|
Registro Completo |
|
Biblioteca(s): |
Embrapa Agricultura Digital. |
|
Data corrente: |
22/12/2015 |
|
Data da última atualização: |
21/01/2020 |
|
Tipo da produção científica: |
Resumo em Anais de Congresso |
|
Autoria: |
BORRO, L. C.; NESHICH, G. |
|
Afiliação: |
IB/Unicamp; GORAN NESHICH, CNPTIA. |
|
Título: |
Ranking optimization in virtual screening using physical-chemical and structural descriptors of the nano-environment for protein-ligand interactions. |
|
Ano de publicação: |
2015 |
|
Fonte/Imprenta: |
In: SÃO PAULO SCHOOL OF ADVANCED SCIENCES ON NEGLECTED DISEASES DRUG DISCOVERY - FOCUS ON KINETOPLASTIDS, 2015, Campinas. Book of abstracts. [Campinas]: CNPEM, [2015]. |
|
Páginas: |
p. 115. |
|
Idioma: |
Inglês |
|
Notas: |
SPSAS-ND3. |
|
Conteúdo: |
During the last two decades, virtual screening (VS) has become an important tool for rational design of drugs and agrochemicals. However, despite of many successful cases VS approaches still have some limitations, especially regarding the ranking of potential ligands according to their binding affinity. In order to create models that can improve the ranking phase in VS campaigns, we propose an in silico approach to identify features that are important and essential to the molecular recognition process. |
|
Palavras-Chave: |
Bioinformática; In silico approach; Virtual screening. |
|
Thesaurus Nal: |
Bioinformatics. |
|
Categoria do assunto: |
A Sistemas de Cultivo |
|
Marc: |
LEADER 01266nam a2200193 a 4500
001 2032239
005 2020-01-21
008 2015 bl uuuu u00u1 u #d
100 1 $aBORRO, L. C.
245 $aRanking optimization in virtual screening using physical-chemical and structural descriptors of the nano-environment for protein-ligand interactions.$h[electronic resource]
260 $aIn: SÃO PAULO SCHOOL OF ADVANCED SCIENCES ON NEGLECTED DISEASES DRUG DISCOVERY - FOCUS ON KINETOPLASTIDS, 2015, Campinas. Book of abstracts. [Campinas]: CNPEM, [2015].$c2015
300 $ap. 115.
500 $aSPSAS-ND3.
520 $aDuring the last two decades, virtual screening (VS) has become an important tool for rational design of drugs and agrochemicals. However, despite of many successful cases VS approaches still have some limitations, especially regarding the ranking of potential ligands according to their binding affinity. In order to create models that can improve the ranking phase in VS campaigns, we propose an in silico approach to identify features that are important and essential to the molecular recognition process.
650 $aBioinformatics
653 $aBioinformática
653 $aIn silico approach
653 $aVirtual screening
700 1 $aNESHICH, G.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
