scholarly journals InterLig: a fast and accurate software for ligand-based virtual screening

2019 ◽  
Author(s):  
Claudio Mirabello ◽  
Björn Wallner
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Small Molecules ◽  
Open Source ◽  
Computational Methods ◽  
New Method ◽  
Scaffold Hopping ◽  
Protein Target ◽  
The Past ◽  
3D Methods

AbstractIn the past few years, drug discovery processes have been relying more and more on computational methods to sift out the most promising molecules before time and resources are spent to test them in experimental settings. Whenever the protein target of a given disease is not known, it becomes fundamental to have accurate methods for ligand-based Virtual Screening, which compare known active molecules against vast libraries of candidate compounds. Recently, 3D-based similarity methods have been developed that are capable of scaffold-hopping and to superimpose matching molecules. Here, we present InterLig, a new method for the comparison and superposition of small molecules based on 3D, topologically-independent alignments of atoms. We test InterLig on a standard benchmark and show that it compares favorably to the best currently available 3D methods.InterLig is open source and is available to everyone at: http://wallnerlab.org/interlig.

scholarly journals InterLig: improved ligand-based virtual screening using topologically independent structural alignments

2020 ◽  
Vol 36 (10) ◽  
pp. 3266-3267
Author(s):  
Claudio Mirabello ◽  
Björn Wallner
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Small Molecules ◽  
Supplementary Information ◽  
Scaffold Hopping ◽  
Supplementary Data ◽  
Protein Target ◽  
The Past ◽  
3D Methods ◽  
Structural Alignments

Abstract Motivation In the past few years, drug discovery processes have been relying more and more on computational methods to sift out the most promising molecules before time and resources are spent to test them in experimental settings. Whenever the protein target of a given disease is not known, it becomes fundamental to have accurate methods for ligand-based virtual screening, which compares known active molecules against vast libraries of candidate compounds. Recently, 3D-based similarity methods have been developed that are capable of scaffold hopping and to superimpose matching molecules. Results Here, we present InterLig, a new method for the comparison and superposition of small molecules using topologically independent alignments of atoms. We test InterLig on a standard benchmark and show that it compares favorably to the best currently available 3D methods. Availability and implementation The program is available from http://wallnerlab.org/InterLig. Supplementary information Supplementary data are available at Bioinformatics online.

Computer-Assisted Drug Virtual Screening Based on the Natural Product Databases

2019 ◽  
Vol 20 (4) ◽  
pp. 293-301 ◽  
Author(s):  
Baoyu Yang ◽  
Jing Mao ◽  
Bing Gao ◽  
Xiuli Lu
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Small Molecules ◽  
Natural Product ◽  
Drug Screening ◽  
Biologically Active ◽  
Computer Assisted ◽  
Toxicity Prediction ◽  
Protein Target

Background:Computer-assisted drug virtual screening models the process of drug screening through computer simulation technology, by docking small molecules in some of the databases to a certain protein target. There are many kinds of small molecules databases available for drug screening, including natural product databases.Methods:Plants have been used as a source of medication for millennia. About 80% of drugs were either natural products or related analogues by 1990, and many natural products are biologically active and have favorable absorption, distribution, metabolization, excretion, and toxicology.Results:In this paper, we review the natural product databases’ contributions to drug discovery based on virtual screening, focusing particularly on the introductions of plant natural products, microorganism natural product, Traditional Chinese medicine databases, as well as natural product toxicity prediction databases.Conclusion:We highlight the applications of these databases in many fields of virtual screening, and attempt to forecast the importance of the natural product database in next-generation drug discovery.

Virtual Screening

2011 ◽  
pp. 28-60 ◽  
Author(s):  
Khaled H. Barakat ◽  
Jonathan Y. Mane ◽  
Jack A. Tuszynski
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Cell Signaling ◽  
Success Rate ◽  
Signaling Pathways ◽  
Computational Methods ◽  
Future Directions ◽  
Biologically Relevant ◽  
The Many ◽  
Cell Signaling Pathways

Virtual screening, or VS, is emerging as a valuable tool in discovering new candidate inhibitors for many biologically relevant targets including the many chemotherapeutic targets that play key roles in cell signaling pathways. However, despite the great advances made in the field thus far, VS is still in constant development with a relatively low success rate that needs to be improved by parallel experimental validation methods. This chapter reviews the recent advances in VS, focusing on the range and type of computational methods and their successful applications in drug discovery. The chapter also discusses both the advantages and limitations of the various techniques used in VS and outlines a number of future directions in which the field may progress.

Targeted protein degradation and regulation with molecular glue: past and recent discoveries

2021 ◽  
Vol 28 ◽  
Author(s):  
Yizheng Fang ◽  
Qiaojun He ◽  
Ji Cao
Keyword(s):  
Drug Discovery ◽  
Protein Degradation ◽  
Small Molecules ◽  
Mechanisms Of Action ◽  
Clinical Settings ◽  
Protein Protein Interaction ◽  
Protein Inhibition ◽  
The Past ◽  
New Methods ◽  
Disease Associated Genes

: The evolution in research and clinical settings of targeted therapies has been inspired by the progress of cancer chemotherapy to use small molecules and monoclonal antibodies for targeting specific disease-associated genes and proteins for noninfectious chronic diseases. In addition to conventional protein inhibition and activation strategies as drug discovery modalities, new methods of targeted protein degradation and regulation using molecular glues have become an attractive approach for drug discovery. Mechanistically, molecular glues trigger interactions between the proteins that originally did not interact by forming ternary complexes as protein-protein interaction (PPI) modulators. New molecular glues and their mechanisms of action have been actively investigated in the past decades. An immunomodulatory imide drug, thalidomide, and its derivatives have been used in the clinic and are a class of molecular glue that induces degradation of several neo-substrates. In this review, we summarize the development of molecular glues and share our opinions on the identification of novel molecular glues in an attempt to promote the concept and inspire further investigations.

scholarly journals SMALL MOLECULES SOLVING BIG PROBLEMS: PRESENT AND FUTURE OF DRUG DISCOVERY

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Anna Lucia Fallacara ◽  
Iuni Margaret Laura Tris ◽  
Amalia Belfiore ◽  
Maurizio Botta
Keyword(s):  
Drug Discovery ◽  
Drug Development ◽  
Small Molecules ◽  
Rational Design ◽  
Development Process ◽  
New Drugs ◽  
Drug Development Process ◽  
Development Models ◽  
The Past ◽  
The Cost

The Drug development process has undergone a great change over the years. The way, from haphazard discovery of new natural products with a potent biological activity to a rational design of small molecule effective against a selected target, has been long and sprinkled with difficulties. The oldest drug development models are widely perceived as opaque and inefficient, with the cost of research and development continuing to rise even if the production of new drugs remains constant. The present paper, will give an overview of the principles, approaches, processes, and status of drug discovery today with an eye towards the past and the future.

scholarly journals Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Haiying Lu ◽  
Qiaodan Zhou ◽  
Jun He ◽  
Zhongliang Jiang ◽  
Cheng Peng ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Small Molecules ◽  
Protein Interactions ◽  
Clinical Studies ◽  
New Drugs ◽  
Protein Protein Interactions ◽  
The Past ◽  
Recent Advances ◽  
Novel Drugs

Abstract Protein–protein interactions (PPIs) have pivotal roles in life processes. The studies showed that aberrant PPIs are associated with various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Therefore, targeting PPIs is a direction in treating diseases and an essential strategy for the development of new drugs. In the past few decades, the modulation of PPIs has been recognized as one of the most challenging drug discovery tasks. In recent years, some PPIs modulators have entered clinical studies, some of which been approved for marketing, indicating that the modulators targeting PPIs have broad prospects. Here, we summarize the recent advances in PPIs modulators, including small molecules, peptides, and antibodies, hoping to provide some guidance to the design of novel drugs targeting PPIs in the future.

scholarly journals Prospective virtual screening with Ultrafast Shape Recognition: the identification of novel inhibitors of arylamine N -acetyltransferases

2009 ◽  
Vol 7 (43) ◽  
pp. 335-342 ◽  
Author(s):  
Pedro J. Ballester ◽  
Isaac Westwood ◽  
Nicola Laurieri ◽  
Edith Sim ◽  
W. Graham Richards
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Small Molecules ◽  
Shape Recognition ◽  
Molecular Targets ◽  
Efficient Manner ◽  
Hit Rate ◽  
Shape Complementarity ◽  
Outstanding Result ◽  
Novel Structures

There is currently a shortage of chemical molecules that can be used as bioactive probes to study molecular targets and potentially as starting points for drug discovery. One inexpensive way to address this problem is to use computational methods to screen a comprehensive database of small molecules to discover novel structures that could lead to alternative and better bioactive probes. Despite that pleasing logic the results have been somewhat mixed. Here we describe a virtual screening technique based on ligand–receptor shape complementarity, Ultrafast Shape Recognition (USR). USR is specifically applied to identify novel inhibitors of arylamine N -acetyltransferases by computationally screening almost 700 million molecular conformers in a time- and resource-efficient manner. A small number of the predicted active compounds were purchased and tested obtaining a confirmed hit rate of 40 per cent which is an outstanding result for a prospective virtual screening.

scholarly journals Accelerating Drug Discovery and Repurposing by Combining Transcriptional Signature Connectivity with Docking

2020 ◽  
Author(s):  
Alexander W. Thorman ◽  
James Reigle ◽  
Somchai Chutipongtanate ◽  
Behrouz Shamsaei ◽  
Marcin Pilarczyk ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Small Molecules ◽  
False Positive ◽  
Target Gene ◽  
Treatment Options ◽  
Small Subset ◽  
Chemical Similarity ◽  
Docking Simulations ◽  
Transcriptional Signature

AbstractThe development of targeted treatment options for precision medicine is hampered by a slow and costly process of drug screening. While small molecule docking simulations are often applied in conjunction with cheminformatic methods to reduce the number of candidate molecules to be tested experimentally, the current approaches suffer from high false positive rates and are computationally expensive. Here, we present a novel in silico approach for drug discovery and repurposing, dubbed connectivity enhanced Structure Activity Relationship (ceSAR) that improves on current methods by combining docking and virtual screening approaches with pharmacogenomics and transcriptional signature connectivity analysis. ceSAR builds on the landmark LINCS library of transcriptional signatures of over 20,000 drug-like molecules and ~5,000 gene knock-downs (KDs) to connect small molecules and their potential targets. For a set of candidate molecules and specific target gene, candidate molecules are first ranked by chemical similarity to their ‘concordant’ LINCS analogs that share signature similarity with a knock-down of the target gene. An efficient method for chemical similarity search, optimized for sparse binary fingerprints of chemical moieties, is used to enable fast searches for large libraries of small molecules. A small subset of candidate compounds identified in the first step is then re-scored by combining signature connectivity with docking simulations. On a set of 20 DUD-E benchmark targets with LINCS KDs, the consensus approach reduces significantly false positive rates, improving the median precision 3-fold over docking methods at the extreme library reduction. We conclude that signature connectivity and docking provide complementary signals, offering an avenue to improve the accuracy of virtual screening while reducing run times by multiple orders of magnitude.

Forging New Scaffolds from Old: Combining Scaffold Hopping and Hierarchical Virtual Screening for Identifying Novel Bcl-2 Inhibitors

2019 ◽  
Vol 19 (13) ◽  
pp. 1162-1172 ◽  
Author(s):  
Vishnupriya Kanakaveti ◽  
Sakthivel Rathinasamy ◽  
Suresh K. Rayala ◽  
Michael Gromiha
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Physicochemical Characterization ◽  
B Cell Lymphoma ◽  
Rational Approach ◽  
Screening Methods ◽  
Scaffold Hopping ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Lead Compounds

Background: Though virtual screening methods have proven to be potent in various instances, the technique is practically incomplete to quench the need of drug discovery process. Thus, the quest for novel designing approaches and chemotypes for improved efficacy of lead compounds has been intensified and logistic approaches such as scaffold hopping and hierarchical virtual screening methods were evolved. Till now, in all the previous attempts these two approaches were applied separately. Objective: In the current work, we made a novel attempt in terms of blending scaffold hopping and hierarchical virtual screening. The prime objective is to assess the hybrid method for its efficacy in identifying active lead molecules for emerging PPI target Bcl-2 (B-cell Lymphoma 2). Method: We designed novel scaffolds from the reported cores and screened a set of 8270 compounds using both scaffold hopping and hierarchical virtual screening for Bcl-2 protein. Also, we enumerated the libraries using clustering, PAINS filtering, physicochemical characterization and SAR matching. Results: We generated a focused library of compounds towards Bcl-2 interface, screened the 8270 compounds and identified top hits for seven families upon fine filtering with PAINS algorithm, features, SAR mapping, synthetic accessibility and similarity search. Our approach retrieved a set of 50 lead compounds. Conclusions: Finding rational approach meeting the needs of drug discovery process for PPI targets is the need of the hour which can be fulfilled by an extended scaffold hopping approach resulting in focused PPI targeting by providing novel leads with better potency.

Sign in / Sign up

Export Citation Format

Share Document