed for the MD-simulated proteins using PTRAJ module. The generated pharmacophore models were used to screen a set of natural compounds and database compounds to select significant HITs. We conclude that the developed pharmacophore model can be a significant model for the identification of HITs as FTase inhibitors.     

Fragment-based hit discovery and structure-based optimization of aminotriazoloquinazolines as novel Hsp90 inhibitors

In the last decade the heat shock protein 90 (Hsp90) has emerged as a major therapeutic target and many efforts have been dedicated to the discovery of Hsp90 inhibitors as new potent anticancer agents. Here we report the identification of a novel class of Hsp90 inhibitors by means of a biophysical FAXS-NMR based screening of a library of fragments. The use of X-ray structure information combined with modeling studies enabled the fragment evolution of the initial triazoloquinazoline hit to a class of compounds with nanomolar potency and drug-like properties suited for further lead optimization.     

Inhibitors of the tyrosine kinase EphB4. Part 2: structure-based discovery and optimisation of 3,5-bis substituted anilinopyrimidines

Crystallographic studies of a range of 3-substituted anilinopyrimidine inhibitors of EphB4 have highlighted two alternative C-2 aniline conformations and this discovery has been exploited in the design of a highly potent series of 3,5-disubstituted anilinopyrimidines. The observed range of cellular activities has been rationalised on the basis of physicochemical and structural characteristics.     

Solvent interaction analysis as a proteomic approach to structure-based biomarker discovery and clinical diagnostics

Proteins have several measurable features in biological fluids that may change under pathological conditions. The current disease biomarker discovery is mostly based on protein concentration in the sample as the measurable feature. Changes in protein structures, such as post-translational modifications and in protein–partner interactions are known to accompany pathological processes. Changes in glycosylation profiles are well-established for many plasma proteins in various types of cancer and other diseases. The solvent interaction analysis method is based on protein partitioning in aqueous two-phase systems and is highly sensitive to changes in protein structure and protein–protein- and protein–partner interactions while independent of the protein concentration in the biological sample. It provides quantitative index: partition coefficient representing changes in protein structure and interactions with partners. The fundamentals of the method are presented with multiple examples of applications of the method to discover and monitor structural protein biomarkers as disease-specific diagnostic indicators.     

Recently integrated human Alu repeats: finding needles in the haystack

Alu elements undergo amplification through retroposition and integration into new locations throughout primate genomes. Over 500,000 Alu elements reside in the human genome, making the identification of newly inserted Alu repeats the genomic equivalent of finding needles in the haystack. Here, we present two complementary methods for rapid detection of newly integrated Alu elements. In the first approach we employ computational biology to mine the human genomic DNA sequence databases in order to identify recently integrated Alu elements. The second method is based on an anchor-PCR technique which we term Allele-Specific Alu PCR (ASAP). In this approach, Alu elements are selectively amplified from anchored DNA generating a display or 'fingerprint' of recently integrated Alu elements. Alu insertion polymorphisms are then detected by comparison of the DNA fingerprints generated from different samples. Here, we explore the utility of these methods by applying them to the identification of members of the smallest previously identified subfamily of Alu repeats in the human genome termed Ya8. This subfamily of Alu repeats is composed of about 50 elements within the human genome. Approximately 50% of the Ya8 Alu family members have inserted in the human genome so recently that they are polymorphic, making them useful markers for the study of human evolution. This revised version was published online in July 2006 with corrections to the Cover Date.