Molecular Recognition Of Ligands Research Articles

Pharmacophore Model for SARS-CoV-2 3CLpro Small-Molecule Inhibitors and in Vitro Experimental Validation of Computationally Screened Inhibitors.

Among the biomedical efforts in response to the current coronavirus (COVID-19) pandemic, pharmacological strategies to reduce viral load in patients with severe forms of the disease are being studied intensively. One of the main drug target proteins proposed so far is the SARS-CoV-2 viral protease 3CLpro (also called Mpro), an essential component for viral replication. Ongoing ligand- and receptor-based computational screening efforts would be facilitated by an improved understanding of the electrostatic, hydrophobic, and steric features that characterize small-molecule inhibitors binding stably to 3CLpro and by an extended collection of known binders. Here, we present combined virtual screening, molecular dynamics (MD) simulation, machine learning, and in vitro experimental validation analyses, which have led to the identification of small-molecule inhibitors of 3CLpro with micromolar activity and to a pharmacophore model that describes functional chemical groups associated with the molecular recognition of ligands by the 3CLpro binding pocket. Experimentally validated inhibitors using a ligand activity assay include natural compounds with the available prior knowledge on safety and bioavailability properties, such as the natural compound rottlerin (IC50 = 37 μM) and synthetic compounds previously not characterized (e.g., compound CID 46897844, IC50 = 31 μM). In combination with the developed pharmacophore model, these and other confirmed 3CLpro inhibitors may provide a basis for further similarity-based screening in independent compound databases and structural design optimization efforts to identify 3CLpro ligands with improved potency and selectivity. Overall, this study suggests that the integration of virtual screening, MD simulations, and machine learning can facilitate 3CLpro-targeted small-molecule screening investigations. Different receptor-, ligand-, and machine learning-based screening strategies provided complementary information, helping to increase the number and diversity of the identified active compounds. Finally, the resulting pharmacophore model and experimentally validated small-molecule inhibitors for 3CLpro provide resources to support follow-up computational screening efforts for this drug target.

Receptor crosstalk improves concentration sensing of multiple ligands.

Cells need to reliably sense external ligand concentrations to achieve various biological functions such as chemotaxis or signaling. The molecular recognition of ligands by surface receptors is degenerate in many systems, leading to crosstalk between ligand-receptor pairs. Crosstalk is often thought of as a deviation from optimal specific recognition, as the binding of noncognate ligands can interfere with the detection of the receptor's cognate ligand, possibly leading to a false triggering of a downstream signaling pathway. Here we quantify the optimal precision of sensing the concentrations of multiple ligands by a collection of promiscuous receptors. We demonstrate that crosstalk can improve precision in concentration sensing and discrimination tasks. To achieve superior precision, the additional information about ligand concentrations contained in short binding events of the noncognate ligand should be exploited. We present a proofreading scheme to realize an approximate estimation of multiple ligand concentrations that reaches a precision close to the derived optimal bounds. Our results help rationalize the observed ubiquity of receptor crosstalk in molecular sensing.

In vitro and in silico evaluation of fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor

The fucosterol has been reported numerous biological activities. In this study, the activity in vitro of the fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor was evaluated. The structural identification was obtained by nuclear magnetic resonance (NMR) spectroscopy and based on experimental data, we combined docking and molecular dynamics simulations coupled to the molecular-mechanics-generalized-born-surface-area approach to evaluating the structural and energetic basis for the molecular recognition of fucosterol and neostigmine at the binding site of acetylcholinesterase (AChE). In addition, the Lineweaver–Burk plot showed the nature of a non-competitive inhibition. The maximum velocity (Vmax) and the constant of Michaelis–Menten (Km) estimated for fucosterol (0.006 µM) were 0.015 1/Vo (ΔA/h and 6.399 1/[ACh] mM−1, respectively. While, for neostigmine (0.14 µM), the Vmax was 0.022 1/Vo (ΔA/h) and Km of 6.726 1/[ACh] mM−1, these results showed a more effective inhibition by fucosterol respect to neostigmine. Structural analysis revealed that neostigmine reaches the AChE binding site reported elsewhere, whereas fucosterol can act as a no-competitive and competitive acetylcholinesterase inhibitor, in agree with kinetic enzymatic experiments. Binding free energy calculations revealed that fucosterol reaches the acetylcholinesterase binding site with higher affinity than neostigmine, which is according to experimental results. Whereas the per-residue decomposition free energy analysis let us identify crucial residues involved in the molecular recognition of ligands by AChE. Results corroborate the ability of theoretical methods to provide crucial information at the atomic level about energetic and structural differences in the binding interaction and affinity from fucosterol with AChE.Communicated by Ramaswamy H. Sarma

Recent Progress in the Molecular Recognition and Therapeutic Importance of Interleukin-1 Receptor-Associated Kinase 4.

Toll-like receptors (TLRs) are the most upstream pattern recognition receptors in the cell, which detect pathogen associated molecular patterns and initiate signal transduction, culminating in the transcription of pro-inflammatory cytokines and antiviral interferon. Interleukin-1 receptor-associated kinase 4 (IRAK4) is a key mediator in TLR (except for TLR3) and interleukin-1 receptor signaling pathways. The loss of kinase function of IRAK4 is associated with increased susceptibility to various pathogens, while its over-activation causes autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, and cancer. The therapeutic importance of this master kinase has been advocated by a number of recent preclinical studies, where potent inhibitors have been administered to improve various TLR-mediated pathologies. Increasing studies of X-ray crystallographic structures with bound inhibitors have improved our knowledge on the molecular recognition of ligands by IRAK4, which will be crucial for the development of new inhibitors with improved potencies. In this review, we briefly discuss the structural aspect of ligand recognition by IRAK4 and highlight its therapeutic importance in the context of TLR-associated unmet medical needs.

Do we see what we should see? Describing non-covalent interactions in protein structures including precision.

The power of X-ray crystal structure analysis as a technique is to 'see where the atoms are'. The results are extensively used by a wide variety of research communities. However, this 'seeing where the atoms are' can give a false sense of security unless the precision of the placement of the atoms has been taken into account. Indeed, the presentation of bond distances and angles to a false precision (i.e. to too many decimal places) is commonplace. This article has three themes. Firstly, a basis for a proper representation of protein crystal structure results is detailed and demonstrated with respect to analyses of Protein Data Bank entries. The basis for establishing the precision of placement of each atom in a protein crystal structure is non-trivial. Secondly, a knowledge base harnessing such a descriptor of precision is presented. It is applied here to the case of salt bridges, i.e. ion pairs, in protein structures; this is the most fundamental place to start with such structure-precision representations since salt bridges are one of the tenets of protein structure stability. Ion pairs also play a central role in protein oligomerization, molecular recognition of ligands and substrates, allosteric regulation, domain motion and α-helix capping. A new knowledge base, SBPS (Salt Bridges in Protein Structures), takes these structural precisions into account and is the first of its kind. The third theme of the article is to indicate natural extensions of the need for such a description of precision, such as those involving metalloproteins and the determination of the protonation states of ionizable amino acids. Overall, it is also noted that this work and these examples are also relevant to protein three-dimensional structure molecular graphics software.

Molecular Recognition in Biomolecules Studied by Statistical-Mechanical Integral-Equation Theory of Liquids

Recent progress in the theory of molecular recognition in biomolecules is reviewed, which has been made based on the statistical mechanics of liquids or the RISM/3D-RISM theory during the last five years in the authors' group. The method requires just the structure of protein and the potential energy parameters for the biomolecules and solutions as inputs. The calculation is carried out in two steps. The first step is to obtain the pair correlation functions for solutions consisting of water and ligands based on the RISM theory. Then, given the pair correlation functions prepared in the first step, we calculate the 3D-distribution functions of water and ligands around and inside protein based on the 3D-RISM theory. The molecular recognition of a ligand by the protein is realized by the 3D-distribution functions: if one finds some conspicuous peaks in the distribution of a ligand inside protein, then the ligand is regarded as "recognized" by the protein. Some biochemical processes are investigated, which are intimately related to the molecular recognition of small ligands including water, noble gases, and ions by a protein.

Molecular Recognition of Ligands in Dipeptidyl Peptidase IV

The serine protease dipeptidyl peptidase IV (DPP-IV) is a clinically validated target for the treatment of type II diabetes and has received considerable interest from the pharmaceutical industry over the last years. Concomitant with a large variety of published small molecule DPP-IV inhibitors almost twenty co-crystal structures have been released to the public as of May 2006. In this review, we discuss the structural characteristics of the DPP-IV binding site and use the available X-ray information together with published structure-activity relationship data to identify the molecular interactions that are most important for tight enzyme-inhibitor binding. Optimized interactions with the two key recognition motifs, i.e. the lipophilic S1 pocket and the negatively charged Glu 205/206 pair, result in large gains in binding free energy, which can be further improved by additional favorable contacts to side chains that flank the active site. First examples show that the lessons learned from the X-ray structures can be successfully incorporated into the design of novel DPP-IV inhibitors.

A novel, modification-dependent ATP-binding aptamer selected from an RNA library incorporating a cationic functionality.

An analogue of uridine triphosphate containing a cationic functional group was incorporated into a degenerate RNA library by enzymatic polymerization. In vitro selection experiments using this library yielded a novel receptor that binds ATP under physiological pH and salt conditions in a manner completely dependent on the presence of the cationic functionality. The consensus sequence and a secondary structure model for the ATP binding site were obtained by the analysis of functional sequences selected from a partially randomized pool based on the minimal parental sequence. Mutational studies of this receptor indicated that several of the modified uridines are critical for ATP binding. Analysis of the binding of ATP analogues revealed that the modified RNA receptor makes numerous contacts with ATP, including interactions with the triphosphate group. In contrast, the aptamer repeatedly isolated from natural RNA libraries does not interact with the triphosphate group of ATP. The incorporation of a cationic amine into nucleic acids clearly allows novel interactions to occur during the molecular recognition of ligands, which carries interesting implications for the RNA world hypothesis. In addition, new materials generated from such functionalized nucleic acids could be useful tools in research and diagnostics.