scholarly journals Matched molecular pair-based data sets for computer-aided medicinal chemistry

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 36 ◽  
Author(s):  
Ye Hu ◽  
Antonio de la Vega de León ◽  
Bijun Zhang ◽  
Jürgen Bajorath
Keyword(s):  
Scientific Community ◽  
Medicinal Chemistry ◽  
Data Sets ◽  
Research Projects ◽  
High Confidence ◽  
Activity Data ◽  
Structural Modifications ◽  
Matched Molecular Pairs ◽  
Structure Activity ◽  
Activity Cliffs

Matched molecular pairs (MMPs) are widely used in medicinal chemistry to study changes in compound properties including biological activity, which are associated with well-defined structural modifications. Herein we describe up-to-date versions of three MMP-based data sets that have originated from in-house research projects. These data sets include activity cliffs, structure-activity relationship (SAR) transfer series, and second generation MMPs based upon retrosynthetic rules. The data sets have in common that they have been derived from compounds included in the latest release of the ChEMBL database for which high-confidence activity data are available. Thus, the activity data associated with MMP-based activity cliffs, SAR transfer series, and retrosynthetic MMPs cover the entire spectrum of current pharmaceutical targets. Our data sets are made freely available to the scientific community.

scholarly journals Matched molecular pair-based data sets for computer-aided medicinal chemistry

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 36 ◽  
Author(s):  
Ye Hu ◽  
Antonio de la Vega de León ◽  
Bijun Zhang ◽  
Jürgen Bajorath
Keyword(s):  
Scientific Community ◽  
Medicinal Chemistry ◽  
Data Sets ◽  
Research Projects ◽  
High Confidence ◽  
Activity Data ◽  
Structural Modifications ◽  
Matched Molecular Pairs ◽  
Structure Activity ◽  
Activity Cliffs

Matched molecular pairs (MMPs) are widely used in medicinal chemistry to study changes in compound properties including biological activity, which are associated with well-defined structural modifications. Herein we describe up-to-date versions of three MMP-based data sets that have originated from in-house research projects. These data sets include activity cliffs, structure-activity relationship (SAR) transfer series, and second generation MMPs based upon retrosynthetic rules. The data sets have in common that they have been derived from compounds included in the ChEMBL database (release 17) for which high-confidence activity data are available. Thus, the activity data associated with MMP-based activity cliffs, SAR transfer series, and retrosynthetic MMPs cover the entire spectrum of current pharmaceutical targets. Our data sets are made freely available to the scientific community.

Alzheimer's Disease: Related Targets, Synthesis of Available Drugs, Bioactive Compounds Under Development, and Promising Results Obtained from Multi-target Approaches

2020 ◽  
Vol 21 ◽  
Author(s):  
Natália F. F. Pirolla ◽  
Victor S. Batista ◽  
Flávia Pereira Dias Viegas ◽  
Vanessa Silva Gontijo ◽  
Caitlin R. McCarthy ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Bioactive Compounds ◽  
Medicinal Chemistry ◽  
Therapeutic Targets ◽  
Effective Drug ◽  
Research Projects ◽  
Drug Candidates ◽  
Structure Activity ◽  
Synthetic Routes

We describe herein the therapeutic targets involved in Alzheimer's disease as well as the available drugs and their synthetic routes. Bioactive compounds under development are also exploited to illustrate some recent research ad-vances on the medicinal chemistry of Alzheimer's disease, including structure-activity relationships for some targets. The importance of multi-target approaches, including some examples from our research projects, guides new perspectives in the search of more effective drug candidates. This review comprises the period between 2001 and early 2020.

scholarly journals Advancing the activity cliff concept, part II

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 75 ◽  
Author(s):  
Dagmar Stumpfe ◽  
Antonio de la Vega de León ◽  
Dilyana Dimova ◽  
Jürgen Bajorath
Keyword(s):  
Medicinal Chemistry ◽  
Current Understanding ◽  
Activity Relationship ◽  
Ligand Efficiency ◽  
Research Activity ◽  
High Interest ◽  
Structure Activity ◽  
Activity Cliff ◽  
Activity Cliffs

We present a follow up contribution to further complement a previous commentary on the activity cliff concept and recent advances in activity cliff research. Activity cliffs have originally been defined as pairs of structurally similar compounds that display a large difference in potency against a given target. For medicinal chemistry, activity cliffs are of high interest because structure-activity relationship (SAR) determinants can often be deduced from them. Herein, we present up-to-date results of systematic analyses of the ligand efficiency and lipophilic efficiency relationships between activity cliff-forming compounds, which further increase their attractiveness for the practice of medicinal chemistry. In addition, we summarize the results of a new analysis of coordinated activity cliffs and clusters they form. Taken together, these findings considerably add to our evaluation and current understanding of the activity cliff concept. The results should be viewed in light of the previous commentary article.

scholarly journals Advancing the activity cliff concept

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 199 ◽  
Author(s):  
Ye Hu ◽  
Dagmar Stumpfe ◽  
Jürgen Bajorath
Keyword(s):  
Chemical Modifications ◽  
Large Magnitude ◽  
Activity Data ◽  
General Audience ◽  
Structure Activity ◽  
Activity Cliff ◽  
Sar Analysis ◽  
Small Chemical ◽  
Detailed Picture ◽  
Activity Cliffs

The activity cliff concept has experienced increasing interest in medicinal chemistry and chemoinformatics. Activity cliffs have originally been defined as pairs of structurally similar compounds that are active against the same target but have a large difference in potency. Activity cliffs are relevant for structure-activity relationship (SAR) analysis and compound optimization because small chemical modifications can be deduced from cliffs that result in large-magnitude changes in potency. In addition to studying activity cliffs on the basis of individual compounds series, they can be systematically identified through mining of compound activity data. This commentary aims to provide a concise yet detailed picture of our current understanding of activity cliffs. It is also meant to introduce the further refined activity cliff concept to a general audience in drug development.

scholarly journals Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications

F1000Research ◽  
2012 ◽  
Vol 1 ◽  
pp. 11 ◽  
Author(s):  
Ye Hu ◽  
Jürgen Bajorath
Keyword(s):  
Medicinal Chemistry ◽  
Pharmaceutical Research ◽  
Software Tools ◽  
Data Sets ◽  
Research Projects ◽  
Link Type ◽  
Different Types ◽  
Basic Ideas

We have generated a number of compound data sets and programs for different types of applications in pharmaceutical research. These data sets and programs were originally designed for our research projects and are made publicly available. Without consulting original literature sources, it is difficult to understand specific features of data sets and software tools, basic ideas underlying their design, and applicability domains. Currently, 30 different entries are available for download from our website. In this data article, we provide an overview of the data and tools we make available and designate the areas of research for which they should be useful. For selected data sets and methods/programs, detailed descriptions are given. This article should help interested readers to select data and tools for specific computational investigations.

Truck Weight Enforcement Measures of Effectiveness: Development and Software Application

1998 ◽  
Vol 1643 (1) ◽  
pp. 152-160 ◽  
Author(s):  
F. R. Hanscom ◽  
M. W. Goelzer
Keyword(s):  
Software Tool ◽  
Field Evaluation ◽  
Seasonal Effects ◽  
Data Sets ◽  
Activity Data ◽  
Software Application ◽  
Enforcement Effort ◽  
Measures Of Effectiveness ◽  
Truck Weight ◽  
Enforcement Activity

A software tool was developed to determine what is accomplished as the result of truck weight enforcement efforts. Traditionally applied measures (e.g., numbers of trucks weighed and citations issued) have simply provided indications of enforcement effort. These previously applied measures failed to provide results in terms of real enforcement objectives, such as deterring overweight trucks and minimizing pavement wear and tear. Consequently the need exists to develop and validate truck weight enforcement measures of effectiveness (MOE). MOEs were developed via a series of analytical procedures. They were subsequently validated in a comprehensive four-state field evaluation. Matched (weigh-in-motion) (WIM) data sets, collected under controlled baseline and enforcement conditions, were analyzed to determine the sensitivity of candidate MOEs to actual enforcement activity. Data collection conditions were controlled in order to avoid contamination from hour-of-day, day-of-week, and seasonal effects. The following MOEs, were validated on the basis of their demonstrated sensitivity to truck weight enforcement objectives and the presence of enforcement activity: (1) severity of overweight violations, (2) proportion of overweight trucks, (3) average equivalent single-axle load (ESAL), (4) excess ESALs, and (5) bridge formula violations. These measures are sensitive to legal load-limit compliance objectives of truck weight enforcement procedures as well as the potential for overweight trucks to produce pavement deterioration. The software User Guide that statistically compares calculated MOEs between observed enforcement conditions is described in this paper. The User Guide also allows users to conduct an automated pavement design life analysis estimating, the theoretical pavement-life effect resulting from the observed enforcement activity.

Therapeutic Journey of 5-Pyrazolones as a Versatile Scaffold: A Review

2021 ◽  
Vol 21 ◽  
Author(s):  
Ravinder Sharma ◽  
Pooja A. Chawla ◽  
Viney Chawla ◽  
Rajeev Verma ◽  
Nandita Nawal ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Protease Inhibitor ◽  
Medicinal Chemistry ◽  
Membered Ring ◽  
Present Review ◽  
Biological Profile ◽  
3C Protease ◽  
Structure Activity ◽  
Derivatives Of ◽  
Heterocyclic Moiety

Abstract: A sizeable proportion of currently marketed drugs come from heterocycles. The heterocyclic moiety 5-pyrazolone is well known five membered ring containing nitrogen. Derivatives of this wonder nucleus have exhibited activities as diverse as antimicrobial, anti-inflammatory, analgesic, antidepressant, anticonvulsant, antidiabetic, antihyperlipidemic, antiviral, antitubercular, antioxidant, anticancer and antiviral including action against severe acute respiratory syndrome (SARS) or 3C protease inhibitor. A number of drugs based on this motif have already made it to the market. Standard texts and literature on medicinal chemistry cite different approaches for the synthesis of 5-pyrazolones. The present review provides an insight view to 5-pyrazolone synthesis, their biological profile and structure activity relationship studies.

scholarly journals Spatial and temporal tools for building a human cell atlas

2019 ◽  
Vol 30 (19) ◽  
pp. 2435-2438 ◽  
Author(s):  
Jonah Cool ◽  
Richard S. Conroy ◽  
Sean E. Hanlon ◽  
Shannon K. Hughes ◽  
Ananda L. Roy
Keyword(s):  
Scientific Community ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Experimental Conditions ◽  
Modeling Tools ◽  
Holistic View ◽  
Multiple Timescales ◽  
Single Cell Sequencing ◽  
Coordination And Collaboration

Improvements in the sensitivity, content, and throughput of microscopy, in the depth and throughput of single-cell sequencing approaches, and in computational and modeling tools for data integration have created a portfolio of methods for building spatiotemporal cell atlases. Challenges in this fast-moving field include optimizing experimental conditions to allow a holistic view of tissues, extending molecular analysis across multiple timescales, and developing new tools for 1) managing large data sets, 2) extracting patterns and correlation from these data, and 3) integrating and visualizing data and derived results in an informative way. The utility of these tools and atlases for the broader scientific community will be accelerated through a commitment to findable, accessible, interoperable, and reusable data and tool sharing principles that can be facilitated through coordination and collaboration between programs working in this space.

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